Transaction
ID: d9e087b938...f031
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
240.33 ERG
Outputs (51)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
232.65 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,939.79
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
3,905.76
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2,818.76
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2,455.41
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
6,703.53
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
4,566.35
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
3,494.31
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
5,146.61
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2,055.66
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
5,652.42
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,841.62
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
5,347.82
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,556.69
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2,474.86
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,147.93
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
214.58
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
750.32
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,562.93
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2,556.90
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
911.68
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
65.04
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
441.40
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
543.09
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,543.61
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
360.71
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
438.22
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
285.02
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
673.32
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
125.61
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
22.59
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
96.84
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
224.04
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
31.39
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,212.60
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
387.63
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
18.39
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,019.05
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
439.68
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
804.34
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,946.14
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
924.06
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
284.50
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2,450.09
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
26.79
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
160.31
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
18,408.49
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
175.43
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.615333333 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
6.59 ERG
Tokens:
0
Transaction Details
Confirmations: 950,615
Total coins transferred: 240.33 ERG
Fees: 0.615333333 ERG
Fees per byte: 0.000011848 ERG
Raw Transaction Data
{
"id": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"inclusionHeight": 815508,
"timestamp": 1660428660884,
"index": 2,
"globalIndex": 3748589,
"numConfirmations": 950615,
"inputs": [
{
"boxId": "160193b52117f269dd831827174c641a1eec0e0ef461d9ea9ea1dc5ddf8ea648",
"value": 1000000,
"index": 0,
"spendingProof": "999347bd0bc83246ab09a75e2d4dc8af85b368a775c271ea4d5c2916e8a768108847e259c3053b654273e5742900e467637181aa066e0970",
"outputBlockId": "15569bce885b6327de083d3a78a4abd02b367b17696a2965954fd2350b7cdd91",
"outputTransactionId": "d7b13eb8f58d6e1c226bbc0de737f3bd864d0272a162cea3cc8d2fbe46a9e09b",
"outputIndex": 0,
"outputGlobalIndex": 20152247,
"outputCreatedAt": 814566,
"outputSettledAt": 814568,
"ergoTree": "102004000e20472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e804040400040205c8010504050304020e20c41e9136c73fb2ee389aa8440ec3da421cea3d29588e8b8f24cdb0be5920d81905c09a0c0580dac40905c09a0c05c09a0c040205a09c0105d00f05c09a0c05c09a0c05c09a0c0e207d2e28431063cbb1e9e14468facc47b984d962532c19b0b14f74d0ce9ed459be040004000400040205f02e0500050004000580dac40908cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d62708cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7d812d601b2db6501fe730000d602db63087201d6037301d604b27202730200d605b2a5730300d606db63087205d607db6308a7d608b27206730400d609d9010959d802d60b8c720902d60c9d9c998c720901720b7305720bed8f720c730691720c7307d60ac1b2a4730800d60bb5a5d9010b6393cbc2720b7309d60c9999720a9d9c720ae4c6a70505730a9c7eb1720b05730bd60d9c720c7ee4c67201040405d60ec17201d60f9c9d9c9d8c720402730c9d720d730d9d9a9c9a720e9d9c720e7e730e05730f7310720d73117312d610e4c6a70405d6119a720f9d9c720f72107313d612e4c672050505ea02d1ededed968302019373148cb27202731500019372038c7204019683080193c27205c2a7938cb27206731600018cb2720773170001938c7208017203da72090186028c720802998cb2720773180002721193c17205c1a793e4c67205040572109072127319927212731a96830201da7209018602b0720b731bd9011341639a8c7213018cb2db63088c721302731c00027211af720bd901136393c17213731daea5d9011363edda7209018602c17213720c93c27213d0731e731f",
"ergoTreeConstants": "0: 0\n1: Coll(71,44,61,78,-54,-96,-113,-73,57,47,-16,65,-18,46,106,-9,95,74,85,-120,16,-89,75,40,96,5,73,-43,57,40,16,-24)\n2: 2\n3: 0\n4: 1\n5: 100\n6: 2\n7: -2\n8: 1\n9: Coll(-60,30,-111,54,-57,63,-78,-18,56,-102,-88,68,14,-61,-38,66,28,-22,61,41,88,-114,-117,-113,36,-51,-80,-66,89,32,-40,25)\n10: 100000\n11: 10000000\n12: 100000\n13: 100000\n14: 1\n15: 10000\n16: 1000\n17: 100000\n18: 100000\n19: 100000\n20: Coll(125,46,40,67,16,99,-53,-79,-23,-31,68,104,-6,-52,71,-71,-124,-39,98,83,44,25,-80,-79,79,116,-48,-50,-98,-44,89,-66)\n21: 0\n22: 0\n23: 0\n24: 1\n25: 3000\n26: 0\n27: 0\n28: 0\n29: 10000000\n30: SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))\n31: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val coll2 = box1.tokens\n val coll3 = placeholder[Coll[Byte]](1)\n val tuple4 = coll2(placeholder[Int](2))\n val box5 = OUTPUTS(placeholder[Int](3))\n val coll6 = box5.tokens\n val coll7 = SELF.tokens\n val tuple8 = coll6(placeholder[Int](4))\n val func9 = {(tuple9: (Long, Long)) =>\n val l11 = tuple9._2\n val l12 = tuple9._1 - l11 * placeholder[Long](5) / l11\n (l12 < placeholder[Long](6)) && (l12 > placeholder[Long](7))\n }\n val l10 = INPUTS(placeholder[Int](8)).value\n val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](9) })\n val l12 = l10 - l10 * SELF.R5[Long].get / placeholder[Long](10) - coll11.size.toLong * placeholder[Long](11)\n val l13 = l12 * box1.R4[Int].get.toLong\n val l14 = box1.value\n val l15 = tuple4._2 / placeholder[Long](12) * l13 / placeholder[Long](13) / l14 + l14 * placeholder[Int](14).toLong / placeholder[Long](15) * placeholder[\n Long\n ](16) + l13 / placeholder[Long](17) * placeholder[Long](18)\n val l16 = SELF.R4[Long].get\n val l17 = l15 + l15 * l16 / placeholder[Long](19)\n val l18 = box5.R5[Long].get\n sigmaProp(\n (\n (\n allOf(Coll[Boolean](placeholder[Coll[Byte]](20) == coll2(placeholder[Int](21))._1, coll3 == tuple4._1)) && allOf(\n Coll[Boolean](\n box5.propositionBytes == SELF.propositionBytes, coll6(placeholder[Int](22))._1 == coll7(placeholder[Int](23))._1, tuple8._1 == coll3, func9(\n (tuple8._2, coll7(placeholder[Int](24))._2 - l17)\n ), box5.value == SELF.value, box5.R4[Long].get == l16, l18 <= placeholder[Long](25), l18 >= placeholder[Long](26)\n )\n )\n ) && allOf(\n Coll[Boolean](\n func9((coll11.fold(placeholder[Long](27), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.tokens(placeholder[Int](28))._2 }), l17)), coll11.forall(\n {(box19: Box) => box19.value == placeholder[Long](29) }\n )\n )\n )\n ) && OUTPUTS.exists({(box19: Box) => func9((box19.value, l12)) && (box19.propositionBytes == placeholder[SigmaProp](30).propBytes) })\n ) && placeholder[SigmaProp](31)\n}",
"address": "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",
"assets": [
{
"tokenId": "fed97da9ab46c8fae5ed075a50d5f4bc2f3b539b11f87e16ae939c01841bea0b",
"index": 0,
"amount": 1,
"name": "Last Extended Phase 2 NETA Emission Box NFT",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 1,
"amount": 1550675480000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "05807d",
"sigmaType": "SLong",
"renderedValue": "8000"
},
"R5": {
"serializedValue": "05f02e",
"sigmaType": "SLong",
"renderedValue": "3000"
}
}
},
{
"boxId": "577fb00c0649e70f0727ce3364a28bf9c0fbf15bdaf1a2ac56bdcecfa62a2c78",
"value": 240329086088,
"index": 1,
"spendingProof": "192400780334d9598066d4134bf1d64fafe70cd84d69a0e50794bc0d67f4c65b1583e20cd7970a6a4de5ef9ea95880e6a3adcfe6c47fa8d1",
"outputBlockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"outputTransactionId": "72fe1cffbed4462f578a40ae92005246e0f6310e968ad89fc349136bb17e7176",
"outputIndex": 0,
"outputGlobalIndex": 20197422,
"outputCreatedAt": 815506,
"outputSettledAt": 815508,
"ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
"address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "53f58e91761f795d645cfe1ddcec680f36ba47a0f919d036b7433c8215c1de07",
"value": 40209606856231,
"index": 0,
"outputBlockId": "44e6d42a01fcac36b24ea1277af5150e27fde2c91cc9086e3d17aeffd56cb03c",
"outputTransactionId": "1f62014ebf00bea0d193dd9da1f777ea19dd7b6126d76f5897b81a1f1a2091f2",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04c80f",
"sigmaType": "SInt",
"renderedValue": "996"
}
}
}
],
"outputs": [
{
"boxId": "ce347048a0e8c4674fbf6f66bba0234e8b548ee0ddfc73926c4b1c3135378472",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 1000000,
"index": 0,
"globalIndex": 20197427,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,44,61,78,-54,-96,-113,-73,57,47,-16,65,-18,46,106,-9,95,74,85,-120,16,-89,75,40,96,5,73,-43,57,40,16,-24)\n2: 2\n3: 0\n4: 1\n5: 100\n6: 2\n7: -2\n8: 1\n9: Coll(-60,30,-111,54,-57,63,-78,-18,56,-102,-88,68,14,-61,-38,66,28,-22,61,41,88,-114,-117,-113,36,-51,-80,-66,89,32,-40,25)\n10: 100000\n11: 10000000\n12: 100000\n13: 100000\n14: 1\n15: 10000\n16: 1000\n17: 100000\n18: 100000\n19: 100000\n20: Coll(125,46,40,67,16,99,-53,-79,-23,-31,68,104,-6,-52,71,-71,-124,-39,98,83,44,25,-80,-79,79,116,-48,-50,-98,-44,89,-66)\n21: 0\n22: 0\n23: 0\n24: 1\n25: 3000\n26: 0\n27: 0\n28: 0\n29: 10000000\n30: SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))\n31: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val coll2 = box1.tokens\n val coll3 = placeholder[Coll[Byte]](1)\n val tuple4 = coll2(placeholder[Int](2))\n val box5 = OUTPUTS(placeholder[Int](3))\n val coll6 = box5.tokens\n val coll7 = SELF.tokens\n val tuple8 = coll6(placeholder[Int](4))\n val func9 = {(tuple9: (Long, Long)) =>\n val l11 = tuple9._2\n val l12 = tuple9._1 - l11 * placeholder[Long](5) / l11\n (l12 < placeholder[Long](6)) && (l12 > placeholder[Long](7))\n }\n val l10 = INPUTS(placeholder[Int](8)).value\n val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](9) })\n val l12 = l10 - l10 * SELF.R5[Long].get / placeholder[Long](10) - coll11.size.toLong * placeholder[Long](11)\n val l13 = l12 * box1.R4[Int].get.toLong\n val l14 = box1.value\n val l15 = tuple4._2 / placeholder[Long](12) * l13 / placeholder[Long](13) / l14 + l14 * placeholder[Int](14).toLong / placeholder[Long](15) * placeholder[\n Long\n ](16) + l13 / placeholder[Long](17) * placeholder[Long](18)\n val l16 = SELF.R4[Long].get\n val l17 = l15 + l15 * l16 / placeholder[Long](19)\n val l18 = box5.R5[Long].get\n sigmaProp(\n (\n (\n allOf(Coll[Boolean](placeholder[Coll[Byte]](20) == coll2(placeholder[Int](21))._1, coll3 == tuple4._1)) && allOf(\n Coll[Boolean](\n box5.propositionBytes == SELF.propositionBytes, coll6(placeholder[Int](22))._1 == coll7(placeholder[Int](23))._1, tuple8._1 == coll3, func9(\n (tuple8._2, coll7(placeholder[Int](24))._2 - l17)\n ), box5.value == SELF.value, box5.R4[Long].get == l16, l18 <= placeholder[Long](25), l18 >= placeholder[Long](26)\n )\n )\n ) && allOf(\n Coll[Boolean](\n func9((coll11.fold(placeholder[Long](27), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.tokens(placeholder[Int](28))._2 }), l17)), coll11.forall(\n {(box19: Box) => box19.value == placeholder[Long](29) }\n )\n )\n )\n ) && OUTPUTS.exists({(box19: Box) => func9((box19.value, l12)) && (box19.propositionBytes == placeholder[SigmaProp](30).propBytes) })\n ) && placeholder[SigmaProp](31)\n}",
"address": "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",
"assets": [
{
"tokenId": "fed97da9ab46c8fae5ed075a50d5f4bc2f3b539b11f87e16ae939c01841bea0b",
"index": 0,
"amount": 1,
"name": "Last Extended Phase 2 NETA Emission Box NFT",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 1,
"amount": 1460463188000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "05807d",
"sigmaType": "SLong",
"renderedValue": "8000"
},
"R5": {
"serializedValue": "05f02e",
"sigmaType": "SLong",
"renderedValue": "3000"
}
},
"spentTransactionId": "1a42048550681d532a5da59ad00831e18344a65822f187cb42f94889dd06fc2b",
"mainChain": true
},
{
"boxId": "28662d7dd8cf747819877f68d6fd2d95c734fcb61f6c598284637e8acd3c3873",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 232649213506,
"index": 1,
"globalIndex": 20197428,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "0008cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d627",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))}",
"address": "9gdLf3Zg1QHgH3BYjFrMA2DSm19CqPNKi9vTCeCT5NSmNZfV29T",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "5c125a13a771c796aa1351d2b0aa7688a495c0ce636f4eb7b31d45d23085b9ba",
"mainChain": true
},
{
"boxId": "06af949ddfb1ec207d12bd8e3db1ec3d962cb38eceda220d2192c9aa4e187db8",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 2,
"globalIndex": 20197429,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1939788350,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "feb05333bbef4c130d038540acdf16f968a54bc76dedfc072d679665c42c02b7",
"mainChain": true
},
{
"boxId": "206272fee207fb1fa40efccc7853c1e8676438cdbffbea34052cfdd3098bbc25",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 3,
"globalIndex": 20197430,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 3905756653,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e0537c748f6a46f694a0fc5b3ecfdfdd164bf284d7ac0c4c5a8da4899f8ca17a",
"mainChain": true
},
{
"boxId": "d7be072a9adfe9483b2696a0b9166fec67586a2fff96d61cd06abce0772ef4c0",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 4,
"globalIndex": 20197431,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 2818756356,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1f4888d8b3c08e78a40b24652b0ec08b160b2c7b16c0efdfae9cafcb85a11b77",
"mainChain": true
},
{
"boxId": "d9c7af462caf30ed7bf1a9c1aa00daca353500f57b2528ddd49f458e660a61e4",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 5,
"globalIndex": 20197432,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 2455412532,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8d0f38045300eadfded6d64e8f2d34dec2ee3871f1da4687010c9787449f7c01",
"mainChain": true
},
{
"boxId": "4baf982f9675f7363268d9660d1e81bb4e85a94903ec314e98a822f3cd1032a0",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 6,
"globalIndex": 20197433,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 6703529353,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "29f53b448d138fecbbafbec82dc0ad7bd7b0d928783ee6f512f216dfb2445bc8",
"mainChain": true
},
{
"boxId": "fbaa9a933fba97ce7751ef70042d7d39fa874f1ae115fbc387069f1ddefe29eb",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 7,
"globalIndex": 20197434,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 4566353902,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7077d9cae938466c60a92a9e68fe111d6d9e9fce488caa7dfb6852b547b581ad",
"mainChain": true
},
{
"boxId": "b5a25a842bcde9fe9a1ebc391fe293b10f9142fdeba4ca316dce04fabcd73d1b",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 8,
"globalIndex": 20197435,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 3494311000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4c82a9b31e65dc9b6dd88997654d5be903da2f027da9041be90fd3c1bdf43ca6",
"mainChain": true
},
{
"boxId": "ef0c5a35d2266fa61cb3435affc93914820d3d6d1a4b92ff29491d1d3f9863b4",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 9,
"globalIndex": 20197436,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 5146607023,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a849947074f23afd3b240aa86c824085e82dbeb1e448736487d1897e1a7ce291",
"mainChain": true
},
{
"boxId": "51c54f02672d3bac93f26d7bdc00c2d74e8cca0781948c4f31ec90960377684d",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 10,
"globalIndex": 20197437,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 2055658547,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8709e3229788ba65d4132ef709eaa9c2d7f9931c025c36908561e38c6c04e959",
"mainChain": true
},
{
"boxId": "c24e01c4fe9a45851c545fa1148b475d48ba78eb97c7a7a83a1dc8bbef96af74",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 11,
"globalIndex": 20197438,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 5652415979,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7e9af632b7f0cbbf3b48060466b542cf509557918dd83742419a9eef9f03c002",
"mainChain": true
},
{
"boxId": "03b0cb2dfdfaee6bcfdc8962b939bb6937e8a0cbb731f1699f64e602f382f8a1",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 12,
"globalIndex": 20197439,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1841618038,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4acd93f58bf37e108b5b259a3db25acfaf31ddf957b28769d44f350c9006eafb",
"mainChain": true
},
{
"boxId": "e0cf58464c9ea0853e44228d87c38f98e22350dfd485c54045f5f02d35682c2a",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 13,
"globalIndex": 20197440,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 5347819176,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9ab5c19f09bf8a4bb9d9313148b6cb0d1b58c946fe7b9c8d15fa97a4d9e94113",
"mainChain": true
},
{
"boxId": "a04fa3943b2c024db7cffbec3e187132ac1272d1d29efb3e9bfc9d329e8e874a",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 14,
"globalIndex": 20197441,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1556687774,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "dd73603844c6cb52f47d333324f9ec2e98cebee6e8ee46ba95a3e0946734bcef",
"mainChain": true
},
{
"boxId": "8ba25eb088b6e6723a0a0047b5e848b08ddf06e03a6296ce8d122c7c44488971",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 15,
"globalIndex": 20197442,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 2474862559,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1a4fad54bdc0ad2eb0f7943e28e492e782afc2bf267cc3231bd9275e6a7b12c9",
"mainChain": true
},
{
"boxId": "5d85d22134b9b883536565215b21c4e27b50ccf212dd6034a5d38aa168ce5eff",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 16,
"globalIndex": 20197443,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1147930483,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "22aa927c34f296e90d997814eb7aa6e74c2a74d825a90fff3be28525621a8e1d",
"mainChain": true
},
{
"boxId": "6b59336007b55eeeb46a771cf608f97e30585d92e72f667867a3239301559709",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 17,
"globalIndex": 20197444,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 214581790,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b0b9247e665546bd9bf4edf7be2416c43c9df23bb3aec6d2bf6a19e342fd5459",
"mainChain": true
},
{
"boxId": "709a1ffa05c1b5e7f4159fa441440f8f3a335363053d6314e7696944cda29e51",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 18,
"globalIndex": 20197445,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 750323579,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7caeafaf1909afe036ff4262c93a64a831a1a6df2ddacbce6b840ff86f62a2f6",
"mainChain": true
},
{
"boxId": "fda9b0da4b18394a6197bd8fe409b0dc60d79ae260fb249c99f2b4c3234c82b2",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 19,
"globalIndex": 20197446,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1562930547,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0749b5d318af115f30e1389695dd39031f6dc09e5903a1fb17a97f6d879e5b09",
"mainChain": true
},
{
"boxId": "ff7b3eab628c21a578d27ef2a32f09645f7d915647f6f84b23e8f6b81488de64",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 20,
"globalIndex": 20197447,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 2556902700,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bbcedf70e5e40a0fbac7bff0306124ac343fbc7da54ef4e4d30b17991c3f0ed3",
"mainChain": true
},
{
"boxId": "f57f8f0475e7b3e5ea7f034fb8575232757b76de2d3bfc1c8945c7cdf738e6ba",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 21,
"globalIndex": 20197448,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 911679414,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b02a36826f597349db19ee46dca0ce92c7c1629cb32f207df6de13e04c4a28a5",
"mainChain": true
},
{
"boxId": "6093e101e24062f1390ec1ed0275383b7f538eed4d79a08fbd0f9a216dfd6280",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 22,
"globalIndex": 20197449,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 65043921,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0540ee03a99d7b1364a828ff72349d67b67fc42ea8c01f617900ca5c870e28a1",
"mainChain": true
},
{
"boxId": "3d0293ced6778d35f388c3b932c8b6baa3c271e6b0d5fc5c820d452e47bcd389",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 23,
"globalIndex": 20197450,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 441396528,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a696028e534b74d0a6442de278a9521f4edc47d139984212d73917609caa6591",
"mainChain": true
},
{
"boxId": "09062681c439403b7b639e809181fc512f11f432785db7be0da23c14d930a5d5",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 24,
"globalIndex": 20197451,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 543085166,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f31d3d1fd09a222ca26ee585a8edf5df68b5ff1953fdcb5fa472cd96b788d4ad",
"mainChain": true
},
{
"boxId": "5a4db91cbac3d9978ebaff351927739d30aa172040b64ace8f2ba7c6f6dfae69",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 25,
"globalIndex": 20197452,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1543606819,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "892e1a091a53f8ce99b52559c0379d0c6a415535ca246ef7abbe743a322941bf",
"mainChain": true
},
{
"boxId": "a2faf294bd4b4427022136d9e04afbc3712eae441fcc9ef4f7454e4ab3c126a7",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 26,
"globalIndex": 20197453,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 360709589,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8b5293f7e02e5133dbfe9f99a5bf6a5bd465b82c75302376b3ee6173df5e08d7",
"mainChain": true
},
{
"boxId": "f46afaafb3067862d11f45991dcb8919d14bd9b7e8d3d3a7ea2040a4b0d18f50",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 27,
"globalIndex": 20197454,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 438221014,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "c300d7c2d01b36f73ee4cabb14f023db007b62352a9c25c72061e8ffff8ed6ef",
"mainChain": true
},
{
"boxId": "afcdc8f9525454af14b93f2c745bc3a7ac6f693d411637260e6dbe44a4ecc165",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 28,
"globalIndex": 20197455,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 285020477,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ac7713182f78d33f4bef512ba4babe8ea6f869748b23fcdeb4e455640a7461f6",
"mainChain": true
},
{
"boxId": "b5e7b4bc5becfd1f39c633bcd71781fd4aa960e3bbe1983f72b22478988920a2",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 29,
"globalIndex": 20197456,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 673317350,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "3aaeb4ae9c2265874f09297f9b19b3457bec3146b43852ec23b69c378b825c12",
"mainChain": true
},
{
"boxId": "84b4f6140bb1e5887031c07da957917861eb3b1a2cb1684ae572687b9f905616",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 30,
"globalIndex": 20197457,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 125613253,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d7ab752470c89fb5f2d75775b3b3940b75e953ddbe2852556cebb3948ddcd7ee",
"mainChain": true
},
{
"boxId": "7db0c2e4437a93ec99cdd1c6fd7055975f2f5fa0328d6b99325f4347d50453a5",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 31,
"globalIndex": 20197458,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 22589456,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "30f80b6d3def0e460d3abcd0d11c50a426ba64a73d93a5b7ef71037213a80cce",
"mainChain": true
},
{
"boxId": "07f937f31f82bdf0a67707f7603f12d6957f732afb39437fcebeff8d916f0f49",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 32,
"globalIndex": 20197459,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 96835152,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7287ac93913ccc9526561ba87b8a50e1a04a76c7b0bbb1229b0d93d1d0a360b7",
"mainChain": true
},
{
"boxId": "938d1df8f78811e589c4e5d162dee250456d949efde344934395bae181281a92",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 33,
"globalIndex": 20197460,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 224036163,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0aa3b2fd91050e77bc932718419548833c208c0b44b3cd338f85260f20d2c448",
"mainChain": true
},
{
"boxId": "4c91b6420b7a68782e61c24a36f29b45c717688ceb96f9f0f6ca6f1477bbbbe7",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 34,
"globalIndex": 20197461,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 31394292,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "873db6611f858339c0c73f0fb7afaf254f8c6d384c412b369175cb7a6d21bcbf",
"mainChain": true
},
{
"boxId": "60a3f2f517541784bc1b689a026e2131cf8236860172542e677bc759eeccbf70",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 35,
"globalIndex": 20197462,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1212595507,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ea9e8e6faa3f76972198d9dc6d0fb381e19a5c5d4b0db663ee8aece65ad6c38d",
"mainChain": true
},
{
"boxId": "961899e0361d3506c4df53b6f04aa820d92baf5cc43c48a4068e1b29d3e2c980",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 36,
"globalIndex": 20197463,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 387629292,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "baf13508f75a526012e834ab7fcca240108dd9d1675a557d8ef41c3493b396e2",
"mainChain": true
},
{
"boxId": "43fd33712c58553f551f6549bff2ecd1ef47b4a16a24c8cfb2a333c6af9f5481",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 37,
"globalIndex": 20197464,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 18385507,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d407013fbfdea27f0f02aa4080ddfa3e509e09f82bd9c03f322b2dca26c62404",
"mainChain": true
},
{
"boxId": "3dccdb24e14c3b30630c816d1117409a7a5edc00ffc827d1fce63404b53e119d",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 38,
"globalIndex": 20197465,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1019051501,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2a77c7da500a6fa7ebe8c8ec2d92cbd67d50d8de8b3f6f4e86a6aff264e09c7b",
"mainChain": true
},
{
"boxId": "2bebbbc6c0c114be02e9113617b6d93d875a7fd53ecc1f6072563b92dc2cc9cd",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 39,
"globalIndex": 20197466,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 439682472,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0e1680e2085bc6af8adb3560e7f407507c684cc0619da9e19150a04e56b36059",
"mainChain": true
},
{
"boxId": "2b23007a3b209d8e9d49178a03495b44d12222e7ca8593ba1b6a4d2d3ea2fe75",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 40,
"globalIndex": 20197467,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 804343412,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "5410bf38d3dcbb382471954da0acd5f1b468278330abbb6fefbb10752df5d288",
"mainChain": true
},
{
"boxId": "495fe65027aa3545003e2c69c291afd0685a9c176b548bcea1d4e1510f33ca0d",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 41,
"globalIndex": 20197468,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1946139379,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "60f23335537f2dedcabb127791cee7c3b50738971e738f2c97e64b75a7f95458",
"mainChain": true
},
{
"boxId": "07383f9eb906513dc46a69dda3a48789a72202a5f3e14e6c0f818bf0fcc9075c",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 42,
"globalIndex": 20197469,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 924056704,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d405eb9099d9d7ac04132fd040d6787a86fc6a194499cb236be7907536139e25",
"mainChain": true
},
{
"boxId": "7da29341392fb8ded0d4ba9dc05bc4083d24a9a7acfeaca1ebebe41c18885c59",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 43,
"globalIndex": 20197470,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 284497239,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7af364dfeb7ed3f4a625f5c0eb88f70eaae514eadd0a5dbc4a3f94f7568d8c03",
"mainChain": true
},
{
"boxId": "03a8ad53abf81e7c8e6bcfe9390cfeaf9644d8ad2f237e6499dce59aabb50711",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 44,
"globalIndex": 20197471,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 2450089937,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2f4e54c982e13d09cea878de163f9c2d62549655ad6ab1cdbe8faa8727975624",
"mainChain": true
},
{
"boxId": "dec4c1a5f1fb6f2c4fe6618819357d7a775e864cfa1035df0a27a5989b443e40",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 45,
"globalIndex": 20197472,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 26793404,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e20d579c1bb589b2152f06e72474fed84a52d84676d5d2d8a18199a51a6d74a4",
"mainChain": true
},
{
"boxId": "f7afa355751a95b944191e4a5c9ffe8aa5ae89cc19054959aedaef479720e001",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 46,
"globalIndex": 20197473,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 160309358,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "db042e6abdfeeeac78c8fa5ee2ba25084de79dbf42ce234ccc36c60a717fb6d6",
"mainChain": true
},
{
"boxId": "40ff29d3f16ad5687e5fa185d80907e295e6ee9f5f3c48b1dcf718b05ed74f2a",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 47,
"globalIndex": 20197474,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 18408494193,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f0807070151f3a1e789788f5c4648ad1f690eed7f844c013cfe36cf40d2cecab",
"mainChain": true
},
{
"boxId": "27ecbe648c2403c86e3c42088df0c24467c5f9cb3fdd6f8b370e869200c98cb9",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 10000000,
"index": 48,
"globalIndex": 20197475,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 175429138,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "6950521172d97208adc434e6b05ea81d19bdfc6cf4fc52c02d9ff63122ad18da",
"mainChain": true
},
{
"boxId": "b9a6af793a07f1e42300a0effeb9fc927d8cb0926597f2de7bf7bfd17e0845f4",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 615333333,
"index": 49,
"globalIndex": 20197476,
"creationHeight": 815506,
"settlementHeight": 815508,
"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": "97de10db654d8d450b15174b96f5829667ab50f4bbfbb4d055d3b9d42cfdb618",
"mainChain": true
},
{
"boxId": "a003b994c84bc918fc401c1e0f4fafa75109fced684266103aef4e63cc28cdb6",
"transactionId": "d9e087b938b3f14e28339eb87a1e37d3000eb46dbd099eb7dbcc350d5081f031",
"blockId": "bb9e4fb0e52d1af50b6803f02e6de44f14c8d99aeb3e9dedd5dadfbc9fa32c15",
"value": 6594539249,
"index": 50,
"globalIndex": 20197477,
"creationHeight": 815506,
"settlementHeight": 815508,
"ergoTree": "0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6d9d81,e53882,...)))}",
"address": "9fMLVMsG8U1PHqHZ8JDQ4Yn6q5wPdruVn2ctwqaqCXVLfWxfc3Q",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 22,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bdb52fc1d9352d82ec8f18ef8946cfdae7c8afb814ca492d87b690c7eddaee8e",
"mainChain": true
}
],
"size": 51935,
"isUnconfirmed": false
}