Transaction
ID: 06a534c2a1...1382
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.9608518 ERG
Tokens:
Loading assets...
Outputs (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
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.9597518 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 154,644
Total coins transferred: 0.9628518 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000001266 ERG
Raw Transaction Data
{
"id": "06a534c2a1362faaef22788d0b3e0a69e616d8b56592677fd2304b3aa3ce1382",
"blockId": "84862eb6259b87c9d979ffafe72a5b950010a127b4eebed2a35d9f3235a7007b",
"inclusionHeight": 1613910,
"timestamp": 1758030900611,
"index": 1,
"globalIndex": 9485371,
"numConfirmations": 154644,
"inputs": [
{
"boxId": "4ca3df5a7f048ab1be8647f6007dc0f23f79463cb5476e7a63706bac6e55705b",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "12e196ece357371de97b86f2c045205ceab7a5410fa734cfbf0c4d58fab4b9fa",
"outputTransactionId": "5e859e93d43b746b95d40406bd5880b8e4925e4979cad1449776b4f9e2f47d39",
"outputIndex": 0,
"outputGlobalIndex": 50275964,
"outputCreatedAt": 1613318,
"outputSettledAt": 1613319,
"ergoTree": "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",
"ergoTreeConstants": "0: 3\n1: 0\n2: Coll(105,-69,41,-112,-47,96,54,47,9,-102,7,-17,93,-105,97,-73,-99,-80,29,-107,9,58,-119,119,-27,-61,-70,-47,-33,78,-5,-50)\n3: 1\n4: 4\n5: Coll(0,8,-51)\n6: 1\n7: 1\n8: 1\n9: 0\n10: 1\n11: 0\n12: 0\n13: Coll(-14,-39,92,-120,-120,58,-67,-114,-67,-72,-77,-66,-111,-22,45,23,-112,80,27,10,-54,-127,-34,40,-51,-108,-38,-118,-109,51,97,70)\n14: -1\n15: false\n16: true\n17: true\n18: 1\n19: 0\n20: 0\n21: 0\n22: 1\n23: 2\n24: 2\n25: 3\n26: 4\n27: 1\n28: false\n29: false\n30: 0\n31: Coll(47,118,46,-91,-45,7,77,49,21,-3,101,-98,-18,52,34,54,78,-78,106,-125,110,51,90,-38,-17,-46,-34,56,-2,-124,-102,-75)\n32: 0\n33: 0\n34: 2\n35: 1\n36: false\n37: 0\n38: 1\n39: 0\n40: Coll(-10,-127,-98,11,124,-7,-100,-116,120,114,-74,47,73,-123,-72,-39,0,-58,21,9,37,-48,30,-78,121,120,117,23,-88,72,-74,-40)\n41: 0\n42: 0\n43: 3\n44: 30\n45: 4\n46: 1\n47: -1\n48: -1\n49: false\n50: true\n51: 1\n52: false\n53: false\n54: 0\n55: 0\n56: 0\n57: 100\n58: 5\n59: 100\n60: 1000000\n61: 0\n62: 1000000\n63: 0\n64: 0\n65: 1000000\n66: 0\n67: 0\n68: 0\n69: 0\n70: 0\n71: true\n72: 0\n73: SigmaProp(ProveDlog(ECPoint(1bf847,c2be87,...)))\n74: true\n75: false",
"ergoTreeScript": "{\n val i1 = SELF.R4[Int].get\n val l2 = HEIGHT.toLong\n val coll3 = SELF.R7[Coll[Long]].get\n val l4 = coll3(placeholder[Int](0))\n val bool5 = l2 < l4\n val coll6 = SELF.tokens(placeholder[Int](1))._1\n val tuple7 = SELF.R5[(Coll[Byte], Coll[Byte])].get\n val coll8 = tuple7._2\n val coll9 = placeholder[Coll[Byte]](2)\n val coll10 = tuple7._1\n val coll11 = SELF.R6[Coll[Coll[Byte]]].get\n val l12 = coll3(placeholder[Int](3))\n val l13 = coll3(placeholder[Int](4))\n val tuple14 = SELF.R8[(Coll[Byte], Long)].get\n val l15 = tuple14._2\n val coll16 = placeholder[Coll[Byte]](5)\n sigmaProp(\n (i1 == placeholder[Int](6)) && (\n (if (((bool5 && (INPUTS.size > placeholder[Int](7))) && (OUTPUTS.size > placeholder[Int](8))) && (CONTEXT.dataInputs.size > placeholder[Int](9))) {(\n val box17 = INPUTS(placeholder[Int](10))\n val box18 = CONTEXT.dataInputs(placeholder[Int](11))\n val coll19 = box18.R5[Coll[Byte]].get\n val box20 = OUTPUTS(placeholder[Int](12))\n if (((blake2b256(box17.propositionBytes) == placeholder[Coll[Byte]](13)) && (box17.R6[Coll[Byte]].get == coll6)) && (((coll19 == coll8) && (blake2b256(box18.propositionBytes) == coll9)) && (box18.R6[Coll[Byte]].get == coll6))) {(\n val coll21 = box17.R9[Coll[Long]].get\n val tuple22 = (placeholder[Long](14), placeholder[Boolean](15))\n val l23 = coll21.fold(tuple22, {(tuple23: ((Long, Boolean), Long)) =>\n val tuple25 = tuple23._1\n val l26 = tuple23._2\n if (tuple25._2) { tuple25 } else { if (blake2b256(box17.R7[Coll[Byte]].get.append(longToByteArray(l26)).append(box17.R8[Coll[Byte]].get).append(coll10)) == box17.R5[Coll[Byte]].get) { (l26, placeholder[Boolean](16)) } else { tuple25 } }\n })._1\n val l24 = box18.R9[Coll[Long]].get.fold(tuple22, {(tuple24: ((Long, Boolean), Long)) =>\n val tuple26 = tuple24._1\n val l27 = tuple24._2\n if (tuple26._2) { tuple26 } else { if (blake2b256(box18.R7[Coll[Byte]].get.append(longToByteArray(l27)).append(box18.R8[Coll[Byte]].get).append(coll10)) == coll19) { (l27, placeholder[Boolean](17)) } else { tuple26 } }\n })._1\n (((((((((((((box20.propositionBytes == SELF.propositionBytes) && (box20.R4[Int].get == i1)) && (box20.tokens.size == placeholder[Int](18))) && (box20.tokens(placeholder[Int](19))._1 == coll6)) && (box20.R5[(Coll[Byte], Coll[Byte])].get == (coll10, if ((l23 > l24) || ((l23 == l24) && (box17.creationInfo._1 < box18.creationInfo._1))) { box17.R5[Coll[Byte]].get } else { coll8 }))) && (box20.R6[Coll[Coll[Byte]]].get == coll11)) && (box20.R7[Coll[Long]].get(placeholder[Int](20)) == coll3(placeholder[Int](21)))) && (box20.R7[Coll[Long]].get(placeholder[Int](22)) == l12)) && (box20.R7[Coll[Long]].get(placeholder[Int](23)) == coll3(placeholder[Int](24)))) && (box20.R7[Coll[Long]].get(placeholder[Int](25)) == l4)) && (box20.R7[Coll[Long]].get(placeholder[Int](26)) == l13 + placeholder[Long](27))) && (box20.R8[(Coll[Byte], Long)].get._2 == l15)) && (box20.R9[(Coll[Byte], Coll[Byte])].get == SELF.R9[(Coll[Byte], Coll[Byte])].get)) && OUTPUTS.exists({(box25: Box) => (((((((blake2b256(box25.propositionBytes) == coll9) && (box25.value == box17.value)) && (box25.R4[Coll[Byte]].get == box17.R4[Coll[Byte]].get)) && (box25.R5[Coll[Byte]].get == box17.R5[Coll[Byte]].get)) && (box25.R6[Coll[Byte]].get == box17.R6[Coll[Byte]].get)) && (box25.R7[Coll[Byte]].get == box17.R7[Coll[Byte]].get)) && (box25.R8[Coll[Byte]].get == box17.R8[Coll[Byte]].get)) && (box25.R9[Coll[Long]].get == coll21) })\n )} else { placeholder[Boolean](28) }\n )} else { placeholder[Boolean](29) } || if (bool5 && (CONTEXT.dataInputs.size > placeholder[Int](30))) {(\n val coll17 = CONTEXT.dataInputs\n val coll18 = coll17.filter({(box18: Box) => blake2b256(box18.propositionBytes) == placeholder[Coll[Byte]](31) })\n val i19 = coll18.size\n val i20 = coll11.size\n if (if (i19 < if (i20 == placeholder[Int](32)) { placeholder[Int](33) } else { i20 / placeholder[Int](34) + placeholder[Int](35) }) { placeholder[Boolean](36) } else {(\n val coll21 = coll18.map({(box21: Box) => box21.tokens(placeholder[Int](37))._1 })\n coll21.indices.forall({(i22: Int) => !coll21.slice(i22 + placeholder[Int](38), i19).exists({(coll24: Coll[Byte]) => coll24 == coll21(i22) }) }) && coll18.forall({(box22: Box) => (coll11.exists({(coll24: Coll[Byte]) => coll24 == box22.tokens(placeholder[Int](39))._1 }) && (box22.R4[Coll[Byte]].get == placeholder[Coll[Byte]](40))) && (box22.R5[Coll[Byte]].get == coll8) })\n )}) {(\n val box21 = OUTPUTS(placeholder[Int](41))\n val coll22 = box21.R7[Coll[Long]].get\n ((((box21.value >= SELF.value + INPUTS.filter({(box23: Box) => (blake2b256(box23.propositionBytes) == coll9) && (box23.R5[Coll[Byte]].get == coll8) })(placeholder[Int](42)).value) && (coll22(placeholder[Int](43)) >= l4 + placeholder[Long](44))) && (coll22(placeholder[Int](45)) == l13 - placeholder[Long](46))) && (box21.R5[(Coll[Byte], Coll[Byte])].get._2 == coll17.filter({(box23: Box) => blake2b256(box23.propositionBytes) == coll9 }).fold((placeholder[Long](47), Coll[Byte]()), {(tuple23: ((Long, Coll[Byte]), Box)) =>\n val box25 = tuple23._2\n val coll26 = box25.R5[Coll[Byte]].get\n val tuple27 = tuple23._1\n if (coll26 != coll8) {(\n val l28 = box25.R9[Coll[Long]].get.fold((placeholder[Long](48), placeholder[Boolean](49)), {(tuple28: ((Long, Boolean), Long)) =>\n val tuple30 = tuple28._1\n val l31 = tuple28._2\n if (tuple30._2) { tuple30 } else { if (blake2b256(box25.R7[Coll[Byte]].get.append(longToByteArray(l31)).append(box25.R8[Coll[Byte]].get).append(coll10)) == coll26) { (l31, placeholder[Boolean](50)) } else { tuple30 } }\n })._1\n if (l28 > tuple27._1) { (l28, coll26) } else { tuple27 }\n )} else { tuple27 }\n })._2)) && ((box21.R4[Int].get == i1) && (i1 == placeholder[Int](51)))\n )} else { placeholder[Boolean](52) }\n )} else { placeholder[Boolean](53) }) || if ((l2 >= l4) && (OUTPUTS.size > placeholder[Int](54))) {(\n val box17 = OUTPUTS(placeholder[Int](55))\n val coll18 = INPUTS.filter({(box18: Box) => blake2b256(box18.propositionBytes) == coll9 })\n val l19 = coll18.fold(placeholder[Long](56), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.value })\n val l20 = l19 * l15 / placeholder[Long](57)\n val l21 = l19 * placeholder[Long](58) / placeholder[Long](59)\n val l22 = l19 - l20 - l21\n val bool23 = l22 >= placeholder[Long](60)\n val l24 = if (bool23) { l21 } else { placeholder[Long](61) }\n val l25 = if ((l24 < placeholder[Long](62)) && (l24 > placeholder[Long](63))) { l24 } else { placeholder[Long](64) }\n val l26 = if (bool23) { l12 + l20 } else { l12 }\n val l27 = if ((l26 < placeholder[Long](65)) && (l26 > placeholder[Long](66))) { l26 } else { placeholder[Long](67) }\n val l28 = l26 - l27\n val l29 = l24 - l25\n (\n (\n (\n (box17.value >= if (bool23) { l22 } else { l22 + l20 + l21 } + l25 + l27) && (\n box17.propositionBytes == coll16.append(\n coll18.filter({(box30: Box) => box30.R5[Coll[Byte]].get == coll8 })(placeholder[Int](68)).R4[Coll[Byte]].get\n )\n )\n ) && (box17.tokens(placeholder[Int](69))._1 == coll6)\n ) && if (l28 > placeholder[Long](70)) {\n OUTPUTS.exists({(box30: Box) => (box30.value >= l28) && (box30.propositionBytes == coll16.append(tuple14._1)) })\n } else { placeholder[Boolean](71) }\n ) && if (l29 > placeholder[Long](72)) {\n OUTPUTS.exists({(box30: Box) => (box30.value >= l29) && (box30.propositionBytes == placeholder[SigmaProp](73).propBytes) })\n } else { placeholder[Boolean](74) }\n )} else { placeholder[Boolean](75) }\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "469632d31f1762c604fb5605f17a6a3acea25dc0c0acd9ed9c99a9657a39ef13",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "3c0e0e2035aa11186c18d3e04f81656248213a1a3c43e89a67045763287e644db60c3f2120cf1c23c763e59fd9bd1643d18a7e98576fadf4aed084adf619b2eadebc950474",
"sigmaType": "(Coll[SByte], Coll[SByte])",
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