Transaction
ID: a592699741...5c32
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00209296 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
20
Spent
Address:
Output transaction:
Settlement height:
Value:
0.51038768 ERG
Tokens:
Loading assets...
Outputs (3)
Unspent
Address:
Settlement height:
Value:
0.00309296 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.50928768 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 49,820
Total coins transferred: 0.51348064 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000205 ERG
Raw Transaction Data
{
"id": "a5926997410ca3d39ce49dc5bd1d9569d42dfd329cba013324d7f7c999015c32",
"blockId": "c819147e113bce05c32cc6713aae97633bafe88aa0a80d52edb8a430a688c3eb",
"inclusionHeight": 1718200,
"timestamp": 1770640468712,
"index": 4,
"globalIndex": 10275815,
"numConfirmations": 49820,
"inputs": [
{
"boxId": "d011c6cb115348fe029883b8160580bf849ed3a203b65aca5289c3585da52cde",
"value": 2092960,
"index": 0,
"spendingProof": null,
"outputBlockId": "5d46fd8b7526b424644d5cebb882e13ab8973af9b56d7d2372a2ca973fc40aca",
"outputTransactionId": "ba9922e2d34cf37b7bf3c16ba9defb91e9edb58699733343704c189a4e87c2af",
"outputIndex": 0,
"outputGlobalIndex": 53477245,
"outputCreatedAt": 1718188,
"outputSettledAt": 1718190,
"ergoTree": "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",
"ergoTreeConstants": "0: 8\n1: Coll(45,-126,27,3,-30,-34,114,118,-69,-21,-77,-1,65,-20,55,79,-99,110,-38,67,100,97,-111,76,1,38,-126,-49,100,95,-92,-54)\n2: 0\n3: 2\n4: 0\n5: Coll(122,-94,-75,-37,-122,16,-18,-68,-23,35,110,21,-55,109,-47,84,-91,113,115,65,96,4,98,-91,-79,-37,114,2,-73,30,-45,38)\n6: 0\n7: 0\n8: 1\n9: 1\n10: 0\n11: 4\n12: -1\n13: false\n14: true\n15: 1\n16: 3\n17: 5\n18: 6\n19: 7\n20: 0\n21: 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)\n22: 0\n23: 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)\n24: Coll(-90,-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,-39)\n25: true\n26: 0\n27: 0\n28: 1\n29: 0\n30: 0\n31: 2\n32: 1\n33: 1\n34: 0\n35: 1\n36: 0\n37: 8\n38: 30\n39: 0\n40: 1\n41: 0\n42: 1\n43: 2\n44: 3\n45: 4\n46: 5\n47: 0\n48: 6\n49: 0\n50: 7\n51: false\n52: false\n53: false\n54: 1\n55: 1\n56: 1\n57: 1\n58: 0\n59: 5\n60: 1\n61: 10\n62: -1\n63: 1\n64: 0\n65: -1\n66: 1\n67: 1\n68: 0\n69: 0\n70: 1\n71: 0\n72: 1\n73: 2\n74: 3\n75: 4\n76: 5\n77: 6\n78: 7\n79: 8\n80: 0\n81: 0\n82: 1\n83: 2\n84: 2\n85: 3\n86: 3\n87: 30\n88: 5\n89: 4\n90: false\n91: false\n92: false\n93: false\n94: false\n95: true\n96: false\n97: 0\n98: Coll(-34,-95,53,-55,103,102,9,81,53,114,-127,-84,25,-103,-109,107,-112,126,-39,-83,-33,-115,43,-82,55,114,26,-29,53,126,107,-22)\n99: 1\n100: 0\n101: 0\n102: 1\n103: 0\n104: 1\n105: 2\n106: 3\n107: 4\n108: 5\n109: 6\n110: 7\n111: 8\n112: false\n113: 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 coll10 = CONTEXT.dataInputs\n val l11 = coll3(placeholder[Int](3))\n val l12 = coll3(placeholder[Int](4))\n val func13 = {(box13: Box) =>\n val coll15 = coll10.filter({(box15: Box) =>\n val opt17 = box15.R4[Coll[Byte]]\n (opt17.isDefined && (opt17.get == box13.R7[Coll[Byte]].get)) && (blake2b256(box15.propositionBytes) == placeholder[Coll[Byte]](5))\n })\n if (coll15.size > placeholder[Int](6)) {(\n val l16 = coll15.fold(coll15(placeholder[Int](7)), {(tuple16: (Box, Box)) =>\n val box18 = tuple16._2\n val box19 = tuple16._1\n if (box18.creationInfo._1 < box19.creationInfo._1) { box18 } else { box19 }\n }).creationInfo._1.toLong\n val l17 = l12 + placeholder[Long](8)\n if (l16 < l17) { l17 } else { l16 }\n )} else { l11 }\n }\n val coll14 = SELF.R9[Coll[Coll[Byte]]].get\n val coll15 = coll14(placeholder[Int](9))\n val func16 = {(box16: Box) =>\n box16.tokens.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 == coll15 }).fold(\n placeholder[Long](10), {(tuple18: (Long, (Coll[Byte], Long))) => tuple18._1 + tuple18._2._2 }\n )\n }\n val l17 = coll3(placeholder[Int](11))\n val coll18 = SELF.R5[Coll[Byte]].get\n val coll19 = tuple8._1\n val func20 = {(box20: Box) => box20.R9[Coll[Long]].get.fold((placeholder[Long](12), placeholder[Boolean](13)), {(tuple22: ((Long, Boolean), Long)) =>\n val tuple24 = tuple22._1\n val l25 = tuple22._2\n if (tuple24._2) { tuple24 } else { if (blake2b256(box20.R7[Coll[Byte]].get.append(coll18).append(longToByteArray(l25)).append(box20.R8[Coll[Byte]].get).append(box20.R4[Coll[Byte]].get).append(coll19)) == box20.R5[Coll[Byte]].get) { (l25, placeholder[Boolean](14)) } else { tuple24 } }\n }) }\n val l21 = coll3(placeholder[Int](15))\n val coll22 = SELF.R7[Coll[Coll[Byte]]].get\n val l23 = coll3(placeholder[Int](16))\n val l24 = coll3(placeholder[Int](17))\n val l25 = coll3(placeholder[Int](18))\n val l26 = coll3(placeholder[Int](19))\n val func27 = {(bool27: Boolean) => if (bool5 && (coll10.size > placeholder[Int](20))) {(\n val coll29 = coll10.filter({(box29: Box) => (((((blake2b256(box29.propositionBytes) == placeholder[Coll[Byte]](21)) && (box29.tokens.size > placeholder[Int](22))) && (box29.R4[Coll[Byte]].get == if (bool27) { placeholder[Coll[Byte]](23) } else { placeholder[Coll[Byte]](24) })) && (box29.R5[Coll[Byte]].get == coll9)) && if (bool27) { box29.R6[Boolean].get && (!box29.R8[Boolean].get) } else { placeholder[Boolean](25) }) && coll22.exists({(coll31: Coll[Byte]) => coll31 == box29.tokens(placeholder[Int](26))._1 }) })\n val coll30 = coll29.map({(box30: Box) => box30.tokens(placeholder[Int](27))._1 })\n val i31 = coll29.size\n val i32 = coll22.size\n val coll33 = OUTPUTS.filter({(box33: Box) => box33.propositionBytes == SELF.propositionBytes })\n if ((coll30.indices.forall({(i34: Int) => !coll30.slice(i34 + placeholder[Int](28), i31).exists({(coll36: Coll[Byte]) => coll36 == coll30(i34) }) }) && (i31 >= if (i32 == placeholder[Int](29)) { placeholder[Int](30) } else { i32 / placeholder[Int](31) + placeholder[Int](32) })) && (coll33.size == placeholder[Int](33))) {(\n val box34 = coll33(placeholder[Int](34))\n val coll35 = INPUTS.filter({(box35: Box) => (blake2b256(box35.propositionBytes) == coll6) && (box35.R5[Coll[Byte]].get == coll9) })\n if ((box34.R6[(Coll[Byte], Coll[Byte])].get._2 == Coll[Byte]()) && (coll35.size == placeholder[Int](35))) { ((func16(box34) >= func16(SELF) + func16(coll35(placeholder[Int](36)))) && (box34.R8[Coll[Long]].get(placeholder[Int](37)) >= l2 + placeholder[Long](38))) && ((((((((((((((box34.tokens(placeholder[Int](39))._1 == coll7) && (box34.R4[Int].get == i1)) && (i1 == placeholder[Int](40))) && (box34.R5[Coll[Byte]].get == coll18)) && (box34.R7[Coll[Coll[Byte]]].get == coll22)) && (box34.R8[Coll[Long]].get(placeholder[Int](41)) == l12)) && (box34.R8[Coll[Long]].get(placeholder[Int](42)) == l21)) && (box34.R8[Coll[Long]].get(placeholder[Int](43)) == l11)) && (box34.R8[Coll[Long]].get(placeholder[Int](44)) == l23)) && (box34.R8[Coll[Long]].get(placeholder[Int](45)) == l17)) && (box34.R8[Coll[Long]].get(placeholder[Int](46)) == l24 + if (bool27) { l25 } else { placeholder[Long](47) })) && (box34.R8[Coll[Long]].get(placeholder[Int](48)) == if (bool27) { placeholder[Long](49) } else { l25 })) && (box34.R8[Coll[Long]].get(placeholder[Int](50)) == l26)) && (box34.R9[Coll[Coll[Byte]]].get == coll14)) } else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n )} else { placeholder[Boolean](53) } }\n sigmaProp(i1 == placeholder[Int](54)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](55))) && (OUTPUTS.size > placeholder[Int](56))) {(\n val coll28 = coll10.filter({(box28: Box) => ((blake2b256(box28.propositionBytes) == coll6) && (box28.R6[Coll[Byte]].get == coll7)) && (box28.R5[Coll[Byte]].get != coll9) })\n if (coll28.size == placeholder[Int](57)) {(\n val box29 = coll28(placeholder[Int](58))\n val l30 = func13(box29)\n if ((((((blake2b256(box29.propositionBytes) == coll6) && (box29.R6[Coll[Byte]].get == coll7)) && (box29.creationInfo._1.toLong < l11)) && (l30 < l11 - placeholder[Long](59) - placeholder[Long](60))) && (func16(box29) >= l17)) && (box29.R9[Coll[Long]].get.size.toLong <= placeholder[Long](61))) {(\n val l31 = func20(box29)._1\n val bool32 = l31 != placeholder[Long](62)\n if (bool32) {(\n val coll33 = Coll[Byte]()\n val coll34 = if (coll9 == coll33) { box29.R5[Coll[Byte]].get } else {(\n val coll34 = coll10.filter({(box34: Box) => ((blake2b256(box34.propositionBytes) == coll6) && (box34.R5[Coll[Byte]].get == coll9)) && (box34.R6[Coll[Byte]].get == coll7) })\n if (coll34.size == placeholder[Int](63)) {(\n val box35 = coll34(placeholder[Int](64))\n val tuple36 = func20(box35)\n val l37 = tuple36._1\n if (tuple36._2 && (l37 != placeholder[Long](65))) {(\n val l38 = l31 * placeholder[Long](66) + l21 * l11 - l30\n val l39 = func13(box35)\n val l40 = l37 * placeholder[Long](67) + l21 * l11 - l39\n if ((l38 > l40) || ((l38 == l40) && (l30 < l39))) { box29.R5[Coll[Byte]].get } else { coll33 }\n )} else { coll33 }\n )} else { coll33 }\n )}\n if ((coll34 != coll33) && (coll34 != coll9)) {(\n val box35 = OUTPUTS(placeholder[Int](68))\n ((((((((((((((((((((((func16(box35) >= func16(SELF)) && (box35.tokens(placeholder[Int](69))._1 == coll7)) && (box35.R4[Int].get == i1)) && (i1 == placeholder[Int](70))) && (box35.R5[Coll[Byte]].get == coll18)) && (box35.R6[(Coll[Byte], Coll[Byte])].get._1 == coll19)) && (box35.R6[(Coll[Byte], Coll[Byte])].get._2 == coll34)) && (box35.R7[Coll[Coll[Byte]]].get == coll22)) && (box35.R8[Coll[Long]].get(placeholder[Int](71)) == l12)) && (box35.R8[Coll[Long]].get(placeholder[Int](72)) == l21)) && (box35.R8[Coll[Long]].get(placeholder[Int](73)) == l11)) && (box35.R8[Coll[Long]].get(placeholder[Int](74)) == l23)) && (box35.R8[Coll[Long]].get(placeholder[Int](75)) == l17)) && (box35.R8[Coll[Long]].get(placeholder[Int](76)) == l24)) && (box35.R8[Coll[Long]].get(placeholder[Int](77)) == l25)) && (box35.R8[Coll[Long]].get(placeholder[Int](78)) == l26)) && (box35.R8[Coll[Long]].get(placeholder[Int](79)) == l4)) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](80)) == coll14(placeholder[Int](81)))) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](82)) == coll15)) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](83)) == coll14(placeholder[Int](84)))) && ((box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](85)) == coll14(placeholder[Int](86))) || (l4 - placeholder[Long](87) + placeholder[Long](88) < l2))) && (box35.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](89))) && bool32\n )} else { placeholder[Boolean](90) }\n )} else { placeholder[Boolean](91) }\n )} else { placeholder[Boolean](92) }\n )} else { placeholder[Boolean](93) }\n )} else { placeholder[Boolean](94) }) || sigmaProp(func27(placeholder[Boolean](95))) || sigmaProp(func27(placeholder[Boolean](96))) || if ((l2 >= l4) && (\n OUTPUTS.size > placeholder[Int](97)\n )) {(\n val coll28 = OUTPUTS.filter({(box28: Box) => blake2b256(box28.propositionBytes) == placeholder[Coll[Byte]](98) })\n if (coll28.size == placeholder[Int](99)) {(\n val box29 = coll28(placeholder[Int](100))\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((box29.tokens(placeholder[Int](101))._1 == coll7) && (box29.R4[Int].get == i1)) && (i1 == placeholder[Int](102))) && (\n box29.R5[Coll[Byte]].get == coll18\n )\n ) && (box29.R6[(Coll[Byte], Coll[Byte])].get._1 == coll19)\n ) && (box29.R6[(Coll[Byte], Coll[Byte])].get._2 == coll9)\n ) && (box29.R7[Coll[Coll[Byte]]].get == coll22)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](103)) == l12)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](104)) == l21)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](105)) == l11)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](106)) == l23)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](107)) == l17)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](108)) == l24)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](109)) == l25)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](110)) == l26)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](111)) == l4)\n ) && (box29.R9[Coll[Coll[Byte]]].get == coll14)\n ) && (func16(box29) >= func16(SELF))\n )\n )} else { sigmaProp(placeholder[Boolean](112)) }\n )} else { sigmaProp(placeholder[Boolean](113)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "22c0d43bba229fdffe9bc9b4bcae0fcf8f0eff7ce8200b86064458f656b91de9",
"index": 0,
"amount": 1,
"name": "Dev Game [822a6c]",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 12000,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e2018e23478c54ccb0a693049db151f13e2be9e9f3622d61f63337e7059cb4099a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "18e23478c54ccb0a693049db151f13e2be9e9f3622d61f63337e7059cb4099a4"
},
"R6": {
"serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f2120f6f52ea950ee462d8710f645f8a89661c7366edec70060c3f5d6984de3065aa8",
"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,f6f52ea950ee462d8710f645f8a89661c7366edec70060c3f5d6984de3065aa8]"
},
"R8": {
"serializedValue": "11099aded10100b0ded101a09c01a01fa0d11900a08d069edfd101",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1718157,0,1718168,10000,2000,210000,0,50000,1718223]"
},
"R7": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
},
"R9": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[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,aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71,0008cd025ac8ab183ffde36068603120b00acdf141b91fe4e0c0c6d562b5f24e1e2cc2d1,0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7]"
},
"R4": {
"serializedValue": "0402",
"sigmaType": "SInt",
"renderedValue": "1"
}
}
},
{
"boxId": "f85d523f88dd4b76e044eb8d2dd33c8711b91142f2d3688870db8f0e10a0c285",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "ce64ec363f0ef55df25d41e8ac2cbaf8d3ee01a5cde7c863602945bf5b99edfb",
"outputTransactionId": "510f8b18056631469e033b70ac7a9e02201604de7833501c153a5c7f669dc485",
"outputIndex": 0,
"outputGlobalIndex": 53476805,
"outputCreatedAt": 1718166,
"outputSettledAt": 1718168,
"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: 2\n26: 90\n27: 0\n28: 3\n29: 3\n30: false\n31: false\n32: false\n33: 1\n34: 0\n35: 7\n36: 1\n37: false\n38: 1\n39: 0\n40: 7\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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{
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}
],
"additionalRegisters": {
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},
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},
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"sigmaType": "Coll[SLong]",
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},
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"sigmaType": "Coll[SByte]",
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}
},
{
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"spendingProof": "f751d05670f89a4c1d08e0b1b6888745eaa64968ad15295ca8bc045fc1d95993388862a36f249d714db4147bf0ceb00ae875c9eee9c62bfd",
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"outputGlobalIndex": 53477295,
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"outputSettledAt": 1718194,
"ergoTree": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(910cc5,459442,...)))}",
"address": "9fcwctfPQPkDfHgxBns5Uu3dwWpaoywhkpLEobLuztfQuV5mt3T",
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"amount": 4003,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
"tokenId": "ed2197ebb2b958670cb568aeed54693617a3f3718d16d1a298b8c8d337193da0",
"index": 47,
"amount": 4103,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
"tokenId": "2293d454406cc0f3b6a7c63db90fc989b4065204d4b101f8fe155d1d65c283ff",
"index": 48,
"amount": 10000,
"name": "TEST FULL WITHDRAW V3 APT",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "950e6f63aab88d72048da7d561efcb1bad568bc7a82fe3cc26ea729619cc3d9f",
"index": 49,
"amount": 7000,
"name": "Test project for 1.2 V1 APT",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "ebb40ecab7bb7d2a935024100806db04f44c62c33ae9756cf6fc4cb6b9aa2d12",
"index": 50,
"amount": 1,
"name": "🚬",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ef0199cb118810aa3b35b5b071d2f417bdc6c27e985bbd425a1f04d31a12a59b",
"index": 51,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "44f3f0b7ebb5369965908aaa586ed811f62c1688e6ae375b7af523cba0027ea6",
"index": 52,
"amount": 37,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "357d59abf7fbfb46fa73faa4f0898475b24713e2fc8311dab37d5b87dfb72392",
"index": 53,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "6236c29eb679e644342f6c606b0fc44ab1adfc782ad0f66bf57ef3002d96e236",
"index": 54,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "3c7b0b07c1f6be6f21c617db4ad45499ecd7283fe4de08dec3a7117a4663ebe0",
"index": 55,
"amount": 95000,
"name": "BeneSpace",
"decimals": 5,
"type": "EIP-004"
},
{
"tokenId": "3a37bdc6364544fc926fc3d914a4e25c91cf5bb2b9c754bc7f0f6184595b9025",
"index": 56,
"amount": 9999900,
"name": "fakeBTC",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "192a3b6a3f0fec229017d5d7caf3ca484f6f254ad857f7feffea2e82b9367eb5",
"index": 57,
"amount": 52301,
"name": "FALCON",
"decimals": 5,
"type": "EIP-004"
},
{
"tokenId": "687fd56baf59225ef3e5dbd8bd2ba240081ba1b0fd320322f434551d0a509249",
"index": 58,
"amount": 23398,
"name": "FALCON Test Project APT",
"decimals": 5,
"type": "EIP-004"
},
{
"tokenId": "322a090ccd17f3f94ff8294410bdebec87723a3a50774113219009d2ac8eadbc",
"index": 59,
"amount": 100,
"name": "TEST TIMESTAMP 17:05 APT",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "36baf7010ff975982f745494d3f441527c9c4b1f26b1729386cf6c3e058a6195",
"index": 60,
"amount": 1,
"name": "TEST V2 APT",
"decimals": 5,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "57cf8df7e178293e439084b58f77ca722ba95a61ac0f36a57899318923e1e2e3",
"value": 1000000,
"index": 0,
"outputBlockId": "906b2e9e1228148f59510a6b4bc8d0a66737bf97602407956ebe7a0222cfb42e",
"outputTransactionId": "4ce72de168cb806f63d127f0422f40d442d6abb8036dbdd9d72c48e77db58dc9",
"outputIndex": 1,
"ergoTree": "19ea061c040004000400040004000400040004000402040205000400050004000402040205000500050005000e20ceea52651b6b206381ea28a2e59f775367cef567c0c2f089dc7e09356b64ef610400040001010100040204000100d803d601c6a7070ed602e47201d603b5a5d9010363eded93c27203c2a791b1db630872037300938cb2db63087203730100018cb2db6308a773020001d1ec95aea4d901046393c272047202d807d604cbc2a7d605b2db6308a7730300d6068c720501d607b5a4d9010763edededededed93cbc27207720491b1db630872077304938cb2db6308720773050001720693e4c67207070e7202e6c67207040ee6c67207050ee6c672070801d608b5a5d9010863edededededed93cbc27208720491b1db630872087306938cb2db6308720873070001720693e4c67208070e7202e6c67208040ee6c67208050ee6c672080801d609dc0c0f720701d9010963d802d60bdb63087209d60cb1720b9591720c7308b4720b7309720c83004d0ed60ae4c6a7040eededed93b07207730ad9010b41639a8c720b018cb2db63088c720b02730b0002b07208730cd9010b41639a8c720b018cb2db63088c720b02730d0002edafb0720983000ed9010b3c1a4d0ed802d60d8c720b01d60e8c8c720b020195ae720dd9010f0e93720f720e720db3720d83010e720ed9010b0e92b0b5dc0c0f720801d9010d63d802d60fdb6308720dd610b1720f95917210730eb4720f730f721083004d0ed9010d4d0e938c720d01720b7310d9010d414d0e9a8c720d018c8c720d0202b0b57209d9010d4d0e938c720d01720b7311d9010d414d0e9a8c720d018c8c720d020292b072087312d9010b41639a8c720b01c18c720b02b072077313d9010b41639a8c720b01c18c720b02aeadb5db6501fed9010b63ed93cbc2720b73148f8cc7720b01a3d9010b638cb2db6308720b73150001d9010b0e93720b720a95e4c6a70601ae7208d9010b63edededed928cb2db6308720b731600028c72050293e4c6720b040e720a93e4c6720b050ee4c6a7050ee4c6720b060193e4c6720b090ee4c6a7090e731773189593b172037319d801d604b27203731a00ededededededed93c67204040ec6a7040e93c67204050ec6a7050e93c672040601c6a7060193c67204070e720193c672040801c6a7080193c67204090ec6a7090e93db63087204db6308a792c17204c1a7731b",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e20f6f52ea950ee462d8710f645f8a89661c7366edec70060c3f5d6984de3065aa8",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6f52ea950ee462d8710f645f8a89661c7366edec70060c3f5d6984de3065aa8"
},
"R6": {
"serializedValue": "0100",
"sigmaType": "SBoolean",
"renderedValue": "false"
},
"R8": {
"serializedValue": "0100",
"sigmaType": "SBoolean",
"renderedValue": "false"
},
"R7": {
"serializedValue": "0e240008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02910cc52aa89e392d2715fc556aea54d5d4d81ccca937a11481771d37395c39b7"
},
"R9": {
"serializedValue": "0e046e756c6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e756c6c"
},
"R4": {
"serializedValue": "0e20a6819e0b7cf99c8c7872b62f4985b8d900c6150925d01eb279787517a848b6d9",
"sigmaType": "Coll[SByte]",
"renderedValue": "a6819e0b7cf99c8c7872b62f4985b8d900c6150925d01eb279787517a848b6d9"
}
}
}
],
"outputs": [
{
"boxId": "2616efd5f00e0f12ef13949b55edc426ec554b86f24c62f9e65cfb00bb4b74c5",
"transactionId": "a5926997410ca3d39ce49dc5bd1d9569d42dfd329cba013324d7f7c999015c32",
"blockId": "c819147e113bce05c32cc6713aae97633bafe88aa0a80d52edb8a430a688c3eb",
"value": 3092960,
"index": 0,
"globalIndex": 53477436,
"creationHeight": 1718199,
"settlementHeight": 1718200,
"ergoTree": "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",
"ergoTreeConstants": "0: 8\n1: Coll(45,-126,27,3,-30,-34,114,118,-69,-21,-77,-1,65,-20,55,79,-99,110,-38,67,100,97,-111,76,1,38,-126,-49,100,95,-92,-54)\n2: 0\n3: 2\n4: 0\n5: Coll(122,-94,-75,-37,-122,16,-18,-68,-23,35,110,21,-55,109,-47,84,-91,113,115,65,96,4,98,-91,-79,-37,114,2,-73,30,-45,38)\n6: 0\n7: 0\n8: 1\n9: 1\n10: 0\n11: 4\n12: -1\n13: false\n14: true\n15: 1\n16: 3\n17: 5\n18: 6\n19: 7\n20: 0\n21: 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)\n22: 0\n23: 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)\n24: Coll(-90,-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,-39)\n25: true\n26: 0\n27: 0\n28: 1\n29: 0\n30: 0\n31: 2\n32: 1\n33: 1\n34: 0\n35: 1\n36: 0\n37: 8\n38: 30\n39: 0\n40: 1\n41: 0\n42: 1\n43: 2\n44: 3\n45: 4\n46: 5\n47: 0\n48: 6\n49: 0\n50: 7\n51: false\n52: false\n53: false\n54: 1\n55: 1\n56: 1\n57: 1\n58: 0\n59: 5\n60: 1\n61: 10\n62: -1\n63: 1\n64: 0\n65: -1\n66: 1\n67: 1\n68: 0\n69: 0\n70: 1\n71: 0\n72: 1\n73: 2\n74: 3\n75: 4\n76: 5\n77: 6\n78: 7\n79: 8\n80: 0\n81: 0\n82: 1\n83: 2\n84: 2\n85: 3\n86: 3\n87: 30\n88: 5\n89: 4\n90: false\n91: false\n92: false\n93: false\n94: false\n95: true\n96: false\n97: 0\n98: Coll(-34,-95,53,-55,103,102,9,81,53,114,-127,-84,25,-103,-109,107,-112,126,-39,-83,-33,-115,43,-82,55,114,26,-29,53,126,107,-22)\n99: 1\n100: 0\n101: 0\n102: 1\n103: 0\n104: 1\n105: 2\n106: 3\n107: 4\n108: 5\n109: 6\n110: 7\n111: 8\n112: false\n113: 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 coll10 = CONTEXT.dataInputs\n val l11 = coll3(placeholder[Int](3))\n val l12 = coll3(placeholder[Int](4))\n val func13 = {(box13: Box) =>\n val coll15 = coll10.filter({(box15: Box) =>\n val opt17 = box15.R4[Coll[Byte]]\n (opt17.isDefined && (opt17.get == box13.R7[Coll[Byte]].get)) && (blake2b256(box15.propositionBytes) == placeholder[Coll[Byte]](5))\n })\n if (coll15.size > placeholder[Int](6)) {(\n val l16 = coll15.fold(coll15(placeholder[Int](7)), {(tuple16: (Box, Box)) =>\n val box18 = tuple16._2\n val box19 = tuple16._1\n if (box18.creationInfo._1 < box19.creationInfo._1) { box18 } else { box19 }\n }).creationInfo._1.toLong\n val l17 = l12 + placeholder[Long](8)\n if (l16 < l17) { l17 } else { l16 }\n )} else { l11 }\n }\n val coll14 = SELF.R9[Coll[Coll[Byte]]].get\n val coll15 = coll14(placeholder[Int](9))\n val func16 = {(box16: Box) =>\n box16.tokens.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 == coll15 }).fold(\n placeholder[Long](10), {(tuple18: (Long, (Coll[Byte], Long))) => tuple18._1 + tuple18._2._2 }\n )\n }\n val l17 = coll3(placeholder[Int](11))\n val coll18 = SELF.R5[Coll[Byte]].get\n val coll19 = tuple8._1\n val func20 = {(box20: Box) => box20.R9[Coll[Long]].get.fold((placeholder[Long](12), placeholder[Boolean](13)), {(tuple22: ((Long, Boolean), Long)) =>\n val tuple24 = tuple22._1\n val l25 = tuple22._2\n if (tuple24._2) { tuple24 } else { if (blake2b256(box20.R7[Coll[Byte]].get.append(coll18).append(longToByteArray(l25)).append(box20.R8[Coll[Byte]].get).append(box20.R4[Coll[Byte]].get).append(coll19)) == box20.R5[Coll[Byte]].get) { (l25, placeholder[Boolean](14)) } else { tuple24 } }\n }) }\n val l21 = coll3(placeholder[Int](15))\n val coll22 = SELF.R7[Coll[Coll[Byte]]].get\n val l23 = coll3(placeholder[Int](16))\n val l24 = coll3(placeholder[Int](17))\n val l25 = coll3(placeholder[Int](18))\n val l26 = coll3(placeholder[Int](19))\n val func27 = {(bool27: Boolean) => if (bool5 && (coll10.size > placeholder[Int](20))) {(\n val coll29 = coll10.filter({(box29: Box) => (((((blake2b256(box29.propositionBytes) == placeholder[Coll[Byte]](21)) && (box29.tokens.size > placeholder[Int](22))) && (box29.R4[Coll[Byte]].get == if (bool27) { placeholder[Coll[Byte]](23) } else { placeholder[Coll[Byte]](24) })) && (box29.R5[Coll[Byte]].get == coll9)) && if (bool27) { box29.R6[Boolean].get && (!box29.R8[Boolean].get) } else { placeholder[Boolean](25) }) && coll22.exists({(coll31: Coll[Byte]) => coll31 == box29.tokens(placeholder[Int](26))._1 }) })\n val coll30 = coll29.map({(box30: Box) => box30.tokens(placeholder[Int](27))._1 })\n val i31 = coll29.size\n val i32 = coll22.size\n val coll33 = OUTPUTS.filter({(box33: Box) => box33.propositionBytes == SELF.propositionBytes })\n if ((coll30.indices.forall({(i34: Int) => !coll30.slice(i34 + placeholder[Int](28), i31).exists({(coll36: Coll[Byte]) => coll36 == coll30(i34) }) }) && (i31 >= if (i32 == placeholder[Int](29)) { placeholder[Int](30) } else { i32 / placeholder[Int](31) + placeholder[Int](32) })) && (coll33.size == placeholder[Int](33))) {(\n val box34 = coll33(placeholder[Int](34))\n val coll35 = INPUTS.filter({(box35: Box) => (blake2b256(box35.propositionBytes) == coll6) && (box35.R5[Coll[Byte]].get == coll9) })\n if ((box34.R6[(Coll[Byte], Coll[Byte])].get._2 == Coll[Byte]()) && (coll35.size == placeholder[Int](35))) { ((func16(box34) >= func16(SELF) + func16(coll35(placeholder[Int](36)))) && (box34.R8[Coll[Long]].get(placeholder[Int](37)) >= l2 + placeholder[Long](38))) && ((((((((((((((box34.tokens(placeholder[Int](39))._1 == coll7) && (box34.R4[Int].get == i1)) && (i1 == placeholder[Int](40))) && (box34.R5[Coll[Byte]].get == coll18)) && (box34.R7[Coll[Coll[Byte]]].get == coll22)) && (box34.R8[Coll[Long]].get(placeholder[Int](41)) == l12)) && (box34.R8[Coll[Long]].get(placeholder[Int](42)) == l21)) && (box34.R8[Coll[Long]].get(placeholder[Int](43)) == l11)) && (box34.R8[Coll[Long]].get(placeholder[Int](44)) == l23)) && (box34.R8[Coll[Long]].get(placeholder[Int](45)) == l17)) && (box34.R8[Coll[Long]].get(placeholder[Int](46)) == l24 + if (bool27) { l25 } else { placeholder[Long](47) })) && (box34.R8[Coll[Long]].get(placeholder[Int](48)) == if (bool27) { placeholder[Long](49) } else { l25 })) && (box34.R8[Coll[Long]].get(placeholder[Int](50)) == l26)) && (box34.R9[Coll[Coll[Byte]]].get == coll14)) } else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n )} else { placeholder[Boolean](53) } }\n sigmaProp(i1 == placeholder[Int](54)) && sigmaProp(if ((bool5 && (INPUTS.size > placeholder[Int](55))) && (OUTPUTS.size > placeholder[Int](56))) {(\n val coll28 = coll10.filter({(box28: Box) => ((blake2b256(box28.propositionBytes) == coll6) && (box28.R6[Coll[Byte]].get == coll7)) && (box28.R5[Coll[Byte]].get != coll9) })\n if (coll28.size == placeholder[Int](57)) {(\n val box29 = coll28(placeholder[Int](58))\n val l30 = func13(box29)\n if ((((((blake2b256(box29.propositionBytes) == coll6) && (box29.R6[Coll[Byte]].get == coll7)) && (box29.creationInfo._1.toLong < l11)) && (l30 < l11 - placeholder[Long](59) - placeholder[Long](60))) && (func16(box29) >= l17)) && (box29.R9[Coll[Long]].get.size.toLong <= placeholder[Long](61))) {(\n val l31 = func20(box29)._1\n val bool32 = l31 != placeholder[Long](62)\n if (bool32) {(\n val coll33 = Coll[Byte]()\n val coll34 = if (coll9 == coll33) { box29.R5[Coll[Byte]].get } else {(\n val coll34 = coll10.filter({(box34: Box) => ((blake2b256(box34.propositionBytes) == coll6) && (box34.R5[Coll[Byte]].get == coll9)) && (box34.R6[Coll[Byte]].get == coll7) })\n if (coll34.size == placeholder[Int](63)) {(\n val box35 = coll34(placeholder[Int](64))\n val tuple36 = func20(box35)\n val l37 = tuple36._1\n if (tuple36._2 && (l37 != placeholder[Long](65))) {(\n val l38 = l31 * placeholder[Long](66) + l21 * l11 - l30\n val l39 = func13(box35)\n val l40 = l37 * placeholder[Long](67) + l21 * l11 - l39\n if ((l38 > l40) || ((l38 == l40) && (l30 < l39))) { box29.R5[Coll[Byte]].get } else { coll33 }\n )} else { coll33 }\n )} else { coll33 }\n )}\n if ((coll34 != coll33) && (coll34 != coll9)) {(\n val box35 = OUTPUTS(placeholder[Int](68))\n ((((((((((((((((((((((func16(box35) >= func16(SELF)) && (box35.tokens(placeholder[Int](69))._1 == coll7)) && (box35.R4[Int].get == i1)) && (i1 == placeholder[Int](70))) && (box35.R5[Coll[Byte]].get == coll18)) && (box35.R6[(Coll[Byte], Coll[Byte])].get._1 == coll19)) && (box35.R6[(Coll[Byte], Coll[Byte])].get._2 == coll34)) && (box35.R7[Coll[Coll[Byte]]].get == coll22)) && (box35.R8[Coll[Long]].get(placeholder[Int](71)) == l12)) && (box35.R8[Coll[Long]].get(placeholder[Int](72)) == l21)) && (box35.R8[Coll[Long]].get(placeholder[Int](73)) == l11)) && (box35.R8[Coll[Long]].get(placeholder[Int](74)) == l23)) && (box35.R8[Coll[Long]].get(placeholder[Int](75)) == l17)) && (box35.R8[Coll[Long]].get(placeholder[Int](76)) == l24)) && (box35.R8[Coll[Long]].get(placeholder[Int](77)) == l25)) && (box35.R8[Coll[Long]].get(placeholder[Int](78)) == l26)) && (box35.R8[Coll[Long]].get(placeholder[Int](79)) == l4)) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](80)) == coll14(placeholder[Int](81)))) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](82)) == coll15)) && (box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](83)) == coll14(placeholder[Int](84)))) && ((box35.R9[Coll[Coll[Byte]]].get(placeholder[Int](85)) == coll14(placeholder[Int](86))) || (l4 - placeholder[Long](87) + placeholder[Long](88) < l2))) && (box35.R9[Coll[Coll[Byte]]].get.size == placeholder[Int](89))) && bool32\n )} else { placeholder[Boolean](90) }\n )} else { placeholder[Boolean](91) }\n )} else { placeholder[Boolean](92) }\n )} else { placeholder[Boolean](93) }\n )} else { placeholder[Boolean](94) }) || sigmaProp(func27(placeholder[Boolean](95))) || sigmaProp(func27(placeholder[Boolean](96))) || if ((l2 >= l4) && (\n OUTPUTS.size > placeholder[Int](97)\n )) {(\n val coll28 = OUTPUTS.filter({(box28: Box) => blake2b256(box28.propositionBytes) == placeholder[Coll[Byte]](98) })\n if (coll28.size == placeholder[Int](99)) {(\n val box29 = coll28(placeholder[Int](100))\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((box29.tokens(placeholder[Int](101))._1 == coll7) && (box29.R4[Int].get == i1)) && (i1 == placeholder[Int](102))) && (\n box29.R5[Coll[Byte]].get == coll18\n )\n ) && (box29.R6[(Coll[Byte], Coll[Byte])].get._1 == coll19)\n ) && (box29.R6[(Coll[Byte], Coll[Byte])].get._2 == coll9)\n ) && (box29.R7[Coll[Coll[Byte]]].get == coll22)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](103)) == l12)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](104)) == l21)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](105)) == l11)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](106)) == l23)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](107)) == l17)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](108)) == l24)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](109)) == l25)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](110)) == l26)\n ) && (box29.R8[Coll[Long]].get(placeholder[Int](111)) == l4)\n ) && (box29.R9[Coll[Coll[Byte]]].get == coll14)\n ) && (func16(box29) >= func16(SELF))\n )\n )} else { sigmaProp(placeholder[Boolean](112)) }\n )} else { sigmaProp(placeholder[Boolean](113)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "22c0d43bba229fdffe9bc9b4bcae0fcf8f0eff7ce8200b86064458f656b91de9",
"index": 0,
"amount": 1,
"name": "Dev Game [822a6c]",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "aa59253a0a9d75d658eec7aeda90f350675b2e1eccfeeed17e5380f619603c71",
"index": 1,
"amount": 14000,
"name": "CAT",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e2018e23478c54ccb0a693049db151f13e2be9e9f3622d61f63337e7059cb4099a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "18e23478c54ccb0a693049db151f13e2be9e9f3622d61f63337e7059cb4099a4"
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"R6": {
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"sigmaType": "(Coll[SByte], Coll[SByte])",
"renderedValue": "[35aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f21,]"
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"R8": {
"serializedValue": "11099aded10100b0ded101a09c01a01fa0d11900a08d06bedfd101",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1718157,0,1718168,10000,2000,210000,0,50000,1718239]"
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"R7": {
"serializedValue": "1a0120758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[758eb79665224492c8fb849a08751d41cd5974a7af1099e5558f5424a3821fc9]"
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