Transaction
ID: 5cce96df7c...d8fa
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.006 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.205 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.006 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.203 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
4
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Transaction Details
Confirmations: 70,223
Total coins transferred: 0.212 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000181 ERG
Raw Transaction Data
{
"id": "5cce96df7cdb554cdbcbbada13ef862d223cbcf4d504059d8317656114dcd8fa",
"blockId": "1bb580d0440bd22a100e90271b10ac1f0f352388eac8891f9a93959cdc7327d6",
"inclusionHeight": 1691358,
"timestamp": 1767395720952,
"index": 5,
"globalIndex": 10078909,
"numConfirmations": 70223,
"inputs": [
{
"boxId": "100b4c35c9328e0e8007d45ce095e4cf9b13a4cd69c795ffa439e0d7af48a76f",
"value": 6000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "38805b85328000ec369d0a1459f9f2df32b5d49c0b374cfa2da2e26e2f5851f4",
"outputTransactionId": "44ac4127c276191afe30dc28533371aecd566fb4c1ea55a91eb1ad80c4a88e88",
"outputIndex": 0,
"outputGlobalIndex": 52706681,
"outputCreatedAt": 1691330,
"outputSettledAt": 1691332,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 1\n5: 1\n6: 2\n7: 2\n8: 3\n9: 3\n10: 1000000\n11: CBigInt(1000000000000000)\n12: 9000000000000000\n13: 0\n14: 0\n15: Coll(122,87,-29,28,-113,-125,-2,-73,115,39,-36,-56,79,5,93,85,59,-3,-121,48,51,-2,84,-7,35,85,-67,-125,-55,114,75,-96)\n16: 0\n17: CBigInt(10000000000000000)\n18: 9000000000000000\n19: 0\n20: 0\n21: Coll(126,-74,102,121,95,-10,67,-71,117,-94,-3,49,10,26,-99,87,74,-97,82,-124,124,112,110,-3,-74,-14,26,51,123,-68,-69,77)\n22: 0\n23: 0\n24: -1\n25: Coll(68,37,63,-13,94,-62,-16,-85,-104,101,-118,54,2,105,51,-94,6,-76,56,78,89,-10,10,96,-77,-72,-93,-18,-13,126,-111,53)\n26: 9000000000000010\n27: 9000000000000010\n28: 0\n29: 0\n30: 0\n31: 0\n32: 2\n33: 1\n34: 3\n35: 1000000\n36: 4\n37: 5\n38: false\n39: 0\n40: 0\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 6\n47: 2\n48: 4\n49: 0\n50: -1\n51: 100000000\n52: 1\n53: 1000\n54: 0\n55: 0\n56: 0\n57: 1\n58: 4000000\n59: 0\n60: 1\n61: 3\n62: 2\n63: 5\n64: 3\n65: 4\n66: 5\n67: 6\n68: 7\n69: 7\n70: 8\n71: 9\n72: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val box2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == coll1(placeholder[Int](2)))\n })(placeholder[Int](3))\n val coll3 = box2.tokens\n val tuple4 = coll3(placeholder[Int](4))\n val tuple5 = coll1(placeholder[Int](5))\n val tuple6 = coll3(placeholder[Int](6))\n val tuple7 = coll1(placeholder[Int](7))\n val coll8 = tuple7._1\n val tuple9 = coll3(placeholder[Int](8))\n val tuple10 = coll1(placeholder[Int](9))\n val coll11 = tuple10._1\n val bool12 = (\n (\n (\n (\n (\n (\n (\n (\n (((box2.propositionBytes == SELF.propositionBytes) && (tuple4._1 == tuple5._1)) && (tuple6._1 == coll8)) && (\n box2.value >= placeholder[Long](10)\n )\n ) && (tuple9._1 == coll11)\n ) && (coll3.size == coll1.size)\n ) && box2.R4[Boolean].get\n ) && box2.R5[Boolean].get\n ) && box2.R6[Boolean].get\n ) && box2.R7[Boolean].get\n ) && box2.R8[Boolean].get\n ) && box2.R9[Boolean].get\n val bi13 = placeholder[BigInt](11)\n val l14 = tuple9._2\n val l15 = tuple6._2\n val l16 = placeholder[Long](12) - l15\n val coll17 = CONTEXT.dataInputs\n val bi18 = coll17.filter({(box18: Box) =>\n val coll20 = box18.tokens\n (coll20.size > placeholder[Int](13)) && (coll20(placeholder[Int](14))._1 == placeholder[Coll[Byte]](15))\n })(placeholder[Int](16)).R5[BigInt].get\n val bi19 = placeholder[BigInt](17)\n val bi20 = l16.toBigInt * bi18 / bi19\n val l21 = tuple10._2\n val l22 = tuple7._2\n val l23 = placeholder[Long](18) - l22\n val box24 = coll17.filter({(box24: Box) =>\n val coll26 = box24.tokens\n (coll26.size > placeholder[Int](19)) && (coll26(placeholder[Int](20))._1 == placeholder[Coll[Byte]](21))\n })(placeholder[Int](22))\n val coll25 = box24.R5[Coll[Byte]].get\n val coll26 = OUTPUTS.filter({(box26: Box) => box26.propositionBytes == coll25 })\n val coll27 = box24.R6[Coll[Long]].get\n val l28 = l14 - l21\n val bool29 = l28 > placeholder[Long](23)\n val l30 = if (bool29) { l28 } else { l28 * placeholder[Long](24) }\n val bool31 = tuple4 == tuple5\n val l32 = l16 - l23\n val coll33 = OUTPUTS.filter({(box33: Box) => blake2b256(box33.propositionBytes) == placeholder[Coll[Byte]](25) })\n sigmaProp(\n (\n (\n (\n (bool12 && (tuple6 == tuple7)) && (\n bi13 * l14.toBigInt + bi20 / placeholder[Long](26) - tuple4._2.toBigInt > bi13 * l21.toBigInt + l23.toBigInt * bi18 / bi19 / placeholder[Long](\n 27\n ) - tuple5._2.toBigInt\n )\n ) && if (coll26.size > placeholder[Int](28)) {(\n val box34 = coll26(placeholder[Int](29))\n val tuple35 = box34.tokens(placeholder[Int](30))\n val l36 = coll27(placeholder[Int](31))\n val l37 = coll27(placeholder[Int](32))\n val l38 = coll27(placeholder[Int](33))\n val l39 = coll27(placeholder[Int](34))\n ((box34.propositionBytes == coll25) && (box34.value >= placeholder[Long](35))) && (\n (\n tuple35._2 >= max(\n if (l30 <= l36) { l30 / l37 } else {\n if (l30 <= l38) { l30 - l36 / l39 + l36 / l37 } else { l30 - l38 - l36 / coll27(placeholder[Int](36)) + l38 / l39 + l36 / l37 }\n }, coll27(placeholder[Int](37))\n )\n ) && (tuple35._1 == coll11)\n )\n )} else { placeholder[Boolean](38) }\n ) || (((bool12 && bool31) && bool29) && (l32 < placeholder[Long](39)))\n ) || if (coll33.size > placeholder[Int](40)) {(\n val box34 = coll33(placeholder[Int](41))\n val tuple35 = box34.tokens(placeholder[Int](42))\n val l36 = tuple35._2\n val bi37 = l36.toBigInt * bi18 / bi19\n val box38 = OUTPUTS.filter({(box38: Box) =>\n val coll40 = box38.tokens\n (coll40.size > placeholder[Int](43)) && box24.R4[Coll[Coll[Byte]]].get.exists({(coll41: Coll[Byte]) => (coll40(placeholder[Int](44))._1 == coll41) && (coll41 == box34.R7[Coll[Byte]].get) })\n })(placeholder[Int](45))\n val coll39 = box38.R4[Coll[Long]].get\n val l40 = coll39(placeholder[Int](46))\n val l41 = coll39(placeholder[Int](47))\n val l42 = box34.value\n val l43 = coll39(placeholder[Int](48))\n val coll44 = box34.R9[Coll[Long]].get\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((bool12 && bool31) && (l36 + l15 == l22)) && (l28 < placeholder[Long](49))) && (\n (l28 * placeholder[Long](50).toBigInt == bi37) && (bi37 >= l40.toBigInt)\n )\n ) && (l32 == l36)\n ) && (tuple35._1 == coll8)\n ) && (box34.R6[Long].get == placeholder[Long](51))\n ) && (coll39(placeholder[Int](52)).toBigInt >= bi37 * l41.toBigInt / placeholder[Int](53).toBigInt)\n ) && (bi20 < coll39(placeholder[Int](54)).toBigInt)\n ) && (\n OUTPUTS.map({(box45: Box) => box45.id }).indexOf(box34.id, placeholder[Int](55)) == box38.R9[Coll[Int]].get(placeholder[Int](56)) - placeholder[\n Int\n ](57)\n )\n ) && ((l42 > placeholder[Long](58)) && (l42 >= l43))\n ) && (\n (\n (\n (\n (\n (\n ((coll44(placeholder[Int](59)) == l41) && (coll44(placeholder[Int](60)) == coll39(placeholder[Int](61)))) && (\n coll44(placeholder[Int](62)) == coll39(placeholder[Int](63))\n )\n ) && (coll44(placeholder[Int](64)) == l43)\n ) && (coll44(placeholder[Int](65)) == l40)\n ) && (coll44(placeholder[Int](66)) >= HEIGHT.toLong)\n ) && (coll44(placeholder[Int](67)) == coll39(placeholder[Int](68)))\n ) && (coll44(placeholder[Int](69)) == coll39(placeholder[Int](70)))\n )\n ) && (bi37 <= coll39(placeholder[Int](71)).toBigInt)\n )} else { placeholder[Boolean](72) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "160056fb797d5393b622547da4db3afa794cbf9ed3911a4d7b65ed8fcb478e01",
"index": 0,
"amount": 1,
"name": "Pool NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "57d9d8d062dd1474a806224871d2fa2a90ee90c112231824bb008efd9a63fbff",
"index": 1,
"amount": 8999999988000001,
"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "7811e443e2fe94a73a11929c7ee3b303be397287be3c07dd8f15696acd5a0fdd",
"index": 2,
"amount": 9000000000000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "089990451bb430f05a85f4ef3bcb6ebf852b3d6ee68d86d78658b9ccef20074f",
"index": 3,
"amount": 12000015,
"name": "QUACKS",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R6": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R8": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R7": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R9": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R4": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
}
}
},
{
"boxId": "a2567cab611e5e448a70ec0385f4ee330c2dcaab8e111299941520e684537dda",
"value": 205000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "7802a30cfeb777a99e81413d865184f1a6e0862790c9493d954bf51cfbbb4ce9",
"outputTransactionId": "010fbe9fd6804b5599529996cc6ff43082b3885103c385e351fb482dbace0ecf",
"outputIndex": 0,
"outputGlobalIndex": 52706800,
"outputCreatedAt": 1691332,
"outputSettledAt": 1691333,
"ergoTree": "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",
"ergoTreeConstants": "0: 3\n1: 0\n2: 1000000\n3: 1\n4: 2\n5: 0\n6: Coll(68,37,63,-13,94,-62,-16,-85,-104,101,-118,54,2,105,51,-94,6,-76,56,78,89,-10,10,96,-77,-72,-93,-18,-13,126,-111,53)\n7: 1000000\n8: 1000000\n9: 1\n10: 1\n11: Coll(120,17,-28,67,-30,-2,-108,-89,58,17,-110,-100,126,-29,-77,3,-66,57,114,-121,-66,60,7,-35,-113,21,105,106,-51,90,15,-35)\n12: 0\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: 5\n15: 10\n16: 0\n17: 0\n18: Coll(22,0,86,-5,121,125,83,-109,-74,34,84,125,-92,-37,58,-6,121,76,-65,-98,-45,-111,26,77,123,101,-19,-113,-53,71,-114,1)\n19: 0\n20: 0",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Byte]].get\n val coll2 = SELF.R5[Coll[Long]].get\n val ge3 = SELF.R9[GroupElement].get\n sigmaProp(if (OUTPUTS.size < placeholder[Int](0)) {(\n val box4 = OUTPUTS(placeholder[Int](1))\n (((box4.propositionBytes == coll1) && (SELF.value - box4.value <= placeholder[Long](2))) && (box4.R4[Coll[Byte]].get == SELF.id)) && (HEIGHT >= SELF.R6[Int].get)\n )} else {(\n val box4 = OUTPUTS(placeholder[Int](3))\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box4.tokens\n val tuple7 = coll6(placeholder[Int](5))\n (((((((((((blake2b256(box4.propositionBytes) == placeholder[Coll[Byte]](6)) && (box5.propositionBytes == coll1)) && ((box4.value == SELF.value - placeholder[Long](7) - placeholder[Long](8)) && (coll6.slice(placeholder[Int](9), coll6.size) == SELF.tokens))) && (((coll2(placeholder[Int](10)) >= tuple7._2) && (tuple7._1 == placeholder[Coll[Byte]](11))) && (box5.tokens(placeholder[Int](12))._1 == placeholder[Coll[Byte]](13)))) && (box4.R4[Coll[Byte]].get == coll1)) && (box4.R8[Coll[Byte]].get == SELF.R7[Coll[Byte]].get)) && (box4.R9[Coll[Long]].get(placeholder[Int](14)) <= HEIGHT + placeholder[Int](15).toLong)) && (SELF.R8[Coll[Byte]].get == box4.R7[Coll[Byte]].get)) && (ge3 == box4.R5[GroupElement].get)) && (INPUTS(placeholder[Int](16)).tokens(placeholder[Int](17))._1 == placeholder[Coll[Byte]](18))) && (box5.tokens(placeholder[Int](19))._2 == coll2(placeholder[Int](20)))) && (box5.R4[Coll[Byte]].get == SELF.id)\n )}) || proveDlog(ge3)\n}",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "110680a4e80380a4e803b6163c108087a70e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[4000000,4000000,1435,30,8,15000000]"
},
"R6": {
"serializedValue": "04a2bbce01",
"sigmaType": "SInt",
"renderedValue": "1691345"
},
"R8": {
"serializedValue": "0e208380bb138bdbf80fe0cd938ffdd888bf9f98908255032c97e58f8d3e66e82c08",
"sigmaType": "Coll[SByte]",
"renderedValue": "8380bb138bdbf80fe0cd938ffdd888bf9f98908255032c97e58f8d3e66e82c08"
},
"R7": {
"serializedValue": "0e24b991e9c025e45d3958871e64ba8e27c415ff5aaf41546442d91e7521d0eab5650a0a0a0a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b991e9c025e45d3958871e64ba8e27c415ff5aaf41546442d91e7521d0eab5650a0a0a0a"
},
"R9": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
}
},
{
"boxId": "6d37e144b04fed8346a20a23fc01167764ca70e17394d75d076d838668a257c6",
"value": 1000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "b973a3a2776a12b6c8161a62443631bac0b2f13831d9b70aa303938ad7d3eb0f",
"outputTransactionId": "f531d66a6a4ad2dbb410164336d53c1a20b86d6f984688e9bf343b4ced433d2f",
"outputIndex": 3,
"outputGlobalIndex": 52694227,
"outputCreatedAt": 1691013,
"outputSettledAt": 1691015,
"ergoTree": "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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": "8380bb138bdbf80fe0cd938ffdd888bf9f98908255032c97e58f8d3e66e82c08",
"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": "110a80a0b787e905fe99f10ab6163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,11413119,1435,30,15000000,8,0,50,15,20000000]"
}
}
}
],
"dataInputs": [
{
"boxId": "8fb367fb070cd857568326b07b35b74788e0c5a03f45faad1d6f548a930dbbfd",
"value": 1000000,
"index": 0,
"outputBlockId": "5b1371b78e9b10928f03f80e5aca6894fadd8c72fe43177255089c1021916d50",
"outputTransactionId": "e92eba0251fa471d7ad77785ae9326482a2960cee85bc26b315ade1f94de5621",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "05daaace01",
"sigmaType": "SLong",
"renderedValue": "1690285"
},
"R5": {
"serializedValue": "06072386f26fc10000",
"sigmaType": "SBigInt",
"renderedValue": "CBigInt(10000000000000000)"
}
}
},
{
"boxId": "55d3b3ab8af5f36805e1e312fe645f831d95e58ff4a734f6bcbc974ea1876ec7",
"value": 1000000,
"index": 1,
"outputBlockId": "5b1371b78e9b10928f03f80e5aca6894fadd8c72fe43177255089c1021916d50",
"outputTransactionId": "6f67544234eec2bf5e4e2b7f23716a1ca274d2fe322897a09f856341744e6ce7",
"outputIndex": 0,
"ergoTree": "100208cd03dda8fe44b65ff96eb9dd442e6f10aca93f7351e96f2cbb1862c21a9055bc8b9604fdafdd09ea027300d191a37301",
"address": "5p17C57VD3UBEed82YvERS2PSQvAocXzcoEW7khEEgmaCnRgs8tbe74pc5xyX1KniEgfW1gyV9Nc",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01208380bb138bdbf80fe0cd938ffdd888bf9f98908255032c97e58f8d3e66e82c08",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[8380bb138bdbf80fe0cd938ffdd888bf9f98908255032c97e58f8d3e66e82c08]"
},
"R5": {
"serializedValue": "0e2e100208cd03f0dbaa5d7b67fac2130f5cb7166bcf4b19bee4ba88567830935d242b972fef300101ea027300d17301",
"sigmaType": "Coll[SByte]",
"renderedValue": "100208cd03f0dbaa5d7b67fac2130f5cb7166bcf4b19bee4ba88567830935d242b972fef300101ea027300d17301"
},
"R6": {
"serializedValue": "1106a01f80b518c0029003f40302",
"sigmaType": "Coll[SLong]",
"renderedValue": "[2000,200000,160,200,250,1]"
}
}
},
{
"boxId": "becf051d8426e4f6b9aab8a97a588471fefdd04b7e0cee50c81ba6d7900b0b32",
"value": 19016513405769,
"index": 2,
"outputBlockId": "b38c677fc0a3c0ef4f2a48ec5ee63b065bd271ae40ad101c0b6f65d975a9449b",
"outputTransactionId": "62d434e012c060b58f2e5f0f44ecfa096427d80565f36a9df340ca5dd3f8bc81",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04ca0f",
"sigmaType": "SInt",
"renderedValue": "997"
}
}
}
],
"outputs": [
{
"boxId": "333664fca130bb3622b4669586771aa934c76f0444c8b757d399c3249f2bce03",
"transactionId": "5cce96df7cdb554cdbcbbada13ef862d223cbcf4d504059d8317656114dcd8fa",
"blockId": "1bb580d0440bd22a100e90271b10ac1f0f352388eac8891f9a93959cdc7327d6",
"value": 6000000,
"index": 0,
"globalIndex": 52707654,
"creationHeight": 1691357,
"settlementHeight": 1691358,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 1\n5: 1\n6: 2\n7: 2\n8: 3\n9: 3\n10: 1000000\n11: CBigInt(1000000000000000)\n12: 9000000000000000\n13: 0\n14: 0\n15: Coll(122,87,-29,28,-113,-125,-2,-73,115,39,-36,-56,79,5,93,85,59,-3,-121,48,51,-2,84,-7,35,85,-67,-125,-55,114,75,-96)\n16: 0\n17: CBigInt(10000000000000000)\n18: 9000000000000000\n19: 0\n20: 0\n21: Coll(126,-74,102,121,95,-10,67,-71,117,-94,-3,49,10,26,-99,87,74,-97,82,-124,124,112,110,-3,-74,-14,26,51,123,-68,-69,77)\n22: 0\n23: 0\n24: -1\n25: Coll(68,37,63,-13,94,-62,-16,-85,-104,101,-118,54,2,105,51,-94,6,-76,56,78,89,-10,10,96,-77,-72,-93,-18,-13,126,-111,53)\n26: 9000000000000010\n27: 9000000000000010\n28: 0\n29: 0\n30: 0\n31: 0\n32: 2\n33: 1\n34: 3\n35: 1000000\n36: 4\n37: 5\n38: false\n39: 0\n40: 0\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 6\n47: 2\n48: 4\n49: 0\n50: -1\n51: 100000000\n52: 1\n53: 1000\n54: 0\n55: 0\n56: 0\n57: 1\n58: 4000000\n59: 0\n60: 1\n61: 3\n62: 2\n63: 5\n64: 3\n65: 4\n66: 5\n67: 6\n68: 7\n69: 7\n70: 8\n71: 9\n72: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val box2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1)) == coll1(placeholder[Int](2)))\n })(placeholder[Int](3))\n val coll3 = box2.tokens\n val tuple4 = coll3(placeholder[Int](4))\n val tuple5 = coll1(placeholder[Int](5))\n val tuple6 = coll3(placeholder[Int](6))\n val tuple7 = coll1(placeholder[Int](7))\n val coll8 = tuple7._1\n val tuple9 = coll3(placeholder[Int](8))\n val tuple10 = coll1(placeholder[Int](9))\n val coll11 = tuple10._1\n val bool12 = (\n (\n (\n (\n (\n (\n (\n (\n (((box2.propositionBytes == SELF.propositionBytes) && (tuple4._1 == tuple5._1)) && (tuple6._1 == coll8)) && (\n box2.value >= placeholder[Long](10)\n )\n ) && (tuple9._1 == coll11)\n ) && (coll3.size == coll1.size)\n ) && box2.R4[Boolean].get\n ) && box2.R5[Boolean].get\n ) && box2.R6[Boolean].get\n ) && box2.R7[Boolean].get\n ) && box2.R8[Boolean].get\n ) && box2.R9[Boolean].get\n val bi13 = placeholder[BigInt](11)\n val l14 = tuple9._2\n val l15 = tuple6._2\n val l16 = placeholder[Long](12) - l15\n val coll17 = CONTEXT.dataInputs\n val bi18 = coll17.filter({(box18: Box) =>\n val coll20 = box18.tokens\n (coll20.size > placeholder[Int](13)) && (coll20(placeholder[Int](14))._1 == placeholder[Coll[Byte]](15))\n })(placeholder[Int](16)).R5[BigInt].get\n val bi19 = placeholder[BigInt](17)\n val bi20 = l16.toBigInt * bi18 / bi19\n val l21 = tuple10._2\n val l22 = tuple7._2\n val l23 = placeholder[Long](18) - l22\n val box24 = coll17.filter({(box24: Box) =>\n val coll26 = box24.tokens\n (coll26.size > placeholder[Int](19)) && (coll26(placeholder[Int](20))._1 == placeholder[Coll[Byte]](21))\n })(placeholder[Int](22))\n val coll25 = box24.R5[Coll[Byte]].get\n val coll26 = OUTPUTS.filter({(box26: Box) => box26.propositionBytes == coll25 })\n val coll27 = box24.R6[Coll[Long]].get\n val l28 = l14 - l21\n val bool29 = l28 > placeholder[Long](23)\n val l30 = if (bool29) { l28 } else { l28 * placeholder[Long](24) }\n val bool31 = tuple4 == tuple5\n val l32 = l16 - l23\n val coll33 = OUTPUTS.filter({(box33: Box) => blake2b256(box33.propositionBytes) == placeholder[Coll[Byte]](25) })\n sigmaProp(\n (\n (\n (\n (bool12 && (tuple6 == tuple7)) && (\n bi13 * l14.toBigInt + bi20 / placeholder[Long](26) - tuple4._2.toBigInt > bi13 * l21.toBigInt + l23.toBigInt * bi18 / bi19 / placeholder[Long](\n 27\n ) - tuple5._2.toBigInt\n )\n ) && if (coll26.size > placeholder[Int](28)) {(\n val box34 = coll26(placeholder[Int](29))\n val tuple35 = box34.tokens(placeholder[Int](30))\n val l36 = coll27(placeholder[Int](31))\n val l37 = coll27(placeholder[Int](32))\n val l38 = coll27(placeholder[Int](33))\n val l39 = coll27(placeholder[Int](34))\n ((box34.propositionBytes == coll25) && (box34.value >= placeholder[Long](35))) && (\n (\n tuple35._2 >= max(\n if (l30 <= l36) { l30 / l37 } else {\n if (l30 <= l38) { l30 - l36 / l39 + l36 / l37 } else { l30 - l38 - l36 / coll27(placeholder[Int](36)) + l38 / l39 + l36 / l37 }\n }, coll27(placeholder[Int](37))\n )\n ) && (tuple35._1 == coll11)\n )\n )} else { placeholder[Boolean](38) }\n ) || (((bool12 && bool31) && bool29) && (l32 < placeholder[Long](39)))\n ) || if (coll33.size > placeholder[Int](40)) {(\n val box34 = coll33(placeholder[Int](41))\n val tuple35 = box34.tokens(placeholder[Int](42))\n val l36 = tuple35._2\n val bi37 = l36.toBigInt * bi18 / bi19\n val box38 = OUTPUTS.filter({(box38: Box) =>\n val coll40 = box38.tokens\n (coll40.size > placeholder[Int](43)) && box24.R4[Coll[Coll[Byte]]].get.exists({(coll41: Coll[Byte]) => (coll40(placeholder[Int](44))._1 == coll41) && (coll41 == box34.R7[Coll[Byte]].get) })\n })(placeholder[Int](45))\n val coll39 = box38.R4[Coll[Long]].get\n val l40 = coll39(placeholder[Int](46))\n val l41 = coll39(placeholder[Int](47))\n val l42 = box34.value\n val l43 = coll39(placeholder[Int](48))\n val coll44 = box34.R9[Coll[Long]].get\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((bool12 && bool31) && (l36 + l15 == l22)) && (l28 < placeholder[Long](49))) && (\n (l28 * placeholder[Long](50).toBigInt == bi37) && (bi37 >= l40.toBigInt)\n )\n ) && (l32 == l36)\n ) && (tuple35._1 == coll8)\n ) && (box34.R6[Long].get == placeholder[Long](51))\n ) && (coll39(placeholder[Int](52)).toBigInt >= bi37 * l41.toBigInt / placeholder[Int](53).toBigInt)\n ) && (bi20 < coll39(placeholder[Int](54)).toBigInt)\n ) && (\n OUTPUTS.map({(box45: Box) => box45.id }).indexOf(box34.id, placeholder[Int](55)) == box38.R9[Coll[Int]].get(placeholder[Int](56)) - placeholder[\n Int\n ](57)\n )\n ) && ((l42 > placeholder[Long](58)) && (l42 >= l43))\n ) && (\n (\n (\n (\n (\n (\n ((coll44(placeholder[Int](59)) == l41) && (coll44(placeholder[Int](60)) == coll39(placeholder[Int](61)))) && (\n coll44(placeholder[Int](62)) == coll39(placeholder[Int](63))\n )\n ) && (coll44(placeholder[Int](64)) == l43)\n ) && (coll44(placeholder[Int](65)) == l40)\n ) && (coll44(placeholder[Int](66)) >= HEIGHT.toLong)\n ) && (coll44(placeholder[Int](67)) == coll39(placeholder[Int](68)))\n ) && (coll44(placeholder[Int](69)) == coll39(placeholder[Int](70)))\n )\n ) && (bi37 <= coll39(placeholder[Int](71)).toBigInt)\n )} else { placeholder[Boolean](72) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "160056fb797d5393b622547da4db3afa794cbf9ed3911a4d7b65ed8fcb478e01",
"index": 0,
"amount": 1,
"name": "Pool NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "57d9d8d062dd1474a806224871d2fa2a90ee90c112231824bb008efd9a63fbff",
"index": 1,
"amount": 8999999988000001,
"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "7811e443e2fe94a73a11929c7ee3b303be397287be3c07dd8f15696acd5a0fdd",
"index": 2,
"amount": 8999999996000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "089990451bb430f05a85f4ef3bcb6ebf852b3d6ee68d86d78658b9ccef20074f",
"index": 3,
"amount": 8000015,
"name": "QUACKS",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R6": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R8": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R7": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R9": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
},
"R4": {
"serializedValue": "0101",
"sigmaType": "SBoolean",
"renderedValue": "true"
}
},
"spentTransactionId": "291c47d43b007a0af9c64e55fb121c3a7e52f8e94f2921f4ce2e64a83d6481db",
"mainChain": true
},
{
"boxId": "df3eed58b87ce4906965ebed934bbe643b953d2bb753a43d44396b2f4af8f89f",
"transactionId": "5cce96df7cdb554cdbcbbada13ef862d223cbcf4d504059d8317656114dcd8fa",
"blockId": "1bb580d0440bd22a100e90271b10ac1f0f352388eac8891f9a93959cdc7327d6",
"value": 203000000,
"index": 1,
"globalIndex": 52707655,
"creationHeight": 1691357,
"settlementHeight": 1691358,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-44,17,44,8,36,-116,93,38,49,-20,-62,74,-14,-64,-45,76,-120,-101,-44,10,26,-70,-85,103,-94,33,-85,-13,-73,-91,36,-19)\n3: 3\n4: 0\n5: 0\n6: 0\n7: CBigInt(10000000000000000)\n8: 0\n9: 0\n10: Coll(122,87,-29,28,-113,-125,-2,-73,115,39,-36,-56,79,5,93,85,59,-3,-121,48,51,-2,84,-7,35,85,-67,-125,-55,114,75,-96)\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: 0\n33: 1\n34: 2\n35: 0\n36: 0\n37: 0\n38: 1\n39: 0\n40: 1\n41: 10000000\n42: 1\n43: 1000000\n44: 1000\n45: 1000\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 = SELF.R9[Coll[Long]].get\n val l6 = coll5(placeholder[Int](3))\n val coll7 = SELF.tokens\n val tuple8 = coll7(placeholder[Int](4))\n val coll9 = tuple8._1\n val coll10 = SELF.R4[Coll[Byte]].get\n val ge11 = SELF.R5[GroupElement].get\n val l12 = SELF.R6[Long].get\n val coll13 = SELF.R8[Coll[Byte]].get\n val l14 = SELF.value\n val func15 = {(box15: Box) =>\n val coll17 = box15.propositionBytes\n val bool18 = coll17 == coll3\n bool18\n }\n val coll16 = OUTPUTS.filter(func15)\n val box17 = coll16.getOrElse(placeholder[Int](5), SELF)\n val coll18 = box17.tokens\n val tuple19 = coll18(placeholder[Int](6))\n val l20 = tuple19._2\n val bi21 = placeholder[BigInt](7)\n val bi22 = CONTEXT.dataInputs.filter({(box22: Box) =>\n val coll24 = box22.tokens\n (coll24.size > placeholder[Int](8)) && (coll24(placeholder[Int](9))._1 == placeholder[Coll[Byte]](10))\n })(placeholder[Int](11)).R5[BigInt].get\n val l23 = tuple8._2\n val bi24 = l23.toBigInt\n val coll25 = coll7.slice(placeholder[Int](12), coll7.size)\n val coll26 = placeholder[Coll[Byte]](13)\n val func27 = {(box27: Box) =>\n val coll29 = box27.propositionBytes\n val coll30 = blake2b256(coll29)\n val bool31 = coll30 == coll4\n bool31\n }\n val coll28 = OUTPUTS.filter(func27)\n val box29 = coll28.getOrElse(placeholder[Int](14), SELF)\n val coll30 = box29.tokens\n val tuple31 = coll30(placeholder[Int](15))\n val l32 = coll5(placeholder[Int](16))\n val bool33 = INPUTS.filter({(box33: Box) => box33.propositionBytes == coll3 }).size == placeholder[Int](17)\n val l34 = HEIGHT.toLong\n val l35 = coll5(placeholder[Int](18))\n val l36 = coll5(placeholder[Int](19))\n val l37 = l35 + l36\n val l38 = coll5(placeholder[Int](20))\n val coll39 = coll13.slice(placeholder[Int](21), placeholder[Int](22))\n val coll40 = coll13.slice(placeholder[Int](23), placeholder[Int](24))\n val l41 = coll5(placeholder[Int](25))\n val bi42 = bi24 * bi22 / bi21\n val bi43 = if (l34 < l37) {(\n val i43 = placeholder[Int](26)\n bi42 * l41.toBigInt + i43.toBigInt / i43.toBigInt\n )} else { bi42 }\n val box44 = coll28.getOrElse(placeholder[Int](27), SELF)\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](28))\n val func47 = {(box47: Box) =>\n val coll49 = box47.propositionBytes\n val coll50 = blake2b256(coll49)\n val bool51 = coll50 == coll4\n bool51\n }\n val coll48 = OUTPUTS.filter(func47)\n val box49 = coll48.getOrElse(placeholder[Int](29), SELF)\n val coll50 = box49.tokens\n val tuple51 = coll50(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func52 = func15\n val coll53 = coll16\n val func54 = func27\n val coll55 = coll28\n val box56 = coll2.getOrElse(placeholder[Int](32), SELF)\n val coll57 = box56.R4[Coll[Long]].get\n val l58 = coll57(placeholder[Int](33))\n val l59 = coll57(placeholder[Int](34))\n if (coll53.size > placeholder[Int](35)) {(\n val box60 = box17\n val bool61 = OUTPUTS.map({(box61: Box) => box61.id }).indexOf(box60.id, placeholder[Int](36)) == box56.R9[Coll[Int]].get(\n placeholder[Int](37)\n ) - placeholder[Int](38)\n val l62 = box60.value\n val coll63 = coll18\n val tuple64 = tuple19\n val coll65 = box60.R4[Coll[Byte]].get\n val ge66 = box60.R5[GroupElement].get\n val coll67 = box60.R7[Coll[Byte]].get\n val bool68 = ((((l62 >= l6) && (tuple64._1 == coll9)) && (coll65 == coll10)) && (ge66 == ge11)) && (coll67 == coll1)\n val coll69 = box60.R8[Coll[Byte]].get\n val l70 = box60.R6[Long].get\n val coll71 = box60.R9[Coll[Long]].get\n val bool72 = coll71 == coll5\n if (coll55.size > placeholder[Int](39)) {(\n val bi73 = l20.toBigInt\n val box74 = box29\n val coll75 = coll30\n val tuple76 = coll75(placeholder[Int](40))\n val tuple77 = tuple31\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool68 && bool61) && (coll13 == coll69)) && (l62 >= l14)) && (l62 <= l14 + placeholder[Long](41))) && (\n bi73 >= bi24 - tuple76._2.toBigInt * bi21 / bi22\n )\n ) && (coll63.slice(placeholder[Int](42), coll63.size) == coll25)\n ) && (l70 == l12)\n ) && bool72\n ) && (((box74.value >= placeholder[Long](43)) && (tuple77._1 == coll9)) && (tuple76._1 == coll26))\n ) && (tuple77._2 == l23 - l20)\n ) && (l58.toBigInt >= bi73 * bi22 / bi21 * l32.toBigInt / placeholder[Int](44).toBigInt)\n ) && bool33\n ) && (l34 >= l37)\n )\n )} else {(\n val bi73 = l58.toBigInt\n val i74 = placeholder[Int](45)\n val bi75 = l20.toBigInt * bi22 / bi21 * l32.toBigInt / i74.toBigInt\n val bool76 = bi73 >= bi75\n val prop77 = sigmaProp(INPUTS.filter({(box77: Box) =>\n val coll79 = box77.tokens\n ((coll79.size > placeholder[Int](46)) && (coll79(placeholder[Int](47))._1 == coll39)) && (box77.R9[Coll[Byte]].get == coll40)\n }).size > placeholder[Int](48)) || proveDlog(ge11)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool68 && bool61) && (coll13 == coll69)) && (l62 >= l14 - placeholder[Long](49))) && (l62 <= l14 + placeholder[Long](50))) && (\n coll63 == coll7\n )\n ) && (l70 > l34 + l38)\n ) && (l70 < l34 + l38 + placeholder[Long](51))\n ) && (bi73 < bi75)\n ) && bool72\n ) && bool33\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool68 && bool61) && (coll13 == coll69)) && (l62 >= l14 - placeholder[Long](52))) && (l62 <= l14 + placeholder[Long](53))) && (\n coll63 == coll7\n )\n ) && (l12 != placeholder[Long](54))\n ) && (l70 == placeholder[Long](55))\n ) && bool76\n ) && bool72\n ) && bool33\n ) || prop77 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool68 && bool61) && (coll13 == coll69)) && (bi73 >= bi43 * l59.toBigInt / i74.toBigInt)) && (tuple64 == tuple8)) && (\n l70 == placeholder[Long](56)\n )\n ) && bool76\n ) && ((coll71(placeholder[Int](57)) == l59) && (coll71(placeholder[Int](58)) == coll57(placeholder[Int](59))))\n ) && bool33\n ) && (coll71(placeholder[Int](60)) == l38)\n ) && (coll71(placeholder[Int](61)) == l6)\n ) && (coll71(placeholder[Int](62)) == l35)\n ) && (coll71(placeholder[Int](63)) == l41)\n ) && (coll71(placeholder[Int](64)) == l36)\n ) || prop77 && sigmaProp((((((bool68 && (l62 == l14)) && (coll63 == coll7)) && (coll65 == coll10)) && (ge66 == ge11)) && (coll67 == coll1)) && bool72)\n )}\n )} else {(\n val bi60 = l58.toBigInt\n val i61 = placeholder[Int](65)\n val box62 = box44\n val coll63 = coll45\n val tuple64 = tuple46\n val tuple65 = coll63(placeholder[Int](66))\n val coll66 = SELF.id\n val bi67 = bi60 - bi43\n val bi68 = coll5(placeholder[Int](67)).toBigInt\n val bi69 = bi67 * i61.toBigInt - bi68 / i61.toBigInt\n val l70 = tuple65._2\n sigmaProp(\n (\n (\n (\n (\n (((bi60 <= bi43 * l32.toBigInt / i61.toBigInt) && (l34 >= l12)) || (l34 > SELF.creationInfo._1.toLong + placeholder[Long](68))) && (\n (((box62.value >= placeholder[Long](69)) && (tuple64._1 == coll9)) && (tuple65._1 == coll26)) && (box62.id != coll66)\n )\n ) && (tuple64._2 == l23)\n ) && if (bi69 < placeholder[BigInt](70)) { l70.toBigInt >= bi60 } else {(\n val box71 = OUTPUTS.filter({(box71: Box) => box71.propositionBytes == coll10 }).getOrElse(placeholder[Int](71), SELF)\n val tuple72 = box71.tokens(placeholder[Int](72))\n (((l70.toBigInt >= bi43 + bi67 * bi68 / i61.toBigInt) && (tuple72._2.toBigInt >= bi69)) && (tuple72._1 == coll26)) && (box71.id != coll66)\n )}\n ) && (\n INPUTS.map({(box71: Box) => box71.id }).indexOf(coll66, placeholder[Int](73)) == box56.R9[Coll[Int]].get(placeholder[Int](74)) * placeholder[Int](\n 75\n ) - placeholder[Int](76)\n )\n ) && bool33\n )\n )}\n )} else {(\n val func52 = func47\n val coll53 = coll48\n val box54 = box49\n val coll55 = coll50\n val tuple56 = tuple51\n val tuple57 = coll55(placeholder[Int](77))\n sigmaProp(\n (\n (\n (((((box54.value >= placeholder[Long](78)) && (tuple56._1 == coll9)) && (tuple57._1 == coll26)) && (box54.id != SELF.id)) && (tuple56._2 == l23)) && (\n tuple57._2.toBigInt > bi43\n )\n ) && if (INPUTS.filter({(box58: Box) =>\n val coll60 = box58.tokens\n ((coll60.size > placeholder[Int](79)) && (coll60(placeholder[Int](80))._1 == coll39)) && (box58.R9[Coll[Byte]].get == coll40)\n }).size > placeholder[Int](81)) { placeholder[Boolean](82) } else {(\n val box58 = OUTPUTS.filter({(box58: Box) => box58.propositionBytes == coll10 }).getOrElse(placeholder[Int](83), SELF)\n ((box58.value >= l14 - placeholder[Long](84)) && (box58.tokens == coll25)) && (box58.id != SELF.id)\n )}\n ) && bool33\n )\n )}\n}",
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"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
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"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
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"creationHeight": 1691357,
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"ergoTree": "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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": "8380bb138bdbf80fe0cd938ffdd888bf9f98908255032c97e58f8d3e66e82c08",
"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": "110a80a0b787e905fe99f10ab6163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,11413119,1435,30,15000000,8,0,50,15,20000000]"
}
},
"spentTransactionId": "291c47d43b007a0af9c64e55fb121c3a7e52f8e94f2921f4ce2e64a83d6481db",
"mainChain": true
},
{
"boxId": "7f21e3ceb88b2b65dcc43886fdd8b6d29743fd3040d74b6afcdd2cfabd179c97",
"transactionId": "5cce96df7cdb554cdbcbbada13ef862d223cbcf4d504059d8317656114dcd8fa",
"blockId": "1bb580d0440bd22a100e90271b10ac1f0f352388eac8891f9a93959cdc7327d6",
"value": 1000000,
"index": 4,
"globalIndex": 52707658,
"creationHeight": 1691357,
"settlementHeight": 1691358,
"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": "bfc011c516facf95a56756964d66ec6fda628f256e084447ce4016e6e72ed6fa",
"mainChain": true
}
],
"size": 5532,
"isUnconfirmed": false
}