Transaction
ID: 49db6eba80...4a0f
Inputs (113)
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:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#100
ca36324dc1b0...a871 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#101
0cc8b274776a...b22b Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#102
d676052abfb4...2c25 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#103
1a6e220ffac2...42e5 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#104
f31dd6ec8985...1f6c Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#105
4423ab8d388e...32a3 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#106
85c31d7a1634...8d64 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#107
2e6b941a4ce6...d7a8 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#108
f39c45fe87d1...eb50 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#109
e11c1cb699b2...ab16 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#110
f4de47fd2163...c0dc Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
#111
2efcf4569f1f...782a Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
10
#112
b00f2822d45c...e728 Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
4
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.22101 ERG
Tokens:
333,000
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
14.02
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 364,750
Total coins transferred: 0.22501 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000391 ERG
Raw Transaction Data
{
"id": "49db6eba80b2ce01e3e59b4f8c28290eea2db0cccbad810e4955944555e34a0f",
"blockId": "d62fb493a732c8b9cfa1ac928c96de111de4873e49a9cb6db7fd1a6f15918e06",
"inclusionHeight": 1408843,
"timestamp": 1733196836024,
"index": 23,
"globalIndex": 8170219,
"numConfirmations": 364750,
"inputs": [
{
"boxId": "d6196d5203fbd306b1358dd7661bf28299ef08d8c1ea440cee5f98553b23e951",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "a7b00728053dfa2e23c0c34d7450e4842bc7cd408b5289ef8f89893c0e75443b",
"outputTransactionId": "2725b282235036c9f41f936aba27484b60d221c253b2e0bb4cf6870d58657a51",
"outputIndex": 1,
"outputGlobalIndex": 44411326,
"outputCreatedAt": 1408832,
"outputSettledAt": 1408834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ddcf399a712ddfea9b6a311d602f88c29475b115e7f995d432459c44f098c035",
"sigmaType": "Coll[SByte]",
"renderedValue": "ddcf399a712ddfea9b6a311d602f88c29475b115e7f995d432459c44f098c035"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e205bda5afc3da1539181c0e4ced33de6bd0cc2c8833785b2b79943c57bc33d536a",
"sigmaType": "Coll[SByte]",
"renderedValue": "5bda5afc3da1539181c0e4ced33de6bd0cc2c8833785b2b79943c57bc33d536a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "164d830a399ce9295b684e1c62b8c4cc587c9a68b18f32c24e23837db4aa124c",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "a7b00728053dfa2e23c0c34d7450e4842bc7cd408b5289ef8f89893c0e75443b",
"outputTransactionId": "8cc5eba67b5da8d9418c195184bd5f587a41c3e6f29e362f0e26aca02924160c",
"outputIndex": 1,
"outputGlobalIndex": 44411330,
"outputCreatedAt": 1408832,
"outputSettledAt": 1408834,
"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": "0e20059e38729e1d06a02358f46a27bde7d5c77cfe1e8af9922a91b541386c009af2",
"sigmaType": "Coll[SByte]",
"renderedValue": "059e38729e1d06a02358f46a27bde7d5c77cfe1e8af9922a91b541386c009af2"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e202513b12a64c38093d1dbc8b532991f4cf56fd6075d6ce12df3ac0c58c3b820d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "2513b12a64c38093d1dbc8b532991f4cf56fd6075d6ce12df3ac0c58c3b820d0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "fbc160b1b0fc6a8070c04b4afdc5ebcdbfba25b1aa3a9fcda05d194d1a65ee93",
"value": 1010000,
"index": 2,
"spendingProof": null,
"outputBlockId": "a7b00728053dfa2e23c0c34d7450e4842bc7cd408b5289ef8f89893c0e75443b",
"outputTransactionId": "6949c3441897fb431015bc4509e06af108d974df69648cbc1aff4147b7483857",
"outputIndex": 1,
"outputGlobalIndex": 44411852,
"outputCreatedAt": 1408832,
"outputSettledAt": 1408834,
"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": "0e203766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "3766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20765fa7d6653a1cb98cf962f4c91bf91d0ad523ff70b882ed1368516fdb73f088",
"sigmaType": "Coll[SByte]",
"renderedValue": "765fa7d6653a1cb98cf962f4c91bf91d0ad523ff70b882ed1368516fdb73f088"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "322d1e509a5630179673fdfdecb5782d07e3dffbea67aeb520f291677b885d4e",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "97bad23d03911acbfc38903edd74e008df626274b661fd7ddb611e6cfb17d652",
"outputTransactionId": "8bb8ef9976bfa165077aba079d19d3256f816a87334ecd2241451e367c2ab524",
"outputIndex": 1,
"outputGlobalIndex": 44411862,
"outputCreatedAt": 1408832,
"outputSettledAt": 1408835,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ea17a62c608a9475a30f1ba345b82c2dd2c799d27dc4d4c9ba84bf7f282de3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea17a62c608a9475a30f1ba345b82c2dd2c799d27dc4d4c9ba84bf7f282de3d5"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e205f39262433c143f5251ab57dcbabcd9f0b01fc9e57a80ea4f447c628f6d96863",
"sigmaType": "Coll[SByte]",
"renderedValue": "5f39262433c143f5251ab57dcbabcd9f0b01fc9e57a80ea4f447c628f6d96863"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "a3492c719148f8005014d09d55a9b7c22e581103bbcaf0ec6ed463f7aa7352ac",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "97bad23d03911acbfc38903edd74e008df626274b661fd7ddb611e6cfb17d652",
"outputTransactionId": "db2c7aa36d8928b6a1b24c87803dbc6d1564cde41dadda393eac09efe064c46c",
"outputIndex": 1,
"outputGlobalIndex": 44411866,
"outputCreatedAt": 1408833,
"outputSettledAt": 1408835,
"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": "0e20742aab33ec1d5b1e29d0d76c31b75d93e60ab3a71f978bcf14e369c2134b3e4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "742aab33ec1d5b1e29d0d76c31b75d93e60ab3a71f978bcf14e369c2134b3e4b"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2080644e12e74f39808fc3f0d12b0327697fd4bab07280d3e6c1db0d3d6f926893",
"sigmaType": "Coll[SByte]",
"renderedValue": "80644e12e74f39808fc3f0d12b0327697fd4bab07280d3e6c1db0d3d6f926893"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "f69f3f29d7dfb7877b552f4e4e0c17322d6ff95ca40c851660ae904ebfefe3b1",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "9023b4f0e86d7bcbf947479e40b0d13581b47f1ce87b79b531bde0512d1122d7",
"outputTransactionId": "408884d916badffdf6a9636a917bbc2dbcad761a0e1610abd25d570bc99d65a5",
"outputIndex": 1,
"outputGlobalIndex": 44411910,
"outputCreatedAt": 1408835,
"outputSettledAt": 1408838,
"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": "0e20f3559bc59e4fb41ad36f0b213740410b4cb61f967968fee72f83d2560199ae84",
"sigmaType": "Coll[SByte]",
"renderedValue": "f3559bc59e4fb41ad36f0b213740410b4cb61f967968fee72f83d2560199ae84"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20e87a629641ff080d8738d90c121973339146b2b4ce3537007f32c1ea03a9d804",
"sigmaType": "Coll[SByte]",
"renderedValue": "e87a629641ff080d8738d90c121973339146b2b4ce3537007f32c1ea03a9d804"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e000d9e7efeb8d3c9160c3ef9c0ae2d0e00e723d27a5545a1af487c3fa0195fe",
"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "b47a2dbf1efcf51dc855e34110c659e3e7fb944de0e4b7dca771ffb64eaee0ec",
"outputIndex": 1,
"outputGlobalIndex": 44411959,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20c6c832a5da7aac3925ec870c16cb94156419e3b579b12252a94801d8bf365647",
"sigmaType": "Coll[SByte]",
"renderedValue": "c6c832a5da7aac3925ec870c16cb94156419e3b579b12252a94801d8bf365647"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20d67930af88912215335157ed5022dfffdc9625c5eb051d767395bc120780a4af",
"sigmaType": "Coll[SByte]",
"renderedValue": "d67930af88912215335157ed5022dfffdc9625c5eb051d767395bc120780a4af"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "580abdc73dc8d60bd5abb1c3b5d6774ca561ae6e477a82a7f46816e933da5719",
"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "7c0f67b90f13f8ed2821ab23be3ceb47b66f863d39248fb4102f706bd497ea94",
"outputIndex": 1,
"outputGlobalIndex": 44411970,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e201b532f49a3da89e577a27cad46cc15bb380a804af44bbbd6d3469ce87096d5bf",
"sigmaType": "Coll[SByte]",
"renderedValue": "1b532f49a3da89e577a27cad46cc15bb380a804af44bbbd6d3469ce87096d5bf"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20b92c4e2d7f2bd189c89113fd4c8a21a0a28e3743485b971dc567626454338073",
"sigmaType": "Coll[SByte]",
"renderedValue": "b92c4e2d7f2bd189c89113fd4c8a21a0a28e3743485b971dc567626454338073"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "575541c738e42e32898745c0d1c2f64e41e06defc4411b90f70e72538c6ff7b9",
"value": 2000000,
"index": 8,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "c00e45f4888fff313207ee372cd8193860cda5d999596ab01c09ab6ad02e36be",
"outputIndex": 1,
"outputGlobalIndex": 44411974,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20e9f3f56000a3f307582cd93fe52aa9afb7689b4007f22f1afd04c15d2c1e80c4",
"sigmaType": "Coll[SByte]",
"renderedValue": "e9f3f56000a3f307582cd93fe52aa9afb7689b4007f22f1afd04c15d2c1e80c4"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20e1bca8972b343263446977b13cfed4c4a318262d9834b6acf8fe7a9ff42dbbbb",
"sigmaType": "Coll[SByte]",
"renderedValue": "e1bca8972b343263446977b13cfed4c4a318262d9834b6acf8fe7a9ff42dbbbb"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "bee0732d50be9fbe1345766c7d1adef28fcaad0e83cfc8daccebf03504151f8e",
"value": 2000000,
"index": 9,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "c56c8454bcd5adf55d3078e4943fe11d0fd1343afa0a277364dfca35359ac8bc",
"outputIndex": 1,
"outputGlobalIndex": 44411978,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20aaacd6193733b8b185053bd09b2b35c9126a828f81e3cda5c41f45135cbb1d59",
"sigmaType": "Coll[SByte]",
"renderedValue": "aaacd6193733b8b185053bd09b2b35c9126a828f81e3cda5c41f45135cbb1d59"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20986c6084e0fe1a297bef77d944596b1ad52aede0ecf3b485cf48c8e0b6900a93",
"sigmaType": "Coll[SByte]",
"renderedValue": "986c6084e0fe1a297bef77d944596b1ad52aede0ecf3b485cf48c8e0b6900a93"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "cc986fa8f2c16e1c88e52fada7eb7315914c5e699802d8685286feea56914cd5",
"value": 2000000,
"index": 10,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "0542e4de34e312aa7c4c0b0e583e40df13a05532ad19ea8c801507d370caa201",
"outputIndex": 1,
"outputGlobalIndex": 44411982,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2019b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29",
"sigmaType": "Coll[SByte]",
"renderedValue": "19b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20528156f8516c8b057430c6e4eb8235c37f2b2edf37dbfaf171b0b259b89c5af9",
"sigmaType": "Coll[SByte]",
"renderedValue": "528156f8516c8b057430c6e4eb8235c37f2b2edf37dbfaf171b0b259b89c5af9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 11,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "0d0733ddb6fbb5408818495605eae237ea141deb23dc12c75497574d1f32e85d",
"outputIndex": 1,
"outputGlobalIndex": 44411986,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6b50c862a12ddc14eb9669032f924327b6d32eb69a4c617016121243c64bd55c"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e206f9b18491d7fcfc0ad924d4327ed7fb3a9ff0597456c416e77f3fa5c72b45cfb",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f9b18491d7fcfc0ad924d4327ed7fb3a9ff0597456c416e77f3fa5c72b45cfb"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "2c1e2e83a441f7b1cecb187797e935bf1f1b058bd9ac39dcc666417d156b78de",
"value": 2000000,
"index": 12,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "1387c0ec73ff9c9fab0cadd933ade139a028e533cc31e85238b9c78d10e3be14",
"outputIndex": 1,
"outputGlobalIndex": 44411990,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e204ccf99baa9ef1f7a72a9ff58e4da6ccd5a9b839c1cd152a3e2ba0bc719457e62",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ccf99baa9ef1f7a72a9ff58e4da6ccd5a9b839c1cd152a3e2ba0bc719457e62"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e201f4e02425b89bc179132d0b0efce27a7b62787d9d988149ac46626215ec702c2",
"sigmaType": "Coll[SByte]",
"renderedValue": "1f4e02425b89bc179132d0b0efce27a7b62787d9d988149ac46626215ec702c2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "05bfa0b6b47d83df4c9788df69ab290defd33f70d4bacd1e7a09d609d46ef744",
"value": 2000000,
"index": 13,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "19cfbd1bea37fa81604eb7888299572c6131f5185cced9b43125685d21fd8b42",
"outputIndex": 1,
"outputGlobalIndex": 44411994,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e209e8e898d814c6fa197d363a3b86c9dc83cf7da0653b34053ba9b7ad4a9915d3a",
"sigmaType": "Coll[SByte]",
"renderedValue": "9e8e898d814c6fa197d363a3b86c9dc83cf7da0653b34053ba9b7ad4a9915d3a"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e206cbcc6a597d3cead7ea93ae6618873c501889a5085e083720df299b20ed0f604",
"sigmaType": "Coll[SByte]",
"renderedValue": "6cbcc6a597d3cead7ea93ae6618873c501889a5085e083720df299b20ed0f604"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "49a155765a76b66397b8849a34ed893f0729ec290e5b4fe170d07dfe496f38c3",
"value": 2000000,
"index": 14,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "1cbfb53b620a923ec0a5b81041a4460654c4b05cf49bae7da8a1fc3dda0de201",
"outputIndex": 1,
"outputGlobalIndex": 44411998,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "4e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20ce6118b84487d7e02854ba0f383b5bc521b03597877e3db1e04f3e847dc5410e",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce6118b84487d7e02854ba0f383b5bc521b03597877e3db1e04f3e847dc5410e"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "21c8099a660f6e6cc61ec2dc633fa2e9598db588f27283179b47182dadf801c1",
"value": 2000000,
"index": 15,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "21fdbe6c0ef07c2d80ce4b26ac19450d34c11ae77aa93fa71d88f0b8fb7d19a8",
"outputIndex": 1,
"outputGlobalIndex": 44412002,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e209b52a11d592695b816cf389d2bc57a15fd64318c50bcef8672df7d323e763094",
"sigmaType": "Coll[SByte]",
"renderedValue": "9b52a11d592695b816cf389d2bc57a15fd64318c50bcef8672df7d323e763094"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "9549071cbc02a1d284aa81a92ecff010c76691fb784137ed41c1498979fd812b",
"value": 2000000,
"index": 16,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "25240bd10bc999e52717ee18f9614283a1e4eb9930382fb942ea5f1c5e3ca352",
"outputIndex": 1,
"outputGlobalIndex": 44412006,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20ff6c1d982c22f3ab091e7488f58d426557e6eb1f9b8d5822a03d7423ab6fcc5e",
"sigmaType": "Coll[SByte]",
"renderedValue": "ff6c1d982c22f3ab091e7488f58d426557e6eb1f9b8d5822a03d7423ab6fcc5e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "ce6d830e7705103a69113944c48bb43c6792f17a22ab29d7cceef8fe9f6d77f1",
"value": 2000000,
"index": 17,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "261f896334dcac9d197034c3909f3350e5ca35b061bfa3a9bae84e318a5aa6b0",
"outputIndex": 1,
"outputGlobalIndex": 44412010,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2092a7c171364ecec3926817b320af35a4830041fb3d9e71dbc38fbf5b177ab22f",
"sigmaType": "Coll[SByte]",
"renderedValue": "92a7c171364ecec3926817b320af35a4830041fb3d9e71dbc38fbf5b177ab22f"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20d8cbc03ac8fca01587070c2c3485938555c205d4547a5cbc9224f62ca8f0cd2f",
"sigmaType": "Coll[SByte]",
"renderedValue": "d8cbc03ac8fca01587070c2c3485938555c205d4547a5cbc9224f62ca8f0cd2f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e3c06a198f14556ff73140a91619953a820911a72edad00264499781af89394a",
"value": 2000000,
"index": 18,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "34a167c3441731b8a779967d960ba3f7413e19a55823c3c014b2e6a8804f778d",
"outputIndex": 1,
"outputGlobalIndex": 44412014,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2019c7bd4c2344bd6f1ad94acc826701cceb9a0dc0c7cf0463fd142036fd0ff380",
"sigmaType": "Coll[SByte]",
"renderedValue": "19c7bd4c2344bd6f1ad94acc826701cceb9a0dc0c7cf0463fd142036fd0ff380"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "13cea3e3cabfa35fd089b4981806e3820bbe45f1b4b934d1de10391f77a1989b",
"value": 2000000,
"index": 19,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "44429f450ea4d8672cab7e6376a940b9119962e3df9f99fdd05a4efafe6f9fd0",
"outputIndex": 1,
"outputGlobalIndex": 44412018,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e203b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e209fbea1d28e95bdee62b0e7e7e16c2017e5a7987eb33b7b7576585cde1e6e55fa",
"sigmaType": "Coll[SByte]",
"renderedValue": "9fbea1d28e95bdee62b0e7e7e16c2017e5a7987eb33b7b7576585cde1e6e55fa"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "3a0bfab10c0dd8c33215fb253461b401a151d03b38bd0aa30c1d9c4bc872cb8a",
"value": 2000000,
"index": 20,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "44c9a7b53b7dd9dd67df7dfc5d40d3af8e09b15fc9a40b42898b65a8e2ee6eaa",
"outputIndex": 1,
"outputGlobalIndex": 44412022,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e201d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20ca77ed4b7bca97c71bdc192cb94d61deef7970228e5518d58241b4af8816aec8",
"sigmaType": "Coll[SByte]",
"renderedValue": "ca77ed4b7bca97c71bdc192cb94d61deef7970228e5518d58241b4af8816aec8"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "24fe40bc190824899d41c418baf8e35cd07ee0bba2c43068a1113d3a268f5454",
"value": 2000000,
"index": 21,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "450d64642e15faf3b3b9ccfc04dd47a903541b164c08510f0bc2e687a792a7e4",
"outputIndex": 1,
"outputGlobalIndex": 44412026,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2046c266a044e977c0ab839f301dca45f4f35c3aba25965713523ce1f6df72b193",
"sigmaType": "Coll[SByte]",
"renderedValue": "46c266a044e977c0ab839f301dca45f4f35c3aba25965713523ce1f6df72b193"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20f714af1bc55975517b57a0a647d0169bc239f57d6f63ab36d60565ba0e1d9be4",
"sigmaType": "Coll[SByte]",
"renderedValue": "f714af1bc55975517b57a0a647d0169bc239f57d6f63ab36d60565ba0e1d9be4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "18bf50f80faae5adb7cc8d320815757a39ac1b82fc8a29d6e3d3dd37c1e893fc",
"value": 2000000,
"index": 22,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "4ba9c57aba51fc516247c9d944e121e1e861b420412de4afb7a5768b414d9239",
"outputIndex": 1,
"outputGlobalIndex": 44412030,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e205252ecb1f1f61787cce1dc38b5bc1b71f55fa8a606eca25b9b3f596932cf4ef6",
"sigmaType": "Coll[SByte]",
"renderedValue": "5252ecb1f1f61787cce1dc38b5bc1b71f55fa8a606eca25b9b3f596932cf4ef6"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20d6c445194fb6b2649a8e23f6f2e430771405dfd750ce8bac6eabf80fb2989a6d",
"sigmaType": "Coll[SByte]",
"renderedValue": "d6c445194fb6b2649a8e23f6f2e430771405dfd750ce8bac6eabf80fb2989a6d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ad5a20eb4965a47bff35aa0ecd8beccca8d78c48383ade5ce9437898e2c930fd",
"value": 2000000,
"index": 23,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "4f0019ca79d1fbf0016dd67cfef67731b0d82d13f853457deba7ef477e09fded",
"outputIndex": 1,
"outputGlobalIndex": 44412034,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e203b9aa597064dc8b0c58f7a9e1463269e80f4c69e49e133c437ef9d70e19fdf53",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b9aa597064dc8b0c58f7a9e1463269e80f4c69e49e133c437ef9d70e19fdf53"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20e7d3fb2128a348afc191ea175aebfa154ab8f99cbdb4fa019d5a5583e488d604",
"sigmaType": "Coll[SByte]",
"renderedValue": "e7d3fb2128a348afc191ea175aebfa154ab8f99cbdb4fa019d5a5583e488d604"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "8e8a582bf008105ea2e08308caaf09016a8b27412536816828bb113c5231bb98",
"value": 2000000,
"index": 24,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "543fd8911c7c35da904a4bef5441457a7b4d78543db9e09a44a813a3f09b5823",
"outputIndex": 1,
"outputGlobalIndex": 44412038,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20cacc2b189e0300a41a77a080699ff25b933eb71bad64297ecb56eeeea5855439",
"sigmaType": "Coll[SByte]",
"renderedValue": "cacc2b189e0300a41a77a080699ff25b933eb71bad64297ecb56eeeea5855439"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e204d977f0b0d2ed0926ef30c93ffb2cf0f0c0f16ae093ac677376a2d348c0d4e18",
"sigmaType": "Coll[SByte]",
"renderedValue": "4d977f0b0d2ed0926ef30c93ffb2cf0f0c0f16ae093ac677376a2d348c0d4e18"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "597c5dd406edfc1872f984626f3513ca6e12dbc6f159476f213fffb466450126",
"value": 2000000,
"index": 25,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "573b518bd77455d31e2bde57ef3b0317718701751c05914900fbff840497fca8",
"outputIndex": 1,
"outputGlobalIndex": 44412042,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2053e28b29c76583401b17e47678a76aa24b7a84ed4cd26f5766b944b9627636fb",
"sigmaType": "Coll[SByte]",
"renderedValue": "53e28b29c76583401b17e47678a76aa24b7a84ed4cd26f5766b944b9627636fb"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20d7e7a0f354e4a6ab8175f6981d79d9489ce7a6d036e6dfe5d2ee136e87aa7318",
"sigmaType": "Coll[SByte]",
"renderedValue": "d7e7a0f354e4a6ab8175f6981d79d9489ce7a6d036e6dfe5d2ee136e87aa7318"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "6616a4255dab07177b7a424cdfb17041261e7924943f43e11a240e01b3096bd6",
"value": 2000000,
"index": 26,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "574a9b5a4eb820777e178aaa620ba5b9641a905a2944ecd801f72bd8019b3510",
"outputIndex": 1,
"outputGlobalIndex": 44412046,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20f0347cb3d75c4fb1561e5b0f8490179290b2b930e9a699df5f0aae48e1a234bf",
"sigmaType": "Coll[SByte]",
"renderedValue": "f0347cb3d75c4fb1561e5b0f8490179290b2b930e9a699df5f0aae48e1a234bf"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e200af0d767ff7a214eae8b7202ffebad7dbaa28726d6b65ff41da247c1ad5a13bf",
"sigmaType": "Coll[SByte]",
"renderedValue": "0af0d767ff7a214eae8b7202ffebad7dbaa28726d6b65ff41da247c1ad5a13bf"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "11899d813cfdbc916a62ed28b095ea5df2747e6e540c0525a7534af7a9b1ece0",
"value": 2000000,
"index": 27,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "577e522473f0823b2a80a245f8399f116f01863269bbbff266bd5b517d5240e5",
"outputIndex": 1,
"outputGlobalIndex": 44412050,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2038813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e",
"sigmaType": "Coll[SByte]",
"renderedValue": "38813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20983ce2ac716fa2be2db5ecf682588680faf1b5646194731754716739cd9b742c",
"sigmaType": "Coll[SByte]",
"renderedValue": "983ce2ac716fa2be2db5ecf682588680faf1b5646194731754716739cd9b742c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2752409c86921ed895b60c556f06ba3baf3fa2c0b12e72aaaf60c49a4cce7e96",
"value": 2000000,
"index": 28,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "619ef12769d5fae6e176a177f5f72b91daf22af386c8b8dad533cdbd537e0bb3",
"outputIndex": 1,
"outputGlobalIndex": 44412054,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "50578332ebb8fb95c5b1a62410257c9982a0bd25d93b1ae6787ea95bb94e9757"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "4c8e6e954a208eef8615019e68efd4adba9294a7c12f4fe0b4a8206d32b4533d"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 29,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "6e0c3ecd1b72005642a9eb61ad486aa677d1c124839da578752cc8a4ee8cd508",
"outputIndex": 1,
"outputGlobalIndex": 44412058,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "77b15cdeebe0239ed033afdaf82d79243e646ebf402f0c7e4717637298f6c469"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "600b637a0e02230e1c947fbfaec83583d846c0b63bbb2bc3a618392a036578d1"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "8ea6d767e5490e67e640f775aa99c43ac6fea2314e46df53e735ebbfbb83e2ad",
"value": 2000000,
"index": 30,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "6e8669806716dd5d65e6510f891fb09ac49ab51b010192810ec9be3efaa1a119",
"outputIndex": 1,
"outputGlobalIndex": 44412062,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20c5d5eb50eccb1f76977d7e416757e506062bb46797f2bcaa60823fa03ee864ae",
"sigmaType": "Coll[SByte]",
"renderedValue": "c5d5eb50eccb1f76977d7e416757e506062bb46797f2bcaa60823fa03ee864ae"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20376d6a584182ddfda930dcc6161ee667e5a6370e030b3e9b89a18f226d018aca",
"sigmaType": "Coll[SByte]",
"renderedValue": "376d6a584182ddfda930dcc6161ee667e5a6370e030b3e9b89a18f226d018aca"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2de9a87ba23552600698d9a2a40e9d06c7aafc684c2686877684c96c8273c90c",
"value": 2000000,
"index": 31,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "706e43296a4a45abc4d8f42cdbd5d9c03f0d985ac5e7f0d7a7c3d1684cca6faa",
"outputIndex": 1,
"outputGlobalIndex": 44412066,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "db8e71a8aa08bc0c7630f53d6189aff5e2c5e6c97d794b7617c0e41701a26c70"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "462f92a7628bb6aa377bdbafa04297a0ea6f4a9e3a6bd99c3c603ad000b372e0"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "3917bcc39396531750621443535364a17bf95f64f4beef71f55d9c519c12e9a8",
"value": 2000000,
"index": 32,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "767c3a2e5b76bab009d3009f16a92e9bd056abbac6b3d93c4d0f8bcdc663276c",
"outputIndex": 1,
"outputGlobalIndex": 44412070,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e200b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a",
"sigmaType": "Coll[SByte]",
"renderedValue": "0b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20b24222750c2d941aa3925cac6583ed05f159eaa9ec9ae3b8ddc79be2eebe1ac2",
"sigmaType": "Coll[SByte]",
"renderedValue": "b24222750c2d941aa3925cac6583ed05f159eaa9ec9ae3b8ddc79be2eebe1ac2"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "3f31c421438d8b100dee61e05d3420c0df2f8712fc0e7d3667325bd64e4ae9e3",
"value": 2000000,
"index": 33,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "7985c9ba3e50cf9164e1cb83f1c2602b70e0909029e06a1c5e2b7c1d7ac355b1",
"outputIndex": 1,
"outputGlobalIndex": 44412074,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20635159e6aa47ccf232ad01ca2c74add48b5195d703ea24f4040155e18afd099d",
"sigmaType": "Coll[SByte]",
"renderedValue": "635159e6aa47ccf232ad01ca2c74add48b5195d703ea24f4040155e18afd099d"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20513927dfa58ec19d0c9bbd244b3e3e055a3a4de9ff503f28b8a03f542ab23aa3",
"sigmaType": "Coll[SByte]",
"renderedValue": "513927dfa58ec19d0c9bbd244b3e3e055a3a4de9ff503f28b8a03f542ab23aa3"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1d99c978e122edced0a55098db19a4f8d54dcfb9f2988c6be7565beb99b7d223",
"value": 2000000,
"index": 34,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "7a4a16786f38dbec8198f513f5dcaac311e89fe740a1e696a1e7e8a240c1ca57",
"outputIndex": 1,
"outputGlobalIndex": 44412078,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "451e6a391af3b38336460dfab25c283697256a195638eeb9627b3b687f42009a"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e207b9bb920cbf5fa7e5f31ae3b1f2b1f7c6a5fd4f9d14b088700f0437294982182",
"sigmaType": "Coll[SByte]",
"renderedValue": "7b9bb920cbf5fa7e5f31ae3b1f2b1f7c6a5fd4f9d14b088700f0437294982182"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "6da65f6178ef8c7cfae3ae93a47866b0d26be5dcc605a442f48aa6e7d5539841",
"value": 2000000,
"index": 35,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "7d5d71f4e0265492686044b6929abdc4f465a06645b82b65001a4936ef2322d8",
"outputIndex": 1,
"outputGlobalIndex": 44412082,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "77e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e206dc2944dabec524f257352f1665541d303dfc1fa605d16d31431825089f1c33a",
"sigmaType": "Coll[SByte]",
"renderedValue": "6dc2944dabec524f257352f1665541d303dfc1fa605d16d31431825089f1c33a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "c50a2d14be97f43eb7d4b6ea2adae7005d5e3e4cb6e03bb82c407881bede88d2",
"value": 2000000,
"index": 36,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "7eaa2ed2bb30c3ab995de3a9ad1f778cf1563368e28a9a80677d581ca2a47050",
"outputIndex": 1,
"outputGlobalIndex": 44412086,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20dea05e9796b8e58d3a7ab92de7463d5a5d365171ffa1b581249e5c55f187f3dc",
"sigmaType": "Coll[SByte]",
"renderedValue": "dea05e9796b8e58d3a7ab92de7463d5a5d365171ffa1b581249e5c55f187f3dc"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e209d88740511eb1e9b20a5739511d3ccb87f48ad9d78b2b7d8554dd7de64b2008e",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d88740511eb1e9b20a5739511d3ccb87f48ad9d78b2b7d8554dd7de64b2008e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "9a327f2ee2f0784913f86391e97ee54cdac0d690df477ea032b01dc6dcb0697b",
"value": 2000000,
"index": 37,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "82570cf2c047f41e1818dfe6a822f4bb136e7dee6b757e7d12b194d72e7b5981",
"outputIndex": 1,
"outputGlobalIndex": 44412090,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "88708d05bd78d4d8b4195f210903fc8bccb2eacd2c3bba6c8c7302ddba29ca92"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "08ee4d8e6ef429d66180b466e3e335a3ca6094e6e6a2c9af462dbdc8bf706277"
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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": 38,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "85704577b3b5e358ac5104e9be3f28091ff8d52bc2e5a829f37d10ab29c8aea0",
"outputIndex": 1,
"outputGlobalIndex": 44412094,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "3aa7ed9864521180387dcc059e46225ada5116a86758bc2b958873bbd7d19366"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0a023affb22309a227f88b94accb14ee0e863f01caa7b762bec53acafccdff9d"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "df1a977f83f5842fe84148ed465518d60d33f27f100e21e7736efd87baac1247",
"value": 2000000,
"index": 39,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "8862b455e78bc1a26cb6c379ca2d360f1ee47fc3e7a77522892686827fadc5be",
"outputIndex": 1,
"outputGlobalIndex": 44412098,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20fbb2edec8b218ca0462a0347473c366a7f102e061f5a4785e8ed701c297e07ec",
"sigmaType": "Coll[SByte]",
"renderedValue": "fbb2edec8b218ca0462a0347473c366a7f102e061f5a4785e8ed701c297e07ec"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20ffc9e62e0933ec53f414b38be9adb51bd534c4d01918e565f2daa11b3745ce5c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ffc9e62e0933ec53f414b38be9adb51bd534c4d01918e565f2daa11b3745ce5c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f635f9826864013bc6dbf482df8d0e3f82b5cc0711e96e49ae71f1c063522521",
"value": 2000000,
"index": 40,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "8bc74233147d3b4011bae19d7479206ef4ee61dc55bcf221bd412bedcb389660",
"outputIndex": 1,
"outputGlobalIndex": 44412102,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2025006e6ba04dedc3938b074ec5d051b3ae25f4d6480d6b24203102bb413cadea",
"sigmaType": "Coll[SByte]",
"renderedValue": "25006e6ba04dedc3938b074ec5d051b3ae25f4d6480d6b24203102bb413cadea"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20a645bd930ed99b6fc93c08091b76b49b0052eb38bbb8d2a540eea2c0b91476c6",
"sigmaType": "Coll[SByte]",
"renderedValue": "a645bd930ed99b6fc93c08091b76b49b0052eb38bbb8d2a540eea2c0b91476c6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "f5ec3793cbc5b8d2029de6dd1bbf5c7cc040fb91ec2d94782b8046a1f28652da",
"value": 2000000,
"index": 41,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "8cdbd556377fa08ae2e1235506d3ee0957b45fbe6b34c888938d48c31b07e7fb",
"outputIndex": 1,
"outputGlobalIndex": 44412106,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e201c7b69b98fbd72077801e215dbc02c1f782d270b49023f705f3230238032e1e3",
"sigmaType": "Coll[SByte]",
"renderedValue": "1c7b69b98fbd72077801e215dbc02c1f782d270b49023f705f3230238032e1e3"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "753fb7e95082f43a58f306cb08fdf28a338db26f260adaef1e3b4a507e8c4d4c",
"value": 2000000,
"index": 42,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "8d307cb4bbd7fa536683979447ec45dcfba232c41fb6b3491bd8bbe0f57ce4f8",
"outputIndex": 1,
"outputGlobalIndex": 44412110,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20386d1c70deb3315854bda324ecf573fc224ab8b78b3c9bb62309592450c91047",
"sigmaType": "Coll[SByte]",
"renderedValue": "386d1c70deb3315854bda324ecf573fc224ab8b78b3c9bb62309592450c91047"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e209e8f749005a092ec6489f78013386c1c601773f261bff0022d1e989d368a1100",
"sigmaType": "Coll[SByte]",
"renderedValue": "9e8f749005a092ec6489f78013386c1c601773f261bff0022d1e989d368a1100"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "efd07afcc55b637c940823a24ae4520286b262aa1f407eccd35fe039689405e0",
"value": 2000000,
"index": 43,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "8f90568c2e9a723194e339ecdc4ff4156c99e99a9f661df5b2da836e0605efc1",
"outputIndex": 1,
"outputGlobalIndex": 44412114,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20177d2ab87b520ce087a394ae20fcc6f221e24f747f664f6c30961288c951d05a",
"sigmaType": "Coll[SByte]",
"renderedValue": "177d2ab87b520ce087a394ae20fcc6f221e24f747f664f6c30961288c951d05a"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e208f5f8e0eb64fe9a268255a5dbefa21989e72eaf76e455695b5d2433bf04f48f8",
"sigmaType": "Coll[SByte]",
"renderedValue": "8f5f8e0eb64fe9a268255a5dbefa21989e72eaf76e455695b5d2433bf04f48f8"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "37bed5bd10a4bada16b73bc7dfa700ad8c85bca32ef293e1c81ee66766427547",
"value": 2000000,
"index": 44,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "93484bf8b5514012c6c6103782f2954e1821859e61b3f146a55142231477ffca",
"outputIndex": 1,
"outputGlobalIndex": 44412118,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20cd3863c3556e8da87295be7fc2c1d61fd0189a324d323bf60e607553f4a4e2f9",
"sigmaType": "Coll[SByte]",
"renderedValue": "cd3863c3556e8da87295be7fc2c1d61fd0189a324d323bf60e607553f4a4e2f9"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2061baa4cd8d6483d978610954d7489f0a99f7131fc71480e2799f4e38220369c6",
"sigmaType": "Coll[SByte]",
"renderedValue": "61baa4cd8d6483d978610954d7489f0a99f7131fc71480e2799f4e38220369c6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "4cb13c06a3d1051ffa23f077d935b0e5e64c3fbca0b003544cd069199e2c761e",
"value": 2000000,
"index": 45,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "937a41c169d07469d80433494d6cb367647974b69ab4542216c90b16629adadd",
"outputIndex": 1,
"outputGlobalIndex": 44412122,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308",
"sigmaType": "Coll[SByte]",
"renderedValue": "f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20ae67903924974a54526e64ee4718e2e0cfb3c9ff6f4e78ce1673d2bb85123fe0",
"sigmaType": "Coll[SByte]",
"renderedValue": "ae67903924974a54526e64ee4718e2e0cfb3c9ff6f4e78ce1673d2bb85123fe0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "224887224b95e04347f67de1feec4d82fd0c88d80993c9714e384807888de129",
"value": 2000000,
"index": 46,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "9c14f99eb16e1895492bc310b7c0e8ff04b25bbd6c6cf58740db5c08546bc654",
"outputIndex": 1,
"outputGlobalIndex": 44412126,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "6a572ba3399722fc5020dfe1443990135cd044893c9e7a72056d613232fa61e8"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f4efa6750e0bce3e42db6b5750d6cadd842fa315cd62782a18fa5da160ab9ce1"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "002687a11e4c997d583790bb73767f75143875befaeaad7205659b3cdef4bd99",
"value": 2000000,
"index": 47,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "9c52e1dcce0ae64e2435946a47828318f3f612ae4f9ae40f15a8171b8a8c7f42",
"outputIndex": 1,
"outputGlobalIndex": 44412130,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "93d73a59f111c37a6e9853fb85ba075264f330dc3b416d2778b7939e3bb6591e"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20445a02640ed072f4b2e2bd0d31aeefe720f81d345fefb00c28ee9f55957b2957",
"sigmaType": "Coll[SByte]",
"renderedValue": "445a02640ed072f4b2e2bd0d31aeefe720f81d345fefb00c28ee9f55957b2957"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 48,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "9f72ac6b4443e8e947b8bdf2296cedffd827eb7d2cdd2d2c6babd72748ea52ff",
"outputIndex": 1,
"outputGlobalIndex": 44412134,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e208ff3e3b368707fba5f6373db7423ab3486b5317bb6d703de4561a4e25ed6c3e6",
"sigmaType": "Coll[SByte]",
"renderedValue": "8ff3e3b368707fba5f6373db7423ab3486b5317bb6d703de4561a4e25ed6c3e6"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20a8151f53fc800a57bfb8d8281d4a5b3f912afc91e7bb56351e8780a861fcf313",
"sigmaType": "Coll[SByte]",
"renderedValue": "a8151f53fc800a57bfb8d8281d4a5b3f912afc91e7bb56351e8780a861fcf313"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "bf8da47f5e5903e744b52cdb7bd29f7a5f2ac273a9875b590fc019cfead2ce46",
"value": 2000000,
"index": 49,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "ae591099ad96d47feb508642a4811c27576158c46ea025eb5eeb36b7174a49ac",
"outputIndex": 1,
"outputGlobalIndex": 44412138,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2094dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865",
"sigmaType": "Coll[SByte]",
"renderedValue": "94dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20c7a93c5eebd5261c4355462b47d12fb21b2b64b2e59723f4a75b9e060d9ed39a",
"sigmaType": "Coll[SByte]",
"renderedValue": "c7a93c5eebd5261c4355462b47d12fb21b2b64b2e59723f4a75b9e060d9ed39a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "fae6bebf6f197eb2c41a01f70b253a8cb8e415c3c25ad7ab4f9e9a6b3f77b622",
"value": 2000000,
"index": 50,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "b1a854baa930d92229671368e1e509bfbb8f9eac9a4eac996b1937fc08d152c5",
"outputIndex": 1,
"outputGlobalIndex": 44412142,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20793848c21ce3e6a7bdfa8613f66f9f99879304a3a4b7fc233228fa959c113fd8",
"sigmaType": "Coll[SByte]",
"renderedValue": "793848c21ce3e6a7bdfa8613f66f9f99879304a3a4b7fc233228fa959c113fd8"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20be5afd2ad6b2dfce4305c9d3c5382d8c249b33a5a37cda3f7f7d5db84d96531b",
"sigmaType": "Coll[SByte]",
"renderedValue": "be5afd2ad6b2dfce4305c9d3c5382d8c249b33a5a37cda3f7f7d5db84d96531b"
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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": 51,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "b502ec68f45ce8d78fac3af1bc10a6a2020865bbee6653d7ea8edb07b7da73be",
"outputIndex": 1,
"outputGlobalIndex": 44412146,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e202e87fa19207174d6ad50b3de5eb06cbabe2f2519b41f20b40e88e34a17ed7db4",
"sigmaType": "Coll[SByte]",
"renderedValue": "2e87fa19207174d6ad50b3de5eb06cbabe2f2519b41f20b40e88e34a17ed7db4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "b5dc311debb0c037fcb493145207b203419e5928f7e30cc6e9d04954d08c447d",
"value": 2000000,
"index": 52,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "bd57094dd04346b271c09adffa3901b61ca6bd5e667d1912deec257f9675bcd9",
"outputIndex": 1,
"outputGlobalIndex": 44412150,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e207530181a4d253cee45656066ca410df26360a9a8618ffe265afa7b25066c4337",
"sigmaType": "Coll[SByte]",
"renderedValue": "7530181a4d253cee45656066ca410df26360a9a8618ffe265afa7b25066c4337"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "03e946ee000198be0c949468a2077a8ce7304b511724ec455dac9c7cf7ab7519",
"value": 2000000,
"index": 53,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "c20ca9f979f2eac67794acc877bbeb7cba670e4752daeb40c0980e7c6722ab35",
"outputIndex": 1,
"outputGlobalIndex": 44412154,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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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"sigmaType": "Coll[SByte]",
"renderedValue": "d289df8aee844cdc1a6b7c84efe280a8d7c51dc6412c3e36b64d4ee71f4cb916"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "d86134521bcb315a2916c15f379f9c4b02c3ff000a6d313f4c3a246ec79c93fa"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "5349edefa43499627b37afddc8137a09177eb1f60270b3dc1cdd7b1bae59a313",
"value": 2000000,
"index": 54,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "c6037d6abd4ba96e97856d12d2d6d72e04db39382429e9184834f0c00c7bb88f",
"outputIndex": 1,
"outputGlobalIndex": 44412158,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858",
"sigmaType": "Coll[SByte]",
"renderedValue": "327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20fcbd643d73e6cb21aa111faf38ce1e401c766920ab76944ec4fe3d5606359895",
"sigmaType": "Coll[SByte]",
"renderedValue": "fcbd643d73e6cb21aa111faf38ce1e401c766920ab76944ec4fe3d5606359895"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "178fce8ba3ea21367aa56d8defbee68c3a8921a7e8455421fc7e185c70548caf",
"value": 2000000,
"index": 55,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "c94881f2fb749cf8a60907f815d0d603e90240742527ee65e578cc7eec1b18d1",
"outputIndex": 1,
"outputGlobalIndex": 44412162,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20f3996e1ea0db8fb08ad54adc396da83dd158c571d60f8241f480afbc2a606617",
"sigmaType": "Coll[SByte]",
"renderedValue": "f3996e1ea0db8fb08ad54adc396da83dd158c571d60f8241f480afbc2a606617"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e204b6e087e7f931effe44d683cb05086df0e105ec8da20df3d22227cd21bcc7d72",
"sigmaType": "Coll[SByte]",
"renderedValue": "4b6e087e7f931effe44d683cb05086df0e105ec8da20df3d22227cd21bcc7d72"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "79b13b2c4fc9ce6a6973f27b1881d7bb6d3d83837994fabd9504c588f304b831",
"value": 2000000,
"index": 56,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "cb90c0549445067d35041b4518070758ad669a34bf6869cc70f50d2a4ac6b7c3",
"outputIndex": 1,
"outputGlobalIndex": 44412166,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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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"sigmaType": "Coll[SByte]",
"renderedValue": "9fd5177131205e443ba2f60bcbc6f23954e5c75fa58038fd6547394fc7f951cc"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20e290adf2dc921a6c7400c241a56ed9d39f7bf6c31b3f0f0c1c6f6f64286b6560",
"sigmaType": "Coll[SByte]",
"renderedValue": "e290adf2dc921a6c7400c241a56ed9d39f7bf6c31b3f0f0c1c6f6f64286b6560"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "885fbdfc973be3d449db26aa4d7a95d65f0226f41f9ab441248cf77855e2ab8d",
"value": 2000000,
"index": 57,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "d4698d67a6e8ce85ecc3302e8dfeb83bcf6ba292f820a8cf00c55cb3c1a20b10",
"outputIndex": 1,
"outputGlobalIndex": 44412170,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f",
"sigmaType": "Coll[SByte]",
"renderedValue": "581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20429bc13f039c259ca8b3fd4f192da8929da9c6d9b2d1c28784f6ed66227bde8d",
"sigmaType": "Coll[SByte]",
"renderedValue": "429bc13f039c259ca8b3fd4f192da8929da9c6d9b2d1c28784f6ed66227bde8d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "4dba9572f58e2216e2e9453e414264b845e6e03e7b7222506ebb0d505c3b9def",
"value": 2000000,
"index": 58,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "d8ea2a1749c0c09b8973f86fdc80b09727c26a26f92eef936f807172ff2bf769",
"outputIndex": 1,
"outputGlobalIndex": 44412174,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e205de7c58e90454fe60345df0afa28bcdc61a34e112d4e541d5b58da6a89d45ea2",
"sigmaType": "Coll[SByte]",
"renderedValue": "5de7c58e90454fe60345df0afa28bcdc61a34e112d4e541d5b58da6a89d45ea2"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e207d1d6ca96a9044187d1463243fc3784f811f5eb42304c5f46ca0a72edd1cce92",
"sigmaType": "Coll[SByte]",
"renderedValue": "7d1d6ca96a9044187d1463243fc3784f811f5eb42304c5f46ca0a72edd1cce92"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "ef6102d0f80457293507b442b37a27edf0e364f29ce2a71e05fc10e0f1e38d6a",
"value": 2000000,
"index": 59,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "da6351d82af2994bc95fb53a977654b3a788fc8c9bf638155179203da1b49a6a",
"outputIndex": 1,
"outputGlobalIndex": 44412178,
"outputCreatedAt": 1408838,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "2cb49b8ebf41f1679770487ddeeb997ae6c0242a1c14de26935906d711054c07"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20aabe5bb4c2d88949e5931d5a729aefc54dcdf554c1c36d42718e0a7eb73407be",
"sigmaType": "Coll[SByte]",
"renderedValue": "aabe5bb4c2d88949e5931d5a729aefc54dcdf554c1c36d42718e0a7eb73407be"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "667557f4dd6071d2645467daa6e70720293475a075df05ccf6dce86d5aceb0a6",
"value": 2000000,
"index": 60,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "daa80894e2cb5ecabf9820173cb3c2fa40b492afcb357ca0534e4b0486873abe",
"outputIndex": 1,
"outputGlobalIndex": 44412182,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20dfdbb50d5860af988cee979add06c9420fa8c3453f950a644f29afd58b0448dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "dfdbb50d5860af988cee979add06c9420fa8c3453f950a644f29afd58b0448dd"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20e957dfc16a9afd1585a20ea71e80da050b3899a4fd392df0dd7e6b14a485be8a",
"sigmaType": "Coll[SByte]",
"renderedValue": "e957dfc16a9afd1585a20ea71e80da050b3899a4fd392df0dd7e6b14a485be8a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "9ee0cd86fb7687b05b3a5a4ab45c5f6cab459335341effa3785a15ed664e705d",
"value": 2000000,
"index": 61,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "de28a1469b70b21b5e057a03f69be25abae6e7d9e1aea6abbf5f3f01cedc7cac",
"outputIndex": 1,
"outputGlobalIndex": 44412186,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e203ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08",
"sigmaType": "Coll[SByte]",
"renderedValue": "3ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2057fc1cdf930a30902670b5976c9b8f484f8bc660b8f77d18774d05a82b27669d",
"sigmaType": "Coll[SByte]",
"renderedValue": "57fc1cdf930a30902670b5976c9b8f484f8bc660b8f77d18774d05a82b27669d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "423d5f8e74e634815a51870bb9458d92374b8cea6771cbb696c1b1e21a80812e",
"value": 2000000,
"index": 62,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "e02669e6f92cf5eed0c99e0d885df6a7c044daa51a95fc337972dbf63b6fb14c",
"outputIndex": 1,
"outputGlobalIndex": 44412190,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20c4cf3f7379f193a4093d3016a5a437170e2293c176b7e1058fe2ef43089391d9",
"sigmaType": "Coll[SByte]",
"renderedValue": "c4cf3f7379f193a4093d3016a5a437170e2293c176b7e1058fe2ef43089391d9"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "3506870ab93adc411b38c7ae9b4122bfbfb08d04a04d91c48f7089636c7e107e",
"value": 2000000,
"index": 63,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "e153050b3a82f6a399ba20d00e523e745adf28ba1cc0f3015c7b1ef75154dcaf",
"outputIndex": 1,
"outputGlobalIndex": 44412194,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20717c8a1a0ff297176cf024f5a41bd95e71ff2cce0fe3a0cc007cde80a69ab2eb",
"sigmaType": "Coll[SByte]",
"renderedValue": "717c8a1a0ff297176cf024f5a41bd95e71ff2cce0fe3a0cc007cde80a69ab2eb"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20e5cb0b23ebbeee01071d2eb4947f9afea0c64d600753d4ed3fad15131239827b",
"sigmaType": "Coll[SByte]",
"renderedValue": "e5cb0b23ebbeee01071d2eb4947f9afea0c64d600753d4ed3fad15131239827b"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "436cd1c4945ec00754ab0b1690f9b32b4bd6bf46bf185d487293134ff3786e12",
"value": 2000000,
"index": 64,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "e437c97a79dac818cda7402104c6232b2a05b4e06d5d8181fe026c7a93487a6b",
"outputIndex": 1,
"outputGlobalIndex": 44412198,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "bfc372a6d2ac00cc08dbe822ee10e55a15ac224b15255f6fd884a488ed515220"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e207407d1bbff7b1e26d901621707cabfea2d8753d6afc1406ab5aa0e720cc9e8a2",
"sigmaType": "Coll[SByte]",
"renderedValue": "7407d1bbff7b1e26d901621707cabfea2d8753d6afc1406ab5aa0e720cc9e8a2"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "aeba6375c6561fe0130d31a4ef82c766dacd448e5afd140fd269abb5da2a24b2",
"value": 2000000,
"index": 65,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "e50fea1fd80baa8a9a660c7ac061258b9bc8c5be27db0623d745fb648f785ffd",
"outputIndex": 1,
"outputGlobalIndex": 44412202,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20309befbcdc22b7c549e1802f4a8e6036a64873a5c70395419f96cbd4b3b95ef5",
"sigmaType": "Coll[SByte]",
"renderedValue": "309befbcdc22b7c549e1802f4a8e6036a64873a5c70395419f96cbd4b3b95ef5"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e203c83fa2bc100460121a70131820826d74aa1d73cc3d6ba076f3a062629c4ec66",
"sigmaType": "Coll[SByte]",
"renderedValue": "3c83fa2bc100460121a70131820826d74aa1d73cc3d6ba076f3a062629c4ec66"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "abdb727d8692d1b75413cd78677df9db23da6682115103364353cb6c00864ebb",
"value": 2000000,
"index": 66,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "e6e67ce6687f9973d925af1697693fd82d49e3b75d329e7ddf6a395287c542bf",
"outputIndex": 1,
"outputGlobalIndex": 44412206,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20be0549204c8f714745f598437ba63f81a4b8cd4ad7599e444dabf9abf3041c1e",
"sigmaType": "Coll[SByte]",
"renderedValue": "be0549204c8f714745f598437ba63f81a4b8cd4ad7599e444dabf9abf3041c1e"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20d23b8a7018c3a944159830d4211a7f84d570445f16574701ebf99de57bd33ea0",
"sigmaType": "Coll[SByte]",
"renderedValue": "d23b8a7018c3a944159830d4211a7f84d570445f16574701ebf99de57bd33ea0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "875e7a566253a664545238fd163f31bf3e694335a9accd002c10d12f448e1784",
"value": 2000000,
"index": 67,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "f1dc9e33c6bc8db1e571ea17339a6e67c497dbdcb6d6d220ee04dd51079b74a6",
"outputIndex": 1,
"outputGlobalIndex": 44412210,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e20c0075069e800d4797f924008c3d69add76586cbd1f418da370acb16710e4fc5b",
"sigmaType": "Coll[SByte]",
"renderedValue": "c0075069e800d4797f924008c3d69add76586cbd1f418da370acb16710e4fc5b"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "c77e516df6b22ad3d501103a883a8eeca76a99912da5f83ed500dd2ea56dc50c",
"value": 2000000,
"index": 68,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "f257c8922857a6f0625824ceb9979e55a96ada3a874173f0c47d0b51303689f5",
"outputIndex": 1,
"outputGlobalIndex": 44412214,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1fee26b7fea6ffc4ed5dece56093b4a5d4fd8a80da5756cbf14e46b719d25fd5"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "3ec2a410167662ab5710498e5e9228c07b467109a4a1c2c17f1a882c000aa6f8",
"value": 2000000,
"index": 69,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "f462bc03f0f1471bfb843f4eb3984a2b20ca651133feee61fb0171d526c83146",
"outputIndex": 1,
"outputGlobalIndex": 44412218,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7",
"sigmaType": "Coll[SByte]",
"renderedValue": "fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20fd335bcef250c6c4e951d18bca8443f52c0f4ac2a7257026ef81bfc91f4e21c8",
"sigmaType": "Coll[SByte]",
"renderedValue": "fd335bcef250c6c4e951d18bca8443f52c0f4ac2a7257026ef81bfc91f4e21c8"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
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{
"boxId": "f951d8e8038313e7110460788d815b860b2dca7569c6c8533e5fd19520153210",
"value": 2000000,
"index": 70,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "f5b06bf003b489950facfd028d301f92cfc66c26727786226c29b6a1f39392ef",
"outputIndex": 1,
"outputGlobalIndex": 44412222,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20329d66895b8d9c84947bfe3d72335158ada0fdd8ac8643f836c81ec85785e01a",
"sigmaType": "Coll[SByte]",
"renderedValue": "329d66895b8d9c84947bfe3d72335158ada0fdd8ac8643f836c81ec85785e01a"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2042f4410808a02f419d5dc8dccb52b9079ce44f287604d05d0fee140f23f9f7d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "42f4410808a02f419d5dc8dccb52b9079ce44f287604d05d0fee140f23f9f7d0"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "cb4514a9b515631d41607247a8ee83d125256c23ca7a4639eae2313f271a0f74",
"value": 2000000,
"index": 71,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "f7af8b9aba4328b475bfda9fd1f2d22ce1b78b7548a52a88199256badc02e8c5",
"outputIndex": 1,
"outputGlobalIndex": 44412226,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e206e8d28288d55d4f3fa3da47932955e12a9f7fd9c5bb47668d706db3cccb7e28a",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e8d28288d55d4f3fa3da47932955e12a9f7fd9c5bb47668d706db3cccb7e28a"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ee6079aedd2537335b9aec5ac15d63acafeb84d5b745b803f5597f420ad93ab1"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "7312f740cc37a10b7bcb35a85718637c4be5cb4e60d56d5b3c31554a3b2938e5",
"value": 2000000,
"index": 72,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "ff11d3f4fb78a64c8267b136423aa8f44c77b5e470417fb9e858f9f013b3ff3e",
"outputIndex": 1,
"outputGlobalIndex": 44412230,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200088840f331eedf07d309096c075208670801d18d730ba3fb2bb341bd5c094ca",
"sigmaType": "Coll[SByte]",
"renderedValue": "0088840f331eedf07d309096c075208670801d18d730ba3fb2bb341bd5c094ca"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2096fe6a126188967852e0e8dd0fd4123f7930151c9c793dcf4ef4d06551972ad2",
"sigmaType": "Coll[SByte]",
"renderedValue": "96fe6a126188967852e0e8dd0fd4123f7930151c9c793dcf4ef4d06551972ad2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "a99e1c23dc93b78dae107cf7e8610ab123f3121498ff638625eb22b5759ab042",
"value": 2000000,
"index": 73,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "15cf4a0427549d2f72b104d9457d128213e31cc3a8ce4705cb21822aa6d1412b",
"outputIndex": 1,
"outputGlobalIndex": 44412234,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e2099eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0",
"sigmaType": "Coll[SByte]",
"renderedValue": "99eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20f531c621d4b6549fd55ce2db7384daa12c298d5df379f8c08d23864719fe1a87",
"sigmaType": "Coll[SByte]",
"renderedValue": "f531c621d4b6549fd55ce2db7384daa12c298d5df379f8c08d23864719fe1a87"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "edd1326c3d32e0b48a03e87db6c7f5ae94758fdfaef1a596917908b52326d1d8",
"value": 2000000,
"index": 74,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "7cd4198e4675128dc145dd3c3c0efc76f3eed72772842c9e375890c2fa3ac6dc",
"outputIndex": 1,
"outputGlobalIndex": 44412238,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6696280d3218decd0ba11a5a954542de86db8915e6ed6210b02ad6edb5d15ff5"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b58bb8498d54f3a015b6547c03c5e80fe317bfede8322b380538e296ea031d4a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "cbb4cb326cdc4d5044954e949d4f7dc3077899ba06f17a0736b3be73b29425f4",
"value": 2000000,
"index": 75,
"spendingProof": null,
"outputBlockId": "ba0c1c762d18a8be72af99d57b380a18a010569ef626616eac8e66135cad18af",
"outputTransactionId": "e3b2267185afe724e1bd21b8b943fa2e39971bd47ef722328bb1debe24fea1ae",
"outputIndex": 1,
"outputGlobalIndex": 44412243,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408840,
"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": "0e20ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2010f0a57292e606c07066a5288d1030bc7977a23dc37cfa58cf2c6770b639dbc6",
"sigmaType": "Coll[SByte]",
"renderedValue": "10f0a57292e606c07066a5288d1030bc7977a23dc37cfa58cf2c6770b639dbc6"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "8a6cb1046ade749005d3784c54e8bfd4061e4d663508e80213cd97a9af0c169a",
"value": 2000000,
"index": 76,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "1579e8873124037c42ae1fe50fc1bd6b76a6a2bb831ad7374a96649eb28d124c",
"outputIndex": 1,
"outputGlobalIndex": 44412302,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e20d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5",
"sigmaType": "Coll[SByte]",
"renderedValue": "d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20aaa6a18a679b2303ffbac185bb2873cc474d795f2768487fba918c1eafeb8b00",
"sigmaType": "Coll[SByte]",
"renderedValue": "aaa6a18a679b2303ffbac185bb2873cc474d795f2768487fba918c1eafeb8b00"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "1179f0d9bf9741d2f9fb022a802925271ceffc7a8a8d9742a27522e498b82e2c",
"value": 2000000,
"index": 77,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "38fba7cc9d778f51019df7da3f2066695d31e3f2a6db0e34fd26ad4d1b621c52",
"outputIndex": 1,
"outputGlobalIndex": 44412306,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e20942c960c9d7843f883cc67b87ed328042109968180ab180e14a42f0600df5f41",
"sigmaType": "Coll[SByte]",
"renderedValue": "942c960c9d7843f883cc67b87ed328042109968180ab180e14a42f0600df5f41"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20f098069b09b3738d11fa73fd86392ab55b6535b771854e3bece50760b3156ffe",
"sigmaType": "Coll[SByte]",
"renderedValue": "f098069b09b3738d11fa73fd86392ab55b6535b771854e3bece50760b3156ffe"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "a90e31848451fe3a37a62ce0a926bba56fbeceb1ae5e029c67e0f268c108045c",
"value": 2000000,
"index": 78,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "a460cf0c974621230a68fea82f2a21b2bac9a1177ec6c103f59ce71607dfe395",
"outputIndex": 1,
"outputGlobalIndex": 44412310,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20c8f111814bd27e1cb36e77993640dec2b75552ca0637b9a7896ef6eec8a41df2",
"sigmaType": "Coll[SByte]",
"renderedValue": "c8f111814bd27e1cb36e77993640dec2b75552ca0637b9a7896ef6eec8a41df2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d559029c52dbc29eac77c4a3e12e5f205ce14091e989912b8441bd7f10c6bbad",
"value": 2000000,
"index": 79,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "e775c832da4413fe44e237c59b4660696bc1a8c416a0be2c7659751c7e8f9344",
"outputIndex": 1,
"outputGlobalIndex": 44412314,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b188db683fdbacca5a356503878c7a4f017030569aed3dd1b665403f64e245c4",
"sigmaType": "Coll[SByte]",
"renderedValue": "b188db683fdbacca5a356503878c7a4f017030569aed3dd1b665403f64e245c4"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20b5fffe20f4502c7ba402955526d8243de23511fef7ee46c2c3656747eb1bbf31",
"sigmaType": "Coll[SByte]",
"renderedValue": "b5fffe20f4502c7ba402955526d8243de23511fef7ee46c2c3656747eb1bbf31"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "22b1abf3c5c8f547bb99c3e4578e72bbe64862158ffcd16f858342fafeda0096",
"value": 2000000,
"index": 80,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "ebef1288e615e317197186d4dc75bbdf16ab3c7ef83d5f955a4020e69912afca",
"outputIndex": 1,
"outputGlobalIndex": 44412318,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e206f3ed92c3f867beec54f5dff6dd8682854eefb9eed2fa9c22f4d2ec5d8fdd050",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f3ed92c3f867beec54f5dff6dd8682854eefb9eed2fa9c22f4d2ec5d8fdd050"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2051081ecf0f0f923f91c3719b175320ebbc9bc18757f3ba4bac21881c56474c0c",
"sigmaType": "Coll[SByte]",
"renderedValue": "51081ecf0f0f923f91c3719b175320ebbc9bc18757f3ba4bac21881c56474c0c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "b9621caaacdb366701c85cbde3c468028b9b1a544df821980d48b33ac819284e",
"value": 2000000,
"index": 81,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "f411ddbb595c8453d4b9e7715cd1f6e75c5baf6e43be04b2d6cf028887fecd1c",
"outputIndex": 1,
"outputGlobalIndex": 44412322,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201a0f3106b93d5720b1d9e423e0a5f69e293bc01f673d28fac737975811322b26",
"sigmaType": "Coll[SByte]",
"renderedValue": "1a0f3106b93d5720b1d9e423e0a5f69e293bc01f673d28fac737975811322b26"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20e30e3a2f4a1264d97d075f158367e154df8ad2abdf0d7ae25d137792702f543a",
"sigmaType": "Coll[SByte]",
"renderedValue": "e30e3a2f4a1264d97d075f158367e154df8ad2abdf0d7ae25d137792702f543a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "de10ce2561502df0b88effe2d7294937169b926e0b3d5d9de64820825cfdbd62",
"value": 2000000,
"index": 82,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "00fa6d0667c67d4dd9f553a70597a4f2a26a1ff01aaa5ef6f4950e2187af2f7a",
"outputIndex": 1,
"outputGlobalIndex": 44412326,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8be41df9ef870f6dda3c200b2d4ee25cba722257a9e36aea0033a6687e3972bb"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "aae755f5c156bff0614f8c241874e23818105c25dc4aac5ee5e8a362d43faced"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "80b868de52bb13b760b44790bb314428ba6f1d76540937bf7312e577bbec9079",
"value": 2000000,
"index": 83,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "0df4cc314abdb5db07b8925407ba764e1d2c11db68870ee5f5ebb0bcc598e782",
"outputIndex": 1,
"outputGlobalIndex": 44412330,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7194c835bcc86f273b5e6ae41434949d81a2904ef00d0199eeb473340332128e"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "151a548eaf3a647e789181e2653e0ce86c0c65c65247b5a611d0b3ec708d6cf9"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "931ded1a123e13d48ec5f088cf05e93500032ad4f11cc1c4e99fc974e5cb9e69",
"value": 2000000,
"index": 84,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "2fe86d01f561bd8f60b74ba76e22e4ccbdde267d829a7a933ff845299f191a89",
"outputIndex": 1,
"outputGlobalIndex": 44412334,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e2093d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9",
"sigmaType": "Coll[SByte]",
"renderedValue": "93d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20d327ea8472d967ef06a490a986bf4eff175f4258bf89097b8cfc10b30f6bc508",
"sigmaType": "Coll[SByte]",
"renderedValue": "d327ea8472d967ef06a490a986bf4eff175f4258bf89097b8cfc10b30f6bc508"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d9c5075f1a268282054cc2660e0ba66a576635ed702d261c91c074cf1504d5c5",
"value": 2000000,
"index": 85,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "387eab96fb7deb64d92583f403d6d284c10bee07baa96bb7df6ea0e64a923055",
"outputIndex": 1,
"outputGlobalIndex": 44412338,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e20333810ee13abfd784cfce3cb6e4fc9d2eb6e75d4884937892de6fbbc8d3a7ce6",
"sigmaType": "Coll[SByte]",
"renderedValue": "333810ee13abfd784cfce3cb6e4fc9d2eb6e75d4884937892de6fbbc8d3a7ce6"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20b731d448e7bfb5f87337fc54ca6ff08e88872735c35ddcd33e24f1f24e38f485",
"sigmaType": "Coll[SByte]",
"renderedValue": "b731d448e7bfb5f87337fc54ca6ff08e88872735c35ddcd33e24f1f24e38f485"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ca207d5518295d38182a9b044ce7aab97ffa79ce223e776187183a330425a075",
"value": 2000000,
"index": 86,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "3b15798a0fb9ab7d7acf7143cd61ce4faf416216f0838339b0666ef20660fb2d",
"outputIndex": 1,
"outputGlobalIndex": 44412342,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e20047f4bd7bbad0ee6e4dc2d6577fe878cb7d2bf780691a83b3f9dac406eb8588d",
"sigmaType": "Coll[SByte]",
"renderedValue": "047f4bd7bbad0ee6e4dc2d6577fe878cb7d2bf780691a83b3f9dac406eb8588d"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "396ca296db601162896da522e158d9e857ab5555392e28c754af8e7d3d52ef04"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "22bf0bcf019dfb84315f68150ce64f661244671c776c264bd01e2e77f3775b9c",
"value": 2000000,
"index": 87,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "48f2c9af37917ee4e99450f8840ea032c298c243190a02f850fdd58df7b1f3d8",
"outputIndex": 1,
"outputGlobalIndex": 44412346,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e2029beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "29beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2053934937a0bbc43a61895a8dbb5c26dc08f0f6d519505d95633e400340b3d2a0",
"sigmaType": "Coll[SByte]",
"renderedValue": "53934937a0bbc43a61895a8dbb5c26dc08f0f6d519505d95633e400340b3d2a0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d75523968d89869dc2c56134da8a3fb3a796a0f65b2b46435580fe947d6771a2",
"value": 2000000,
"index": 88,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "4c87d94d81a9d0a24028c145a74406b66cf92676ce69cb26f97d33a698ba101b",
"outputIndex": 1,
"outputGlobalIndex": 44412350,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e205a0514d1b96b31a1b0bfaff718a2f441d2bc4326700588c44f5ca8949a0d3fdf",
"sigmaType": "Coll[SByte]",
"renderedValue": "5a0514d1b96b31a1b0bfaff718a2f441d2bc4326700588c44f5ca8949a0d3fdf"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "5c5e39ca46d87e794ec4fac6c6a1933061028c47522ae1b37226e35f0a585b6b",
"value": 2000000,
"index": 89,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "4d023d21be28c7324dd79f91a45debf42082af6cf9ff93b96534afde288fcfc6",
"outputIndex": 1,
"outputGlobalIndex": 44412354,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": {
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"serializedValue": "0e200aedbdc717d62dd354f6b59640f85a6f9b6ffababa1235b2d71738fd8517341e",
"sigmaType": "Coll[SByte]",
"renderedValue": "0aedbdc717d62dd354f6b59640f85a6f9b6ffababa1235b2d71738fd8517341e"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e201134fecadca10473ddc0d76fc1a7839bed31b3170e2a518b77f6aa1e129cbabd",
"sigmaType": "Coll[SByte]",
"renderedValue": "1134fecadca10473ddc0d76fc1a7839bed31b3170e2a518b77f6aa1e129cbabd"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "946469245765249c474b76bacfc0b7aebad5544283d0808b6557deccb740d2ba",
"value": 2000000,
"index": 90,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "50d6fb43fa90aeb6e719c3a1232ea7173d11daadeeaa05091b9c5452bacd036b",
"outputIndex": 1,
"outputGlobalIndex": 44412358,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e208e4ad9d51dc7163937eaeb6760c53bfb4d64d7369580d056ae32df6795c2dd4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "8e4ad9d51dc7163937eaeb6760c53bfb4d64d7369580d056ae32df6795c2dd4b"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2063ff4607f1e22331a4cd164f33c492275450b4d4d50605e6ce285d574b22a562",
"sigmaType": "Coll[SByte]",
"renderedValue": "63ff4607f1e22331a4cd164f33c492275450b4d4d50605e6ce285d574b22a562"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e37eb8db000009a8c2cc1719f600df506e5f95bcb30d3bfea5b286f09a5e7ccf",
"value": 2000000,
"index": 91,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "5d155598aeb7a39a5c8ac2426d298143c38dd9d5fac6419315372440d2627b44",
"outputIndex": 1,
"outputGlobalIndex": 44412362,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e20f881c6baffd9bd4b1fb7241b8cf8cab0058ccc89f66a873ec64c8d1a0e0596bd",
"sigmaType": "Coll[SByte]",
"renderedValue": "f881c6baffd9bd4b1fb7241b8cf8cab0058ccc89f66a873ec64c8d1a0e0596bd"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20f0c9c05429f329c4b509ac65e6b716d882162380b651620401ab99dc899a38ec",
"sigmaType": "Coll[SByte]",
"renderedValue": "f0c9c05429f329c4b509ac65e6b716d882162380b651620401ab99dc899a38ec"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "03fe688a56b55da0c2f60b1942460dcf9feafae326c3e4df6df62dd1100a7da9",
"value": 2000000,
"index": 92,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "64d1af188fa77f79e009640b770e88f344ceb82e068a79bef1988707997fbef3",
"outputIndex": 1,
"outputGlobalIndex": 44412366,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e203497f5106ba457314a058d4ae85c7b99de8c5de7d3c0801c68a72cce274a2671",
"sigmaType": "Coll[SByte]",
"renderedValue": "3497f5106ba457314a058d4ae85c7b99de8c5de7d3c0801c68a72cce274a2671"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e207f585485506ef69cacd90e265ef5e84cdd1656bfaeeb1920bb4c4d9b3b6c8331",
"sigmaType": "Coll[SByte]",
"renderedValue": "7f585485506ef69cacd90e265ef5e84cdd1656bfaeeb1920bb4c4d9b3b6c8331"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "d7c78824000feabf312e2efc6ccfc5ac55c6f642d6ab7c33999af42e21022ef9",
"value": 2000000,
"index": 93,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "65ce39a73948d6f9fbd8761d67d36bf0f97b0d7baf5978d92168c03a78310740",
"outputIndex": 1,
"outputGlobalIndex": 44412370,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205e9116ec8a5fe109fcb28d46fc9b3f5e6aa8a37d88cdbf0ba1d6f7f0c974b0f7",
"sigmaType": "Coll[SByte]",
"renderedValue": "5e9116ec8a5fe109fcb28d46fc9b3f5e6aa8a37d88cdbf0ba1d6f7f0c974b0f7"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e207799315f5322467713fbd0c3cb7f1d5a37732e5465b4a219ee7cec4afea9ac06",
"sigmaType": "Coll[SByte]",
"renderedValue": "7799315f5322467713fbd0c3cb7f1d5a37732e5465b4a219ee7cec4afea9ac06"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "338d0a39d957bb9160e0fa7a7826a397938be766eff710125ef72af2cfc477f1",
"value": 2000000,
"index": 94,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "746f7ed31767ae80f60ced3de81c8ca5e4c52a04b8d74d07adc85b88d8012d96",
"outputIndex": 1,
"outputGlobalIndex": 44412374,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20bb5f676dea40d456552f6cbdb963e0426387c7c0c64c7512b5d35418f3759d0d",
"sigmaType": "Coll[SByte]",
"renderedValue": "bb5f676dea40d456552f6cbdb963e0426387c7c0c64c7512b5d35418f3759d0d"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20087d49fd6fc226ae59865d5ccb91727bb4cb501674051fd00c283eec37b7988b",
"sigmaType": "Coll[SByte]",
"renderedValue": "087d49fd6fc226ae59865d5ccb91727bb4cb501674051fd00c283eec37b7988b"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "8f1191b917ad78a55ee34b19ff075b439476d72a77b041acd202540a918fb1b1",
"value": 2000000,
"index": 95,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "8d32584af4fb689fc5896c5972d962dfb564ea5e4e58cecb00aa12bbca2438b0",
"outputIndex": 1,
"outputGlobalIndex": 44412378,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e209f63cf59c815cdb6b2d06998e2516cb43e82654dc4bcfdbc442eda75f2189d17",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f63cf59c815cdb6b2d06998e2516cb43e82654dc4bcfdbc442eda75f2189d17"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f2cf66f1dda80df09040954ba5cacf076ca001c06d53a9567f372ce80034ad00"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "5eff76afbd7d496d30becf1771cccba73d14718655465cbd83f3bac217a6b022",
"value": 2000000,
"index": 96,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "90ca991c1a835244a8abeec76afff09ce560c72728c1af44fb14313d082f9178",
"outputIndex": 1,
"outputGlobalIndex": 44412382,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e209d57b0fed60a6f7c06e57cdf6c8fe88f5df4f44dbd41d5f43ed4b971aa13c017",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d57b0fed60a6f7c06e57cdf6c8fe88f5df4f44dbd41d5f43ed4b971aa13c017"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e201a0ede9d4363bb5e4233b9ea46bfd14e1cf45f24620bceea7f24c8948dae00bf",
"sigmaType": "Coll[SByte]",
"renderedValue": "1a0ede9d4363bb5e4233b9ea46bfd14e1cf45f24620bceea7f24c8948dae00bf"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "11654e247dcaf8f78a5435de656bc440ab7d44492206a5a3c4166dfa0628ecce",
"value": 2000000,
"index": 97,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "916b3e3bd61b6b00d8000e814aed94d4ceb7566a1c119a6450efed6b82e2269e",
"outputIndex": 1,
"outputGlobalIndex": 44412386,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e200dba2cea2e980eaaf6f1e8cf6485b2801671c13b6f975d392b4920b71488a3b3",
"sigmaType": "Coll[SByte]",
"renderedValue": "0dba2cea2e980eaaf6f1e8cf6485b2801671c13b6f975d392b4920b71488a3b3"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20880c759ea34921c9b650c47c5639b3c51ee7b78b40492d8f82d19245b92246ab",
"sigmaType": "Coll[SByte]",
"renderedValue": "880c759ea34921c9b650c47c5639b3c51ee7b78b40492d8f82d19245b92246ab"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "7009b9828b5a68b2a53b8f99174b5d64ae0bed22171c5c9ffd1dae6fd40cfb40",
"value": 2000000,
"index": 98,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "a25618361c254448375491f59ffad15d565f4a8fcc8bf2743cd2baf5b17b0b00",
"outputIndex": 1,
"outputGlobalIndex": 44412390,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e206b9a44a2b2d58f7049a288c911d955e8d70558ecb2705437f908beb783ddce00",
"sigmaType": "Coll[SByte]",
"renderedValue": "6b9a44a2b2d58f7049a288c911d955e8d70558ecb2705437f908beb783ddce00"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2067542919bb62fd764ebadf17c0821659257518c613adba9e36e3dd5da01fadcd",
"sigmaType": "Coll[SByte]",
"renderedValue": "67542919bb62fd764ebadf17c0821659257518c613adba9e36e3dd5da01fadcd"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "45081dfb12d75f84fadedb176f26586700eebc284b9b7008ee8ec46b2803130d",
"value": 2000000,
"index": 99,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "ac5ea2c191644ac8cc60546b53b3b944731badba608bbbba91087caf7270762a",
"outputIndex": 1,
"outputGlobalIndex": 44412394,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e20dd6e1620c63423f28efdbed8f59fb5109dab5adaa70c0e7dcecc7abb2ae7fa9e",
"sigmaType": "Coll[SByte]",
"renderedValue": "dd6e1620c63423f28efdbed8f59fb5109dab5adaa70c0e7dcecc7abb2ae7fa9e"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2045aa95ad4c7671c951a3e54ef9b7088910fdbce4abaa38144584a6d92ee1d036",
"sigmaType": "Coll[SByte]",
"renderedValue": "45aa95ad4c7671c951a3e54ef9b7088910fdbce4abaa38144584a6d92ee1d036"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ca36324dc1b052d378cb154e1becfd9873a0fd9fc461c0e7d2e412546f03a871",
"value": 2000000,
"index": 100,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "b41cf08b85baefc7b280ae009ebb525728e9a4fd91824b68d1f6be5223d30b67",
"outputIndex": 1,
"outputGlobalIndex": 44412398,
"outputCreatedAt": 1408838,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7d2f5dd0dce52c5e42b935cb986095bdfac1c6102018f4c715d830e736d96876"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a6cf6fb3a32e28522642d7d360d5cd8c34cd67f9f178e95be61e74a31cc30c69"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 101,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "b5a51c70318651553887aa64db51e497c5fb48fa03583a8a69f4cc66fa2a6b0a",
"outputIndex": 1,
"outputGlobalIndex": 44412402,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "cc0718bb04b077042722255a5bc711370613aedd2983b214b83d562f630d00d0"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "50886f785d6238c43a94c476d7b30215f2757af6cae9b761a387ca67cf383ea1"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "d676052abfb457045f63ca49250e0c5a4b8e30b922ee921985e3796393882c25",
"value": 2000000,
"index": 102,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "b9d279f485b00ef7b77441af9b85ab598655f23b95de4cbfdd05cf8ce1c435f4",
"outputIndex": 1,
"outputGlobalIndex": 44412406,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e2074d14ee349bc54781627bafddea455bf045eac5941d64e2175704a150b8a070d",
"sigmaType": "Coll[SByte]",
"renderedValue": "74d14ee349bc54781627bafddea455bf045eac5941d64e2175704a150b8a070d"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e206029a6dce755e289e223ed8b8407fdc1715963538649cc97c1ace498754fd47c",
"sigmaType": "Coll[SByte]",
"renderedValue": "6029a6dce755e289e223ed8b8407fdc1715963538649cc97c1ace498754fd47c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1a6e220ffac28f867911687bc88edabad8ee4d284f8632d039a1a5a7d22a42e5",
"value": 2000000,
"index": 103,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "c06759b0855093d3e12cde71537ed23f50bd1dd191f92c3d61821cebcb8e3b67",
"outputIndex": 1,
"outputGlobalIndex": 44412410,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e20e4826206c7a12594a7eb4b44cac46968127e9d39748919bdb01a232c3b7ea537",
"sigmaType": "Coll[SByte]",
"renderedValue": "e4826206c7a12594a7eb4b44cac46968127e9d39748919bdb01a232c3b7ea537"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20066dcf9845b3b646663d65f53eb23ecda42096d2e57202c5ad948b15c528d48a",
"sigmaType": "Coll[SByte]",
"renderedValue": "066dcf9845b3b646663d65f53eb23ecda42096d2e57202c5ad948b15c528d48a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "f31dd6ec898538f1850cdd3d3ff2665e7524462e26e27b55d616ca463f4e1f6c",
"value": 2000000,
"index": 104,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "cbef11d6fc1d2528231003bc588ebb76ea3c47895d07308102feeb89e900b1cf",
"outputIndex": 1,
"outputGlobalIndex": 44412414,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e206e3897f1a1c06dd2eeebd4ec9287dc0abd119e7f0a03c7938c181ba21fcddc96",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e3897f1a1c06dd2eeebd4ec9287dc0abd119e7f0a03c7938c181ba21fcddc96"
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"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"R6": {
"serializedValue": "0e201d40dfb80bfa6af7b85241b6bfa4cb899132a024e0fa81cbd6a6fb00fc71c8a1",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d40dfb80bfa6af7b85241b6bfa4cb899132a024e0fa81cbd6a6fb00fc71c8a1"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "4423ab8d388ef0d59a406a3df44ca7aaa90776d1fde46b80e4b61f81144032a3",
"value": 2000000,
"index": 105,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "d7e007cedcb307333957530a68187900ceb3b12c580634cbd427df9d7c297cff",
"outputIndex": 1,
"outputGlobalIndex": 44412418,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "0e20c2fa6283d1be597ef8ab3db6dfdf0111f56dce82303d094759fa58513955144d",
"sigmaType": "Coll[SByte]",
"renderedValue": "c2fa6283d1be597ef8ab3db6dfdf0111f56dce82303d094759fa58513955144d"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20ea9e8bb56df5ad970a6a1d59f82fd03edc4e341588bd497adc411639161d37c6",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea9e8bb56df5ad970a6a1d59f82fd03edc4e341588bd497adc411639161d37c6"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "85c31d7a163488c7714a4ecd606d1fb84c5f9abdc9e99c672a48f0e932be8d64",
"value": 2000000,
"index": 106,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "e71f34d05ec28413832fe0755d56370742e833ad4ee79c3c250be798224a7c8c",
"outputIndex": 1,
"outputGlobalIndex": 44412422,
"outputCreatedAt": 1408838,
"outputSettledAt": 1408841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a6ff2fc001a271b31891207c3588580a10475c6e9c8bc4b8a7a05edc072ba4dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "a6ff2fc001a271b31891207c3588580a10475c6e9c8bc4b8a7a05edc072ba4dd"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e20b5bdb5dc28bb57fec68467046457879ff3db99c724b706530ce3831e93c1275e",
"sigmaType": "Coll[SByte]",
"renderedValue": "b5bdb5dc28bb57fec68467046457879ff3db99c724b706530ce3831e93c1275e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "2e6b941a4ce6cdbc7ab0f18ae7ba1af1fb778e3ecd16a5529a24c169f663d7a8",
"value": 2000000,
"index": 107,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "e7a397e72533a2ad09f56b6418787596b72226a459d1ed5227079840cc0cda57",
"outputIndex": 1,
"outputGlobalIndex": 44412426,
"outputCreatedAt": 1408838,
"outputSettledAt": 1408841,
"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": "0e20497e21752b5a1b85c8b814a205d2f5257ba08e2bccd92fcdd9dc80125917a07b",
"sigmaType": "Coll[SByte]",
"renderedValue": "497e21752b5a1b85c8b814a205d2f5257ba08e2bccd92fcdd9dc80125917a07b"
},
"R5": {
"serializedValue": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e207d6d00c604b8cd29f8b32cd2cbeaa6961de36c306716d1e37dd4025421de3d0f",
"sigmaType": "Coll[SByte]",
"renderedValue": "7d6d00c604b8cd29f8b32cd2cbeaa6961de36c306716d1e37dd4025421de3d0f"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "f39c45fe87d1028c0ca6f9ddde5ccfb8fa7a455a8ffed8bdd9dc226d3079eb50",
"value": 2000000,
"index": 108,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "02a1b96314708d1dfad2cf370b8374861560f90577843a6112aa7565725cfc4d",
"outputIndex": 1,
"outputGlobalIndex": 44412430,
"outputCreatedAt": 1408839,
"outputSettledAt": 1408841,
"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": "0e2052e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67",
"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
},
"R6": {
"serializedValue": "0e2032bffb54a5d3d50d00f4eee2e07cfb930da955ddd9c937bf1a90f485f5ae0be5",
"sigmaType": "Coll[SByte]",
"renderedValue": "32bffb54a5d3d50d00f4eee2e07cfb930da955ddd9c937bf1a90f485f5ae0be5"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e11c1cb699b255cc7a4420f6361afb7e49fc79289fbe25d9436509abf43aab16",
"value": 2000000,
"index": 109,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "5e08cabc1662856180537f993cf12c071d166f1e8e2f00e1ed8537ef915a9f16",
"outputIndex": 1,
"outputGlobalIndex": 44412434,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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"
}
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"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"sigmaType": "Coll[SByte]",
"renderedValue": "14459b546b5e6ad87416a97701f5896bd9229d198453bb32cd554257e64f7e31"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "f4de47fd21638cdf64068534673ea80145442ad5ef44b4fee41301d4e661c0dc",
"value": 2000000,
"index": 110,
"spendingProof": null,
"outputBlockId": "2ee8c35f541999e641e78f973acbc3b99c6001790974431b8aedd280814fd33c",
"outputTransactionId": "a4597191f2fa8922c97b97d15af2fe4bf5a35d0384cd863845e6f07a52ff326f",
"outputIndex": 1,
"outputGlobalIndex": 44412441,
"outputCreatedAt": 1408837,
"outputSettledAt": 1408841,
"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": "52e7256660e869a2cd92b2d9255e20ac0c028cc56b1a00fc2f74594ad98bbe67"
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"sigmaType": "Coll[SByte]",
"renderedValue": "9fae9d186899b32835f364338bf6b455f8be48c8acdc052ccac5a6336a9433ea"
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"sigmaType": "Coll[SByte]",
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{
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"value": 2000000,
"index": 111,
"spendingProof": "337dc01ed8205b47757ae7bc328133dbe762ada993a6ad3a89d01ec21f08a04847546704cb9024a4e34592e1079a0871061d739d34aa0164",
"outputBlockId": "5f44fffe816b23f633fac615326c6fbe070c868bf90b8d40c3df4f92220ae630",
"outputTransactionId": "f81952794df961ad11df53c03b58c04219300875966521756a9b31a0d918e6da",
"outputIndex": 1,
"outputGlobalIndex": 43928573,
"outputCreatedAt": 1396458,
"outputSettledAt": 1396460,
"ergoTree": "0008cd029064f9e0b3b63690a88fd5b89f0869f18b1feec15928e181d2b49e16a58a9d50",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(9064f9,4e71bb,...)))}",
"address": "9fcespxXgkxCavMD3m7uSVHa7k2tfxua6xmv4YiLbxbs8e1orpa",
"assets": [
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 0,
"amount": 9935,
"name": "RSN",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "b00f2822d45c79cf072cf51493d73704b4f052961bc4feb9076a995d04e5e728",
"value": 2000000,
"index": 112,
"spendingProof": "6c20458bf95585e810d13daec36d584cce15f91c0a0fec7835f972cad26021ba9e8145f169ba0d1ec37bec6840b7e4d56e715894737f52d6",
"outputBlockId": "71222b54253d4a82b6c703e7b9ee26b1cafde7ab1dd1a90f5c0960e4883b59bf",
"outputTransactionId": "18f6a3f3d887d23dfdf79277edb15d1a1138eced23600d60206086b91875d6a6",
"outputIndex": 3,
"outputGlobalIndex": 43935582,
"outputCreatedAt": 1396626,
"outputSettledAt": 1396628,
"ergoTree": "0008cd029064f9e0b3b63690a88fd5b89f0869f18b1feec15928e181d2b49e16a58a9d50",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(9064f9,4e71bb,...)))}",
"address": "9fcespxXgkxCavMD3m7uSVHa7k2tfxua6xmv4YiLbxbs8e1orpa",
"assets": [
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 0,
"amount": 4088,
"name": "RSN",
"decimals": 3,
"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": "ab86ef4f71052119110026cd560f504be6d581f9356a65e4b3416064b4734acd",
"value": 2000000,
"index": 1,
"outputBlockId": "a7b00728053dfa2e23c0c34d7450e4842bc7cd408b5289ef8f89893c0e75443b",
"outputTransactionId": "581ec17455d131ce79f1ef2271e0e8f124196641e527764d526ae7ce0ae0e3cc",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "05fa01",
"sigmaType": "SLong",
"renderedValue": "125"
}
}
}
],
"outputs": [
{
"boxId": "6bd4af77619fa710653cf3838b69ed693a9f4d08430d65c687ab8faa6b171af8",
"transactionId": "49db6eba80b2ce01e3e59b4f8c28290eea2db0cccbad810e4955944555e34a0f",
"blockId": "d62fb493a732c8b9cfa1ac928c96de111de4873e49a9cb6db7fd1a6f15918e06",
"value": 221010000,
"index": 0,
"globalIndex": 44412551,
"creationHeight": 1408841,
"settlementHeight": 1408843,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: Coll(61,77,106,-65,36,-120,39,27,1,109,101,-87,-13,74,9,45,48,68,77,113,-89,14,-91,30,1,-42,-90,-15,-73,98,118,115)\n10: 1\n11: 0\n12: Coll(82,-43,103,29,47,-108,82,-33,-82,-22,-125,-66,-113,-62,-1,0,-115,58,113,109,-76,-77,-112,-34,-78,119,5,-41,60,96,-108,-22)\n13: 21600\n14: Coll(-98,-6,68,-25,-102,33,112,49,-105,-94,-40,-120,-4,32,76,-10,67,87,17,-51,-17,-49,-33,91,-53,-113,-71,41,-27,9,27,-70)",
"ergoTreeScript": "{\n val i1 = SELF.R7[Int].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == SELF.tokens(placeholder[Int](2))._1)\n }).slice(placeholder[Int](3), i1)\n val coll3 = OUTPUTS(placeholder[Int](4)).propositionBytes\n val coll4 = blake2b256(coll3)\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll2.size == i1, SELF.R4[Coll[Byte]].get == blake2b256(\n coll2.map({(box5: Box) => box5.R4[Coll[Byte]].get }).fold(Coll[Byte](), {(tuple5: (Coll[Byte], Coll[Byte])) => tuple5._1.append(tuple5._2) })\n ), coll2.forall(\n {(box5: Box) =>\n ((box5.propositionBytes == coll3) && (box5.tokens(placeholder[Int](5))._1 == SELF.tokens(placeholder[Int](6))._1)) && (\n box5.tokens(placeholder[Int](7))._2 == SELF.tokens(placeholder[Int](8))._2 / i1.toLong\n )\n }\n ), if (coll4 == placeholder[Coll[Byte]](9)) {\n allOf(\n Coll[Boolean](\n INPUTS(placeholder[Int](10)).tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), HEIGHT - placeholder[Int](13) >= SELF.creationInfo._1\n )\n )\n } else {\n allOf(\n Coll[Boolean](INPUTS.exists({(box5: Box) => blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](14) }), coll4 == SELF.R6[Coll[Byte]].get)\n )\n }\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 333000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201da5c8802d68efc780b333b0779b239e5aa06cb99bfeb4935ccd6d5b8a51bca2",
"sigmaType": "Coll[SByte]",
"renderedValue": "1da5c8802d68efc780b333b0779b239e5aa06cb99bfeb4935ccd6d5b8a51bca2"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[66303037396466636334373633353335336238383362333632353962303434323233623465356135666233343138383539656463663630323234366561303231,6572676f,63617264616e6f,39686d4b666f6a543655613669357a4c534c6156787a544d6f47753963644d7339364a6a4c6e33455632677a35647233387268,616464723171396330787974633863636b64616b6b68737536777139653967347a7679396865616c6a7064746832667a747634376e636363783879396a366437666c6d6e756d3630667572346d7775323739786d6573756432636e73396c743571736b67386863,0000076991dadc00,000000097ce3a780,000000008106ca5b,657267,30346239353336383339336338323166313830646565653832323966626439343162616166396264373438656263646266376164626231342e37323733343535323437,38653430313262636338376333343637643165373162613133353034663765643165323434363434376564643239643637373563636336346237613634316534,0000000000157f3a]"
},
"R6": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
},
"R7": {
"serializedValue": "04de01",
"sigmaType": "SInt",
"renderedValue": "111"
}
},
"spentTransactionId": "d763b0188a9968ab1ad52b22481ed11f6f718605fdd6ff42a4eade1f2bff6b18",
"mainChain": true
},
{
"boxId": "3f9bf9bf8a5cec69802a88c9c159b036b948a9b305d0015b86396f62160ad3d7",
"transactionId": "49db6eba80b2ce01e3e59b4f8c28290eea2db0cccbad810e4955944555e34a0f",
"blockId": "d62fb493a732c8b9cfa1ac928c96de111de4873e49a9cb6db7fd1a6f15918e06",
"value": 2000000,
"index": 1,
"globalIndex": 44412552,
"creationHeight": 1408841,
"settlementHeight": 1408843,
"ergoTree": "0008cd029064f9e0b3b63690a88fd5b89f0869f18b1feec15928e181d2b49e16a58a9d50",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(9064f9,4e71bb,...)))}",
"address": "9fcespxXgkxCavMD3m7uSVHa7k2tfxua6xmv4YiLbxbs8e1orpa",
"assets": [
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 0,
"amount": 14023,
"name": "RSN",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "46e35ac907dff4aef2d5e753c0b5cb28447efbfae9a5726845f9190a4ac2bad2",
"mainChain": true
},
{
"boxId": "8203a8293f13416d63b62e08445db8d582e78a1027a4e0bd5fb2fe878ef03d80",
"transactionId": "49db6eba80b2ce01e3e59b4f8c28290eea2db0cccbad810e4955944555e34a0f",
"blockId": "d62fb493a732c8b9cfa1ac928c96de111de4873e49a9cb6db7fd1a6f15918e06",
"value": 2000000,
"index": 2,
"globalIndex": 44412553,
"creationHeight": 1408841,
"settlementHeight": 1408843,
"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": "1e6ad52f1120d0a8e69baa24fb7a4a205efbffbe363fb27f42a82b9fec2d9a79",
"mainChain": true
}
],
"size": 5116,
"isUnconfirmed": false
}