Transaction
ID: f90d504660...a1ce
Inputs (116)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00101 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#100
5a64cfd93498...2b4b Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#101
e4d030893a87...d2db Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#102
56b36add07a5...85c2 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#103
8f54630c1647...642c Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#104
1268d57dc977...d527 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#105
13bcf1e4b06d...8a0a Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#106
04c0cabab7cd...e972 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#107
d03b7098b95b...c244 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#108
8e1e66480b95...34e7 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#109
a1e53c8c6074...b10c Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#110
9326eca0c64d...2d3e Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#111
167e232ea271...6b07 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#112
847036b7aea2...bb13 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#113
71b46f1ea4b6...f022 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#114
57807b974f6d...39c4 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#115
212c60c273c1...8aef Spent
Address:
Output transaction:
Settlement height:
Value:
0.042 ERG
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.22901 ERG
Tokens:
345,000
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.04 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 361,615
Total coins transferred: 0.27101 ERG
Fees: 0.002 ERG
Fees per byte: 0.00000039 ERG
Raw Transaction Data
{
"id": "f90d50466096e742df5dc70a0b0ab6f0912a4e1c47645b3d36ca854f4dc5a1ce",
"blockId": "0475f45f2367fdd15a34302bd7a79ea6927ab2084bdb0e9c51617d3675a66cdc",
"inclusionHeight": 1405351,
"timestamp": 1732775392958,
"index": 19,
"globalIndex": 8132714,
"numConfirmations": 361615,
"inputs": [
{
"boxId": "dfb668c0f2d384459869efddb225549067f184f2a53ee14492adbb942fe88e1c",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "c9ee2c232af91c23a157b29c82bacf2518ecf8461660357c1e76964e47a39117",
"outputTransactionId": "688940b481c97d26a5fa3b956440c2818785b9ba76aa5ec9a8a90b6481945645",
"outputIndex": 1,
"outputGlobalIndex": 44238530,
"outputCreatedAt": 1405341,
"outputSettledAt": 1405343,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ddcf399a712ddfea9b6a311d602f88c29475b115e7f995d432459c44f098c035",
"sigmaType": "Coll[SByte]",
"renderedValue": "ddcf399a712ddfea9b6a311d602f88c29475b115e7f995d432459c44f098c035"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20d7a26e2ee082ab2558d50d8cda5674358cfc78da214bbbbde6445e6556d0ac95",
"sigmaType": "Coll[SByte]",
"renderedValue": "d7a26e2ee082ab2558d50d8cda5674358cfc78da214bbbbde6445e6556d0ac95"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "651827c6dc957d7d9f752d20d578ed270a22cb25e01e5e830bb4340b53396609",
"value": 1010000,
"index": 1,
"spendingProof": null,
"outputBlockId": "c9ee2c232af91c23a157b29c82bacf2518ecf8461660357c1e76964e47a39117",
"outputTransactionId": "8557627a3ebc9c8591d60adb5d6c16e5a6775a2fcd77d2f77dd990e9264fb55c",
"outputIndex": 1,
"outputGlobalIndex": 44238535,
"outputCreatedAt": 1405341,
"outputSettledAt": 1405343,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "3766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20b913c4ff8a31534a3ef645cc8e4dadf9daf7b0bc76b101c2f4df2e7694ba8e47",
"sigmaType": "Coll[SByte]",
"renderedValue": "b913c4ff8a31534a3ef645cc8e4dadf9daf7b0bc76b101c2f4df2e7694ba8e47"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "bd898f25831a4408b744a0460bbf34776e388e2c21de7f7d3c481e12b5e6c7b7",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "a3311eb6e0262cc4bab1df8f1af242feb6fdd586980ba88cea4b82914a4afa9d",
"outputTransactionId": "4b7b3ebb072e361fddbb91af133337a7b9366cf177beadd88873a4d1ad793e28",
"outputIndex": 1,
"outputGlobalIndex": 44238543,
"outputCreatedAt": 1405341,
"outputSettledAt": 1405344,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20059e38729e1d06a02358f46a27bde7d5c77cfe1e8af9922a91b541386c009af2",
"sigmaType": "Coll[SByte]",
"renderedValue": "059e38729e1d06a02358f46a27bde7d5c77cfe1e8af9922a91b541386c009af2"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20ce46cce4a2fdcd94fc90b13258c2a35f47fa5236b44e0b57d76b09dc8b9ae551",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce46cce4a2fdcd94fc90b13258c2a35f47fa5236b44e0b57d76b09dc8b9ae551"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "03e27339a0c076bb038a776344f378bb8ef5ce82399b817ffba3cdaf1a8e132b",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "237fccc4faa5415fd2658a71902b0f7e83613fec3ee9c99c56d6b4aaa03a2827",
"outputTransactionId": "a4967ab5f683d2643eec8238fe2376b305cbd00c27088e7eadad3227a0cc7055",
"outputIndex": 1,
"outputGlobalIndex": 44238562,
"outputCreatedAt": 1405343,
"outputSettledAt": 1405345,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ea17a62c608a9475a30f1ba345b82c2dd2c799d27dc4d4c9ba84bf7f282de3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea17a62c608a9475a30f1ba345b82c2dd2c799d27dc4d4c9ba84bf7f282de3d5"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20f07f1117eed8d4e7be5cb385e2c0c78546f7836d21fe34c1c40065703fe59407",
"sigmaType": "Coll[SByte]",
"renderedValue": "f07f1117eed8d4e7be5cb385e2c0c78546f7836d21fe34c1c40065703fe59407"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ef6f1d53dc2568a09dab7556fa4ea414393b5337d368381df19f63b3fd37c495",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "237fccc4faa5415fd2658a71902b0f7e83613fec3ee9c99c56d6b4aaa03a2827",
"outputTransactionId": "833391557812aa6fdb964462dd34c71288a704828572fc43fa8b75da6a458ea4",
"outputIndex": 1,
"outputGlobalIndex": 44238567,
"outputCreatedAt": 1405343,
"outputSettledAt": 1405345,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "742aab33ec1d5b1e29d0d76c31b75d93e60ab3a71f978bcf14e369c2134b3e4b"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e209ea95b372ff3977864a8b6ac30f686f44dea914cabf7975217e268adf4536654",
"sigmaType": "Coll[SByte]",
"renderedValue": "9ea95b372ff3977864a8b6ac30f686f44dea914cabf7975217e268adf4536654"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "8851a6e4a6a36175a237432fb51939a091da3c5fe72af424f326fd1172fb8cde",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "89b71bba4ee34f7f11f794e7e462a0542332c4c03f98cf8eecf7c276b8750b6d",
"outputTransactionId": "6a2b994e4e57167e9db0d2f12dbbb0a565b987c43236a9483590f209a4d4ef69",
"outputIndex": 1,
"outputGlobalIndex": 44238587,
"outputCreatedAt": 1405344,
"outputSettledAt": 1405346,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f3559bc59e4fb41ad36f0b213740410b4cb61f967968fee72f83d2560199ae84"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7b9c96abc7edc8f96aa187cb4551580ba490643728c72788c85d35b0b8a8aff0"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "89b71bba4ee34f7f11f794e7e462a0542332c4c03f98cf8eecf7c276b8750b6d",
"outputTransactionId": "5b8c407dd345722189cfb3b0f5c8bbc2c8755d5230ea90f96b5fd205d6f66577",
"outputIndex": 1,
"outputGlobalIndex": 44238592,
"outputCreatedAt": 1405344,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200088840f331eedf07d309096c075208670801d18d730ba3fb2bb341bd5c094ca",
"sigmaType": "Coll[SByte]",
"renderedValue": "0088840f331eedf07d309096c075208670801d18d730ba3fb2bb341bd5c094ca"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e209ca9c3dced938b89f6f8ad2b552bb587abb67c21350c29634e354c8408012aaf",
"sigmaType": "Coll[SByte]",
"renderedValue": "9ca9c3dced938b89f6f8ad2b552bb587abb67c21350c29634e354c8408012aaf"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ea825d97321dfd6e3f4103a5a26f62e2b5d56fe209b0a5b57db39b60b84991b7",
"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "89b71bba4ee34f7f11f794e7e462a0542332c4c03f98cf8eecf7c276b8750b6d",
"outputTransactionId": "bc20004665b5de072d408927326e01df8183780e91a245edcc94fe7ab99b6c61",
"outputIndex": 1,
"outputGlobalIndex": 44238597,
"outputCreatedAt": 1405344,
"outputSettledAt": 1405346,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6696280d3218decd0ba11a5a954542de86db8915e6ed6210b02ad6edb5d15ff5"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e205eaad4fb2e18233f399bd611c93c0672c2364e325f40c9728635b1fc1b54521e",
"sigmaType": "Coll[SByte]",
"renderedValue": "5eaad4fb2e18233f399bd611c93c0672c2364e325f40c9728635b1fc1b54521e"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 8,
"spendingProof": null,
"outputBlockId": "89b71bba4ee34f7f11f794e7e462a0542332c4c03f98cf8eecf7c276b8750b6d",
"outputTransactionId": "d135bc857ff51dfba10e9c5ac7f816569f7ecc36d081f73217fe383051632016",
"outputIndex": 1,
"outputGlobalIndex": 44238602,
"outputCreatedAt": 1405344,
"outputSettledAt": 1405346,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f3ed92c3f867beec54f5dff6dd8682854eefb9eed2fa9c22f4d2ec5d8fdd050"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20af81ed3b2e4293ef6fe720ff232818742ddb4c9e305c7567d9499a3bdf74fe85",
"sigmaType": "Coll[SByte]",
"renderedValue": "af81ed3b2e4293ef6fe720ff232818742ddb4c9e305c7567d9499a3bdf74fe85"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 9,
"spendingProof": null,
"outputBlockId": "d461c8a0317b2387281e9f9cc4568cfc2e5e9e528e289b624df9b4edf1a54621",
"outputTransactionId": "8071826ad0242a7f64653ff0c3573489a3f2b7dbeff0bcf9e298d551b10925d6",
"outputIndex": 1,
"outputGlobalIndex": 44238639,
"outputCreatedAt": 1405345,
"outputSettledAt": 1405347,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20621fb713bbd2ada003d4011847753211eabe84a42b64256d3b57842d03ee32e0",
"sigmaType": "Coll[SByte]",
"renderedValue": "621fb713bbd2ada003d4011847753211eabe84a42b64256d3b57842d03ee32e0"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20f887b76440d998b0d8c5783cb151ed489f8abaff9692f276056ef03173f326ff",
"sigmaType": "Coll[SByte]",
"renderedValue": "f887b76440d998b0d8c5783cb151ed489f8abaff9692f276056ef03173f326ff"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ef95e77edee70526e3fb39846de225dd0c0d863fdff5b48debde931a7ce6c59c",
"value": 2000000,
"index": 10,
"spendingProof": null,
"outputBlockId": "d461c8a0317b2387281e9f9cc4568cfc2e5e9e528e289b624df9b4edf1a54621",
"outputTransactionId": "d3be680a0e1c76e75834c8921b6476d656c7f74aeed9be225b80f2a9e6db4f80",
"outputIndex": 1,
"outputGlobalIndex": 44238644,
"outputCreatedAt": 1405345,
"outputSettledAt": 1405347,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1b532f49a3da89e577a27cad46cc15bb380a804af44bbbd6d3469ce87096d5bf"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "be935fc5fc38d51f1c61b9a00fcc1d78c8c616c599aebc73612f447e03105900"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "bb8778dec30d2e55869519b4e7b8e04eb95a5d95c6a19517cffaae75f110e3a0",
"value": 2000000,
"index": 11,
"spendingProof": null,
"outputBlockId": "d461c8a0317b2387281e9f9cc4568cfc2e5e9e528e289b624df9b4edf1a54621",
"outputTransactionId": "d97409b55cc99c75addaa18b67944681c629368fc0debe1fd6c46af806ddcacc",
"outputIndex": 1,
"outputGlobalIndex": 44238649,
"outputCreatedAt": 1405345,
"outputSettledAt": 1405347,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e2009e7a611ed18d7dab87400a7818b735e97429e878e8a6114afdda962b88e3ea3",
"sigmaType": "Coll[SByte]",
"renderedValue": "09e7a611ed18d7dab87400a7818b735e97429e878e8a6114afdda962b88e3ea3"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 12,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "1888465803fcea34f080dce4fc674d1f18ebb4557f8745a0182542e73924bd6d",
"outputIndex": 1,
"outputGlobalIndex": 44239002,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201a4632387dca978547717b8cce0c5f9c772f10afde5b0923604e97986ebd99a3",
"sigmaType": "Coll[SByte]",
"renderedValue": "1a4632387dca978547717b8cce0c5f9c772f10afde5b0923604e97986ebd99a3"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20110b57bb846a5789f1376b3809f717b125e98a983c300e84620241279375d6c1",
"sigmaType": "Coll[SByte]",
"renderedValue": "110b57bb846a5789f1376b3809f717b125e98a983c300e84620241279375d6c1"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c4871c012d48efe9dd60674162198d5c77cb6a46573d63e700254ec2d0309a5f",
"value": 2000000,
"index": 13,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "2e07082b055ff8ce05423dc0801a5fc92ac1b9f89e9a539c709362e3c4d95cb6",
"outputIndex": 1,
"outputGlobalIndex": 44239007,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8a8d76067e347c2303dae5fc7fb360b83df71ba1d97dc4e02b6537f27a93af95"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 14,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "4d819b6d50b8a280e212c1fd0f7ab442cb8ced2c374336a0438a95fb7440a160",
"outputIndex": 1,
"outputGlobalIndex": 44239012,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "11828b9a658cce6c56ce70ecf14abf9b01eecd8cf9d599b609a3f0b3d14952fd"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 15,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "536abc42660362e83d5bbf01958f9a9a0b2fe1aa29985d05cce99ce5f4b5d14e",
"outputIndex": 1,
"outputGlobalIndex": 44239017,
"outputCreatedAt": 1405346,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20635159e6aa47ccf232ad01ca2c74add48b5195d703ea24f4040155e18afd099d",
"sigmaType": "Coll[SByte]",
"renderedValue": "635159e6aa47ccf232ad01ca2c74add48b5195d703ea24f4040155e18afd099d"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2007f92fb1d846be8e35ee9079d87eded21c95d7c8db3b97e12ff1959d8d679b50",
"sigmaType": "Coll[SByte]",
"renderedValue": "07f92fb1d846be8e35ee9079d87eded21c95d7c8db3b97e12ff1959d8d679b50"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "38d50f1bad80fe2a85ecb167b416ec7bc484bc45277ddf1748f2095cdc4af660",
"value": 2000000,
"index": 16,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "6123b41bcde034fdf0e741a43c751f6369e3599aeb2c5525b75268cbff433580",
"outputIndex": 1,
"outputGlobalIndex": 44239022,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206688602460b5e65381f6d3bd60ebe459b5bdc6ec3c1d4824b37a6edba227f400",
"sigmaType": "Coll[SByte]",
"renderedValue": "6688602460b5e65381f6d3bd60ebe459b5bdc6ec3c1d4824b37a6edba227f400"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e206f212bcdbce0b94aa0e2f05c6dfa802bff5e060d7e06453f1d222112531873f4",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f212bcdbce0b94aa0e2f05c6dfa802bff5e060d7e06453f1d222112531873f4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "f6d057aab4047abe4876127e9ad7591115584c913e735180fcba8a9b08be8c96",
"value": 2000000,
"index": 17,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "660630e407cee3e576013ce3755d54294cbb64ed62ba9e3fb5144e3a71ceb7a7",
"outputIndex": 1,
"outputGlobalIndex": 44239027,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e203aa7ed9864521180387dcc059e46225ada5116a86758bc2b958873bbd7d19366",
"sigmaType": "Coll[SByte]",
"renderedValue": "3aa7ed9864521180387dcc059e46225ada5116a86758bc2b958873bbd7d19366"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20bbee12393f283be8d250b674c391c98512e692481a3a81d8d6b16b230301fea7",
"sigmaType": "Coll[SByte]",
"renderedValue": "bbee12393f283be8d250b674c391c98512e692481a3a81d8d6b16b230301fea7"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "294f31fb22388263b2e2cb2bc7651ea7f96b454048f011cdf02c62ad74356a3d",
"value": 2000000,
"index": 18,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "686f682fce98e3cdc8628fc8494caa5ac77ba2f5da00651c1ad35cd526aa3b3e",
"outputIndex": 1,
"outputGlobalIndex": 44239032,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a",
"sigmaType": "Coll[SByte]",
"renderedValue": "0b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e203defb2048bfb3029c33d198f4e8322f2125ae508ca6cc3427920a0c6453178ef",
"sigmaType": "Coll[SByte]",
"renderedValue": "3defb2048bfb3029c33d198f4e8322f2125ae508ca6cc3427920a0c6453178ef"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "aa09e33dfb71bacc068a37a2b2ab0309d0e07b8035acbb3ab793e4917252d0a2",
"value": 2000000,
"index": 19,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "88a4f04da029871ae038ec4f55a69050b2885176d7327736bcd009cb80f28917",
"outputIndex": 1,
"outputGlobalIndex": 44239037,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2093d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9",
"sigmaType": "Coll[SByte]",
"renderedValue": "93d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20b743ec77b6fb712793d82808b2d69da3aa1a72118114e05f86c129f393933ab6",
"sigmaType": "Coll[SByte]",
"renderedValue": "b743ec77b6fb712793d82808b2d69da3aa1a72118114e05f86c129f393933ab6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 20,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "9d9756c79d73e651a9fc1adf9159d197d84c2e6b5a4aa9d239bfbd29354eb348",
"outputIndex": 1,
"outputGlobalIndex": 44239042,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "070f3caa50bf71d492682e8ba8b40d7337bbb49bbc425848ac9434ee19882b79"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 21,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "d60434425722b812c971788fd8ef3f7bb3c511be2c66841c70786e7fe6ab77d0",
"outputIndex": 1,
"outputGlobalIndex": 44239047,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7",
"sigmaType": "Coll[SByte]",
"renderedValue": "1fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2092e22712647bb497c7a4ccc90fb5a95d8b0bff2ba34e1cb36eb09223d95c3f99",
"sigmaType": "Coll[SByte]",
"renderedValue": "92e22712647bb497c7a4ccc90fb5a95d8b0bff2ba34e1cb36eb09223d95c3f99"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "82be66027f6ca27e64a8f13e0a00e1a1774e62dc3b21c317104d2077fad9b3f2",
"value": 2000000,
"index": 22,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "e7d9c134a8c50ff3603e650be983cc34dd3e8cdec40bd431f15e87128092cef3",
"outputIndex": 1,
"outputGlobalIndex": 44239052,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20333810ee13abfd784cfce3cb6e4fc9d2eb6e75d4884937892de6fbbc8d3a7ce6",
"sigmaType": "Coll[SByte]",
"renderedValue": "333810ee13abfd784cfce3cb6e4fc9d2eb6e75d4884937892de6fbbc8d3a7ce6"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20693a8f3739de9920b75236d0fb96ee3db407749b576ce3dc498da80614afd2b9",
"sigmaType": "Coll[SByte]",
"renderedValue": "693a8f3739de9920b75236d0fb96ee3db407749b576ce3dc498da80614afd2b9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "79e8dbf2fb942bb0fe8a18c96d22f7c4a592a4e4f500dc45ce88e5ac06381e82",
"value": 2000000,
"index": 23,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "ed68b0a4a41a826a8658bd9a8c811c004563267f8e85fd957b32942d94520e8b",
"outputIndex": 1,
"outputGlobalIndex": 44239057,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405348,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f",
"sigmaType": "Coll[SByte]",
"renderedValue": "581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f58b048f6d3a5f18e3e7a169f16969df1420f0befe443c391612e466ba4bfc2d"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 24,
"spendingProof": null,
"outputBlockId": "3cd77a00fe18a9285827d663542ed0e6646e0413391d4e9c767da4f670615cc9",
"outputTransactionId": "9b5f0502b0077aa10632910cafad42b282764bd89a0cb8807aa9b3550c6aab21",
"outputIndex": 1,
"outputGlobalIndex": 44239108,
"outputCreatedAt": 1405346,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2016cd30028d001fee06761a3da0e6329d39e5e5ef80030531634f2abddddbe360",
"sigmaType": "Coll[SByte]",
"renderedValue": "16cd30028d001fee06761a3da0e6329d39e5e5ef80030531634f2abddddbe360"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "dc785b96bee8e40e4b5118425c6e12054012f1a4843a74790d5b0e7c8b293f4f",
"value": 2000000,
"index": 25,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "d3bb8b38962585cbbedcc5a7815263ed9b9559856083a83659d762441ac9a45b",
"outputIndex": 1,
"outputGlobalIndex": 44239124,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c6c832a5da7aac3925ec870c16cb94156419e3b579b12252a94801d8bf365647",
"sigmaType": "Coll[SByte]",
"renderedValue": "c6c832a5da7aac3925ec870c16cb94156419e3b579b12252a94801d8bf365647"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "af397884a59346dbe5cece6f156910ea47477f39143da75583832b9da43126eb"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "bd0de968125514343d2d6edc75de30f446dad75ad0bb745bdcbb2590de168e4b",
"value": 2000000,
"index": 26,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "b7e788ada3198d3de886318c21afddd828ae82763a02d792e39350dd9e56a157",
"outputIndex": 1,
"outputGlobalIndex": 44239129,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20f881c6baffd9bd4b1fb7241b8cf8cab0058ccc89f66a873ec64c8d1a0e0596bd",
"sigmaType": "Coll[SByte]",
"renderedValue": "f881c6baffd9bd4b1fb7241b8cf8cab0058ccc89f66a873ec64c8d1a0e0596bd"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e209aab119c23298eabe0867cc8b97cf3317ca36ebbb55145991260e74c5bbb7aa5",
"sigmaType": "Coll[SByte]",
"renderedValue": "9aab119c23298eabe0867cc8b97cf3317ca36ebbb55145991260e74c5bbb7aa5"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "721a2a280a62258bad3703712daf965834621dfbbde3095d40bfd5c55bcc5a8f",
"value": 2000000,
"index": 27,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "0505604df3d0643b94bdd9c595b5fc63ec4d6d9a10873fc4440bc67093712286",
"outputIndex": 1,
"outputGlobalIndex": 44239133,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2019b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29",
"sigmaType": "Coll[SByte]",
"renderedValue": "19b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20f76a1f3a15333bb2f89ae1b3c76b403cecedb87c101dfdb92c409d19e28e9844",
"sigmaType": "Coll[SByte]",
"renderedValue": "f76a1f3a15333bb2f89ae1b3c76b403cecedb87c101dfdb92c409d19e28e9844"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c5aefc79eade742726521badc5b47025d811f20fb1f890bbcf878b1330bc80f0",
"value": 2000000,
"index": 28,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "05a141516bf27b9d5af386bc254022b330b3c13a7301609e720abbb8060cb569",
"outputIndex": 1,
"outputGlobalIndex": 44239138,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e204e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916",
"sigmaType": "Coll[SByte]",
"renderedValue": "4e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2036798bf312fddac564105f533943e6e1e03b64362d99b07c604ac3ff4ac315fa",
"sigmaType": "Coll[SByte]",
"renderedValue": "36798bf312fddac564105f533943e6e1e03b64362d99b07c604ac3ff4ac315fa"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 29,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "06f7e37c00a9fa81d0b31753710b187317c945352476f0df0d92d5472068b324",
"outputIndex": 1,
"outputGlobalIndex": 44239143,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20dc9aaa6c02c4b1db7f949eb7f70ea4d60e696f78ba623234f4aaefd235860cbd",
"sigmaType": "Coll[SByte]",
"renderedValue": "dc9aaa6c02c4b1db7f949eb7f70ea4d60e696f78ba623234f4aaefd235860cbd"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3ea3d2a3ed03d3c6f12014a2cfc7df089af963a74695fe8416412b4d66b796b3"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 30,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "079a4e41fd4dc3fcde843d0dfa10092e9b9aa99a38cffd591c1f9e2029986bfc",
"outputIndex": 1,
"outputGlobalIndex": 44239148,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20cacc2b189e0300a41a77a080699ff25b933eb71bad64297ecb56eeeea5855439",
"sigmaType": "Coll[SByte]",
"renderedValue": "cacc2b189e0300a41a77a080699ff25b933eb71bad64297ecb56eeeea5855439"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20884c7f5b743c247aa2076fec243d44c3ce5e964c5d12c513679a1339ce488e62",
"sigmaType": "Coll[SByte]",
"renderedValue": "884c7f5b743c247aa2076fec243d44c3ce5e964c5d12c513679a1339ce488e62"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "953da8ecc9ceac9d3ad4c739461bbc1a2e6ee6e6f059cea2804ce95e42602048",
"value": 2000000,
"index": 31,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "08f5dfec99a344fec8d6db1ca4b578c305e10314f12872ca6fe4e570ac447ceb",
"outputIndex": 1,
"outputGlobalIndex": 44239153,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2050578332ebb8fb95c5b1a62410257c9982a0bd25d93b1ae6787ea95bb94e9757",
"sigmaType": "Coll[SByte]",
"renderedValue": "50578332ebb8fb95c5b1a62410257c9982a0bd25d93b1ae6787ea95bb94e9757"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20536db546f82a0e93c86917c4c226ac2f94ea02dee69ccc8fc6df3f968e7e200d",
"sigmaType": "Coll[SByte]",
"renderedValue": "536db546f82a0e93c86917c4c226ac2f94ea02dee69ccc8fc6df3f968e7e200d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "8a07718b956c850d611540f3f4374f2af5e0d0d9a83265833cc0c7d1b4b144c5",
"value": 2000000,
"index": 32,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "091aec5dd514c1ea8d82032d245554e28f6cd411760d179a86cecfab68857eaf",
"outputIndex": 1,
"outputGlobalIndex": 44239158,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a6ff2fc001a271b31891207c3588580a10475c6e9c8bc4b8a7a05edc072ba4dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "a6ff2fc001a271b31891207c3588580a10475c6e9c8bc4b8a7a05edc072ba4dd"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20689354ed3072a53a91683ca4a3286632dc490981adf0832eb4f7efa34faf960e",
"sigmaType": "Coll[SByte]",
"renderedValue": "689354ed3072a53a91683ca4a3286632dc490981adf0832eb4f7efa34faf960e"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c797eb1dd06117eeefaa7450accb36b2d6218f059dfdfda4f31f1e04b3834552",
"value": 2000000,
"index": 33,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "095ab517f3866832913028f4e07671d9ff36d653d330bdb0f942d4df650c9012",
"outputIndex": 1,
"outputGlobalIndex": 44239163,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08",
"sigmaType": "Coll[SByte]",
"renderedValue": "3ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e209521c295f43f15b177a3727ed350104bb0c649d42871c01cdd94b2df3d4e3f64",
"sigmaType": "Coll[SByte]",
"renderedValue": "9521c295f43f15b177a3727ed350104bb0c649d42871c01cdd94b2df3d4e3f64"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "11d824aed31bb2812652b20a70f927581d8f8ec8f2067958cfa6e5cbd5e21513",
"value": 2000000,
"index": 34,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "0a064e328e1e8abd6495644dd40d4ef7b9f95cc0bec4922964a4a24dd89af900",
"outputIndex": 1,
"outputGlobalIndex": 44239168,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "94dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20f61c5f99b8acbb910e02516e2fe925cdabde928b68daef5888c37dac4ef62a8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f61c5f99b8acbb910e02516e2fe925cdabde928b68daef5888c37dac4ef62a8b"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 35,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "0b6355f79eca6fc0688e0c1e38270230aa81d48930fd69f185a26c03a5aee338",
"outputIndex": 1,
"outputGlobalIndex": 44239173,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9d57b0fed60a6f7c06e57cdf6c8fe88f5df4f44dbd41d5f43ed4b971aa13c017"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "396dec2caecea4f753436e6bb4f07f0a12eb740eeb161064307478b1a18a7802"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 36,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "0be15bded3fb4c70c9a73ba1def5c4526060a5d93ea53a3811c0731cd06d2558",
"outputIndex": 1,
"outputGlobalIndex": 44239178,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d289df8aee844cdc1a6b7c84efe280a8d7c51dc6412c3e36b64d4ee71f4cb916",
"sigmaType": "Coll[SByte]",
"renderedValue": "d289df8aee844cdc1a6b7c84efe280a8d7c51dc6412c3e36b64d4ee71f4cb916"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2035dbcbd7af49cb0b63fa46efb7642b0827e9b560df2f485502df1283882319ec",
"sigmaType": "Coll[SByte]",
"renderedValue": "35dbcbd7af49cb0b63fa46efb7642b0827e9b560df2f485502df1283882319ec"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1843f341a9e6d0dac0f23808b4c094cfdb7c50eb1fbc19433f18ba11aa66b73f",
"value": 2000000,
"index": 37,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "0d1cabd0b386a30239cf43c512bbd2619ba541a946cca86375c4765563d95a3b",
"outputIndex": 1,
"outputGlobalIndex": 44239183,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5de7c58e90454fe60345df0afa28bcdc61a34e112d4e541d5b58da6a89d45ea2"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "da113cc1050a52ab4853c6b6fbf51b09f6f1024239e6bb7da378c7f9e3dba3be"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 38,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "0ea604704b000c40140a267c009c9f33393b200993c5371168158dd757d9c11f",
"outputIndex": 1,
"outputGlobalIndex": 44239188,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3684a6fc79378d5207e1dc5bc3f399d2367031b79a2fc76f8d0bfe2082c71be7"
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "195a527c6d6e9d33473eecdf9b59483f544e93f0023243935813a54c352519cf"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 39,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "12f8610e3c0914679e9bfd9f319bb56ecb4e0fba92c07e6f0b15baa6836fb76b",
"outputIndex": 1,
"outputGlobalIndex": 44239193,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691",
"sigmaType": "Coll[SByte]",
"renderedValue": "916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e206f4ea3e45d4cd2af03612dd2db7653f6fc2940d5e99248e6a74f6abaed48c0e9",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f4ea3e45d4cd2af03612dd2db7653f6fc2940d5e99248e6a74f6abaed48c0e9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "680934309a77a88daf5ccad4cb17dc2eb27a1fcc375ecd8672dfffe4d9043e70",
"value": 2000000,
"index": 40,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "1af07144d906a3881c9206af022b5f3967e4b590a1a0305bd10a3a4efcbd4a8b",
"outputIndex": 1,
"outputGlobalIndex": 44239198,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c2fa6283d1be597ef8ab3db6dfdf0111f56dce82303d094759fa58513955144d",
"sigmaType": "Coll[SByte]",
"renderedValue": "c2fa6283d1be597ef8ab3db6dfdf0111f56dce82303d094759fa58513955144d"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2050c6922bd3a3da3c74fb92a35af6f31be13adc1fa91e0a407c109e25e36c4c21",
"sigmaType": "Coll[SByte]",
"renderedValue": "50c6922bd3a3da3c74fb92a35af6f31be13adc1fa91e0a407c109e25e36c4c21"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "3a8499a77fa8a3f3b771e6d2ee90c30d7c7ded247649502c49d82bdaa5ad5c6d",
"value": 2000000,
"index": 41,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "1b56b6fb4a8f0a39e9416a541b91ff95b899242cde3ed0c5b83fccc8dae61172",
"outputIndex": 1,
"outputGlobalIndex": 44239203,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7",
"sigmaType": "Coll[SByte]",
"renderedValue": "fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20367daa8c9edc62e60ff77fb270572f1a88209e4c59662aa923876b7e1ff1440f",
"sigmaType": "Coll[SByte]",
"renderedValue": "367daa8c9edc62e60ff77fb270572f1a88209e4c59662aa923876b7e1ff1440f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
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"value": 2000000,
"index": 42,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "1c7340e3847affb656bf745ec6ce8d870d9cbdc092e21d33b7054d7ea36d2fb4",
"outputIndex": 1,
"outputGlobalIndex": 44239208,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e208e4ad9d51dc7163937eaeb6760c53bfb4d64d7369580d056ae32df6795c2dd4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "8e4ad9d51dc7163937eaeb6760c53bfb4d64d7369580d056ae32df6795c2dd4b"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20f4c00b2ca1dd993e8bdb15d16a7fd79f6758a968ef99ef574deabd65a18feafe",
"sigmaType": "Coll[SByte]",
"renderedValue": "f4c00b2ca1dd993e8bdb15d16a7fd79f6758a968ef99ef574deabd65a18feafe"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "019491e27881e862f05322765d6457e9ca293d66845b8bbe92321cd07d649495",
"value": 2000000,
"index": 43,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "1ea4e32dbe51c963018a192a23cac9f152156ebc6aec1f7cb751bf5da8ff7233",
"outputIndex": 1,
"outputGlobalIndex": 44239213,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2038813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e",
"sigmaType": "Coll[SByte]",
"renderedValue": "38813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20550c3f8c2e2f66c282b532f6ab4a40901ac3c81d488bf8e95c422b310a3dde45",
"sigmaType": "Coll[SByte]",
"renderedValue": "550c3f8c2e2f66c282b532f6ab4a40901ac3c81d488bf8e95c422b310a3dde45"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "4813d2c77d62be4c9bf131828edbed3470c5a41f8fc50e7935309db8c6e0ce54",
"value": 2000000,
"index": 44,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "203e7f41dbace70b0a8c78cbafc2ac1ed190ab377dceda3dcc932182136d5742",
"outputIndex": 1,
"outputGlobalIndex": 44239218,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20bfc372a6d2ac00cc08dbe822ee10e55a15ac224b15255f6fd884a488ed515220",
"sigmaType": "Coll[SByte]",
"renderedValue": "bfc372a6d2ac00cc08dbe822ee10e55a15ac224b15255f6fd884a488ed515220"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20e87474e3ef6aacb96afbb02f90e5478510a015524ce2726faefdc8deffc7e47a",
"sigmaType": "Coll[SByte]",
"renderedValue": "e87474e3ef6aacb96afbb02f90e5478510a015524ce2726faefdc8deffc7e47a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c5e515b76aa620475aa7d026c7b4361c21a19ba4f3eeabf6ec69cd394fb999bf",
"value": 2000000,
"index": 45,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "24224ab10e0d7555983e240ba43b003f7916567d1140ce66c4e3910c9a2e5281",
"outputIndex": 1,
"outputGlobalIndex": 44239223,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5",
"sigmaType": "Coll[SByte]",
"renderedValue": "d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2009b9d8dd53c982726cfcfe921b85e8bba62c78d468d4149c252846824dbfa54d",
"sigmaType": "Coll[SByte]",
"renderedValue": "09b9d8dd53c982726cfcfe921b85e8bba62c78d468d4149c252846824dbfa54d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f6f6c05797c202e10750e7eb48d27fedeeae369636db6a48ecbce6a896bbdc20",
"value": 2000000,
"index": 46,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "2847801123d39087790d4d53a20ed26395cbe596199c07b073170e612f6f6556",
"outputIndex": 1,
"outputGlobalIndex": 44239228,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "497e21752b5a1b85c8b814a205d2f5257ba08e2bccd92fcdd9dc80125917a07b"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9d833b5d4c628bb303a9332f2a27acb563b91ae6b931a4df185fccb5db68c369"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 47,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "322bae24f434de7f97da29345c232e3373d8cb3b5d584aa80590f8dd8e3ada89",
"outputIndex": 1,
"outputGlobalIndex": 44239233,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "38218f14f29151e31e746f4d53d45d57d39ae5609f15b512abf1570cbfad1924"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 48,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "36cc42dfc3c62650381e9686d0222dcff6f4a012a4415153e727e81c9c5d1bd8",
"outputIndex": 1,
"outputGlobalIndex": 44239238,
"outputCreatedAt": 1405347,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20e4826206c7a12594a7eb4b44cac46968127e9d39748919bdb01a232c3b7ea537",
"sigmaType": "Coll[SByte]",
"renderedValue": "e4826206c7a12594a7eb4b44cac46968127e9d39748919bdb01a232c3b7ea537"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e208de2040486e68d951652307a028df0705353f5014a779d4a77a74ba7e5bf63d4",
"sigmaType": "Coll[SByte]",
"renderedValue": "8de2040486e68d951652307a028df0705353f5014a779d4a77a74ba7e5bf63d4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "bb167f365a02365776c9517176ac7a1e9ba48b310f73d65af9575cc0d9c553aa",
"value": 2000000,
"index": 49,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "375d61818cf9cb32062e02c680c1da404c7bdcd1fb04c637ca373e26dacfa0e3",
"outputIndex": 1,
"outputGlobalIndex": 44239243,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858",
"sigmaType": "Coll[SByte]",
"renderedValue": "327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20c9c7702eda7bfbb0ecccaf7b324ff74b18841d59dc51a439f43e7a6f0fe8ddff",
"sigmaType": "Coll[SByte]",
"renderedValue": "c9c7702eda7bfbb0ecccaf7b324ff74b18841d59dc51a439f43e7a6f0fe8ddff"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "7a2392e1c515f505fdc4e2c6fda9ee64b4da0a877192853cfa23d4d8aa7770c5",
"value": 2000000,
"index": 50,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "378bb53beef7b7639dae835b86a465cbe87729c02ec189acbdca5b2ed25cc18d",
"outputIndex": 1,
"outputGlobalIndex": 44239248,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200dba2cea2e980eaaf6f1e8cf6485b2801671c13b6f975d392b4920b71488a3b3",
"sigmaType": "Coll[SByte]",
"renderedValue": "0dba2cea2e980eaaf6f1e8cf6485b2801671c13b6f975d392b4920b71488a3b3"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "e75b16254f82fabd7f74ff614196b2fb65b3078717634cb84258fdfbdbfb1fed"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "40f480b98253d79f0f971c88fab6d83840401939897b94fb22f2426c4c58efae",
"value": 2000000,
"index": 51,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "3b72af629272045cec49ea48f32ac51a536b654961795a200cf20d89e6e4d74a",
"outputIndex": 1,
"outputGlobalIndex": 44239253,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201a0f3106b93d5720b1d9e423e0a5f69e293bc01f673d28fac737975811322b26",
"sigmaType": "Coll[SByte]",
"renderedValue": "1a0f3106b93d5720b1d9e423e0a5f69e293bc01f673d28fac737975811322b26"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20da6f5f92fef85c886297304fb876bf165441b3b6c98e096cdd388cb7c3727bd2",
"sigmaType": "Coll[SByte]",
"renderedValue": "da6f5f92fef85c886297304fb876bf165441b3b6c98e096cdd388cb7c3727bd2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "631c89e466b6b0de7f22f511b249a752af107ffda56aeb3065bedc5bde97b4aa",
"value": 2000000,
"index": 52,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "3ba9ee610313f0dc89aef496be3c907b5c51b1d2a623901fbab0a4947d0b1334",
"outputIndex": 1,
"outputGlobalIndex": 44239258,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2077e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5",
"sigmaType": "Coll[SByte]",
"renderedValue": "77e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20ca3eecc32cc6a1247e613b2dfa5f7d41e124ec04ee05422a50fdb604fd2eae79",
"sigmaType": "Coll[SByte]",
"renderedValue": "ca3eecc32cc6a1247e613b2dfa5f7d41e124ec04ee05422a50fdb604fd2eae79"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "822087b61fd8ab65f63bd807eb6f5b23cfda1493e6172636045a750e2fd4865e",
"value": 2000000,
"index": 53,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "3cbb3b4bec53eb98f91dfcc37994045def384c37e0117c268b48985f085d4435",
"outputIndex": 1,
"outputGlobalIndex": 44239263,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2074d14ee349bc54781627bafddea455bf045eac5941d64e2175704a150b8a070d",
"sigmaType": "Coll[SByte]",
"renderedValue": "74d14ee349bc54781627bafddea455bf045eac5941d64e2175704a150b8a070d"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20d502d414a585676bbe22081c70f2e3fb22882fb598a5314de6c3b4d6e20343df",
"sigmaType": "Coll[SByte]",
"renderedValue": "d502d414a585676bbe22081c70f2e3fb22882fb598a5314de6c3b4d6e20343df"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6030f4399f9fc1de561a3c09ae6113d76a1fa92135b74c22cd39268c7eacf956",
"value": 2000000,
"index": 54,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "3fb9b52aaf75331fdd1999620244b33e886096950268a2c5c1b20c1af71fd38d",
"outputIndex": 1,
"outputGlobalIndex": 44239268,
"outputCreatedAt": 1405346,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2076895958ec1827e9b3f9e302921812290f72c7c986defe9ff749ad78f212dde9",
"sigmaType": "Coll[SByte]",
"renderedValue": "76895958ec1827e9b3f9e302921812290f72c7c986defe9ff749ad78f212dde9"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e203a723c2ec8adeb21d324dbbb9a74285c2ea99044e581ee45d06333fed5226e1a",
"sigmaType": "Coll[SByte]",
"renderedValue": "3a723c2ec8adeb21d324dbbb9a74285c2ea99044e581ee45d06333fed5226e1a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "bd159bdbb4917156cc154ae1645ea207a182df197e5afcb7f6ca05556bc04d32",
"value": 2000000,
"index": 55,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "3fed20792eb151f6ab46aa53fe9df7aef178bec8f67595fef7cc28eb6b0e32ee",
"outputIndex": 1,
"outputGlobalIndex": 44239273,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9e8e898d814c6fa197d363a3b86c9dc83cf7da0653b34053ba9b7ad4a9915d3a"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2011672a5da04991400bed602f42cbe1b97e387e12b4fbeec3f864dbd75ae68f88",
"sigmaType": "Coll[SByte]",
"renderedValue": "11672a5da04991400bed602f42cbe1b97e387e12b4fbeec3f864dbd75ae68f88"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "f2e01e0a0a3d09decd6f7eb500d828a228a32b5ec619b5181091134f6a4a26cb",
"value": 2000000,
"index": 56,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "43591d26ff5428d20f6899d597ee649b0ff79a760e158dae23d659be961bf8a7",
"outputIndex": 1,
"outputGlobalIndex": 44239278,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20dd6e1620c63423f28efdbed8f59fb5109dab5adaa70c0e7dcecc7abb2ae7fa9e",
"sigmaType": "Coll[SByte]",
"renderedValue": "dd6e1620c63423f28efdbed8f59fb5109dab5adaa70c0e7dcecc7abb2ae7fa9e"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ba08884db2e988e44bfc003ce34c06b547d4e05f480530ec7912202353d2c1c4"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 57,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "496de1c22720fe08d90a8534de3ea50f5c23ca7f75dc48d87002b69fc137a6a9",
"outputIndex": 1,
"outputGlobalIndex": 44239283,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205b2f71b4f694115bd565d05668bb6537d47eb28c40961c5afcc6486771ee5ac6",
"sigmaType": "Coll[SByte]",
"renderedValue": "5b2f71b4f694115bd565d05668bb6537d47eb28c40961c5afcc6486771ee5ac6"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e207f087f9117e8c30b41ccd7141a49a612e0bdd338400ed2c075341b1a20043f54",
"sigmaType": "Coll[SByte]",
"renderedValue": "7f087f9117e8c30b41ccd7141a49a612e0bdd338400ed2c075341b1a20043f54"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "0e50db0963936ece43fadcaf90d8df1a62514e1e7dafeeecbc3326fedbead3b0",
"value": 2000000,
"index": 58,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "4f685bdb1e4e1bec944d1f25c637521acb5479746d72f6e04248b16c01daee76",
"outputIndex": 1,
"outputGlobalIndex": 44239288,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fbb2edec8b218ca0462a0347473c366a7f102e061f5a4785e8ed701c297e07ec",
"sigmaType": "Coll[SByte]",
"renderedValue": "fbb2edec8b218ca0462a0347473c366a7f102e061f5a4785e8ed701c297e07ec"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20279d4def0555085434af031ca810831bf3304ea67a9763d076cad5506fb42a91",
"sigmaType": "Coll[SByte]",
"renderedValue": "279d4def0555085434af031ca810831bf3304ea67a9763d076cad5506fb42a91"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "3a4c86c85cbde3bb74069dd5236e9bffde3701bad34dcaa9640d542da3a714b1",
"value": 2000000,
"index": 59,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "5378ad596f1f661d1fee842678c9c0f46890287529c2f202223ae2f3ed22388e",
"outputIndex": 1,
"outputGlobalIndex": 44239293,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2053e28b29c76583401b17e47678a76aa24b7a84ed4cd26f5766b944b9627636fb",
"sigmaType": "Coll[SByte]",
"renderedValue": "53e28b29c76583401b17e47678a76aa24b7a84ed4cd26f5766b944b9627636fb"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20155a140863ea25eb59ae30dfb91ff3ba0491666a27ba28cfc09cdbee507ff916",
"sigmaType": "Coll[SByte]",
"renderedValue": "155a140863ea25eb59ae30dfb91ff3ba0491666a27ba28cfc09cdbee507ff916"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "86b038f629bf979e416c6b2b786c6f6870c402f5098b244a3332bb73d5c12e8c",
"value": 2000000,
"index": 60,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "586270b16203c69be25c1bd3a0c994b53dd298a511a93b60ca695724e48f6d4c",
"outputIndex": 1,
"outputGlobalIndex": 44239298,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20329d66895b8d9c84947bfe3d72335158ada0fdd8ac8643f836c81ec85785e01a",
"sigmaType": "Coll[SByte]",
"renderedValue": "329d66895b8d9c84947bfe3d72335158ada0fdd8ac8643f836c81ec85785e01a"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e202c4cc3342547b85c959e1692451b1c27b84e0e030f334ed18314c6c2ba628b32",
"sigmaType": "Coll[SByte]",
"renderedValue": "2c4cc3342547b85c959e1692451b1c27b84e0e030f334ed18314c6c2ba628b32"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "7def7af0616c349e4828293897dbbe6ed50c80f55c5e5aef830b92ebd9ab9e2f",
"value": 2000000,
"index": 61,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "59d5b17678ed8a71be515f8a4d2ac46a9ea4f4718079ea0be3de199729e73e10",
"outputIndex": 1,
"outputGlobalIndex": 44239303,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3b9aa597064dc8b0c58f7a9e1463269e80f4c69e49e133c437ef9d70e19fdf53"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ac93e249820b8a4a4c4f5fac936cb4d7fb5ca4867453734170b885965962ba1b"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 62,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "59f122c42a3762a71bfabdd1e2d39e3c0ef126af0d0d6ec287af956501d12125",
"outputIndex": 1,
"outputGlobalIndex": 44239308,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6b50c862a12ddc14eb9669032f924327b6d32eb69a4c617016121243c64bd55c"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a25ad7deb6717f64a068f56ee0b9c253c1a562397730383eac5e1e552b6b94da"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 63,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "5a971975d20122e3c86aa1718436fc6b6f9c90fc649885e5fe71a2a9e846327e",
"outputIndex": 1,
"outputGlobalIndex": 44239313,
"outputCreatedAt": 1405347,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20942c960c9d7843f883cc67b87ed328042109968180ab180e14a42f0600df5f41",
"sigmaType": "Coll[SByte]",
"renderedValue": "942c960c9d7843f883cc67b87ed328042109968180ab180e14a42f0600df5f41"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e206362e88cde544418a1ee449f6bd6c491748382ee547f87e551bb1aebe0b15de9",
"sigmaType": "Coll[SByte]",
"renderedValue": "6362e88cde544418a1ee449f6bd6c491748382ee547f87e551bb1aebe0b15de9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "63bf6955017f2f5e0df0e6e460a79ec78fa894afaa0910a1369cba03a34104d4",
"value": 2000000,
"index": 64,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "5e2e5f581af9019e18d1cdb3e9d2b13efcbfb37b09d1e068c4e0ca690a23220d",
"outputIndex": 1,
"outputGlobalIndex": 44239318,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20fac6f406a18214575bac4760c78f1571230522d5c12feef0d223cb9d5484ae3c",
"sigmaType": "Coll[SByte]",
"renderedValue": "fac6f406a18214575bac4760c78f1571230522d5c12feef0d223cb9d5484ae3c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "dfa98b493fc1749c7f387f5b8dd67c00dabd93fe5177436ca217344d6bcb86b8",
"value": 2000000,
"index": 65,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "69d957e96be9c48c6f245d9f58dbfe9bbb674d61fe5273cfaeda1a3122c82ea1",
"outputIndex": 1,
"outputGlobalIndex": 44239323,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20386d1c70deb3315854bda324ecf573fc224ab8b78b3c9bb62309592450c91047",
"sigmaType": "Coll[SByte]",
"renderedValue": "386d1c70deb3315854bda324ecf573fc224ab8b78b3c9bb62309592450c91047"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "83cad6d6adc96dda241b8c33d4cc85f7a908dac1bba964b813a95656e9688f69"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "e9f774f0e2de0daa38a9dfed8218a5e3ce0ce5e692e32cf449aa1c5c412bc4df",
"value": 2000000,
"index": 66,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "6c8858287cbca322b7481da2765cc271b284dfea8aa72800759e26777267945a",
"outputIndex": 1,
"outputGlobalIndex": 44239328,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202cb49b8ebf41f1679770487ddeeb997ae6c0242a1c14de26935906d711054c07",
"sigmaType": "Coll[SByte]",
"renderedValue": "2cb49b8ebf41f1679770487ddeeb997ae6c0242a1c14de26935906d711054c07"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e201177721edbe18c06ea138a83b4fa2f71b80e8dd8388aa9967f47632cb9d445a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1177721edbe18c06ea138a83b4fa2f71b80e8dd8388aa9967f47632cb9d445a4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "4cf78edcdedc160df78ccfe36bde255e96f9836f7e9259e04ac7021c01fb051d",
"value": 2000000,
"index": 67,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "6cffdbb90332b5ec916ee4efeb5678a21b048f2a036734fd648c0abc9aacd2ff",
"outputIndex": 1,
"outputGlobalIndex": 44239333,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2089cf6f1a787deb69ca7216e0183af7b880ffd23e1d18dd7cd4cbe0d60b4e2079",
"sigmaType": "Coll[SByte]",
"renderedValue": "89cf6f1a787deb69ca7216e0183af7b880ffd23e1d18dd7cd4cbe0d60b4e2079"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ec56ec3f75b5aaadbe94af63c487653a5f23ff34e253824b467362837cacff20",
"value": 2000000,
"index": 68,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "6db97665f1c624532f0496cbe6f97d4a207ee3cb31a1d9c82062bf16faa3437e",
"outputIndex": 1,
"outputGlobalIndex": 44239338,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2021ec3089084258295d454c433a8659455cc2adbfd18d112c5251454082109ffc",
"sigmaType": "Coll[SByte]",
"renderedValue": "21ec3089084258295d454c433a8659455cc2adbfd18d112c5251454082109ffc"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e202144a07625d22bc1f18fcdedb0dd202227ad830258fb5b9048a1758753470add",
"sigmaType": "Coll[SByte]",
"renderedValue": "2144a07625d22bc1f18fcdedb0dd202227ad830258fb5b9048a1758753470add"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c3ce026388a1cfbf549090688f77f71826fdf234c5abb4ed6e515dea89b83523",
"value": 2000000,
"index": 69,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "6decf7481a6f23435bafdacabf603fbbd4a0f2e71782e2e0d9ddeecc14da9538",
"outputIndex": 1,
"outputGlobalIndex": 44239343,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2025006e6ba04dedc3938b074ec5d051b3ae25f4d6480d6b24203102bb413cadea",
"sigmaType": "Coll[SByte]",
"renderedValue": "25006e6ba04dedc3938b074ec5d051b3ae25f4d6480d6b24203102bb413cadea"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e200ce19ce4d09250c38981009a55cb7420a5effb9768832b789a029d6190d1ad58",
"sigmaType": "Coll[SByte]",
"renderedValue": "0ce19ce4d09250c38981009a55cb7420a5effb9768832b789a029d6190d1ad58"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "91420485ab7f759032909141d40f74f324076d503d713518ea9880be2d8f3793",
"value": 2000000,
"index": 70,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "6dfe10a99e046a120d7d019352e2865c9fc29a077458cd2a64908b345ac5f354",
"outputIndex": 1,
"outputGlobalIndex": 44239348,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201f2544ae82ab043f2889c81ac9db7ab9d74bb4af631631b5ef2200879ee7fdb3",
"sigmaType": "Coll[SByte]",
"renderedValue": "1f2544ae82ab043f2889c81ac9db7ab9d74bb4af631631b5ef2200879ee7fdb3"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20e4cca0849d50b12ad54b57b597578fa759778d86618c213d33a1fddb4503b54f",
"sigmaType": "Coll[SByte]",
"renderedValue": "e4cca0849d50b12ad54b57b597578fa759778d86618c213d33a1fddb4503b54f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "9e8d133732b88c21b6c4878f9ed6ac31c2400d8e5e56aede189f9bdbbe5e7f68",
"value": 2000000,
"index": 71,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "71a4e7592de369f557b3159582b1546ef7d4a947aac375345bd5370c77fe0dc5",
"outputIndex": 1,
"outputGlobalIndex": 44239353,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c",
"sigmaType": "Coll[SByte]",
"renderedValue": "b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e206014bd9b847f9217d2de5f320f9155c1c414c35bcb989490ede7a4fd13e49cbb",
"sigmaType": "Coll[SByte]",
"renderedValue": "6014bd9b847f9217d2de5f320f9155c1c414c35bcb989490ede7a4fd13e49cbb"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "73eb37d5ed1e60f4d2b7ec90d395dbb267ce7623760384fa4a39defe0ff1095c",
"value": 2000000,
"index": 72,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "74f8ca194193b80e45ec6a991993d3554cd4b358ac71d2a2f93d1dc89ea1c025",
"outputIndex": 1,
"outputGlobalIndex": 44239358,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20e7dc5ea26648e7c931e4853216a613208ab09a9e16fbdb121f453d356b37a1d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "e7dc5ea26648e7c931e4853216a613208ab09a9e16fbdb121f453d356b37a1d5"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6d29b4e5a387ddde2a928f0ed2c132ba718f40d87948c9094f379bdfe7a37fd2",
"value": 2000000,
"index": 73,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "75e9a41ef97b21a4d6f0ce5b348ae68cf7935dbf0d16b0d39cc800268067c8b4",
"outputIndex": 1,
"outputGlobalIndex": 44239363,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b188db683fdbacca5a356503878c7a4f017030569aed3dd1b665403f64e245c4",
"sigmaType": "Coll[SByte]",
"renderedValue": "b188db683fdbacca5a356503878c7a4f017030569aed3dd1b665403f64e245c4"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e203c53d37bc94e859ef7f565b5218a17409ea1f02de91edbc7bb676a2aaefc5046",
"sigmaType": "Coll[SByte]",
"renderedValue": "3c53d37bc94e859ef7f565b5218a17409ea1f02de91edbc7bb676a2aaefc5046"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "c28cef7df347c2ae96c44954c03d54da1eca78d90017a592870d194733d369f6",
"value": 2000000,
"index": 74,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "7ab33a83ea52323d8661191e9f64be01e8e2aed8faa9bb91a699cb553042efb0",
"outputIndex": 1,
"outputGlobalIndex": 44239368,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200aedbdc717d62dd354f6b59640f85a6f9b6ffababa1235b2d71738fd8517341e",
"sigmaType": "Coll[SByte]",
"renderedValue": "0aedbdc717d62dd354f6b59640f85a6f9b6ffababa1235b2d71738fd8517341e"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "bcef800cb08109007dbe1cba4a001c280e2dc2845c7bac1d7f22d0032d6bf5f9"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "f755cba9a62ecf8ceb8be46b3ad6753c618906304f2385680ae2afd185107e41",
"value": 2000000,
"index": 75,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "7b59caf0de59abfc5e51109eb2e99ac83b481336aefa7450504980e0e42b5347",
"outputIndex": 1,
"outputGlobalIndex": 44239373,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d326d49b29448eb3aacd1b8cf5ef0724bdacc4b9dd789e30b040f8aeab6741c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "d326d49b29448eb3aacd1b8cf5ef0724bdacc4b9dd789e30b040f8aeab6741c7"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2022a790609a54c77e37c8f001e9794e2de685c24063ea8ebc3c44c6e6526b5347",
"sigmaType": "Coll[SByte]",
"renderedValue": "22a790609a54c77e37c8f001e9794e2de685c24063ea8ebc3c44c6e6526b5347"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2d20516750659e9623fa81600ad31bdab7ca6cbd9b38ce2f52dc6e3d55e03cf9",
"value": 2000000,
"index": 76,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "8029d9831d443911324595c8d71c63d17863d5534108ba94f8a6dd24374d1514",
"outputIndex": 1,
"outputGlobalIndex": 44239378,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "dea05e9796b8e58d3a7ab92de7463d5a5d365171ffa1b581249e5c55f187f3dc"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "70b8e88c9dbc77c57454f00aa34deccbc044b9a4d3136c722d11e020fdfbfc9b"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 77,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "80ae3e35236ba55ba7ebfa985954a860127316a56a5349f497cd53108260197d",
"outputIndex": 1,
"outputGlobalIndex": 44239383,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8631eee440347aaa2e803cf150926fd49f2c628354ba0fc56fe95d79470a31f7"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 78,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "86846384407370a7564424eebbbc0dda44cfff276fada49d01e594c89ce7e06b",
"outputIndex": 1,
"outputGlobalIndex": 44239388,
"outputCreatedAt": 1405347,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20177d2ab87b520ce087a394ae20fcc6f221e24f747f664f6c30961288c951d05a",
"sigmaType": "Coll[SByte]",
"renderedValue": "177d2ab87b520ce087a394ae20fcc6f221e24f747f664f6c30961288c951d05a"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e207963f6261df495a64581693da1c2d37cec4ea381d56a02da41cb7a9111c496aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "7963f6261df495a64581693da1c2d37cec4ea381d56a02da41cb7a9111c496aa"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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{
"boxId": "6493e235ad04670ddee3d9e5714cc28643a7fe66c0d7907026a190ec46056995",
"value": 2000000,
"index": 79,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "884d4832a8e910d191af2ed21cb580ee189a675af3c9937e7322fb4536a016a3",
"outputIndex": 1,
"outputGlobalIndex": 44239393,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6b9a44a2b2d58f7049a288c911d955e8d70558ecb2705437f908beb783ddce00"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b97c3ad3b484a738a19850e0f8a256521460efb79805baa12c3142e6f2ecaf73"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 80,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "89d5af2a2d0c8a33987b1ce7cddfc1bbd5cabffd6579d0c33789322cdc476a2c",
"outputIndex": 1,
"outputGlobalIndex": 44239398,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7194c835bcc86f273b5e6ae41434949d81a2904ef00d0199eeb473340332128e"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "4c8796b160c89f97285fa860c69f0b2c87ec06f5c978f428c1e0ff17953356e5"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 81,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "8c0c093593a54d80b519a8b2acf75c9714b1eea385803ca293f557b56e8f771e",
"outputIndex": 1,
"outputGlobalIndex": 44239403,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20cc0718bb04b077042722255a5bc711370613aedd2983b214b83d562f630d00d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "cc0718bb04b077042722255a5bc711370613aedd2983b214b83d562f630d00d0"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20d62d9b5b3afd9f1eb3056bc5f5a00141de266cc126ca0261fb69a987f8d95dc4",
"sigmaType": "Coll[SByte]",
"renderedValue": "d62d9b5b3afd9f1eb3056bc5f5a00141de266cc126ca0261fb69a987f8d95dc4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e93d0d52e234295bc02874d2bd78eda77df79b1806255a9395c58b7c942ad141",
"value": 2000000,
"index": 82,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "96e8c90d03872dad2cd9f25d1f0b212a399d446673bac41ab6fab196fc3ee304",
"outputIndex": 1,
"outputGlobalIndex": 44239408,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "2ede0d2546c1c3f717ecf003131888c4a82a18283ed6eba82105f6879dbcc8d5"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "2410e9eef278ce9a4a85ca203031637020a99f0c4aa537b4753a53e6f5d9993f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "959ec9fb110f229b56528f2a4c852ed17b234a5dd452d180b4b6454b58d37591",
"value": 2000000,
"index": 83,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "9a469b00d8e63ad73c234de9f5e1c33e488ef163a12644a52997573dc1f26017",
"outputIndex": 1,
"outputGlobalIndex": 44239413,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "94683fa395102a3b9f5df98182d49d3b55c3e7219b0f9ed2f055dbb575b229f3"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "83b6322f919ba05c2581c44cc6cc945a9b34855a4956c3650f79d2503cc372b4",
"value": 2000000,
"index": 84,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "9de67c65b299886f7dc2d4c77a09e1fcf246c448792c12a8981a671aea5cef16",
"outputIndex": 1,
"outputGlobalIndex": 44239418,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203497f5106ba457314a058d4ae85c7b99de8c5de7d3c0801c68a72cce274a2671",
"sigmaType": "Coll[SByte]",
"renderedValue": "3497f5106ba457314a058d4ae85c7b99de8c5de7d3c0801c68a72cce274a2671"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2094cb14de7f05113363e44285a662134d6822f871133e8362b972cec1ae191bca",
"sigmaType": "Coll[SByte]",
"renderedValue": "94cb14de7f05113363e44285a662134d6822f871133e8362b972cec1ae191bca"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "24b3a01820ccce171c197daf1e86c8c3b0891518a46c8fa7ebb2edbbaa0aa296",
"value": 2000000,
"index": 85,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "9ec20d32e79c41fdedb4d720d983ce495ccde11a4594f07e9a7dc85f76eb6d64",
"outputIndex": 1,
"outputGlobalIndex": 44239423,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9fd5177131205e443ba2f60bcbc6f23954e5c75fa58038fd6547394fc7f951cc"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e20e8e4615c189c50420d3b2ed840d6c7385003d79527912783f9413a91d0442de7",
"sigmaType": "Coll[SByte]",
"renderedValue": "e8e4615c189c50420d3b2ed840d6c7385003d79527912783f9413a91d0442de7"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "bc810aeed6637a1fcccae3289efa99dfd754002a9fe000e0312a55be2197d320",
"value": 2000000,
"index": 86,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "9f3f69969e019915f73deeca4541168a05ca7829f5d4d05ae6ac857ebf3c6fa8",
"outputIndex": 1,
"outputGlobalIndex": 44239428,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7d2f5dd0dce52c5e42b935cb986095bdfac1c6102018f4c715d830e736d96876"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "70f70d9d475ae387af8ce6bc599aaa84de7aa7e5f3c2845ae52525e3a8bd8d82"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "301ab3b18f31cca3d55478ab4368d1fd452c10f6f4beb82d203d088d74c2dba1",
"value": 2000000,
"index": 87,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "a0476c3b67d03f7dff1a2313a239bdf67eda6a829dcb42985f7fb71466bcd230",
"outputIndex": 1,
"outputGlobalIndex": 44239433,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202ab8f5990a72893dc39fe796e0da8373827b397b1c043a0424d7426c28341a61",
"sigmaType": "Coll[SByte]",
"renderedValue": "2ab8f5990a72893dc39fe796e0da8373827b397b1c043a0424d7426c28341a61"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e203172b1145892eef08d531deb42d58c945a189bb20933dc4fc136784608307bd9",
"sigmaType": "Coll[SByte]",
"renderedValue": "3172b1145892eef08d531deb42d58c945a189bb20933dc4fc136784608307bd9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "7b0f9f98d1968e5b57441adaa4364ddf28b80328820fd90e35838aa8ffba4ec9",
"value": 2000000,
"index": 88,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "a5eede9ced058ca6f4bdf71670076d97e24ca524fb0d8b45a33e6248052bb4ce",
"outputIndex": 1,
"outputGlobalIndex": 44239438,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206a572ba3399722fc5020dfe1443990135cd044893c9e7a72056d613232fa61e8",
"sigmaType": "Coll[SByte]",
"renderedValue": "6a572ba3399722fc5020dfe1443990135cd044893c9e7a72056d613232fa61e8"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20edf2fb67bc1b73551f83098bbc8b7c8fe5b62753845a8980d736f1bf16c60f22",
"sigmaType": "Coll[SByte]",
"renderedValue": "edf2fb67bc1b73551f83098bbc8b7c8fe5b62753845a8980d736f1bf16c60f22"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "4b6d36d70cf8890a75013f75380c5eb341a462c6761c32940d19c46197d6170c",
"value": 2000000,
"index": 89,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "a96cb565b760b29ec4415fa16a235012f7f33e4ecf4582198522fb5d206bcd83",
"outputIndex": 1,
"outputGlobalIndex": 44239443,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308",
"sigmaType": "Coll[SByte]",
"renderedValue": "f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2060aa71cd2270b5537ab882bf98a1f274f4332198961a7413c62b23206d368d33",
"sigmaType": "Coll[SByte]",
"renderedValue": "60aa71cd2270b5537ab882bf98a1f274f4332198961a7413c62b23206d368d33"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "edffe3058d56c4f368ac462031e437a7b224c73f0669f53894af5d9808c02a9b",
"value": 2000000,
"index": 90,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "a9c601fbd8bbec7a236d09b133dc3d869b529f1ffbe6404e7756bacd9a67dbc5",
"outputIndex": 1,
"outputGlobalIndex": 44239448,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2093d73a59f111c37a6e9853fb85ba075264f330dc3b416d2778b7939e3bb6591e",
"sigmaType": "Coll[SByte]",
"renderedValue": "93d73a59f111c37a6e9853fb85ba075264f330dc3b416d2778b7939e3bb6591e"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e207e5a68df9359f8a7c12c7ae94b2c41a3c0e6962d3171818e95507bec9e277cdd",
"sigmaType": "Coll[SByte]",
"renderedValue": "7e5a68df9359f8a7c12c7ae94b2c41a3c0e6962d3171818e95507bec9e277cdd"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "69d3db140e7fa3cb2fb37048828e1bb1e0f0eee85e30cf351c4c110628eb163d",
"value": 2000000,
"index": 91,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "aefc9252e55cdf89eaa1cb7e5d6f45631fbea52a88579fb0b5cc6ded433fe038",
"outputIndex": 1,
"outputGlobalIndex": 44239453,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698",
"sigmaType": "Coll[SByte]",
"renderedValue": "ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20df68e7decd90d3145a186b62782769f3b0a96380a57689c7240f944fa84fd37a",
"sigmaType": "Coll[SByte]",
"renderedValue": "df68e7decd90d3145a186b62782769f3b0a96380a57689c7240f944fa84fd37a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "c3ada9e2a579a5a06b4c7419baf18bb496ea5307b13542adca15dcb79431cb1a",
"value": 2000000,
"index": 92,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "b793be106f919d0b9e769fd85d2f3d4e01656416420184ae3c1046246a750a30",
"outputIndex": 1,
"outputGlobalIndex": 44239458,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2050380024330dbf7001125ff8d8c3df6ffecf302f61eb96e71d1698718f8d5f8f",
"sigmaType": "Coll[SByte]",
"renderedValue": "50380024330dbf7001125ff8d8c3df6ffecf302f61eb96e71d1698718f8d5f8f"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "08ef1ca4b0fa43c81af52a5528f0cd48b4fc5331e770e59a920393c68c94f651"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "d859ef07afffa60c86bac8b6023525e68e6cc66dc47ad4441083be2d450c3397",
"value": 2000000,
"index": 93,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "b99a8612e4068de2ef92e77e429c6b8874346f057ade62ae303bfe64cf932efc",
"outputIndex": 1,
"outputGlobalIndex": 44239463,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207fdb6e568e0adf674fa20a687c4e9147905bb6ad6f63c3777ccd227b6201e84b",
"sigmaType": "Coll[SByte]",
"renderedValue": "7fdb6e568e0adf674fa20a687c4e9147905bb6ad6f63c3777ccd227b6201e84b"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20bd3a9a316a81c56901e7d8757eb393dd13e49384fa2d893fae90acda84e09b5e",
"sigmaType": "Coll[SByte]",
"renderedValue": "bd3a9a316a81c56901e7d8757eb393dd13e49384fa2d893fae90acda84e09b5e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "76e39766e33ead6756bc48abe9546c803c775cc54e7d0aa175f3b1ed4679dfc3",
"value": 2000000,
"index": 94,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "c13992a5f7cb80207012339ed196069c808fc3921d63b56f21d1cd84582235d1",
"outputIndex": 1,
"outputGlobalIndex": 44239468,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "99eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5931c7b6d7ffd1aa0a7b2609ef983fac7b82749144db21d1dc1483b1154b3572"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 95,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "c71d22c850baa7af1ef1c9a282d5ede09a27a2cff2d98f8746c3be06c09c0950",
"outputIndex": 1,
"outputGlobalIndex": 44239473,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"sigmaType": "Coll[SByte]",
"renderedValue": "79c1d48e99fa27ce113618f815e84f090250678f11f91895447a8607e8926849"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 96,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "c89a6131fe6e710ffd5c81af16e77bf5b466bf3c4e6c11f97226c413f365dcca",
"outputIndex": 1,
"outputGlobalIndex": 44239478,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20047f4bd7bbad0ee6e4dc2d6577fe878cb7d2bf780691a83b3f9dac406eb8588d",
"sigmaType": "Coll[SByte]",
"renderedValue": "047f4bd7bbad0ee6e4dc2d6577fe878cb7d2bf780691a83b3f9dac406eb8588d"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e203cc0f865f0b1e3e23ee82819bd0418dca0f1f9ee688d451e84506378a3437c54",
"sigmaType": "Coll[SByte]",
"renderedValue": "3cc0f865f0b1e3e23ee82819bd0418dca0f1f9ee688d451e84506378a3437c54"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "958a89385b11105e670cafe543f51a5674c127eada79a424be39e987d99944c1",
"value": 2000000,
"index": 97,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "c9de27de9282a501b19f7feb0f00f66ed747cc9f20f10021729400764027c865",
"outputIndex": 1,
"outputGlobalIndex": 44239483,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "46c266a044e977c0ab839f301dca45f4f35c3aba25965713523ce1f6df72b193"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b2c1b6780b22cfcba2a950a0d5f2d8332e6cdf0de05c9192472bfe5322030dfb"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 98,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "ccf50f5352ebe6658e4d711178580ad79a14ef7ac7a49c59a87fdf67b60c6c61",
"outputIndex": 1,
"outputGlobalIndex": 44239488,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "451e6a391af3b38336460dfab25c283697256a195638eeb9627b3b687f42009a"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "2d6158e32663cc1a49d08b0de21ac19cd224a5d07679ed333c05fc794e4e53a0"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 99,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "cedf11bf531a41e7258af10f35e271ed5c66f434f7f8aa44b117dcd90bcae07e",
"outputIndex": 1,
"outputGlobalIndex": 44239493,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202e044c831f37e35eb02d07a35879a58b35a5c890272e25f0db77fe0fb9e26277",
"sigmaType": "Coll[SByte]",
"renderedValue": "2e044c831f37e35eb02d07a35879a58b35a5c890272e25f0db77fe0fb9e26277"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20dec5eba8f86143ad8003e105aef2cd503d2942b73aa071d2614f7c8580373c4c",
"sigmaType": "Coll[SByte]",
"renderedValue": "dec5eba8f86143ad8003e105aef2cd503d2942b73aa071d2614f7c8580373c4c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "5a64cfd934987ec63154b6c38f74b0b67c26bbc47187c08cf7da07e1f6ef2b4b",
"value": 2000000,
"index": 100,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "cf21411c8d2513d291227ffbfc60c0d51d5f34f0743198be2d2374cedd830462",
"outputIndex": 1,
"outputGlobalIndex": 44239498,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20bb5f676dea40d456552f6cbdb963e0426387c7c0c64c7512b5d35418f3759d0d",
"sigmaType": "Coll[SByte]",
"renderedValue": "bb5f676dea40d456552f6cbdb963e0426387c7c0c64c7512b5d35418f3759d0d"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20b61c49eb077aef9c4553add1d24b18b6e9896a0f7d559654873aa6909f7555f4",
"sigmaType": "Coll[SByte]",
"renderedValue": "b61c49eb077aef9c4553add1d24b18b6e9896a0f7d559654873aa6909f7555f4"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 101,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "d0035299e9d0067cf903d0fcf668a9ef00cb72b420bc7874e29cf09cc124e5d5",
"outputIndex": 1,
"outputGlobalIndex": 44239503,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2029beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "29beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "653ae4f32df94a97993d9ab0c6efc4a272dc9f72ff15f3849dab5674f43f4b7c"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 102,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "d3338ea75cac8b5bbfad1b8b343f91889747222cf55e1ef90603fd72b0841eb2",
"outputIndex": 1,
"outputGlobalIndex": 44239508,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20793848c21ce3e6a7bdfa8613f66f9f99879304a3a4b7fc233228fa959c113fd8",
"sigmaType": "Coll[SByte]",
"renderedValue": "793848c21ce3e6a7bdfa8613f66f9f99879304a3a4b7fc233228fa959c113fd8"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2019419dc516755c56f31a6bd5053e44ddb3789e0fd59d2327ea86ded1c4c029be",
"sigmaType": "Coll[SByte]",
"renderedValue": "19419dc516755c56f31a6bd5053e44ddb3789e0fd59d2327ea86ded1c4c029be"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "8f54630c1647c095853d7c60fa15dcd4ad64abe9783362ad2d00a9673b6f642c",
"value": 2000000,
"index": 103,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "d4db4e92c755c15cf2d1300764dc2bcf5da6f77eb818a456922bac1bdcf0f768",
"outputIndex": 1,
"outputGlobalIndex": 44239513,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d",
"sigmaType": "Coll[SByte]",
"renderedValue": "f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
"serializedValue": "0e208d30ec691ec235cdea8e17effdc46fca66f3a663deae10612be975b89601e62c",
"sigmaType": "Coll[SByte]",
"renderedValue": "8d30ec691ec235cdea8e17effdc46fca66f3a663deae10612be975b89601e62c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "1268d57dc9772e8547371b9d6640b4cc324d21e18e16422b471c4a758431d527",
"value": 2000000,
"index": 104,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "de3598eb5634afcd3ff79bee947aecbc7c0d8201ba6f51f211f37f8cdb10d716",
"outputIndex": 1,
"outputGlobalIndex": 44239518,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e208ff3e3b368707fba5f6373db7423ab3486b5317bb6d703de4561a4e25ed6c3e6",
"sigmaType": "Coll[SByte]",
"renderedValue": "8ff3e3b368707fba5f6373db7423ab3486b5317bb6d703de4561a4e25ed6c3e6"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "03bbbade789926777e0b3b23ea17db25a9c074ae4cef76f4d0ba1d85c9a9d51f"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 105,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "e30a73032ae2eb7f0cf78313a1ab27d4a7dddc811e9e04fa5e34b30f8a601feb",
"outputIndex": 1,
"outputGlobalIndex": 44239523,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f3996e1ea0db8fb08ad54adc396da83dd158c571d60f8241f480afbc2a606617",
"sigmaType": "Coll[SByte]",
"renderedValue": "f3996e1ea0db8fb08ad54adc396da83dd158c571d60f8241f480afbc2a606617"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2014ec359b245615f7650cb7b5c3fe878403aa8ff717d67ce85586d462e7fb5c90",
"sigmaType": "Coll[SByte]",
"renderedValue": "14ec359b245615f7650cb7b5c3fe878403aa8ff717d67ce85586d462e7fb5c90"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "04c0cabab7cd14ff84aefd5b95657b40a27a2e56dd79d5a83e0393734109e972",
"value": 2000000,
"index": 106,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "e884f174f7557721a70ae8cc53e6663b1e54d4abd076279f62193fd605e7b4c3",
"outputIndex": 1,
"outputGlobalIndex": 44239528,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2037b104e8763eb64be8a1775a5ee95135ecc1f5e0941a02031f1b9f2c2c0ed0e4",
"sigmaType": "Coll[SByte]",
"renderedValue": "37b104e8763eb64be8a1775a5ee95135ecc1f5e0941a02031f1b9f2c2c0ed0e4"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20f3aa4b7381e07fbecdc771d5e3e63b2653cd60fb71f4ee7e68c7554e44255e45",
"sigmaType": "Coll[SByte]",
"renderedValue": "f3aa4b7381e07fbecdc771d5e3e63b2653cd60fb71f4ee7e68c7554e44255e45"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "d03b7098b95b9023de51b8ff897c82e33a25f399eb477accdb3a4beac471c244",
"value": 2000000,
"index": 107,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "f076b74d16ee7095053c65b83f179ac01cd89d95ee9028a276690019268565f9",
"outputIndex": 1,
"outputGlobalIndex": 44239533,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2009a22d2ec41eda22d4eb20e2591830b2fe3c9a53cb8df64a9da93e6699ffb306",
"sigmaType": "Coll[SByte]",
"renderedValue": "09a22d2ec41eda22d4eb20e2591830b2fe3c9a53cb8df64a9da93e6699ffb306"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6da41e3ae2a49917382131e8e55aa954d5cd2b6233cf09abb66540a2db274fbf"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "8e1e66480b9530080b6f9dc813a9793f56ff29d90dd549ab85c7720ff6cf34e7",
"value": 2000000,
"index": 108,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "f146acda63712ac703b4ee5ce6e67c9d5ea0c046e6f37f6cf6afee20cf24d6c4",
"outputIndex": 1,
"outputGlobalIndex": 44239538,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2092a7c171364ecec3926817b320af35a4830041fb3d9e71dbc38fbf5b177ab22f",
"sigmaType": "Coll[SByte]",
"renderedValue": "92a7c171364ecec3926817b320af35a4830041fb3d9e71dbc38fbf5b177ab22f"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20cd48014e20cb06d0677527555f4ce703f19f7d9840692b5d529c6b2ae6b2c44d",
"sigmaType": "Coll[SByte]",
"renderedValue": "cd48014e20cb06d0677527555f4ce703f19f7d9840692b5d529c6b2ae6b2c44d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "a1e53c8c6074ad0ff6a04e66ea77c8e17af061468090bec81681e64d6fb2b10c",
"value": 2000000,
"index": 109,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "f14be63d6f9c513aec938f38a20c2e7be24fcaf8e29afc74c030ee4cddf05e3b",
"outputIndex": 1,
"outputGlobalIndex": 44239543,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206e3897f1a1c06dd2eeebd4ec9287dc0abd119e7f0a03c7938c181ba21fcddc96",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e3897f1a1c06dd2eeebd4ec9287dc0abd119e7f0a03c7938c181ba21fcddc96"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e2080ca5d039121a463ed387404d5755c74fe0568692a0c2e989c194eeac16d2f0c",
"sigmaType": "Coll[SByte]",
"renderedValue": "80ca5d039121a463ed387404d5755c74fe0568692a0c2e989c194eeac16d2f0c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "9326eca0c64d10714767bfda810cd549688f3b9028098f52dda62a84e3782d3e",
"value": 2000000,
"index": 110,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "fcf59d708cd3aae7a0efa2ba8b1c0156fc1fe440368135c0552a97d82a47779c",
"outputIndex": 1,
"outputGlobalIndex": 44239548,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e208be41df9ef870f6dda3c200b2d4ee25cba722257a9e36aea0033a6687e3972bb",
"sigmaType": "Coll[SByte]",
"renderedValue": "8be41df9ef870f6dda3c200b2d4ee25cba722257a9e36aea0033a6687e3972bb"
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"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20c9682937445a1ef4150ebdd43954902f857025333cc166e5a05d2f94adc324b6",
"sigmaType": "Coll[SByte]",
"renderedValue": "c9682937445a1ef4150ebdd43954902f857025333cc166e5a05d2f94adc324b6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "167e232ea2711c9073f335fca16b9834ff0a00d62d4d58829c205e804c816b07",
"value": 2000000,
"index": 111,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "fe65f7ba9215072729b0d8132247000a084ddfb035f0ce02315ecf7742d117e9",
"outputIndex": 1,
"outputGlobalIndex": 44239553,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205252ecb1f1f61787cce1dc38b5bc1b71f55fa8a606eca25b9b3f596932cf4ef6",
"sigmaType": "Coll[SByte]",
"renderedValue": "5252ecb1f1f61787cce1dc38b5bc1b71f55fa8a606eca25b9b3f596932cf4ef6"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20486c6201de4318bb54dc53a5b8cd20b5d1b225a2e0985eea166eb2522d7d99c6",
"sigmaType": "Coll[SByte]",
"renderedValue": "486c6201de4318bb54dc53a5b8cd20b5d1b225a2e0985eea166eb2522d7d99c6"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "847036b7aea2121338d1a6fa1bdfcf747b4ad216486a24854257c22395ccbb13",
"value": 2000000,
"index": 112,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "feef2582db6e9aaa72c2400a7bc1572d1423758621d11b7cbb956b3396522e44",
"outputIndex": 1,
"outputGlobalIndex": 44239558,
"outputCreatedAt": 1405346,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205e9116ec8a5fe109fcb28d46fc9b3f5e6aa8a37d88cdbf0ba1d6f7f0c974b0f7",
"sigmaType": "Coll[SByte]",
"renderedValue": "5e9116ec8a5fe109fcb28d46fc9b3f5e6aa8a37d88cdbf0ba1d6f7f0c974b0f7"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20e59b1ccbb7421b311fb4e9a69695774c92dea1bfb3c6168bc7161e28cba1b05c",
"sigmaType": "Coll[SByte]",
"renderedValue": "e59b1ccbb7421b311fb4e9a69695774c92dea1bfb3c6168bc7161e28cba1b05c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "71b46f1ea4b64422eaef819c64f20912c1fb9825f4fdde754d08d9eb8a30f022",
"value": 2000000,
"index": 113,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "9ca8c244db10ec028e1fbb7f7ac5f8dca28fb1e786b32b5f5cfa8a3139a65da1",
"outputIndex": 1,
"outputGlobalIndex": 44239563,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e204ccf99baa9ef1f7a72a9ff58e4da6ccd5a9b839c1cd152a3e2ba0bc719457e62",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ccf99baa9ef1f7a72a9ff58e4da6ccd5a9b839c1cd152a3e2ba0bc719457e62"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ce0507370ec0cd72969c6610b89c5e810e5e1e553c022cd19237b9c0ff1c813f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "57807b974f6d312582663a75ba7275a3c05d4df98767ac141b73df28cc0c39c4",
"value": 2000000,
"index": 114,
"spendingProof": null,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "b5cec1fbe1e8fee5f00a4cbd986db107384fdcbaf0fbe996d9df4f5e3c63157e",
"outputIndex": 1,
"outputGlobalIndex": 44239568,
"outputCreatedAt": 1405347,
"outputSettledAt": 1405349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20dfdbb50d5860af988cee979add06c9420fa8c3453f950a644f29afd58b0448dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "dfdbb50d5860af988cee979add06c9420fa8c3453f950a644f29afd58b0448dd"
},
"R5": {
"serializedValue": "0e20f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6198c6cdbc351018f281e7ad7f7d5e8c76bc8f8ae9b95e25983871183a6614b"
},
"R6": {
"serializedValue": "0e20fcec9858b1a4961bb0ebcd8d0108ef3a7e38749b042d32048b4df27499ab868d",
"sigmaType": "Coll[SByte]",
"renderedValue": "fcec9858b1a4961bb0ebcd8d0108ef3a7e38749b042d32048b4df27499ab868d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "212c60c273c1132bd7c0074a9328dc6bc01c9aa74b9fde770fabcf927cea8aef",
"value": 42000000,
"index": 115,
"spendingProof": "80bb6107d076fa96e8a0ce475db3e1c359c9827f44e5a44468712427a13d66208b0038d3d4d1aa316e249fd57164a9196c4a8ae7f6d6637a",
"outputBlockId": "6107e797e41109de80c4c9986316ade3397a1901e9e5fbda42a2ca30826f4c04",
"outputTransactionId": "b06e549a9e27271cea371ce88b9391da65af8ee9e64a7ee1e26a4c73f12beb10",
"outputIndex": 2,
"outputGlobalIndex": 43617596,
"outputCreatedAt": 1388034,
"outputSettledAt": 1388036,
"ergoTree": "0008cd029064f9e0b3b63690a88fd5b89f0869f18b1feec15928e181d2b49e16a58a9d50",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(9064f9,4e71bb,...)))}",
"address": "9fcespxXgkxCavMD3m7uSVHa7k2tfxua6xmv4YiLbxbs8e1orpa",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "a0f81c737b38ec451dc072369bc74609896b3bd245762140f44edbd5a934f90d",
"value": 1100000,
"index": 0,
"outputBlockId": "9cd9da9a7bebc91af8af522b342397f6f0cb88719817b60aa0cb53a9758daccf",
"outputTransactionId": "a0029995fad90f6b31ac46d0ad4e823a8349c16a413f885c829c74a840107a3b",
"outputIndex": 1,
"ergoTree": "100604000400040004000e2055bf993b4376ba132264d084f06fe033321ab43c68db1435a0e7e0bf77ddb7350402d803d601b2db6501fe730000d602b2db6308b2a5730100730200d603b2db6308a7730300ea02d196830301aedb63087201d901044d0e938c7204017304938c7202018c720301938c7202028c72030298b2e4c672010510730500ade4c67201041ad901040ecdee7204",
"address": "prufxZid3SJMyUVhAPFAF4uLyCZbEMWCMXRSyuMEvDUHZf81JcGcmu1EW1U9hUuJerWer5vmjhiJMmjbCqDwPMKRy169SPaLTxDp5tZ2rCrKjiv7xVAsnmphxSNBpj6qqB8fs1rWJGn9dN7t74qvx6oVHZny8KNMrqfEDjcWRv7wP21sZFP4rie4YhWJs8Z6swQ3DA28B5bzMZkMqfR7",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1106809bee027802c8018080babbc82e808ece1c",
"sigmaType": "Coll[SLong]",
"renderedValue": "[3000000,60,1,100,800000000000,30000000]"
}
}
},
{
"boxId": "9fba6d1ff4c5156d2a83f310c3674873b5481cc4f53c2407526189eb4efdcab4",
"value": 2000000,
"index": 1,
"outputBlockId": "59f4968f26500ee1c2723742f1155a8cd64bfc890dcf1ba267e11722cd0e2a7e",
"outputTransactionId": "281a8a5844643072e5448aad2cf65f0d4ab4f9c515440915d688028a08bf73f7",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "05f801",
"sigmaType": "SLong",
"renderedValue": "124"
}
}
}
],
"outputs": [
{
"boxId": "45524103f50d7a1ecada00f13b31690bf01bba262b415961a9da5fd2baee4b90",
"transactionId": "f90d50466096e742df5dc70a0b0ab6f0912a4e1c47645b3d36ca854f4dc5a1ce",
"blockId": "0475f45f2367fdd15a34302bd7a79ea6927ab2084bdb0e9c51617d3675a66cdc",
"value": 229010000,
"index": 0,
"globalIndex": 44239673,
"creationHeight": 1405349,
"settlementHeight": 1405351,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: Coll(61,77,106,-65,36,-120,39,27,1,109,101,-87,-13,74,9,45,48,68,77,113,-89,14,-91,30,1,-42,-90,-15,-73,98,118,115)\n10: 1\n11: 0\n12: Coll(82,-43,103,29,47,-108,82,-33,-82,-22,-125,-66,-113,-62,-1,0,-115,58,113,109,-76,-77,-112,-34,-78,119,5,-41,60,96,-108,-22)\n13: 21600\n14: Coll(-98,-6,68,-25,-102,33,112,49,-105,-94,-40,-120,-4,32,76,-10,67,87,17,-51,-17,-49,-33,91,-53,-113,-71,41,-27,9,27,-70)",
"ergoTreeScript": "{\n val i1 = SELF.R7[Int].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == SELF.tokens(placeholder[Int](2))._1)\n }).slice(placeholder[Int](3), i1)\n val coll3 = OUTPUTS(placeholder[Int](4)).propositionBytes\n val coll4 = blake2b256(coll3)\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll2.size == i1, SELF.R4[Coll[Byte]].get == blake2b256(\n coll2.map({(box5: Box) => box5.R4[Coll[Byte]].get }).fold(Coll[Byte](), {(tuple5: (Coll[Byte], Coll[Byte])) => tuple5._1.append(tuple5._2) })\n ), coll2.forall(\n {(box5: Box) =>\n ((box5.propositionBytes == coll3) && (box5.tokens(placeholder[Int](5))._1 == SELF.tokens(placeholder[Int](6))._1)) && (\n box5.tokens(placeholder[Int](7))._2 == SELF.tokens(placeholder[Int](8))._2 / i1.toLong\n )\n }\n ), if (coll4 == placeholder[Coll[Byte]](9)) {\n allOf(\n Coll[Boolean](\n INPUTS(placeholder[Int](10)).tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), HEIGHT - placeholder[Int](13) >= SELF.creationInfo._1\n )\n )\n } else {\n allOf(\n Coll[Boolean](INPUTS.exists({(box5: Box) => blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](14) }), coll4 == SELF.R6[Coll[Byte]].get)\n )\n }\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 345000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2076136927e0ecf6445d1a6b97537f9c01ae2fe04287dc3c40d2f39c81d26801bf",
"sigmaType": "Coll[SByte]",
"renderedValue": "76136927e0ecf6445d1a6b97537f9c01ae2fe04287dc3c40d2f39c81d26801bf"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[31663661353731366337326165356335393466373631336263306430653130353664363934353339306661646662613265393535363236346464643837613336,6572676f,63617264616e6f,3967644678616a676d52323166387076464e464d626d456a556b586e53656954365958774574536b386b63554e51454a6a6d59,61646472317178306d677433656d337865337635637a6c72387467746d6135736c6d776a703876303864303478636e756b6d776e377864756e63386c643274637634787872336d78366a36396c6878676633776a77393461373730686c747a6d71393477397578,000000000191f612,0000000000a913d8,00000000003d0900,65303233633566333832623665393666626438373866363831316161633733333435343839303332313537616435616666623834616566643439353663323937,616461,66333965376637663763383237333436656630336364363463663363663830393061383564653566646636376633326237303537623732373831663830633237,0000000000157197]"
},
"R6": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
},
"R7": {
"serializedValue": "04e601",
"sigmaType": "SInt",
"renderedValue": "115"
}
},
"spentTransactionId": "9bb5ef2524472819bef53c99185b715480ab9ff3de4a50d5ba47fb0150d7b052",
"mainChain": true
},
{
"boxId": "fc6df8219f9eb5c51d025bf93a94fa8107247b7d657423ad0a6927db75eb35c8",
"transactionId": "f90d50466096e742df5dc70a0b0ab6f0912a4e1c47645b3d36ca854f4dc5a1ce",
"blockId": "0475f45f2367fdd15a34302bd7a79ea6927ab2084bdb0e9c51617d3675a66cdc",
"value": 40000000,
"index": 1,
"globalIndex": 44239674,
"creationHeight": 1405349,
"settlementHeight": 1405351,
"ergoTree": "0008cd029064f9e0b3b63690a88fd5b89f0869f18b1feec15928e181d2b49e16a58a9d50",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(9064f9,4e71bb,...)))}",
"address": "9fcespxXgkxCavMD3m7uSVHa7k2tfxua6xmv4YiLbxbs8e1orpa",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "32c9b74493ea10b2de56db6fddb9c56a8f34b6e94102cdfc879b98c81eb7b1a9",
"mainChain": true
},
{
"boxId": "92d828e8fff2136e5e45fd855011f48129ec5cfc7ac6cf5cc89dc7f2f52f14c8",
"transactionId": "f90d50466096e742df5dc70a0b0ab6f0912a4e1c47645b3d36ca854f4dc5a1ce",
"blockId": "0475f45f2367fdd15a34302bd7a79ea6927ab2084bdb0e9c51617d3675a66cdc",
"value": 2000000,
"index": 2,
"globalIndex": 44239675,
"creationHeight": 1405349,
"settlementHeight": 1405351,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "a10e67ad154c855e303beee6f855e0ff552b62705b63a5d0e443b903d3245aac",
"mainChain": true
}
],
"size": 5125,
"isUnconfirmed": false
}