Transaction
ID: 17697b3b28...d078
Inputs (12)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 799,512
Total coins transferred: 0.0132 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000588 ERG
Raw Transaction Data
{
"id": "17697b3b280e5b05b6f2b81d19b53104e43359ce79cdbc193678153df751d078",
"blockId": "6793cb60b246abf90acf1c9dc4acb1f583464feed195c067d15fb6af1a97ac2e",
"inclusionHeight": 960156,
"timestamp": 1678797383200,
"index": 25,
"globalIndex": 4894363,
"numConfirmations": 799512,
"inputs": [
{
"boxId": "7f674cf9e1baeaf358552aeeb17c7c45e32f11e2684e800230094c4c4357fddf",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
"outputTransactionId": "0b1c064b53378e0b9ea447c8fa46ed61898c468bd7263947a1c87068aee1771a",
"outputIndex": 1,
"outputGlobalIndex": 27383001,
"outputCreatedAt": 960142,
"outputSettledAt": 960146,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b]"
},
"R5": {
"serializedValue": "1a0120e3a36dbeafe863be4d17f50c3ca9e0ac3d92a833aaa27db53b85e7d8588d4d3f",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e3a36dbeafe863be4d17f50c3ca9e0ac3d92a833aaa27db53b85e7d8588d4d3f]"
},
"R6": {
"serializedValue": "0e20f5438385454e6ec5ce565d957828ad1101461d16d212daf568e6a4ee1de3bd09",
"sigmaType": "Coll[SByte]",
"renderedValue": "f5438385454e6ec5ce565d957828ad1101461d16d212daf568e6a4ee1de3bd09"
},
"R7": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
}
}
},
{
"boxId": "2377be21e692375f54c3213076a8950fc2a6983bdb0441d1ff9ab8b5a449befc",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
"outputTransactionId": "1cdb86beb20f1fb04817faea760ea266d553fac06ba4ea36dc8c9ca05bc312b9",
"outputIndex": 1,
"outputGlobalIndex": 27383005,
"outputCreatedAt": 960142,
"outputSettledAt": 960146,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
"address": "58grLgCGkp4jiVK8vkjKLHfvgryuUoo9aoELjx9stSh6Q4fBk1Y9y4bC7JsWRNPSSiuNqqYk7DnFQ99CMetbVjuCqr8ztfNhBvYBHFRAWzfjj43GZG2Tp2XPcyXJ7fc51hcmQanMchp1jCkakdoFnUM4aXL8cvjZwienr1hngZN1BH4VJJTqCuwPSNc5gC5yBByKwUrKSxKNAmgYgBsVYCBokUb6e8dYadrf2cxNTMamMZHh6wBzMK1KMbTJcu5pRwJB32rhWYNCVvZZq3nD2GmYQydWEDmGoU5NW4YkhwxCzzvX3emKknNdoESx4Py3oGUvYfvjC2cykxua7jEbgcgXwri7d4nJWneY6YkSz5xxtBnBUKt55oGTwffzvN4ESe7hUkL5p3cFNNZFb3gPXhwGxC7xtCae5YkSdzE4uX9dfkajgRxFcqkAKaUM7caAfUBpV4jqZxgwDixXqyWdyLw8ZxCi4QWtDBttQ8C72Ne7DmiW4p7E6Ym8LTRgXTKFVHuipSPw8hDXVgn3wg6WtNpB5Fwo6jvByyBWjUeDhtfgAcTe7sL2iFGXXtEyS6y29fmauRTTfR44ipDxASHdu9uBwscU7ZQmqN4W4Xj5BGMM4ocNrS83zKPm5WPMTrkETmZr4qAoFAfg6LkYjDyNgxrnjySSe4BdCCixswYHJG7h2Rkf52kQMXgzeE8wFYoUAx2qgahx9qP7wFtF3BqnStjPmWYb1L4zc1gHHg2BB19abi1x2BFzanXaWRD9rU8fToJfN9wBuQUqS779hH6KYH9SWJVmeGJuzwfPfrVfgekkrbuDh2ADTQV38p5kXtHHsdJwCGt2rMm8yJ7Kf",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01200b5fe301668c691ba7310038a612e01b717f20062dd19c1a4552edb7b0037ce1",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[0b5fe301668c691ba7310038a612e01b717f20062dd19c1a4552edb7b0037ce1]"
},
"R5": {
"serializedValue": "1a0120e3a36dbeafe863be4d17f50c3ca9e0ac3d92a833aaa27db53b85e7d8588d4d3f",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e3a36dbeafe863be4d17f50c3ca9e0ac3d92a833aaa27db53b85e7d8588d4d3f]"
},
"R6": {
"serializedValue": "0e203a0dd194803e58cf4737357ef460814e6a6dfc18fc610d755c76e29ccb4038f5",
"sigmaType": "Coll[SByte]",
"renderedValue": "3a0dd194803e58cf4737357ef460814e6a6dfc18fc610d755c76e29ccb4038f5"
},
"R7": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
}
}
},
{
"boxId": "318146256bd55666c0e886d385278b76f850e136bc1bc9860fdc99e2d4d3df94",
"value": 1100000,
"index": 2,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
"outputTransactionId": "3038c524833aaef1d38468da96fb3dbed38234559b44ade9a5d6b3a1568f6be6",
"outputIndex": 1,
"outputGlobalIndex": 27383009,
"outputCreatedAt": 960142,
"outputSettledAt": 960146,
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"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
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"sigmaType": "Coll[Coll[SByte]]",
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"R5": {
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"R7": {
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"sigmaType": "Coll[SByte]",
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{
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"index": 3,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
"outputTransactionId": "535dbb9882ce0506f0223d3b16c22838e619e455bacc5e64d939292b53e8dc2a",
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"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"spendingProof": null,
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"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[294bbe6ae9df2b402d93536ef7b741e0ccc7527f7d51a09ee50606b30491388f]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e3a36dbeafe863be4d17f50c3ca9e0ac3d92a833aaa27db53b85e7d8588d4d3f]"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "2c604aaa9930083d0633730be8120f9193fcb7e405555af5dfe44443a58e2ab5"
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"R7": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
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{
"boxId": "e43e98f8cb6007100555d6274dd813ae4164f24b88bad565fc71839ab4cba298",
"value": 1100000,
"index": 5,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
"outputTransactionId": "6d7788361a3910c067a05077e498b8d7dd18cf0368372b55e07690f063115727",
"outputIndex": 1,
"outputGlobalIndex": 27383021,
"outputCreatedAt": 960142,
"outputSettledAt": 960146,
"ergoTree": "101c04000e20fac086e399443b5196f66c5296eeb589cc8a3a9b0187ab2a4de38ab9b3e2f3bd04000200020004020400010004000400040004000400040604040402050205c8010500040204000400020004000400040204000400d80bd601b2a4730000d6027301d60393cbc272017202d604e4c6a7041ad6059572037201b2a5730200d606e4c67205041ad607c67205051ad608e67207d609957208b0e472078301027303d901093c0e0eb38c7209018c7209028301027304d60ab472097305b17209d60bb2a5730600957203d801d60cb2b5a5d9010c63d801d60ec6720c041a95e6720e93e4720e72047307730800d19683040193cbc2720ce4c6a7070e938cb2db6308720c730900018cb2db6308a7730a0001efae7206d9010d0e93720483010e720d93cbb3720ab27204730b00e4c6a7060ed801d60ccbc2720b9593720c7202d806d60db5a4d9010d6393c2a7c2720dd60eb1720dd60fb2db6501fe730c00d610e4c6720f0611d611b27210730d00d6129ab27210730e009d9cb27210730f00997eb1e4c6720f041a0573107311d19683080192c1720bb0ad720dd9011363c172137312d90113599a8c7213018c72130293b1b5720dd901136393e4c67213041a72047313ae7206d901130e9383010e7213720493e4c67205060ee4c6a7070e93b17206720e93cbb3720ab27204731400e4c6a7060e93e4c6a7051a83010e957208cbb2e472077315008301027316917e720e05958f7211721272117212d19683050193c5a7c57201938cb2db6308720b731700018cb2db6308a77318000193e4c6720b041a7204938cb2db6308b2a4731900731a0001b27204731b0093720ce4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"name": "Cardano-RWT-V.beta",
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"type": "EIP-004"
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"index": 6,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
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"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"index": 0,
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"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
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"sigmaType": "Coll[Coll[SByte]]",
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"R5": {
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"renderedValue": "[e3a36dbeafe863be4d17f50c3ca9e0ac3d92a833aaa27db53b85e7d8588d4d3f]"
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"sigmaType": "Coll[SByte]",
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"R7": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
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{
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"value": 1100000,
"index": 7,
"spendingProof": null,
"outputBlockId": "f9e214dfe91bfbb5fdecf2a8852d96160e7f4a52c842d085982ee90128b73a52",
"outputTransactionId": "9c94020a09b0b896da7c7d133edaac273ea7750be406203d24489e35864a0aa8",
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"outputGlobalIndex": 27383029,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"assets": [
{
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"name": "Cardano-RWT-V.beta",
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"sigmaType": "Coll[Coll[SByte]]",
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"R5": {
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"R7": {
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"sigmaType": "Coll[SByte]",
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"spendingProof": null,
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"ergoTreeConstants": "0: 0\n1: Coll(-6,-64,-122,-29,-103,68,59,81,-106,-10,108,82,-106,-18,-75,-119,-52,-118,58,-101,1,-121,-85,42,77,-29,-118,-71,-77,-30,-13,-67)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 1\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll13.size\n val box15 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](13))\n val l18 = coll16(placeholder[Int](14)) + coll16(placeholder[Int](15)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box19: Box) => box19.value }).fold(\n placeholder[Long](18), {(tuple19: (Long, Long)) => tuple19._1 + tuple19._2 }\n ), coll13.filter({(box19: Box) => box19.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](19), coll6.exists(\n {(coll19: Coll[Byte]) => Coll[Coll[Byte]](coll19) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i14, blake2b256(coll10.append(coll4(placeholder[Int](20)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](21))) } else { Coll[Byte](placeholder[Byte](22)) }\n ), i14.toLong > if (l17 < l18) { l17 } else { l18 }\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](23))._1 == SELF.tokens(placeholder[Int](24))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[6572676f,77e739069bedab7311ba06ad9fbd0c52fb5a09d9ffa21a31deca925b09773fbe,484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029,f9f75e886f9f88a3ba0809ae60accd3de67ab0ce5ba3436524c5bf666dd3b1dc,294bbe6ae9df2b402d93536ef7b741e0ccc7527f7d51a09ee50606b30491388f,8abfa5881954da4848d720847f3b4f1577682cf5738827388bf418f2487f4852,9f3c93a1d23a8f9e7724c30d81bd3b8ba69f20c89753699a994b82bf6ae26925,eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b,0b5fe301668c691ba7310038a612e01b717f20062dd19c1a4552edb7b0037ce1,9dc9311055af1547a6739d7cdd5e17b75aa7338e8990f41fff40bbbe0d644446,005740bfc12e8af70d5230c872be782a3201312108579c7461780ef590268168]"
},
"R5": {
"serializedValue": "110b00d00fd00fd00fd00fd00fd00fd00fd00fd00fd00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1000,1000,1000,1000,1000,1000,1000,1000,1000,1000]"
},
"R6": {
"serializedValue": "1104d00f8c010228",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000,70,1,20]"
},
"R7": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
}
}
}
],
"outputs": [
{
"boxId": "83a2f97582f9114870a67fa98904775f262d1a0c6430909e01808b64eedc129f",
"transactionId": "17697b3b280e5b05b6f2b81d19b53104e43359ce79cdbc193678153df751d078",
"blockId": "6793cb60b246abf90acf1c9dc4acb1f583464feed195c067d15fb6af1a97ac2e",
"value": 11000000,
"index": 0,
"globalIndex": 27384073,
"creationHeight": 960151,
"settlementHeight": 960156,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(10,-76,-39,-12,-34,6,-68,-85,-55,71,58,10,41,-35,11,-97,40,21,-110,38,-16,-85,-71,-43,-61,93,79,119,-58,-104,3,-31)\n3: 1\n4: 0\n5: Coll(-8,51,-9,86,-31,-65,-99,21,-72,-7,-124,-82,-6,100,72,32,64,-42,-56,-77,-20,33,123,43,-24,-72,-92,119,-24,45,-112,13)\n6: 7200\n7: Coll(106,26,12,-10,30,-60,20,-119,22,40,30,109,-126,-95,-47,122,96,-18,-41,-124,82,0,64,29,82,49,55,127,70,67,-70,103)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Coll[Byte]]].get\n val i2 = coll1.size\n val coll3 = OUTPUTS.slice(placeholder[Int](0), i2)\n val coll4 = OUTPUTS(placeholder[Int](1)).propositionBytes\n val coll5 = blake2b256(coll4)\n sigmaProp(allOf(Coll[Boolean](i2 == coll3.size, coll1.zip(coll3).forall({(tuple6: (Coll[Byte], Box)) =>\n val box8 = tuple6._2\n (Coll[Coll[Byte]](tuple6._1) == box8.R4[Coll[Coll[Byte]]].get) && (box8.propositionBytes == coll4)\n }), if (coll5 == placeholder[Coll[Byte]](2)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](3)).tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), HEIGHT - placeholder[Int](6) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](7) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
"address": "21oSXpSmAC6qWRafUZuukJvGaH5cWHsyZd4TyLmPq3rC5PDEEdMmk9Tn7iyYG4omoiPcwLqaHPTczj5EADDMEK8M2hX5ESrUQZ2E7V3Ca2yxRQ3RiyoGFN348Rrkp6MY5ExjdEPj9Tv6ygeRjcDTjwXGufdj51AKbFn8Jtx9jHCAR5vEpFFiJtV1FWCbc1tfVzgXojGkrBQjrazCsYaKm1Ed2zsC97He6RV5bPDLYMp4o9m6HDSXS3Ea9weh7PBWeLzUttV54AfGtAS3RQ7Wc2DvdRZYju1Kz7ZxiQEYmeSDzrrh3g6atG2RnbRXCJQrA3xFuSkc4ERCMcWojzy2YWrZcCQJC6SpXhnzQ8wJphWEutgtqo",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 10,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b,0b5fe301668c691ba7310038a612e01b717f20062dd19c1a4552edb7b0037ce1,005740bfc12e8af70d5230c872be782a3201312108579c7461780ef590268168,77e739069bedab7311ba06ad9fbd0c52fb5a09d9ffa21a31deca925b09773fbe,294bbe6ae9df2b402d93536ef7b741e0ccc7527f7d51a09ee50606b30491388f,f9f75e886f9f88a3ba0809ae60accd3de67ab0ce5ba3436524c5bf666dd3b1dc,484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029,8abfa5881954da4848d720847f3b4f1577682cf5738827388bf418f2487f4852,9dc9311055af1547a6739d7cdd5e17b75aa7338e8990f41fff40bbbe0d644446,9f3c93a1d23a8f9e7724c30d81bd3b8ba69f20c89753699a994b82bf6ae26925]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[65396632653136666564623932333063363933326230656563393632343837653936326665656565383233353634363564396335376365386530366363353661,63617264616e6f,6572676f,616464723171796470643565676472766671396836613071736837356e7373746d766b617a3061646a766d64363837636735796a77676e6866643373636d6a616d32783666336b7075746367743470357168353973336b777761366564786a7873346873376878,39677864333139696d5336444b6f66377a4a3164525269424d5973745359367a50484e506f534c364a74694c7a6b3154574d33,0000000000000e6d,0000000000000bb8,000000000000012c,6173736574317677756e30613532786a763574633278393277677236783370367133753466726e6d71387130,35313763393162346561363830313636646464336636376232376230323734633230626264326165623832623630656166356266353437316233376636383461,64393861336135383865646434363630623461353761336630333831653735386236373035336138633935666435386633616336356166646434386639326230,000000000081f1c0]"
},
"R6": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
}
},
"spentTransactionId": "c4cfea8cbcdf615d013c141f4580827a299cd6165fbcb95f1994eea42a2249f0",
"mainChain": true
},
{
"boxId": "a4d71e6ad6a5254dd6f80990f86624b4d868298806df51a35478927ccbd137fe",
"transactionId": "17697b3b280e5b05b6f2b81d19b53104e43359ce79cdbc193678153df751d078",
"blockId": "6793cb60b246abf90acf1c9dc4acb1f583464feed195c067d15fb6af1a97ac2e",
"value": 1100000,
"index": 1,
"globalIndex": 27384074,
"creationHeight": 960151,
"settlementHeight": 960156,
"ergoTree": "0008cd02c32af9ee1aa0aa2b24f8a1a30e6ff15b9cbf7613e929bdb5fbf2de79b72259d4",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c32af9,f8c208,...)))}",
"address": "9g11pJtHqBDNxdzWrChmbm89DUgP7sxZJD8Rcme6rH1B1FQZUS4",
"assets": [
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 0,
"amount": 9375,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "86835ef6288207f915a2219a8e2916095d82b684cecca46e948b5f8fcd5cbd34",
"mainChain": true
},
{
"boxId": "4a44f82e33d0fa178a29b660103740176d2e07be21417c24df75743164408a99",
"transactionId": "17697b3b280e5b05b6f2b81d19b53104e43359ce79cdbc193678153df751d078",
"blockId": "6793cb60b246abf90acf1c9dc4acb1f583464feed195c067d15fb6af1a97ac2e",
"value": 1100000,
"index": 2,
"globalIndex": 27384075,
"creationHeight": 960151,
"settlementHeight": 960156,
"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": "21521ea9db3b689556523db3daff7a5002967c36d43ec93a24f1543dc46a75ef",
"mainChain": true
}
],
"size": 1870,
"isUnconfirmed": false
}