Transaction
ID: bc6d32f5d3...42cd
Inputs (5)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0988 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
1.55 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.43 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.1 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.1 ERG
Tokens:
Loading assets...
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0968 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.55 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.43 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.098 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.098 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Transaction Details
Confirmations: 470,972
Total coins transferred: 3.29 ERG
Fees: 0.01 ERG
Fees per byte: 0.000007893 ERG
Raw Transaction Data
{
"id": "bc6d32f5d342b6ef7030d1cb3a8fb3552d54d5170ee9105f25f40407e1c242cd",
"blockId": "c07c35cc89873eaafc0152ed05c4489fdfe24d8d1e0c7d104370b54dc7e69060",
"inclusionHeight": 1288879,
"timestamp": 1718671577004,
"index": 3,
"globalIndex": 7367390,
"numConfirmations": 470972,
"inputs": [
{
"boxId": "498361ec6bef6a640157069b22b0bf7dea666e6e6b881e322636a34864353010",
"value": 98800000,
"index": 0,
"spendingProof": "9139a6c56c995ea3581e960cb3f840730ae2c279b5ebaa035cedadf373bef5cb6b1b5bbb66a80741ea9e50928cc10ff6428aa469e042b3d1",
"outputBlockId": "ada3d5277e8b018f496a7ec2201eab0313232e31538a6e0d1e9db4fe6ca07155",
"outputTransactionId": "b6625b5fc264302801ce6f4f0a155edee502e4f4b0d9acee652d08dba6833607",
"outputIndex": 2,
"outputGlobalIndex": 40869425,
"outputCreatedAt": 1288260,
"outputSettledAt": 1288267,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 2\n2: 0\n3: 1\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 1\n10: 2\n11: 0\n12: 0\n13: 0\n14: 4\n15: 0\n16: 0\n17: 3\n18: -1\n19: -1\n20: -1\n21: 1\n22: 0\n23: 1\n24: 0\n25: 2\n26: 0\n27: 1\n28: 0\n29: CBigInt(1000)\n30: 1\n31: CBigInt(1000)\n32: -1\n33: -1\n34: 0\n35: 2\n36: CBigInt(0)\n37: true\n38: 1\n39: 0\n40: 1\n41: 2\n42: 1\n43: true\n44: false\n45: 0\n46: Coll(-94,81,-67,-108,126,35,-68,-50,-11,47,-73,-50,-51,61,99,-57,-22,32,-78,105,89,-82,-117,-105,-18,-21,-67,-109,56,-100,125,74)",
"ergoTreeScript": "{\n val opt1 = SELF.R4[Coll[Byte]]\n val coll2 = opt1.get\n val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](0)))\n val opt4 = SELF.R5[Coll[Long]]\n val opt5 = SELF.R6[Coll[Long]]\n val opt6 = SELF.R7[Coll[Byte]]\n val coll7 = SELF.R8[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1))\n val l9 = coll7(placeholder[Int](2))\n val l10 = coll7(placeholder[Int](3))\n val l11 = CONTEXT.preHeader.timestamp\n val coll12 = opt4.get\n val coll13 = SELF.tokens\n val box14 = CONTEXT.dataInputs(placeholder[Int](4))\n val l15 = box14.R6[Long].get\n val l16 = SELF.value\n val coll17 = Coll[Byte]()\n val coll18 = opt6.get\n val tuple19 = coll13.getOrElse(placeholder[Int](5), (coll17, l16))\n val coll20 = tuple19._1\n val i21 = coll20.size\n val bool22 = i21 == placeholder[Int](6)\n val box23 = INPUTS(placeholder[Int](7))\n val coll24 = box23.id\n val coll25 = SELF.id\n val bool26 = coll24 == coll25\n val i27 = placeholder[Int](8)\n val i28 = placeholder[Int](9)\n val i29 = if (bool26) { i27 } else { i28 }\n val i30 = i29 + placeholder[Int](10)\n val box31 = OUTPUTS.getOrElse(i30, SELF)\n val tuple32 = \n val l32 = box31.value\n val tuple33 = (coll17, l32)\n tuple33\n \n val tuple33 = \n val coll33 = box31.tokens\n val tuple34 = (coll20, placeholder[Long](11))\n val tuple35 = coll33.getOrElse(placeholder[Int](12), tuple34)\n tuple35\n \n val tuple34 = if (bool22) { tuple32 } else { tuple33 }\n val l35 = tuple34._2\n val coll36 = opt5.get\n val l37 = coll36(placeholder[Int](13))\n val i38 = i29 + placeholder[Int](14)\n val box39 = OUTPUTS.getOrElse(i38, SELF)\n val tuple40 = \n val l40 = box39.value\n val tuple41 = (coll17, l40)\n tuple41\n \n val tuple41 = \n val coll41 = box39.tokens\n val tuple42 = (coll20, placeholder[Long](15))\n val tuple43 = coll41.getOrElse(placeholder[Int](16), tuple42)\n tuple43\n \n val tuple42 = if (bool22) { tuple40 } else { tuple41 }\n val l43 = tuple42._2\n val tuple44 = box14.R7[(Coll[Byte], Coll[Byte])].get\n val coll45 = box14.R4[Coll[Int]].get\n val coll46 = tuple42._1\n proveDlog(decodePoint(coll2.slice(placeholder[Int](17), coll2.size))) && sigmaProp(\n ((((box3.R4[Coll[Byte]] == opt1) && (box3.R5[Coll[Long]] == opt4)) && (box3.R6[Coll[Long]] == opt5)) && (box3.R7[Coll[Byte]] == opt6)) && (\n box3.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](18), placeholder[Long](19), placeholder[Long](20))) == Coll[Long](\n l9, l10, l8 + placeholder[Long](21)\n )\n )\n ) || sigmaProp(if (l11 > coll12(placeholder[Int](22))) { if (l11 > coll12(placeholder[Int](23))) {(\n val box47 = OUTPUTS(placeholder[Int](24))\n allOf(Coll[Boolean](box47.tokens == coll13, box47.value >= l16 - placeholder[Long](25) * l15, box47.propositionBytes == coll2))\n )} else {(\n val box47 = box23\n val coll48 = coll24\n val coll49 = coll25\n val bool50 = bool26\n val i51 = i27\n val i52 = i28\n val i53 = i29\n val box54 = OUTPUTS.getOrElse(i53, SELF)\n val tuple55 = box54.tokens.getOrElse(placeholder[Int](26), (coll17, box54.value))\n val l56 = tuple55._2\n val coll57 = coll20\n val i58 = i21\n val bool59 = bool22\n val i60 = i30\n val box61 = box31\n val tuple62 = tuple32\n val tuple63 = tuple33\n val tuple64 = tuple34\n val l65 = tuple19._2\n val bi66 = coll36(placeholder[Int](27)) - l10.toBigInt\n val bi67 = bi66 * l56.toBigInt / l37 - l9.toBigInt\n val bi68 = if (bi67 > bi66) { bi66 } else { bi67 }\n val bi69 = if (coll18 == tuple44._2) { bi68 * coll45(placeholder[Int](28)).toBigInt / placeholder[BigInt](29) } else { bi68 * coll45(placeholder[Int](30)).toBigInt / placeholder[BigInt](31) }\n val i70 = i38\n val box71 = box39\n val tuple72 = tuple40\n val tuple73 = tuple41\n val tuple74 = tuple42\n val coll75 = box61.propositionBytes\n val l76 = l9 + l56\n val coll77 = box61.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](32), placeholder[Long](33)))\n allOf(Coll[Boolean](((((((l56 > placeholder[Long](34)) && (tuple55._1 == coll18)) && (if (bool59) {(\n val l78 = l35\n l65 - l78 - l15 * placeholder[Long](35)\n )} else { l65 - l35 }.toBigInt <= bi68 + l43.toBigInt)) && (box54.propositionBytes == coll2)) && (if (bi69 > placeholder[BigInt](36)) { if (bool59) {(\n val coll78 = coll46\n val l79 = l43\n ((coll78 == coll57) && (l79.toBigInt >= bi69)) && (l79.toBigInt <= bi69 + l15.toBigInt)\n )} else { (coll46 == coll57) && (l43.toBigInt == bi69) } } else { placeholder[Boolean](37) } && (box71.propositionBytes == box14.R5[Coll[Byte]].get))) && (INPUTS(i53).id == coll49)) && (box47.propositionBytes == INPUTS(placeholder[Int](38)).propositionBytes), ((((((((coll75 == if (l76 >= l37) { coll2 } else { SELF.propositionBytes }) && (box61.R4[Coll[Byte]].get == coll2)) && (box61.R5[Coll[Long]].get == coll12)) && (box61.R6[Coll[Long]].get == coll36)) && (box61.R7[Coll[Byte]].get == coll18)) && (coll77(placeholder[Int](39)) == l76)) && (coll77(placeholder[Int](40)).toBigInt == l10.toBigInt + bi68)) && (coll77(placeholder[Int](41)) == l8 + placeholder[Long](42))) && if (coll75 == coll2) { placeholder[Boolean](43) } else { tuple64._1 == coll57 }))\n )} } else { placeholder[Boolean](44) }) && sigmaProp(\n (box14.tokens(placeholder[Int](45))._1 == placeholder[Coll[Byte]](46)) && (((coll18, coll20) == tuple44) || ((coll20, coll18) == tuple44))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 0,
"amount": 606,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1102008080d0d88bdea2e302",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,100000000000000000]"
},
"R6": {
"serializedValue": "110280b6f7f302d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[390000000,1000]"
},
"R8": {
"serializedValue": "110380fce29401a00602",
"sigmaType": "Coll[SLong]",
"renderedValue": "[156000000,400,1]"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331"
}
}
},
{
"boxId": "903c5d2a0c639e8d693b28dd7db81645f0941901c1aae837e4b177703a97ac8b",
"value": 1554400000,
"index": 1,
"spendingProof": "b244667904bbd37f9f6354a61d6df3652b9270581b42f68f33681a4002c8ec64d094c4acbc83e546f7fd4d4e225be54b99981ca78a8d8444",
"outputBlockId": "ada3d5277e8b018f496a7ec2201eab0313232e31538a6e0d1e9db4fe6ca07155",
"outputTransactionId": "6ea831db4ca9bf542593c5900d5adf0b47667222a987fe2fe9248968013e68ad",
"outputIndex": 0,
"outputGlobalIndex": 40869417,
"outputCreatedAt": 1288258,
"outputSettledAt": 1288267,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 2\n2: 0\n3: 1\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 1\n10: 2\n11: 0\n12: 0\n13: 0\n14: 4\n15: 0\n16: 0\n17: 3\n18: -1\n19: -1\n20: -1\n21: 1\n22: 0\n23: 1\n24: 0\n25: 2\n26: 0\n27: 1\n28: 0\n29: CBigInt(1000)\n30: 1\n31: CBigInt(1000)\n32: -1\n33: -1\n34: 0\n35: 2\n36: CBigInt(0)\n37: true\n38: 1\n39: 0\n40: 1\n41: 2\n42: 1\n43: true\n44: false\n45: 0\n46: Coll(-94,81,-67,-108,126,35,-68,-50,-11,47,-73,-50,-51,61,99,-57,-22,32,-78,105,89,-82,-117,-105,-18,-21,-67,-109,56,-100,125,74)",
"ergoTreeScript": "{\n val opt1 = SELF.R4[Coll[Byte]]\n val coll2 = opt1.get\n val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](0)))\n val opt4 = SELF.R5[Coll[Long]]\n val opt5 = SELF.R6[Coll[Long]]\n val opt6 = SELF.R7[Coll[Byte]]\n val coll7 = SELF.R8[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1))\n val l9 = coll7(placeholder[Int](2))\n val l10 = coll7(placeholder[Int](3))\n val l11 = CONTEXT.preHeader.timestamp\n val coll12 = opt4.get\n val coll13 = SELF.tokens\n val box14 = CONTEXT.dataInputs(placeholder[Int](4))\n val l15 = box14.R6[Long].get\n val l16 = SELF.value\n val coll17 = Coll[Byte]()\n val coll18 = opt6.get\n val tuple19 = coll13.getOrElse(placeholder[Int](5), (coll17, l16))\n val coll20 = tuple19._1\n val i21 = coll20.size\n val bool22 = i21 == placeholder[Int](6)\n val box23 = INPUTS(placeholder[Int](7))\n val coll24 = box23.id\n val coll25 = SELF.id\n val bool26 = coll24 == coll25\n val i27 = placeholder[Int](8)\n val i28 = placeholder[Int](9)\n val i29 = if (bool26) { i27 } else { i28 }\n val i30 = i29 + placeholder[Int](10)\n val box31 = OUTPUTS.getOrElse(i30, SELF)\n val tuple32 = \n val l32 = box31.value\n val tuple33 = (coll17, l32)\n tuple33\n \n val tuple33 = \n val coll33 = box31.tokens\n val tuple34 = (coll20, placeholder[Long](11))\n val tuple35 = coll33.getOrElse(placeholder[Int](12), tuple34)\n tuple35\n \n val tuple34 = if (bool22) { tuple32 } else { tuple33 }\n val l35 = tuple34._2\n val coll36 = opt5.get\n val l37 = coll36(placeholder[Int](13))\n val i38 = i29 + placeholder[Int](14)\n val box39 = OUTPUTS.getOrElse(i38, SELF)\n val tuple40 = \n val l40 = box39.value\n val tuple41 = (coll17, l40)\n tuple41\n \n val tuple41 = \n val coll41 = box39.tokens\n val tuple42 = (coll20, placeholder[Long](15))\n val tuple43 = coll41.getOrElse(placeholder[Int](16), tuple42)\n tuple43\n \n val tuple42 = if (bool22) { tuple40 } else { tuple41 }\n val l43 = tuple42._2\n val tuple44 = box14.R7[(Coll[Byte], Coll[Byte])].get\n val coll45 = box14.R4[Coll[Int]].get\n val coll46 = tuple42._1\n proveDlog(decodePoint(coll2.slice(placeholder[Int](17), coll2.size))) && sigmaProp(\n ((((box3.R4[Coll[Byte]] == opt1) && (box3.R5[Coll[Long]] == opt4)) && (box3.R6[Coll[Long]] == opt5)) && (box3.R7[Coll[Byte]] == opt6)) && (\n box3.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](18), placeholder[Long](19), placeholder[Long](20))) == Coll[Long](\n l9, l10, l8 + placeholder[Long](21)\n )\n )\n ) || sigmaProp(if (l11 > coll12(placeholder[Int](22))) { if (l11 > coll12(placeholder[Int](23))) {(\n val box47 = OUTPUTS(placeholder[Int](24))\n allOf(Coll[Boolean](box47.tokens == coll13, box47.value >= l16 - placeholder[Long](25) * l15, box47.propositionBytes == coll2))\n )} else {(\n val box47 = box23\n val coll48 = coll24\n val coll49 = coll25\n val bool50 = bool26\n val i51 = i27\n val i52 = i28\n val i53 = i29\n val box54 = OUTPUTS.getOrElse(i53, SELF)\n val tuple55 = box54.tokens.getOrElse(placeholder[Int](26), (coll17, box54.value))\n val l56 = tuple55._2\n val coll57 = coll20\n val i58 = i21\n val bool59 = bool22\n val i60 = i30\n val box61 = box31\n val tuple62 = tuple32\n val tuple63 = tuple33\n val tuple64 = tuple34\n val l65 = tuple19._2\n val bi66 = coll36(placeholder[Int](27)) - l10.toBigInt\n val bi67 = bi66 * l56.toBigInt / l37 - l9.toBigInt\n val bi68 = if (bi67 > bi66) { bi66 } else { bi67 }\n val bi69 = if (coll18 == tuple44._2) { bi68 * coll45(placeholder[Int](28)).toBigInt / placeholder[BigInt](29) } else { bi68 * coll45(placeholder[Int](30)).toBigInt / placeholder[BigInt](31) }\n val i70 = i38\n val box71 = box39\n val tuple72 = tuple40\n val tuple73 = tuple41\n val tuple74 = tuple42\n val coll75 = box61.propositionBytes\n val l76 = l9 + l56\n val coll77 = box61.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](32), placeholder[Long](33)))\n allOf(Coll[Boolean](((((((l56 > placeholder[Long](34)) && (tuple55._1 == coll18)) && (if (bool59) {(\n val l78 = l35\n l65 - l78 - l15 * placeholder[Long](35)\n )} else { l65 - l35 }.toBigInt <= bi68 + l43.toBigInt)) && (box54.propositionBytes == coll2)) && (if (bi69 > placeholder[BigInt](36)) { if (bool59) {(\n val coll78 = coll46\n val l79 = l43\n ((coll78 == coll57) && (l79.toBigInt >= bi69)) && (l79.toBigInt <= bi69 + l15.toBigInt)\n )} else { (coll46 == coll57) && (l43.toBigInt == bi69) } } else { placeholder[Boolean](37) } && (box71.propositionBytes == box14.R5[Coll[Byte]].get))) && (INPUTS(i53).id == coll49)) && (box47.propositionBytes == INPUTS(placeholder[Int](38)).propositionBytes), ((((((((coll75 == if (l76 >= l37) { coll2 } else { SELF.propositionBytes }) && (box61.R4[Coll[Byte]].get == coll2)) && (box61.R5[Coll[Long]].get == coll12)) && (box61.R6[Coll[Long]].get == coll36)) && (box61.R7[Coll[Byte]].get == coll18)) && (coll77(placeholder[Int](39)) == l76)) && (coll77(placeholder[Int](40)).toBigInt == l10.toBigInt + bi68)) && (coll77(placeholder[Int](41)) == l8 + placeholder[Long](42))) && if (coll75 == coll2) { placeholder[Boolean](43) } else { tuple64._1 == coll57 }))\n )} } else { placeholder[Boolean](44) }) && sigmaProp(\n (box14.tokens(placeholder[Int](45))._1 == placeholder[Coll[Byte]](46)) && (((coll18, coll20) == tuple44) || ((coll20, coll18) == tuple44))\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "1102008080d0d88bdea2e302",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,100000000000000000]"
},
"R6": {
"serializedValue": "1102c03e80a0a5dd0a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[4000,1440000000]"
},
"R8": {
"serializedValue": "1103000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,0]"
},
"R7": {
"serializedValue": "0e20003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0"
},
"R4": {
"serializedValue": "0e240008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331"
}
}
},
{
"boxId": "3b99909184ce10187f55f364a9273cd8505cea3efe9a2944ae76efcb3223d607",
"value": 1433200000,
"index": 2,
"spendingProof": "dc88432e252bcea8b49e8c17f35b2cf67eba8c0a89147577e3151b974f23ca8c7a4faede4cab245d9119389a9f901dbf9e018c76eefd6dc9",
"outputBlockId": "ada3d5277e8b018f496a7ec2201eab0313232e31538a6e0d1e9db4fe6ca07155",
"outputTransactionId": "caa8d47de208b548c35f29ab5ffac698feff5840b35b422e6f9ed109eec86501",
"outputIndex": 0,
"outputGlobalIndex": 40869414,
"outputCreatedAt": 1288257,
"outputSettledAt": 1288267,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 2\n2: 0\n3: 1\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 1\n10: 2\n11: 0\n12: 0\n13: 0\n14: 4\n15: 0\n16: 0\n17: 3\n18: -1\n19: -1\n20: -1\n21: 1\n22: 0\n23: 1\n24: 0\n25: 2\n26: 0\n27: 1\n28: 0\n29: CBigInt(1000)\n30: 1\n31: CBigInt(1000)\n32: -1\n33: -1\n34: 0\n35: 2\n36: CBigInt(0)\n37: true\n38: 1\n39: 0\n40: 1\n41: 2\n42: 1\n43: true\n44: false\n45: 0\n46: Coll(-94,81,-67,-108,126,35,-68,-50,-11,47,-73,-50,-51,61,99,-57,-22,32,-78,105,89,-82,-117,-105,-18,-21,-67,-109,56,-100,125,74)",
"ergoTreeScript": "{\n val opt1 = SELF.R4[Coll[Byte]]\n val coll2 = opt1.get\n val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](0)))\n val opt4 = SELF.R5[Coll[Long]]\n val opt5 = SELF.R6[Coll[Long]]\n val opt6 = SELF.R7[Coll[Byte]]\n val coll7 = SELF.R8[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1))\n val l9 = coll7(placeholder[Int](2))\n val l10 = coll7(placeholder[Int](3))\n val l11 = CONTEXT.preHeader.timestamp\n val coll12 = opt4.get\n val coll13 = SELF.tokens\n val box14 = CONTEXT.dataInputs(placeholder[Int](4))\n val l15 = box14.R6[Long].get\n val l16 = SELF.value\n val coll17 = Coll[Byte]()\n val coll18 = opt6.get\n val tuple19 = coll13.getOrElse(placeholder[Int](5), (coll17, l16))\n val coll20 = tuple19._1\n val i21 = coll20.size\n val bool22 = i21 == placeholder[Int](6)\n val box23 = INPUTS(placeholder[Int](7))\n val coll24 = box23.id\n val coll25 = SELF.id\n val bool26 = coll24 == coll25\n val i27 = placeholder[Int](8)\n val i28 = placeholder[Int](9)\n val i29 = if (bool26) { i27 } else { i28 }\n val i30 = i29 + placeholder[Int](10)\n val box31 = OUTPUTS.getOrElse(i30, SELF)\n val tuple32 = \n val l32 = box31.value\n val tuple33 = (coll17, l32)\n tuple33\n \n val tuple33 = \n val coll33 = box31.tokens\n val tuple34 = (coll20, placeholder[Long](11))\n val tuple35 = coll33.getOrElse(placeholder[Int](12), tuple34)\n tuple35\n \n val tuple34 = if (bool22) { tuple32 } else { tuple33 }\n val l35 = tuple34._2\n val coll36 = opt5.get\n val l37 = coll36(placeholder[Int](13))\n val i38 = i29 + placeholder[Int](14)\n val box39 = OUTPUTS.getOrElse(i38, SELF)\n val tuple40 = \n val l40 = box39.value\n val tuple41 = (coll17, l40)\n tuple41\n \n val tuple41 = \n val coll41 = box39.tokens\n val tuple42 = (coll20, placeholder[Long](15))\n val tuple43 = coll41.getOrElse(placeholder[Int](16), tuple42)\n tuple43\n \n val tuple42 = if (bool22) { tuple40 } else { tuple41 }\n val l43 = tuple42._2\n val tuple44 = box14.R7[(Coll[Byte], Coll[Byte])].get\n val coll45 = box14.R4[Coll[Int]].get\n val coll46 = tuple42._1\n proveDlog(decodePoint(coll2.slice(placeholder[Int](17), coll2.size))) && sigmaProp(\n ((((box3.R4[Coll[Byte]] == opt1) && (box3.R5[Coll[Long]] == opt4)) && (box3.R6[Coll[Long]] == opt5)) && (box3.R7[Coll[Byte]] == opt6)) && (\n box3.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](18), placeholder[Long](19), placeholder[Long](20))) == Coll[Long](\n l9, l10, l8 + placeholder[Long](21)\n )\n )\n ) || sigmaProp(if (l11 > coll12(placeholder[Int](22))) { if (l11 > coll12(placeholder[Int](23))) {(\n val box47 = OUTPUTS(placeholder[Int](24))\n allOf(Coll[Boolean](box47.tokens == coll13, box47.value >= l16 - placeholder[Long](25) * l15, box47.propositionBytes == coll2))\n )} else {(\n val box47 = box23\n val coll48 = coll24\n val coll49 = coll25\n val bool50 = bool26\n val i51 = i27\n val i52 = i28\n val i53 = i29\n val box54 = OUTPUTS.getOrElse(i53, SELF)\n val tuple55 = box54.tokens.getOrElse(placeholder[Int](26), (coll17, box54.value))\n val l56 = tuple55._2\n val coll57 = coll20\n val i58 = i21\n val bool59 = bool22\n val i60 = i30\n val box61 = box31\n val tuple62 = tuple32\n val tuple63 = tuple33\n val tuple64 = tuple34\n val l65 = tuple19._2\n val bi66 = coll36(placeholder[Int](27)) - l10.toBigInt\n val bi67 = bi66 * l56.toBigInt / l37 - l9.toBigInt\n val bi68 = if (bi67 > bi66) { bi66 } else { bi67 }\n val bi69 = if (coll18 == tuple44._2) { bi68 * coll45(placeholder[Int](28)).toBigInt / placeholder[BigInt](29) } else { bi68 * coll45(placeholder[Int](30)).toBigInt / placeholder[BigInt](31) }\n val i70 = i38\n val box71 = box39\n val tuple72 = tuple40\n val tuple73 = tuple41\n val tuple74 = tuple42\n val coll75 = box61.propositionBytes\n val l76 = l9 + l56\n val coll77 = box61.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](32), placeholder[Long](33)))\n allOf(Coll[Boolean](((((((l56 > placeholder[Long](34)) && (tuple55._1 == coll18)) && (if (bool59) {(\n val l78 = l35\n l65 - l78 - l15 * placeholder[Long](35)\n )} else { l65 - l35 }.toBigInt <= bi68 + l43.toBigInt)) && (box54.propositionBytes == coll2)) && (if (bi69 > placeholder[BigInt](36)) { if (bool59) {(\n val coll78 = coll46\n val l79 = l43\n ((coll78 == coll57) && (l79.toBigInt >= bi69)) && (l79.toBigInt <= bi69 + l15.toBigInt)\n )} else { (coll46 == coll57) && (l43.toBigInt == bi69) } } else { placeholder[Boolean](37) } && (box71.propositionBytes == box14.R5[Coll[Byte]].get))) && (INPUTS(i53).id == coll49)) && (box47.propositionBytes == INPUTS(placeholder[Int](38)).propositionBytes), ((((((((coll75 == if (l76 >= l37) { coll2 } else { SELF.propositionBytes }) && (box61.R4[Coll[Byte]].get == coll2)) && (box61.R5[Coll[Long]].get == coll12)) && (box61.R6[Coll[Long]].get == coll36)) && (box61.R7[Coll[Byte]].get == coll18)) && (coll77(placeholder[Int](39)) == l76)) && (coll77(placeholder[Int](40)).toBigInt == l10.toBigInt + bi68)) && (coll77(placeholder[Int](41)) == l8 + placeholder[Long](42))) && if (coll75 == coll2) { placeholder[Boolean](43) } else { tuple64._1 == coll57 }))\n )} } else { placeholder[Boolean](44) }) && sigmaProp(\n (box14.tokens(placeholder[Int](45))._1 == placeholder[Coll[Byte]](46)) && (((coll18, coll20) == tuple44) || ((coll20, coll18) == tuple44))\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "1102008080d0d88bdea2e302",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,100000000000000000]"
},
"R6": {
"serializedValue": "1102c03e80e8ecea09",
"sigmaType": "Coll[SLong]",
"renderedValue": "[4000,1320000000]"
},
"R8": {
"serializedValue": "1103000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,0]"
},
"R7": {
"serializedValue": "0e20003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0"
},
"R4": {
"serializedValue": "0e240008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331"
}
}
},
{
"boxId": "1082c65a3515ba9a485a6968bbae15312f8eff4631c37013bd538cf42a8429d7",
"value": 100000000,
"index": 3,
"spendingProof": "d52594bc3a960cbeca4a21cccc975925f974488c9e0df0ed014a94400ccc51b7897ca4ff8287a341b654a7627603a4069f0ca49212b28517",
"outputBlockId": "aa96f35029a48139b754c5e15583c39ef636e006329f8cb84073582d35a410de",
"outputTransactionId": "3999c145a2d5832221ba33089ecee404aa565d571d1dc61a55c0e43ced0c1ec6",
"outputIndex": 0,
"outputGlobalIndex": 40869408,
"outputCreatedAt": 1288256,
"outputSettledAt": 1288266,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 2\n2: 0\n3: 1\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 1\n10: 2\n11: 0\n12: 0\n13: 0\n14: 4\n15: 0\n16: 0\n17: 3\n18: -1\n19: -1\n20: -1\n21: 1\n22: 0\n23: 1\n24: 0\n25: 2\n26: 0\n27: 1\n28: 0\n29: CBigInt(1000)\n30: 1\n31: CBigInt(1000)\n32: -1\n33: -1\n34: 0\n35: 2\n36: CBigInt(0)\n37: true\n38: 1\n39: 0\n40: 1\n41: 2\n42: 1\n43: true\n44: false\n45: 0\n46: Coll(-94,81,-67,-108,126,35,-68,-50,-11,47,-73,-50,-51,61,99,-57,-22,32,-78,105,89,-82,-117,-105,-18,-21,-67,-109,56,-100,125,74)",
"ergoTreeScript": "{\n val opt1 = SELF.R4[Coll[Byte]]\n val coll2 = opt1.get\n val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](0)))\n val opt4 = SELF.R5[Coll[Long]]\n val opt5 = SELF.R6[Coll[Long]]\n val opt6 = SELF.R7[Coll[Byte]]\n val coll7 = SELF.R8[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1))\n val l9 = coll7(placeholder[Int](2))\n val l10 = coll7(placeholder[Int](3))\n val l11 = CONTEXT.preHeader.timestamp\n val coll12 = opt4.get\n val coll13 = SELF.tokens\n val box14 = CONTEXT.dataInputs(placeholder[Int](4))\n val l15 = box14.R6[Long].get\n val l16 = SELF.value\n val coll17 = Coll[Byte]()\n val coll18 = opt6.get\n val tuple19 = coll13.getOrElse(placeholder[Int](5), (coll17, l16))\n val coll20 = tuple19._1\n val i21 = coll20.size\n val bool22 = i21 == placeholder[Int](6)\n val box23 = INPUTS(placeholder[Int](7))\n val coll24 = box23.id\n val coll25 = SELF.id\n val bool26 = coll24 == coll25\n val i27 = placeholder[Int](8)\n val i28 = placeholder[Int](9)\n val i29 = if (bool26) { i27 } else { i28 }\n val i30 = i29 + placeholder[Int](10)\n val box31 = OUTPUTS.getOrElse(i30, SELF)\n val tuple32 = \n val l32 = box31.value\n val tuple33 = (coll17, l32)\n tuple33\n \n val tuple33 = \n val coll33 = box31.tokens\n val tuple34 = (coll20, placeholder[Long](11))\n val tuple35 = coll33.getOrElse(placeholder[Int](12), tuple34)\n tuple35\n \n val tuple34 = if (bool22) { tuple32 } else { tuple33 }\n val l35 = tuple34._2\n val coll36 = opt5.get\n val l37 = coll36(placeholder[Int](13))\n val i38 = i29 + placeholder[Int](14)\n val box39 = OUTPUTS.getOrElse(i38, SELF)\n val tuple40 = \n val l40 = box39.value\n val tuple41 = (coll17, l40)\n tuple41\n \n val tuple41 = \n val coll41 = box39.tokens\n val tuple42 = (coll20, placeholder[Long](15))\n val tuple43 = coll41.getOrElse(placeholder[Int](16), tuple42)\n tuple43\n \n val tuple42 = if (bool22) { tuple40 } else { tuple41 }\n val l43 = tuple42._2\n val tuple44 = box14.R7[(Coll[Byte], Coll[Byte])].get\n val coll45 = box14.R4[Coll[Int]].get\n val coll46 = tuple42._1\n proveDlog(decodePoint(coll2.slice(placeholder[Int](17), coll2.size))) && sigmaProp(\n ((((box3.R4[Coll[Byte]] == opt1) && (box3.R5[Coll[Long]] == opt4)) && (box3.R6[Coll[Long]] == opt5)) && (box3.R7[Coll[Byte]] == opt6)) && (\n box3.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](18), placeholder[Long](19), placeholder[Long](20))) == Coll[Long](\n l9, l10, l8 + placeholder[Long](21)\n )\n )\n ) || sigmaProp(if (l11 > coll12(placeholder[Int](22))) { if (l11 > coll12(placeholder[Int](23))) {(\n val box47 = OUTPUTS(placeholder[Int](24))\n allOf(Coll[Boolean](box47.tokens == coll13, box47.value >= l16 - placeholder[Long](25) * l15, box47.propositionBytes == coll2))\n )} else {(\n val box47 = box23\n val coll48 = coll24\n val coll49 = coll25\n val bool50 = bool26\n val i51 = i27\n val i52 = i28\n val i53 = i29\n val box54 = OUTPUTS.getOrElse(i53, SELF)\n val tuple55 = box54.tokens.getOrElse(placeholder[Int](26), (coll17, box54.value))\n val l56 = tuple55._2\n val coll57 = coll20\n val i58 = i21\n val bool59 = bool22\n val i60 = i30\n val box61 = box31\n val tuple62 = tuple32\n val tuple63 = tuple33\n val tuple64 = tuple34\n val l65 = tuple19._2\n val bi66 = coll36(placeholder[Int](27)) - l10.toBigInt\n val bi67 = bi66 * l56.toBigInt / l37 - l9.toBigInt\n val bi68 = if (bi67 > bi66) { bi66 } else { bi67 }\n val bi69 = if (coll18 == tuple44._2) { bi68 * coll45(placeholder[Int](28)).toBigInt / placeholder[BigInt](29) } else { bi68 * coll45(placeholder[Int](30)).toBigInt / placeholder[BigInt](31) }\n val i70 = i38\n val box71 = box39\n val tuple72 = tuple40\n val tuple73 = tuple41\n val tuple74 = tuple42\n val coll75 = box61.propositionBytes\n val l76 = l9 + l56\n val coll77 = box61.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](32), placeholder[Long](33)))\n allOf(Coll[Boolean](((((((l56 > placeholder[Long](34)) && (tuple55._1 == coll18)) && (if (bool59) {(\n val l78 = l35\n l65 - l78 - l15 * placeholder[Long](35)\n )} else { l65 - l35 }.toBigInt <= bi68 + l43.toBigInt)) && (box54.propositionBytes == coll2)) && (if (bi69 > placeholder[BigInt](36)) { if (bool59) {(\n val coll78 = coll46\n val l79 = l43\n ((coll78 == coll57) && (l79.toBigInt >= bi69)) && (l79.toBigInt <= bi69 + l15.toBigInt)\n )} else { (coll46 == coll57) && (l43.toBigInt == bi69) } } else { placeholder[Boolean](37) } && (box71.propositionBytes == box14.R5[Coll[Byte]].get))) && (INPUTS(i53).id == coll49)) && (box47.propositionBytes == INPUTS(placeholder[Int](38)).propositionBytes), ((((((((coll75 == if (l76 >= l37) { coll2 } else { SELF.propositionBytes }) && (box61.R4[Coll[Byte]].get == coll2)) && (box61.R5[Coll[Long]].get == coll12)) && (box61.R6[Coll[Long]].get == coll36)) && (box61.R7[Coll[Byte]].get == coll18)) && (coll77(placeholder[Int](39)) == l76)) && (coll77(placeholder[Int](40)).toBigInt == l10.toBigInt + bi68)) && (coll77(placeholder[Int](41)) == l8 + placeholder[Long](42))) && if (coll75 == coll2) { placeholder[Boolean](43) } else { tuple64._1 == coll57 }))\n )} } else { placeholder[Boolean](44) }) && sigmaProp(\n (box14.tokens(placeholder[Int](45))._1 == placeholder[Coll[Byte]](46)) && (((coll18, coll20) == tuple44) || ((coll20, coll18) == tuple44))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 0,
"amount": 4040,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1102008080d0d88bdea2e302",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,100000000000000000]"
},
"R6": {
"serializedValue": "110280a8839c0cc03e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1640000000,4000]"
},
"R8": {
"serializedValue": "1103000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,0]"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331"
}
}
},
{
"boxId": "df8d7a8564236f2cb6995007beedc3ec74952f10f7a604be376823397b97e378",
"value": 100000000,
"index": 4,
"spendingProof": "c0d213a13ac12eedc9331648037af9c6425e6fd0061f6ce13e5043c15408e03a517ed2749d56a49cfee5176e08f094cab0e07c70a19568cf",
"outputBlockId": "87a06f6f2305f5a2d0d68b398092f43da51e70e0e676373edd5bf76ab4233615",
"outputTransactionId": "e00a153e991e61871f62d5997209f09816a84f957d08f4fd38121389bf54d4d8",
"outputIndex": 0,
"outputGlobalIndex": 40869402,
"outputCreatedAt": 1288255,
"outputSettledAt": 1288265,
"ergoTree": "102f04000404040004020400040004000400040004020404050004000400040805000400040605010501050105020400040204000504040004020400060203e80402060203e805010501050005040601000101040204000402040405020101010004000e20a251bd947e23bccef52fb7cecd3d63c7ea20b26959ae8b97eeebbd93389c7d4ad82ed601c6a7040ed602e47201d603b2a5dc0c1aa402a7730000d604c6a70511d605c6a70611d606c6a7070ed607e4c6a70811d608b27207730100d609b27207730200d60ab27207730300d60bdb6903db6503fed60ce47204d60ddb6308a7d60eb2db6501fe730400d60fe4c6720e0605d610c1a7d611830002d612e47206d613b2720d730501860272117210d6148c721301d615b17214d6169372157306d617b2a4730700d618c57217d619c5a7d61a9372187219d61b7308d61c7309d61d95721a721b721cd61e9a721d730ad61fb2a5721e01a7d620d802d620c1721fd6218602721172207221d621d803d621db6308721fd62286027214730bd623b27221730c0172227223d62295721672207221d6238c722202d624e47205d625b27224730d00d6269a721d730ed627b2a5722601a7d628d802d628c17227d6298602721172287229d629d803d629db63087227d62a86027214730fd62bb27229731001722a722bd62a95721672287229d62b8c722a02d62ce4c6720e073c0e0ed62de4c6720e0410d62e8c722a01ea02eb02ea02cdeeb472027311b17202d1edededed93c67203040e720193c672030511720493c672030611720593c67203070e720693e5c6720308118303057312731373148303057209720a9a72087315d19591720bb2720c7316009591720bb2720c731700d801d62fb2a57318009683030193db6308722f720d92c1722f9972109c7319720f93c2722f7202d81fd62f7217d6307218d6317219d632721ad633721bd634721cd635721dd636b2a5723501a7d637b2db63087236731a0186027211c17236d6388c723702d6397214d63a7215d63b7216d63c721ed63d721fd63e7220d63f7221d6407222d6418c721302d6427e99b27224731b00720a06d6439d9c72427e7238067e997225720906d64495917243724272427243d645959372128c722c029d9c72447eb2722d731c0006731d9d9c72447eb2722d731e0006731fd6467226d6477227d6487228d6497229d64a722ad64bc2723dd64c9a72097238d64de5c6723d08118302057320732196830201edededededed9172387322938c7237017212907e95723bd801d64e722399997241724e9c720f73239972417223069a72447e722b0693c272367202ed95917245732495723bd802d64e722ed64f722beded93724e7239927e724f067245907e724f069a72457e720f06ed93722e7239937e722b067245732593c27247e4c6720e050e93c5b2a4723500723193c2722fc2b2a4732600edededededededed93724b9592724c72257202c2a793e4c6723d040e720293e4c6723d0511720c93e4c6723d0611722493e4c6723d070e721293b2724d732700724c937eb2724d732800069a7e720a06724493b2724d7329009a7208732a9593724b7202732b938c7240017239732cd1ed938cb2db6308720e732d0001732eec93860272127214722c93860272147212722c",
"ergoTreeConstants": "0: 0\n1: 2\n2: 0\n3: 1\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 1\n10: 2\n11: 0\n12: 0\n13: 0\n14: 4\n15: 0\n16: 0\n17: 3\n18: -1\n19: -1\n20: -1\n21: 1\n22: 0\n23: 1\n24: 0\n25: 2\n26: 0\n27: 1\n28: 0\n29: CBigInt(1000)\n30: 1\n31: CBigInt(1000)\n32: -1\n33: -1\n34: 0\n35: 2\n36: CBigInt(0)\n37: true\n38: 1\n39: 0\n40: 1\n41: 2\n42: 1\n43: true\n44: false\n45: 0\n46: Coll(-94,81,-67,-108,126,35,-68,-50,-11,47,-73,-50,-51,61,99,-57,-22,32,-78,105,89,-82,-117,-105,-18,-21,-67,-109,56,-100,125,74)",
"ergoTreeScript": "{\n val opt1 = SELF.R4[Coll[Byte]]\n val coll2 = opt1.get\n val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](0)))\n val opt4 = SELF.R5[Coll[Long]]\n val opt5 = SELF.R6[Coll[Long]]\n val opt6 = SELF.R7[Coll[Byte]]\n val coll7 = SELF.R8[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1))\n val l9 = coll7(placeholder[Int](2))\n val l10 = coll7(placeholder[Int](3))\n val l11 = CONTEXT.preHeader.timestamp\n val coll12 = opt4.get\n val coll13 = SELF.tokens\n val box14 = CONTEXT.dataInputs(placeholder[Int](4))\n val l15 = box14.R6[Long].get\n val l16 = SELF.value\n val coll17 = Coll[Byte]()\n val coll18 = opt6.get\n val tuple19 = coll13.getOrElse(placeholder[Int](5), (coll17, l16))\n val coll20 = tuple19._1\n val i21 = coll20.size\n val bool22 = i21 == placeholder[Int](6)\n val box23 = INPUTS(placeholder[Int](7))\n val coll24 = box23.id\n val coll25 = SELF.id\n val bool26 = coll24 == coll25\n val i27 = placeholder[Int](8)\n val i28 = placeholder[Int](9)\n val i29 = if (bool26) { i27 } else { i28 }\n val i30 = i29 + placeholder[Int](10)\n val box31 = OUTPUTS.getOrElse(i30, SELF)\n val tuple32 = \n val l32 = box31.value\n val tuple33 = (coll17, l32)\n tuple33\n \n val tuple33 = \n val coll33 = box31.tokens\n val tuple34 = (coll20, placeholder[Long](11))\n val tuple35 = coll33.getOrElse(placeholder[Int](12), tuple34)\n tuple35\n \n val tuple34 = if (bool22) { tuple32 } else { tuple33 }\n val l35 = tuple34._2\n val coll36 = opt5.get\n val l37 = coll36(placeholder[Int](13))\n val i38 = i29 + placeholder[Int](14)\n val box39 = OUTPUTS.getOrElse(i38, SELF)\n val tuple40 = \n val l40 = box39.value\n val tuple41 = (coll17, l40)\n tuple41\n \n val tuple41 = \n val coll41 = box39.tokens\n val tuple42 = (coll20, placeholder[Long](15))\n val tuple43 = coll41.getOrElse(placeholder[Int](16), tuple42)\n tuple43\n \n val tuple42 = if (bool22) { tuple40 } else { tuple41 }\n val l43 = tuple42._2\n val tuple44 = box14.R7[(Coll[Byte], Coll[Byte])].get\n val coll45 = box14.R4[Coll[Int]].get\n val coll46 = tuple42._1\n proveDlog(decodePoint(coll2.slice(placeholder[Int](17), coll2.size))) && sigmaProp(\n ((((box3.R4[Coll[Byte]] == opt1) && (box3.R5[Coll[Long]] == opt4)) && (box3.R6[Coll[Long]] == opt5)) && (box3.R7[Coll[Byte]] == opt6)) && (\n box3.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](18), placeholder[Long](19), placeholder[Long](20))) == Coll[Long](\n l9, l10, l8 + placeholder[Long](21)\n )\n )\n ) || sigmaProp(if (l11 > coll12(placeholder[Int](22))) { if (l11 > coll12(placeholder[Int](23))) {(\n val box47 = OUTPUTS(placeholder[Int](24))\n allOf(Coll[Boolean](box47.tokens == coll13, box47.value >= l16 - placeholder[Long](25) * l15, box47.propositionBytes == coll2))\n )} else {(\n val box47 = box23\n val coll48 = coll24\n val coll49 = coll25\n val bool50 = bool26\n val i51 = i27\n val i52 = i28\n val i53 = i29\n val box54 = OUTPUTS.getOrElse(i53, SELF)\n val tuple55 = box54.tokens.getOrElse(placeholder[Int](26), (coll17, box54.value))\n val l56 = tuple55._2\n val coll57 = coll20\n val i58 = i21\n val bool59 = bool22\n val i60 = i30\n val box61 = box31\n val tuple62 = tuple32\n val tuple63 = tuple33\n val tuple64 = tuple34\n val l65 = tuple19._2\n val bi66 = coll36(placeholder[Int](27)) - l10.toBigInt\n val bi67 = bi66 * l56.toBigInt / l37 - l9.toBigInt\n val bi68 = if (bi67 > bi66) { bi66 } else { bi67 }\n val bi69 = if (coll18 == tuple44._2) { bi68 * coll45(placeholder[Int](28)).toBigInt / placeholder[BigInt](29) } else { bi68 * coll45(placeholder[Int](30)).toBigInt / placeholder[BigInt](31) }\n val i70 = i38\n val box71 = box39\n val tuple72 = tuple40\n val tuple73 = tuple41\n val tuple74 = tuple42\n val coll75 = box61.propositionBytes\n val l76 = l9 + l56\n val coll77 = box61.R8[Coll[Long]].getOrElse(Coll[Long](placeholder[Long](32), placeholder[Long](33)))\n allOf(Coll[Boolean](((((((l56 > placeholder[Long](34)) && (tuple55._1 == coll18)) && (if (bool59) {(\n val l78 = l35\n l65 - l78 - l15 * placeholder[Long](35)\n )} else { l65 - l35 }.toBigInt <= bi68 + l43.toBigInt)) && (box54.propositionBytes == coll2)) && (if (bi69 > placeholder[BigInt](36)) { if (bool59) {(\n val coll78 = coll46\n val l79 = l43\n ((coll78 == coll57) && (l79.toBigInt >= bi69)) && (l79.toBigInt <= bi69 + l15.toBigInt)\n )} else { (coll46 == coll57) && (l43.toBigInt == bi69) } } else { placeholder[Boolean](37) } && (box71.propositionBytes == box14.R5[Coll[Byte]].get))) && (INPUTS(i53).id == coll49)) && (box47.propositionBytes == INPUTS(placeholder[Int](38)).propositionBytes), ((((((((coll75 == if (l76 >= l37) { coll2 } else { SELF.propositionBytes }) && (box61.R4[Coll[Byte]].get == coll2)) && (box61.R5[Coll[Long]].get == coll12)) && (box61.R6[Coll[Long]].get == coll36)) && (box61.R7[Coll[Byte]].get == coll18)) && (coll77(placeholder[Int](39)) == l76)) && (coll77(placeholder[Int](40)).toBigInt == l10.toBigInt + bi68)) && (coll77(placeholder[Int](41)) == l8 + placeholder[Long](42))) && if (coll75 == coll2) { placeholder[Boolean](43) } else { tuple64._1 == coll57 }))\n )} } else { placeholder[Boolean](44) }) && sigmaProp(\n (box14.tokens(placeholder[Int](45))._1 == placeholder[Coll[Byte]](46)) && (((coll18, coll20) == tuple44) || ((coll20, coll18) == tuple44))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 0,
"amount": 4040,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1102008080d0d88bdea2e302",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,100000000000000000]"
},
"R6": {
"serializedValue": "110280c0f0f50bc03e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1600000000,4000]"
},
"R8": {
"serializedValue": "1103000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,0]"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02a7d13182a4cf84f2c16f36e04ed4730ce8388d767b204df01ffd739cba0c2331"
}
}
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