Transaction
ID: 038c57eb31...7034
Inputs (16)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
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0.005 ERG
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Output transaction:
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0.005 ERG
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0.005 ERG
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Output transaction:
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Value:
0.005 ERG
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Address:
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0.005 ERG
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0.005 ERG
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0.005 ERG
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0.005 ERG
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0.005 ERG
Tokens:
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Spent
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Output transaction:
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0.005 ERG
Tokens:
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Spent
Address:
Output transaction:
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0.005 ERG
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Output transaction:
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0.005 ERG
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0.005 ERG
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0.005 ERG
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77.59 ERG
Outputs (18)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
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Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
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Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
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Spent
Address:
Spent in transaction:
Settlement height:
Value:
75.18 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.25 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Confirmations: 684,164
Total coins transferred: 77.66 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000211 ERG
Raw Transaction Data
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"outputTransactionId": "dd3281bd613c93073ac40d4f314d26225bdd298215ffe5cc63494a021405c11a",
"outputIndex": 0,
"outputGlobalIndex": 32407196,
"outputCreatedAt": 1085202,
"outputSettledAt": 1085204,
"ergoTree": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e496bf,1508e8,...)))}",
"address": "9gFjWZu9qg2Qoq4efpa8Eu6FrigkistVrYqAUA4u6QhDKbKPBGd",
"assets": [
{
"tokenId": "42af4a7d273b47ee81e4e6c38cd47d3d84c808fe9ff283a98423643986a11312",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
},
"R8": {
"serializedValue": "0e2023b4418190915608397759d7231169baa7eb3eceb5244da902b9636ef99f86f8",
"sigmaType": "Coll[SByte]",
"renderedValue": "23b4418190915608397759d7231169baa7eb3eceb5244da902b9636ef99f86f8"
},
"R7": {
"serializedValue": "0e020101",
"sigmaType": "Coll[SByte]",
"renderedValue": "0101"
},
"R9": {
"serializedValue": "0e42697066733a2f2f626166796265696164697a3577787836616f7534737a7976746565776c6c756f70346861696471657a34676274616862697a697967793373727171",
"sigmaType": "Coll[SByte]",
"renderedValue": "697066733a2f2f626166796265696164697a3577787836616f7534737a7976746565776c6c756f70346861696471657a34676274616862697a697967793373727171"
},
"R4": {
"serializedValue": "0e1161736868687838202d20476869626c6920",
"sigmaType": "Coll[SByte]",
"renderedValue": "61736868687838202d20476869626c6920"
}
}
},
{
"boxId": "44e4d8cc74567cc2255a068ecdca889a22e89fdc7711d77e23c2f96cfe834414",
"value": 77589220260,
"index": 15,
"spendingProof": "d1dc65465490b312a5dcb20ace8fd02f73819ce607dc7897e6239fdac91cbd8e79a390070e70606213ed9cdcae68558ac7d4d64fcef05ec2",
"outputBlockId": "eaae4dda8831d41f02cfb1249aa0970f79e2db70155b88a7eb1925416f3c1239",
"outputTransactionId": "16e2b549761ed05b25d1c8e4603c2be63d88d4131f37913fe57c646de50f86fa",
"outputIndex": 1,
"outputGlobalIndex": 32407172,
"outputCreatedAt": 1085202,
"outputSettledAt": 1085204,
"ergoTree": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e496bf,1508e8,...)))}",
"address": "9gFjWZu9qg2Qoq4efpa8Eu6FrigkistVrYqAUA4u6QhDKbKPBGd",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "573d9010b852894b9f99bc072933e6cfa115b490f857451e385dbc2e8448cf7c",
"value": 4219364,
"index": 0,
"outputBlockId": "b3cfb684232fe21e89a8132c966b08c6772b72369822c397d25a7bc8e98c9bda",
"outputTransactionId": "aa58e9d389d3044fda4201159d5d62752e0820f8d0b8506cec28ac4fd0ea826e",
"outputIndex": 0,
"ergoTree": "0008cd03b04048a9708f0a2b109d75513a2483e3b9ede622efb3cc03bdddf93bccd93ac5",
"address": "9hoRnjysKfkwZSCgSFNzSXMohwYn8DqruuYxD6vT7Ubw55qnwiZ",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e240008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd03d4e3f9c9956945986a2bc2621a2fc02b9f7492fe57c87be07a33a0d7ccef5bc8"
},
"R6": {
"serializedValue": "0580dac409",
"sigmaType": "SLong",
"renderedValue": "10000000"
},
"R8": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R7": {
"serializedValue": "110280dddb0180fca402",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1800000,2400000]"
},
"R4": {
"serializedValue": "0428",
"sigmaType": "SInt",
"renderedValue": "20"
}
}
}
],
"outputs": [
{
"boxId": "5702d78fbd1dd2123aa6242d47c6a0e5bef383456f65a8537c74cdc0df14edeb",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 0,
"globalIndex": 32423925,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "f8e50492f1b934836fd77a92e36c8824503fe9cc6c6e4eadf2a64617340d5127",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "353518b6d5d08351a7b19ea045e8bc58d0e04b2e39bef921239ea747199ac6d2",
"mainChain": true
},
{
"boxId": "01880a3984d23931e3af11a8acbd0740cc87c690216a75a482896e239590df9a",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 1,
"globalIndex": 32423926,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "103f040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e4722b95ec8f723473209272347321d802d635b2a5732201a7d636b2db6308723573230186027202c17235eded928c7236029d9c720a7e7234057324938c723601720993c27235c2722a95ed9372347325e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732673277236adb4a573289a73297236d9013763d801d639b2db63087237732a0186027202c1723795938c72390172098602c272378c72390286027202732b732c732d93cbc3722a8c723301d808d620b2a5732e00d621db63087220d622b27221732f0186027202c17220d6238c722202d6249172117330d625e4c672120711d626b2a5733100d627b2db6308722673320186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733300ed7224927223721193b27201733400b2722173350093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257336009a7210b27225733700721093c672200611720693e4c67220070e720993b172219593b1720973387339733a93c27226721eeced938c7227017209928c722702720a93720a733b733cd1938cb2db63087212733d0001733e",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "5117de959b864fb5c83de5554c65ab2670668f69923a26bf6d9218c621492c8d",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "6d1d58922a2a0d0be3ec065cd940170b74c660b2e7fb77be3dfe1ed0c9f8e257",
"mainChain": true
},
{
"boxId": "14f4f40c6db8709c202c8df86ddab4401ce3d466ede80d2d3b6203a0fb5a0778",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 2,
"globalIndex": 32423927,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "6f2554ad9e28c6bec02d5adae82827bfef2d45c4dffb9c029e4a408b40e77bf0",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "f1fa2e98d9fcd2f17cc2ba61dedc5ed0f37e2dbcebc8a37729c49b6f44e2679a",
"mainChain": true
},
{
"boxId": "9ab0fe72685852de3d12fc52a1d95adbbe37b96e9fe3fac2934b2ba0ba4737db",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 3,
"globalIndex": 32423928,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "e0b810644196c6d07652865cddfe91e73d177d2609669f824e87e8ac5ad14ba1",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "f389b6fc71b51f65a16b4853e456541dad2aec901b1da52f00aa223cedbd0284",
"mainChain": true
},
{
"boxId": "698257625294e97f24939e8f311ef70b76cd743a311806f61d96e70dc963a3cc",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 4,
"globalIndex": 32423929,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "c71e80d8bc725dd6277f98856392eefffe4f4cf79660a496967c036fb7aac320",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "d8c51d56cd60c048cc3ba51e5bd73421f94599f17b3956b95a72e93b3c471af1",
"mainChain": true
},
{
"boxId": "8a87d9fd4f254f494454a25773cfb39b0583dfb140bae1127ca8256aacf1189f",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 5,
"globalIndex": 32423930,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "3NtW3QbiLwaF7f2h7NyiFZwSV3LqNwFNBH5HQgzeGtttvsLCS4e19bjkpDbuNbzBXtjvK3eyi94G9YNjeR94F4ix5iAXHSwmSsZ2ftbMCBfxf9JfgouBAvbrcKoDnioJmQdTfQLi8ubzsnzfi3aCE9sV1mXLxob6Dto5XCCGhuBXEB631qRpxaWkASSpgwHhAJdJQcM1ikTtfTXcVmx7n3rtQ83i1xvb4zaJYHA4SGBwT4je2dFd27k8gRpvTgk5RbxxzsiBTpdbyB1a2eEfHfyQztYrC7NPD6M94aiHKtfzCvXjGZPpFohMLsdV4H8yggtqeiay3Nxj2MctjkyTWfKkr1dbWit9bHGyT58fXMpPbBr96NQfZsPNgWFMpusN2VJo9LyMFaGZYZgDyzykTuD6UvwfC2GBLuW1bk12YvuTbqhszbxVaWjf47Kzm13xkotdseL6a7NTULKFbFv8uLUVindCiqu4Gbv26V6kh9xCSM9vPvbqw67uH4QXUcj2N2THFS8CjZkatjHBQhMzDngiAyd8jKfhqa9w6N87S2jJNnZoKT87tKqLXA5oyvVfz4BNFqhHANfGfrQvAXLfoiZ2nCRyYYcy1BCvQ8TWiwf48MPuhKcipa5UdrndgAe7EZrVB3SbFnP7a3KfHkX36LfZBxbH7V2g9C3a9JnkkFhAFM1wfBYrvbJbSN8siGqEusfPh3D6UFAwNNN9aAKiYXZE3H1u4zVb8trNawRp7Ye3Rr8bTBEqX65xs1jpdZCzHUzQMikjBsUaRrCtkWut3PEtmVeQXUVRKwz2eYFaE4sX2zUuMuswKY911Lw38jNHcmUdwXYXCEEZNGY4b2LbMjyMpFHcnM5PMdoAPtx21LTB2oSMqGGcDPr5kigNeYUacjxEjimhMSnxYiVhnoQPKjftvzJwtvdT55fewwLGcRUDP8Koa31pkjubLtpPbiXCyiZ4iXZ2c1M82Wpxsb6EpGvkuhm5iiUi6Kdj6Ya4fzJhmgZLJZu57TxxTr1AB3EfH4AYqnKhrJeBwb5jcv5YD8vtWVeZ53wDaBGyEgkCZxZvgff4rkX2yBu3pCpQZheTxUepQzykqNJck3Y2gMJcC8nxYyjbtpgckReo2LT4bZi5DKsyv6QNWruenSEd3KavrMuyaiBu3LFxxvKwGJFXfZiEku5pALnbi15npqHuxhmwXwhbQFXUVfwviHsJH71qY889oQjERkweQkEB9AFk8hkkLG5aGyWruGLJa3546CPc6Zvbqwt33CZGbpo7jcuuG4rP4G2dpefASG8H45A8NeiGcQq3LXCvAw9MyzLmkVpvFG71nqurqdJCexWcawiLC1QiQwis4AFn9qgf4TLNprpAHPWr1nYAXa78f8DiXy5ahCNjArVq1SdseuFG3S1aoCEP8hbTWmHzBeRmJVsGhJXpNi2h9UiePxWsBBzVm5usMpsaBuckmxxXJyQAantCqFCVXcB71ZLi3pUjTYv2E4Ldf8QEjuSHMqmUv8HWvUudHRiPpCnqoyxyzjQtjbbcqAaSo7zKF1i3d6swUQbcjyULQTkL2oPwYy6vB7yenYXrCEWmyV85iH3wdYzdJj6CYoD5vRKAoNh1kMxZ82nkyB7KoCqr3AePVdSoWned8LMURXdGDdGCpVr7QtcHBL2E3RY4A3drPYpc1DWct8gwPGbowLJkHLNhPwsxTuLReLuotmT7Gheyd6NYUFtz1aWM516uNdDDg5bEPGXzJAGEx1UjZArrStByZcMKRDYVMG6NtNjLvDJCZEvLgBRG1Bi79mgBBbV75",
"assets": [
{
"tokenId": "7306c4457ed10a8b2be3be94b5a5e1433562f4afe3aaa188333ca15f940a8cf8",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "113496a2d57b84ecd3e8f4f4f7ba10378f0cc1ed6539bcd7d2cfde57a3b520ca",
"mainChain": true
},
{
"boxId": "428a7fd9b4b2b9ff4aad0b26a6f09350d5f3fa9acb6721347b832d777d093102",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 6,
"globalIndex": 32423931,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "103f040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e4722b95ec8f723473209272347321d802d635b2a5732201a7d636b2db6308723573230186027202c17235eded928c7236029d9c720a7e7234057324938c723601720993c27235c2722a95ed9372347325e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732673277236adb4a573289a73297236d9013763d801d639b2db63087237732a0186027202c1723795938c72390172098602c272378c72390286027202732b732c732d93cbc3722a8c723301d808d620b2a5732e00d621db63087220d622b27221732f0186027202c17220d6238c722202d6249172117330d625e4c672120711d626b2a5733100d627b2db6308722673320186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733300ed7224927223721193b27201733400b2722173350093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257336009a7210b27225733700721093c672200611720693e4c67220070e720993b172219593b1720973387339733a93c27226721eeced938c7227017209928c722702720a93720a733b733cd1938cb2db63087212733d0001733e",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "c49ee30c416a7daa81a558aae1bfb8a2b011b161032f2a04002b9f4392d5ee1a",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "896b297c09b88acaf75a49f2a4c2499368d66eb6aa842933776c76d4fb657308",
"mainChain": true
},
{
"boxId": "238b6dedd1d72cd096fa32ac33cb8755f87d821634709590dec6f374723f6810",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 7,
"globalIndex": 32423932,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "103f040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e4722b95ec8f723473209272347321d802d635b2a5732201a7d636b2db6308723573230186027202c17235eded928c7236029d9c720a7e7234057324938c723601720993c27235c2722a95ed9372347325e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732673277236adb4a573289a73297236d9013763d801d639b2db63087237732a0186027202c1723795938c72390172098602c272378c72390286027202732b732c732d93cbc3722a8c723301d808d620b2a5732e00d621db63087220d622b27221732f0186027202c17220d6238c722202d6249172117330d625e4c672120711d626b2a5733100d627b2db6308722673320186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733300ed7224927223721193b27201733400b2722173350093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257336009a7210b27225733700721093c672200611720693e4c67220070e720993b172219593b1720973387339733a93c27226721eeced938c7227017209928c722702720a93720a733b733cd1938cb2db63087212733d0001733e",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "170ea90ea36bdccf80381a9531401a26da83a414398a306930977967176bd225",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "b95695062a43e2ca2ce486a6a9981d1194e5315dae41eb8be7ef2f9c5ebbbfe8",
"mainChain": true
},
{
"boxId": "355c697d4e346356e1897896f51ae004cd8a9f61bad93e0c3a1783e358032721",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 8,
"globalIndex": 32423933,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "3NtW3QbiLwaF7f2h7NyiFZwSV3LqNwFNBH5HQgzeGtttvsLCS4e19bjkpDbuNbzBXtjvK3eyi94G9YNjeR94F4ix5iAXHSwmSsZ2ftbMCBfxf9JfgouBAvbrcKoDnioJmQdTfQLi8ubzsnzfi3aCE9sV1mXLxob6Dto5XCCGhuBXEB631qRpxaWkASSpgwHhAJdJQcM1ikTtfTXcVmx7n3rtQ83i1xvb4zaJYHA4SGBwT4je2dFd27k8gRpvTgk5RbxxzsiBTpdbyB1a2eEfHfyQztYrC7NPD6M94aiHKtfzCvXjGZPpFohMLsdV4H8yggtqeiay3Nxj2MctjkyTWfKkr1dbWit9bHGyT58fXMpPbBr96NQfZsPNgWFMpusN2VJo9LyMFaGZYZgDyzykTuD6UvwfC2GBLuW1bk12YvuTbqhszbxVaWjf47Kzm13xkotdseL6a7NTULKFbFv8uLUVindCiqu4Gbv26V6kh9xCSM9vPvbqw67uH4QXUcj2N2THFS8CjZkatjHBQhMzDngiAyd8jKfhqa9w6N87S2jJNnZoKT87tKqLXA5oyvVfz4BNFqhHANfGfrQvAXLfoiZ2nCRyYYcy1BCvQ8TWiwf48MPuhKcipa5UdrndgAe7EZrVB3SbFnP7a3KfHkX36LfZBxbH7V2g9C3a9JnkkFhAFM1wfBYrvbJbSN8siGqEusfPh3D6UFAwNNN9aAKiYXZE3H1u4zVb8trNawRp7Ye3Rr8bTBEqX65xs1jpdZCzHUzQMikjBsUaRrCtkWut3PEtmVeQXUVRKwz2eYFaE4sX2zUuMuswKY911Lw38jNHcmUdwXYXCEEZNGY4b2LbMjyMpFHcnM5PMdoAPtx21LTB2oSMqGGcDPr5kigNeYUacjxEjimhMSnxYiVhnoQPKjftvzJwtvdT55fewwLGcRUDP8Koa31pkjubLtpPbiXCyiZ4iXZ2c1M82Wpxsb6EpGvkuhm5iiUi6Kdj6Ya4fzJhmgZLJZu57TxxTr1AB3EfH4AYqnKhrJeBwb5jcv5YD8vtWVeZ53wDaBGyEgkCZxZvgff4rkX2yBu3pCpQZheTxUepQzykqNJck3Y2gMJcC8nxYyjbtpgckReo2LT4bZi5DKsyv6QNWruenSEd3KavrMuyaiBu3LFxxvKwGJFXfZiEku5pALnbi15npqHuxhmwXwhbQFXUVfwviHsJH71qY889oQjERkweQkEB9AFk8hkkLG5aGyWruGLJa3546CPc6Zvbqwt33CZGbpo7jcuuG4rP4G2dpefASG8H45A8NeiGcQq3LXCvAw9MyzLmkVpvFG71nqurqdJCexWcawiLC1QiQwis4AFn9qgf4TLNprpAHPWr1nYAXa78f8DiXy5ahCNjArVq1SdseuFG3S1aoCEP8hbTWmHzBeRmJVsGhJXpNi2h9UiePxWsBBzVm5usMpsaBuckmxxXJyQAantCqFCVXcB71ZLi3pUjTYv2E4Ldf8QEjuSHMqmUv8HWvUudHRiPpCnqoyxyzjQtjbbcqAaSo7zKF1i3d6swUQbcjyULQTkL2oPwYy6vB7yenYXrCEWmyV85iH3wdYzdJj6CYoD5vRKAoNh1kMxZ82nkyB7KoCqr3AePVdSoWned8LMURXdGDdGCpVr7QtcHBL2E3RY4A3drPYpc1DWct8gwPGbowLJkHLNhPwsxTuLReLuotmT7Gheyd6NYUFtz1aWM516uNdDDg5bEPGXzJAGEx1UjZArrStByZcMKRDYVMG6NtNjLvDJCZEvLgBRG1Bi79mgBBbV75",
"assets": [
{
"tokenId": "f1c90bdf808179f9df5aa701ed9262ce1614c1252977eff51ff2dcc6c0da57da",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "d27c80fa3ece515398ffa31c7f37f67362bb433cff81985d96b4bc8e1bc81edd",
"mainChain": true
},
{
"boxId": "fcb2b3c9aade64c068a4c5fd504640d20fee514609dc8f3900d2a70ae155b72d",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 9,
"globalIndex": 32423934,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "3NtW3QbiLwaF7f2h7NyiFZwSV3LqNwFNBH5HQgzeGtttvsLCS4e19bjkpDbuNbzBXtjvK3eyi94G9YNjeR94F4ix5iAXHSwmSsZ2ftbMCBfxf9JfgouBAvbrcKoDnioJmQdTfQLi8ubzsnzfi3aCE9sV1mXLxob6Dto5XCCGhuBXEB631qRpxaWkASSpgwHhAJdJQcM1ikTtfTXcVmx7n3rtQ83i1xvb4zaJYHA4SGBwT4je2dFd27k8gRpvTgk5RbxxzsiBTpdbyB1a2eEfHfyQztYrC7NPD6M94aiHKtfzCvXjGZPpFohMLsdV4H8yggtqeiay3Nxj2MctjkyTWfKkr1dbWit9bHGyT58fXMpPbBr96NQfZsPNgWFMpusN2VJo9LyMFaGZYZgDyzykTuD6UvwfC2GBLuW1bk12YvuTbqhszbxVaWjf47Kzm13xkotdseL6a7NTULKFbFv8uLUVindCiqu4Gbv26V6kh9xCSM9vPvbqw67uH4QXUcj2N2THFS8CjZkatjHBQhMzDngiAyd8jKfhqa9w6N87S2jJNnZoKT87tKqLXA5oyvVfz4BNFqhHANfGfrQvAXLfoiZ2nCRyYYcy1BCvQ8TWiwf48MPuhKcipa5UdrndgAe7EZrVB3SbFnP7a3KfHkX36LfZBxbH7V2g9C3a9JnkkFhAFM1wfBYrvbJbSN8siGqEusfPh3D6UFAwNNN9aAKiYXZE3H1u4zVb8trNawRp7Ye3Rr8bTBEqX65xs1jpdZCzHUzQMikjBsUaRrCtkWut3PEtmVeQXUVRKwz2eYFaE4sX2zUuMuswKY911Lw38jNHcmUdwXYXCEEZNGY4b2LbMjyMpFHcnM5PMdoAPtx21LTB2oSMqGGcDPr5kigNeYUacjxEjimhMSnxYiVhnoQPKjftvzJwtvdT55fewwLGcRUDP8Koa31pkjubLtpPbiXCyiZ4iXZ2c1M82Wpxsb6EpGvkuhm5iiUi6Kdj6Ya4fzJhmgZLJZu57TxxTr1AB3EfH4AYqnKhrJeBwb5jcv5YD8vtWVeZ53wDaBGyEgkCZxZvgff4rkX2yBu3pCpQZheTxUepQzykqNJck3Y2gMJcC8nxYyjbtpgckReo2LT4bZi5DKsyv6QNWruenSEd3KavrMuyaiBu3LFxxvKwGJFXfZiEku5pALnbi15npqHuxhmwXwhbQFXUVfwviHsJH71qY889oQjERkweQkEB9AFk8hkkLG5aGyWruGLJa3546CPc6Zvbqwt33CZGbpo7jcuuG4rP4G2dpefASG8H45A8NeiGcQq3LXCvAw9MyzLmkVpvFG71nqurqdJCexWcawiLC1QiQwis4AFn9qgf4TLNprpAHPWr1nYAXa78f8DiXy5ahCNjArVq1SdseuFG3S1aoCEP8hbTWmHzBeRmJVsGhJXpNi2h9UiePxWsBBzVm5usMpsaBuckmxxXJyQAantCqFCVXcB71ZLi3pUjTYv2E4Ldf8QEjuSHMqmUv8HWvUudHRiPpCnqoyxyzjQtjbbcqAaSo7zKF1i3d6swUQbcjyULQTkL2oPwYy6vB7yenYXrCEWmyV85iH3wdYzdJj6CYoD5vRKAoNh1kMxZ82nkyB7KoCqr3AePVdSoWned8LMURXdGDdGCpVr7QtcHBL2E3RY4A3drPYpc1DWct8gwPGbowLJkHLNhPwsxTuLReLuotmT7Gheyd6NYUFtz1aWM516uNdDDg5bEPGXzJAGEx1UjZArrStByZcMKRDYVMG6NtNjLvDJCZEvLgBRG1Bi79mgBBbV75",
"assets": [
{
"tokenId": "bfd98a051babf12e0c04f57eecbcfc6b5be2db7ae7eb358211e0cece57b1c7cc",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "8b5fef9a635773a8b9adc5ec960eba600d853dad14ac1ba80c1b3beaa3c64d32",
"mainChain": true
},
{
"boxId": "81eabedbfce7dc6270467d62f3befc5424cb834ad23a246d960a6b3b1d5013c2",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 10,
"globalIndex": 32423935,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "2db41effd207b19ff6645c96ec3d92b3eb14ef08c8b7f4e54af7b4756cb0b98b",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "95bc1d6e9d964560ef2912cee0925909c69ba0f6138e1c8af001c604985fca77",
"mainChain": true
},
{
"boxId": "96240ae90c0a0478dbc35978301112a13073a185782e651cdf49ce50c365ed32",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 11,
"globalIndex": 32423936,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "77fde6a19330fac1e8d5df79024ffc125bd17d89f89f5f71ba3d6cb3aa7e95f5",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "e5bc80a3ebb8f3e763c638bcb1abd118d0e7b32b60cf0edf104c999127376d10",
"mainChain": true
},
{
"boxId": "9ef86068ab9fe0fe0f5b9c3dc094379d3cbe9f4421c43820761e46a239ea92e0",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 12,
"globalIndex": 32423937,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "f589b12c398d765bf00e532a54c768327dba5b912106107943f8ed7dbbe370c2",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "c5cd29a7620191c0102535069422f402d9ab3aeecbb4fdf3fe95d09d930df3b7",
"mainChain": true
},
{
"boxId": "ad8ba77e9d538d540a994f599bf8e35aec91c8bcbb6db0125cefcce55f987f3f",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 13,
"globalIndex": 32423938,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "ad6b29d67c2e20fa7550a672b49c5a61a5f1ef1c68b79219bc2b22d2445452c1",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "fb2c6d6f21b072f5f5daa1947b84dfd360c70b953bf4bd0ffb3df8b820bac3b1",
"mainChain": true
},
{
"boxId": "9f2313811fc349908718c6abf3bec7a0d5da4f6628db5ca5819b79dc78010052",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 15000000,
"index": 14,
"globalIndex": 32423939,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "42af4a7d273b47ee81e4e6c38cd47d3d84c808fe9ff283a98423643986a11312",
"index": 0,
"amount": 1,
"name": "ashhhx8 - Ghibli ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "598e94ace3cd6280ffafa7ed62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1694066115847,1698298200000]"
},
"R6": {
"serializedValue": "11038094ebdc038084af5f8090dfc04a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[500000000,100000000,10000000000]"
},
"R8": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77"
}
},
"spentTransactionId": "846b40beccd5cd857b3cd14eaccef3cb89d1e06031d6101f844c2d43884964a5",
"mainChain": true
},
{
"boxId": "c2b41f053512783f15b2fa3d5b26201236f5dd0e69b54ef44d319c19c24cc9dd",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 75184220260,
"index": 15,
"globalIndex": 32423940,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "0008cd02e496bf60e0ddf0aeb0b7a69ff539478405c9f5d426300a8c586af5b0d78c9b77",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e496bf,1508e8,...)))}",
"address": "9gFjWZu9qg2Qoq4efpa8Eu6FrigkistVrYqAUA4u6QhDKbKPBGd",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "53590e6af0fec1e4df403ffa0dbc6fc522ca63f870e2b3db4fbcc30484bdf113",
"mainChain": true
},
{
"boxId": "c42b4e31d23f5920622edb74d568ac7f75967e0edc037ca83f3005d256b5e538",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 2250000000,
"index": 16,
"globalIndex": 32423941,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"ergoTree": "0008cd03240e71da7ba42ff1e2f68c425ee64ca7d9504a1c84b0c95de4a6effe68804d1d",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(240e71,dfb102,...)))}",
"address": "9gjghouPwq9TCKyFAAvHPsoE1n9moZWec9oKeRzAjnV9p4hAzvo",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "7fece15071d59730926082b6711156786aa9c8b404850ef51329715b892bf796",
"mainChain": true
},
{
"boxId": "9878f05a842c6065012fbede56ea68f30cd7c94f758d976d8cf15773caf06013",
"transactionId": "038c57eb3118061eb29abb9740f350a5835050462dfb2179b63c08a75b967034",
"blockId": "4a29a7e0eaefd17e1ce726973584970b618239f8a5165a601125ab35b9c0a6e9",
"value": 5000000,
"index": 17,
"globalIndex": 32423942,
"creationHeight": 1085718,
"settlementHeight": 1085720,
"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": "9731a5fd28f756e1403aa95e20ef456594aabe7eff4c022bae230cfe8b922920",
"mainChain": true
}
],
"size": 23643,
"isUnconfirmed": false
}