Transaction
ID: 8fd5f383ba...9b58
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00147312 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.06413668 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00274356 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.06176624 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 84,295
Total coins transferred: 0.0656098 ERG
Fees: 0.0011 ERG
Fees per byte: 0.00000019 ERG
Raw Transaction Data
{
"id": "8fd5f383ba263af4d7df3518aed18a8d98cdc87b602aa025453e4d5729b89b58",
"blockId": "0d622ca4e7b8037b4ddf9dc5a938bcb620016e8d55a44be46ede1d0dd589867d",
"inclusionHeight": 1688377,
"timestamp": 1767035196694,
"index": 7,
"globalIndex": 10053667,
"numConfirmations": 84295,
"inputs": [
{
"boxId": "1380e61b1d4f743ef91875217869657a49358a4aebb65c05b665c4ea7a791b43",
"value": 1473120,
"index": 0,
"spendingProof": null,
"outputBlockId": "36bc83cb5199f1d3f1e5b288f7b347170d30f1d2d4a642707b472fa94cf61430",
"outputTransactionId": "a66d8d66a10d815adf754459b567ca8a6472287a7e35bba8df403d7d3fcf3878",
"outputIndex": 0,
"outputGlobalIndex": 52605455,
"outputCreatedAt": 1688354,
"outputSettledAt": 1688356,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(99,-121,-128,-9,-99,49,38,90,-4,-30,10,-46,-97,57,-56,-115,20,-114,111,105,11,-38,-6,85,104,-60,-120,47,46,104,9,64)\n2: 0\n3: 2\n4: 1\n5: 0\n6: 1\n7: 0\n8: 1\n9: 0\n10: true\n11: Coll(62,-20,75,88,66,-75,57,-101,-57,96,-12,-123,2,-97,91,66,82,39,115,78,-84,-45,125,11,-127,27,-66,41,72,67,9,-109)\n12: 1\n13: 0\n14: false\n15: true\n16: 10\n17: false\n18: Coll(58,-108,98,24,98,-10,116,84,-53,-35,97,62,-45,-90,68,-126,-71,-33,-29,9,60,97,-126,53,107,-92,-12,-95,68,17,-9,-107)\n19: 0\n20: Coll(-126,-103,-39,-114,21,-21,-18,127,-93,-102,-41,22,-34,124,-117,-79,-111,121,10,27,-12,-73,-61,-7,26,-13,90,14,54,24,119,6)\n21: 0\n22: 0\n23: 1\n24: 1\n25: 0\n26: 1\n27: 2\n28: 3\n29: 3\n30: 4\n31: 4\n32: 5\n33: 5\n34: 0\n35: 0\n36: 1\n37: 3\n38: 1\n39: false\n40: false\n41: false\n42: 2\n43: 0\n44: 5\n45: 1000000\n46: 1000000\n47: Coll(-30,2,-17,8,63,13,87,-9,42,-104,-14,113,37,38,-126,-84,-91,-88,-102,-22,-96,-30,104,41,-102,-96,-20,-23,1,9,-127,-63)\n48: 1\n49: 1\n50: 2\n51: 30\n52: false\n53: 0\n54: 0\n55: 0\n56: 1000000\n57: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R8[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n val coll6 = SELF.R6[Coll[Byte]].get\n val coll7 = Coll[Byte]()\n val coll8 = SELF.tokens(placeholder[Int](2))._1\n val tuple9 = SELF.R5[(Coll[Byte], Long)].get\n val coll10 = tuple9._1\n val l11 = coll3(placeholder[Int](3))\n val coll12 = SELF.R9[Coll[Coll[Byte]]].get\n val coll13 = coll12(placeholder[Int](4))\n val bool14 = coll13 == coll7\n val func15 = {(box15: Box) =>\n if (bool14) { box15.value } else {\n box15.tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll13 }).fold(\n placeholder[Long](5), {(tuple17: (Long, (Coll[Byte], Long))) => tuple17._1 + tuple17._2._2 }\n )\n }\n }\n val l16 = coll3(placeholder[Int](6))\n val coll17 = SELF.R7[Coll[Coll[Byte]]].get\n val l18 = tuple9._2\n sigmaProp((i1 == placeholder[Int](7)) && ((if (l2 >= l4) {(\n val coll19 = OUTPUTS.filter({(box19: Box) => blake2b256(box19.propositionBytes) == coll5 })\n if (coll19.size == placeholder[Int](8)) {(\n val box20 = coll19(placeholder[Int](9))\n val tuple21 = box20.R6[(Coll[Byte], Coll[Byte])].get\n val coll22 = tuple21._1\n val coll23 = tuple21._2\n if (((blake2b256(coll22) == coll6) && (blake2b256(box20.propositionBytes) == coll5)) && if (coll23 == coll7) { placeholder[Boolean](10) } else {(\n val coll24 = CONTEXT.dataInputs.filter({(box24: Box) => ((blake2b256(box24.propositionBytes) == placeholder[Coll[Byte]](11)) && (box24.R6[Coll[Byte]].get == coll8)) && (box24.R5[Coll[Byte]].get == coll23) })\n if (coll24.size == placeholder[Int](12)) {(\n val box25 = coll24(placeholder[Int](13))\n val coll26 = box25.R9[Coll[Long]].get\n ((coll26.fold(placeholder[Boolean](14), {(tuple27: (Boolean, Long)) =>\n val bool29 = tuple27._1\n if (bool29) { bool29 } else { if (blake2b256(box25.R7[Coll[Byte]].get.append(coll10).append(longToByteArray(tuple27._2)).append(box25.R8[Coll[Byte]].get).append(box25.R4[Coll[Byte]].get).append(coll22)) == box25.R5[Coll[Byte]].get) { placeholder[Boolean](15) } else { bool29 } }\n }) && if (bool14) { box25.value >= l11 } else { box25.tokens.exists({(tuple27: (Coll[Byte], Long)) => (tuple27._1 == coll13) && (tuple27._2 >= l11) }) }) && (box25.creationInfo._1.toLong < l4)) && (coll26.size.toLong <= placeholder[Long](16))\n )} else { placeholder[Boolean](17) }\n )}) {(\n val coll24 = CONTEXT.dataInputs.filter({(box24: Box) => ((((((blake2b256(box24.propositionBytes) == placeholder[Coll[Byte]](18)) && (box24.tokens.size > placeholder[Int](19))) && (box24.R4[Coll[Byte]].get == placeholder[Coll[Byte]](20))) && (box24.R5[Coll[Byte]].get == coll8)) && box24.R6[Boolean].get) && box24.R8[Boolean].get) && coll17.exists({(coll26: Coll[Byte]) => coll26 == box24.tokens(placeholder[Int](21))._1 }) })\n val coll25 = coll24.map({(box25: Box) => box25.tokens(placeholder[Int](22))._1 })\n ((((((((((((((func15(box20) >= l16) && (box20.tokens.filter({(tuple26: (Coll[Byte], Long)) => tuple26._1 == coll8 }).size == placeholder[Int](23))) && (box20.R4[Int].get == placeholder[Int](24))) && (box20.R5[Coll[Byte]].get == coll10)) && (box20.R7[Coll[Coll[Byte]]].get == coll17)) && (box20.R8[Coll[Long]].get(placeholder[Int](25)) == l4)) && (box20.R8[Coll[Long]].get(placeholder[Int](26)) == l16)) && (box20.R8[Coll[Long]].get(placeholder[Int](27)) == l11)) && (box20.R8[Coll[Long]].get(placeholder[Int](28)) == coll3(placeholder[Int](29)))) && (box20.R8[Coll[Long]].get(placeholder[Int](30)) >= coll3(placeholder[Int](31)))) && (box20.R8[Coll[Long]].get(placeholder[Int](32)) >= l2 + placeholder[Long](33))) && (box20.R9[Coll[Coll[Byte]]].get(placeholder[Int](34)) == coll12(placeholder[Int](35)))) && (box20.R9[Coll[Coll[Byte]]].get(placeholder[Int](36)) == coll13)) && (box20.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](37))) && coll25.indices.forall({(i26: Int) => !coll25.slice(i26 + placeholder[Int](38), coll24.size).exists({(coll28: Coll[Byte]) => coll28 == coll25(i26) }) })\n )} else { placeholder[Boolean](39) }\n )} else { placeholder[Boolean](40) }\n )} else { placeholder[Boolean](41) } || if ((l2 < l4) && (OUTPUTS.size >= placeholder[Int](42))) {(\n val box19 = OUTPUTS(placeholder[Int](43))\n val l20 = l16 - l16 / placeholder[Long](44)\n val l21 = if (bool14) { if (l20 < placeholder[Long](45)) { placeholder[Long](46) } else { l20 } } else { l20 }\n ((((((((blake2b256(box19.propositionBytes) == placeholder[Coll[Byte]](47)) && (func15(box19) >= l21)) && (box19.tokens.filter({(tuple22: (Coll[Byte], Long)) => (tuple22._1 == coll8) && (tuple22._2 == placeholder[Long](48)) }).size == placeholder[Int](49))) && (box19.R4[Int].get == placeholder[Int](50))) && (box19.R5[Long].get >= l2 + placeholder[Long](51))) && (blake2b256(box19.R6[Coll[Byte]].get) == coll6)) && (box19.R7[Long].get == l21)) && (box19.R8[Long].get == l4)) && (box19.R9[Coll[Coll[Byte]]].get == coll12)\n )} else { placeholder[Boolean](52) }) || if ((l2 < l18) && (OUTPUTS.size > placeholder[Int](53))) {(\n val box19 = OUTPUTS.filter({(box19: Box) => blake2b256(box19.propositionBytes) == blake2b256(SELF.propositionBytes) })(placeholder[Int](54))\n val l20 = box19.value\n val tuple21 = box19.R5[(Coll[Byte], Long)].get\n ((((((((box19.tokens(placeholder[Int](55))._1 == coll8) && ((l20 >= placeholder[Long](56)) && (l20 == SELF.value))) && (tuple21._1 == blake2b256(coll10.append(SELF.id)))) && (tuple21._2 == l18)) && (box19.R4[Int].get == i1)) && (box19.R6[Coll[Byte]].get == coll6)) && (box19.R7[Coll[Coll[Byte]]].get == coll17)) && (box19.R8[Coll[Long]].get == coll3)) && (box19.R9[Coll[Coll[Byte]]].get == coll12)\n )} else { placeholder[Boolean](57) }))\n}",
"address": "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",
"assets": [
{
"tokenId": "1e247b3247eebeecbe6a363b5b8c5f2604a7f3712d822081a8ab5d1fc911f52d",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 1000,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "4d0e08bc31f0ca723155f4c68cce01",
"sigmaType": "(Coll[SByte], SLong)",
"renderedValue": "[bc31f0ca723155f4,1688355]"
},
"R6": {
"serializedValue": "0e20b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4b3b5bb7d059e48b3acb460389c2ce69e90b426fe53d719da72873d846eaf2a"
},
"R8": {
"serializedValue": "1105e88cce01d00fe8070a28",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1688372,1000,500,5,20]"
},
"R7": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
},
"R9": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[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,aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71]"
},
"R4": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
}
}
},
{
"boxId": "cd575d098715fcd8e9dcd4ce2683e2809b1fa90591d9ef818d14b3e4d08e42ba",
"value": 64136680,
"index": 1,
"spendingProof": "4b972a3ef4290040666ebb632edb61fd6624a8ae027fd1f780edf4d2d32ea1a53b9e2a6f178f5156f4f31ea5e673e5c7b4dfbd46d95ce97b",
"outputBlockId": "fd94d39ba26720d910eba1b7e93c481375ab5be502a03a74264275fd804dde27",
"outputTransactionId": "10dea6b1e359987ba6643acfd05a5a9c6e0ec74b03f25156a377556e79c4bd73",
"outputIndex": 2,
"outputGlobalIndex": 52605924,
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"ergoTreeConstants": "0: 5\n1: Coll(62,-20,75,88,66,-75,57,-101,-57,96,-12,-123,2,-97,91,66,82,39,115,78,-84,-45,125,11,-127,27,-66,41,72,67,9,-109)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 2\n7: 1\n8: 3\n9: 4\n10: 2\n11: Coll(58,-108,98,24,98,-10,116,84,-53,-35,97,62,-45,-90,68,-126,-71,-33,-29,9,60,97,-126,53,107,-92,-12,-95,68,17,-9,-107)\n12: 1000000\n13: 0\n14: Coll(0,8,-51)\n15: Coll(0,8,-51,2,90,-56,-85,24,63,-3,-29,96,104,96,49,32,-80,10,-51,-15,65,-71,31,-28,-32,-64,-58,-43,98,-75,-14,78,30,44,-62,-47)\n16: 1\n17: 1\n18: 1\n19: 1\n20: 0\n21: 0\n22: 10\n23: -1\n24: false\n25: true\n26: -1\n27: 1\n28: 0\n29: true\n30: -1\n31: 0\n32: 1\n33: 0\n34: 1\n35: 2\n36: 3\n37: 4\n38: 5\n39: 0\n40: 0\n41: 1\n42: 2\n43: 5\n44: 5\n45: 3\n46: false\n47: false\n48: false\n49: false\n50: false\n51: 0\n52: 0\n53: Coll(-10,-127,-98,11,124,-7,-100,-116,120,114,-74,47,73,-123,-72,-39,0,-58,21,9,37,-48,30,-78,121,120,117,23,-88,72,-74,-40)\n54: 0\n55: 0\n56: 1\n57: 0\n58: 0\n59: 2\n60: 1\n61: 1\n62: 0\n63: true\n64: 1\n65: 0\n66: false\n67: true\n68: 10\n69: false\n70: 1\n71: 0\n72: 5\n73: 5\n74: 0\n75: 1\n76: 0\n77: 1\n78: 2\n79: 3\n80: 4\n81: false\n82: false\n83: false\n84: 0\n85: 0\n86: 100\n87: 0\n88: 0\n89: 5\n90: 100\n91: 0\n92: 0\n93: 0\n94: 3\n95: 3\n96: 5\n97: 0\n98: 0\n99: 0\n100: 3\n101: 3\n102: false\n103: 1\n104: 0\n105: false\n106: true\n107: 10\n108: 100\n109: 0\n110: 0\n111: 0\n112: 10000000\n113: 0\n114: 0\n115: 0\n116: 0\n117: 0\n118: 0\n119: 0\n120: 0\n121: 0\n122: 10000000\n123: 0\n124: true\n125: 0\n126: 0\n127: 0\n128: 0\n129: 0\n130: 0\n131: 0\n132: 10000000\n133: 0\n134: true\n135: false\n136: false\n137: 0\n138: 0\n139: 10000000\n140: 0\n141: 0\n142: 0\n143: 0\n144: 0\n145: 0\n146: true\n147: 0\n148: 0\n149: 0\n150: 0\n151: 0\n152: true\n153: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R8[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val bool5 = l2 < l4\n val coll6 = placeholder[Coll[Byte]](1)\n val coll7 = SELF.tokens(placeholder[Int](2))._1\n val tuple8 = SELF.R6[(Coll[Byte], Coll[Byte])].get\n val coll9 = tuple8._2\n val l10 = coll3(placeholder[Int](3))\n val coll11 = SELF.R9[Coll[Coll[Byte]]].get\n val coll12 = coll11(placeholder[Int](4))\n val coll13 = Coll[Byte]()\n val bool14 = coll12 == coll13\n val func15 = {(box15: Box) =>\n if (bool14) { box15.value } else {\n box15.tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll12 }).fold(\n placeholder[Long](5), {(tuple17: (Long, (Coll[Byte], Long))) => tuple17._1 + tuple17._2._2 }\n )\n }\n }\n val l16 = coll3(placeholder[Int](6))\n val coll17 = SELF.R5[Coll[Byte]].get\n val coll18 = tuple8._1\n val coll19 = SELF.R7[Coll[Coll[Byte]]].get\n val l20 = coll3(placeholder[Int](7))\n val l21 = coll3(placeholder[Int](8))\n val l22 = coll3(placeholder[Int](9))\n val coll23 = coll11(placeholder[Int](10))\n val coll24 = placeholder[Coll[Byte]](11)\n val l25 = if (bool14) { placeholder[Long](12) } else { placeholder[Long](13) }\n val coll26 = placeholder[Coll[Byte]](14)\n val coll27 = placeholder[Coll[Byte]](15)\n sigmaProp(i1 == placeholder[Int](16)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](17))) && (OUTPUTS.size > placeholder[Int](18))) {(\n val coll28 = CONTEXT.dataInputs\n val coll29 = coll28.filter({(box29: Box) => ((blake2b256(box29.propositionBytes) == coll6) && (box29.R6[Coll[Byte]].get == coll7)) && (box29.R5[Coll[Byte]].get != coll9) })\n if (coll29.size == placeholder[Int](19)) {(\n val box30 = coll29(placeholder[Int](20))\n val box31 = OUTPUTS(placeholder[Int](21))\n if (((((blake2b256(box30.propositionBytes) == coll6) && (box30.R6[Coll[Byte]].get == coll7)) && (box30.creationInfo._1.toLong < l10)) && (func15(box30) >= l16)) && (box30.R9[Coll[Long]].get.size.toLong <= placeholder[Long](22))) {(\n val tuple32 = (placeholder[Long](23), placeholder[Boolean](24))\n val l33 = box30.R9[Coll[Long]].get.fold(tuple32, {(tuple33: ((Long, Boolean), Long)) =>\n val tuple35 = tuple33._1\n val l36 = tuple33._2\n if (tuple35._2) { tuple35 } else { if (blake2b256(box30.R7[Coll[Byte]].get.append(coll17).append(longToByteArray(l36)).append(box30.R8[Coll[Byte]].get).append(box30.R4[Coll[Byte]].get).append(coll18)) == box30.R5[Coll[Byte]].get) { (l36, placeholder[Boolean](25)) } else { tuple35 } }\n })._1\n val bool34 = l33 != placeholder[Long](26)\n if (bool34) {(\n val coll35 = if (coll9 == coll13) { box30.R5[Coll[Byte]].get } else {(\n val coll35 = coll28.filter({(box35: Box) => ((blake2b256(box35.propositionBytes) == coll6) && (box35.R5[Coll[Byte]].get == coll9)) && (box35.R6[Coll[Byte]].get == coll7) })\n if (coll35.size == placeholder[Int](27)) {(\n val box36 = coll35(placeholder[Int](28))\n val tuple37 = box36.R9[Coll[Long]].get.fold(tuple32, {(tuple37: ((Long, Boolean), Long)) =>\n val tuple39 = tuple37._1\n val l40 = tuple37._2\n if (tuple39._2) { tuple39 } else { if (blake2b256(box36.R7[Coll[Byte]].get.append(coll17).append(longToByteArray(l40)).append(box36.R8[Coll[Byte]].get).append(box36.R4[Coll[Byte]].get).append(coll18)) == box36.R5[Coll[Byte]].get) { (l40, placeholder[Boolean](29)) } else { tuple39 } }\n })\n val l38 = tuple37._1\n if (tuple37._2 && (l38 != placeholder[Long](30))) {(\n val i39 = box30.creationInfo._1\n val l40 = l33 * l10 - i39.toLong\n val i41 = box36.creationInfo._1\n val l42 = l38 * l10 - i41.toLong\n if ((l40 > l42) || ((l40 == l42) && (i39 < i41))) { box30.R5[Coll[Byte]].get } else { coll13 }\n )} else { coll13 }\n )} else { coll13 }\n )}\n if ((coll35 != coll13) && (coll35 != coll9)) { ((((((((((((((((((func15(box31) >= func15(SELF)) && (box31.tokens(placeholder[Int](31))._1 == coll7)) && (box31.R4[Int].get == i1)) && (i1 == placeholder[Int](32))) && (box31.R5[Coll[Byte]].get == coll17)) && (box31.R6[(Coll[Byte], Coll[Byte])].get._1 == coll18)) && (box31.R6[(Coll[Byte], Coll[Byte])].get._2 == coll35)) && (box31.R7[Coll[Coll[Byte]]].get == coll19)) && (box31.R8[Coll[Long]].get(placeholder[Int](33)) == l10)) && (box31.R8[Coll[Long]].get(placeholder[Int](34)) == l20)) && (box31.R8[Coll[Long]].get(placeholder[Int](35)) == l16)) && (box31.R8[Coll[Long]].get(placeholder[Int](36)) == l21)) && (box31.R8[Coll[Long]].get(placeholder[Int](37)) == l22)) && (box31.R8[Coll[Long]].get(placeholder[Int](38)) == l4)) && (box31.R9[Coll[Coll[Byte]]].get(placeholder[Int](39)) == coll11(placeholder[Int](40)))) && (box31.R9[Coll[Coll[Byte]]].get(placeholder[Int](41)) == coll12)) && ((box31.R9[Coll[Coll[Byte]]].get(placeholder[Int](42)) == coll23) || (l4 - placeholder[Long](43) + placeholder[Long](44) < l2))) && (box31.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](45))) && bool34 } else { placeholder[Boolean](46) }\n )} else { placeholder[Boolean](47) }\n )} else { placeholder[Boolean](48) }\n )} else { placeholder[Boolean](49) }\n )} else { placeholder[Boolean](50) }) || sigmaProp(if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](51))) {(\n val coll28 = CONTEXT.dataInputs\n val coll29 = coll28.filter({(box29: Box) => ((((((blake2b256(box29.propositionBytes) == coll24) && (box29.tokens.size > placeholder[Int](52))) && (box29.R4[Coll[Byte]].get == placeholder[Coll[Byte]](53))) && (box29.R5[Coll[Byte]].get == coll9)) && box29.R6[Boolean].get) && (!box29.R8[Boolean].get)) && coll19.exists({(coll31: Coll[Byte]) => coll31 == box29.tokens(placeholder[Int](54))._1 }) })\n val coll30 = coll29.map({(box30: Box) => box30.tokens(placeholder[Int](55))._1 })\n val i31 = coll29.size\n val i32 = coll19.size\n val coll33 = OUTPUTS.filter({(box33: Box) => box33.propositionBytes == SELF.propositionBytes })\n if ((coll30.indices.forall({(i34: Int) => !coll30.slice(i34 + placeholder[Int](56), i31).exists({(coll36: Coll[Byte]) => coll36 == coll30(i34) }) }) && (i31 >= if (i32 == placeholder[Int](57)) { placeholder[Int](58) } else { i32 / placeholder[Int](59) + placeholder[Int](60) })) && (coll33.size == placeholder[Int](61))) {(\n val box34 = coll33(placeholder[Int](62))\n val coll35 = box34.R6[(Coll[Byte], Coll[Byte])].get._2\n val coll36 = INPUTS.filter({(box36: Box) => (blake2b256(box36.propositionBytes) == coll6) && (box36.R5[Coll[Byte]].get == coll9) })\n if (if (coll35 == coll13) { placeholder[Boolean](63) } else {(\n val coll37 = coll28.filter({(box37: Box) => ((blake2b256(box37.propositionBytes) == coll6) && (box37.R6[Coll[Byte]].get == coll7)) && (box37.R5[Coll[Byte]].get == coll35) })\n if (coll37.size == placeholder[Int](64)) {(\n val box38 = coll37(placeholder[Int](65))\n val coll39 = box38.R9[Coll[Long]].get\n ((coll39.fold(placeholder[Boolean](66), {(tuple40: (Boolean, Long)) =>\n val bool42 = tuple40._1\n if (bool42) { bool42 } else { if (blake2b256(box38.R7[Coll[Byte]].get.append(coll17).append(longToByteArray(tuple40._2)).append(box38.R8[Coll[Byte]].get).append(box38.R4[Coll[Byte]].get).append(coll18)) == box38.R5[Coll[Byte]].get) { placeholder[Boolean](67) } else { bool42 } }\n }) && (func15(box38) >= l16)) && (box38.creationInfo._1.toLong < l10)) && (coll39.size.toLong <= placeholder[Long](68))\n )} else { placeholder[Boolean](69) }\n )} && (coll36.size == placeholder[Int](70))) {(\n val coll37 = box34.R8[Coll[Long]].get\n ((func15(box34) >= func15(SELF) + func15(coll36(placeholder[Int](71)))) && (coll37(placeholder[Int](72)) >= l2 + placeholder[Long](73))) && (((((((((((box34.tokens(placeholder[Int](74))._1 == coll7) && (box34.R4[Int].get == i1)) && (i1 == placeholder[Int](75))) && (box34.R5[Coll[Byte]].get == coll17)) && (box34.R7[Coll[Coll[Byte]]].get == coll19)) && (coll37(placeholder[Int](76)) == l10)) && (coll37(placeholder[Int](77)) == l20)) && (coll37(placeholder[Int](78)) == l16)) && (coll37(placeholder[Int](79)) == l21)) && (coll37(placeholder[Int](80)) == l22)) && (box34.R9[Coll[Coll[Byte]]].get == coll11))\n )} else { placeholder[Boolean](81) }\n )} else { placeholder[Boolean](82) }\n )} else { placeholder[Boolean](83) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](84))) {(\n val bool28 = coll9 != coll13\n val coll29 = INPUTS.filter({(box29: Box) => (blake2b256(box29.propositionBytes) == coll6) && (box29.R6[Coll[Byte]].get == coll7) })\n val l30 = coll29.fold(placeholder[Long](85), {(tuple30: (Long, Box)) => tuple30._1 + func15(tuple30._2) }) + func15(SELF) - l20\n val l31 = l30 * l21 / placeholder[Long](86)\n val l32 = l31 * coll19.size.toLong\n val l33 = l32 - if ((l31 < l25) && (l31 > placeholder[Long](87))) { l32 } else { placeholder[Long](88) }\n val l34 = l30 * placeholder[Long](89) / placeholder[Long](90)\n val l35 = l34 - if ((l34 < l25) && (l34 > placeholder[Long](91))) { l34 } else { placeholder[Long](92) }\n val prop36 = if (coll23.slice(placeholder[Int](93), placeholder[Int](94)) == coll26) {\n proveDlog(decodePoint(coll23.slice(placeholder[Int](95), coll23.size)))\n } else { sigmaProp(INPUTS.exists({(box36: Box) => box36.propositionBytes == coll23 })) }\n val coll37 = INPUTS.filter({(box37: Box) => (blake2b256(box37.propositionBytes) == coll6) && (box37.R5[Coll[Byte]].get == coll9) })\n val prop38 = if (bool28) { if (l2 >= l4 + placeholder[Long](96)) { prop36 } else { if (coll37.size > placeholder[Int](97)) {(\n val coll38 = coll37(placeholder[Int](98)).R4[Coll[Byte]].get\n if (coll38.slice(placeholder[Int](99), placeholder[Int](100)) == coll26) { proveDlog(decodePoint(coll38.slice(placeholder[Int](101), coll38.size))) } else { sigmaProp(INPUTS.exists({(box39: Box) => box39.propositionBytes == coll38 })) }\n )} else { sigmaProp(placeholder[Boolean](102)) } } } else { prop36 }\n if (bool28) {(\n val coll39 = coll29.filter({(box39: Box) => box39.R5[Coll[Byte]].get == coll9 })\n if (coll39.size == placeholder[Int](103)) {(\n val box40 = coll39(placeholder[Int](104))\n val coll41 = box40.R9[Coll[Long]].get\n val coll42 = box40.R4[Coll[Byte]].get\n if (((coll41.fold(placeholder[Boolean](105), {(tuple43: (Boolean, Long)) =>\n val bool45 = tuple43._1\n if (bool45) { bool45 } else { if (blake2b256(box40.R7[Coll[Byte]].get.append(coll17).append(longToByteArray(tuple43._2)).append(box40.R8[Coll[Byte]].get).append(coll42).append(coll18)) == box40.R5[Coll[Byte]].get) { placeholder[Boolean](106) } else { bool45 } }\n }) && (func15(box40) >= l16)) && (box40.creationInfo._1.toLong < l10)) && (coll41.size.toLong <= placeholder[Long](107))) {(\n val l43 = l30 * l22 / placeholder[Long](108)\n val l44 = l30 - l43 - l33 - l35\n val bool45 = l44 < l16\n val l46 = if (bool45) { placeholder[Long](109) } else { l35 }\n prop38 && sigmaProp(\n (\n (\n (\n (\n OUTPUTS.filter({(box47: Box) => box47.propositionBytes == coll42 }).fold(\n placeholder[Long](110), {(tuple47: (Long, Box)) => tuple47._1 + func15(tuple47._2) }\n ) - INPUTS.filter({(box47: Box) => box47.propositionBytes == coll42 }).fold(\n placeholder[Long](111), {(tuple47: (Long, Box)) => tuple47._1 + func15(tuple47._2) }\n ) >= if (bool45) { l30 } else { l44 } - if (bool14) { placeholder[Long](112) } else { placeholder[Long](113) }\n ) && OUTPUTS.exists(\n {(box47: Box) =>\n ((box47.propositionBytes == coll42) && (box47.tokens.size > placeholder[Int](114))) && (box47.tokens(placeholder[Int](115))._1 == coll7)\n }\n )\n ) && (\n OUTPUTS.filter({(box47: Box) => box47.propositionBytes == coll23 }).fold(\n placeholder[Long](116), {(tuple47: (Long, Box)) => tuple47._1 + func15(tuple47._2) }\n ) - INPUTS.filter({(box47: Box) => box47.propositionBytes == coll23 }).fold(\n placeholder[Long](117), {(tuple47: (Long, Box)) => tuple47._1 + func15(tuple47._2) }\n ) >= l20 + if (bool45) { placeholder[Long](118) } else { l43 }\n )\n ) && if (l46 > placeholder[Long](119)) {\n OUTPUTS.filter({(box47: Box) => box47.propositionBytes == coll27 }).fold(\n placeholder[Long](120), {(tuple47: (Long, Box)) => tuple47._1 + func15(tuple47._2) }\n ) - INPUTS.filter({(box47: Box) => box47.propositionBytes == coll27 }).fold(\n placeholder[Long](121), {(tuple47: (Long, Box)) => tuple47._1 + func15(tuple47._2) }\n ) >= l46 - if (bool14) { placeholder[Long](122) } else { placeholder[Long](123) }\n } else { placeholder[Boolean](124) }\n ) && if (if (bool45) { placeholder[Long](125) } else { l33 } > placeholder[Long](126)) {\n CONTEXT.dataInputs.filter(\n {(box47: Box) =>\n ((blake2b256(box47.propositionBytes) == coll24) && (box47.tokens.size > placeholder[Int](127))) && coll19.exists(\n {(coll49: Coll[Byte]) => coll49 == box47.tokens(placeholder[Int](128))._1 }\n )\n }\n ).map({(box47: Box) => box47.R7[Coll[Byte]].get }).forall(\n {(coll47: Coll[Byte]) =>\n OUTPUTS.filter({(box49: Box) => box49.propositionBytes == coll47 }).fold(\n placeholder[Long](129), {(tuple49: (Long, Box)) => tuple49._1 + func15(tuple49._2) }\n ) - INPUTS.filter({(box49: Box) => box49.propositionBytes == coll47 }).fold(\n placeholder[Long](130), {(tuple49: (Long, Box)) => tuple49._1 + func15(tuple49._2) }\n ) >= if (bool45) { placeholder[Long](131) } else { l31 } - if (bool14) { placeholder[Long](132) } else { placeholder[Long](133) }\n }\n )\n } else { placeholder[Boolean](134) }\n )\n )} else { sigmaProp(placeholder[Boolean](135)) }\n )} else { sigmaProp(placeholder[Boolean](136)) }\n )} else {\n prop38 && sigmaProp(\n (\n (\n (\n OUTPUTS.filter({(box39: Box) => box39.propositionBytes == coll23 }).fold(\n placeholder[Long](137), {(tuple39: (Long, Box)) => tuple39._1 + func15(tuple39._2) }\n ) - INPUTS.filter({(box39: Box) => box39.propositionBytes == coll23 }).fold(\n placeholder[Long](138), {(tuple39: (Long, Box)) => tuple39._1 + func15(tuple39._2) }\n ) >= l30 + l20 - l35 - l33 - if (bool14) { placeholder[Long](139) } else { placeholder[Long](140) }\n ) && OUTPUTS.exists(\n {(box39: Box) =>\n ((box39.propositionBytes == coll23) && (box39.tokens.size > placeholder[Int](141))) && (box39.tokens(placeholder[Int](142))._1 == coll7)\n }\n )\n ) && if (l35 > placeholder[Long](143)) {\n OUTPUTS.filter({(box39: Box) => box39.propositionBytes == coll27 }).fold(\n placeholder[Long](144), {(tuple39: (Long, Box)) => tuple39._1 + func15(tuple39._2) }\n ) - INPUTS.filter({(box39: Box) => box39.propositionBytes == coll27 }).fold(\n placeholder[Long](145), {(tuple39: (Long, Box)) => tuple39._1 + func15(tuple39._2) }\n ) >= l35\n } else { placeholder[Boolean](146) }\n ) && if (l33 > placeholder[Long](147)) {\n CONTEXT.dataInputs.filter(\n {(box39: Box) =>\n ((blake2b256(box39.propositionBytes) == coll24) && (box39.tokens.size > placeholder[Int](148))) && coll19.exists(\n {(coll41: Coll[Byte]) => coll41 == box39.tokens(placeholder[Int](149))._1 }\n )\n }\n ).map({(box39: Box) => box39.R7[Coll[Byte]].get }).forall(\n {(coll39: Coll[Byte]) =>\n OUTPUTS.filter({(box41: Box) => box41.propositionBytes == coll39 }).fold(\n placeholder[Long](150), {(tuple41: (Long, Box)) => tuple41._1 + func15(tuple41._2) }\n ) - INPUTS.filter({(box41: Box) => box41.propositionBytes == coll39 }).fold(\n placeholder[Long](151), {(tuple41: (Long, Box)) => tuple41._1 + func15(tuple41._2) }\n ) >= l31\n }\n )\n } else { placeholder[Boolean](152) }\n )\n }\n )} else { sigmaProp(placeholder[Boolean](153)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "1e247b3247eebeecbe6a363b5b8c5f2604a7f3712d822081a8ab5d1fc911f52d",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 1000,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e08bc31f0ca723155f4",
"sigmaType": "Coll[SByte]",
"renderedValue": "bc31f0ca723155f4"
},
"R6": {
"serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f2100",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,]"
},
"R8": {
"serializedValue": "1106e88cce01d00fe8070a288e8dce01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1688372,1000,500,5,20,1688391]"
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