Transaction
ID: 4adde6e13c...7838
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0036 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
219.41 ERG
Tokens:
Loading assets...
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
219.41 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0036 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 40,242
Total coins transferred: 219.41 ERG
Fees: 0.002 ERG
Fees per byte: 0.000000318 ERG
Raw Transaction Data
{
"id": "4adde6e13c3abcd962dfc852e962105d2c9445caa3bda3d6a74c47de11d27838",
"blockId": "6b7f6d0374afaab2536a6f1989d1917ef93f7cd972dd56e27e735f868811dc19",
"inclusionHeight": 1727812,
"timestamp": 1771803298523,
"index": 9,
"globalIndex": 10344652,
"numConfirmations": 40242,
"inputs": [
{
"boxId": "399d68b11ab77de71d653a2cbd3d6246fd0da84c20005d849c5f1459dbe5da0e",
"value": 1000000,
"index": 0,
"spendingProof": "da443b51410fff8cc8c42392ee12268144d37cdbaf9805679adc7942050b598a2e07aa4182c7664e91d0384159f94e31a061f89f4a6cb52a",
"outputBlockId": "64b75de2a3bd7a56f68b88c31acfa72718d72cdec5834ae5d9f3cb808f777e0b",
"outputTransactionId": "db6633ad389e2b047233617c522fcf5b5223b9c44a62089c8c6a1ae9a091e755",
"outputIndex": 3,
"outputGlobalIndex": 53646311,
"outputCreatedAt": 1724404,
"outputSettledAt": 1724405,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: Coll(-49,84,-61,62,-121,24,-40,-108,65,-73,-70,119,45,28,-89,-83,-91,40,-100,-2,-27,-90,-65,7,-45,-84,50,104,-95,94,-105,41)\n5: 1100000\n6: 0\n7: 0\n8: 0\n9: 0\n10: 1\n11: 1\n12: 1000\n13: 1000\n14: 0\n15: 0\n16: 0\n17: 0\n18: Coll(53,10,46,3,-60,3,80,-117,18,-119,93,-84,-8,51,-32,56,-96,-42,-109,18,-124,-123,82,47,-72,-124,-54,-21,35,-43,-103,13)\n19: 0\n20: CBigInt(10000000000000000)\n21: Coll(-80,-96,89,91,-62,-43,-103,63,48,29,93,-40,94,-114,23,64,61,77,-10,52,-73,-77,30,91,62,68,6,103,36,-21,86,109)\n22: 0\n23: 2\n24: 0\n25: 0\n26: 0\n27: false\n28: 0\n29: 0\n30: 1\n31: 1100000\n32: true\n33: false\n34: false",
"ergoTreeScript": "{\n val ge1 = SELF.R5[GroupElement].get\n val coll2 = SELF.tokens\n val box3 = OUTPUTS.filter({(box3: Box) =>\n val coll5 = box3.tokens\n (coll5.size > placeholder[Int](0)) && (coll5(placeholder[Int](1)) == coll2(placeholder[Int](2)))\n }).getOrElse(placeholder[Int](3), SELF)\n val coll4 = SELF.R4[Coll[Byte]].get\n val coll5 = SELF.R6[Coll[Long]].get\n val coll6 = SELF.R7[Coll[Byte]].get\n val coll7 = INPUTS.filter({(box7: Box) => blake2b256(box7.propositionBytes) == placeholder[Coll[Byte]](4) })\n proveDlog(ge1) || sigmaProp(\n (\n (((box3.propositionBytes == SELF.propositionBytes) && (box3.value >= SELF.value - placeholder[Long](5))) && (box3.tokens == coll2)) && (\n (\n (((box3.R4[Coll[Byte]].get == coll4) && (box3.R5[GroupElement].get == ge1)) && (box3.R6[Coll[Long]].get == coll5)) && (\n box3.R7[Coll[Byte]].get == coll6\n )\n ) && (box3.R9[Coll[Coll[Byte]]].get == SELF.R9[Coll[Coll[Byte]]].get)\n )\n ) && (box3.id != SELF.id)\n ) && sigmaProp(if (coll7.size > placeholder[Int](6)) {(\n val bi8 = OUTPUTS.filter({(box8: Box) =>\n val coll10 = box8.tokens\n (coll10.size > placeholder[Int](7)) && (coll10(placeholder[Int](8))._1 == coll6)\n })(placeholder[Int](9)).R4[Coll[Long]].get(placeholder[Int](10)).toBigInt\n val bi9 = bi8 - bi8 * coll5(placeholder[Int](11)).toBigInt / placeholder[Int](12).toBigInt\n val l10 = placeholder[Long](13)\n val box11 = coll7(placeholder[Int](14))\n val coll12 = box11.tokens\n val tuple13 = coll12(placeholder[Int](15))\n val l14 = tuple13._2\n val bi15 = l14.toBigInt * CONTEXT.dataInputs.filter({(box15: Box) =>\n val coll17 = box15.tokens\n (coll17.size > placeholder[Int](16)) && (coll17(placeholder[Int](17))._1 == placeholder[Coll[Byte]](18))\n })(placeholder[Int](19)).R5[BigInt].get / placeholder[BigInt](20)\n val coll16 = OUTPUTS.filter({(box16: Box) => blake2b256(box16.propositionBytes) == placeholder[Coll[Byte]](21) })\n val coll17 = OUTPUTS.filter({(box17: Box) => box17.propositionBytes == coll4 })\n (((bi9 * l10.toBigInt / bi15 < coll5(placeholder[Int](22)).toBigInt) || (HEIGHT.toLong >= coll5(placeholder[Int](23)))) && if (coll16.size > placeholder[Int](24)) {(\n val tuple18 = coll16(placeholder[Int](25)).tokens(placeholder[Int](26))\n (tuple18._1 == tuple13._1) && (tuple18._2 == l14)\n )} else { placeholder[Boolean](27) }) && if ((coll17.size > placeholder[Int](28)) && (bi9 > bi15)) {(\n val box18 = coll17(placeholder[Int](29))\n val bi19 = bi9 - bi15 * l10.toBigInt / bi9\n val coll20 = box18.tokens\n val coll21 = coll12.slice(placeholder[Int](30), coll12.size)\n ((box18.value.toBigInt >= box11.value.toBigInt * bi19 / l10.toBigInt - placeholder[Long](31).toBigInt) && (coll20.size == coll21.size)) && coll21.zip(coll20).forall({(tuple22: ((Coll[Byte], Long), (Coll[Byte], Long))) =>\n val tuple24 = tuple22._2\n val tuple25 = tuple22._1\n (tuple24._1 == tuple25._1) && (tuple24._2.toBigInt >= tuple25._2.toBigInt * bi19 / l10.toBigInt)\n })\n )} else { if (bi9 <= bi15) { placeholder[Boolean](32) } else { placeholder[Boolean](33) } }\n )} else { placeholder[Boolean](34) })\n}",
"address": "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",
"assets": [
{
"tokenId": "c598b2a33c6dfe9eae2ee291072195d9af02025630ff5f61823a04a67eb4defe",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
},
"R6": {
"serializedValue": "1103e0126480aaea55",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1200,50,90000000]"
},
"R8": {
"serializedValue": "0e08019c6f226bafdfe7",
"sigmaType": "Coll[SByte]",
"renderedValue": "019c6f226bafdfe7"
},
"R7": {
"serializedValue": "0e201c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59",
"sigmaType": "Coll[SByte]",
"renderedValue": "1c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59"
},
"R9": {
"serializedValue": "1a0108019c6f226bafdfe7",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[019c6f226bafdfe7]"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
}
},
{
"boxId": "570bdb16912d4ce75638139e25dfcd14268b7c18c8b16d3286464706f1eaedaf",
"value": 1000000,
"index": 1,
"spendingProof": "05283c0c684f4f738ffd56537801735f0ac502cd9b6477ed0944a8cfeebc38b23275fa15097a663806c906f7d6d43e05de250a3da190b5fa",
"outputBlockId": "37a02485817d70595ae5c8acf214286d6b7f6a2846d003953ed9c42112623128",
"outputTransactionId": "37f52277fc0922ce87d45ccf767981bb89112add45821462b0fa7a88a819ef0b",
"outputIndex": 1,
"outputGlobalIndex": 53646782,
"outputCreatedAt": 1724418,
"outputSettledAt": 1724420,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-49,84,-61,62,-121,24,-40,-108,65,-73,-70,119,45,28,-89,-83,-91,40,-100,-2,-27,-90,-65,7,-45,-84,50,104,-95,94,-105,41)\n1: 0\n2: 2\n3: 1\n4: 0\n5: 0\n6: 32\n7: 32\n8: 40\n9: 2\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 2\n16: 0\n17: 0\n18: 1\n19: 0\n20: 2\n21: 2\n22: 0\n23: 0\n24: 100\n25: 10\n26: 5000000\n27: 5000000\n28: 5000000\n29: 0\n30: 0\n31: 0\n32: 0\n33: 0\n34: true\n35: 1\n36: 0\n37: 0\n38: 1000000\n39: false\n40: false\n41: false",
"ergoTreeScript": "{\n val ge1 = SELF.R7[GroupElement].get\n val coll2 = placeholder[Coll[Byte]](0)\n val coll3 = INPUTS.filter({(box3: Box) => blake2b256(box3.propositionBytes) == coll2 })\n val tuple4 = SELF.tokens(placeholder[Int](1))\n val coll5 = tuple4._1\n val coll6 = SELF.R9[Coll[Coll[Byte]]].get\n proveDlog(ge1) || sigmaProp(if (coll3.size == placeholder[Int](2)) {(\n val box7 = coll3(placeholder[Int](3))\n val box8 = coll3(placeholder[Int](4))\n if (coll3.forall({(box9: Box) =>\n val coll11 = box9.R8[Coll[Byte]].get\n (coll11.slice(placeholder[Int](5), placeholder[Int](6)) == coll5) && coll6.exists({(coll12: Coll[Byte]) => coll12 == coll11.slice(placeholder[Int](7), placeholder[Int](8)) })\n })) {(\n val i9 = placeholder[Int](9) * INPUTS.indexOf(box7, placeholder[Int](10))\n val i10 = i9 + placeholder[Int](11)\n if (OUTPUTS.size > i10) {(\n val l11 = OUTPUTS(i9 + placeholder[Int](12)).R4[Coll[Long]].get(placeholder[Int](13))\n val l12 = OUTPUTS(i10).R4[Coll[Long]].get(placeholder[Int](14))\n val box13 = OUTPUTS(placeholder[Int](15) * INPUTS.indexOf(box8, placeholder[Int](16)))\n val box14 = OUTPUTS(i9)\n val bool15 = l11 >= l12\n val bool16 = if (bool15) { placeholder[Int](17) } else { placeholder[Int](18) } == placeholder[Int](19)\n val box17 = if (bool16) { box13 } else { box14 }\n val l18 = box17.value\n val box19 = if (bool16) { box8 } else { box7 }\n val l20 = box19.value\n val l21 = if (bool15) { l11 - l12 } else { l12 - l11 }\n val l22 = if (bool15) { placeholder[Long](20) * l11 } else { placeholder[Long](21) * l12 }\n val l23 = l20 * l21 / l22\n val l24 = l20 - l23\n val box25 = if (bool16) { box14 } else { box13 }\n val box26 = if (bool16) { box7 } else { box8 }\n val l27 = box26.value + l23\n val coll28 = box17.tokens\n val coll29 = box19.tokens\n val coll30 = OUTPUTS.filter({(box30: Box) => ((box30.propositionBytes == SELF.propositionBytes) && (box30.tokens.size > placeholder[Int](22))) && (box30.tokens(placeholder[Int](23))._1 == coll5) })\n ((((if (l11 > l12) { l11 - l12 } else { l12 - l11 } * placeholder[Long](24) > placeholder[Long](25) * if (l11 < l12) { l11 } else { l12 }) && ((blake2b256(box13.propositionBytes) == coll2) && (blake2b256(box14.propositionBytes) == coll2))) && (box13.value + box14.value >= box8.value + box7.value - placeholder[Long](26))) && ((((((l18 >= l24 - placeholder[Long](27)) && (l18 <= l24)) && (box25.value >= l27)) && (box25.value <= l27 + placeholder[Long](28))) && ((coll28(placeholder[Int](29)) == coll29(placeholder[Int](30))) && (box25.tokens(placeholder[Int](31)) == box26.tokens(placeholder[Int](32))))) && coll29.indices.forall({(i31: Int) => if (i31 == placeholder[Int](33)) { placeholder[Boolean](34) } else {(\n val tuple33 = coll28(i31)\n val tuple34 = coll29(i31)\n val coll35 = tuple34._1\n val l36 = tuple34._2\n val l37 = l36 * l21 / l22\n (((tuple33._1 == coll35) && (tuple33._2 == l36 - l37)) && (box25.tokens(i31)._1 == coll35)) && (box25.tokens(i31)._2 == box26.tokens(i31)._2 + l37)\n )} }))) && ((coll30.size == placeholder[Int](35)) && \n val box31 = coll30(placeholder[Int](36))\n ((((((box31.tokens(placeholder[Int](37)) == tuple4) && (box31.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box31.R5[Coll[Coll[Byte]]].get == SELF.R5[Coll[Coll[Byte]]].get)) && (box31.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get)) && (box31.R7[GroupElement].get == ge1)) && (box31.R9[Coll[Coll[Byte]]].get == coll6)) && (box31.value >= placeholder[Long](38))\n )\n )} else { placeholder[Boolean](39) }\n )} else { placeholder[Boolean](40) }\n )} else { placeholder[Boolean](41) })\n}",
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"sigmaType": "Coll[Coll[SByte]]",
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},
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}
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(fdde03,8d151a,...)))}",
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],
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}
],
"dataInputs": [],
"outputs": [
{
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"transactionId": "4adde6e13c3abcd962dfc852e962105d2c9445caa3bda3d6a74c47de11d27838",
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"value": 1000000,
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: Coll(-49,84,-61,62,-121,24,-40,-108,65,-73,-70,119,45,28,-89,-83,-91,40,-100,-2,-27,-90,-65,7,-45,-84,50,104,-95,94,-105,41)\n5: 1100000\n6: 0\n7: 0\n8: 0\n9: 0\n10: 1\n11: 1\n12: 1000\n13: 1000\n14: 0\n15: 0\n16: 0\n17: 0\n18: Coll(53,10,46,3,-60,3,80,-117,18,-119,93,-84,-8,51,-32,56,-96,-42,-109,18,-124,-123,82,47,-72,-124,-54,-21,35,-43,-103,13)\n19: 0\n20: CBigInt(10000000000000000)\n21: Coll(-80,-96,89,91,-62,-43,-103,63,48,29,93,-40,94,-114,23,64,61,77,-10,52,-73,-77,30,91,62,68,6,103,36,-21,86,109)\n22: 0\n23: 2\n24: 0\n25: 0\n26: 0\n27: false\n28: 0\n29: 0\n30: 1\n31: 1100000\n32: true\n33: false\n34: false",
"ergoTreeScript": "{\n val ge1 = SELF.R5[GroupElement].get\n val coll2 = SELF.tokens\n val box3 = OUTPUTS.filter({(box3: Box) =>\n val coll5 = box3.tokens\n (coll5.size > placeholder[Int](0)) && (coll5(placeholder[Int](1)) == coll2(placeholder[Int](2)))\n }).getOrElse(placeholder[Int](3), SELF)\n val coll4 = SELF.R4[Coll[Byte]].get\n val coll5 = SELF.R6[Coll[Long]].get\n val coll6 = SELF.R7[Coll[Byte]].get\n val coll7 = INPUTS.filter({(box7: Box) => blake2b256(box7.propositionBytes) == placeholder[Coll[Byte]](4) })\n proveDlog(ge1) || sigmaProp(\n (\n (((box3.propositionBytes == SELF.propositionBytes) && (box3.value >= SELF.value - placeholder[Long](5))) && (box3.tokens == coll2)) && (\n (\n (((box3.R4[Coll[Byte]].get == coll4) && (box3.R5[GroupElement].get == ge1)) && (box3.R6[Coll[Long]].get == coll5)) && (\n box3.R7[Coll[Byte]].get == coll6\n )\n ) && (box3.R9[Coll[Coll[Byte]]].get == SELF.R9[Coll[Coll[Byte]]].get)\n )\n ) && (box3.id != SELF.id)\n ) && sigmaProp(if (coll7.size > placeholder[Int](6)) {(\n val bi8 = OUTPUTS.filter({(box8: Box) =>\n val coll10 = box8.tokens\n (coll10.size > placeholder[Int](7)) && (coll10(placeholder[Int](8))._1 == coll6)\n })(placeholder[Int](9)).R4[Coll[Long]].get(placeholder[Int](10)).toBigInt\n val bi9 = bi8 - bi8 * coll5(placeholder[Int](11)).toBigInt / placeholder[Int](12).toBigInt\n val l10 = placeholder[Long](13)\n val box11 = coll7(placeholder[Int](14))\n val coll12 = box11.tokens\n val tuple13 = coll12(placeholder[Int](15))\n val l14 = tuple13._2\n val bi15 = l14.toBigInt * CONTEXT.dataInputs.filter({(box15: Box) =>\n val coll17 = box15.tokens\n (coll17.size > placeholder[Int](16)) && (coll17(placeholder[Int](17))._1 == placeholder[Coll[Byte]](18))\n })(placeholder[Int](19)).R5[BigInt].get / placeholder[BigInt](20)\n val coll16 = OUTPUTS.filter({(box16: Box) => blake2b256(box16.propositionBytes) == placeholder[Coll[Byte]](21) })\n val coll17 = OUTPUTS.filter({(box17: Box) => box17.propositionBytes == coll4 })\n (((bi9 * l10.toBigInt / bi15 < coll5(placeholder[Int](22)).toBigInt) || (HEIGHT.toLong >= coll5(placeholder[Int](23)))) && if (coll16.size > placeholder[Int](24)) {(\n val tuple18 = coll16(placeholder[Int](25)).tokens(placeholder[Int](26))\n (tuple18._1 == tuple13._1) && (tuple18._2 == l14)\n )} else { placeholder[Boolean](27) }) && if ((coll17.size > placeholder[Int](28)) && (bi9 > bi15)) {(\n val box18 = coll17(placeholder[Int](29))\n val bi19 = bi9 - bi15 * l10.toBigInt / bi9\n val coll20 = box18.tokens\n val coll21 = coll12.slice(placeholder[Int](30), coll12.size)\n ((box18.value.toBigInt >= box11.value.toBigInt * bi19 / l10.toBigInt - placeholder[Long](31).toBigInt) && (coll20.size == coll21.size)) && coll21.zip(coll20).forall({(tuple22: ((Coll[Byte], Long), (Coll[Byte], Long))) =>\n val tuple24 = tuple22._2\n val tuple25 = tuple22._1\n (tuple24._1 == tuple25._1) && (tuple24._2.toBigInt >= tuple25._2.toBigInt * bi19 / l10.toBigInt)\n })\n )} else { if (bi9 <= bi15) { placeholder[Boolean](32) } else { placeholder[Boolean](33) } }\n )} else { placeholder[Boolean](34) })\n}",
"address": "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",
"assets": [
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"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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"R6": {
"serializedValue": "1103a09c016480aaea55",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000,50,90000000]"
},
"R8": {
"serializedValue": "0e08019c6f226bafdfe7",
"sigmaType": "Coll[SByte]",
"renderedValue": "019c6f226bafdfe7"
},
"R7": {
"serializedValue": "0e201c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59",
"sigmaType": "Coll[SByte]",
"renderedValue": "1c72a845195aea10ae9ac073cec4a83fb9c246746e7ee14d008c32bc9d2a0e59"
},
"R9": {
"serializedValue": "1a0108019c6f226bafdfe7",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[019c6f226bafdfe7]"
},
"R4": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
}
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"spentTransactionId": "462c521ff33f9ee5f3cc4a95b1395d8c82fff9dc4cf9c68fbbcea9d2e0341ab3",
"mainChain": true
},
{
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"transactionId": "4adde6e13c3abcd962dfc852e962105d2c9445caa3bda3d6a74c47de11d27838",
"blockId": "6b7f6d0374afaab2536a6f1989d1917ef93f7cd972dd56e27e735f868811dc19",
"value": 1000000,
"index": 1,
"globalIndex": 53741779,
"creationHeight": 1727809,
"settlementHeight": 1727812,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-49,84,-61,62,-121,24,-40,-108,65,-73,-70,119,45,28,-89,-83,-91,40,-100,-2,-27,-90,-65,7,-45,-84,50,104,-95,94,-105,41)\n1: 0\n2: 2\n3: 1\n4: 0\n5: 0\n6: 32\n7: 32\n8: 40\n9: 2\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 2\n16: 0\n17: 0\n18: 1\n19: 0\n20: 2\n21: 2\n22: 0\n23: 0\n24: 100\n25: 10\n26: 5000000\n27: 5000000\n28: 5000000\n29: 0\n30: 0\n31: 0\n32: 0\n33: 0\n34: true\n35: 1\n36: 0\n37: 0\n38: 1000000\n39: false\n40: false\n41: false",
"ergoTreeScript": "{\n val ge1 = SELF.R7[GroupElement].get\n val coll2 = placeholder[Coll[Byte]](0)\n val coll3 = INPUTS.filter({(box3: Box) => blake2b256(box3.propositionBytes) == coll2 })\n val tuple4 = SELF.tokens(placeholder[Int](1))\n val coll5 = tuple4._1\n val coll6 = SELF.R9[Coll[Coll[Byte]]].get\n proveDlog(ge1) || sigmaProp(if (coll3.size == placeholder[Int](2)) {(\n val box7 = coll3(placeholder[Int](3))\n val box8 = coll3(placeholder[Int](4))\n if (coll3.forall({(box9: Box) =>\n val coll11 = box9.R8[Coll[Byte]].get\n (coll11.slice(placeholder[Int](5), placeholder[Int](6)) == coll5) && coll6.exists({(coll12: Coll[Byte]) => coll12 == coll11.slice(placeholder[Int](7), placeholder[Int](8)) })\n })) {(\n val i9 = placeholder[Int](9) * INPUTS.indexOf(box7, placeholder[Int](10))\n val i10 = i9 + placeholder[Int](11)\n if (OUTPUTS.size > i10) {(\n val l11 = OUTPUTS(i9 + placeholder[Int](12)).R4[Coll[Long]].get(placeholder[Int](13))\n val l12 = OUTPUTS(i10).R4[Coll[Long]].get(placeholder[Int](14))\n val box13 = OUTPUTS(placeholder[Int](15) * INPUTS.indexOf(box8, placeholder[Int](16)))\n val box14 = OUTPUTS(i9)\n val bool15 = l11 >= l12\n val bool16 = if (bool15) { placeholder[Int](17) } else { placeholder[Int](18) } == placeholder[Int](19)\n val box17 = if (bool16) { box13 } else { box14 }\n val l18 = box17.value\n val box19 = if (bool16) { box8 } else { box7 }\n val l20 = box19.value\n val l21 = if (bool15) { l11 - l12 } else { l12 - l11 }\n val l22 = if (bool15) { placeholder[Long](20) * l11 } else { placeholder[Long](21) * l12 }\n val l23 = l20 * l21 / l22\n val l24 = l20 - l23\n val box25 = if (bool16) { box14 } else { box13 }\n val box26 = if (bool16) { box7 } else { box8 }\n val l27 = box26.value + l23\n val coll28 = box17.tokens\n val coll29 = box19.tokens\n val coll30 = OUTPUTS.filter({(box30: Box) => ((box30.propositionBytes == SELF.propositionBytes) && (box30.tokens.size > placeholder[Int](22))) && (box30.tokens(placeholder[Int](23))._1 == coll5) })\n ((((if (l11 > l12) { l11 - l12 } else { l12 - l11 } * placeholder[Long](24) > placeholder[Long](25) * if (l11 < l12) { l11 } else { l12 }) && ((blake2b256(box13.propositionBytes) == coll2) && (blake2b256(box14.propositionBytes) == coll2))) && (box13.value + box14.value >= box8.value + box7.value - placeholder[Long](26))) && ((((((l18 >= l24 - placeholder[Long](27)) && (l18 <= l24)) && (box25.value >= l27)) && (box25.value <= l27 + placeholder[Long](28))) && ((coll28(placeholder[Int](29)) == coll29(placeholder[Int](30))) && (box25.tokens(placeholder[Int](31)) == box26.tokens(placeholder[Int](32))))) && coll29.indices.forall({(i31: Int) => if (i31 == placeholder[Int](33)) { placeholder[Boolean](34) } else {(\n val tuple33 = coll28(i31)\n val tuple34 = coll29(i31)\n val coll35 = tuple34._1\n val l36 = tuple34._2\n val l37 = l36 * l21 / l22\n (((tuple33._1 == coll35) && (tuple33._2 == l36 - l37)) && (box25.tokens(i31)._1 == coll35)) && (box25.tokens(i31)._2 == box26.tokens(i31)._2 + l37)\n )} }))) && ((coll30.size == placeholder[Int](35)) && \n val box31 = coll30(placeholder[Int](36))\n ((((((box31.tokens(placeholder[Int](37)) == tuple4) && (box31.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box31.R5[Coll[Coll[Byte]]].get == SELF.R5[Coll[Coll[Byte]]].get)) && (box31.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get)) && (box31.R7[GroupElement].get == ge1)) && (box31.R9[Coll[Coll[Byte]]].get == coll6)) && (box31.value >= placeholder[Long](38))\n )\n )} else { placeholder[Boolean](39) }\n )} else { placeholder[Boolean](40) }\n )} else { placeholder[Boolean](41) })\n}",
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"assets": [
{
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"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1a0208019c6f226bafdfe708019c5f4ad40abc36",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[019c6f226bafdfe7,019c5f4ad40abc36]"
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"R6": {
"serializedValue": "0e240008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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"R8": {
"serializedValue": "1a0208019c6f226bafdfe708019c5f4ad40abc36",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[019c6f226bafdfe7,019c5f4ad40abc36]"
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"R7": {
"serializedValue": "0702fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7",
"sigmaType": "SGroupElement",
"renderedValue": "02fdde0388f38cc75ced977fafe3c6a7bf5a513e5b1f666e60b8feed3d6b7513c7"
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