Transaction
ID: 3ffcb2cf4d...7b40
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.9343518 ERG
Tokens:
Loading assets...
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.9332518 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 141,672
Total coins transferred: 0.9363518 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000323 ERG
Raw Transaction Data
{
"id": "3ffcb2cf4d660dd5ddd7c5b781ec5129df45b5d17cc5f4cc7dd26ec405687b40",
"blockId": "db8577a4b5023aa35e406067ac4127cbfe2d3cabdcde8607c6f4c8fecba4c0d3",
"inclusionHeight": 1615352,
"timestamp": 1758204053458,
"index": 7,
"globalIndex": 9494107,
"numConfirmations": 141672,
"inputs": [
{
"boxId": "edfec5bfccf616fbcf549487efa658ab445972d156ca45b325e5444e31b10afa",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "4aa7f8eec848cdcafa590fee946b57ff6d2b30ec2e454eedc84dd4bbe2cb0f9c",
"outputTransactionId": "12e99e3bf4efa9fe2da6c53c3da3d4b0451b24c92b14ebe806803517f947346a",
"outputIndex": 0,
"outputGlobalIndex": 50332383,
"outputCreatedAt": 1615345,
"outputSettledAt": 1615347,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(105,-69,41,-112,-47,96,54,47,9,-102,7,-17,93,-105,97,-73,-99,-80,29,-107,9,58,-119,119,-27,-61,-70,-47,-33,78,-5,-50)\n3: 2\n4: 1\n5: 0\n6: 0\n7: Coll(-14,-39,92,-120,-120,58,-67,-114,-67,-72,-77,-66,-111,-22,45,23,-112,80,27,10,-54,-127,-34,40,-51,-108,-38,-118,-109,51,97,70)\n8: Coll(-12,23,-98,5,63,-104,-75,-9,100,-6,29,114,90,-42,80,102,-55,126,-74,52,91,79,-76,-64,73,72,106,84,-38,81,-92,78)\n9: -1\n10: 0\n11: -1\n12: false\n13: true\n14: 1\n15: 1\n16: -1\n17: 0\n18: 1\n19: 1\n20: 0\n21: 1\n22: 2\n23: 3\n24: 30\n25: 4\n26: false\n27: false\n28: false\n29: false\n30: 2\n31: 0\n32: 5\n33: 1000000\n34: 1000000\n35: Coll(-114,10,-82,-64,-66,49,-126,-79,-119,82,14,127,111,55,-64,-59,55,-91,109,94,23,22,31,-70,97,-16,-79,-50,-89,-53,-120,-85)\n36: 1\n37: 2\n38: 30\n39: 1\n40: 1000000\n41: false",
"ergoTreeScript": "{\n val l1 = HEIGHT.toLong\n val coll2 = SELF.R8[Coll[Long]].get\n val l3 = coll2(placeholder[Int](0))\n val coll4 = SELF.R6[Coll[Byte]].get\n val coll5 = SELF.tokens(placeholder[Int](1))._1\n val coll6 = placeholder[Coll[Byte]](2)\n val l7 = coll2(placeholder[Int](3))\n val l8 = coll2(placeholder[Int](4))\n val tuple9 = SELF.R5[(Coll[Byte], Long)].get\n sigmaProp((SELF.R4[Int].get == placeholder[Int](5)) && (if (l1 >= l3) {(\n val box10 = OUTPUTS(placeholder[Int](6))\n val tuple11 = box10.R5[(Coll[Byte], Coll[Byte])].get\n val coll12 = tuple11._1\n val coll13 = INPUTS.filter({(box13: Box) => (blake2b256(box13.propositionBytes) == placeholder[Coll[Byte]](7)) && (box13.R6[Coll[Byte]].get == coll5) })\n if (((blake2b256(coll12) == coll4) && (blake2b256(box10.propositionBytes) == placeholder[Coll[Byte]](8))) && (coll13.size == OUTPUTS.filter({(box14: Box) => (blake2b256(box14.propositionBytes) == coll6) && (box14.R6[Coll[Byte]].get == coll5) }).size)) {(\n val tuple14 = coll13.fold((placeholder[Long](9), (Coll[Byte](), placeholder[Long](10))), {(tuple14: ((Long, (Coll[Byte], Long)), Box)) =>\n val box16 = tuple14._2\n val coll17 = box16.R5[Coll[Byte]].get\n val tuple18 = box16.R9[Coll[Long]].get.fold((placeholder[Long](11), placeholder[Boolean](12)), {(tuple18: ((Long, Boolean), Long)) =>\n val tuple20 = tuple18._1\n val l21 = tuple18._2\n if (tuple20._2) { tuple20 } else { if (blake2b256(box16.R7[Coll[Byte]].get.append(longToByteArray(l21)).append(box16.R8[Coll[Byte]].get).append(coll12)) == coll17) { (l21, placeholder[Boolean](13)) } else { tuple20 } }\n })\n val l19 = box16.value\n val bool20 = (tuple18._2 && (l19 >= l7)) && OUTPUTS.exists({(box20: Box) => (((blake2b256(box20.propositionBytes) == coll6) && (box20.value == l19)) && (box20.R4[Coll[Byte]].get == box16.R4[Coll[Byte]].get)) && (box20.R5[Coll[Byte]].get == coll17) })\n val tuple21 = tuple14._1\n val l22 = tuple18._1\n val tuple23 = tuple21._2\n val l24 = tuple23._2\n val l25 = tuple21._1\n if (bool20 && \n val l26 = l25\n l22 > l26\n ) {(\n val l26 = l24\n (l22, (coll17, l26 + placeholder[Long](14)))\n )} else { if (bool20) { (l25, (tuple23._1, l24 + placeholder[Long](15))) } else { tuple21 } }\n })\n val tuple15 = tuple14._2\n if (tuple14._1 > placeholder[Long](16)) {(\n val l16 = tuple15._2\n if (l16 == coll13.size.toLong) {(\n val coll17 = SELF.R7[Coll[Coll[Byte]]].get\n val coll18 = CONTEXT.dataInputs\n val coll19 = coll18.map({(box19: Box) => box19.tokens(placeholder[Int](17))._1 })\n ((coll17.size == coll18.size) && coll17.forall({(coll20: Coll[Byte]) => coll19.exists({(coll22: Coll[Byte]) => coll22 == coll20 }) })) && ((((((((((((tuple11._2 == tuple15._1) && (box10.value >= l8)) && (box10.tokens.filter({(tuple20: (Coll[Byte], Long)) => tuple20._1 == coll5 }).size == placeholder[Int](18))) && (box10.R4[Int].get == placeholder[Int](19))) && (box10.R6[Coll[Coll[Byte]]].get == coll19)) && (box10.R7[Coll[Long]].get(placeholder[Int](20)) == l3)) && (box10.R7[Coll[Long]].get(placeholder[Int](21)) == l8)) && (box10.R7[Coll[Long]].get(placeholder[Int](22)) == l7)) && (box10.R7[Coll[Long]].get(placeholder[Int](23)) >= l1 + placeholder[Long](24))) && (box10.R7[Coll[Long]].get(placeholder[Int](25)) == l16)) && (box10.R8[(Coll[Byte], Long)].get._2 == tuple9._2)) && (box10.R9[(Coll[Byte], Coll[Byte])].get == (tuple9._1, SELF.R9[Coll[Byte]].get)))\n )} else { placeholder[Boolean](26) }\n )} else { placeholder[Boolean](27) }\n )} else { placeholder[Boolean](28) }\n )} else { placeholder[Boolean](29) } || if ((l1 < l3) && (OUTPUTS.size >= placeholder[Int](30))) {(\n val box10 = OUTPUTS(placeholder[Int](31))\n val l11 = l8 / placeholder[Long](32)\n val l12 = l8 - l11\n val bool13 = l12 < placeholder[Long](33)\n val l14 = if (bool13) { placeholder[Long](34) } else { l12 }\n ((((((((blake2b256(box10.propositionBytes) == placeholder[Coll[Byte]](35)) && (box10.value >= l14)) && (box10.tokens.filter({(tuple15: (Coll[Byte], Long)) => tuple15._1 == coll5 }).size == placeholder[Int](36))) && (box10.R4[Int].get == placeholder[Int](37))) && (box10.R5[Long].get >= l1 + placeholder[Long](38))) && (blake2b256(box10.R6[Coll[Byte]].get) == coll4)) && (box10.R7[Long].get == l14)) && box10.R8[Coll[Byte]].isDefined) && (OUTPUTS(placeholder[Int](39)).value >= if (bool13) { l8 - placeholder[Long](40) } else { l11 })\n )} else { placeholder[Boolean](41) }))\n}",
"address": "PvqSSqckAa5pHpe8i7AjB9Yr9sUAuv9Q1Hz98i7EVp892SMPX11BcLRNpgUcc4GzGSqaRbqZiRRcEMbhFey9hJaJiUQMJWLpM7dygykDhiPEFoMsth9Pjwdu7V1f68o2dPp4FFquCkMx7rQTQ532UZ7Z4i8j2Gt87grQm3Lti18xa5WCMWWDqq18xbe3P7QzWfaeojh97Q9ok1kLeMQxaP6f3ZggcMAFRM6U9RrHSTA5MGFYsG4cv43j4E6SfQrr6SZazAtM3ZWiq5NRFqyFdeb1MEueUcaBnJkA5w3oNcs7Ni2LWMiomKSrLMhfFkRVxn95rPWCVZwrgouxpegjADRpuCwqQCguec7CVKZabKxTbEFqEeDZbfzEyZSKBxfvQicMCbPuGoezdEJBpPiDyeY1Xb7BL9RNrbtuQiq3Db1gnnCGmwGuHbPuMuuggHMUTN7ncWg96xR9KLPcQz1gdSJeRX6hmH4D8rYJK7gGGLUckyMhHxtVQcBV9LnGrLru9Jq8MVeQZ2cDNBFBWSDV7LSjjLJexkCQRQRzUTUnjTykgqWZnvLeHU9qFRisXKDrdu3Fs3ZxzojYtHDJ9gW52eqvvuv4GHq9fS8gPfBwWBohdk8fjYna2zx4ZiuJZySD4C7JzqHXzkWnx96TZxq2TfqLeB4u1FzUwqcADKKLGqWF2udYqMx5SpSEG7ofNMDncW3dXC9ZfqEHVVY4GfVFcEiMs1XPnHexFDQshzzbbxpsB5puDvkwSQ9PC1hqyqdTbjX6JmcDBuEwRoGMX9YiHgubKWUv9npC6zVT9NcWfMxKo3m9Mg9t3xX1EmKNRvbN1nHnY7dpfaqVGpeWgYWujiTdSfcrmQFDLHBTggxZoben4AQqWYPa5YbZwMH6FLsj7H7YxAtR5SJiiFy2Z7KvYwdi3nqYWSa1Y64WK2SPdeX4vk8sH6p2iNZmdY22izekB8Vz8n6aoE4E718AXReTBkKCQT7fTrkZeZxfi9cUVaDmajtM57i6fs6wLqmcdd1vXrqso6hhVZ6CDsYiDxDG5xrAxrTSvRm98HLFEW194v4DBKYphJAvNhW31Lcoiw13euubDXErbsT7Xy62zWcNk4rdDZRwbXEYp8MLVSL3orKHHQjUFGZwvtZTz5iNbk9Cor5m2tic8zatUHH5sGYMr25WcsJSyxiEPg3nCF4wf6LZyGGTKg48j7oFdzDjeHkqz1c3TVkKM4muHRAnELipsGabVfVVfEBEx4oymsX6e8Q5DqSes67Y3csT53F1qGKBtnPuthZmTeoPTRyFqrgRZkGRXmX8zQJnLrgKsvYsQoSZFzMoTjQNT1TmKDqyFPtGQp2hCth21Yi28ipTB6yBujzEBkvAQCbPcEXZ45dSQJyWfni9jhWpFfrKFUcuhUjHhnZSZfYh6NU7DkRsp7T3qPm183LQZmTczpFeHE8P3WvT4owj7awsL76r2KkbY32jCgfuVFr78LTvvdsCyB38AurgkBhb",
"assets": [
{
"tokenId": "2c5d596d617aaafe16f3f58b2c562d046eda658f0243dc1119614160d92a4717",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "4d0e2102910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b728",
"sigmaType": "(Coll[SByte], SLong)",
"renderedValue": "[02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7,20]"
},
"R6": {
"serializedValue": "0e20b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a"
},
"R8": {
"serializedValue": "1103ec97c50180897a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1615350,1000000,1000000]"
},
"R7": {
"serializedValue": "1a01202da371e44ef2083041fa048a55db55f7013d81f3c12ac79c3f814a282e1c7839",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[2da371e44ef2083041fa048a55db55f7013d81f3c12ac79c3f814a282e1c7839]"
},
"R9": {
"serializedValue": "0e9e017b227469746c65223a2254657374205638222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c227765624c696e6b223a22222c22736572766963654964223a2262666165616638386165346163316265366464376164356632343766333063666339636439303336303330303035346162363132366136366663343337323466222c226d6972726f7255726c73223a5b5d7d",
"sigmaType": "Coll[SByte]",
"renderedValue": "7b227469746c65223a2254657374205638222c226465736372697074696f6e223a22222c22696d61676555524c223a22222c227765624c696e6b223a22222c22736572766963654964223a2262666165616638386165346163316265366464376164356632343766333063666339636439303336303330303035346162363132366136366663343337323466222c226d6972726f7255726c73223a5b5d7d"
},
"R4": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
}
}
},
{
"boxId": "55003ed331d9fc1d41031e4e2adf333f4b85cdcbfed17c19cdf9fcf5055d2775",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "f83c548cf0cc532c6242956ec9650b8e19ac5935db4a66a520aaf9d53d13995f",
"outputTransactionId": "6d6ef690cb981981b3dbebe401ce0a1c254f38da0b4c87b1ba438e78536d3f7e",
"outputIndex": 0,
"outputGlobalIndex": 50332478,
"outputCreatedAt": 1615347,
"outputSettledAt": 1615349,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(105,-69,41,-112,-47,96,54,47,9,-102,7,-17,93,-105,97,-73,-99,-80,29,-107,9,58,-119,119,-27,-61,-70,-47,-33,78,-5,-50)\n2: 0\n3: Coll(0,8,-51)\n4: 0\n5: 1\n6: 0\n7: 3\n8: 0\n9: false\n10: false\n11: 1\n12: 1\n13: 0\n14: 5\n15: 0\n16: false\n17: false\n18: 0\n19: 0\n20: 0\n21: 2\n22: false\n23: 0\n24: 0\n25: 0\n26: 0\n27: 0\n28: 720\n29: false\n30: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val bool2 = box1.propositionBytes != SELF.propositionBytes\n val coll3 = SELF.R6[Coll[Byte]].get\n val coll4 = placeholder[Coll[Byte]](1)\n val coll5 = SELF.R4[Coll[Byte]].get\n val coll6 = CONTEXT.dataInputs\n val bool7 = coll6.size > placeholder[Int](2)\n val coll8 = placeholder[Coll[Byte]](3)\n sigmaProp(((if (bool2 && (box1.R4[Int].get == placeholder[Int](4))) {(\n val coll9 = box1.tokens\n if ((((((coll9.size == placeholder[Int](5)) && (coll9(placeholder[Int](6))._1 == coll3)) && box1.R5[(Coll[Byte], Long)].isDefined) && box1.R6[Coll[Byte]].isDefined) && box1.R8[Coll[Long]].isDefined) && (box1.R8[Coll[Long]].get.size == placeholder[Int](7))) { (HEIGHT.toLong >= box1.R8[Coll[Long]].get(placeholder[Int](8))) && OUTPUTS.exists({(box10: Box) => ((((((((blake2b256(box10.propositionBytes) == coll4) && (box10.value == SELF.value)) && (box10.tokens == SELF.tokens)) && (box10.R4[Coll[Byte]].get == coll5)) && (box10.R5[Coll[Byte]].get == SELF.R5[Coll[Byte]].get)) && (box10.R6[Coll[Byte]].get == coll3)) && (box10.R7[Coll[Byte]].get == SELF.R7[Coll[Byte]].get)) && (box10.R8[Coll[Byte]].get == SELF.R8[Coll[Byte]].get)) && (box10.R9[Coll[Long]].get == SELF.R9[Coll[Long]].get) }) } else { placeholder[Boolean](9) }\n )} else { placeholder[Boolean](10) } || if (bool2 && (box1.R4[Int].get == placeholder[Int](11))) {(\n val coll9 = box1.tokens\n if ((((((((coll9.size == placeholder[Int](12)) && (coll9(placeholder[Int](13))._1 == coll3)) && box1.R5[(Coll[Byte], Coll[Byte])].isDefined) && box1.R6[Coll[Coll[Byte]]].isDefined) && box1.R7[Coll[Long]].isDefined) && (box1.R7[Coll[Long]].get.size == placeholder[Int](14))) && box1.R8[(Coll[Byte], Long)].isDefined) && box1.R9[(Coll[Byte], Coll[Byte])].isDefined) { (SELF.creationInfo._1.toLong < box1.R7[Coll[Long]].get(placeholder[Int](15))) && OUTPUTS.exists({(box10: Box) => ((((((((blake2b256(box10.propositionBytes) == coll4) && (box10.value == SELF.value)) && (box10.tokens == SELF.tokens)) && (box10.R4[Coll[Byte]].get == coll5)) && (box10.R5[Coll[Byte]].get == SELF.R5[Coll[Byte]].get)) && (box10.R6[Coll[Byte]].get == coll3)) && (box10.R7[Coll[Byte]].get == SELF.R7[Coll[Byte]].get)) && (box10.R8[Coll[Byte]].get == SELF.R8[Coll[Byte]].get)) && (box10.R9[Coll[Long]].get == SELF.R9[Coll[Long]].get) }) } else { placeholder[Boolean](16) }\n )} else { placeholder[Boolean](17) }) || if (bool7) {(\n val box9 = coll6(placeholder[Int](18))\n val coll10 = box9.tokens\n ((((coll10.size > placeholder[Int](19)) && (coll10(placeholder[Int](20))._1 == coll3)) && box9.R6[Coll[Byte]].isDefined) && (box9.R4[Int].get == placeholder[Int](21))) && OUTPUTS.exists({(box11: Box) => (box11.propositionBytes == coll8.append(coll5)) && (box11.value >= SELF.value) })\n )} else { placeholder[Boolean](22) }) || if (bool7) {(\n val box9 = coll6(placeholder[Int](23))\n val coll10 = box9.tokens\n if (((coll10.size > placeholder[Int](24)) && (coll10(placeholder[Int](25))._1 == coll3)) && (box9.R4[Int].get == placeholder[Int](26))) { (HEIGHT.toLong >= box9.R8[Coll[Long]].get(placeholder[Int](27)) + placeholder[Long](28)) && OUTPUTS.exists({(box11: Box) => (box11.propositionBytes == coll8.append(coll5)) && (box11.value >= SELF.value) }) } else { placeholder[Boolean](29) }\n )} else { placeholder[Boolean](30) })\n}",
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"sigmaType": "Coll[SByte]",
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},
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
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"R9": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[20,300,100,20,11,203,20001,203]"
},
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"sigmaType": "Coll[SByte]",
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}
},
{
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"index": 2,
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"outputIndex": 2,
"outputGlobalIndex": 50332480,
"outputCreatedAt": 1615347,
"outputSettledAt": 1615349,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
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],
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{
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},
"R6": {
"serializedValue": "3d05018084af5f",
"sigmaType": "(SBoolean, SLong)",
"renderedValue": "[true,100000000]"
},
"R8": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R7": {
"serializedValue": "0e20cedca8dc7be135c9ae7cae80a953cb3d798d4956cc7b3fac10a4cb1f4a092984",
"sigmaType": "Coll[SByte]",
"renderedValue": "cedca8dc7be135c9ae7cae80a953cb3d798d4956cc7b3fac10a4cb1f4a092984"
},
"R9": {
"serializedValue": "0e046e756c6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e756c6c"
},
"R4": {
"serializedValue": "0e208299d98e15ebee7fa39ad716de7c8bb191790a1bf4b7c3f91af35a0e36187706",
"sigmaType": "Coll[SByte]",
"renderedValue": "8299d98e15ebee7fa39ad716de7c8bb191790a1bf4b7c3f91af35a0e36187706"
}
}
}
],
"outputs": [
{
"boxId": "c464d0e0a9715b1b38287bce1edaaa024e0982a9672d400a94928e3d55d5c340",
"transactionId": "3ffcb2cf4d660dd5ddd7c5b781ec5129df45b5d17cc5f4cc7dd26ec405687b40",
"blockId": "db8577a4b5023aa35e406067ac4127cbfe2d3cabdcde8607c6f4c8fecba4c0d3",
"value": 1000000,
"index": 0,
"globalIndex": 50332527,
"creationHeight": 1615350,
"settlementHeight": 1615352,
"ergoTree": "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",
"ergoTreeConstants": "0: 3\n1: 0\n2: Coll(105,-69,41,-112,-47,96,54,47,9,-102,7,-17,93,-105,97,-73,-99,-80,29,-107,9,58,-119,119,-27,-61,-70,-47,-33,78,-5,-50)\n3: 1\n4: 4\n5: Coll(0,8,-51)\n6: 1\n7: 1\n8: 1\n9: 0\n10: 1\n11: 0\n12: 0\n13: Coll(-14,-39,92,-120,-120,58,-67,-114,-67,-72,-77,-66,-111,-22,45,23,-112,80,27,10,-54,-127,-34,40,-51,-108,-38,-118,-109,51,97,70)\n14: -1\n15: false\n16: true\n17: true\n18: 1\n19: 0\n20: 0\n21: 0\n22: 1\n23: 2\n24: 2\n25: 3\n26: 4\n27: 1\n28: false\n29: false\n30: 0\n31: Coll(47,118,46,-91,-45,7,77,49,21,-3,101,-98,-18,52,34,54,78,-78,106,-125,110,51,90,-38,-17,-46,-34,56,-2,-124,-102,-75)\n32: 0\n33: 0\n34: 2\n35: 1\n36: false\n37: 0\n38: 1\n39: 0\n40: Coll(-10,-127,-98,11,124,-7,-100,-116,120,114,-74,47,73,-123,-72,-39,0,-58,21,9,37,-48,30,-78,121,120,117,23,-88,72,-74,-40)\n41: 0\n42: 0\n43: 3\n44: 30\n45: 4\n46: 1\n47: -1\n48: -1\n49: false\n50: true\n51: 1\n52: false\n53: false\n54: 0\n55: 0\n56: 0\n57: 100\n58: 5\n59: 100\n60: 1000000\n61: 0\n62: 1000000\n63: 0\n64: 0\n65: 1000000\n66: 0\n67: 0\n68: 0\n69: 0\n70: 0\n71: true\n72: 0\n73: SigmaProp(ProveDlog(ECPoint(1bf847,c2be87,...)))\n74: true\n75: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R7[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val bool5 = l2 < l4\n val coll6 = SELF.tokens(placeholder[Int](1))._1\n val tuple7 = SELF.R5[(Coll[Byte], Coll[Byte])].get\n val coll8 = tuple7._2\n val coll9 = placeholder[Coll[Byte]](2)\n val coll10 = tuple7._1\n val coll11 = SELF.R6[Coll[Coll[Byte]]].get\n val l12 = coll3(placeholder[Int](3))\n val l13 = coll3(placeholder[Int](4))\n val tuple14 = SELF.R8[(Coll[Byte], Long)].get\n val l15 = tuple14._2\n val coll16 = placeholder[Coll[Byte]](5)\n sigmaProp(\n (i1 == placeholder[Int](6)) && (\n (if (((bool5 && (INPUTS.size > placeholder[Int](7))) && (OUTPUTS.size > placeholder[Int](8))) && (CONTEXT.dataInputs.size > placeholder[Int](9))) {(\n val box17 = INPUTS(placeholder[Int](10))\n val box18 = CONTEXT.dataInputs(placeholder[Int](11))\n val coll19 = box18.R5[Coll[Byte]].get\n val box20 = OUTPUTS(placeholder[Int](12))\n if (((blake2b256(box17.propositionBytes) == placeholder[Coll[Byte]](13)) && (box17.R6[Coll[Byte]].get == coll6)) && (((coll19 == coll8) && (blake2b256(box18.propositionBytes) == coll9)) && (box18.R6[Coll[Byte]].get == coll6))) {(\n val coll21 = box17.R9[Coll[Long]].get\n val tuple22 = (placeholder[Long](14), placeholder[Boolean](15))\n val l23 = coll21.fold(tuple22, {(tuple23: ((Long, Boolean), Long)) =>\n val tuple25 = tuple23._1\n val l26 = tuple23._2\n if (tuple25._2) { tuple25 } else { if (blake2b256(box17.R7[Coll[Byte]].get.append(longToByteArray(l26)).append(box17.R8[Coll[Byte]].get).append(coll10)) == box17.R5[Coll[Byte]].get) { (l26, placeholder[Boolean](16)) } else { tuple25 } }\n })._1\n val l24 = box18.R9[Coll[Long]].get.fold(tuple22, {(tuple24: ((Long, Boolean), Long)) =>\n val tuple26 = tuple24._1\n val l27 = tuple24._2\n if (tuple26._2) { tuple26 } else { if (blake2b256(box18.R7[Coll[Byte]].get.append(longToByteArray(l27)).append(box18.R8[Coll[Byte]].get).append(coll10)) == coll19) { (l27, placeholder[Boolean](17)) } else { tuple26 } }\n })._1\n (((((((((((((box20.propositionBytes == SELF.propositionBytes) && (box20.R4[Int].get == i1)) && (box20.tokens.size == placeholder[Int](18))) && (box20.tokens(placeholder[Int](19))._1 == coll6)) && (box20.R5[(Coll[Byte], Coll[Byte])].get == (coll10, if ((l23 > l24) || ((l23 == l24) && (box17.creationInfo._1 < box18.creationInfo._1))) { box17.R5[Coll[Byte]].get } else { coll8 }))) && (box20.R6[Coll[Coll[Byte]]].get == coll11)) && (box20.R7[Coll[Long]].get(placeholder[Int](20)) == coll3(placeholder[Int](21)))) && (box20.R7[Coll[Long]].get(placeholder[Int](22)) == l12)) && (box20.R7[Coll[Long]].get(placeholder[Int](23)) == coll3(placeholder[Int](24)))) && (box20.R7[Coll[Long]].get(placeholder[Int](25)) == l4)) && (box20.R7[Coll[Long]].get(placeholder[Int](26)) == l13 + placeholder[Long](27))) && (box20.R8[(Coll[Byte], Long)].get._2 == l15)) && (box20.R9[(Coll[Byte], Coll[Byte])].get == SELF.R9[(Coll[Byte], Coll[Byte])].get)) && OUTPUTS.exists({(box25: Box) => (((((((blake2b256(box25.propositionBytes) == coll9) && (box25.value == box17.value)) && (box25.R4[Coll[Byte]].get == box17.R4[Coll[Byte]].get)) && (box25.R5[Coll[Byte]].get == box17.R5[Coll[Byte]].get)) && (box25.R6[Coll[Byte]].get == box17.R6[Coll[Byte]].get)) && (box25.R7[Coll[Byte]].get == box17.R7[Coll[Byte]].get)) && (box25.R8[Coll[Byte]].get == box17.R8[Coll[Byte]].get)) && (box25.R9[Coll[Long]].get == coll21) })\n )} else { placeholder[Boolean](28) }\n )} else { placeholder[Boolean](29) } || if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](30))) {(\n val coll17 = CONTEXT.dataInputs\n val coll18 = coll17.filter({(box18: Box) => blake2b256(box18.propositionBytes) == placeholder[Coll[Byte]](31) })\n val i19 = coll18.size\n val i20 = coll11.size\n if (if (i19 < if (i20 == placeholder[Int](32)) { placeholder[Int](33) } else { i20 / placeholder[Int](34) + placeholder[Int](35) }) { placeholder[Boolean](36) } else {(\n val coll21 = coll18.map({(box21: Box) => box21.tokens(placeholder[Int](37))._1 })\n coll21.indices.forall({(i22: Int) => !coll21.slice(i22 + placeholder[Int](38), i19).exists({(coll24: Coll[Byte]) => coll24 == coll21(i22) }) }) && coll18.forall({(box22: Box) => (coll11.exists({(coll24: Coll[Byte]) => coll24 == box22.tokens(placeholder[Int](39))._1 }) && (box22.R4[Coll[Byte]].get == placeholder[Coll[Byte]](40))) && (box22.R5[Coll[Byte]].get == coll8) })\n )}) {(\n val box21 = OUTPUTS(placeholder[Int](41))\n val coll22 = box21.R7[Coll[Long]].get\n ((((box21.value >= SELF.value + INPUTS.filter({(box23: Box) => (blake2b256(box23.propositionBytes) == coll9) && (box23.R5[Coll[Byte]].get == coll8) })(placeholder[Int](42)).value) && (coll22(placeholder[Int](43)) >= l4 + placeholder[Long](44))) && (coll22(placeholder[Int](45)) == l13 - placeholder[Long](46))) && (box21.R5[(Coll[Byte], Coll[Byte])].get._2 == coll17.filter({(box23: Box) => blake2b256(box23.propositionBytes) == coll9 }).fold((placeholder[Long](47), Coll[Byte]()), {(tuple23: ((Long, Coll[Byte]), Box)) =>\n val box25 = tuple23._2\n val coll26 = box25.R5[Coll[Byte]].get\n val tuple27 = tuple23._1\n if (coll26 != coll8) {(\n val l28 = box25.R9[Coll[Long]].get.fold((placeholder[Long](48), placeholder[Boolean](49)), {(tuple28: ((Long, Boolean), Long)) =>\n val tuple30 = tuple28._1\n val l31 = tuple28._2\n if (tuple30._2) { tuple30 } else { if (blake2b256(box25.R7[Coll[Byte]].get.append(longToByteArray(l31)).append(box25.R8[Coll[Byte]].get).append(coll10)) == coll26) { (l31, placeholder[Boolean](50)) } else { tuple30 } }\n })._1\n if (l28 > tuple27._1) { (l28, coll26) } else { tuple27 }\n )} else { tuple27 }\n })._2)) && ((box21.R4[Int].get == i1) && (i1 == placeholder[Int](51)))\n )} else { placeholder[Boolean](52) }\n )} else { placeholder[Boolean](53) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](54))) {(\n val box17 = OUTPUTS(placeholder[Int](55))\n val coll18 = INPUTS.filter({(box18: Box) => blake2b256(box18.propositionBytes) == coll9 })\n val l19 = coll18.fold(placeholder[Long](56), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.value })\n val l20 = l19 * l15 / placeholder[Long](57)\n val l21 = l19 * placeholder[Long](58) / placeholder[Long](59)\n val l22 = l19 - l20 - l21\n val bool23 = l22 >= placeholder[Long](60)\n val l24 = if (bool23) { l21 } else { placeholder[Long](61) }\n val l25 = if ((l24 < placeholder[Long](62)) && (l24 > placeholder[Long](63))) { l24 } else { placeholder[Long](64) }\n val l26 = if (bool23) { l12 + l20 } else { l12 }\n val l27 = if ((l26 < placeholder[Long](65)) && (l26 > placeholder[Long](66))) { l26 } else { placeholder[Long](67) }\n val l28 = l26 - l27\n val l29 = l24 - l25\n (\n (\n (\n (box17.value >= if (bool23) { l22 } else { l22 + l20 + l21 } + l25 + l27) && (\n box17.propositionBytes == coll16.append(\n coll18.filter({(box30: Box) => box30.R5[Coll[Byte]].get == coll8 })(placeholder[Int](68)).R4[Coll[Byte]].get\n )\n )\n ) && (box17.tokens(placeholder[Int](69))._1 == coll6)\n ) && if (l28 > placeholder[Long](70)) {\n OUTPUTS.exists({(box30: Box) => (box30.value >= l28) && (box30.propositionBytes == coll16.append(tuple14._1)) })\n } else { placeholder[Boolean](71) }\n ) && if (l29 > placeholder[Long](72)) {\n OUTPUTS.exists({(box30: Box) => (box30.value >= l29) && (box30.propositionBytes == placeholder[SigmaProp](73).propBytes) })\n } else { placeholder[Boolean](74) }\n )} else { placeholder[Boolean](75) }\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "2c5d596d617aaafe16f3f58b2c562d046eda658f0243dc1119614160d92a4717",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f212029e9bb084e932051259f5b2d10c72506368f9777efe13b129853536f1f1d116d",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,29e9bb084e932051259f5b2d10c72506368f9777efe13b129853536f1f1d116d]"
},
"R6": {
"serializedValue": "1a01202da371e44ef2083041fa048a55db55f7013d81f3c12ac79c3f814a282e1c7839",
"sigmaType": "Coll[Coll[SByte]]",
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