Transaction
ID: 205eda427c...cb1b
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.203 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.5094 ERG
Tokens:
Loading assets...
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.4 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.3104 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 71,634
Total coins transferred: 0.7134 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000413 ERG
Raw Transaction Data
{
"id": "205eda427c261ec1efe8dcfc233a52ebe300d0cf43b59c3c2c3097b1ba0ecb1b",
"blockId": "355e6eebaf2c0b6e86755269126e5a66a69a1f3cb5aaeb027db3d69e0640061e",
"inclusionHeight": 1705194,
"timestamp": 1769067016843,
"index": 16,
"globalIndex": 10182966,
"numConfirmations": 71634,
"inputs": [
{
"boxId": "b608c810a4fb2319252b78fc354c67aac3691d5e3bf0a6b6ff535199ee91137d",
"value": 203000000,
"index": 0,
"spendingProof": "ebec3a3ac3a9917e784ce10fbbeff032f62f77e098b4f44f0714a64473d5aa11c010bd4e1997595f24630d8ec6e3bfe811b080c57b4da856",
"outputBlockId": "64a2d556559e3b6fa212f181d576b6166a32b632a029c64e8c1d4e80a0f4ac52",
"outputTransactionId": "e5697711ba93c2f867ea8fac14525cb2449e2802578278cf992136026c12c43b",
"outputIndex": 1,
"outputGlobalIndex": 53118584,
"outputCreatedAt": 1705179,
"outputSettledAt": 1705182,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(26,22,4,80,-125,-72,-7,-123,90,-102,20,50,66,57,25,94,73,-8,-125,-65,11,23,75,-123,49,-65,78,-74,5,-98,30,5)\n3: 0\n4: 0\n5: 3\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(94,-85,40,-19,-25,-26,69,48,71,11,44,66,125,-107,-19,120,90,83,-55,99,-106,-63,28,24,-125,78,127,-80,-73,108,-11,83)\n12: 0\n13: 1\n14: 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)\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: 1000000\n49: 10000000\n50: 5\n51: 1000000\n52: 10000000\n53: 100000000\n54: 100000000\n55: 100000000\n56: 0\n57: 1\n58: 3\n59: 2\n60: 3\n61: 5\n62: 6\n63: 7\n64: 1000\n65: 1\n66: 1\n67: 980000\n68: 1000000\n69: CBigInt(1)\n70: 0\n71: 0\n72: 0\n73: 0\n74: -1\n75: 1\n76: 1\n77: 2000000\n78: 0\n79: 0\n80: 0\n81: true\n82: 0\n83: 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 i5 = INPUTS.indexOf(SELF, placeholder[Int](3))\n val coll6 = INPUTS.filter({(box6: Box) => box6.propositionBytes == coll3 })\n val i7 = coll6.indexOf(SELF, placeholder[Int](4))\n val coll8 = SELF.R9[Coll[Long]].get\n val l9 = coll8(placeholder[Int](5))\n val coll10 = SELF.tokens\n val tuple11 = coll10(placeholder[Int](6))\n val coll12 = tuple11._1\n val coll13 = SELF.R4[Coll[Byte]].get\n val ge14 = SELF.R5[GroupElement].get\n val l15 = SELF.R6[Long].get\n val coll16 = SELF.R8[Coll[Byte]].get\n val l17 = SELF.value\n val func18 = {(box18: Box) =>\n val coll20 = box18.propositionBytes\n val bool21 = coll20 == coll3\n bool21\n }\n val coll19 = OUTPUTS.filter(func18)\n val box20 = coll19.getOrElse(i7, SELF)\n val coll21 = box20.tokens\n val tuple22 = coll21(placeholder[Int](7))\n val l23 = tuple22._2\n val bi24 = placeholder[BigInt](8)\n val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n val coll27 = box25.tokens\n (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n })(placeholder[Int](12)).R5[BigInt].get\n val l26 = tuple11._2\n val bi27 = l26.toBigInt\n val coll28 = coll10.slice(placeholder[Int](13), coll10.size)\n val coll29 = placeholder[Coll[Byte]](14)\n val func30 = {(box30: Box) =>\n val coll32 = box30.propositionBytes\n val coll33 = blake2b256(coll32)\n val bool34 = coll33 == coll4\n bool34\n }\n val coll31 = OUTPUTS.filter(func30)\n val box32 = coll31.getOrElse(i5, SELF)\n val coll33 = box32.tokens\n val tuple34 = coll33(placeholder[Int](15))\n val l35 = coll8(placeholder[Int](16))\n val i36 = coll6.size\n val bool37 = i36 == placeholder[Int](17)\n val l38 = HEIGHT.toLong\n val l39 = coll8(placeholder[Int](18))\n val l40 = coll8(placeholder[Int](19))\n val l41 = l39 + l40\n val l42 = coll8(placeholder[Int](20))\n val coll43 = coll16.slice(placeholder[Int](21), placeholder[Int](22))\n val coll44 = coll16.slice(placeholder[Int](23), placeholder[Int](24))\n val l45 = coll8(placeholder[Int](25))\n val bi46 = bi27 * bi25 / bi24\n val bi47 = if (l38 < l41) {(\n val i47 = placeholder[Int](26)\n bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n )} else { bi46 }\n val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n val coll49 = box48.tokens\n val tuple50 = coll49(placeholder[Int](28))\n val func51 = {(box51: Box) =>\n val coll53 = box51.propositionBytes\n val coll54 = blake2b256(coll53)\n val bool55 = coll54 == coll4\n bool55\n }\n val coll52 = OUTPUTS.filter(func51)\n val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n val coll54 = box53.tokens\n val tuple55 = coll54(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func56 = func18\n val coll57 = coll19\n val i58 = coll57.size\n val func59 = func30\n val coll60 = coll31\n val box61 = coll2.getOrElse(i5, SELF)\n val coll62 = box61.R4[Coll[Long]].get\n val l63 = coll62(placeholder[Int](32))\n val l64 = coll62(placeholder[Int](33))\n if (i58 > placeholder[Int](34)) {(\n val box65 = box20\n val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n placeholder[Int](36)\n ) - placeholder[Int](37)\n val l67 = box65.value\n val coll68 = coll21\n val tuple69 = tuple22\n val coll70 = box65.R4[Coll[Byte]].get\n val ge71 = box65.R5[GroupElement].get\n val coll72 = box65.R7[Coll[Byte]].get\n val bool73 = ((((l67 >= l9) && (tuple69._1 == coll12)) && (coll70 == coll13)) && (ge71 == ge14)) && (coll72 == coll1)\n val coll74 = box65.R8[Coll[Byte]].get\n val l75 = box65.R6[Long].get\n val coll76 = box65.R9[Coll[Long]].get\n val bool77 = coll76 == coll8\n if (coll60.size > placeholder[Int](38)) {(\n val bi78 = l23.toBigInt\n val box79 = box32\n val coll80 = coll33\n val tuple81 = coll80(placeholder[Int](39))\n val tuple82 = tuple34\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (l67 >= l17)) && (l67 <= l17 + placeholder[Long](40))) && (\n bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n )\n ) && (coll68.slice(placeholder[Int](41), coll68.size) == coll28)\n ) && (l75 == l15)\n ) && bool77\n ) && (((box79.value >= placeholder[Long](42)) && (tuple82._1 == coll12)) && (tuple81._1 == coll29))\n ) && (tuple82._2 == l26 - l23)\n ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](43).toBigInt)\n ) && bool37\n ) && (l38 >= l41)\n )\n )} else {(\n val bi78 = l63.toBigInt\n val i79 = placeholder[Int](44)\n val bi80 = l23.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n val bool81 = bi78 >= bi80\n val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n val coll84 = box82.tokens\n ((coll84.size > placeholder[Int](45)) && (coll84(placeholder[Int](46))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i5) == coll44)\n }).size > placeholder[Int](47)) || proveDlog(ge14)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (l67 >= l17 - placeholder[Long](48))) && (l67 <= l17 + placeholder[Long](49))) && (\n coll68 == coll10\n )\n ) && (l75 > l38 + l42)\n ) && (l75 < l38 + l42 + placeholder[Long](50))\n ) && (bi78 < bi80)\n ) && bool77\n ) && bool37\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (l67 >= l17 - placeholder[Long](51))) && (l67 <= l17 + placeholder[Long](52))) && (\n coll68 == coll10\n )\n ) && (l15 != placeholder[Long](53))\n ) && (l75 == placeholder[Long](54))\n ) && bool81\n ) && bool77\n ) && bool37\n ) || prop82 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple11)) && (\n l75 == placeholder[Long](55)\n )\n ) && bool81\n ) && ((coll76(placeholder[Int](56)) == l64) && (coll76(placeholder[Int](57)) == coll62(placeholder[Int](58))))\n ) && (i36 == i58)\n ) && (coll76(placeholder[Int](59)) == l42)\n ) && (coll76(placeholder[Int](60)) == l9)\n ) && (coll76(placeholder[Int](61)) == l39)\n ) && (coll76(placeholder[Int](62)) == l45)\n ) && (coll76(placeholder[Int](63)) == l40)\n ) || prop82 && sigmaProp(\n ((((((bool73 && (l67 == l17)) && (coll68 == coll10)) && (coll70 == coll13)) && (ge71 == ge14)) && (coll72 == coll1)) && bool77) && (i36 == i58)\n )\n )}\n )} else {(\n val bi65 = l63.toBigInt\n val i66 = placeholder[Int](64)\n val box67 = box48\n val coll68 = coll49\n val tuple69 = tuple50\n val tuple70 = coll68(placeholder[Int](65))\n val coll71 = SELF.id\n val bi72 = bi65 - bi47\n val bi73 = coll8(placeholder[Int](66)).toBigInt\n val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n val l75 = tuple70._2\n sigmaProp(\n (\n (\n (\n (\n (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l15)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](67))) && (\n (((box67.value >= placeholder[Long](68)) && (tuple69._1 == coll12)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n )\n ) && (tuple69._2 == l26)\n ) && if (bi74 < placeholder[BigInt](69)) { l75.toBigInt >= bi65 } else {(\n val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll13 }).getOrElse(placeholder[Int](70), SELF)\n val tuple77 = box76.tokens(placeholder[Int](71))\n (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n )}\n ) && (\n INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](72)) == box61.R9[Coll[Int]].get(placeholder[Int](73)) * placeholder[Int](\n 74\n ) - placeholder[Int](75)\n )\n ) && bool37\n )\n )}\n )} else {(\n val func56 = func51\n val coll57 = coll52\n val box58 = box53\n val coll59 = coll54\n val tuple60 = tuple55\n val tuple61 = coll59(placeholder[Int](76))\n sigmaProp(\n (\n (\n (\n ((((box58.value >= placeholder[Long](77)) && (tuple60._1 == coll12)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n ) && (tuple61._2.toBigInt > bi47)\n ) && if (INPUTS.filter({(box62: Box) =>\n val coll64 = box62.tokens\n ((coll64.size > placeholder[Int](78)) && (coll64(placeholder[Int](79))._1 == coll43)) && (box62.R9[Coll[Byte]].get == coll44)\n }).size > placeholder[Int](80)) { placeholder[Boolean](81) } else {(\n val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll13 }).getOrElse(placeholder[Int](82), SELF)\n ((box62.value >= l17 - placeholder[Long](83)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n )}\n ) && bool37\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "4da927a3fee45d875e3c269a5f744dba1bfb05486a9afc6e0129a453beded1e5",
"index": 0,
"amount": 4000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R6": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R8": {
"serializedValue": "0e0100",
"sigmaType": "Coll[SByte]",
"renderedValue": "00"
},
"R7": {
"serializedValue": "0e20cd56d30b63deab7ca526f834c2aa10e0fc1ff37f079039acb62db51b65173205",
"sigmaType": "Coll[SByte]",
"renderedValue": "cd56d30b63deab7ca526f834c2aa10e0fc1ff37f079039acb62db51b65173205"
},
"R9": {
"serializedValue": "1108b6163c108087a70e00c093d001641e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1435,30,8,15000000,0,1705184,50,15]"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
}
},
{
"boxId": "3707fed30384b69dade14dbe8b1cec7145eac0ac95b42ff5b9096d76d9ae1ce9",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "64a2d556559e3b6fa212f181d576b6166a32b632a029c64e8c1d4e80a0f4ac52",
"outputTransactionId": "e5697711ba93c2f867ea8fac14525cb2449e2802578278cf992136026c12c43b",
"outputIndex": 3,
"outputGlobalIndex": 53118586,
"outputCreatedAt": 1705179,
"outputSettledAt": 1705182,
"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": [
{
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"index": 0,
"amount": 1,
"name": "Logic NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[46463b61bae37a3f2f0963798d57279167d82e17f78ccd0ccedec7e49cbdbbd1]"
},
"R6": {
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"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": "110a80a0b787e905a6c1ed0bb6163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,12431443,1435,30,15000000,8,0,50,15,20000000]"
}
}
},
{
"boxId": "5903d9e1be2cc71e21258f51b8e14acd03f897dbbe3ed157e790006cb4dd57a9",
"value": 509400000,
"index": 2,
"spendingProof": "9a3d3c798ae0ea555335fddc4081cd5b076738e33be09f8ee17717e28b381ea55e2d644b6fa5ee8b8abcd12c14d4f871aa9fa26c495cdef3",
"outputBlockId": "dc891e1275d9337e7838f500fba8e0347c7a55a76b7aa34de21d7ce3962bc3dd",
"outputTransactionId": "ae4bdb3d6ecdaffc387d1f99882fe6adab5354c3d39d087c8e255d4914dbbbb0",
"outputIndex": 1,
"outputGlobalIndex": 53117214,
"outputCreatedAt": 1705130,
"outputSettledAt": 1705134,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
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"index": 0,
"amount": 9999999,
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{
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{
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{
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{
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{
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{
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{
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{
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},
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},
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"name": "Lender Tokens",
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},
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},
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],
"additionalRegisters": {}
}
],
"dataInputs": [
{
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"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": "7b55e9391d0cb454a4ef432aebb36b818cc1556dc2b2d840cd3ee6eb5e0030a5",
"transactionId": "205eda427c261ec1efe8dcfc233a52ebe300d0cf43b59c3c2c3097b1ba0ecb1b",
"blockId": "355e6eebaf2c0b6e86755269126e5a66a69a1f3cb5aaeb027db3d69e0640061e",
"value": 400000000,
"index": 0,
"globalIndex": 53118844,
"creationHeight": 1705191,
"settlementHeight": 1705194,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(26,22,4,80,-125,-72,-7,-123,90,-102,20,50,66,57,25,94,73,-8,-125,-65,11,23,75,-123,49,-65,78,-74,5,-98,30,5)\n3: 0\n4: 0\n5: 3\n6: 0\n7: 0\n8: CBigInt(10000000000000000)\n9: 0\n10: 0\n11: Coll(94,-85,40,-19,-25,-26,69,48,71,11,44,66,125,-107,-19,120,90,83,-55,99,-106,-63,28,24,-125,78,127,-80,-73,108,-11,83)\n12: 0\n13: 1\n14: 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)\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: 1000000\n49: 10000000\n50: 5\n51: 1000000\n52: 10000000\n53: 100000000\n54: 100000000\n55: 100000000\n56: 0\n57: 1\n58: 3\n59: 2\n60: 3\n61: 5\n62: 6\n63: 7\n64: 1000\n65: 1\n66: 1\n67: 980000\n68: 1000000\n69: CBigInt(1)\n70: 0\n71: 0\n72: 0\n73: 0\n74: -1\n75: 1\n76: 1\n77: 2000000\n78: 0\n79: 0\n80: 0\n81: true\n82: 0\n83: 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 i5 = INPUTS.indexOf(SELF, placeholder[Int](3))\n val coll6 = INPUTS.filter({(box6: Box) => box6.propositionBytes == coll3 })\n val i7 = coll6.indexOf(SELF, placeholder[Int](4))\n val coll8 = SELF.R9[Coll[Long]].get\n val l9 = coll8(placeholder[Int](5))\n val coll10 = SELF.tokens\n val tuple11 = coll10(placeholder[Int](6))\n val coll12 = tuple11._1\n val coll13 = SELF.R4[Coll[Byte]].get\n val ge14 = SELF.R5[GroupElement].get\n val l15 = SELF.R6[Long].get\n val coll16 = SELF.R8[Coll[Byte]].get\n val l17 = SELF.value\n val func18 = {(box18: Box) =>\n val coll20 = box18.propositionBytes\n val bool21 = coll20 == coll3\n bool21\n }\n val coll19 = OUTPUTS.filter(func18)\n val box20 = coll19.getOrElse(i7, SELF)\n val coll21 = box20.tokens\n val tuple22 = coll21(placeholder[Int](7))\n val l23 = tuple22._2\n val bi24 = placeholder[BigInt](8)\n val bi25 = CONTEXT.dataInputs.filter({(box25: Box) =>\n val coll27 = box25.tokens\n (coll27.size > placeholder[Int](9)) && (coll27(placeholder[Int](10))._1 == placeholder[Coll[Byte]](11))\n })(placeholder[Int](12)).R5[BigInt].get\n val l26 = tuple11._2\n val bi27 = l26.toBigInt\n val coll28 = coll10.slice(placeholder[Int](13), coll10.size)\n val coll29 = placeholder[Coll[Byte]](14)\n val func30 = {(box30: Box) =>\n val coll32 = box30.propositionBytes\n val coll33 = blake2b256(coll32)\n val bool34 = coll33 == coll4\n bool34\n }\n val coll31 = OUTPUTS.filter(func30)\n val box32 = coll31.getOrElse(i5, SELF)\n val coll33 = box32.tokens\n val tuple34 = coll33(placeholder[Int](15))\n val l35 = coll8(placeholder[Int](16))\n val i36 = coll6.size\n val bool37 = i36 == placeholder[Int](17)\n val l38 = HEIGHT.toLong\n val l39 = coll8(placeholder[Int](18))\n val l40 = coll8(placeholder[Int](19))\n val l41 = l39 + l40\n val l42 = coll8(placeholder[Int](20))\n val coll43 = coll16.slice(placeholder[Int](21), placeholder[Int](22))\n val coll44 = coll16.slice(placeholder[Int](23), placeholder[Int](24))\n val l45 = coll8(placeholder[Int](25))\n val bi46 = bi27 * bi25 / bi24\n val bi47 = if (l38 < l41) {(\n val i47 = placeholder[Int](26)\n bi46 * l45.toBigInt + i47.toBigInt / i47.toBigInt\n )} else { bi46 }\n val box48 = coll31.getOrElse(placeholder[Int](27), SELF)\n val coll49 = box48.tokens\n val tuple50 = coll49(placeholder[Int](28))\n val func51 = {(box51: Box) =>\n val coll53 = box51.propositionBytes\n val coll54 = blake2b256(coll53)\n val bool55 = coll54 == coll4\n bool55\n }\n val coll52 = OUTPUTS.filter(func51)\n val box53 = coll52.getOrElse(placeholder[Int](29), SELF)\n val coll54 = box53.tokens\n val tuple55 = coll54(placeholder[Int](30))\n if (coll2.size > placeholder[Int](31)) {(\n val func56 = func18\n val coll57 = coll19\n val i58 = coll57.size\n val func59 = func30\n val coll60 = coll31\n val box61 = coll2.getOrElse(i5, SELF)\n val coll62 = box61.R4[Coll[Long]].get\n val l63 = coll62(placeholder[Int](32))\n val l64 = coll62(placeholder[Int](33))\n if (i58 > placeholder[Int](34)) {(\n val box65 = box20\n val bool66 = OUTPUTS.map({(box66: Box) => box66.id }).indexOf(box65.id, placeholder[Int](35)) == box61.R9[Coll[Int]].get(\n placeholder[Int](36)\n ) - placeholder[Int](37)\n val l67 = box65.value\n val coll68 = coll21\n val tuple69 = tuple22\n val coll70 = box65.R4[Coll[Byte]].get\n val ge71 = box65.R5[GroupElement].get\n val coll72 = box65.R7[Coll[Byte]].get\n val bool73 = ((((l67 >= l9) && (tuple69._1 == coll12)) && (coll70 == coll13)) && (ge71 == ge14)) && (coll72 == coll1)\n val coll74 = box65.R8[Coll[Byte]].get\n val l75 = box65.R6[Long].get\n val coll76 = box65.R9[Coll[Long]].get\n val bool77 = coll76 == coll8\n if (coll60.size > placeholder[Int](38)) {(\n val bi78 = l23.toBigInt\n val box79 = box32\n val coll80 = coll33\n val tuple81 = coll80(placeholder[Int](39))\n val tuple82 = tuple34\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (l67 >= l17)) && (l67 <= l17 + placeholder[Long](40))) && (\n bi78 >= bi27 - tuple81._2.toBigInt * bi24 / bi25\n )\n ) && (coll68.slice(placeholder[Int](41), coll68.size) == coll28)\n ) && (l75 == l15)\n ) && bool77\n ) && (((box79.value >= placeholder[Long](42)) && (tuple82._1 == coll12)) && (tuple81._1 == coll29))\n ) && (tuple82._2 == l26 - l23)\n ) && (l63.toBigInt >= bi78 * bi25 / bi24 * l35.toBigInt / placeholder[Int](43).toBigInt)\n ) && bool37\n ) && (l38 >= l41)\n )\n )} else {(\n val bi78 = l63.toBigInt\n val i79 = placeholder[Int](44)\n val bi80 = l23.toBigInt * bi25 / bi24 * l35.toBigInt / i79.toBigInt\n val bool81 = bi78 >= bi80\n val prop82 = sigmaProp(INPUTS.filter({(box82: Box) =>\n val coll84 = box82.tokens\n ((coll84.size > placeholder[Int](45)) && (coll84(placeholder[Int](46))._1 == coll43)) && (box82.R9[Coll[Coll[Byte]]].get(i5) == coll44)\n }).size > placeholder[Int](47)) || proveDlog(ge14)\n sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (l67 >= l17 - placeholder[Long](48))) && (l67 <= l17 + placeholder[Long](49))) && (\n coll68 == coll10\n )\n ) && (l75 > l38 + l42)\n ) && (l75 < l38 + l42 + placeholder[Long](50))\n ) && (bi78 < bi80)\n ) && bool77\n ) && bool37\n ) || sigmaProp(\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (l67 >= l17 - placeholder[Long](51))) && (l67 <= l17 + placeholder[Long](52))) && (\n coll68 == coll10\n )\n ) && (l15 != placeholder[Long](53))\n ) && (l75 == placeholder[Long](54))\n ) && bool81\n ) && bool77\n ) && bool37\n ) || prop82 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool73 && bool66) && (coll16 == coll74)) && (bi78 >= bi47 * l64.toBigInt / i79.toBigInt)) && (tuple69 == tuple11)) && (\n l75 == placeholder[Long](55)\n )\n ) && bool81\n ) && ((coll76(placeholder[Int](56)) == l64) && (coll76(placeholder[Int](57)) == coll62(placeholder[Int](58))))\n ) && (i36 == i58)\n ) && (coll76(placeholder[Int](59)) == l42)\n ) && (coll76(placeholder[Int](60)) == l9)\n ) && (coll76(placeholder[Int](61)) == l39)\n ) && (coll76(placeholder[Int](62)) == l45)\n ) && (coll76(placeholder[Int](63)) == l40)\n ) || prop82 && sigmaProp(\n ((((((bool73 && (l67 == l17)) && (coll68 == coll10)) && (coll70 == coll13)) && (ge71 == ge14)) && (coll72 == coll1)) && bool77) && (i36 == i58)\n )\n )}\n )} else {(\n val bi65 = l63.toBigInt\n val i66 = placeholder[Int](64)\n val box67 = box48\n val coll68 = coll49\n val tuple69 = tuple50\n val tuple70 = coll68(placeholder[Int](65))\n val coll71 = SELF.id\n val bi72 = bi65 - bi47\n val bi73 = coll8(placeholder[Int](66)).toBigInt\n val bi74 = bi72 * i66.toBigInt - bi73 / i66.toBigInt\n val l75 = tuple70._2\n sigmaProp(\n (\n (\n (\n (\n (((bi65 <= bi47 * l35.toBigInt / i66.toBigInt) && (l38 >= l15)) || (l38 > SELF.creationInfo._1.toLong + placeholder[Long](67))) && (\n (((box67.value >= placeholder[Long](68)) && (tuple69._1 == coll12)) && (tuple70._1 == coll29)) && (box67.id != coll71)\n )\n ) && (tuple69._2 == l26)\n ) && if (bi74 < placeholder[BigInt](69)) { l75.toBigInt >= bi65 } else {(\n val box76 = OUTPUTS.filter({(box76: Box) => box76.propositionBytes == coll13 }).getOrElse(placeholder[Int](70), SELF)\n val tuple77 = box76.tokens(placeholder[Int](71))\n (((l75.toBigInt >= bi47 + bi72 * bi73 / i66.toBigInt) && (tuple77._2.toBigInt >= bi74)) && (tuple77._1 == coll29)) && (box76.id != coll71)\n )}\n ) && (\n INPUTS.map({(box76: Box) => box76.id }).indexOf(coll71, placeholder[Int](72)) == box61.R9[Coll[Int]].get(placeholder[Int](73)) * placeholder[Int](\n 74\n ) - placeholder[Int](75)\n )\n ) && bool37\n )\n )}\n )} else {(\n val func56 = func51\n val coll57 = coll52\n val box58 = box53\n val coll59 = coll54\n val tuple60 = tuple55\n val tuple61 = coll59(placeholder[Int](76))\n sigmaProp(\n (\n (\n (\n ((((box58.value >= placeholder[Long](77)) && (tuple60._1 == coll12)) && (tuple61._1 == coll29)) && (box58.id != SELF.id)) && (tuple60._2 == l26)\n ) && (tuple61._2.toBigInt > bi47)\n ) && if (INPUTS.filter({(box62: Box) =>\n val coll64 = box62.tokens\n ((coll64.size > placeholder[Int](78)) && (coll64(placeholder[Int](79))._1 == coll43)) && (box62.R9[Coll[Byte]].get == coll44)\n }).size > placeholder[Int](80)) { placeholder[Boolean](81) } else {(\n val box62 = OUTPUTS.filter({(box62: Box) => box62.propositionBytes == coll13 }).getOrElse(placeholder[Int](82), SELF)\n ((box62.value >= l17 - placeholder[Long](83)) && (box62.tokens == coll28)) && (box62.id != SELF.id)\n )}\n ) && bool37\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "4da927a3fee45d875e3c269a5f744dba1bfb05486a9afc6e0129a453beded1e5",
"index": 0,
"amount": 4000000,
"name": "Borrow Token QUACKS - Beta-2.0",
"decimals": 9,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R6": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R8": {
"serializedValue": "0e0100",
"sigmaType": "Coll[SByte]",
"renderedValue": "00"
},
"R7": {
"serializedValue": "0e20cd56d30b63deab7ca526f834c2aa10e0fc1ff37f079039acb62db51b65173205",
"sigmaType": "Coll[SByte]",
"renderedValue": "cd56d30b63deab7ca526f834c2aa10e0fc1ff37f079039acb62db51b65173205"
},
"R9": {
"serializedValue": "110892163c108087a70e00c093d001641e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1417,30,8,15000000,0,1705184,50,15]"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
},
"spentTransactionId": "cd5525761d2187833ad2dba66a8e79399a576bde31ad8c39d82624a3e51362fb",
"mainChain": true
},
{
"boxId": "68ae4b2edde10c18349f70c0cc511a04cc2d95e2dd00fbc63d8fd5c25cc80b95",
"transactionId": "205eda427c261ec1efe8dcfc233a52ebe300d0cf43b59c3c2c3097b1ba0ecb1b",
"blockId": "355e6eebaf2c0b6e86755269126e5a66a69a1f3cb5aaeb027db3d69e0640061e",
"value": 1000000,
"index": 1,
"globalIndex": 53118845,
"creationHeight": 1705191,
"settlementHeight": 1705194,
"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": [
{
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"index": 0,
"amount": 1,
"name": "Logic NFT QUACKS - Beta-2.0",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
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"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": "10020202",
"sigmaType": "Coll[SInt]",
"renderedValue": "[1,1]"
},
"R4": {
"serializedValue": "110a80a0b787e905bea9d31792163c8087a70e1000641e80b48913",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000000,24799839,1417,30,15000000,8,0,50,15,20000000]"
}
},
"spentTransactionId": "cd5525761d2187833ad2dba66a8e79399a576bde31ad8c39d82624a3e51362fb",
"mainChain": true
},
{
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"transactionId": "205eda427c261ec1efe8dcfc233a52ebe300d0cf43b59c3c2c3097b1ba0ecb1b",
"blockId": "355e6eebaf2c0b6e86755269126e5a66a69a1f3cb5aaeb027db3d69e0640061e",
"value": 310400000,
"index": 2,
"globalIndex": 53118846,
"creationHeight": 1705191,
"settlementHeight": 1705194,
"ergoTree": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
"address": "9gSsDJixycevrHL7xxD7dr9R9G3Mi4W7LVohvK1GAjycsJc7zSy",
"assets": [
{
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"index": 0,
"amount": 9999999,
"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 1,
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"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
},
{
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"index": 2,
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"type": "EIP-004"
},
{
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"name": "Lend Token rsADA-1e",
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},
{
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"index": 4,
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"name": "Bid Token",
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"type": "EIP-004"
},
{
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},
{
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"type": "EIP-004"
},
{
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"index": 7,
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"name": "Lend Token QUACKS-2.0",
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"type": "EIP-004"
},
{
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"name": "Dummy tokens 2",
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"type": "EIP-004"
},
{
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"index": 9,
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},
{
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"name": "Lend Token QUACKS - Beta-2.0",
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},
{
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},
{
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"name": "Lender Tokens",
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"type": "EIP-004"
},
{
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},
{
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"name": "Lend Token QUACKS - Beta-2.0",
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"type": "EIP-004"
},
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},
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"decimals": 6,
"type": "EIP-004"
},
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"name": "Lend Token QUACKS - Beta-2.0",
"decimals": 2,
"type": "EIP-004"
},
{
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"name": "Duckpools Team Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 19,
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"name": "Lend Token rsBTC-1f",
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"type": "EIP-004"
},
{
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"index": 20,
"amount": 12011952,
"name": "Lend Token QUACKS-2.0",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b304affb389ff961badb8c8db77c82001bf1d8bf05bde8767fb204b100f71a8e",
"mainChain": true
},
{
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"transactionId": "205eda427c261ec1efe8dcfc233a52ebe300d0cf43b59c3c2c3097b1ba0ecb1b",
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"value": 2000000,
"index": 3,
"globalIndex": 53118847,
"creationHeight": 1705191,
"settlementHeight": 1705194,
"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",
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"additionalRegisters": {},
"spentTransactionId": "ccec5e23bf27b4ccdd4d9d87dadf9674012dd66c50ed244bf528c1833a883886",
"mainChain": true
}
],
"size": 4840,
"isUnconfirmed": false
}