Transaction
ID: ceee1b37ad...6837
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...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 805,302
Total coins transferred: 0.0132 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000608 ERG
Raw Transaction Data
{
"id": "ceee1b37ad049d44c4172fa5be2131b50eedf637fdb01fe5be3e66ed482a6837",
"blockId": "f7b08eda84990b8c509fa8c7b9e9f7360ae5dd293306ffe9dc78a7f4e6b5a590",
"inclusionHeight": 960157,
"timestamp": 1678797514581,
"index": 20,
"globalIndex": 4894387,
"numConfirmations": 805302,
"inputs": [
{
"boxId": "82501a087864dc6e1086ccbbe632297c1ad1941d922ab5846ab1abc5e2f2dcbb",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "3f5d1aa6d43266df59169499a85b50bec6ed19ea5e6a7637425a42d043c61e8f",
"outputIndex": 1,
"outputGlobalIndex": 27383155,
"outputCreatedAt": 960143,
"outputSettledAt": 960148,
"ergoTree": "101c04000e204791c75d9e73dd1546e0c391d190350176ba91acdaff9387cf00dc86d6fc33ab04000200020004020400010004000400040004000400040604040402050205c8010500040204000400020004000400040204000400d80bd601b2a4730000d6027301d60393cbc272017202d604e4c6a7041ad6059572037201b2a5730200d606e4c67205041ad607c67205051ad608e67207d609957208b0e472078301027303d901093c0e0eb38c7209018c7209028301027304d60ab472097305b17209d60bb2a5730600957203d801d60cb2b5a5d9010c63d801d60ec6720c041a95e6720e93e4720e72047307730800d19683040193cbc2720ce4c6a7070e938cb2db6308720c730900018cb2db6308a7730a0001efae7206d9010d0e93720483010e720d93cbb3720ab27204730b00e4c6a7060ed801d60ccbc2720b9593720c7202d806d60db5a4d9010d6393c2a7c2720dd60eb1720dd60fb2db6501fe730c00d610e4c6720f0611d611b27210730d00d6129ab27210730e009d9cb27210730f00997eb1e4c6720f041a0573107311d19683080192c1720bb0ad720dd9011363c172137312d90113599a8c7213018c72130293b1b5720dd901136393e4c67213041a72047313ae7206d901130e9383010e7213720493e4c67205060ee4c6a7070e93b17206720e93cbb3720ab27204731400e4c6a7060e93e4c6a7051a83010e957208cbb2e472077315008301027316917e720e05958f7211721272117212d19683050193c5a7c57201938cb2db6308720b731700018cb2db6308a77318000193e4c6720b041a7204938cb2db6308b2a4731900731a0001b27204731b0093720ce4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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": "383d70ab083cc23336a46370fe730b2c51db0e831586b6d545202cbc33938ee1",
"index": 0,
"amount": 1,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120e39047fa7025f5eb94f0b1a9d6d4728b5a4270ea1155e4e5b0e265db46589d5c",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e39047fa7025f5eb94f0b1a9d6d4728b5a4270ea1155e4e5b0e265db46589d5c]"
},
"R5": {
"serializedValue": "1a01205049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
},
"R6": {
"serializedValue": "0e2024af67d9aad2730a8cda71405a76a1acd6596f9e8b7469c5e61f624084a36a69",
"sigmaType": "Coll[SByte]",
"renderedValue": "24af67d9aad2730a8cda71405a76a1acd6596f9e8b7469c5e61f624084a36a69"
},
"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
}
}
},
{
"boxId": "b3c37c0c162153705bde21f803c8500e5817c354c881e294a0d202a2863a0be0",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "8b89ce706ce17e37465cf6910a5a2963b4439b7938666b9573e74ef9fd0e3b6c",
"outputIndex": 1,
"outputGlobalIndex": 27383159,
"outputCreatedAt": 960143,
"outputSettledAt": 960148,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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": "383d70ab083cc23336a46370fe730b2c51db0e831586b6d545202cbc33938ee1",
"index": 0,
"amount": 1,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120d4e03eda58a338f8f65b40de258407dbdbbd9b8ccca374f66be8d97e52c8a752",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d4e03eda58a338f8f65b40de258407dbdbbd9b8ccca374f66be8d97e52c8a752]"
},
"R5": {
"serializedValue": "1a01205049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
},
"R6": {
"serializedValue": "0e20167bf9b3f8d239ae656ef1c05bfa33fca52fff48b4b9afb96455984a5a1c501d",
"sigmaType": "Coll[SByte]",
"renderedValue": "167bf9b3f8d239ae656ef1c05bfa33fca52fff48b4b9afb96455984a5a1c501d"
},
"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
}
}
},
{
"boxId": "00d60e1ef40d119733777cdd46dee476d777a8eba0c83b5be45f34e960b9a2d3",
"value": 1100000,
"index": 2,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "b7392eaf4b898f493fc3f549624f1a791a2474b73a0f05da3f54e01b35ebd707",
"outputIndex": 1,
"outputGlobalIndex": 27383163,
"outputCreatedAt": 960143,
"outputSettledAt": 960148,
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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": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "1a0120c1f5aa4b1a713396a63f556df49c70add93b3471cbca893c6146fce5a4b95e76",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[c1f5aa4b1a713396a63f556df49c70add93b3471cbca893c6146fce5a4b95e76]"
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"R5": {
"serializedValue": "1a01205049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
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"R6": {
"serializedValue": "0e20b6a517bfd70ac9a17d5db47189863f506ba25a46abcebfdeedc25ea7c0c32a9f",
"sigmaType": "Coll[SByte]",
"renderedValue": "b6a517bfd70ac9a17d5db47189863f506ba25a46abcebfdeedc25ea7c0c32a9f"
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"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
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},
{
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"value": 1100000,
"index": 3,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "4da6508fcfd0045e1b34a83b52d4cf69645146daa1f4e29dd8672fa435e6d4a9",
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"outputGlobalIndex": 27383167,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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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"index": 0,
"amount": 1,
"name": "Ergo-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": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
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"sigmaType": "Coll[SByte]",
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"R7": {
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"sigmaType": "Coll[SByte]",
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{
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"index": 4,
"spendingProof": null,
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"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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": [
{
"tokenId": "383d70ab083cc23336a46370fe730b2c51db0e831586b6d545202cbc33938ee1",
"index": 0,
"amount": 1,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120d206d6f37bc63fae26fbb591d5d4b60181db35fb712ae6dfa2c5faf0078d66eb",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d206d6f37bc63fae26fbb591d5d4b60181db35fb712ae6dfa2c5faf0078d66eb]"
},
"R5": {
"serializedValue": "1a01205049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
},
"R6": {
"serializedValue": "0e209da8e7e38abd899273bff5455f62bd28675ca4423c8cd08c58ddefd74ceedd3a",
"sigmaType": "Coll[SByte]",
"renderedValue": "9da8e7e38abd899273bff5455f62bd28675ca4423c8cd08c58ddefd74ceedd3a"
},
"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
}
}
},
{
"boxId": "67a4b886a5b9713283ed2bf8be19f8ab80c9e9b740c0cbb1fd650011945d4fa4",
"value": 1100000,
"index": 5,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "72a2638b510b17e422831c209b9322eb4c41637dc10348b9f5626f710fdc17b3",
"outputIndex": 1,
"outputGlobalIndex": 27383175,
"outputCreatedAt": 960143,
"outputSettledAt": 960148,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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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"index": 0,
"amount": 1,
"name": "Ergo-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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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5adad51d2cf305d93fd951c35ae4cf6e6a04f95303dad300fea20c660181b156"
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"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
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{
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"index": 6,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "76e42b3128efbc7ebf4bc2c9557ad74ae53c9ccf715cfe77e87b9a2b858d733d",
"outputIndex": 1,
"outputGlobalIndex": 27383179,
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"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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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"index": 0,
"amount": 1,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120ed6b8b63d187198f3ba55468231b5c83c050f7273364211fcf3b1ca7526ff302",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[ed6b8b63d187198f3ba55468231b5c83c050f7273364211fcf3b1ca7526ff302]"
},
"R5": {
"serializedValue": "1a01205049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
},
"R6": {
"serializedValue": "0e20e0e68c17ee4037419541dad78a86aad24cdcefeaf63eb4f0537b40db39d39a3a",
"sigmaType": "Coll[SByte]",
"renderedValue": "e0e68c17ee4037419541dad78a86aad24cdcefeaf63eb4f0537b40db39d39a3a"
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"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
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{
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"value": 1100000,
"index": 7,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "9c0e327ee0e9dddcd419fdd48eba2752d946d4e7bd0382bd10dbaa49da55447d",
"outputIndex": 1,
"outputGlobalIndex": 27383183,
"outputCreatedAt": 960143,
"outputSettledAt": 960148,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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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"index": 0,
"amount": 1,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[730488119f223822c77c9c89fa73e1794116dd1503fcabf3fc9217ffe7b7b508]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "4de72f40d052003a63878fea04fc99bec1a32c853600d07311a34c6be8526ac5"
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"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
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{
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"value": 1100000,
"index": 8,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "a40e3e9bda123c2df7b92daa229a13e3d07a56bb94b2612a16d51032d166bfed",
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"outputGlobalIndex": 27383187,
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"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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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"index": 0,
"amount": 1,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120da06f26f55cca0ad06880e0e8fe40d4011373e526f6aafe47caba8f5fa169707",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[da06f26f55cca0ad06880e0e8fe40d4011373e526f6aafe47caba8f5fa169707]"
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"R5": {
"serializedValue": "1a01205049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5049744f0d84de8da38fbd0cf5e48f91d4f6ae45c421d3daa792350a48c05a8e]"
},
"R6": {
"serializedValue": "0e203b91089d8789d452878b19799b15871f244f121b9e6cfac2eb16daea58a45e48",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b91089d8789d452878b19799b15871f244f121b9e6cfac2eb16daea58a45e48"
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"R7": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
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{
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"value": 1100000,
"index": 9,
"spendingProof": null,
"outputBlockId": "68e3a235df7c9d08588a2ce113dec1c85b2b7e7485f530ee07f15c210b193699",
"outputTransactionId": "f2bcac2f09bc9807f3b3c4121bbc72073e738350ea73e90f142ec3afc7860e2f",
"outputIndex": 1,
"outputGlobalIndex": 27383191,
"outputCreatedAt": 960143,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,-111,-57,93,-98,115,-35,21,70,-32,-61,-111,-47,-112,53,1,118,-70,-111,-84,-38,-1,-109,-121,-49,0,-36,-122,-42,-4,51,-85)\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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"type": "EIP-004"
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(1dd9f3,1ca860,...)))}",
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"address": "9ggxCpx47tL8Ty5DeH2VJM6VcWS1P7PdmXVhCYSjmC4Q7bCeFrh",
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"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[6572676f,c1f5aa4b1a713396a63f556df49c70add93b3471cbca893c6146fce5a4b95e76,d4e03eda58a338f8f65b40de258407dbdbbd9b8ccca374f66be8d97e52c8a752,ed6b8b63d187198f3ba55468231b5c83c050f7273364211fcf3b1ca7526ff302,846f72637b75f4817eb3f6e8542cb2d92875cf1ddce0fd5b734fc7c9bb48ac60,101f5f0995d90c80a9491815571ed1c9fc5522922fa3bbccbd575d1aa7255f90,e09921d0a87bb63e94aa6074c090a903a280ebd8cfba862396e56668f7138fe1,730488119f223822c77c9c89fa73e1794116dd1503fcabf3fc9217ffe7b7b508,da06f26f55cca0ad06880e0e8fe40d4011373e526f6aafe47caba8f5fa169707,d206d6f37bc63fae26fbb591d5d4b60181db35fb712ae6dfa2c5faf0078d66eb,e39047fa7025f5eb94f0b1a9d6d4728b5a4270ea1155e4e5b0e265db46589d5c]"
},
"R5": {
"serializedValue": "110b00c801c801d00fd00fd00fd00fd00fd00fd00fc801",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,100,100,1000,1000,1000,1000,1000,1000,1000,100]"
},
"R6": {
"serializedValue": "1104d00f8c010228",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000,70,1,20]"
},
"R7": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
}
}
}
],
"outputs": [
{
"boxId": "7b400edbe39be38b5b38e91f14534fdd1fcd1d81b85d17a01e5456bff4124ec7",
"transactionId": "ceee1b37ad049d44c4172fa5be2131b50eedf637fdb01fe5be3e66ed482a6837",
"blockId": "f7b08eda84990b8c509fa8c7b9e9f7360ae5dd293306ffe9dc78a7f4e6b5a590",
"value": 11000000,
"index": 0,
"globalIndex": 27384168,
"creationHeight": 960154,
"settlementHeight": 960157,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-73,-16,-100,27,10,-105,77,102,-103,-87,89,58,40,104,8,-83,18,116,-113,-88,2,90,-71,-83,-53,36,55,94,3,-107,-8,21)\n3: 1\n4: 0\n5: Coll(55,8,14,-89,-110,92,64,121,101,-14,112,19,-2,102,-46,-25,-42,-110,-26,-115,-64,-34,-110,25,-17,-2,72,25,-50,-88,-57,-77)\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": "21oSXpSmAC6qp2H72o1YW4D9Dxq3mSkee28gWAFqqd9NRTx15VHM6RwVxScoDnN4jiTegJvto6yK4rZDV788EKrJdoftYXVdQDaeakfgJJhLSfpJcadGZLLwJQkpoRJpesAgY8QfkuyLTkVNbNNshvsA4x3kfvPFDGDQfn8AdN6hJ1FnibRdcj3uY9NQTjjLWNGb1XNdUQyGv73qBJobfaRm9GyXzk9wUq54VhKdcxzTjzuJTtCCv2cxBXKup4EzEEXDNWLcfsD8bNknob5bmUDuTGszsPZHcwAwXgcqsxKvcki7KUs7d666iyu5fNgvFTx8B3D1ageWpAD5RcBbmfiGNEL9k7BnwWiP2pU5DwhJzWH3iU",
"assets": [
{
"tokenId": "383d70ab083cc23336a46370fe730b2c51db0e831586b6d545202cbc33938ee1",
"index": 0,
"amount": 10,
"name": "Ergo-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e39047fa7025f5eb94f0b1a9d6d4728b5a4270ea1155e4e5b0e265db46589d5c,d4e03eda58a338f8f65b40de258407dbdbbd9b8ccca374f66be8d97e52c8a752,c1f5aa4b1a713396a63f556df49c70add93b3471cbca893c6146fce5a4b95e76,e09921d0a87bb63e94aa6074c090a903a280ebd8cfba862396e56668f7138fe1,d206d6f37bc63fae26fbb591d5d4b60181db35fb712ae6dfa2c5faf0078d66eb,846f72637b75f4817eb3f6e8542cb2d92875cf1ddce0fd5b734fc7c9bb48ac60,ed6b8b63d187198f3ba55468231b5c83c050f7273364211fcf3b1ca7526ff302,730488119f223822c77c9c89fa73e1794116dd1503fcabf3fc9217ffe7b7b508,da06f26f55cca0ad06880e0e8fe40d4011373e526f6aafe47caba8f5fa169707,101f5f0995d90c80a9491815571ed1c9fc5522922fa3bbccbd575d1aa7255f90]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[64323664333363623063376639623763313966303734306436313536613363633938613430313465376565316265643931626437353535663763393261353366,6572676f,63617264616e6f,3967376372356e3545487077416a6f595a70706a74575a663464754c434d46467a6f50736756364c744b447a5242634a324863,61646472317139373779347334783337757a3463777775676e647170633933706d737366326c64303566356e676c6d6b66336b6a786d63643632397a7a6c7a3666356c3870326674777473716766343532676574707833356b6363733573347171666576327067,000000001d021d39,000000000bebc200,00000000000f4240,657267,617373657431703430723065756e32616c737a6c78686a376b3475796c796134636a35346c786b6a6a6d736d,35663863643036393435346638313031313365353563666237333061666337313664336161356531356634653962376332356162386665353430633437303164,00000000000ea687]"
},
"R6": {
"serializedValue": "0e20ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ed7f723921f2efd4ec2fbc6a1262376e346c130e6aff4daf63addfe996f2d71c"
}
},
"spentTransactionId": "8150cc835c872179d4027982600b6cd68f5cce1db9492ef8a29f73d4facd06b3",
"mainChain": true
},
{
"boxId": "2cb129c6738c7bdc8c93a30063a5105109252ea3b6c6ce8bcbdd4a5ec1bfed02",
"transactionId": "ceee1b37ad049d44c4172fa5be2131b50eedf637fdb01fe5be3e66ed482a6837",
"blockId": "f7b08eda84990b8c509fa8c7b9e9f7360ae5dd293306ffe9dc78a7f4e6b5a590",
"value": 1100000,
"index": 1,
"globalIndex": 27384169,
"creationHeight": 960154,
"settlementHeight": 960157,
"ergoTree": "0008cd031dd9f3a88b1625db4d6b5618db6afd3da1a1cf21b598e33a6ba32abace1f0e04",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(1dd9f3,1ca860,...)))}",
"address": "9ggxCpx47tL8Ty5DeH2VJM6VcWS1P7PdmXVhCYSjmC4Q7bCeFrh",
"assets": [
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 0,
"amount": 19266,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "994b14e8a3a5a99e4d1f9a047939da9c6ce7b4b13b0b18b6be7cef9689290a9e",
"transactionId": "ceee1b37ad049d44c4172fa5be2131b50eedf637fdb01fe5be3e66ed482a6837",
"blockId": "f7b08eda84990b8c509fa8c7b9e9f7360ae5dd293306ffe9dc78a7f4e6b5a590",
"value": 1100000,
"index": 2,
"globalIndex": 27384170,
"creationHeight": 960154,
"settlementHeight": 960157,
"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": "68bfc47c8f5e07f6c362222ef1e3efba9089908bf784258ccb255ce2cde311f4",
"mainChain": true
}
],
"size": 1810,
"isUnconfirmed": false
}