Transaction
ID: 06aa310cf2...325f
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.1195 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00003996 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
126.54 ERG
Tokens:
Loading assets...
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.15 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
126.5 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 699,219
Total coins transferred: 126.67 ERG
Fees: 0.005 ERG
Fees per byte: 0.000002362 ERG
Raw Transaction Data
{
"id": "06aa310cf24bbe8b2194e2618d7366a2558ca9efb8275cf393acf298911e325f",
"blockId": "f177dd34835bd68145f2712c0b73ee4745db3fa852efc3c2624948524584a430",
"inclusionHeight": 1069297,
"timestamp": 1692064548033,
"index": 6,
"globalIndex": 5674935,
"numConfirmations": 699219,
"inputs": [
{
"boxId": "1d3d03b1335b3846c351e1536f7bc7fde5c8f209a961510c10cc082cc11ad522",
"value": 15000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "3a9a5936bea02d65eb07093703536a34cd21a71202de6270cb95478f5ca78fe0",
"outputTransactionId": "c7ec87b04812b2f3d52a8a92562c928c9e17274744ae848cac9fd4f5d39045bd",
"outputIndex": 0,
"outputGlobalIndex": 31803220,
"outputCreatedAt": 1069293,
"outputSettledAt": 1069295,
"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": "529aae28fba7259a05e2851c11a025f4b2d0facfbfb40777932a9ef476a3a679",
"index": 0,
"amount": 1,
"name": "Peperg #158",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "5980948aebbe62809fabc0bf62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692060960000,1692150360000]"
},
"R6": {
"serializedValue": "11038088debe018084af5f80c6868f01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[200000000,100000000,150000000]"
},
"R8": {
"serializedValue": "0e240008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42"
}
}
},
{
"boxId": "6b1b7b00ff6dfef623047dd9ea14fdd546e6344adb62359844aa9208344738cf",
"value": 119500000,
"index": 1,
"spendingProof": "7b0d8e459543b954bc700af6ed0ace49d10a4426515b89abaf6c4b3f6727a082ac8dd784bc95f8aabe6edb141b154551d310a2277f556360",
"outputBlockId": "72e249d141b45fa14001e68ebcc1514fd6efe18a8f729b49077e01f3d948d3d3",
"outputTransactionId": "fd2fb02b8d00c0319dac8a178bed3e766f0f1d1ca359b0557149bf67e0cb9e51",
"outputIndex": 2,
"outputGlobalIndex": 31801316,
"outputCreatedAt": 1069229,
"outputSettledAt": 1069231,
"ergoTree": "0008cd02360a5c0c935958ec4949c1a263ace8f610565e42bd5f45ed9b7018dcf33581f9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(360a5c,cb0814,...)))}",
"address": "9evruWoFfhTZ4q4Xc4whQK4bJMqMAF7z9YeygzLvCHMgR17Pt5n",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "4cde78887f478b6c9238f9be148d588a56c42e5dabafa0dd4b5be891983b5762",
"value": 39960,
"index": 2,
"spendingProof": "444007c031df3e42452de7eb371bba740ac9969f0413366029e33fd223d303c5eb195d0a4167f63d3055a953690d12333136d238ca89c515",
"outputBlockId": "72e249d141b45fa14001e68ebcc1514fd6efe18a8f729b49077e01f3d948d3d3",
"outputTransactionId": "fd2fb02b8d00c0319dac8a178bed3e766f0f1d1ca359b0557149bf67e0cb9e51",
"outputIndex": 0,
"outputGlobalIndex": 31801314,
"outputCreatedAt": 1069229,
"outputSettledAt": 1069231,
"ergoTree": "0008cd02360a5c0c935958ec4949c1a263ace8f610565e42bd5f45ed9b7018dcf33581f9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(360a5c,cb0814,...)))}",
"address": "9evruWoFfhTZ4q4Xc4whQK4bJMqMAF7z9YeygzLvCHMgR17Pt5n",
"assets": [
{
"tokenId": "7e0a857c0105a90068480b9d37c30751ccf0be1b9d23d54486cd9703d966dd88",
"index": 0,
"amount": 1,
"name": "Psychedelic TV",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "6381ad60ba3604402bb1f887681c20c30b648ada288cf3c7f942336ad320ac7d",
"value": 126537101235,
"index": 3,
"spendingProof": "89a0a670c51820e662d1be22aecd06aba8fe53baf8c57c3db725aa955cf9b8ed03c6a8da070af72152c2a3a346b8d84481c98b6b8daa86cd",
"outputBlockId": "004bc80b541fd8505068b10d98b4b415194fc9b3ae300b93f017895afe0c9f13",
"outputTransactionId": "1f8509897577288fef58ba4b749f8d0db362f37953e8c4b59aaebba76323a4f2",
"outputIndex": 3,
"outputGlobalIndex": 31801980,
"outputCreatedAt": 1069254,
"outputSettledAt": 1069256,
"ergoTree": "0008cd02360a5c0c935958ec4949c1a263ace8f610565e42bd5f45ed9b7018dcf33581f9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(360a5c,cb0814,...)))}",
"address": "9evruWoFfhTZ4q4Xc4whQK4bJMqMAF7z9YeygzLvCHMgR17Pt5n",
"assets": [
{
"tokenId": "9a06d9e545a41fd51eeffc5e20d818073bf820c635e2a9d922269913e0de369d",
"index": 0,
"amount": 1493856680,
"name": "SPF",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 1,
"amount": 11799,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
}
],
"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": "02df3dbb986fd9a470808ccf77562f2c7caf720237af282f7bd1bd9e4572f00a",
"transactionId": "06aa310cf24bbe8b2194e2618d7366a2558ca9efb8275cf393acf298911e325f",
"blockId": "f177dd34835bd68145f2712c0b73ee4745db3fa852efc3c2624948524584a430",
"value": 150000000,
"index": 0,
"globalIndex": 31803372,
"creationHeight": 1069295,
"settlementHeight": 1069297,
"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": "529aae28fba7259a05e2851c11a025f4b2d0facfbfb40777932a9ef476a3a679",
"index": 0,
"amount": 1,
"name": "Peperg #158",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "5980948aebbe62f4bc91eebe62",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692060960000,1692064165690]"
},
"R6": {
"serializedValue": "11038088debe018084af5f80c6868f01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[200000000,100000000,150000000]"
},
"R8": {
"serializedValue": "0e240008cd02360a5c0c935958ec4949c1a263ace8f610565e42bd5f45ed9b7018dcf33581f9",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02360a5c0c935958ec4949c1a263ace8f610565e42bd5f45ed9b7018dcf33581f9"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42"
}
},
"spentTransactionId": "990f5afa01c5cdb9dacd8439f43685198796a7f82c390bb02225f1926b2a5db2",
"mainChain": true
},
{
"boxId": "7deae2abfd39cddc373f0eff5237cacbe97a2ac5f05256c381841f69c75fa5ed",
"transactionId": "06aa310cf24bbe8b2194e2618d7366a2558ca9efb8275cf393acf298911e325f",
"blockId": "f177dd34835bd68145f2712c0b73ee4745db3fa852efc3c2624948524584a430",
"value": 15000000,
"index": 1,
"globalIndex": 31803373,
"creationHeight": 1069295,
"settlementHeight": 1069297,
"ergoTree": "0008cd034ebb8fd5a8e4f943659421310da9b884bb9a779760309ca8838d7b36abe15c42",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4ebb8f,705450,...)))}",
"address": "9h4Up2fLnb57knScCHyFppKv5fkQZt8b3iWsW26FCeBRcmd2VfZ",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "a3eefd87c96ebbc7c51ee6138f5e8da653a918cd8d59e077b8f3b7efe0db75fe",
"mainChain": true
},
{
"boxId": "2a309df329c0dfbbc637f47e67192877f826302a2caa7f6880c262815c991bcd",
"transactionId": "06aa310cf24bbe8b2194e2618d7366a2558ca9efb8275cf393acf298911e325f",
"blockId": "f177dd34835bd68145f2712c0b73ee4745db3fa852efc3c2624948524584a430",
"value": 5000000,
"index": 2,
"globalIndex": 31803374,
"creationHeight": 1069295,
"settlementHeight": 1069297,
"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": "c373061ab8013c8b1060d09524a271ca59bea67fa6de6abed3e50bc9c8933f93",
"mainChain": true
},
{
"boxId": "61df00dc1cbfa9920c51e7dcbfd70ca63d2cba6b1e76002ddd6c2fc95e2f4c1d",
"transactionId": "06aa310cf24bbe8b2194e2618d7366a2558ca9efb8275cf393acf298911e325f",
"blockId": "f177dd34835bd68145f2712c0b73ee4745db3fa852efc3c2624948524584a430",
"value": 126501641195,
"index": 3,
"globalIndex": 31803375,
"creationHeight": 1069295,
"settlementHeight": 1069297,
"ergoTree": "0008cd02360a5c0c935958ec4949c1a263ace8f610565e42bd5f45ed9b7018dcf33581f9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(360a5c,cb0814,...)))}",
"address": "9evruWoFfhTZ4q4Xc4whQK4bJMqMAF7z9YeygzLvCHMgR17Pt5n",
"assets": [
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