Transaction
ID: 4d38c9e657...e035
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
119,999.99
Spent
Address:
Output transaction:
Settlement height:
Value:
0.1592 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.203 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (6)
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.203 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.1562 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 70,472
Total coins transferred: 0.3642 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000416 ERG
Raw Transaction Data
{
"id": "4d38c9e6575746266f4f18ec53b26c4e2f7e24d0fb9d01f81e3b38b93097e035",
"blockId": "4d257ff406e72f15baee973e316a2b8f652e52c5ea16af00376095e0f2c91ee0",
"inclusionHeight": 1700804,
"timestamp": 1768536106533,
"index": 16,
"globalIndex": 10152030,
"numConfirmations": 70472,
"inputs": [
{
"boxId": "229870e7e6fc22d63bdb17df4ae95480f0d7db67004b26c8e17f0ed7b8b8c561",
"value": 1000000,
"index": 0,
"spendingProof": "cd098321b79a09e1252cdb1223952fbcee4adf56b28f437f225f643a3a9b4657b7a73eab2f31a75b449c27eaeda651bef5241061db0be829",
"outputBlockId": "07695687fa76267e9057af65587d4565d73fc9a2f6d585df13599599604bd2a9",
"outputTransactionId": "fb0ac60a8100fda134801be4a462a07ba12f495069818d1753b12a551a968c4a",
"outputIndex": 2,
"outputGlobalIndex": 52991097,
"outputCreatedAt": 1700593,
"outputSettledAt": 1700595,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
"tokenId": "2a94722d4d3b95f4ccdde4ac81e34d6498acabcfeee3b8b6070de7dde56d740b",
"index": 0,
"amount": 11999999,
"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0500",
"sigmaType": "SLong",
"renderedValue": "0"
},
"R5": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
},
"R6": {
"serializedValue": "0400",
"sigmaType": "SInt",
"renderedValue": "0"
},
"R7": {
"serializedValue": "0e2093ca74910232a9be5abb9947538dd984ac5a753f8a29f8588dd8ff9ed430f209",
"sigmaType": "Coll[SByte]",
"renderedValue": "93ca74910232a9be5abb9947538dd984ac5a753f8a29f8588dd8ff9ed430f209"
}
}
},
{
"boxId": "269e77a49b2474a2bcbece9d889d8f32c83d849ff96d47759c8de34c56ac274a",
"value": 159200000,
"index": 1,
"spendingProof": "fd9cc40e1f616ce166be5595ca7ef62926c0828d3a75a29e20821da6ad848ea8d5a63d54bf2dd09e22290159e23a88428279069b364ed122",
"outputBlockId": "f8bf141f65bc52fe6b9727b1cb6474ffe0fbca214023b157aebe8e40f8be74bc",
"outputTransactionId": "c4dc5932963fedac83d66806f89e5755c7a48a47c32a9c303de33d4d49a74d0f",
"outputIndex": 1,
"outputGlobalIndex": 52991174,
"outputCreatedAt": 1700596,
"outputSettledAt": 1700597,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
"tokenId": "1a6957d590303a457d8c2a1937ffebca95de3c466f523b93370d60fb4cf045dd",
"index": 0,
"amount": 111952,
"name": "Lend Token QUACKS-2.0",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "4a3e8bc22f2643a22227197a6fedd204d2acf7202b25408a3b55747e64b1c5f1",
"index": 1,
"amount": 12011952,
"name": "Lend Token QUACKS-2.0",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "3ed13ea6ea4c96d5281c1bf3c0d73fb5b724fb9165b2273be2b3478e7a82d56d",
"index": 2,
"amount": 12011952,
"name": "Lend Token QUACKS-2.0",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "a175679466e4e2673c110beb3b65af6be4ea9d0ef82d8fece2e85e72bd2212ad",
"index": 3,
"amount": 12011952,
"name": "Lend Token QUACKS-2.0",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "1bcf2c8f5f93a1643df4d01e1bc4cfa36e1fffbf604b852c87b976a77dae96c8",
"index": 4,
"amount": 17,
"name": "Lender Tokens",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "028ec31acacaa6aab6cd89a16cab5f9046cfea701262f8c9532ace433075353a",
"index": 5,
"amount": 143137,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
"tokenId": "52cb2223f414ef7753c82e487503c1c53d0b371b4785f093ccced551d7c261fa",
"index": 6,
"amount": 1,
"name": "Bulls on Parade 2024",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "7a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0",
"index": 7,
"amount": 1118499,
"name": "rsBTC",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "f02790600e7aff717354ba765cbb1c207a48c9856f63c08c721641c320aa54a6",
"index": 8,
"amount": 12011952,
"name": "Lend Token QUACKS-2.0",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "a92aab36106192b1a1d4b5b1b83affd82e54b273bce19f0419f8b5ce6a61ba70",
"value": 203000000,
"index": 2,
"spendingProof": "9deb70e2b2ff7b2095cad8ba30418929dc086e2f5251fdf1260847d0d195f156411ac098d933aaf30a222fd6b092c41ac630a17378b64f4c",
"outputBlockId": "9222da919d1392555ddceed55cbaa5625a9e0908ee22313475a03ce7af06e653",
"outputTransactionId": "f57a35bd990359e2c9ab652a124610a8c2a70b735a18310ad28dc16d9f8b65e5",
"outputIndex": 1,
"outputGlobalIndex": 52996559,
"outputCreatedAt": 1700763,
"outputSettledAt": 1700767,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-57,-107,81,83,82,124,-96,12,-49,65,-128,-60,58,55,-7,87,-5,-42,-67,-62,-52,3,-119,-24,-52,-34,-40,-62,-103,34,-16,74)\n3: 0\n4: 3\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(49,44,23,63,-23,-57,112,104,106,-64,16,27,37,-99,110,78,-90,105,-81,-1,-106,50,24,14,24,-115,51,-101,-123,106,-44,127)\n11: 0\n12: 1\n13: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n14: 0\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 1\n40: 10000000\n41: 1\n42: 1000000\n43: 1000\n44: 1000\n45: 0\n46: 0\n47: 0\n48: 0\n49: 1000000\n50: 10000000\n51: 5\n52: 1000000\n53: 10000000\n54: 100000000\n55: 100000000\n56: 100000000\n57: 0\n58: 1\n59: 3\n60: 2\n61: 3\n62: 5\n63: 6\n64: 7\n65: 1000\n66: 1\n67: 1\n68: 980000\n69: 1000000\n70: CBigInt(1)\n71: 0\n72: 0\n73: 0\n74: 0\n75: -1\n76: 1\n77: 1\n78: 2000000\n79: 0\n80: 0\n81: 0\n82: true\n83: 0\n84: 1000000",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Byte]].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n })\n val coll3 = SELF.propositionBytes\n val coll4 = placeholder[Coll[Byte]](2)\n val coll5 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n val coll7 = SELF.R9[Coll[Long]].get\n val l8 = coll7(placeholder[Int](4))\n val coll9 = SELF.tokens\n val tuple10 = coll9(placeholder[Int](5))\n val coll11 = tuple10._1\n val coll12 = SELF.R4[Coll[Byte]].get\n val ge13 = SELF.R5[GroupElement].get\n val l14 = SELF.R6[Long].get\n val coll15 = SELF.R8[Coll[Byte]].get\n val l16 = SELF.value\n val func17 = {(box17: Box) =>\n val coll19 = box17.propositionBytes\n val bool20 = coll19 == coll3\n bool20\n }\n val coll18 = OUTPUTS.filter(func17)\n val box19 = coll18.getOrElse(i6, SELF)\n val coll20 = box19.tokens\n val tuple21 = coll20(placeholder[Int](6))\n val l22 = tuple21._2\n val bi23 = placeholder[BigInt](7)\n val bi24 = CONTEXT.dataInputs.filter({(box24: Box) =>\n val coll26 = box24.tokens\n (coll26.size > placeholder[Int](8)) && (coll26(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n })(placeholder[Int](11)).R5[BigInt].get\n val l25 = tuple10._2\n val bi26 = l25.toBigInt\n val coll27 = coll9.slice(placeholder[Int](12), coll9.size)\n val coll28 = placeholder[Coll[Byte]](13)\n val func29 = {(box29: Box) =>\n val coll31 = box29.propositionBytes\n val coll32 = blake2b256(coll31)\n val bool33 = coll32 == coll4\n bool33\n }\n val coll30 = OUTPUTS.filter(func29)\n val box31 = coll30.getOrElse(placeholder[Int](14), SELF)\n val coll32 = box31.tokens\n val tuple33 = coll32(placeholder[Int](15))\n val l34 = coll7(placeholder[Int](16))\n val i35 = coll5.size\n val bool36 = i35 == placeholder[Int](17)\n val l37 = HEIGHT.toLong\n val l38 = coll7(placeholder[Int](18))\n val l39 = coll7(placeholder[Int](19))\n val l40 = l38 + l39\n val l41 = coll7(placeholder[Int](20))\n val coll42 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n val coll43 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n val l44 = coll7(placeholder[Int](25))\n val bi45 = bi26 * bi24 / bi23\n val bi46 = if (l37 < l40) {(\n val i46 = placeholder[Int](26)\n bi45 * l44.toBigInt + i46.toBigInt / i46.toBigInt\n )} else { bi45 }\n val box47 = coll30.getOrElse(placeholder[Int](27), SELF)\n val coll48 = box47.tokens\n val tuple49 = coll48(placeholder[Int](28))\n val func50 = {(box50: Box) =>\n val coll52 = box50.propositionBytes\n val coll53 = blake2b256(coll52)\n val bool54 = coll53 == coll4\n bool54\n }\n val coll51 = OUTPUTS.filter(func50)\n val box52 = coll51.getOrElse(placeholder[Int](29), SELF)\n val coll53 = box52.tokens\n val tuple54 = coll53(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func55 = func17\n val coll56 = coll18\n val i57 = coll56.size\n val func58 = func29\n val coll59 = coll30\n val box60 = coll2.getOrElse(i6, SELF)\n val coll61 = box60.R4[Coll[Long]].get\n val l62 = coll61(placeholder[Int](32))\n val l63 = coll61(placeholder[Int](33))\n if (i57 > placeholder[Int](34)) {(\n val box64 = box19\n val bool65 = OUTPUTS.map({(box65: Box) => box65.id }).indexOf(box64.id, placeholder[Int](35)) == box60.R9[Coll[Int]].get(\n placeholder[Int](36)\n ) - placeholder[Int](37)\n val l66 = box64.value\n val coll67 = coll20\n val tuple68 = tuple21\n val coll69 = box64.R4[Coll[Byte]].get\n val ge70 = box64.R5[GroupElement].get\n val coll71 = box64.R7[Coll[Byte]].get\n val bool72 = ((((l66 >= l8) && (tuple68._1 == coll11)) && (coll69 == coll12)) && (ge70 == ge13)) && (coll71 == coll1)\n val coll73 = box64.R8[Coll[Byte]].get\n val l74 = box64.R6[Long].get\n val coll75 = box64.R9[Coll[Long]].get\n val bool76 = coll75 == coll7\n if (coll59.size > placeholder[Int](38)) {(\n val bi77 = l22.toBigInt\n val box78 = box31\n val coll79 = coll32\n val tuple80 = coll79(placeholder[Int](39))\n val tuple81 = tuple33\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (l66 >= l16)) && (l66 <= l16 + placeholder[Long](40))) && (\n bi77 >= bi26 - tuple80._2.toBigInt * bi23 / bi24\n )\n ) && (coll67.slice(placeholder[Int](41), coll67.size) == coll27)\n ) && (l74 == l14)\n ) && bool76\n ) && (((box78.value >= placeholder[Long](42)) && (tuple81._1 == coll11)) && (tuple80._1 == coll28))\n ) && (tuple81._2 == l25 - l22)\n ) && (l62.toBigInt >= bi77 * bi24 / bi23 * l34.toBigInt / placeholder[Int](43).toBigInt)\n ) && bool36\n ) && (l37 >= l40)\n )\n )} else {(\n val bi77 = l62.toBigInt\n val i78 = placeholder[Int](44)\n val bi79 = l22.toBigInt * bi24 / bi23 * l34.toBigInt / i78.toBigInt\n val bool80 = bi77 >= bi79\n val prop81 = sigmaProp(INPUTS.filter({(box81: Box) =>\n val coll83 = box81.tokens\n ((coll83.size > placeholder[Int](45)) && (coll83(placeholder[Int](46))._1 == coll42)) && (box81.R9[Coll[Coll[Byte]]].get(INPUTS.indexOf(SELF, placeholder[Int](47))) == coll43)\n }).size > placeholder[Int](48)) || proveDlog(ge13)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (l66 >= l16 - placeholder[Long](49))) && (l66 <= l16 + placeholder[Long](50))) && (\n coll67 == coll9\n )\n ) && (l74 > l37 + l41)\n ) && (l74 < l37 + l41 + placeholder[Long](51))\n ) && (bi77 < bi79)\n ) && bool76\n ) && bool36\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (l66 >= l16 - placeholder[Long](52))) && (l66 <= l16 + placeholder[Long](53))) && (\n coll67 == coll9\n )\n ) && (l14 != placeholder[Long](54))\n ) && (l74 == placeholder[Long](55))\n ) && bool80\n ) && bool76\n ) && bool36\n ) || prop81 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (bi77 >= bi46 * l63.toBigInt / i78.toBigInt)) && (tuple68 == tuple10)) && (\n l74 == placeholder[Long](56)\n )\n ) && bool80\n ) && ((coll75(placeholder[Int](57)) == l63) && (coll75(placeholder[Int](58)) == coll61(placeholder[Int](59))))\n ) && (i35 == i57)\n ) && (coll75(placeholder[Int](60)) == l41)\n ) && (coll75(placeholder[Int](61)) == l8)\n ) && (coll75(placeholder[Int](62)) == l38)\n ) && (coll75(placeholder[Int](63)) == l44)\n ) && (coll75(placeholder[Int](64)) == l39)\n ) || prop81 && sigmaProp(\n ((((((bool72 && (l66 == l16)) && (coll67 == coll9)) && (coll69 == coll12)) && (ge70 == ge13)) && (coll71 == coll1)) && bool76) && (i35 == i57)\n )\n )}\n )} else {(\n val bi64 = l62.toBigInt\n val i65 = placeholder[Int](65)\n val box66 = box47\n val coll67 = coll48\n val tuple68 = tuple49\n val tuple69 = coll67(placeholder[Int](66))\n val coll70 = SELF.id\n val bi71 = bi64 - bi46\n val bi72 = coll7(placeholder[Int](67)).toBigInt\n val bi73 = bi71 * i65.toBigInt - bi72 / i65.toBigInt\n val l74 = tuple69._2\n sigmaProp(\n (\n (\n (\n (\n (((bi64 <= bi46 * l34.toBigInt / i65.toBigInt) && (l37 >= l14)) || (l37 > SELF.creationInfo._1.toLong + placeholder[Long](68))) && (\n (((box66.value >= placeholder[Long](69)) && (tuple68._1 == coll11)) && (tuple69._1 == coll28)) && (box66.id != coll70)\n )\n ) && (tuple68._2 == l25)\n ) && if (bi73 < placeholder[BigInt](70)) { l74.toBigInt >= bi64 } else {(\n val box75 = OUTPUTS.filter({(box75: Box) => box75.propositionBytes == coll12 }).getOrElse(placeholder[Int](71), SELF)\n val tuple76 = box75.tokens(placeholder[Int](72))\n (((l74.toBigInt >= bi46 + bi71 * bi72 / i65.toBigInt) && (tuple76._2.toBigInt >= bi73)) && (tuple76._1 == coll28)) && (box75.id != coll70)\n )}\n ) && (\n INPUTS.map({(box75: Box) => box75.id }).indexOf(coll70, placeholder[Int](73)) == box60.R9[Coll[Int]].get(placeholder[Int](74)) * placeholder[Int](\n 75\n ) - placeholder[Int](76)\n )\n ) && bool36\n )\n )}\n )} else {(\n val func55 = func50\n val coll56 = coll51\n val box57 = box52\n val coll58 = coll53\n val tuple59 = tuple54\n val tuple60 = coll58(placeholder[Int](77))\n sigmaProp(\n (\n (\n (\n ((((box57.value >= placeholder[Long](78)) && (tuple59._1 == coll11)) && (tuple60._1 == coll28)) && (box57.id != SELF.id)) && (tuple59._2 == l25)\n ) && (tuple60._2.toBigInt > bi46)\n ) && if (INPUTS.filter({(box61: Box) =>\n val coll63 = box61.tokens\n ((coll63.size > placeholder[Int](79)) && (coll63(placeholder[Int](80))._1 == coll42)) && (box61.R9[Coll[Byte]].get == coll43)\n }).size > placeholder[Int](81)) { placeholder[Boolean](82) } else {(\n val box61 = OUTPUTS.filter({(box61: Box) => box61.propositionBytes == coll12 }).getOrElse(placeholder[Int](83), SELF)\n ((box61.value >= l16 - placeholder[Long](84)) && (box61.tokens == coll27)) && (box61.id != SELF.id)\n )}\n ) && bool36\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "2d3e8387e711d6fb76f11d434207427b450dbb365872116acfcd38eb6caf3039",
"index": 0,
"amount": 4000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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"R6": {
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"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "00"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3c4bd1d515fd887189eafab63df87bf0638e667a77ac41361c4d93094f333b1e"
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"R9": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[1435,30,8,15000000,0,1700768,50,15]"
},
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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{
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"value": 1000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "9fd844288f2a676a0bf2f6b0b9ad743d84cef6eb6c2aa9b3441edb7bb4bb73cc",
"outputTransactionId": "0fa75981f2dc856a2a82d7df98828e8a498b24d259904960c545ececc43bf7a7",
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"outputCreatedAt": 1700780,
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val box2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n })(placeholder[Int](3))\n val coll3 = box2.propositionBytes\n val coll4 = box2.R4[Coll[Long]].get\n val l5 = coll4(placeholder[Int](4))\n val coll6 = SELF.R4[Coll[Long]].get\n val l7 = coll6(placeholder[Int](5))\n val l8 = coll4(placeholder[Int](6))\n val l9 = coll6(placeholder[Int](7))\n val l10 = coll4(placeholder[Int](8))\n val l11 = coll6(placeholder[Int](9))\n val l12 = coll4(placeholder[Int](10))\n val l13 = coll6(placeholder[Int](11))\n val l14 = coll4(placeholder[Int](12))\n val l15 = coll6(placeholder[Int](13))\n val l16 = coll4(placeholder[Int](14))\n val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n val coll18 = box2.R5[Coll[Coll[Byte]]].get\n val coll19 = SELF.R6[Coll[Long]].get\n val coll20 = box2.R6[Coll[Long]].get\n val coll21 = CONTEXT.dataInputs\n val coll22 = box2.R9[Coll[Int]].get\n val i23 = coll22(placeholder[Int](15))\n val box24 = coll21(i23)\n val coll25 = box24.tokens\n val i26 = coll22(placeholder[Int](16))\n val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n val bi28 = box27.value.toBigInt\n val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n val coll30 = box2.R7[Coll[Long]].get\n val bi31 = placeholder[BigInt](22)\n val bi32 = placeholder[BigInt](23)\n val bi33 = placeholder[BigInt](24)\n val bi34 = placeholder[BigInt](25)\n val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n val tuple37 = tuple35._2\n val l38 = tuple37._2\n val box39 = tuple37._1\n val bi40 = tuple35._1\n if (l38 > placeholder[Long](26)) {(\n val bi41 = l38.toBigInt\n val bi42 = box39.R4[Int].get.toBigInt\n val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n )} else { bi40 }\n }) - placeholder[Int](28).toBigInt\n val bi36 = box24.R4[Int].get.toBigInt\n val bi37 = box24.value.toBigInt\n val l38 = placeholder[Long](29)\n val coll39 = box27.tokens\n val i40 = coll39.size\n val coll41 = box2.R8[Coll[Coll[Byte]]].get\n val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n val i43 = coll29.size\n val i44 = coll30.size\n sigmaProp(\n (\n (\n (\n (\n (\n (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n l9 == l10\n )\n ) && (l11 == l12)\n ) && (l13 == l14)\n ) && (l15 == l16)\n ) && (coll17 == coll18)\n ) && (coll19 == coll20)\n ) && placeholder[SigmaProp](32) || sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n placeholder[Int](34)\n ).toBigInt\n )\n ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n val i47 = tuple45._2\n val l48 = coll30(i47)\n val bi49 = tuple45._1\n if (l48 > placeholder[Long](40)) {(\n val box50 = coll29(i47)\n val bi51 = l48.toBigInt\n val bi52 = box50.R4[Int].get.toBigInt\n val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n )} else { bi49 }\n }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n ) && coll39.slice(placeholder[Int](45), i40).forall(\n {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n )\n ) && coll42.indices.forall({(i45: Int) =>\n val coll47 = coll29(i45).tokens\n (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n })\n ) && ((i43 == i44) && (i43 == coll42.size))\n ) && (i44 == coll41.size)\n ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n ) && (l7 == max(l8, placeholder[Long](52)))\n ) && (l9 == max(l10, placeholder[Long](53)))\n ) && (l11 == max(l12, placeholder[Long](54)))\n ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n ) && (l13 == max(l14, placeholder[Long](57)))\n ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "3c4bd1d515fd887189eafab63df87bf0638e667a77ac41361c4d93094f333b1e",
"index": 0,
"amount": 1,
"name": "Logic NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1a012046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
},
"R6": {
"serializedValue": "1101f015",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1400]"
},
"R8": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R7": {
"serializedValue": "1100",
"sigmaType": "Coll[SLong]",
"renderedValue": "[]"
},
"R9": {
"serializedValue": "10020404",
"sigmaType": "Coll[SInt]",
"renderedValue": "[2,2]"
},
"R4": {
"serializedValue": "110a80a0b787e905ee97e235fe153c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,56378871,1407,30,15000000,8,0,50,15,20000000]"
}
}
}
],
"dataInputs": [
{
"boxId": "d1f88d846dfa99501be39a73fa8c61c2de3a8a65b4d76974d23235ce82446a22",
"value": 1000000,
"index": 0,
"outputBlockId": "a3f0c8cabb65027fce235d32db37a6d6809113f131ecea32af23b6267f619120",
"outputTransactionId": "86b4b3a8bca0e4fdb25f51bdf53ecd0e4fb7669cece71076a8747554a24dadf9",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "05f4c6cf01",
"sigmaType": "SLong",
"renderedValue": "1700282"
},
"R5": {
"serializedValue": "06072386f26fc10000",
"sigmaType": "SBigInt",
"renderedValue": "CBigInt(10000000000000000)"
}
}
},
{
"boxId": "70e7023d5a7e52c9e617fc714180d7f21603b5671e79dec8e2eb39679ec679e6",
"value": 18212416862359,
"index": 1,
"outputBlockId": "a22193c71f3b82bc5bf01cd67e1c430ffbaab904142b3c71a28e623b1d43fa45",
"outputTransactionId": "12ef44d01c154a01d8930a26c603ac2987d33556f04e78a7b391631405fe10e9",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04ca0f",
"sigmaType": "SInt",
"renderedValue": "997"
}
}
}
],
"outputs": [
{
"boxId": "a54d1f31cdb602b2a6effc14eb77511a17cc32ca13d2d43430b864c53373f697",
"transactionId": "4d38c9e6575746266f4f18ec53b26c4e2f7e24d0fb9d01f81e3b38b93097e035",
"blockId": "4d257ff406e72f15baee973e316a2b8f652e52c5ea16af00376095e0f2c91ee0",
"value": 1000000,
"index": 0,
"globalIndex": 52997582,
"creationHeight": 1700801,
"settlementHeight": 1700804,
"ergoTree": "100208cd03199bd9865508d9e9c998e828d8313cb1bf83d43ac79c467d33f8d1223fde382c04a5c203ea027300d191a37301",
"ergoTreeConstants": "0: SigmaProp(ProveDlog(ECPoint(199bd9,a14ea8,...)))\n1: -28819",
"ergoTreeScript": "{placeholder[SigmaProp](0) && sigmaProp(HEIGHT > placeholder[Int](1))}",
"address": "26DFznnsFVBgMJVSDq7oiS4HA1WZF8qT88jKcygK3eYfCrC9udi8DkuEr8yCYD7rDQYC74Uf9k5",
"assets": [
{
"tokenId": "229870e7e6fc22d63bdb17df4ae95480f0d7db67004b26c8e17f0ed7b8b8c561",
"index": 0,
"amount": 1000000,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R6": {
"serializedValue": "05e012",
"sigmaType": "SLong",
"renderedValue": "1200"
},
"R8": {
"serializedValue": "0464",
"sigmaType": "SInt",
"renderedValue": "50"
},
"R7": {
"serializedValue": "0e203c4bd1d515fd887189eafab63df87bf0638e667a77ac41361c4d93094f333b1e",
"sigmaType": "Coll[SByte]",
"renderedValue": "3c4bd1d515fd887189eafab63df87bf0638e667a77ac41361c4d93094f333b1e"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "77c3c1f5e9643af268c0c7458365650ad35c4800683c5f35c6b46e5bb8f80bed",
"transactionId": "4d38c9e6575746266f4f18ec53b26c4e2f7e24d0fb9d01f81e3b38b93097e035",
"blockId": "4d257ff406e72f15baee973e316a2b8f652e52c5ea16af00376095e0f2c91ee0",
"value": 203000000,
"index": 1,
"globalIndex": 52997583,
"creationHeight": 1700801,
"settlementHeight": 1700804,
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"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-57,-107,81,83,82,124,-96,12,-49,65,-128,-60,58,55,-7,87,-5,-42,-67,-62,-52,3,-119,-24,-52,-34,-40,-62,-103,34,-16,74)\n3: 0\n4: 3\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(49,44,23,63,-23,-57,112,104,106,-64,16,27,37,-99,110,78,-90,105,-81,-1,-106,50,24,14,24,-115,51,-101,-123,106,-44,127)\n11: 0\n12: 1\n13: Coll(8,-103,-112,69,27,-76,48,-16,90,-123,-12,-17,59,-53,110,-65,-123,43,61,110,-26,-115,-122,-41,-122,88,-71,-52,-17,32,7,79)\n14: 0\n15: 0\n16: 0\n17: 1\n18: 5\n19: 7\n20: 2\n21: 0\n22: 32\n23: 32\n24: 40\n25: 6\n26: 1000\n27: 0\n28: 0\n29: 0\n30: 0\n31: 0\n32: 1\n33: 2\n34: 0\n35: 0\n36: 0\n37: 1\n38: 0\n39: 1\n40: 10000000\n41: 1\n42: 1000000\n43: 1000\n44: 1000\n45: 0\n46: 0\n47: 0\n48: 0\n49: 1000000\n50: 10000000\n51: 5\n52: 1000000\n53: 10000000\n54: 100000000\n55: 100000000\n56: 100000000\n57: 0\n58: 1\n59: 3\n60: 2\n61: 3\n62: 5\n63: 6\n64: 7\n65: 1000\n66: 1\n67: 1\n68: 980000\n69: 1000000\n70: CBigInt(1)\n71: 0\n72: 0\n73: 0\n74: 0\n75: -1\n76: 1\n77: 1\n78: 2000000\n79: 0\n80: 0\n81: 0\n82: true\n83: 0\n84: 1000000",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Byte]].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == coll1)\n })\n val coll3 = SELF.propositionBytes\n val coll4 = placeholder[Coll[Byte]](2)\n val coll5 = INPUTS.filter({(box5: Box) => box5.propositionBytes == coll3 })\n val i6 = coll5.indexOf(SELF, placeholder[Int](3))\n val coll7 = SELF.R9[Coll[Long]].get\n val l8 = coll7(placeholder[Int](4))\n val coll9 = SELF.tokens\n val tuple10 = coll9(placeholder[Int](5))\n val coll11 = tuple10._1\n val coll12 = SELF.R4[Coll[Byte]].get\n val ge13 = SELF.R5[GroupElement].get\n val l14 = SELF.R6[Long].get\n val coll15 = SELF.R8[Coll[Byte]].get\n val l16 = SELF.value\n val func17 = {(box17: Box) =>\n val coll19 = box17.propositionBytes\n val bool20 = coll19 == coll3\n bool20\n }\n val coll18 = OUTPUTS.filter(func17)\n val box19 = coll18.getOrElse(i6, SELF)\n val coll20 = box19.tokens\n val tuple21 = coll20(placeholder[Int](6))\n val l22 = tuple21._2\n val bi23 = placeholder[BigInt](7)\n val bi24 = CONTEXT.dataInputs.filter({(box24: Box) =>\n val coll26 = box24.tokens\n (coll26.size > placeholder[Int](8)) && (coll26(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n })(placeholder[Int](11)).R5[BigInt].get\n val l25 = tuple10._2\n val bi26 = l25.toBigInt\n val coll27 = coll9.slice(placeholder[Int](12), coll9.size)\n val coll28 = placeholder[Coll[Byte]](13)\n val func29 = {(box29: Box) =>\n val coll31 = box29.propositionBytes\n val coll32 = blake2b256(coll31)\n val bool33 = coll32 == coll4\n bool33\n }\n val coll30 = OUTPUTS.filter(func29)\n val box31 = coll30.getOrElse(placeholder[Int](14), SELF)\n val coll32 = box31.tokens\n val tuple33 = coll32(placeholder[Int](15))\n val l34 = coll7(placeholder[Int](16))\n val i35 = coll5.size\n val bool36 = i35 == placeholder[Int](17)\n val l37 = HEIGHT.toLong\n val l38 = coll7(placeholder[Int](18))\n val l39 = coll7(placeholder[Int](19))\n val l40 = l38 + l39\n val l41 = coll7(placeholder[Int](20))\n val coll42 = coll15.slice(placeholder[Int](21), placeholder[Int](22))\n val coll43 = coll15.slice(placeholder[Int](23), placeholder[Int](24))\n val l44 = coll7(placeholder[Int](25))\n val bi45 = bi26 * bi24 / bi23\n val bi46 = if (l37 < l40) {(\n val i46 = placeholder[Int](26)\n bi45 * l44.toBigInt + i46.toBigInt / i46.toBigInt\n )} else { bi45 }\n val box47 = coll30.getOrElse(placeholder[Int](27), SELF)\n val coll48 = box47.tokens\n val tuple49 = coll48(placeholder[Int](28))\n val func50 = {(box50: Box) =>\n val coll52 = box50.propositionBytes\n val coll53 = blake2b256(coll52)\n val bool54 = coll53 == coll4\n bool54\n }\n val coll51 = OUTPUTS.filter(func50)\n val box52 = coll51.getOrElse(placeholder[Int](29), SELF)\n val coll53 = box52.tokens\n val tuple54 = coll53(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func55 = func17\n val coll56 = coll18\n val i57 = coll56.size\n val func58 = func29\n val coll59 = coll30\n val box60 = coll2.getOrElse(i6, SELF)\n val coll61 = box60.R4[Coll[Long]].get\n val l62 = coll61(placeholder[Int](32))\n val l63 = coll61(placeholder[Int](33))\n if (i57 > placeholder[Int](34)) {(\n val box64 = box19\n val bool65 = OUTPUTS.map({(box65: Box) => box65.id }).indexOf(box64.id, placeholder[Int](35)) == box60.R9[Coll[Int]].get(\n placeholder[Int](36)\n ) - placeholder[Int](37)\n val l66 = box64.value\n val coll67 = coll20\n val tuple68 = tuple21\n val coll69 = box64.R4[Coll[Byte]].get\n val ge70 = box64.R5[GroupElement].get\n val coll71 = box64.R7[Coll[Byte]].get\n val bool72 = ((((l66 >= l8) && (tuple68._1 == coll11)) && (coll69 == coll12)) && (ge70 == ge13)) && (coll71 == coll1)\n val coll73 = box64.R8[Coll[Byte]].get\n val l74 = box64.R6[Long].get\n val coll75 = box64.R9[Coll[Long]].get\n val bool76 = coll75 == coll7\n if (coll59.size > placeholder[Int](38)) {(\n val bi77 = l22.toBigInt\n val box78 = box31\n val coll79 = coll32\n val tuple80 = coll79(placeholder[Int](39))\n val tuple81 = tuple33\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (l66 >= l16)) && (l66 <= l16 + placeholder[Long](40))) && (\n bi77 >= bi26 - tuple80._2.toBigInt * bi23 / bi24\n )\n ) && (coll67.slice(placeholder[Int](41), coll67.size) == coll27)\n ) && (l74 == l14)\n ) && bool76\n ) && (((box78.value >= placeholder[Long](42)) && (tuple81._1 == coll11)) && (tuple80._1 == coll28))\n ) && (tuple81._2 == l25 - l22)\n ) && (l62.toBigInt >= bi77 * bi24 / bi23 * l34.toBigInt / placeholder[Int](43).toBigInt)\n ) && bool36\n ) && (l37 >= l40)\n )\n )} else {(\n val bi77 = l62.toBigInt\n val i78 = placeholder[Int](44)\n val bi79 = l22.toBigInt * bi24 / bi23 * l34.toBigInt / i78.toBigInt\n val bool80 = bi77 >= bi79\n val prop81 = sigmaProp(INPUTS.filter({(box81: Box) =>\n val coll83 = box81.tokens\n ((coll83.size > placeholder[Int](45)) && (coll83(placeholder[Int](46))._1 == coll42)) && (box81.R9[Coll[Coll[Byte]]].get(INPUTS.indexOf(SELF, placeholder[Int](47))) == coll43)\n }).size > placeholder[Int](48)) || proveDlog(ge13)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (l66 >= l16 - placeholder[Long](49))) && (l66 <= l16 + placeholder[Long](50))) && (\n coll67 == coll9\n )\n ) && (l74 > l37 + l41)\n ) && (l74 < l37 + l41 + placeholder[Long](51))\n ) && (bi77 < bi79)\n ) && bool76\n ) && bool36\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (l66 >= l16 - placeholder[Long](52))) && (l66 <= l16 + placeholder[Long](53))) && (\n coll67 == coll9\n )\n ) && (l14 != placeholder[Long](54))\n ) && (l74 == placeholder[Long](55))\n ) && bool80\n ) && bool76\n ) && bool36\n ) || prop81 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool72 && bool65) && (coll15 == coll73)) && (bi77 >= bi46 * l63.toBigInt / i78.toBigInt)) && (tuple68 == tuple10)) && (\n l74 == placeholder[Long](56)\n )\n ) && bool80\n ) && ((coll75(placeholder[Int](57)) == l63) && (coll75(placeholder[Int](58)) == coll61(placeholder[Int](59))))\n ) && (i35 == i57)\n ) && (coll75(placeholder[Int](60)) == l41)\n ) && (coll75(placeholder[Int](61)) == l8)\n ) && (coll75(placeholder[Int](62)) == l38)\n ) && (coll75(placeholder[Int](63)) == l44)\n ) && (coll75(placeholder[Int](64)) == l39)\n ) || prop81 && sigmaProp(\n ((((((bool72 && (l66 == l16)) && (coll67 == coll9)) && (coll69 == coll12)) && (ge70 == ge13)) && (coll71 == coll1)) && bool76) && (i35 == i57)\n )\n )}\n )} else {(\n val bi64 = l62.toBigInt\n val i65 = placeholder[Int](65)\n val box66 = box47\n val coll67 = coll48\n val tuple68 = tuple49\n val tuple69 = coll67(placeholder[Int](66))\n val coll70 = SELF.id\n val bi71 = bi64 - bi46\n val bi72 = coll7(placeholder[Int](67)).toBigInt\n val bi73 = bi71 * i65.toBigInt - bi72 / i65.toBigInt\n val l74 = tuple69._2\n sigmaProp(\n (\n (\n (\n (\n (((bi64 <= bi46 * l34.toBigInt / i65.toBigInt) && (l37 >= l14)) || (l37 > SELF.creationInfo._1.toLong + placeholder[Long](68))) && (\n (((box66.value >= placeholder[Long](69)) && (tuple68._1 == coll11)) && (tuple69._1 == coll28)) && (box66.id != coll70)\n )\n ) && (tuple68._2 == l25)\n ) && if (bi73 < placeholder[BigInt](70)) { l74.toBigInt >= bi64 } else {(\n val box75 = OUTPUTS.filter({(box75: Box) => box75.propositionBytes == coll12 }).getOrElse(placeholder[Int](71), SELF)\n val tuple76 = box75.tokens(placeholder[Int](72))\n (((l74.toBigInt >= bi46 + bi71 * bi72 / i65.toBigInt) && (tuple76._2.toBigInt >= bi73)) && (tuple76._1 == coll28)) && (box75.id != coll70)\n )}\n ) && (\n INPUTS.map({(box75: Box) => box75.id }).indexOf(coll70, placeholder[Int](73)) == box60.R9[Coll[Int]].get(placeholder[Int](74)) * placeholder[Int](\n 75\n ) - placeholder[Int](76)\n )\n ) && bool36\n )\n )}\n )} else {(\n val func55 = func50\n val coll56 = coll51\n val box57 = box52\n val coll58 = coll53\n val tuple59 = tuple54\n val tuple60 = coll58(placeholder[Int](77))\n sigmaProp(\n (\n (\n (\n ((((box57.value >= placeholder[Long](78)) && (tuple59._1 == coll11)) && (tuple60._1 == coll28)) && (box57.id != SELF.id)) && (tuple59._2 == l25)\n ) && (tuple60._2.toBigInt > bi46)\n ) && if (INPUTS.filter({(box61: Box) =>\n val coll63 = box61.tokens\n ((coll63.size > placeholder[Int](79)) && (coll63(placeholder[Int](80))._1 == coll42)) && (box61.R9[Coll[Byte]].get == coll43)\n }).size > placeholder[Int](81)) { placeholder[Boolean](82) } else {(\n val box61 = OUTPUTS.filter({(box61: Box) => box61.propositionBytes == coll12 }).getOrElse(placeholder[Int](83), SELF)\n ((box61.value >= l16 - placeholder[Long](84)) && (box61.tokens == coll27)) && (box61.id != SELF.id)\n )}\n ) && bool36\n )\n )}\n}",
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"R9": {
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
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"ergoTreeConstants": "",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 4\n6: 4\n7: 5\n8: 5\n9: 6\n10: 6\n11: 8\n12: 8\n13: 7\n14: 7\n15: 1\n16: 0\n17: 0\n18: 1\n19: -1\n20: 1\n21: 1\n22: CBigInt(0)\n23: CBigInt(2)\n24: CBigInt(100)\n25: CBigInt(1000)\n26: 0\n27: 2\n28: 5000000\n29: 1000000000000\n30: 1\n31: 0\n32: SigmaProp(ProveDlog(ECPoint(dda8fe,c3416e,...)))\n33: 2\n34: 1\n35: 3\n36: 1000\n37: 0\n38: 30\n39: 0\n40: 0\n41: 2\n42: 1\n43: 2\n44: 1001\n45: 1\n46: 0\n47: 2\n48: 0\n49: 1\n50: 0\n51: 0\n52: 4000000\n53: 1\n54: 0\n55: 1000\n56: 0\n57: 0\n58: 9\n59: 9\n60: 0\n61: 0\n62: 0",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val box2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == SELF.tokens(placeholder[Int](2)))\n })(placeholder[Int](3))\n val coll3 = box2.propositionBytes\n val coll4 = box2.R4[Coll[Long]].get\n val l5 = coll4(placeholder[Int](4))\n val coll6 = SELF.R4[Coll[Long]].get\n val l7 = coll6(placeholder[Int](5))\n val l8 = coll4(placeholder[Int](6))\n val l9 = coll6(placeholder[Int](7))\n val l10 = coll4(placeholder[Int](8))\n val l11 = coll6(placeholder[Int](9))\n val l12 = coll4(placeholder[Int](10))\n val l13 = coll6(placeholder[Int](11))\n val l14 = coll4(placeholder[Int](12))\n val l15 = coll6(placeholder[Int](13))\n val l16 = coll4(placeholder[Int](14))\n val coll17 = SELF.R5[Coll[Coll[Byte]]].get\n val coll18 = box2.R5[Coll[Coll[Byte]]].get\n val coll19 = SELF.R6[Coll[Long]].get\n val coll20 = box2.R6[Coll[Long]].get\n val coll21 = CONTEXT.dataInputs\n val coll22 = box2.R9[Coll[Int]].get\n val i23 = coll22(placeholder[Int](15))\n val box24 = coll21(i23)\n val coll25 = box24.tokens\n val i26 = coll22(placeholder[Int](16))\n val box27 = if (i26 > placeholder[Int](17)) { OUTPUTS(i26 - placeholder[Int](18)) } else { INPUTS(i26 * placeholder[Int](19) - placeholder[Int](20)) }\n val bi28 = box27.value.toBigInt\n val coll29 = coll21.slice(i23 + placeholder[Int](21), coll21.size)\n val coll30 = box2.R7[Coll[Long]].get\n val bi31 = placeholder[BigInt](22)\n val bi32 = placeholder[BigInt](23)\n val bi33 = placeholder[BigInt](24)\n val bi34 = placeholder[BigInt](25)\n val bi35 = bi28 + coll29.zip(coll30).fold(bi31, {(tuple35: (BigInt, (Box, Long))) =>\n val tuple37 = tuple35._2\n val l38 = tuple37._2\n val box39 = tuple37._1\n val bi40 = tuple35._1\n if (l38 > placeholder[Long](26)) {(\n val bi41 = l38.toBigInt\n val bi42 = box39.R4[Int].get.toBigInt\n val bi43 = box39.tokens(placeholder[Int](27))._2.toBigInt\n bi40 + box39.value.toBigInt * bi41 * bi42 / bi43 + bi43 * bi32 / bi33 * bi34 + bi41 * bi42\n )} else { bi40 }\n }) - placeholder[Int](28).toBigInt\n val bi36 = box24.R4[Int].get.toBigInt\n val bi37 = box24.value.toBigInt\n val l38 = placeholder[Long](29)\n val coll39 = box27.tokens\n val i40 = coll39.size\n val coll41 = box2.R8[Coll[Coll[Byte]]].get\n val coll42 = coll18.slice(placeholder[Int](30), coll18.size)\n val i43 = coll29.size\n val i44 = coll30.size\n sigmaProp(\n (\n (\n (\n (\n (\n (((((coll1 == coll3) && (SELF.value == box2.value)) && (SELF.tokens == box2.tokens)) && (l5 == placeholder[Long](31))) && (l7 == l8)) && (\n l9 == l10\n )\n ) && (l11 == l12)\n ) && (l13 == l14)\n ) && (l15 == l16)\n ) && (coll17 == coll18)\n ) && (coll19 == coll20)\n ) && placeholder[SigmaProp](32) || sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((coll3 == coll1) && ((coll18 == coll17) && (coll20 == coll19))) && (\n coll25(placeholder[Int](33))._2.toBigInt * bi35 * bi36 / bi37 + bi37 * bi32 / bi33 * bi34 + bi35 * bi36 == coll4(\n placeholder[Int](34)\n ).toBigInt\n )\n ) && (max(min(coll4(placeholder[Int](35)), placeholder[Long](36)), placeholder[Long](37)) == placeholder[Long](38))\n ) && (bi28 * l38.toBigInt * coll20(placeholder[Int](39)).toBigInt / bi35 + coll30.indices.fold(bi31, {(tuple45: (BigInt, Int)) =>\n val i47 = tuple45._2\n val l48 = coll30(i47)\n val bi49 = tuple45._1\n if (l48 > placeholder[Long](40)) {(\n val box50 = coll29(i47)\n val bi51 = l48.toBigInt\n val bi52 = box50.R4[Int].get.toBigInt\n val bi53 = box50.tokens(placeholder[Int](41))._2.toBigInt\n bi49 + box50.value.toBigInt * bi51 * bi52 / bi53 + bi53 * bi32 / bi33 * bi34 + bi51 * bi52 * l38.toBigInt * coll20.slice(placeholder[Int](42), coll20.size)(i47).toBigInt / bi35\n )} else { bi49 }\n }) / l38.toBigInt == max(coll4(placeholder[Int](43)), placeholder[Long](44)).toBigInt)\n ) && coll39.slice(placeholder[Int](45), i40).forall(\n {(tuple45: (Coll[Byte], Long)) => coll41.zip(coll30).exists({(tuple47: (Coll[Byte], Long)) => tuple47 == tuple45 }) }\n )\n ) && coll42.indices.forall({(i45: Int) =>\n val coll47 = coll29(i45).tokens\n (coll42(i45) == coll47(placeholder[Int](46))._1) && (coll41(i45) == coll47(placeholder[Int](47))._1)\n })\n ) && ((i43 == i44) && (i43 == coll42.size))\n ) && (i44 == coll41.size)\n ) && (coll30.filter({(l45: Long) => l45 == placeholder[Long](48) }).size == i44 - i40 - placeholder[Int](49))\n ) && (coll6(placeholder[Int](50)) == max(l5, placeholder[Long](51)))\n ) && (l7 == max(l8, placeholder[Long](52)))\n ) && (l9 == max(l10, placeholder[Long](53)))\n ) && (l11 == max(l12, placeholder[Long](54)))\n ) && (l15 == max(min(l16, placeholder[Long](55)), placeholder[Long](56)))\n ) && (l13 == max(l14, placeholder[Long](57)))\n ) && (coll6(placeholder[Int](58)) == max(coll4(placeholder[Int](59)), placeholder[Long](60)))\n ) && (coll25(placeholder[Int](61))._1 == coll18(placeholder[Int](62)))\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "3c4bd1d515fd887189eafab63df87bf0638e667a77ac41361c4d93094f333b1e",
"index": 0,
"amount": 1,
"name": "Logic NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1a012046463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
},
"R6": {
"serializedValue": "1101f015",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1400]"
},
"R8": {
"serializedValue": "1a00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[]"
},
"R7": {
"serializedValue": "1100",
"sigmaType": "Coll[SLong]",
"renderedValue": "[]"
},
"R9": {
"serializedValue": "10020402",
"sigmaType": "Coll[SInt]",
"renderedValue": "[2,1]"
},
"R4": {
"serializedValue": "110a80a0b787e905a6c1ed0bb6163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,12431443,1435,30,15000000,8,0,50,15,20000000]"
}
},
"spentTransactionId": "ec8715212bcc632ed947b7ebdf939b8ca6286d56cd8067c58cd629b974f5c11e",
"mainChain": true
},
{
"boxId": "7afe85d4f02dcdcecc9a6bc8384e062e6b72404a99f3980ccf823aa73edd037e",
"transactionId": "4d38c9e6575746266f4f18ec53b26c4e2f7e24d0fb9d01f81e3b38b93097e035",
"blockId": "4d257ff406e72f15baee973e316a2b8f652e52c5ea16af00376095e0f2c91ee0",
"value": 2000000,
"index": 5,
"globalIndex": 52997587,
"creationHeight": 1700801,
"settlementHeight": 1700804,
"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": "7ec4db998028c36e64c1436bc20d7f3b22c514f9da4e7d09a17228e63aad1c7e",
"mainChain": true
}
],
"size": 4807,
"isUnconfirmed": false
}