Transaction
ID: d0da18e4bf...76da
Inputs (94)
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:
0.00101 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:
2.86 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.18501 ERG
Tokens:
279,000
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.86 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00205 ERG
Transaction Details
Confirmations: 139,666
Total coins transferred: 3.05 ERG
Fees: 0.00205 ERG
Fees per byte: 0.000000474 ERG
Raw Transaction Data
{
"id": "d0da18e4bf7921e04c278d09a2e4956424fa99ff7a9f83dd5a05b4a9a92f76da",
"blockId": "370a82feed29609c0db5c0cec3b0d80b3127352319a9246d05905156e0995600",
"inclusionHeight": 1623413,
"timestamp": 1759181834538,
"index": 1,
"globalIndex": 9542696,
"numConfirmations": 139666,
"inputs": [
{
"boxId": "802c85f860b00ccea4086b749a793cfb9afd7b3564b84e1bc9e6f75b3337bc7c",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "2f57b70a470dc38ed620ce40d7082c715ba2c6340f0509d47c5713ffcd7f1807",
"outputTransactionId": "e36f6e920bc01b83e5c3b066e7ff2192a5eff78ab2091ae3a0dd529309054616",
"outputIndex": 1,
"outputGlobalIndex": 50533745,
"outputCreatedAt": 1623398,
"outputSettledAt": 1623399,
"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": "0e2029beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "29beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e204d7bcc5698808bfa3883e770f31e4e8efe06213d6449c6da4f1b3c252e915d2c",
"sigmaType": "Coll[SByte]",
"renderedValue": "4d7bcc5698808bfa3883e770f31e4e8efe06213d6449c6da4f1b3c252e915d2c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "9c83cc8916752410fec20dad2eec831ec9d7e8917205baf1c03bccc2d9c09013",
"outputTransactionId": "e41e43ab680fb4caf5b9d4a94294f61d3a3adc5dd0a5b2b2c62fd7703af941d5",
"outputIndex": 1,
"outputGlobalIndex": 50533814,
"outputCreatedAt": 1623402,
"outputSettledAt": 1623403,
"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": {
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"serializedValue": "0e206576e8c63376413c7590e342bf637a9cfb8c25eecf73edf78ed96d2668e0e557",
"sigmaType": "Coll[SByte]",
"renderedValue": "6576e8c63376413c7590e342bf637a9cfb8c25eecf73edf78ed96d2668e0e557"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e20d32fc30554631acea8f5859b08690f00818a23d104d6ddea7ae4701dbe98bc59",
"sigmaType": "Coll[SByte]",
"renderedValue": "d32fc30554631acea8f5859b08690f00818a23d104d6ddea7ae4701dbe98bc59"
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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": 2,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "75994a81ff46c936dbb072d5ecae05c1d1741fe40fc0e7e382141ade00c45bbc",
"outputIndex": 1,
"outputGlobalIndex": 50533877,
"outputCreatedAt": 1623405,
"outputSettledAt": 1623407,
"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": "0e20a841b23663f1548f4489e46978c6ee3ee6df43af85c2d907923b908e423b508d",
"sigmaType": "Coll[SByte]",
"renderedValue": "a841b23663f1548f4489e46978c6ee3ee6df43af85c2d907923b908e423b508d"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e203b6909535cae36feefd912fc001de9a6f201555f5195c0c7c1df00391a01d384",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b6909535cae36feefd912fc001de9a6f201555f5195c0c7c1df00391a01d384"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "4f3593fa731e92853802d8bf4c370154c8a9cbe2cd8d8642912cbbda00711b8a",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "bd722d7e466a5c1ac05326ccfee17748ff0b5136e45ba6f791841d1324c4b1b2",
"outputIndex": 1,
"outputGlobalIndex": 50533882,
"outputCreatedAt": 1623405,
"outputSettledAt": 1623407,
"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": "0e20cb2f19da29f4bee653709192e4912a0dee7cfa4d01a0cfe951212802f1d12ab4",
"sigmaType": "Coll[SByte]",
"renderedValue": "cb2f19da29f4bee653709192e4912a0dee7cfa4d01a0cfe951212802f1d12ab4"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e201f2ba77f224848895ad1991dfeeb6e7abaa5248fbbbf5b2cf69f208f322b0cb5",
"sigmaType": "Coll[SByte]",
"renderedValue": "1f2ba77f224848895ad1991dfeeb6e7abaa5248fbbbf5b2cf69f208f322b0cb5"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "0e4b079a625279e95fb2a43e6f5b063953e250dc172f5659659507a594e288fd",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "d5125e4ff49ee0bbf46c2b906abb13d588870c58ba5d57248b6f1d4b788f41f8",
"outputIndex": 1,
"outputGlobalIndex": 50533887,
"outputCreatedAt": 1623405,
"outputSettledAt": 1623407,
"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": "0e20b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20de80f01457a42a24c326dc2d94dc3768cf49382354de706c41899a6aa805acc2",
"sigmaType": "Coll[SByte]",
"renderedValue": "de80f01457a42a24c326dc2d94dc3768cf49382354de706c41899a6aa805acc2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3f50d3bf84d9f8e5f66c6b305da331d1f491cfd85f88971a6b29f9fcfd7acd16",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "444ad0d0b25b53d7dae728cd5723a4e8a3d6abf7dca1bcd5a38fb5c1a1e8cf94",
"outputIndex": 1,
"outputGlobalIndex": 50533892,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623407,
"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": "0e205bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c",
"sigmaType": "Coll[SByte]",
"renderedValue": "5bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20b1233438943549e2c1531d065ae82fbc5d0ccaefede9be48c4be9f145639c419",
"sigmaType": "Coll[SByte]",
"renderedValue": "b1233438943549e2c1531d065ae82fbc5d0ccaefede9be48c4be9f145639c419"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "007a4129b0664c3d6669d9f1acabbc95c56ed6f60f59ece89100e480bf65a94d",
"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "66c0617cc0e05ec10af942c8ece23c7369877b05ebab9576253ace7f77a2e984",
"outputIndex": 1,
"outputGlobalIndex": 50533897,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623407,
"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": "0e20ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e204ff0a3a78ff81cc5d17286af130747f9f0667e27aecb23e21bdd93b3cf02783a",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ff0a3a78ff81cc5d17286af130747f9f0667e27aecb23e21bdd93b3cf02783a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "68b5e96f7939d71eb1e51891860a7b41fbc8ec366ce6d8a0924351204081f1b3",
"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "94dbef9eac994b72245e689d44d7fe08af7aa2151a7369ee8524b731deab95aa",
"outputIndex": 1,
"outputGlobalIndex": 50533902,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623407,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20791d9b3032c29cf6826ed927db91df14df0acd23d50ede3d9502510f074e33fc",
"sigmaType": "Coll[SByte]",
"renderedValue": "791d9b3032c29cf6826ed927db91df14df0acd23d50ede3d9502510f074e33fc"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c54d9ad1d172653dd1056e51c84dd641891bdab880c60c2ab595f54eb10a68ec",
"value": 2000000,
"index": 8,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "af05db5ecd131f0ab4d30bad440caf7dc0062aca36c6669c99a14ba45cf1532f",
"outputIndex": 1,
"outputGlobalIndex": 50533907,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623407,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20ef13c936f23fe3683e27e62e98f9febb96aa6648e5983fc80f755f9e2e99f7e0",
"sigmaType": "Coll[SByte]",
"renderedValue": "ef13c936f23fe3683e27e62e98f9febb96aa6648e5983fc80f755f9e2e99f7e0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1df3596922e6e2f4e990700b61f90486a63263bb9a99b98af4de501ad6ca979d",
"value": 2000000,
"index": 9,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "d25b9b6c02f86860596277e101c245235743a784e78ed5e5bab71aaf1b6f1e0a",
"outputIndex": 1,
"outputGlobalIndex": 50533912,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623407,
"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": "0e20716181df51a93550afae6dd2e899c4e21e5e4ea9a666a4c739d828960ae89a47",
"sigmaType": "Coll[SByte]",
"renderedValue": "716181df51a93550afae6dd2e899c4e21e5e4ea9a666a4c739d828960ae89a47"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20a23f60e54284b33f90bfd2ab1fcbe93a4582bad5818f797bb0c1c5ffc6528422",
"sigmaType": "Coll[SByte]",
"renderedValue": "a23f60e54284b33f90bfd2ab1fcbe93a4582bad5818f797bb0c1c5ffc6528422"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ce733bd2f2b115f6cefa2a4e479721f612dccf435d165b0d959baaa41585ae2c",
"value": 1010000,
"index": 10,
"spendingProof": null,
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "97ca9e3943f003dc39440ea1dd9d54805e682acdf7b1b09ff7821a13fc48edc0",
"outputIndex": 1,
"outputGlobalIndex": 50533925,
"outputCreatedAt": 1623403,
"outputSettledAt": 1623407,
"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": "0e203766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "3766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "535f067ddbab6f329f0038e2467a2997fc592870838c46b383109e131489923a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "83172b1182c99ea7a982c9ccf631d5c86bd3fe62de2926367ab90e61c0c172de",
"value": 2000000,
"index": 11,
"spendingProof": null,
"outputBlockId": "2fa7664f0bc17ef55e7b7c0ccf0c4dd453542333b268c9e5f959c2680b498584",
"outputTransactionId": "e74e4872aaf663678057ef1258ad1d208893653209a6b4243b7716171087e8fc",
"outputIndex": 1,
"outputGlobalIndex": 50533935,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623408,
"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": "0e20329629a6d99dd6f1a0aba033848f0ca356394f1416a8bf7c49e85b5164b1b14f",
"sigmaType": "Coll[SByte]",
"renderedValue": "329629a6d99dd6f1a0aba033848f0ca356394f1416a8bf7c49e85b5164b1b14f"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20952bef76f25c1c8c1e308fdd00f67434c733468f783f7bbc8a5153486a11048e",
"sigmaType": "Coll[SByte]",
"renderedValue": "952bef76f25c1c8c1e308fdd00f67434c733468f783f7bbc8a5153486a11048e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "4d12aad3bcb10cd79cac4eb799ec603145469f3cf884c35c6addee3e249f93bc",
"value": 2000000,
"index": 12,
"spendingProof": null,
"outputBlockId": "2fa7664f0bc17ef55e7b7c0ccf0c4dd453542333b268c9e5f959c2680b498584",
"outputTransactionId": "0ad1e2f0f88a24c9178003c642910988a3f12c76b5d63037c2835a63903a9701",
"outputIndex": 1,
"outputGlobalIndex": 50533940,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623408,
"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": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9c9296e482c81b9725e516c1d121e2281ac0570e0e65438666be972e91758e6b"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2009cac51a1865c72cd34580bd3156b92dc597d16bdc8f4ae2f012ab043469ba1d",
"sigmaType": "Coll[SByte]",
"renderedValue": "09cac51a1865c72cd34580bd3156b92dc597d16bdc8f4ae2f012ab043469ba1d"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "fccf5314f2d043670de8f958f4806de86a4464b8d31c993d942975a2d26601dd",
"value": 2000000,
"index": 13,
"spendingProof": null,
"outputBlockId": "2fa7664f0bc17ef55e7b7c0ccf0c4dd453542333b268c9e5f959c2680b498584",
"outputTransactionId": "c2b995c1762e368a18f7dd99d0ffb2ab284cd6d012134b347092973b63b4a3e0",
"outputIndex": 1,
"outputGlobalIndex": 50533945,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623408,
"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": "0e2069cecf842b211bee823665b779bd0a4b93add45787e36d936bcdb7a7f7bbff2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "69cecf842b211bee823665b779bd0a4b93add45787e36d936bcdb7a7f7bbff2a"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20cf21391f493ef0f658c724218b2769cff3fb3dbacc27651cc9f1f5d6db629df2",
"sigmaType": "Coll[SByte]",
"renderedValue": "cf21391f493ef0f658c724218b2769cff3fb3dbacc27651cc9f1f5d6db629df2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "55ec5f07477b21f779330cd2ab4a391f976644a67024e7e9e5b877448b0f7cf1",
"value": 2000000,
"index": 14,
"spendingProof": null,
"outputBlockId": "2fa7664f0bc17ef55e7b7c0ccf0c4dd453542333b268c9e5f959c2680b498584",
"outputTransactionId": "4bb266609899d5f499a0035624c2c580c2141c66d759326f50e4ccd7d1b1cb30",
"outputIndex": 1,
"outputGlobalIndex": 50533950,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623408,
"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": "0e20f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d",
"sigmaType": "Coll[SByte]",
"renderedValue": "f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e203947dbacee77da47fe0e09ba88b5852b4fd9cb125d67103ef22aa8387d2c1bbf",
"sigmaType": "Coll[SByte]",
"renderedValue": "3947dbacee77da47fe0e09ba88b5852b4fd9cb125d67103ef22aa8387d2c1bbf"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3cb2da1cb7fd4a4d28de0ea913fb3f58ab39768f20430a006e25ac22033c73ac",
"value": 2000000,
"index": 15,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "2282b39b1d86ecca1d6576bcd6c3591dc39916ddb8e7c159b3f69b97b4a37607",
"outputIndex": 1,
"outputGlobalIndex": 50534052,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e209a3a0ee65250ab11322f2399ee679eae4b59d3b931c1317968ca1ec1be3f456b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9a3a0ee65250ab11322f2399ee679eae4b59d3b931c1317968ca1ec1be3f456b"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2015ddc467c47f95bdd45c8d37f913c0c7ca1bfed590a5723141ff551e4d00cd68",
"sigmaType": "Coll[SByte]",
"renderedValue": "15ddc467c47f95bdd45c8d37f913c0c7ca1bfed590a5723141ff551e4d00cd68"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "24fa46d235bc8b9583f031ac017bdd291552a43c2cdffa51cc5b5bc16323c636",
"value": 2000000,
"index": 16,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "16de29e08a943fc2e62eead4dca62a57a537d1bde8e59ac4c282ac90446ed113",
"outputIndex": 1,
"outputGlobalIndex": 50534056,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2054b70ee64a1f8d0e40ffe199837cf62a1df74a22a173d57b8ea3bb79c4474891",
"sigmaType": "Coll[SByte]",
"renderedValue": "54b70ee64a1f8d0e40ffe199837cf62a1df74a22a173d57b8ea3bb79c4474891"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "510a30d4bf0e59d3cc6867f77bd168d9b78661567c71ddd31dd86575a30e5253",
"value": 2000000,
"index": 17,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "3fbeac2fb659e1c448a011c1b084a6e0473e756bd12676f04e681c6ba4152763",
"outputIndex": 1,
"outputGlobalIndex": 50534061,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e200b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a",
"sigmaType": "Coll[SByte]",
"renderedValue": "0b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e202165a73ae60a4e4d44315e99e73d7097424110561ae1880a96d083c8fba79ca1",
"sigmaType": "Coll[SByte]",
"renderedValue": "2165a73ae60a4e4d44315e99e73d7097424110561ae1880a96d083c8fba79ca1"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "18ca632e80d857ab9518df85b3a0b750b6f650d1e5101bf76c41f2a5d78314b2",
"value": 2000000,
"index": 18,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "907e0fe1ffcc7c72791e01a78e26e7700ce3a5c0d958d04772131b7d544913a2",
"outputIndex": 1,
"outputGlobalIndex": 50534066,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20efd806919b55c5d5d9102b647af0fd2484cbd064c193da9cbe9cef75eb83dfe9",
"sigmaType": "Coll[SByte]",
"renderedValue": "efd806919b55c5d5d9102b647af0fd2484cbd064c193da9cbe9cef75eb83dfe9"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2029da7148b449932322f3b39d681a04b35e8f34ac7257731ba5a24c3627b2f379",
"sigmaType": "Coll[SByte]",
"renderedValue": "29da7148b449932322f3b39d681a04b35e8f34ac7257731ba5a24c3627b2f379"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "e74df67102718ce6d5fe77eb02d74b6aec450032d18ccbfca9fb363a49340d22",
"value": 2000000,
"index": 19,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "c9670fa780ca05d381e2a0a060259e2878e4f80e7b429ef973d6541fe416b985",
"outputIndex": 1,
"outputGlobalIndex": 50534071,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20fb093c0296fb003c49f1404877704ff45e3f0585e1b98f7ab23c0459a65a10df",
"sigmaType": "Coll[SByte]",
"renderedValue": "fb093c0296fb003c49f1404877704ff45e3f0585e1b98f7ab23c0459a65a10df"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2cdffb8249313924ed040d1d89ca4d989a4a4302ec396a1e5b6847b443df6c45",
"value": 2000000,
"index": 20,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "ec8eb3d75c3d64e2ed2491ef59434a48a30ff1e0919cfb18add91969eb332c96",
"outputIndex": 1,
"outputGlobalIndex": 50534076,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698",
"sigmaType": "Coll[SByte]",
"renderedValue": "ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20ba2eaf0a911efe5e349a27bacb451dea0187dad6b28167e520a5da2f98935859",
"sigmaType": "Coll[SByte]",
"renderedValue": "ba2eaf0a911efe5e349a27bacb451dea0187dad6b28167e520a5da2f98935859"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "36bd281dd2c1c09cd6f8b41cb54b3d34f5965ce5a3c079f8c0d44aa5e5abe084",
"value": 2000000,
"index": 21,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "0338d9cfd340eeb0f561dc0f174c1e6796538f3094930eaf9ad88806a502cb55",
"outputIndex": 1,
"outputGlobalIndex": 50534081,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e202248234c5efb1aa1731732d33f184c02a0fdc1a98c1f3380c65dd7f1fa6e48f1",
"sigmaType": "Coll[SByte]",
"renderedValue": "2248234c5efb1aa1731732d33f184c02a0fdc1a98c1f3380c65dd7f1fa6e48f1"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e203a9dbcd8c14a55557dfb9059e7f607dd0b86e5668dda05f1fcd64494da1bb0aa",
"sigmaType": "Coll[SByte]",
"renderedValue": "3a9dbcd8c14a55557dfb9059e7f607dd0b86e5668dda05f1fcd64494da1bb0aa"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "add6d8dbb4979ac7f2e1a498c1b7976841f4c884132b8ea3a64e3b611a5d2b03",
"value": 2000000,
"index": 22,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "081cfc423d9b8e3edfee5ffb7269ff015b3a33fda0367960cb7de7d7a0dec064",
"outputIndex": 1,
"outputGlobalIndex": 50534086,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20315a9f8b06f0e39d5c1b4e5ef069cf75aedd27206e2f90dbc77eab0e1b18bfc1",
"sigmaType": "Coll[SByte]",
"renderedValue": "315a9f8b06f0e39d5c1b4e5ef069cf75aedd27206e2f90dbc77eab0e1b18bfc1"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e20d9b0c09c7d95879ef5ce0996f4a468c15779e1aff4a46f9224c2f0d4e5e0828f",
"sigmaType": "Coll[SByte]",
"renderedValue": "d9b0c09c7d95879ef5ce0996f4a468c15779e1aff4a46f9224c2f0d4e5e0828f"
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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": 23,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "16a1f70221549c982874ef2a62349426a62f2d6bac8050c73f7617d475b5cb18",
"outputIndex": 1,
"outputGlobalIndex": 50534091,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e204e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916",
"sigmaType": "Coll[SByte]",
"renderedValue": "4e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20d453ec24913e4cf89a8ad83386d26fd8fe649ce09dcfd39ebfb754044a961f03",
"sigmaType": "Coll[SByte]",
"renderedValue": "d453ec24913e4cf89a8ad83386d26fd8fe649ce09dcfd39ebfb754044a961f03"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "34a10b050b529a6dd78fec8cc47f59d6d0debcd3be02bd60956bcb442558150d",
"value": 2000000,
"index": 24,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "1ba0edd42286a364e7567606f46f37bce24c5443051cfb45c1c504613cf35d9f",
"outputIndex": 1,
"outputGlobalIndex": 50534096,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e201a82e3723f16b7a77e409a9177d10e700975265cc961a52b7433037cbd575ff8",
"sigmaType": "Coll[SByte]",
"renderedValue": "1a82e3723f16b7a77e409a9177d10e700975265cc961a52b7433037cbd575ff8"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "004cd8a79247b41b0e90a5842af430d6aa28f153b97cef409fd4f748d4f91b17",
"value": 2000000,
"index": 25,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "29f62673d62d5aca4515cce3093072333aef67a7e620009e4b934ebd68884f91",
"outputIndex": 1,
"outputGlobalIndex": 50534101,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e203684a6fc79378d5207e1dc5bc3f399d2367031b79a2fc76f8d0bfe2082c71be7",
"sigmaType": "Coll[SByte]",
"renderedValue": "3684a6fc79378d5207e1dc5bc3f399d2367031b79a2fc76f8d0bfe2082c71be7"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20b439dff0b663c57d0cfaaa59b2e6a01642bdda855e9120b7f38bced8b483a24b",
"sigmaType": "Coll[SByte]",
"renderedValue": "b439dff0b663c57d0cfaaa59b2e6a01642bdda855e9120b7f38bced8b483a24b"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "80d09b077b86830a31748ff61cfe0016d5987dec3f0b1a00a9641f665571b323",
"value": 2000000,
"index": 26,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "2a8bbbe27494e36bc011f3200eb653d43d9ca1245384b243e1fdc4251fb91e3d",
"outputIndex": 1,
"outputGlobalIndex": 50534106,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20db8e71a8aa08bc0c7630f53d6189aff5e2c5e6c97d794b7617c0e41701a26c70",
"sigmaType": "Coll[SByte]",
"renderedValue": "db8e71a8aa08bc0c7630f53d6189aff5e2c5e6c97d794b7617c0e41701a26c70"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20b61e0d80cd393ea1ce75bcd1f3b30b4009bee637962c279d3154a166d74f7824",
"sigmaType": "Coll[SByte]",
"renderedValue": "b61e0d80cd393ea1ce75bcd1f3b30b4009bee637962c279d3154a166d74f7824"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "985cb01f83592ac662667783b68fda445f92ae40bc414999198116ad9ecaa6e8",
"value": 2000000,
"index": 27,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "2e1d683c8f00a063f153be373771bdcf4a287ea42d2691662f97d5b9ecc4f013",
"outputIndex": 1,
"outputGlobalIndex": 50534111,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e207381c9f36069e7048067d5ad4c25f6161c1969edd804fb76ac9805b626fca188",
"sigmaType": "Coll[SByte]",
"renderedValue": "7381c9f36069e7048067d5ad4c25f6161c1969edd804fb76ac9805b626fca188"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20581ff972321c8d144e84b53a26cf80f2c9d3c2999f84d2803322e77058cc0e18",
"sigmaType": "Coll[SByte]",
"renderedValue": "581ff972321c8d144e84b53a26cf80f2c9d3c2999f84d2803322e77058cc0e18"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "3a004532a21d1e070e684ddf5a717a1b0bc9fd1f5f433e05f05924086ab95b6a",
"value": 2000000,
"index": 28,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "3509be99dc21a5efa770d44837e4f3b8362172947a5136c32e65d4e899c86703",
"outputIndex": 1,
"outputGlobalIndex": 50534116,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2017b791083d0d4a3532c9e7d9c46a7e397418453cda398c8abafa18aee8a705a7",
"sigmaType": "Coll[SByte]",
"renderedValue": "17b791083d0d4a3532c9e7d9c46a7e397418453cda398c8abafa18aee8a705a7"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e204db34020b72351b59b9014b40584dba3b3a87e7f333903dac95028e41271e088",
"sigmaType": "Coll[SByte]",
"renderedValue": "4db34020b72351b59b9014b40584dba3b3a87e7f333903dac95028e41271e088"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "7ce18c58106c3e912efe564d2a0681c99a9bed322bfa61d02c910a55f550b5d2",
"value": 2000000,
"index": 29,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "350adf5aeb37ada6bbba8f8dea56defca475d06ad07a48c1fc53cd5e4d3f820c",
"outputIndex": 1,
"outputGlobalIndex": 50534121,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e201cebf17e8687c5b8038094a1241961c54c65773e30c4970389ee39fa9dc956ea",
"sigmaType": "Coll[SByte]",
"renderedValue": "1cebf17e8687c5b8038094a1241961c54c65773e30c4970389ee39fa9dc956ea"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20ed87ccdc54f074d488ae2d4de72842179d62f8fec6c6a9a890b1a5684c608546",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed87ccdc54f074d488ae2d4de72842179d62f8fec6c6a9a890b1a5684c608546"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "50afc4547cb2a28a7aff82f86d008dddaac0a693c829211e9756a48614716e27",
"value": 2000000,
"index": 30,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "377d38581397cbd5ea6a368650347c5142bceee468ee00368e4f39e455010f13",
"outputIndex": 1,
"outputGlobalIndex": 50534126,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2099eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0",
"sigmaType": "Coll[SByte]",
"renderedValue": "99eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20739db130d4a9390fb3cd7771f24053fac9f4d1555a23d895918140bf616262b5",
"sigmaType": "Coll[SByte]",
"renderedValue": "739db130d4a9390fb3cd7771f24053fac9f4d1555a23d895918140bf616262b5"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "aa0005e851c2b6d2e38e6e983760c66af2559208a218c9c1231b49430ce48bb6",
"value": 2000000,
"index": 31,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "3d8537080f87aab8aabc46c51232785291b1720d2212e5caed67945e5578f75b",
"outputIndex": 1,
"outputGlobalIndex": 50534131,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20efd342ad271e276e15cabc828640e4469ed6239cf795e0b7f7930eaaff69a0c0",
"sigmaType": "Coll[SByte]",
"renderedValue": "efd342ad271e276e15cabc828640e4469ed6239cf795e0b7f7930eaaff69a0c0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ae75644922f874aa34f02b8aacc2ac2a5475b5f64d2f8d26e0973c4b9b253af1",
"value": 2000000,
"index": 32,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "3f9ee0314e86be68dbb4261cc291b8ac9838cd033b9be30eb60b1218f9736b97",
"outputIndex": 1,
"outputGlobalIndex": 50534136,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20bc013c1a061ba42a7b0441032ae8352c2dd00948cbad10f25354133544b49701",
"sigmaType": "Coll[SByte]",
"renderedValue": "bc013c1a061ba42a7b0441032ae8352c2dd00948cbad10f25354133544b49701"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "01f04b67c01c3a6616541a34d1a87ef6556b7099e9fff325fa059960ffd73269",
"value": 2000000,
"index": 33,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "412a40e8dd08d180e836bc174a14eef6b68042c45dcae89ea23e7599101e73da",
"outputIndex": 1,
"outputGlobalIndex": 50534141,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "3aa7ed9864521180387dcc059e46225ada5116a86758bc2b958873bbd7d19366"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20d42a471c550444a69bff0826dcc2b312e374f844d9cf52a253501c6708003530",
"sigmaType": "Coll[SByte]",
"renderedValue": "d42a471c550444a69bff0826dcc2b312e374f844d9cf52a253501c6708003530"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 34,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "422af36ceb084461e396536171250455b746d769bb91686f6c5f1b296b54c224",
"outputIndex": 1,
"outputGlobalIndex": 50534146,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2038813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e",
"sigmaType": "Coll[SByte]",
"renderedValue": "38813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8dee3ad323fe1806e40eaa3e6227712cd5fe35fc72480b54228e5721f1178408"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "aa30c546f45592f21729254866c6bd6023217be418cb398db6e0563586a700a4",
"value": 2000000,
"index": 35,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "44cbb0680d874346869eec7abc66de51cd6875e425b2e18ad0b77a56d27ce657",
"outputIndex": 1,
"outputGlobalIndex": 50534151,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2064dbc5cd50cf91f773c5de6e40b745c2cef048a5770f804dd185de5412bb9680",
"sigmaType": "Coll[SByte]",
"renderedValue": "64dbc5cd50cf91f773c5de6e40b745c2cef048a5770f804dd185de5412bb9680"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d5994a01f6356105fc407147b17ca9b9b8a597bf776482177322415558b5ae3b",
"value": 2000000,
"index": 36,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "46c84886cf40e1e1ab6ee7b086d51461db53e56dcbab613345059bb593726a67",
"outputIndex": 1,
"outputGlobalIndex": 50534156,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e2097ccaa554d7918228e3ba22f0ae54c71c17ab70eab7087c994df6d9a3fe6f0b1",
"sigmaType": "Coll[SByte]",
"renderedValue": "97ccaa554d7918228e3ba22f0ae54c71c17ab70eab7087c994df6d9a3fe6f0b1"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2081f74ed750392c08b0203c336fe5b5dd69143457015264bdde682fbed06691b8",
"sigmaType": "Coll[SByte]",
"renderedValue": "81f74ed750392c08b0203c336fe5b5dd69143457015264bdde682fbed06691b8"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "9a03f6a4566ae721d99ade256e1502d25ccaec2f7dc35b04c36b619ff7bc1011",
"value": 2000000,
"index": 37,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "47b9cd0c25f71aa367442bdb6ada36549de3af8fe1506dcb026fa00abd456460",
"outputIndex": 1,
"outputGlobalIndex": 50534161,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c",
"sigmaType": "Coll[SByte]",
"renderedValue": "b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e203611de2811378d00a2d8ea7228b5b8574a87ccd225c20d003d8d73d974686a73",
"sigmaType": "Coll[SByte]",
"renderedValue": "3611de2811378d00a2d8ea7228b5b8574a87ccd225c20d003d8d73d974686a73"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "9445c077f3069deb5c5fef1e9f652ae2ef20be94c6b181945b1fbad84c393e34",
"value": 2000000,
"index": 38,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "4925a0eba758eef4e50d7b4f5a04da49a30f00103eccfbbea57a294f4c2cd461",
"outputIndex": 1,
"outputGlobalIndex": 50534166,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20ad24d3cb8c3161b97c75ab50883ca635368020088376b7a03e654a4673ff95e8",
"sigmaType": "Coll[SByte]",
"renderedValue": "ad24d3cb8c3161b97c75ab50883ca635368020088376b7a03e654a4673ff95e8"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20b550e88c8d7580e77dee586b0ddf9154a47b12e95b83cbcbf30b472a3e50d64d",
"sigmaType": "Coll[SByte]",
"renderedValue": "b550e88c8d7580e77dee586b0ddf9154a47b12e95b83cbcbf30b472a3e50d64d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "9c57434f811c67a1ab0763f6fb1df375cce76c7fb232b218e1cb68902a4b154f",
"value": 2000000,
"index": 39,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "4e6db50eed88a18126cbe8464622a9de11d58ac139eb6c819eae094c48ccad51",
"outputIndex": 1,
"outputGlobalIndex": 50534171,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20a1e2ea874ca07c83ad85e3e4e86e653a41a72acbdf96bedea9ea51f80e176c27",
"sigmaType": "Coll[SByte]",
"renderedValue": "a1e2ea874ca07c83ad85e3e4e86e653a41a72acbdf96bedea9ea51f80e176c27"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e209d9cd592bfb96216b013b7be533d9f6cc7b3113dc42fa9b0ec76eafe5c7a9a58",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d9cd592bfb96216b013b7be533d9f6cc7b3113dc42fa9b0ec76eafe5c7a9a58"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "9acf8951977182dbb376784b05583db6ca1d1ff7bc423e0aca30a20144b2d4cd",
"value": 2000000,
"index": 40,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "564f965c584bb9d70eb1dcaf9f7c35e90692370f59cbd5b193c67ee91ea2d932",
"outputIndex": 1,
"outputGlobalIndex": 50534176,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c18ff18293e0ddc0a9ba56235956617a4dfdc5780a5e8580f518442a9e8b7f7c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "7e8386ab93b578af4ac9cddc0886685b1a06cdfe02841a96dbf26ec213fa18bd",
"value": 2000000,
"index": 41,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "56625027c4d61f6ec0861c21417524fcc84edc4439b222b6a48958b43af1b467",
"outputIndex": 1,
"outputGlobalIndex": 50534181,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2088708d05bd78d4d8b4195f210903fc8bccb2eacd2c3bba6c8c7302ddba29ca92",
"sigmaType": "Coll[SByte]",
"renderedValue": "88708d05bd78d4d8b4195f210903fc8bccb2eacd2c3bba6c8c7302ddba29ca92"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20f763e4077428711523eb603375002b429fd94f594d79ee3d2c831932797d5a9e",
"sigmaType": "Coll[SByte]",
"renderedValue": "f763e4077428711523eb603375002b429fd94f594d79ee3d2c831932797d5a9e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "05dc97b7cadb70a6544d84bfb50ac6fcb9494e939ee6a7c9106e4d47c5533ecd",
"value": 2000000,
"index": 42,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "5878068eff95b6f544e768501a3b1756436b51528695591430d111cf125d741d",
"outputIndex": 1,
"outputGlobalIndex": 50534186,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e203a81faca46b5e3edc08f3f0a18cd1fb81ac9e919fea2b50ef4b546ed1da06e34",
"sigmaType": "Coll[SByte]",
"renderedValue": "3a81faca46b5e3edc08f3f0a18cd1fb81ac9e919fea2b50ef4b546ed1da06e34"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "72bd47b03ce715dbc4addc5c0add0decf81c780f7b346005c869ec3be1540e94",
"value": 2000000,
"index": 43,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "5eca1fb4ff8017a0b31dd292540a5f04c269d3edd500fe48500b8fe65ae3c7c9",
"outputIndex": 1,
"outputGlobalIndex": 50534191,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e206b50c862a12ddc14eb9669032f924327b6d32eb69a4c617016121243c64bd55c",
"sigmaType": "Coll[SByte]",
"renderedValue": "6b50c862a12ddc14eb9669032f924327b6d32eb69a4c617016121243c64bd55c"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e202af2d5344c1e93e0be35e49e9d1c22f6bf56844a4503f70fa28a62af7ddc4ac0",
"sigmaType": "Coll[SByte]",
"renderedValue": "2af2d5344c1e93e0be35e49e9d1c22f6bf56844a4503f70fa28a62af7ddc4ac0"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 44,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "6046c1565b0caf676334ddeb1ab1d1ac1d9fd180398df3526ae3cc4fc48cddd2",
"outputIndex": 1,
"outputGlobalIndex": 50534196,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e206435f0cabc1b3081f365859bc6e0fe6535e6342e4e65bc5a6c3373d32f280594",
"sigmaType": "Coll[SByte]",
"renderedValue": "6435f0cabc1b3081f365859bc6e0fe6535e6342e4e65bc5a6c3373d32f280594"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20df118681e96075c731577fad48d70f1a1978d1902eb7a1fd1853d55b01864286",
"sigmaType": "Coll[SByte]",
"renderedValue": "df118681e96075c731577fad48d70f1a1978d1902eb7a1fd1853d55b01864286"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "cd1085c78e1f49f64dd2f8be503ab253644c36be4bad2bda3b1f62549a796958",
"value": 2000000,
"index": 45,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "666660e5e600b2c63cf09c1e4252d9128722111961dbd479713785c2186fb843",
"outputIndex": 1,
"outputGlobalIndex": 50534201,
"outputCreatedAt": 1623408,
"outputSettledAt": 1623409,
"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": "0e20e9042ff2bdd32a7bc7efb798e6ebc733bee9f7b05bda74c4ee57ee356ed561fe",
"sigmaType": "Coll[SByte]",
"renderedValue": "e9042ff2bdd32a7bc7efb798e6ebc733bee9f7b05bda74c4ee57ee356ed561fe"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e206309bd5206813204bea998214502b4b4399940e3e6e4b15c0157feb1d1afd07c",
"sigmaType": "Coll[SByte]",
"renderedValue": "6309bd5206813204bea998214502b4b4399940e3e6e4b15c0157feb1d1afd07c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "fa9178e4d30198e0fbf49b11ca36242095ebe1192399e0830516e9b27b2525dd",
"value": 2000000,
"index": 46,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "7337025718c59c981801a48c05760d07c7d0b8dac921366b5e931118c131f563",
"outputIndex": 1,
"outputGlobalIndex": 50534206,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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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"sigmaType": "Coll[SByte]",
"renderedValue": "c652bb3c7ca4d20cc6f02a0aa5f06bdf9194925c99c867b0fe928151ecee0806"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e209b377b2133947ad8da3b778e19d81015b3df4086fba7933c353a11e1721969ae",
"sigmaType": "Coll[SByte]",
"renderedValue": "9b377b2133947ad8da3b778e19d81015b3df4086fba7933c353a11e1721969ae"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "fcafb9fe244deeb6bad07b46559a54f84ac37330e2a7dbb7104b1841679c9dbf",
"value": 2000000,
"index": 47,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "73fe1b876e02caaf5617cb3c0acf37e9d3e409e7e1fd8d11d8cc3709415d3a4e",
"outputIndex": 1,
"outputGlobalIndex": 50534211,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20e658bd869bc04c3e547c5634f0fcd46d5fb66c2ac10a6a0d41fb63b5ffb2bd18",
"sigmaType": "Coll[SByte]",
"renderedValue": "e658bd869bc04c3e547c5634f0fcd46d5fb66c2ac10a6a0d41fb63b5ffb2bd18"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e206923bae74af57d6eb2d44fc987f004f1c582a5f039e860a74f7c95f6dd803aa9",
"sigmaType": "Coll[SByte]",
"renderedValue": "6923bae74af57d6eb2d44fc987f004f1c582a5f039e860a74f7c95f6dd803aa9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ff1650c10c52c642d926b90a68fccd9d1106580e538f853c5d398b3334accfbb",
"value": 2000000,
"index": 48,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "7b282e28d9272387736438f2023aafc48c214f086d5214b5423c24f84b1867cf",
"outputIndex": 1,
"outputGlobalIndex": 50534216,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "ce985a97d78a34e8782801ca5cd997ccc63db2cdbfacda500f9f27f40efad3d5"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "14f3c50fa944e74c0ab6f2a3cec47e38125fe1058e373e719061c28096c8cae6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "1f770aaaddf38337572c6a85fd1b5aa563fa5da1aebf4216cc0b39e257490ce5",
"value": 2000000,
"index": 49,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "7bcd2e2e5ee5cf69d77af2b1a5656e7ef7abe7b0f411eaba4eb420677516b869",
"outputIndex": 1,
"outputGlobalIndex": 50534221,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20f2c363d81912cc3d8785ea9c607efed83af3a9b3ceb451e9cb005e57e8837f2c",
"sigmaType": "Coll[SByte]",
"renderedValue": "f2c363d81912cc3d8785ea9c607efed83af3a9b3ceb451e9cb005e57e8837f2c"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8c893230253e13bb64b7fefca4666b6bd88a0b5330f3ce9e988ad6b7668fa8a8"
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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": 50,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "807495554416ccf2a214e28bb4ed6003b5b99c73a81da463f27598b55ede52fd",
"outputIndex": 1,
"outputGlobalIndex": 50534226,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e200230bc2fa5d72266f12a375fe531aa712b74723ba29d4a118a9920871f77d53a",
"sigmaType": "Coll[SByte]",
"renderedValue": "0230bc2fa5d72266f12a375fe531aa712b74723ba29d4a118a9920871f77d53a"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20c942832510c8440be3974ff1f946882511b56e7cc8345abd4cc3be9867a98a36",
"sigmaType": "Coll[SByte]",
"renderedValue": "c942832510c8440be3974ff1f946882511b56e7cc8345abd4cc3be9867a98a36"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f3cc213b1d721ffcb00bc967e9515bf4b238a55161ba5d3069754792159bd872",
"value": 2000000,
"index": 51,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "82f67c9f194a06dc11294f01734f7a1f7420da2ef2cce62a8d334cc4225a38aa",
"outputIndex": 1,
"outputGlobalIndex": 50534231,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "bf604d00656a110d0af06d25c0103af1f472f7eec6b664812cf29dbaab04e095"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e2012f5b053fd47fbc8f9097960641e20de88a0d23738c66ba11f077d7bd73f2a17",
"sigmaType": "Coll[SByte]",
"renderedValue": "12f5b053fd47fbc8f9097960641e20de88a0d23738c66ba11f077d7bd73f2a17"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 52,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "860ec87ec98080baa2ebd4a46802776288557e0f4871a5c76b0dc3afed64128c",
"outputIndex": 1,
"outputGlobalIndex": 50534236,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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]",
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"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "88f24e79760b76bd86f5d65b8ac8a499ca9e46a039bac7e5c38a4f11c8cc516e"
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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": 53,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "86d1c8394abdba41add8a72e612c878e572215c40f272371d26d482190a30f75",
"outputIndex": 1,
"outputGlobalIndex": 50534241,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20f9f53533ac2e6bc2965c9a6b6daff832a22cca3df388dd3caf0aeed146abcca6",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9f53533ac2e6bc2965c9a6b6daff832a22cca3df388dd3caf0aeed146abcca6"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20d74905f5cfc453141bd6ebf61bddddf34c096be376c199dca6833d5f98408d71",
"sigmaType": "Coll[SByte]",
"renderedValue": "d74905f5cfc453141bd6ebf61bddddf34c096be376c199dca6833d5f98408d71"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "d5e8bb2bc5684f45da3c1b8b455d87785204ef2b0be058480e71c8e71c6260e7",
"value": 2000000,
"index": 54,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "88abf8751ba3129493abfc528c4d4415159ff74e67286803f3dd12ab370865f8",
"outputIndex": 1,
"outputGlobalIndex": 50534246,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2077e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5",
"sigmaType": "Coll[SByte]",
"renderedValue": "77e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20e286cff8367f739a1db1d9fe404e11f231cd8c136eeb3e25ae3ca96c68d8fd74",
"sigmaType": "Coll[SByte]",
"renderedValue": "e286cff8367f739a1db1d9fe404e11f231cd8c136eeb3e25ae3ca96c68d8fd74"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 55,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "8a8bf2ef11799fc6e13481030f9b383b683a5627fc8775e049f81058ce362617",
"outputIndex": 1,
"outputGlobalIndex": 50534251,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20c386c262988461b04977347cbecb30fc79432bb3b9a056d2cdc882f96aa39a96",
"sigmaType": "Coll[SByte]",
"renderedValue": "c386c262988461b04977347cbecb30fc79432bb3b9a056d2cdc882f96aa39a96"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ba23312050d27a6a33a4998dd512d32c084993d52744a7dcdb656397f66a2248",
"value": 2000000,
"index": 56,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "92858d58bf0758edcad5229af99029e85aa5c282e5beec2227816800a1c7132b",
"outputIndex": 1,
"outputGlobalIndex": 50534256,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20dada336c4564a1906c2b55a813173917df580aee389e714f08ef49fd181129b5",
"sigmaType": "Coll[SByte]",
"renderedValue": "dada336c4564a1906c2b55a813173917df580aee389e714f08ef49fd181129b5"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2016bed006b09cf1d61c11c55ef97b2d7dfe21d39dc97d8a2b2827d2d0b7bdbf09",
"sigmaType": "Coll[SByte]",
"renderedValue": "16bed006b09cf1d61c11c55ef97b2d7dfe21d39dc97d8a2b2827d2d0b7bdbf09"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "52f49ddb9989cf693bbcfd48ef60483e5b881388633da3ce95dba4bc803d2947",
"value": 2000000,
"index": 57,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "95be86968bc4202a1ab92ebac44a105693c2bd5ef6fc97e97141c33bdac426d4",
"outputIndex": 1,
"outputGlobalIndex": 50534261,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "3b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e209fbe7ee50a97177ff675e0b2cc90e56605bf07cc44f8516fac7bd9d2049bcd7d",
"sigmaType": "Coll[SByte]",
"renderedValue": "9fbe7ee50a97177ff675e0b2cc90e56605bf07cc44f8516fac7bd9d2049bcd7d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "b16dbeb252665638fe93f1ef15ddc78f545027e5e3c2e5a065152d8f3eca1a05",
"value": 2000000,
"index": 58,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "9b4bc65c3a4168fd053a8ce29cd7c827acac2c71a5af9f13f5598df85f9348f6",
"outputIndex": 1,
"outputGlobalIndex": 50534266,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "fb50eeb02f090392ce61c8f7954b82e75a75256239721ad5fe30c7d902b2ded7"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2023ca531bd836ca15c18f0d8858bbb1624397afc5ed1598575aaf39cd743a2cc3",
"sigmaType": "Coll[SByte]",
"renderedValue": "23ca531bd836ca15c18f0d8858bbb1624397afc5ed1598575aaf39cd743a2cc3"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "4c95030da8bfcc7b5c98ad4fe89e1c06831824950dded70b995211a3ff42fae6",
"value": 2000000,
"index": 59,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "9b778ddf4a3b56fb43c474546a977aa31f9b913101705ffea5b194cc898e5c3d",
"outputIndex": 1,
"outputGlobalIndex": 50534271,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2012afc46a7412ec1f67c32bdb4747b25d3cf3becd6b79be6335708252ce400f24",
"sigmaType": "Coll[SByte]",
"renderedValue": "12afc46a7412ec1f67c32bdb4747b25d3cf3becd6b79be6335708252ce400f24"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3684830b5cefac3e4c300875f62ecbe85df83f2a4d931975b26d69161b5ca47d",
"value": 2000000,
"index": 60,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "9d8c450c36e3d791c82626d2da67dd6be3b4d5554e55898f732c6a103509bfae",
"outputIndex": 1,
"outputGlobalIndex": 50534276,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e205b94fd2a70cac5a896f832d8a41020f80b8a2e3c400f49da364b759afd4f8ec1",
"sigmaType": "Coll[SByte]",
"renderedValue": "5b94fd2a70cac5a896f832d8a41020f80b8a2e3c400f49da364b759afd4f8ec1"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20fd2507371842367bdc46804f5481bebdcd4efa981464a81c9e96bfa479893246",
"sigmaType": "Coll[SByte]",
"renderedValue": "fd2507371842367bdc46804f5481bebdcd4efa981464a81c9e96bfa479893246"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "23567fc765f662594f4e018c0df068bc82ab270112b41e75534e60c63df8ff77",
"value": 2000000,
"index": 61,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "9dd45637d06a047aeee0eb980332a88d5bdad5714aa8c6519552d554b5282388",
"outputIndex": 1,
"outputGlobalIndex": 50534281,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20451e6a391af3b38336460dfab25c283697256a195638eeb9627b3b687f42009a",
"sigmaType": "Coll[SByte]",
"renderedValue": "451e6a391af3b38336460dfab25c283697256a195638eeb9627b3b687f42009a"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e208a0060a30cdcf2fe35d1afadf1bb244512ef0328d509360d4cab261e33eddcc1",
"sigmaType": "Coll[SByte]",
"renderedValue": "8a0060a30cdcf2fe35d1afadf1bb244512ef0328d509360d4cab261e33eddcc1"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "37c5dc161566b329d726e7087ac93a892ca781a48b4e69ee3ecc859de252a463",
"value": 2000000,
"index": 62,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "a5a4745cec431f167059b1fd3e586e595d92e32f6c520decf3b40ebfb96b991c",
"outputIndex": 1,
"outputGlobalIndex": 50534286,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e2094dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865",
"sigmaType": "Coll[SByte]",
"renderedValue": "94dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e203c3be59856b76a15a37a2ca95f35c95ccbc95a4da7ac0b515b8579ba2ddb7df5",
"sigmaType": "Coll[SByte]",
"renderedValue": "3c3be59856b76a15a37a2ca95f35c95ccbc95a4da7ac0b515b8579ba2ddb7df5"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "25348eca45bfc42772079c866a347d9ed1f882cd43f14003886627929df62d9b",
"value": 2000000,
"index": 63,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "a612392fb04f4258711b7dcf95747699bef93399eb3a2454d3c7086d4a1df988",
"outputIndex": 1,
"outputGlobalIndex": 50534291,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e206e8d28288d55d4f3fa3da47932955e12a9f7fd9c5bb47668d706db3cccb7e28a",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e8d28288d55d4f3fa3da47932955e12a9f7fd9c5bb47668d706db3cccb7e28a"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20dfb7592b4d056e41f4aec1e9aa5b79f254f5fd953675cb369e6e9aa28c860e93",
"sigmaType": "Coll[SByte]",
"renderedValue": "dfb7592b4d056e41f4aec1e9aa5b79f254f5fd953675cb369e6e9aa28c860e93"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "03e024039d0b0dcc5eee41d20b11db69dff4321b6ed616d795c49fbdfbb3ad92",
"value": 2000000,
"index": 64,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "ac927ff38e856127821752deb8605c3cbbee32ccca8c191425056c4fb1109715",
"outputIndex": 1,
"outputGlobalIndex": 50534296,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e201f2544ae82ab043f2889c81ac9db7ab9d74bb4af631631b5ef2200879ee7fdb3",
"sigmaType": "Coll[SByte]",
"renderedValue": "1f2544ae82ab043f2889c81ac9db7ab9d74bb4af631631b5ef2200879ee7fdb3"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20b58572dbe53cbfb88956f2453a9a8e920348758624d36eca17f9815bd5493acb",
"sigmaType": "Coll[SByte]",
"renderedValue": "b58572dbe53cbfb88956f2453a9a8e920348758624d36eca17f9815bd5493acb"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f395f1edaa8be44e963ac2ffd972217576232c89360ba647d9c3fa3ce63d5f29",
"value": 2000000,
"index": 65,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "b2adecc481755ba3f68d5bb9fca7cb04a9dc0877a425db940906767eb20fb6d4",
"outputIndex": 1,
"outputGlobalIndex": 50534301,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e201d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20c31cb83f5be58720b313cdb9d69efcf7d4a4e66286feff4da8953dc4e32253b9",
"sigmaType": "Coll[SByte]",
"renderedValue": "c31cb83f5be58720b313cdb9d69efcf7d4a4e66286feff4da8953dc4e32253b9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6a682adc056b8bc3f08b45b8bc70c9a98e937a950df331b135db732090a6cc40",
"value": 2000000,
"index": 66,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "b5d4b9e809ad26d8d429106cd69144d59a3cf0348450412fe0a4cc788dc5f106",
"outputIndex": 1,
"outputGlobalIndex": 50534306,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858",
"sigmaType": "Coll[SByte]",
"renderedValue": "327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2052941900d3b047d23245b0ec846d74294f5f5ab45619401131f07d4336bd14e1",
"sigmaType": "Coll[SByte]",
"renderedValue": "52941900d3b047d23245b0ec846d74294f5f5ab45619401131f07d4336bd14e1"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "a5393990d00410e91793856631f67238e60f2da909b7372271e960681dc64a31",
"value": 2000000,
"index": 67,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "bad1156d64d1dc64faf06a74bc9a5908b5ebf1d36aa3c9bf09aef0018f6255c9",
"outputIndex": 1,
"outputGlobalIndex": 50534311,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2095fd7ccc35711b6abdbb65ee04d6f66a7036073e2489a0bd76a4fd448da28ea7",
"sigmaType": "Coll[SByte]",
"renderedValue": "95fd7ccc35711b6abdbb65ee04d6f66a7036073e2489a0bd76a4fd448da28ea7"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "88e0c98e4912300ce8579102ccb4e193f04c4e53088fc045b84c37b6e6cb4b8c",
"value": 2000000,
"index": 68,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "be28e1d0d5dc361f58db835e4b165986b791c7abcc0725baa3919e2d5ef48fbc",
"outputIndex": 1,
"outputGlobalIndex": 50534316,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e2087f5a101be45cefe086c96a68c92c8901806c3169c430dea014b640aabb0eac9",
"sigmaType": "Coll[SByte]",
"renderedValue": "87f5a101be45cefe086c96a68c92c8901806c3169c430dea014b640aabb0eac9"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20956bb86d1134a799c451fa2b1d4b4eff3be176b6047237b4b7a5a923b5802758",
"sigmaType": "Coll[SByte]",
"renderedValue": "956bb86d1134a799c451fa2b1d4b4eff3be176b6047237b4b7a5a923b5802758"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "820cd0349ef4a51412e8e1d27dcd2763b2e24145d813d27242e0d0909f8b109c",
"value": 2000000,
"index": 69,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "be562badfad3ad958da16b4371e80ada4ed34cb48a6960bdf816ec003d9c5e69",
"outputIndex": 1,
"outputGlobalIndex": 50534321,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308",
"sigmaType": "Coll[SByte]",
"renderedValue": "f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20b6a5ae59b070074b46d8ba2c61d6efd5aea7c796bd7b79cc845a9afa16822241",
"sigmaType": "Coll[SByte]",
"renderedValue": "b6a5ae59b070074b46d8ba2c61d6efd5aea7c796bd7b79cc845a9afa16822241"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "d3387f129788190b9a587fe31c0ed3eb0239a5675660f19383447eff13975003",
"value": 2000000,
"index": 70,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "c15e5874ca6c8a2249536a08b4d3e1ffc3d83aaee2224b8755b1f884795da42a",
"outputIndex": 1,
"outputGlobalIndex": 50534326,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e207c85fde0d6f95c49aeec5ac1117386c2b89717de5cdf20e82e86fe784e352cd2",
"sigmaType": "Coll[SByte]",
"renderedValue": "7c85fde0d6f95c49aeec5ac1117386c2b89717de5cdf20e82e86fe784e352cd2"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e208e4ccc3b8724c874604db4f464d8612533c0680db0b6a3f09e058bfe81b29de6",
"sigmaType": "Coll[SByte]",
"renderedValue": "8e4ccc3b8724c874604db4f464d8612533c0680db0b6a3f09e058bfe81b29de6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "2327962b41880c3409adbd81587c2dadcc026e11895d9810ca675bb7d090c1d1",
"value": 2000000,
"index": 71,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "cc5d4cefd7c71782e692efe88de3fe196b79d1e6d945628568f48058bfb40124",
"outputIndex": 1,
"outputGlobalIndex": 50534331,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20884a1b36838137057dc7e877db3131222ecc167c1a4a08ef7bb81c62a26f5715",
"sigmaType": "Coll[SByte]",
"renderedValue": "884a1b36838137057dc7e877db3131222ecc167c1a4a08ef7bb81c62a26f5715"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20027f94ef3393b2eb670f544299a5df1671e131ce934cbef3eaee82d503f5a706",
"sigmaType": "Coll[SByte]",
"renderedValue": "027f94ef3393b2eb670f544299a5df1671e131ce934cbef3eaee82d503f5a706"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "df941ab704da1a472dfae3de11631f4f42cea8e85263731b946e1cb8eefd2af1",
"value": 2000000,
"index": 72,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "cc86806e3fb3662afcc4843152746cb312955b263788147ccfd22e304d598aa6",
"outputIndex": 1,
"outputGlobalIndex": 50534336,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "93d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e203129ed1cf53897a432e543b081b0e1c3f1243a426b64c589ef5fd306d80d9ce5",
"sigmaType": "Coll[SByte]",
"renderedValue": "3129ed1cf53897a432e543b081b0e1c3f1243a426b64c589ef5fd306d80d9ce5"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "a6daf5fde6b6fc8300d39048977e184a1204bd3063809323a41254bd71d866e1",
"value": 2000000,
"index": 73,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "cd8688854415965f2ae034ec0cd1b76d03a91d755d2644164a7a4c331b7abd08",
"outputIndex": 1,
"outputGlobalIndex": 50534341,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "e823c39c23aad5017b9832e82d87d531ef30adc5093577a19dcd3b22bc4e1a55"
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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": 74,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "ce29a739688df1c50cd7f90a80057e4671c7329e826fa19d068409042610db4b",
"outputIndex": 1,
"outputGlobalIndex": 50534346,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e206015f62700f812c2c79249ad2bfa3f378ad443fdf925666cbd02fdad481ff0a7",
"sigmaType": "Coll[SByte]",
"renderedValue": "6015f62700f812c2c79249ad2bfa3f378ad443fdf925666cbd02fdad481ff0a7"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e206ba28cd22184d1bd8456894e41a282028ce958fe8bb00d5e821a0eb784023a8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6ba28cd22184d1bd8456894e41a282028ce958fe8bb00d5e821a0eb784023a8b"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f76e32816a5bfdbe60099f1f7594c6427a5b34663bc591ee51330683abbb00b5",
"value": 2000000,
"index": 75,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "d26d194e22b81e6d2553f383b274ae21afc2f055fab8c6c588b33e620d365be0",
"outputIndex": 1,
"outputGlobalIndex": 50534351,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20aa7c8b3b2504769432f5dfc91219e733d1b2ae9c88a6e479c2c600170bf5757d",
"sigmaType": "Coll[SByte]",
"renderedValue": "aa7c8b3b2504769432f5dfc91219e733d1b2ae9c88a6e479c2c600170bf5757d"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2098702c5709e1706a1a82396ad3c37f0a70512db0ccec57eb0fcc31d3cd1b8e9f",
"sigmaType": "Coll[SByte]",
"renderedValue": "98702c5709e1706a1a82396ad3c37f0a70512db0ccec57eb0fcc31d3cd1b8e9f"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "b91167f1542fac6632573413fcf50df059330f34b28d0a8798baa2941ad7198e",
"value": 2000000,
"index": 76,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "d2d9921c95e476426481aebd962b46c4b59df09e22f6ae0f62a520e7bbe231cb",
"outputIndex": 1,
"outputGlobalIndex": 50534356,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e201fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7",
"sigmaType": "Coll[SByte]",
"renderedValue": "1fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e20c2efb46e4da448dac2da0e66aeabefc246a75650720b005adb4671f2cb244d85",
"sigmaType": "Coll[SByte]",
"renderedValue": "c2efb46e4da448dac2da0e66aeabefc246a75650720b005adb4671f2cb244d85"
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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": 77,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "d6671ae991a2a1a6ede23d9c6f35c9731313b21eea063bad889393c699d0813d",
"outputIndex": 1,
"outputGlobalIndex": 50534361,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20fb78ce4375e2fe9b6abaf87e82c35528e8857be5ccf5b02de56c51bf20132be7",
"sigmaType": "Coll[SByte]",
"renderedValue": "fb78ce4375e2fe9b6abaf87e82c35528e8857be5ccf5b02de56c51bf20132be7"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20db49b772798b8172ac2dd1ce40412347fded8ff8e6a99d2715cb18eabbcf80dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "db49b772798b8172ac2dd1ce40412347fded8ff8e6a99d2715cb18eabbcf80dd"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "73882635324b81f243439f8d73771a40a49bb401e571d2882b378a9024790608",
"value": 2000000,
"index": 78,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "d6a421a581b3c75e730115c4d91510350aa30caf2cbc9fd98e96576321267f99",
"outputIndex": 1,
"outputGlobalIndex": 50534366,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e207845b379038839e73742082513897e2f9a98dca30e96705a3f7489d592509d2e",
"sigmaType": "Coll[SByte]",
"renderedValue": "7845b379038839e73742082513897e2f9a98dca30e96705a3f7489d592509d2e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6d817a541b93c7d1d5034ec6d33268a8e3256817804c9c3f86daaa5d87f3f485",
"value": 2000000,
"index": 79,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "d9a3a98c3476f4788e76971c88f191cda7b60c6068f6939ea89b2cbadc5908c4",
"outputIndex": 1,
"outputGlobalIndex": 50534371,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20db521a1953cc84dfede6527b941a8bca07230aafdcf0056961d459aa7b1f4f7e",
"sigmaType": "Coll[SByte]",
"renderedValue": "db521a1953cc84dfede6527b941a8bca07230aafdcf0056961d459aa7b1f4f7e"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20db381b55c593b146f7fcbb91e95f081c63cb6fe672b44bbfbcdcac9a26ae8766",
"sigmaType": "Coll[SByte]",
"renderedValue": "db381b55c593b146f7fcbb91e95f081c63cb6fe672b44bbfbcdcac9a26ae8766"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "8fd5754e15e8dbbf925693dbad4bf160a877ee38f65389302d556abe5f8212c0",
"value": 2000000,
"index": 80,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "e2b2ce0f9b0e289d0a6b38afb3a67609cca31da443e7feeb72f3d4187d7e676f",
"outputIndex": 1,
"outputGlobalIndex": 50534376,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32",
"sigmaType": "Coll[SByte]",
"renderedValue": "bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20fd32820f86962efa61f30daff84bcfc6639d3cc5b77a94fa71171f29c611a9f0",
"sigmaType": "Coll[SByte]",
"renderedValue": "fd32820f86962efa61f30daff84bcfc6639d3cc5b77a94fa71171f29c611a9f0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ceda320657babd1bf4063c3f4a3d9e49c24b1bbeeee995ae7a83e8bf728a04ba",
"value": 2000000,
"index": 81,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "ea4e83e24522315888b08b498feb8dae9ec2fbdeede537be03b37d37edfb4c9a",
"outputIndex": 1,
"outputGlobalIndex": 50534381,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20775df6d6db0307212c5afa022c474b07e6b59c99b7156db272338a853735e2fb",
"sigmaType": "Coll[SByte]",
"renderedValue": "775df6d6db0307212c5afa022c474b07e6b59c99b7156db272338a853735e2fb"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e207a146aead50dbb6bc050a555a63499fbf6a638bfa860ef56b29f1ceddbf27379",
"sigmaType": "Coll[SByte]",
"renderedValue": "7a146aead50dbb6bc050a555a63499fbf6a638bfa860ef56b29f1ceddbf27379"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "fb2cc857f9eaf5698b734ba7d2a774c9327c89720be808c6c8763778e534c9a1",
"value": 2000000,
"index": 82,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "ee65096fe1997cace4d7902d5ab92bbfe1bab19d08c72f8f1cc74c1690cd889b",
"outputIndex": 1,
"outputGlobalIndex": 50534386,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20fd143679ed97043e6728236f766050ebc56195273eabadd67eb5df2ae77757ee",
"sigmaType": "Coll[SByte]",
"renderedValue": "fd143679ed97043e6728236f766050ebc56195273eabadd67eb5df2ae77757ee"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20ce5a635692694a6927d678cf5dd1534196a3c7fd8f5c1c2923d8d4461c124f3d",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce5a635692694a6927d678cf5dd1534196a3c7fd8f5c1c2923d8d4461c124f3d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "597dd1ecaf5332937c80bb16386f286674583f3917bb7e3c1be4ea82ccce6fae",
"value": 2000000,
"index": 83,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "fd2979aec229bdf3f8a556a3578c80180c329d2e9d77b5326ab7e5277a36bdc9",
"outputIndex": 1,
"outputGlobalIndex": 50534391,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20309befbcdc22b7c549e1802f4a8e6036a64873a5c70395419f96cbd4b3b95ef5",
"sigmaType": "Coll[SByte]",
"renderedValue": "309befbcdc22b7c549e1802f4a8e6036a64873a5c70395419f96cbd4b3b95ef5"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20f1ab4a4d1737653713706b22f01b5f33189c9d8f495a87d353a0a04d525c827a",
"sigmaType": "Coll[SByte]",
"renderedValue": "f1ab4a4d1737653713706b22f01b5f33189c9d8f495a87d353a0a04d525c827a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "99b28855cfbbdbd1b13a5e05dd6ec832865ba24ef044071481af8fba14992048",
"value": 2000000,
"index": 84,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "151d6e58f5314393299a7e535757376f074d65e61db5212e6f09a9aecccdbe3d",
"outputIndex": 1,
"outputGlobalIndex": 50534396,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7",
"sigmaType": "Coll[SByte]",
"renderedValue": "fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e208cd9f7d549c0b3913302756128517348526927a64fefb3ffc631fae57c7794ae",
"sigmaType": "Coll[SByte]",
"renderedValue": "8cd9f7d549c0b3913302756128517348526927a64fefb3ffc631fae57c7794ae"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "f02ae954c6e998e247b8ecce9e943d5603a7e0d9039562f908e21fa3c11a7f99",
"value": 2000000,
"index": 85,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "23b4da89e35cd591249d1ef59b58a63a0804c380538998d0c88a0808d01cbb52",
"outputIndex": 1,
"outputGlobalIndex": 50534401,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0ab09974c63962a46326ba99448da5c29bb826ddb4773ba4a2f0deb0204a1bf6"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "40fe5ec62ae6f4bb014884bb4737b6b319a7ab2f4d5e4891e363a941841a056d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "860815add4e6bea7e601f3884ceda743ffdbe62ab96a0857440802ea9876efb5",
"value": 2000000,
"index": 86,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "4cbed04d5ac98152261b5e1bb9359ecd32ebe86e31281726663437cc1dc76162",
"outputIndex": 1,
"outputGlobalIndex": 50534406,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f",
"sigmaType": "Coll[SByte]",
"renderedValue": "581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20c75368d68b0a83fac20f78fc5ce447056c0866f90b12d882445a5d47b81f06c3",
"sigmaType": "Coll[SByte]",
"renderedValue": "c75368d68b0a83fac20f78fc5ce447056c0866f90b12d882445a5d47b81f06c3"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f444b400acb851dd3e10e1980e459c3cb2fca3e0250a0c1a23a37980630c686a",
"value": 2000000,
"index": 87,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "7582483aacde3c07e3d0e0f07ede8e8f9825b7d11386fcad45d1b351f6c1b660",
"outputIndex": 1,
"outputGlobalIndex": 50534411,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2018aeeab47d55f0f07f44e24687cd529b20feab32dda0ae9e1171d22abd9cde49",
"sigmaType": "Coll[SByte]",
"renderedValue": "18aeeab47d55f0f07f44e24687cd529b20feab32dda0ae9e1171d22abd9cde49"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2048f6befa88e3aeb636429d4e457eb42089f909b21b777c01262d6c202b77ec92",
"sigmaType": "Coll[SByte]",
"renderedValue": "48f6befa88e3aeb636429d4e457eb42089f909b21b777c01262d6c202b77ec92"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "ef9593ad558570df4d0db698ce2dacdcab07903570b6d679ac41bdb07ee5c4e3",
"value": 2000000,
"index": 88,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "775f84a97377be347b7999dcbe0792d74029b7ac26ff9de9376585a393c009cb",
"outputIndex": 1,
"outputGlobalIndex": 50534416,
"outputCreatedAt": 1623406,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
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"R6": {
"serializedValue": "0e2071e9af967a02cdb1a41b916d9d45fb2b6555739be3177f00cb6025869c53d355",
"sigmaType": "Coll[SByte]",
"renderedValue": "71e9af967a02cdb1a41b916d9d45fb2b6555739be3177f00cb6025869c53d355"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "a5111f554085e5530d89fe0b7b5ac03e776a62a4f47a5575cb627b429bb1d5be",
"value": 2000000,
"index": 89,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "7ef4a47f617cfd6487acbbd0fa9aa063cf73b2cf16f7a8634a8855b05c52f05f",
"outputIndex": 1,
"outputGlobalIndex": 50534421,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e2037b104e8763eb64be8a1775a5ee95135ecc1f5e0941a02031f1b9f2c2c0ed0e4",
"sigmaType": "Coll[SByte]",
"renderedValue": "37b104e8763eb64be8a1775a5ee95135ecc1f5e0941a02031f1b9f2c2c0ed0e4"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e2059aac2b1e3c2e1c1ed71931281cd0d5dfc7aa4163f395d9737c1e678d8258332",
"sigmaType": "Coll[SByte]",
"renderedValue": "59aac2b1e3c2e1c1ed71931281cd0d5dfc7aa4163f395d9737c1e678d8258332"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "968d994f95b54b70a2cb0c1861872d004df7e8c31d1994d63bd57e808c58db39",
"value": 2000000,
"index": 90,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "8bdd381fa88baaa8a284aa808f3d97f165be42d737e5826d1705c95739317062",
"outputIndex": 1,
"outputGlobalIndex": 50534426,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20d114141aca72e56eab859e29d74690560ac900b38169c4fe21439ee824ddb9cb",
"sigmaType": "Coll[SByte]",
"renderedValue": "d114141aca72e56eab859e29d74690560ac900b38169c4fe21439ee824ddb9cb"
},
"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20f2b4f789d1e570c18a388d6dc2eb11a8ab1268a352ec57e23be4800f86befe9f",
"sigmaType": "Coll[SByte]",
"renderedValue": "f2b4f789d1e570c18a388d6dc2eb11a8ab1268a352ec57e23be4800f86befe9f"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "e4eccd2b4016c3045e9e52641655655144b06c2008850352bedbead8bb04be76",
"value": 2000000,
"index": 91,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "4a8967af796965a427674b16fa0465fdb162830787c61854e12366c02741e5b9",
"outputIndex": 1,
"outputGlobalIndex": 50534431,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e206ec9d6e697910811ff55128761de199db6f1bec294ae63402a9cf8c738691b9b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6ec9d6e697910811ff55128761de199db6f1bec294ae63402a9cf8c738691b9b"
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"R5": {
"serializedValue": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20142187a05e3c92c0aebcc78a384e4919b856f2319d6104b1c32aef6d23817fb5",
"sigmaType": "Coll[SByte]",
"renderedValue": "142187a05e3c92c0aebcc78a384e4919b856f2319d6104b1c32aef6d23817fb5"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "a0c55d9fc9e17e3689fd5bb99f67ddfc5e8d545ef82e20fb078a71a2f1b2a046",
"value": 2000000,
"index": 92,
"spendingProof": null,
"outputBlockId": "cbe74ac1312832c83b84da417c1e1ebb2790e2699c477e19e60f12402b5cdcb5",
"outputTransactionId": "55410078678af29df879b7dfa51ec9020c0f7f9b371b227870576e66e49cf7ef",
"outputIndex": 1,
"outputGlobalIndex": 50534436,
"outputCreatedAt": 1623407,
"outputSettledAt": 1623409,
"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": "0e20504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "504a07ddaed1cc7f37492bb1e2c139ef0573fda07c6558172b6d09c7a5bd0f6c"
},
"R6": {
"serializedValue": "0e20f385e64cf912cc0fc78afff0e0b2f04989a2c2fbefabd38418678d642e6107d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "f385e64cf912cc0fc78afff0e0b2f04989a2c2fbefabd38418678d642e6107d0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "281ff16ed3081d576f51f23e8941129cdccf2673861da174cb51adb0896c3808",
"value": 2860287891,
"index": 93,
"spendingProof": "d8953d2ebd02cc4ad5a461af4b1bb191ae5b9f66d98772a8f9567954a280102f6c61ccfde6b860c96ba1dd2fc2935fc53e9325b550909f32",
"outputBlockId": "cc2f11b8e443db07884eff60cb13e2753e39b76e263c6fd49caa309313c3704b",
"outputTransactionId": "d5125e4ff49ee0bbf46c2b906abb13d588870c58ba5d57248b6f1d4b788f41f8",
"outputIndex": 2,
"outputGlobalIndex": 50533888,
"outputCreatedAt": 1623405,
"outputSettledAt": 1623407,
"ergoTree": "0008cd023a646fe1a98364670421ab6154f6f4d7986f4c97821734cfbdd7a8114512fbd2",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3a646f,c87a21,...)))}",
"address": "9exn4wdR2SReA7668vqNSen6c8KPqDs3RKwwEzZYTxq7QH5BwBX",
"assets": [
{
"tokenId": "b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33",
"index": 0,
"amount": 1,
"name": "WID-b2d33-QH5BwBX",
"decimals": 0,
"type": "EIP-004"
}
],
"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": "ad266ea17e65da1767d497b454d7a497734204713d84d6f4023bf45c03ced9de",
"value": 2000000,
"index": 1,
"outputBlockId": "68c26f588e13dcc052e74b523844b4cd4de7cf6b83e4983b24c7ae1a7a2b4fb8",
"outputTransactionId": "488558de92d386975f63cc86dfbbf7f90ae1f9d1cfeb96ee19e6037f6c3c23f2",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "05f401",
"sigmaType": "SLong",
"renderedValue": "122"
}
}
}
],
"outputs": [
{
"boxId": "b1a499a40ebe644d883153bce5be3ba48225efe8c182a58ea1dad47b5ae39d80",
"transactionId": "d0da18e4bf7921e04c278d09a2e4956424fa99ff7a9f83dd5a05b4a9a92f76da",
"blockId": "370a82feed29609c0db5c0cec3b0d80b3127352319a9246d05905156e0995600",
"value": 185010000,
"index": 0,
"globalIndex": 50534552,
"creationHeight": 1623411,
"settlementHeight": 1623413,
"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": "ZsPNMsGz8D8y11MAneZTVjJndCjgTUjPFBh5wF6ZNmMySHVDcBmMx2VxGFNCcMxCKDPkdPEzZp4bt5pgwrpZyKV6nmzCAh6SaX5ZnN2fL2X2UTuLvmuk6t8BqrxoiKHmqASttYk6xJPNabuF9ZNMYQBikFWDmq2jrxZS1MG6gQQ2Mx1MgXVvPs9ZkDTe8TykK4MuvQwtjaatjugK3FC5gsB4e4KiTcMPzreUkHvC8mZQGTtGkmHSbq8hkUDfa8MUMAka4oV3unyhgvx9MHjSDNaKWtqrWJpHCsQqPxvzPKohoYSNQt6H3V6ddw1dzGbBz8eKSbno5tEaLSryLDeMAbXhivALPZ3uCyWvx9BKFxSpuqCuQs9aXH7zKedvxzE6XRrrC2TZcWn5UinvbMNu3S4i5oTK2Y8WeVfoy5XHRbK7AL9w9pimJBp5Dx2UnhhHrWbeg9XyVZP7uCEqcUK3iVFmdG2euUa84Jbr7XVaE8v3sBa8LvYdxc6wAVfgPNNbQNxK7Y",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 279000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20db65566911a2368b29259616c8eb7232f3ef11215ca4b78eeb6eeaa99c0c48e3",
"sigmaType": "Coll[SByte]",
"renderedValue": "db65566911a2368b29259616c8eb7232f3ef11215ca4b78eeb6eeaa99c0c48e3"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[30393839323665386332643065373835346564643232363438303630353361373737303531383437376238383763333633396435313337353635383865316633,6572676f,62696e616e6365,3966435455384d3845423752595a7171584b346974387644686774677841416e3855424b566d77776d73564773585945684559,307862663864396131313132316366623838343631393964316535343264643335626631636435643030,00000005d21dba00,000000031910b5d9,000000000817aa06,657267,307865306538613034323432663335623935646336346230376530656165323361386534336137386534,34313863346338373066373336666237333539353034363132363035373566643231663231353764343436633663373466306436326631653463616432653266,000000000018c563]"
},
"R6": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
},
"R7": {
"serializedValue": "04ba01",
"sigmaType": "SInt",
"renderedValue": "93"
}
},
"spentTransactionId": "cfc7a56575bc611992089cc07bb0ed1695a6b185c8679732f7be7a71d1f5f7f5",
"mainChain": true
},
{
"boxId": "f8172ae9f33aa279a50ffb859da581e58d01e43ee30a76f55f0432d4cf253d34",
"transactionId": "d0da18e4bf7921e04c278d09a2e4956424fa99ff7a9f83dd5a05b4a9a92f76da",
"blockId": "370a82feed29609c0db5c0cec3b0d80b3127352319a9246d05905156e0995600",
"value": 2858237891,
"index": 1,
"globalIndex": 50534553,
"creationHeight": 1623411,
"settlementHeight": 1623413,
"ergoTree": "0008cd023a646fe1a98364670421ab6154f6f4d7986f4c97821734cfbdd7a8114512fbd2",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3a646f,c87a21,...)))}",
"address": "9exn4wdR2SReA7668vqNSen6c8KPqDs3RKwwEzZYTxq7QH5BwBX",
"assets": [
{
"tokenId": "b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33",
"index": 0,
"amount": 1,
"name": "WID-b2d33-QH5BwBX",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "528a7c950a97407da27e6f08db1d6f30d04305f413a17f0c82c814a76beb121f",
"mainChain": true
},
{
"boxId": "1e7aeb9563691b66b89c87aa0d735cde36e4b3be6a1eab9010bf997f97807163",
"transactionId": "d0da18e4bf7921e04c278d09a2e4956424fa99ff7a9f83dd5a05b4a9a92f76da",
"blockId": "370a82feed29609c0db5c0cec3b0d80b3127352319a9246d05905156e0995600",
"value": 2050000,
"index": 2,
"globalIndex": 50534554,
"creationHeight": 1623411,
"settlementHeight": 1623413,
"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": "269ccad99539a0c6fd2e03a2ec9b5e425ef8bc929e54bbfc1c0e6fc38a05f560",
"mainChain": true
}
],
"size": 4329,
"isUnconfirmed": false
}