Transaction
ID: 6abcb0c964...95fb
Inputs (6)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.779963911 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.724963912 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.644963911 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.644963912 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.2 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Confirmations: 737,806
Total coins transferred: 1.52 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000811 ERG
Raw Transaction Data
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Byte]].get\n val l2 = CONTEXT.preHeader.timestamp\n val tuple3 = SELF.R5[(Long, Long)].get\n val l4 = tuple3._1\n val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n val i6 = box5.R4[Int].get\n val coll7 = SELF.R6[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll10 = box9.tokens\n val coll11 = Coll[Byte]()\n val l12 = box9.value\n val tuple13 = (coll11, l12)\n val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n val coll15 = SELF.R7[Coll[Byte]].get\n val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll17 = box16.tokens\n val l18 = box16.value\n val tuple19 = (coll11, l18)\n val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n val box21 = OUTPUTS(placeholder[Int](9))\n allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n )} else {(\n val box21 = box9\n val coll22 = coll10\n val coll23 = coll11\n val l24 = l12\n val tuple25 = tuple13\n val tuple26 = tuple14\n val box27 = box16\n val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n val opt29 = box28.R4[Int]\n val bool30 = opt29.isDefined\n val coll31 = coll17\n val l32 = l18\n val tuple33 = tuple19\n val tuple34 = tuple20\n val tuple35 = SELF.tokens(placeholder[Int](13))\n allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n val i36 = opt29.getOrElse(placeholder[Int](16))\n if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n val i36 = opt29.get\n if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i38 = coll37.size\n coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n })\n )} else { placeholder[Boolean](39) } }\n )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
"address": "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",
"assets": [
{
"tokenId": "15cc46470cffaaccddbabd357b20c8bcecfac03efd09f0ad45d324ac08df4726",
"index": 0,
"amount": 1,
"name": "andro killer 9",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
},
"R5": {
"serializedValue": "59b2dacf839a62b2eba6918a64",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1687120639641,1719347239641]"
},
"R6": {
"serializedValue": "110380c8afa0250002",
"sigmaType": "Coll[SLong]",
"renderedValue": "[5000000000,0,1]"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
}
},
"spentTransactionId": "7a44f2c56b1ff9327ba571927b3341b9567a3089eeb95c551f9539aac178195a",
"mainChain": true
},
{
"boxId": "eb7a0770cd4d5907782cef104477e7cbde836480ebcb43a8a1149f3677963bb3",
"transactionId": "6abcb0c9644064882278ecce7da1e6ce5c6b0cbd7924cf8e79e3766ea31c95fb",
"blockId": "fb7a4b9c2260c19878746aa4fb48a3cf89345c16eb208dd0e7ee6843d763c405",
"value": 15000000,
"index": 1,
"globalIndex": 30185704,
"creationHeight": 1028633,
"settlementHeight": 1028635,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 1\n4: 2\n5: 0\n6: 1\n7: 0\n8: 3\n9: 0\n10: 3\n11: 2\n12: 1\n13: 0\n14: 0\n15: 1000\n16: 0\n17: 2\n18: 10\n19: 2\n20: 0\n21: 0\n22: 0\n23: 1000\n24: 1000\n25: 0\n26: 0\n27: 2\n28: 10\n29: 3\n30: 0\n31: 1000\n32: 2\n33: 1000\n34: 0\n35: 3\n36: 3\n37: 0\n38: 0\n39: false\n40: true\n41: false\n42: 0\n43: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Byte]].get\n val l2 = CONTEXT.preHeader.timestamp\n val tuple3 = SELF.R5[(Long, Long)].get\n val l4 = tuple3._1\n val box5 = CONTEXT.dataInputs(placeholder[Int](0))\n val i6 = box5.R4[Int].get\n val coll7 = SELF.R6[Coll[Long]].get\n val l8 = coll7(placeholder[Int](1)) - l2 - l4 / coll7(placeholder[Int](2)) * coll7(placeholder[Int](3))\n val box9 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n val coll10 = box9.tokens\n val coll11 = Coll[Byte]()\n val l12 = box9.value\n val tuple13 = (coll11, l12)\n val tuple14 = coll10.getOrElse(placeholder[Int](5), tuple13)\n val coll15 = SELF.R7[Coll[Byte]].get\n val box16 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll17 = box16.tokens\n val l18 = box16.value\n val tuple19 = (coll11, l18)\n val tuple20 = coll17.getOrElse(placeholder[Int](7), tuple19)\n proveDlog(decodePoint(coll1.slice(placeholder[Int](8), coll1.size))) || sigmaProp(if (l2 > l4) { if (l2 > tuple3._2) {(\n val box21 = OUTPUTS(placeholder[Int](9))\n allOf(Coll[Boolean](OUTPUTS.size == placeholder[Int](10), box21.tokens == SELF.tokens, box21.value >= SELF.value - placeholder[Long](11) * box5.R6[Long].get, box21.propositionBytes == coll1))\n )} else {(\n val box21 = box9\n val coll22 = coll10\n val coll23 = coll11\n val l24 = l12\n val tuple25 = tuple13\n val tuple26 = tuple14\n val box27 = box16\n val box28 = box27.R4[Box].getOrElse(OUTPUTS(OUTPUTS.size - placeholder[Int](12)))\n val opt29 = box28.R4[Int]\n val bool30 = opt29.isDefined\n val coll31 = coll17\n val l32 = l18\n val tuple33 = tuple19\n val tuple34 = tuple20\n val tuple35 = SELF.tokens(placeholder[Int](13))\n allOf(Coll[Boolean](INPUTS(placeholder[Int](14)).id == SELF.id, ((box21.propositionBytes == coll1) && (tuple26._2 >= l8 * placeholder[Int](15) - i6 - if (bool30) {(\n val i36 = opt29.getOrElse(placeholder[Int](16))\n if ((i36 < placeholder[Int](17)) || (i36 >= placeholder[Int](18))) { i36 } else { if ((i36 == placeholder[Int](19)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) { box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](20), {(tuple37: (Int, (Coll[Byte], Int))) => tuple37._1 + tuple37._2._2 }) } else { placeholder[Int](21) } }\n )} else { placeholder[Int](22) }.toLong / placeholder[Long](23))) && (tuple26._1 == coll15), ((box27.propositionBytes == box5.R5[Coll[Byte]].get) && (tuple34._2 >= l8 * i6.toLong / placeholder[Long](24))) && (tuple34._1 == coll15), tuple35 == OUTPUTS.getOrElse(placeholder[Int](25), SELF).tokens(placeholder[Int](26)), if (bool30) {(\n val i36 = opt29.get\n if ((i36 < placeholder[Int](27)) || (i36 >= placeholder[Int](28))) {(\n val box37 = OUTPUTS.getOrElse(placeholder[Int](29), SELF)\n val tuple38 = box37.tokens.getOrElse(placeholder[Int](30), (coll23, box37.value))\n ((tuple38._2 >= l8 * i36.toLong / placeholder[Long](31)) && (tuple38._1 == coll15)) && (box37.propositionBytes == box28.propositionBytes)\n )} else { if ((i36 == placeholder[Int](32)) && box28.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll37 = box28.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i38 = coll37.size\n coll37.map({(tuple39: (Coll[Byte], Int)) => (tuple39._1, tuple39._2.toLong * l8 / placeholder[Long](33)) }).slice(placeholder[Int](34), i38) == OUTPUTS.slice(placeholder[Int](35), placeholder[Int](36) + i38).map({(box39: Box) =>\n val tuple41 = box39.tokens.getOrElse(placeholder[Int](37), (coll23, box39.value))\n if (tuple41._1 == coll15) { (box39.propositionBytes, tuple41._2) } else { (coll23, placeholder[Long](38)) }\n })\n )} else { placeholder[Boolean](39) } }\n )} else { placeholder[Boolean](40) } && (blake2b256(box28.bytes) == tuple35._1)))\n )} } else { placeholder[Boolean](41) }) && sigmaProp(box5.tokens(placeholder[Int](42))._1 == placeholder[Coll[Byte]](43))\n}",
"address": "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",
"assets": [
{
"tokenId": "beeac1cb622081eae41f5fbce76906454d009f4b70c3ceacb65a14ad1fe4fd15",
"index": 0,
"amount": 1,
"name": "andro killer 8",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e240008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd02eaccb7004435f6ca3a1228125368e5ab0cdae3c36a142cf785b8b5029fba7482"
},
"R5": {
"serializedValue": "59b2dacf839a62b2eba6918a64",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1687120639641,1719347239641]"
},
"R6": {
"serializedValue": "110380c8afa0250002",
"sigmaType": "Coll[SLong]",
"renderedValue": "[5000000000,0,1]"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
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