Transaction
ID: 21bb0271e8...cebe
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00143748 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
1
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
1
Spent
Address:
Output transaction:
Settlement height:
Value:
0.98064968 ERG
Tokens:
Loading assets...
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
5
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
0
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.97898716 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 82,436
Total coins transferred: 0.98408716 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000402 ERG
Raw Transaction Data
{
"id": "21bb0271e85c2fb7908f36eb636ac2751a3e097576887fde19736aa93268cebe",
"blockId": "07c05767a680e86c63bad7e0ed25bb5887555366207c75fbf677c5c7d4f7f161",
"inclusionHeight": 1695432,
"timestamp": 1767887358976,
"index": 2,
"globalIndex": 10113209,
"numConfirmations": 82436,
"inputs": [
{
"boxId": "93efe8905fc63892fbe37cb299fa5d096222749c1b2996a5b2086671598145cd",
"value": 1437480,
"index": 0,
"spendingProof": "aa60183574bdf232edc781f3d457de94efb140e043e9de7222456a6aad5db171f1ff3e40ead880bca354f2f177746f26db19824e146f2c8a",
"outputBlockId": "16a8cf35d7148c940e1cb7d05dce75beb78827b5482c06eded9cbbe6e83c7e1e",
"outputTransactionId": "729ea7646cb221e0d32b2e8eccaf54b6daaabaefa09b2dbcd01d68f871d1eed6",
"outputIndex": 0,
"outputGlobalIndex": 52844832,
"outputCreatedAt": 1695385,
"outputSettledAt": 1695386,
"ergoTree": 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"ergoTreeConstants": "0: 5\n1: Coll(3,119,75,87,95,-98,29,-103,49,-2,-104,-124,71,49,118,-34,109,19,-84,-57,-62,-120,30,-8,111,74,-123,-101,-6,-20,29,-78)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 2\n7: -1\n8: false\n9: true\n10: 1\n11: 3\n12: 4\n13: 2\n14: 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)\n15: Coll(0,8,-51)\n16: 1\n17: 1\n18: 1\n19: 1\n20: 0\n21: 0\n22: 10\n23: -1\n24: 1\n25: 0\n26: -1\n27: 0\n28: 1\n29: 0\n30: 1\n31: 2\n32: 3\n33: 4\n34: 5\n35: 0\n36: 0\n37: 1\n38: 2\n39: 5\n40: 5\n41: 3\n42: false\n43: false\n44: false\n45: false\n46: false\n47: 0\n48: 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)\n49: 0\n50: 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)\n51: 0\n52: 0\n53: 1\n54: 0\n55: 0\n56: 2\n57: 1\n58: 1\n59: 0\n60: true\n61: 1\n62: 0\n63: 10\n64: false\n65: 1\n66: 0\n67: 5\n68: 5\n69: 0\n70: 1\n71: 0\n72: 1\n73: 2\n74: 3\n75: 4\n76: 0\n77: false\n78: false\n79: false\n80: 0\n81: Coll(-65,-122,-35,24,-60,88,124,-14,-74,117,-80,126,44,-32,-26,-118,-31,-2,87,53,-62,-85,-26,108,-16,52,-91,11,20,-12,-64,110)\n82: 0\n83: 1000000\n84: 50000\n85: 1000000\n86: 0\n87: 0\n88: 0\n89: true\n90: 0\n91: Coll(25,-72,3,14,5,0,5,0,4,0,14,32,58,-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,-107,4,0,4,0,4,0,4,2,1,0,5,0,5,0,4,0,4,2,1,1,-40,4,-42,1,-39,1,1,99,-80,-75,-37,99,8,114,1,-39,1,3,77,14,-109,-116,114,3,1,-28,-58,-89,5,14,115,0,-39,1,3,65)\n92: 1\n93: 0\n94: false\n95: true\n96: 0\n97: 3\n98: 3\n99: 5\n100: 0\n101: 0\n102: 0\n103: 3\n104: 3\n105: false\n106: 1\n107: 0\n108: 10\n109: 1000000\n110: 0\n111: 0\n112: 0\n113: 0\n114: 0\n115: 0\n116: 0\n117: 0\n118: 0\n119: true\n120: 0\n121: 0\n122: true\n123: false\n124: false\n125: 0\n126: 0\n127: 0\n128: 0\n129: 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 func13 = {(box13: Box) =>\n box13.tokens.filter({(tuple15: (Coll[Byte], Long)) => tuple15._1 == coll12 }).fold(\n placeholder[Long](5), {(tuple15: (Long, (Coll[Byte], Long))) => tuple15._1 + tuple15._2._2 }\n )\n }\n val l14 = coll3(placeholder[Int](6))\n val coll15 = SELF.R5[Coll[Byte]].get\n val coll16 = tuple8._1\n val func17 = {(box17: Box) => box17.R9[Coll[Long]].get.fold((placeholder[Long](7), placeholder[Boolean](8)), {(tuple19: ((Long, Boolean), Long)) =>\n val tuple21 = tuple19._1\n val l22 = tuple19._2\n if (tuple21._2) { tuple21 } else { if (blake2b256(box17.R7[Coll[Byte]].get.append(coll15).append(longToByteArray(l22)).append(box17.R8[Coll[Byte]].get).append(box17.R4[Coll[Byte]].get).append(coll16)) == box17.R5[Coll[Byte]].get) { (l22, placeholder[Boolean](9)) } else { tuple21 } }\n }) }\n val coll18 = SELF.R7[Coll[Coll[Byte]]].get\n val l19 = coll3(placeholder[Int](10))\n val l20 = coll3(placeholder[Int](11))\n val l21 = coll3(placeholder[Int](12))\n val coll22 = coll11(placeholder[Int](13))\n val coll23 = placeholder[Coll[Byte]](14)\n val coll24 = 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 coll25 = CONTEXT.dataInputs\n val coll26 = coll25.filter({(box26: Box) => ((blake2b256(box26.propositionBytes) == coll6) && (box26.R6[Coll[Byte]].get == coll7)) && (box26.R5[Coll[Byte]].get != coll9) })\n if (coll26.size == placeholder[Int](19)) {(\n val box27 = coll26(placeholder[Int](20))\n val box28 = OUTPUTS(placeholder[Int](21))\n if (((((blake2b256(box27.propositionBytes) == coll6) && (box27.R6[Coll[Byte]].get == coll7)) && (box27.creationInfo._1.toLong < l10)) && (func13(box27) >= l14)) && (box27.R9[Coll[Long]].get.size.toLong <= placeholder[Long](22))) {(\n val l29 = func17(box27)._1\n val bool30 = l29 != placeholder[Long](23)\n if (bool30) {(\n val coll31 = Coll[Byte]()\n val coll32 = if (coll9 == coll31) { box27.R5[Coll[Byte]].get } else {(\n val coll32 = coll25.filter({(box32: Box) => ((blake2b256(box32.propositionBytes) == coll6) && (box32.R5[Coll[Byte]].get == coll9)) && (box32.R6[Coll[Byte]].get == coll7) })\n if (coll32.size == placeholder[Int](24)) {(\n val box33 = coll32(placeholder[Int](25))\n val tuple34 = func17(box33)\n val l35 = tuple34._1\n if (tuple34._2 && (l35 != placeholder[Long](26))) {(\n val i36 = box27.creationInfo._1\n val l37 = l29 * l10 - i36.toLong\n val i38 = box33.creationInfo._1\n val l39 = l35 * l10 - i38.toLong\n if ((l37 > l39) || ((l37 == l39) && (i36 < i38))) { box27.R5[Coll[Byte]].get } else { coll31 }\n )} else { coll31 }\n )} else { coll31 }\n )}\n if ((coll32 != coll31) && (coll32 != coll9)) { ((((((((((((((((((func13(box28) >= func13(SELF)) && (box28.tokens(placeholder[Int](27))._1 == coll7)) && (box28.R4[Int].get == i1)) && (i1 == placeholder[Int](28))) && (box28.R5[Coll[Byte]].get == coll15)) && (box28.R6[(Coll[Byte], Coll[Byte])].get._1 == coll16)) && (box28.R6[(Coll[Byte], Coll[Byte])].get._2 == coll32)) && (box28.R7[Coll[Coll[Byte]]].get == coll18)) && (box28.R8[Coll[Long]].get(placeholder[Int](29)) == l10)) && (box28.R8[Coll[Long]].get(placeholder[Int](30)) == l19)) && (box28.R8[Coll[Long]].get(placeholder[Int](31)) == l14)) && (box28.R8[Coll[Long]].get(placeholder[Int](32)) == l20)) && (box28.R8[Coll[Long]].get(placeholder[Int](33)) == l21)) && (box28.R8[Coll[Long]].get(placeholder[Int](34)) == l4)) && (box28.R9[Coll[Coll[Byte]]].get(placeholder[Int](35)) == coll11(placeholder[Int](36)))) && (box28.R9[Coll[Coll[Byte]]].get(placeholder[Int](37)) == coll12)) && ((box28.R9[Coll[Coll[Byte]]].get(placeholder[Int](38)) == coll22) || (l4 - placeholder[Long](39) + placeholder[Long](40) < l2))) && (box28.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](41))) && bool30 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n )} else { placeholder[Boolean](44) }\n )} else { placeholder[Boolean](45) }\n )} else { placeholder[Boolean](46) }) || sigmaProp(if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](47))) {(\n val coll25 = CONTEXT.dataInputs\n val coll26 = coll25.filter({(box26: Box) => ((((((blake2b256(box26.propositionBytes) == placeholder[Coll[Byte]](48)) && (box26.tokens.size > placeholder[Int](49))) && (box26.R4[Coll[Byte]].get == placeholder[Coll[Byte]](50))) && (box26.R5[Coll[Byte]].get == coll9)) && box26.R6[Boolean].get) && (!box26.R8[Boolean].get)) && coll18.exists({(coll28: Coll[Byte]) => coll28 == box26.tokens(placeholder[Int](51))._1 }) })\n val coll27 = coll26.map({(box27: Box) => box27.tokens(placeholder[Int](52))._1 })\n val i28 = coll26.size\n val i29 = coll18.size\n val coll30 = OUTPUTS.filter({(box30: Box) => box30.propositionBytes == SELF.propositionBytes })\n if ((coll27.indices.forall({(i31: Int) => !coll27.slice(i31 + placeholder[Int](53), i28).exists({(coll33: Coll[Byte]) => coll33 == coll27(i31) }) }) && (i28 >= if (i29 == placeholder[Int](54)) { placeholder[Int](55) } else { i29 / placeholder[Int](56) + placeholder[Int](57) })) && (coll30.size == placeholder[Int](58))) {(\n val box31 = coll30(placeholder[Int](59))\n val coll32 = box31.R6[(Coll[Byte], Coll[Byte])].get._2\n val coll33 = INPUTS.filter({(box33: Box) => (blake2b256(box33.propositionBytes) == coll6) && (box33.R5[Coll[Byte]].get == coll9) })\n if (if (coll32 == Coll[Byte]()) { placeholder[Boolean](60) } else {(\n val coll34 = coll25.filter({(box34: Box) => ((blake2b256(box34.propositionBytes) == coll6) && (box34.R6[Coll[Byte]].get == coll7)) && (box34.R5[Coll[Byte]].get == coll32) })\n if (coll34.size == placeholder[Int](61)) {(\n val box35 = coll34(placeholder[Int](62))\n ((func17(box35)._2 && (func13(box35) >= l14)) && (box35.creationInfo._1.toLong < l10)) && (box35.R9[Coll[Long]].get.size.toLong <= placeholder[Long](63))\n )} else { placeholder[Boolean](64) }\n )} && (coll33.size == placeholder[Int](65))) {(\n val coll34 = box31.R8[Coll[Long]].get\n ((func13(box31) >= func13(SELF) + func13(coll33(placeholder[Int](66)))) && (coll34(placeholder[Int](67)) >= l2 + placeholder[Long](68))) && (((((((((((box31.tokens(placeholder[Int](69))._1 == coll7) && (box31.R4[Int].get == i1)) && (i1 == placeholder[Int](70))) && (box31.R5[Coll[Byte]].get == coll15)) && (box31.R7[Coll[Coll[Byte]]].get == coll18)) && (coll34(placeholder[Int](71)) == l10)) && (coll34(placeholder[Int](72)) == l19)) && (coll34(placeholder[Int](73)) == l14)) && (coll34(placeholder[Int](74)) == l20 + l21)) && (coll34(placeholder[Int](75)) == placeholder[Long](76))) && (box31.R9[Coll[Coll[Byte]]].get == coll11))\n )} else { placeholder[Boolean](77) }\n )} else { placeholder[Boolean](78) }\n )} else { placeholder[Boolean](79) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](80))) {(\n val bool25 = coll9 != Coll[Byte]()\n val coll26 = INPUTS.filter({(box26: Box) =>\n val coll28 = blake2b256(box26.propositionBytes)\n ((coll28 == coll6) || (coll28 == placeholder[Coll[Byte]](81))) && (box26.R6[Coll[Byte]].get == coll7)\n })\n val l27 = coll26.fold(placeholder[Long](82), {(tuple27: (Long, Box)) => tuple27._1 + func13(tuple27._2) }) + func13(SELF) - l19\n val l28 = l27 * l20 / placeholder[Long](83) * coll18.size.toLong\n val l29 = l27 * placeholder[Long](84) / placeholder[Long](85)\n val bool30 = if (l29 > placeholder[Long](86)) {\n OUTPUTS.filter({(box30: Box) => box30.propositionBytes == coll23 }).fold(\n placeholder[Long](87), {(tuple30: (Long, Box)) => tuple30._1 + func13(tuple30._2) }\n ) - INPUTS.filter({(box30: Box) => box30.propositionBytes == coll23 }).fold(\n placeholder[Long](88), {(tuple30: (Long, Box)) => tuple30._1 + func13(tuple30._2) }\n ) >= l29\n } else { placeholder[Boolean](89) }\n val bool31 = if (l28 > placeholder[Long](90)) {(\n val coll31 = OUTPUTS.filter({(box31: Box) => box31.propositionBytes == placeholder[Coll[Byte]](91) })\n if (coll31.size == placeholder[Int](92)) {(\n val box32 = coll31(placeholder[Int](93))\n ((func13(box32) >= l28) && (box32.R4[Coll[Coll[Byte]]].get == coll18)) && (box32.R5[Coll[Byte]].get == coll12)\n )} else { placeholder[Boolean](94) }\n )} else { placeholder[Boolean](95) }\n val prop32 = if (coll22.slice(placeholder[Int](96), placeholder[Int](97)) == coll24) {\n proveDlog(decodePoint(coll22.slice(placeholder[Int](98), coll22.size)))\n } else { sigmaProp(INPUTS.exists({(box32: Box) => box32.propositionBytes == coll22 })) }\n val coll33 = INPUTS.filter({(box33: Box) => (blake2b256(box33.propositionBytes) == coll6) && (box33.R5[Coll[Byte]].get == coll9) })\n val prop34 = if (bool25) { if (l2 >= l4 + placeholder[Long](99)) { prop32 } else { if (coll33.size > placeholder[Int](100)) {(\n val coll34 = coll33(placeholder[Int](101)).R4[Coll[Byte]].get\n if (coll34.slice(placeholder[Int](102), placeholder[Int](103)) == coll24) { proveDlog(decodePoint(coll34.slice(placeholder[Int](104), coll34.size))) } else { sigmaProp(INPUTS.exists({(box35: Box) => box35.propositionBytes == coll34 })) }\n )} else { sigmaProp(placeholder[Boolean](105)) } } } else { prop32 }\n if (bool25) {(\n val coll35 = coll26.filter({(box35: Box) => box35.R5[Coll[Byte]].get == coll9 })\n if (coll35.size == placeholder[Int](106)) {(\n val box36 = coll35(placeholder[Int](107))\n if (((func17(box36)._2 && (func13(box36) >= l14)) && (box36.creationInfo._1.toLong < l10)) && (\n box36.R9[Coll[Long]].get.size.toLong <= placeholder[Long](108)\n )) {(\n val coll37 = box36.R4[Coll[Byte]].get\n val l38 = l27 * l21 / placeholder[Long](109)\n val l39 = l27 - l38 - l28 - l29\n val bool40 = l39 < l14\n prop34 && sigmaProp(\n (\n (\n (\n (\n OUTPUTS.filter({(box41: Box) => box41.propositionBytes == coll37 }).fold(\n placeholder[Long](110), {(tuple41: (Long, Box)) => tuple41._1 + func13(tuple41._2) }\n ) - INPUTS.filter({(box41: Box) => box41.propositionBytes == coll37 }).fold(\n placeholder[Long](111), {(tuple41: (Long, Box)) => tuple41._1 + func13(tuple41._2) }\n ) >= if (bool40) { l27 } else { l39 }\n ) && OUTPUTS.exists(\n {(box41: Box) =>\n ((box41.propositionBytes == coll37) && (box41.tokens.size > placeholder[Int](112))) && (box41.tokens(placeholder[Int](113))._1 == coll7)\n }\n )\n ) && (\n OUTPUTS.filter({(box41: Box) => box41.propositionBytes == coll22 }).fold(\n placeholder[Long](114), {(tuple41: (Long, Box)) => tuple41._1 + func13(tuple41._2) }\n ) - INPUTS.filter({(box41: Box) => box41.propositionBytes == coll22 }).fold(\n placeholder[Long](115), {(tuple41: (Long, Box)) => tuple41._1 + func13(tuple41._2) }\n ) >= l19 + if (bool40) { placeholder[Long](116) } else { l38 }\n )\n ) && if (if (bool40) { placeholder[Long](117) } else { l29 } == placeholder[Long](118)) { placeholder[Boolean](119) } else { bool30 }\n ) && if (if (bool40) { placeholder[Long](120) } else { l28 } == placeholder[Long](121)) { placeholder[Boolean](122) } else { bool31 }\n )\n )} else { sigmaProp(placeholder[Boolean](123)) }\n )} else { sigmaProp(placeholder[Boolean](124)) }\n )} else {\n prop34 && sigmaProp(\n (\n (\n (\n OUTPUTS.filter({(box35: Box) => box35.propositionBytes == coll22 }).fold(\n placeholder[Long](125), {(tuple35: (Long, Box)) => tuple35._1 + func13(tuple35._2) }\n ) - INPUTS.filter({(box35: Box) => box35.propositionBytes == coll22 }).fold(\n placeholder[Long](126), {(tuple35: (Long, Box)) => tuple35._1 + func13(tuple35._2) }\n ) >= l27 + l19 - l29 - l28\n ) && OUTPUTS.exists(\n {(box35: Box) =>\n ((box35.propositionBytes == coll22) && (box35.tokens.size > placeholder[Int](127))) && (box35.tokens(placeholder[Int](128))._1 == coll7)\n }\n )\n ) && bool30\n ) && bool31\n )\n }\n )} else { sigmaProp(placeholder[Boolean](129)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "9c17dccbdea7041f524315bbdba68a04c7d9fa05961d87705f7cc4a455ccaaa7",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 500,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e080f9f5f05d2a29bd2",
"sigmaType": "Coll[SByte]",
"renderedValue": "0f9f5f05d2a29bd2"
},
"R6": {
"serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21201dc84a07c41754f58ca7a41c6ac74ed9fb76dc85830f957eda59b0e62b780f16",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,1dc84a07c41754f58ca7a41c6ac74ed9fb76dc85830f957eda59b0e62b780f16]"
},
"R8": {
"serializedValue": "1106b0f8ce01e807c801a08d0680b518d0face01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1695256,500,100,50000,200000,1695400]"
},
"R7": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
},
"R9": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[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,aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71,0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7]"
},
"R4": {
"serializedValue": "0402",
"sigmaType": "SInt",
"renderedValue": "1"
}
}
},
{
"boxId": "0ca7450ed46d60587fd74ba48d1e27da0df1e6719134b4410f958a1aecfcea5e",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "90e9058710b0e4091ced1560794e63332a18549e258d3c01aca2623fe9e04832",
"outputTransactionId": "05d88e83d0daacc27c5b05858da391ef6218b3878236f25bed98dc42e41f85e2",
"outputIndex": 0,
"outputGlobalIndex": 52840634,
"outputCreatedAt": 1695239,
"outputSettledAt": 1695240,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(0,8,-51)\n2: 1\n3: 0\n4: 1\n5: 0\n6: 1\n7: 0\n8: 1\n9: 0\n10: 1\n11: false\n12: 0\n13: 0\n14: 0\n15: 2\n16: 0\n17: 3\n18: 3\n19: false\n20: 1\n21: 0\n22: 1\n23: 0\n24: 0\n25: 0\n26: 5\n27: 0\n28: 3\n29: 3\n30: false\n31: false\n32: false\n33: 1\n34: 0\n35: 5\n36: 1\n37: false\n38: 1\n39: 0\n40: 5\n41: 1\n42: 1\n43: false\n44: 1\n45: 0\n46: 1\n47: 1\n48: 2\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: false\n55: false\n56: 0\n57: 0\n58: 0\n59: 0\n60: 0\n61: 3\n62: 3\n63: 0\n64: false\n65: 0\n66: 0\n67: false\n68: 0\n69: 0\n70: 3\n71: 3\n72: false\n73: false\n74: false\n75: false\n76: false",
"ergoTreeScript": "{\n val coll1 = CONTEXT.dataInputs\n val bool2 = coll1.size > placeholder[Int](0)\n val coll3 = SELF.R6[Coll[Byte]].get\n val coll4 = SELF.R4[Coll[Byte]].get\n val coll5 = placeholder[Coll[Byte]](1)\n val coll6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n (coll8.size >= placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == coll3)\n })\n val coll7 = INPUTS.filter({(box7: Box) =>\n val coll9 = box7.tokens\n (coll9.size >= placeholder[Int](4)) && (coll9(placeholder[Int](5))._1 == coll3)\n })\n val coll8 = coll1.filter({(box8: Box) =>\n val coll10 = box8.tokens\n (coll10.size >= placeholder[Int](6)) && (coll10(placeholder[Int](7))._1 == coll3)\n })\n if (bool2) {(\n val coll9 = coll1.filter({(box9: Box) =>\n val coll11 = box9.tokens\n (coll11.size >= placeholder[Int](8)) && (coll11(placeholder[Int](9))._1 == coll3)\n })\n if (coll9.size != placeholder[Int](10)) { sigmaProp(placeholder[Boolean](11)) } else {(\n val box10 = coll9(placeholder[Int](12))\n val coll11 = box10.tokens\n sigmaProp(\n ((coll11.size > placeholder[Int](13)) && (coll11(placeholder[Int](14))._1 == coll3)) && (box10.R4[Int].get == placeholder[Int](15))\n ) && sigmaProp(coll4.slice(placeholder[Int](16), placeholder[Int](17)) == coll5) && proveDlog(\n decodePoint(coll4.slice(placeholder[Int](18), coll4.size))\n ) || sigmaProp(INPUTS.exists({(box12: Box) => box12.propositionBytes == coll4 }))\n )}\n )} else { sigmaProp(placeholder[Boolean](19)) } || if (bool2) {(\n val coll9 = coll1.filter({(box9: Box) =>\n val coll11 = box9.tokens\n (coll11.size >= placeholder[Int](20)) && (coll11(placeholder[Int](21))._1 == coll3)\n })\n if (coll9.size == placeholder[Int](22)) {(\n val box10 = coll9(placeholder[Int](23))\n if (box10.R4[Int].get == placeholder[Int](24)) {\n sigmaProp(HEIGHT.toLong >= box10.R8[Coll[Long]].get(placeholder[Int](25)) + placeholder[Long](26)) && sigmaProp(\n coll4.slice(placeholder[Int](27), placeholder[Int](28)) == coll5\n ) && proveDlog(decodePoint(coll4.slice(placeholder[Int](29), coll4.size))) || sigmaProp(\n INPUTS.exists({(box11: Box) => box11.propositionBytes == coll4 })\n )\n } else { sigmaProp(placeholder[Boolean](30)) }\n )} else { sigmaProp(placeholder[Boolean](31)) }\n )} else { sigmaProp(placeholder[Boolean](32)) } || sigmaProp(if (coll6.size == placeholder[Int](33)) {(\n val box9 = coll6(placeholder[Int](34))\n (HEIGHT.toLong >= box9.R8[Coll[Long]].get(placeholder[Int](35))) && (box9.R4[Int].get == placeholder[Int](36))\n )} else { placeholder[Boolean](37) }) || sigmaProp(if (coll7.size == placeholder[Int](38)) {(\n val box9 = coll7(placeholder[Int](39))\n (((HEIGHT.toLong < box9.R8[Coll[Long]].get(placeholder[Int](40))) && (SELF.R5[Coll[Byte]].get == box9.R6[(Coll[Byte], Coll[Byte])].get._2)) && (OUTPUTS.filter({(box10: Box) => box10.propositionBytes == box9.propositionBytes }).size == placeholder[Int](41))) && (box9.R4[Int].get == placeholder[Int](42))\n )} else { placeholder[Boolean](43) }) || if (coll8.size == placeholder[Int](44)) {(\n val box9 = coll8(placeholder[Int](45))\n if (box9.R4[Int].get == placeholder[Int](46)) {(\n val coll10 = SELF.propositionBytes\n val coll11 = OUTPUTS.filter(\n {(box11: Box) => ((box11.propositionBytes != coll10) && box11.R6[Coll[Byte]].isDefined) && (box11.R6[Coll[Byte]].get == coll3) }\n )\n val coll12 = box9.R9[Coll[Coll[Byte]]].get\n val coll13 = coll12(placeholder[Int](47))\n val coll14 = coll12(placeholder[Int](48))\n val tuple15 = box9.R6[(Coll[Byte], Coll[Byte])].get\n val coll16 = tuple15._2\n if (coll11.size == placeholder[Int](49)) {(\n val coll17 = coll11(placeholder[Int](50)).tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll13 })\n sigmaProp(if (coll17.size > placeholder[Int](51)) { coll17(placeholder[Int](52))._2 } else { placeholder[Long](53) } >= INPUTS.filter({(box18: Box) =>\n val coll20 = box18.propositionBytes\n if ((coll20 == coll10) || (((coll20 != coll10) && box18.R6[Coll[Byte]].isDefined) && (box18.R6[Coll[Byte]].get == coll3))) {(\n val opt21 = box18.R6[Coll[Byte]]\n if (opt21.isDefined) { opt21.get == coll3 } else { placeholder[Boolean](54) }\n )} else { placeholder[Boolean](55) }\n }).fold(placeholder[Long](56), {(tuple18: (Long, Box)) =>\n val coll20 = tuple18._2.tokens.filter({(tuple20: (Coll[Byte], Long)) => tuple20._1 == coll13 })\n tuple18._1 + if (coll20.size > placeholder[Int](57)) { coll20(placeholder[Int](58))._2 } else { placeholder[Long](59) }\n })) && if (coll14.slice(placeholder[Int](60), placeholder[Int](61)) == coll5) {\n proveDlog(decodePoint(coll14.slice(placeholder[Int](62), coll14.size)))\n } else { sigmaProp(INPUTS.exists({(box18: Box) => box18.propositionBytes == coll14 })) } || if (coll16.size > placeholder[Int](63)) {(\n val coll18 = if (SELF.R5[Coll[Byte]].get == coll16) { coll4 } else {(\n val coll18 = coll1.filter({(box18: Box) =>\n val opt20 = box18.R5[Coll[Byte]]\n if (opt20.isDefined) { opt20.get == coll16 } else { placeholder[Boolean](64) }\n })\n if (coll18.size > placeholder[Int](65)) {(\n val box19 = coll18(placeholder[Int](66))\n val coll20 = box19.R4[Coll[Byte]].get\n if (box19.R9[Coll[Long]].get.fold(placeholder[Boolean](67), {(tuple21: (Boolean, Long)) =>\n val bool23 = tuple21._1\n if (bool23) { bool23 } else { blake2b256(box19.R7[Coll[Byte]].get.append(box9.R5[Coll[Byte]].get).append(longToByteArray(tuple21._2)).append(box19.R8[Coll[Byte]].get).append(coll20).append(tuple15._1)) == box19.R5[Coll[Byte]].get }\n })) { coll20 } else { Coll[Byte]() }\n )} else { Coll[Byte]() }\n )}\n val i19 = coll18.size\n if (i19 > placeholder[Int](68)) {\n if (coll18.slice(placeholder[Int](69), placeholder[Int](70)) == coll5) { proveDlog(decodePoint(coll18.slice(placeholder[Int](71), i19))) } else {\n sigmaProp(INPUTS.exists({(box20: Box) => box20.propositionBytes == coll18 }))\n }\n } else { sigmaProp(placeholder[Boolean](72)) }\n )} else { sigmaProp(placeholder[Boolean](73)) }\n )} else { sigmaProp(placeholder[Boolean](74)) }\n )} else { sigmaProp(placeholder[Boolean](75)) }\n )} else { sigmaProp(placeholder[Boolean](76)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 0,
"amount": 100,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e201dc84a07c41754f58ca7a41c6ac74ed9fb76dc85830f957eda59b0e62b780f16",
"sigmaType": "Coll[SByte]",
"renderedValue": "1dc84a07c41754f58ca7a41c6ac74ed9fb76dc85830f957eda59b0e62b780f16"
},
"R6": {
"serializedValue": "0e209c17dccbdea7041f524315bbdba68a04c7d9fa05961d87705f7cc4a455ccaaa7",
"sigmaType": "Coll[SByte]",
"renderedValue": "9c17dccbdea7041f524315bbdba68a04c7d9fa05961d87705f7cc4a455ccaaa7"
},
"R8": {
"serializedValue": "0e20df4714fbf52818f9908376a907328d4cb01e71104044a6316fae4262784d015d",
"sigmaType": "Coll[SByte]",
"renderedValue": "df4714fbf52818f9908376a907328d4cb01e71104044a6316fae4262784d015d"
},
"R7": {
"serializedValue": "0e206b0fd3bb639df1f45a1f39411a5d03caf1c2c477077f9d742a4582337f1732dc",
"sigmaType": "Coll[SByte]",
"renderedValue": "6b0fd3bb639df1f45a1f39411a5d03caf1c2c477077f9d742a4582337f1732dc"
},
"R9": {
"serializedValue": "11053c18140628",
"sigmaType": "Coll[SLong]",
"renderedValue": "[30,12,10,3,20]"
},
"R4": {
"serializedValue": "0e240008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
}
}
},
{
"boxId": "ccbc22b874ad0ede9af346e7530dae9e1c7d6b189a37912c1bcd55a805ac9380",
"value": 1000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "219d9b75a96770c777f69f421ddf7f0c4aca8787e865a6c0b6a91e6bfd3e4f36",
"outputTransactionId": "89cb7885069df40a62046e56272362e338b63802c8aa7fd3fba2a8115369eabf",
"outputIndex": 0,
"outputGlobalIndex": 52840788,
"outputCreatedAt": 1695242,
"outputSettledAt": 1695244,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(0,8,-51)\n2: 1\n3: 0\n4: 1\n5: 0\n6: 1\n7: 0\n8: 1\n9: 0\n10: 1\n11: false\n12: 0\n13: 0\n14: 0\n15: 2\n16: 0\n17: 3\n18: 3\n19: false\n20: 1\n21: 0\n22: 1\n23: 0\n24: 0\n25: 0\n26: 5\n27: 0\n28: 3\n29: 3\n30: false\n31: false\n32: false\n33: 1\n34: 0\n35: 5\n36: 1\n37: false\n38: 1\n39: 0\n40: 5\n41: 1\n42: 1\n43: false\n44: 1\n45: 0\n46: 1\n47: 1\n48: 2\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: false\n55: false\n56: 0\n57: 0\n58: 0\n59: 0\n60: 0\n61: 3\n62: 3\n63: 0\n64: false\n65: 0\n66: 0\n67: false\n68: 0\n69: 0\n70: 3\n71: 3\n72: false\n73: false\n74: false\n75: false\n76: false",
"ergoTreeScript": "{\n val coll1 = CONTEXT.dataInputs\n val bool2 = coll1.size > placeholder[Int](0)\n val coll3 = SELF.R6[Coll[Byte]].get\n val coll4 = SELF.R4[Coll[Byte]].get\n val coll5 = placeholder[Coll[Byte]](1)\n val coll6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n (coll8.size >= placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == coll3)\n })\n val coll7 = INPUTS.filter({(box7: Box) =>\n val coll9 = box7.tokens\n (coll9.size >= placeholder[Int](4)) && (coll9(placeholder[Int](5))._1 == coll3)\n })\n val coll8 = coll1.filter({(box8: Box) =>\n val coll10 = box8.tokens\n (coll10.size >= placeholder[Int](6)) && (coll10(placeholder[Int](7))._1 == coll3)\n })\n if (bool2) {(\n val coll9 = coll1.filter({(box9: Box) =>\n val coll11 = box9.tokens\n (coll11.size >= placeholder[Int](8)) && (coll11(placeholder[Int](9))._1 == coll3)\n })\n if (coll9.size != placeholder[Int](10)) { sigmaProp(placeholder[Boolean](11)) } else {(\n val box10 = coll9(placeholder[Int](12))\n val coll11 = box10.tokens\n sigmaProp(\n ((coll11.size > placeholder[Int](13)) && (coll11(placeholder[Int](14))._1 == coll3)) && (box10.R4[Int].get == placeholder[Int](15))\n ) && sigmaProp(coll4.slice(placeholder[Int](16), placeholder[Int](17)) == coll5) && proveDlog(\n decodePoint(coll4.slice(placeholder[Int](18), coll4.size))\n ) || sigmaProp(INPUTS.exists({(box12: Box) => box12.propositionBytes == coll4 }))\n )}\n )} else { sigmaProp(placeholder[Boolean](19)) } || if (bool2) {(\n val coll9 = coll1.filter({(box9: Box) =>\n val coll11 = box9.tokens\n (coll11.size >= placeholder[Int](20)) && (coll11(placeholder[Int](21))._1 == coll3)\n })\n if (coll9.size == placeholder[Int](22)) {(\n val box10 = coll9(placeholder[Int](23))\n if (box10.R4[Int].get == placeholder[Int](24)) {\n sigmaProp(HEIGHT.toLong >= box10.R8[Coll[Long]].get(placeholder[Int](25)) + placeholder[Long](26)) && sigmaProp(\n coll4.slice(placeholder[Int](27), placeholder[Int](28)) == coll5\n ) && proveDlog(decodePoint(coll4.slice(placeholder[Int](29), coll4.size))) || sigmaProp(\n INPUTS.exists({(box11: Box) => box11.propositionBytes == coll4 })\n )\n } else { sigmaProp(placeholder[Boolean](30)) }\n )} else { sigmaProp(placeholder[Boolean](31)) }\n )} else { sigmaProp(placeholder[Boolean](32)) } || sigmaProp(if (coll6.size == placeholder[Int](33)) {(\n val box9 = coll6(placeholder[Int](34))\n (HEIGHT.toLong >= box9.R8[Coll[Long]].get(placeholder[Int](35))) && (box9.R4[Int].get == placeholder[Int](36))\n )} else { placeholder[Boolean](37) }) || sigmaProp(if (coll7.size == placeholder[Int](38)) {(\n val box9 = coll7(placeholder[Int](39))\n (((HEIGHT.toLong < box9.R8[Coll[Long]].get(placeholder[Int](40))) && (SELF.R5[Coll[Byte]].get == box9.R6[(Coll[Byte], Coll[Byte])].get._2)) && (OUTPUTS.filter({(box10: Box) => box10.propositionBytes == box9.propositionBytes }).size == placeholder[Int](41))) && (box9.R4[Int].get == placeholder[Int](42))\n )} else { placeholder[Boolean](43) }) || if (coll8.size == placeholder[Int](44)) {(\n val box9 = coll8(placeholder[Int](45))\n if (box9.R4[Int].get == placeholder[Int](46)) {(\n val coll10 = SELF.propositionBytes\n val coll11 = OUTPUTS.filter(\n {(box11: Box) => ((box11.propositionBytes != coll10) && box11.R6[Coll[Byte]].isDefined) && (box11.R6[Coll[Byte]].get == coll3) }\n )\n val coll12 = box9.R9[Coll[Coll[Byte]]].get\n val coll13 = coll12(placeholder[Int](47))\n val coll14 = coll12(placeholder[Int](48))\n val tuple15 = box9.R6[(Coll[Byte], Coll[Byte])].get\n val coll16 = tuple15._2\n if (coll11.size == placeholder[Int](49)) {(\n val coll17 = coll11(placeholder[Int](50)).tokens.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 == coll13 })\n sigmaProp(if (coll17.size > placeholder[Int](51)) { coll17(placeholder[Int](52))._2 } else { placeholder[Long](53) } >= INPUTS.filter({(box18: Box) =>\n val coll20 = box18.propositionBytes\n if ((coll20 == coll10) || (((coll20 != coll10) && box18.R6[Coll[Byte]].isDefined) && (box18.R6[Coll[Byte]].get == coll3))) {(\n val opt21 = box18.R6[Coll[Byte]]\n if (opt21.isDefined) { opt21.get == coll3 } else { placeholder[Boolean](54) }\n )} else { placeholder[Boolean](55) }\n }).fold(placeholder[Long](56), {(tuple18: (Long, Box)) =>\n val coll20 = tuple18._2.tokens.filter({(tuple20: (Coll[Byte], Long)) => tuple20._1 == coll13 })\n tuple18._1 + if (coll20.size > placeholder[Int](57)) { coll20(placeholder[Int](58))._2 } else { placeholder[Long](59) }\n })) && if (coll14.slice(placeholder[Int](60), placeholder[Int](61)) == coll5) {\n proveDlog(decodePoint(coll14.slice(placeholder[Int](62), coll14.size)))\n } else { sigmaProp(INPUTS.exists({(box18: Box) => box18.propositionBytes == coll14 })) } || if (coll16.size > placeholder[Int](63)) {(\n val coll18 = if (SELF.R5[Coll[Byte]].get == coll16) { coll4 } else {(\n val coll18 = coll1.filter({(box18: Box) =>\n val opt20 = box18.R5[Coll[Byte]]\n if (opt20.isDefined) { opt20.get == coll16 } else { placeholder[Boolean](64) }\n })\n if (coll18.size > placeholder[Int](65)) {(\n val box19 = coll18(placeholder[Int](66))\n val coll20 = box19.R4[Coll[Byte]].get\n if (box19.R9[Coll[Long]].get.fold(placeholder[Boolean](67), {(tuple21: (Boolean, Long)) =>\n val bool23 = tuple21._1\n if (bool23) { bool23 } else { blake2b256(box19.R7[Coll[Byte]].get.append(box9.R5[Coll[Byte]].get).append(longToByteArray(tuple21._2)).append(box19.R8[Coll[Byte]].get).append(coll20).append(tuple15._1)) == box19.R5[Coll[Byte]].get }\n })) { coll20 } else { Coll[Byte]() }\n )} else { Coll[Byte]() }\n )}\n val i19 = coll18.size\n if (i19 > placeholder[Int](68)) {\n if (coll18.slice(placeholder[Int](69), placeholder[Int](70)) == coll5) { proveDlog(decodePoint(coll18.slice(placeholder[Int](71), i19))) } else {\n sigmaProp(INPUTS.exists({(box20: Box) => box20.propositionBytes == coll18 }))\n }\n } else { sigmaProp(placeholder[Boolean](72)) }\n )} else { sigmaProp(placeholder[Boolean](73)) }\n )} else { sigmaProp(placeholder[Boolean](74)) }\n )} else { sigmaProp(placeholder[Boolean](75)) }\n )} else { sigmaProp(placeholder[Boolean](76)) }\n}",
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"assets": [
{
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"amount": 100,
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],
"additionalRegisters": {
"R5": {
"serializedValue": "0e2018cf75b444fbca3cf9fa9df8ecb9fbb8600e836622739846b1d594adc7776dea",
"sigmaType": "Coll[SByte]",
"renderedValue": "18cf75b444fbca3cf9fa9df8ecb9fbb8600e836622739846b1d594adc7776dea"
},
"R6": {
"serializedValue": "0e209c17dccbdea7041f524315bbdba68a04c7d9fa05961d87705f7cc4a455ccaaa7",
"sigmaType": "Coll[SByte]",
"renderedValue": "9c17dccbdea7041f524315bbdba68a04c7d9fa05961d87705f7cc4a455ccaaa7"
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"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b39679d55b0724ba3a9e21a7f5a2ba0c35cd30581a3870b1869ebe5a91de17b2"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3bcc58faedd80c52512b0cf489b68b3e41dd1cf5be13954d186e8635e01198db"
},
"R9": {
"serializedValue": "11065018402cd08c0102",
"sigmaType": "Coll[SLong]",
"renderedValue": "[40,12,32,22,9000,1]"
},
"R4": {
"serializedValue": "0e240008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
}
}
},
{
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"index": 3,
"spendingProof": "a6ee9852b13b8d92d6edd810bb0f19b3d18dda3eb0396ef1af597247f0507abe55e8073b27c432199fa4b5da974722b3b37d1c461782921b",
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"outputTransactionId": "89cb7885069df40a62046e56272362e338b63802c8aa7fd3fba2a8115369eabf",
"outputIndex": 2,
"outputGlobalIndex": 52840790,
"outputCreatedAt": 1695242,
"outputSettledAt": 1695244,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
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{
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{
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{
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{
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{
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{
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{
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{
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{
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{
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"type": "EIP-004"
},
{
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{
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{
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{
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{
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{
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},
{
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"index": 42,
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"name": "fakeBTC",
"decimals": 2,
"type": "EIP-004"
},
{
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"name": "FALCON",
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"type": "EIP-004"
},
{
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"index": 44,
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"type": "EIP-004"
},
{
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"index": 45,
"amount": 100,
"name": "TEST TIMESTAMP 17:05 APT",
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"type": "EIP-004"
},
{
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"name": "TEST V2 APT",
"decimals": 5,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "532a61b93c9c3f02b8e81afddb1f72badab84696634fd2340ecab557dc36524e",
"transactionId": "21bb0271e85c2fb7908f36eb636ac2751a3e097576887fde19736aa93268cebe",
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"index": 0,
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"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
"assets": [
{
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},
{
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"decimals": 2,
"type": "EIP-004"
}
],
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},
{
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
"assets": [
{
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"index": 0,
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}
],
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},
{
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"ergoTree": "0008cd025ac8ab183ffde36068603120b00acdf141b91fe4e0c0c6d562b5f24e1e2cc2d1",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(5ac8ab,1fc551,...)))}",
"address": "9fD3U2uorV2kUR85P7ukUCLHEyYn77FWVgNNgQTH3mfG7FzvgyY",
"assets": [
{
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"index": 0,
"amount": 10,
"name": "CAT",
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}
],
"additionalRegisters": {},
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},
{
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"blockId": "07c05767a680e86c63bad7e0ed25bb5887555366207c75fbf677c5c7d4f7f161",
"value": 1000000,
"index": 3,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 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)\n4: 0\n5: 0\n6: 0\n7: 1\n8: false\n9: 0\n10: 0\n11: 0\n12: 1\n13: true",
"ergoTreeScript": "{\n val func1 = {(box1: Box) =>\n box1.tokens.filter({(tuple3: (Coll[Byte], Long)) => tuple3._1 == SELF.R5[Coll[Byte]].get }).fold(\n placeholder[Long](0), {(tuple3: (Long, (Coll[Byte], Long))) => tuple3._1 + tuple3._2._2 }\n )\n }\n val l2 = func1(SELF)\n val coll3 = SELF.R4[Coll[Coll[Byte]]].get\n val i4 = coll3.size\n if ((l2 > placeholder[Long](1)) && (i4 > placeholder[Int](2))) {(\n val coll5 = CONTEXT.dataInputs.filter(\n {(box5: Box) =>\n ((blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](3)) && (box5.tokens.size > placeholder[Int](4))) && coll3.exists(\n {(coll7: Coll[Byte]) => coll7 == box5.tokens(placeholder[Int](5))._1 }\n )\n }\n )\n val coll6 = coll5.map({(box6: Box) => box6.tokens(placeholder[Int](6))._1 })\n val bool7 = coll6.forall({(coll7: Coll[Byte]) => coll6.filter({(coll9: Coll[Byte]) => coll9 == coll7 }).size == placeholder[Int](7) })\n val coll8 = coll5.map({(box8: Box) => box8.R7[Coll[Byte]].get })\n if ((!bool7) || (!((coll5.size == i4) && bool7))) { sigmaProp(placeholder[Boolean](8)) } else {\n sigmaProp(coll8.fold(Coll[Coll[Byte]](), {(tuple9: (Coll[Coll[Byte]], Coll[Byte])) =>\n val coll11 = tuple9._1\n val coll12 = tuple9._2\n if (coll11.exists({(coll13: Coll[Byte]) => coll13 == coll12 })) { coll11 } else { coll11.append(Coll[Coll[Byte]](coll12)) }\n }).forall({(coll9: Coll[Byte]) => OUTPUTS.filter({(box11: Box) => box11.propositionBytes == coll9 }).fold(placeholder[Long](9), {(tuple11: (Long, Box)) => tuple11._1 + func1(tuple11._2) }) - INPUTS.filter({(box11: Box) => box11.propositionBytes == coll9 }).fold(placeholder[Long](10), {(tuple11: (Long, Box)) => tuple11._1 + func1(tuple11._2) }) >= l2 / i4.toLong * coll8.fold(placeholder[Int](11), {(tuple11: (Int, Coll[Byte])) =>\n val i13 = tuple11._1\n if (tuple11._2 == coll9) { i13 + placeholder[Int](12) } else { i13 }\n }).toLong }))\n }\n )} else { sigmaProp(placeholder[Boolean](13)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 0,
"amount": 10,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
},
"R5": {
"serializedValue": "0e20aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"sigmaType": "Coll[SByte]",
"renderedValue": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "e420c3bc13006d1caa7dbbe369d6732e992513ed6685db8c34193726f47e16eb",
"transactionId": "21bb0271e85c2fb7908f36eb636ac2751a3e097576887fde19736aa93268cebe",
"blockId": "07c05767a680e86c63bad7e0ed25bb5887555366207c75fbf677c5c7d4f7f161",
"value": 1100000,
"index": 4,
"globalIndex": 52846170,
"creationHeight": 1695431,
"settlementHeight": 1695432,
"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": "6b61e75f13b09debfe7062419cc1a1a2364b834d49d4db67fa3adf0d357995a3",
"mainChain": true
},
{
"boxId": "1b6a059be31aeee9723c95d0ce189bcdd9d504f938c68e7bcf73046176d157c5",
"transactionId": "21bb0271e85c2fb7908f36eb636ac2751a3e097576887fde19736aa93268cebe",
"blockId": "07c05767a680e86c63bad7e0ed25bb5887555366207c75fbf677c5c7d4f7f161",
"value": 978987160,
"index": 5,
"globalIndex": 52846171,
"creationHeight": 1695431,
"settlementHeight": 1695432,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
"assets": [
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 0,
"amount": 95830348,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "a6b3df8edc3223975b49247b425e69a85cb45f3c7a94668ba89c890f2f0d2194",
"index": 1,
"amount": 4700,
"name": "TEST DEV 50 PERCENT APT",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "6ab9fd7c9f372d0c9d14d664366e3d01a59034d69a4c97718d1c10365a3e7440",
"index": 2,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "74b523d60361e82c42128283957aec7e01fe5fe6e29b6546645d3f7e16b3b92a",
"index": 3,
"amount": 999899770975,
"name": "GOLD",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "a95f16e4ec81aadd57d7746b2ea01c5246b4fe23499b3723a1b0398224d1f57e",
"index": 4,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "bdd963aed92ff3c5b0b14558069d7c55c787d88a0f9f15f941ddde28e79212d6",
"index": 5,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
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