Transaction
ID: 354a2b4f8f...9bed
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
2.02 ERG
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.01 ERG
Tokens:
Loading assets...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0022 ERG
Transaction Details
Confirmations: 8,878
Total coins transferred: 2.02 ERG
Fees: 0.0022 ERG
Fees per byte: 0.000000735 ERG
Raw Transaction Data
{
"id": "354a2b4f8fd83174769910c7facc20739feeffe660809d61fa9b6fe502ce9bed",
"blockId": "c947f0b9a59bbb4e5a9d060b436dc1b29e5a74bf977f5555080a51b9bb49aed4",
"inclusionHeight": 1749898,
"timestamp": 1774477404703,
"index": 2,
"globalIndex": 10500116,
"numConfirmations": 8878,
"inputs": [
{
"boxId": "71cb708c4c60b6295da134539c7e152674518fd501bcf0cf409bd4b062a1ad79",
"value": 2018600000,
"index": 0,
"spendingProof": "973ab398988269c0f3320ae898f7e76c66b69b3cf1da6af2c90706afbcc60d18d13bb0bf8c6ebf854bfb87ac45d7309d1a8869235e237016",
"outputBlockId": "99649e636106572ecb2611aca30e6b5317f5c318d4323ba9209727ae11cc167f",
"outputTransactionId": "4dca8ca414eb823ee23f7e6567e793f2192f5819c0dc9c19988f4cd4c550c5d1",
"outputIndex": 0,
"outputGlobalIndex": 54345160,
"outputCreatedAt": 1748559,
"outputSettledAt": 1749897,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: 0\n8: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n9: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n10: 10\n11: 4\n12: 6\n13: 1000000\n14: false\n15: 5\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 720\n26: 1\n27: 0\n28: 0\n29: 1\n30: 0\n31: 1\n32: 2\n33: 1\n34: 3\n35: 0\n36: 1000000\n37: 0\n38: 0\n39: 0\n40: 17\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 0\n48: 0\n49: 1000\n50: 100\n51: 1000\n52: 0\n53: 100\n54: 0\n55: 2\n56: 0\n57: 17\n58: 1\n59: 2\n60: 17\n61: 0\n62: 17\n63: 1000000\n64: 0\n65: 3\n66: 2000000\n67: 1\n68: 1\n69: 1\n70: 1\n71: 2\n72: 1\n73: 1000000\n74: 0\n75: 1\n76: 2\n77: 1\n78: 0\n79: false\n80: 1\n81: 3\n82: 1000000\n83: 1\n84: 1000000\n85: 1\n86: 1\n87: false\n88: 0\n89: 0\n90: 0\n91: 0\n92: 0\n93: 1000000\n94: 1000000\n95: 0\n96: 0\n97: 1000\n98: 0\n99: 17\n100: 0\n101: 17\n102: 2\n103: 1\n104: 2\n105: 0\n106: true\n107: 1\n108: 2\n109: 0\n110: true\n111: false\n112: 1\n113: 0\n114: 1\n115: 0\n116: 0\n117: 0\n118: 0\n119: 1000000\n120: 0\n121: Coll(49,-126,103,79,7,-37,-71,-115,105,109,56,-19,-91,62,99,-21,59,-11,-2,87,15,113,-34,-24,94,-71,84,-42,-49,-112,59,-70)\n122: 0\n123: 0\n124: 0\n125: true\n126: false\n127: 2\n128: false",
"ergoTreeScript": "{\n val coll1 = SELF.R9[Coll[Coll[Byte]]].get\n val prop2 = proveDlog(decodePoint(coll1(placeholder[Int](0))))\n val coll3 = SELF.tokens\n val tuple4 = (Coll[Byte](), placeholder[Long](1))\n val tuple5 = coll3.getOrElse(placeholder[Int](2), tuple4)\n val coll6 = tuple5._1\n val coll7 = SELF.R7[Coll[Byte]].get\n val bool8 = coll6 == coll7\n val bool9 = !bool8\n val box10 = OUTPUTS(placeholder[Int](3))\n val coll11 = box10.propositionBytes\n val coll12 = prop2.propBytes\n val coll13 = SELF.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = coll13(placeholder[Int](5))\n val coll16 = placeholder[Coll[Byte]](6)\n val l17 = coll13(placeholder[Int](7))\n val coll18 = placeholder[Coll[Byte]](8)\n val coll19 = placeholder[Coll[Byte]](9)\n val l20 = coll13(placeholder[Int](10))\n val l21 = coll13(placeholder[Int](11))\n val l22 = coll13(placeholder[Int](12))\n val l23 = l22 + placeholder[Long](13)\n val coll24 = SELF.R5[Coll[Byte]].get\n val bool25 = if (coll11 == SELF.propositionBytes) {\n (\n (\n (((box10.value >= l23) && (box10.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box10.R5[Coll[Byte]].get == coll24)) && (\n box10.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get\n )\n ) && (box10.R8[Coll[Long]].get == coll13)\n ) && (box10.R9[Coll[Coll[Byte]]].get == coll1)\n } else { placeholder[Boolean](14) }\n val coll26 = SELF.id\n val l27 = coll13(placeholder[Int](15))\n val coll28 = box10.tokens\n val tuple29 = coll28.getOrElse(placeholder[Int](16), tuple4)\n val coll30 = tuple29._1\n val tuple31 = coll28.getOrElse(placeholder[Int](17), tuple4)\n val l32 = tuple5._2\n val l33 = coll13(placeholder[Int](18))\n val l34 = tuple29._2\n val coll35 = tuple31._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l32 == placeholder[Long](21))\n val tuple40 = coll3.getOrElse(placeholder[Int](22), tuple4)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple4)\n val l42 = HEIGHT.toLong\n val l43 = coll13(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll13(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val l49 = tuple46._1\n if (box48.id != coll26) { box48.tokens.fold(l49, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) } else { l49 }\n })\n val bool47 = ((bool25 && (box10.R7[Coll[Byte]].get == coll7)) && \n val coll47 = coll30\n coll47 == coll6\n ) && (l34 == placeholder[Long](29))\n val bool48 = OUTPUTS.fold(placeholder[Long](30), {(tuple48: (Long, Box)) => tuple48._2.tokens.fold(tuple48._1, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) }) == placeholder[Long](31)\n val l49 = tuple31._2\n prop2 && sigmaProp((bool9 && (OUTPUTS.size == placeholder[Int](32))) && (coll11 == coll12)) || sigmaProp(\n (((if ((bool9 && (INPUTS.size == placeholder[Int](33))) && (OUTPUTS.size == placeholder[Int](34))) {(\n val bool50 = l14 == placeholder[Long](35)\n val l51 = l21 * l20 / placeholder[Long](36)\n val bool52 = l51 > placeholder[Long](37)\n ((((((((((if (bool50) {(\n val box53 = CONTEXT.dataInputs(placeholder[Int](38))\n val i54 = l15.toInt\n val l55 = box53.R5[Coll[Long]].get(i54)\n val bool56 = box53.tokens(placeholder[Int](39))._1 == coll16\n val coll57 = box53.R4[Coll[Coll[Byte]]].get(i54)\n if (l15 == placeholder[Long](40)) { bool56 && (l55 > placeholder[Long](41)) } else { if (l17 == placeholder[Long](42)) { ((bool56 && (coll57.size > placeholder[Int](43))) && (l55 > placeholder[Long](44))) && (coll3(placeholder[Int](45))._1 == coll57) } else { (bool56 && (coll57.size > placeholder[Int](46))) && (l55 > placeholder[Long](47)) } }\n )} else {(\n val coll53 = coll3(placeholder[Int](48))._1\n (coll53 == coll18) || (coll53 == coll19)\n )} && if (bool50) { (l20 == placeholder[Long](49)) || (l20 == placeholder[Long](50)) } else { ((l20 == placeholder[Long](51)) && (coll3(placeholder[Int](52))._1 == coll18)) || ((l20 == placeholder[Long](53)) && (coll3(placeholder[Int](54))._1 == coll19)) }) && bool52) && bool25) && (box10.R7[Coll[Byte]].get == coll26)) && (box10.value == SELF.value - l22 - l27)) && (box10.value >= placeholder[Long](55) * l23)) && (coll30 == coll26)) && \n val bool53 = l17 == placeholder[Long](56)\n ((((((((bool53 && bool50) && (l15 != placeholder[Long](57))) && \n val coll54 = coll35\n coll54 == coll24\n ) && (tuple31 == tuple5)) && (l34 == l32 / l33 + placeholder[Long](58))) && (coll28.size == placeholder[Int](59))) || (((bool53 && bool50) && (l15 == placeholder[Long](60))) && \n val l54 = l33 * CONTEXT.dataInputs(placeholder[Int](61)).R5[Coll[Long]].get(placeholder[Int](62)) / placeholder[Long](63)\n val l55 = SELF.value\n (((l54 > placeholder[Long](64)) && (l34 == l55 - placeholder[Long](65) * l22 - l27 - placeholder[Long](66) / l54 + placeholder[Long](67))) && (coll28.size == placeholder[Int](68))) && (box10.value >= l55 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](69)) && bool50) && (coll35 == coll24)) && (tuple31 == tuple5)) && bool52) && (l34 == l32 / l51 + placeholder[Long](70))) && (coll28.size == placeholder[Int](71)))) || ((l14 == placeholder[Long](72)) && \n val l54 = l36 * l20 / placeholder[Long](73)\n ((((l54 > placeholder[Long](74)) && (coll35 == coll24)) && (tuple31 == tuple5)) && (l34 == l32 / l54 + placeholder[Long](75))) && (coll28.size == placeholder[Int](76))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](77)))) && (coll38.size == placeholder[Int](78))) && (box37.value >= l27)\n )} else { placeholder[Boolean](79) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](80))) && (OUTPUTS.size == placeholder[Int](81))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](82)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](83))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](84))) && (coll38.size == placeholder[Int](85))) && (tuple41._1 == coll6)) && (tuple41._2 == l32 - placeholder[Long](86)) } else { placeholder[Boolean](87) }) || if ((bool45 && (l14 == placeholder[Long](88))) && (l46 > placeholder[Long](89))) {(\n val box50 = CONTEXT.dataInputs(placeholder[Int](90))\n val i51 = l15.toInt\n val l52 = box50.R5[Coll[Long]].get(i51)\n val bool53 = l52 > placeholder[Long](91)\n val bool54 = box50.tokens(placeholder[Int](92))._1 == coll16\n val l55 = l33 * l52 / placeholder[Long](93)\n val l56 = l21 * l20 / placeholder[Long](94)\n val bool57 = (l55 > placeholder[Long](95)) && (l56 > placeholder[Long](96))\n val l58 = l55 * l46\n val coll59 = if (l20 == placeholder[Long](97)) { coll18 } else { coll19 }\n val l60 = l56 * l46\n val coll61 = box50.R4[Coll[Coll[Byte]]].get(i51)\n val bool62 = (coll61.size > placeholder[Int](98)) || (l15 == placeholder[Long](99))\n if (l17 == placeholder[Long](100)) { if (l15 == placeholder[Long](101)) {(\n val box63 = OUTPUTS(placeholder[Int](102))\n ((((((bool54 && bool53) && bool57) && (box37.value >= l58)) && ((box63.propositionBytes == coll12) && box63.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll59) && (tuple64._2 >= l60) }))) && bool47) && bool48) && (box10.value >= SELF.value - l58 - l22)\n )} else {(\n val tuple63 = coll3(placeholder[Int](103))\n val box64 = OUTPUTS(placeholder[Int](104))\n ((((((((((bool54 && bool62) && bool53) && bool57) && (tuple63._1 == coll61)) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll61) && (tuple65._2 >= l58) })) && ((box64.propositionBytes == coll12) && box64.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll59) && (tuple65._2 >= l60) }))) && if (l49 > placeholder[Long](105)) { coll35 == coll61 } else { placeholder[Boolean](106) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l58)\n )} } else {(\n val tuple63 = coll3(placeholder[Int](107))\n val coll64 = tuple63._1\n val box65 = OUTPUTS(placeholder[Int](108))\n ((((((((((bool54 && bool62) && bool53) && bool57) && ((coll64 == coll18) || (coll64 == coll19))) && coll38.exists({(tuple66: (Coll[Byte], Long)) => (tuple66._1 == coll64) && (tuple66._2 >= l60) })) && ((box65.propositionBytes == coll12) && box65.tokens.exists({(tuple66: (Coll[Byte], Long)) => (tuple66._1 == coll61) && (tuple66._2 >= l58) }))) && if (l49 > placeholder[Long](109)) { coll35 == coll64 } else { placeholder[Boolean](110) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l60)\n )}\n )} else { placeholder[Boolean](111) }) || if ((bool45 && (l14 == placeholder[Long](112))) && (l46 > placeholder[Long](113))) {(\n val tuple50 = coll3(placeholder[Int](114))\n val coll51 = tuple50._1\n val box52 = CONTEXT.dataInputs(placeholder[Int](115))\n val l53 = box52.R8[Coll[Long]].get(l15.toInt)\n val l54 = if (l17 == placeholder[Long](116)) { if (l53 > l21) {(\n val l54 = l53 - l21\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](117) } } else { if (l53 < l21) {(\n val l54 = l21 - l53\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](118) } }\n val l55 = l54 * l20 / placeholder[Long](119)\n val l56 = l55 * l46\n ((((((((((coll51 == coll18) || (coll51 == coll19)) && (box52.tokens(placeholder[Int](120))._1 == placeholder[Coll[Byte]](121))) && (l54 > placeholder[Long](122))) && (l55 > placeholder[Long](123))) && coll38.exists({(tuple57: (Coll[Byte], Long)) => (tuple57._1 == coll51) && (tuple57._2 >= l56) })) && if (l49 > placeholder[Long](124)) { coll35 == coll51 } else { placeholder[Boolean](125) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple50._2 - l56)\n )} else { placeholder[Boolean](126) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](127)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](128) }\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110b000280897a8abad501a0c21e80dac40980c78c022200a0c21ec801",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,1000000,1748613,250000,10000000,2200000,17,0,250000,100]"
},
"R7": {
"serializedValue": "0e200000000000000000000000000000000000000000000000000000000000000000",
"sigmaType": "Coll[SByte]",
"renderedValue": "0000000000000000000000000000000000000000000000000000000000000000"
},
"R9": {
"serializedValue": "1a022102795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73240008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73,0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8]"
},
"R4": {
"serializedValue": "0e0e4552472043616c6c2024302e3235",
"sigmaType": "Coll[SByte]",
"renderedValue": "4552472043616c6c2024302e3235"
}
}
}
],
"dataInputs": [
{
"boxId": "ac99a1eadde51e62cb48b85731e46ef56136a0a2c2c0d035416475f79e736ef0",
"value": 150000000,
"index": 0,
"outputBlockId": "a0572fca9270bb8f8253e852730a68dadb254a03b7e96cfd573736e51e63a85e",
"outputTransactionId": "16ac127b686954c7163ac83517e271083b90f1e79438d8a2fe08236efef46552",
"outputIndex": 0,
"ergoTree": "10040e20ea7b36e294b1a954a80752eac288711728e5b91b0b3c0596548c755665050b88040004000400d804d6017300d602b2a5730100d603b1e4c67202041ad604b1e4c672020511ea02d1ededededededed938cb2db6308a7730200017201938cb2db6308720273030001720193c27202c2a7927203b1e4c6a7041a927204b1e4c6a70511937203720492c17202c1a7e6c672020608e4c6a70608",
"address": "QqJr1n1xDwmVKHreupY52BAX35qjNng6DCjpvB2dUpqTWaBxXtHJvuY5qFYg25xQ8fQ7kFdodBmXqGDAoRcsJHoaTt4MvjCyAz2hJPpG1Br9o3YBwoFvJyufMSjTwbSVGrPKSxPq9f1TBpJuthgw7rMgd6DDwDndMyiQ4M9wnm9FXuup12EzDTZavsJ1D6bPD81eS1iR6ppRNcVyEbAr95kRkry",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a1520203ef3066a912f35c488487cc2cb94bdb0d30680dab22551c7e6fdbc70dfcc8e207a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b020050322548722d36f094e341f59ed93eb22118b363eb4efe8c461a52c4d93e2c32048132396ebd00831e603c73cf01e01f248dd1966d2cc976caf52ef76f7ac6e3620e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c29700000000000000000000000000206122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad0000",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[203ef3066a912f35c488487cc2cb94bdb0d30680dab22551c7e6fdbc70dfcc8e,7a51950e5f548549ec1aa63ffdc38279505b11e7e803d01bcf8347e0123c88b0,050322548722d36f094e341f59ed93eb22118b363eb4efe8c461a52c4d93e2c3,48132396ebd00831e603c73cf01e01f248dd1966d2cc976caf52ef76f7ac6e36,e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297,,,,,,,,,,,,,,6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad,,]"
},
"R5": {
"serializedValue": "111580a8d6b9078084af5f80a8d6b90780897a80897a00000000000000000000000080a8d6b907fee5030000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000000000,100000000,1000000000,1000000,1000000,0,0,0,0,0,0,0,0,0,0,0,0,1000000000,31103,0,0]"
},
"R6": {
"serializedValue": "08cd03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b",
"sigmaType": "SSigmaProp",
"renderedValue": "03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b"
}
}
}
],
"outputs": [
{
"boxId": "8648dea80dcbf358beb373239e5e2a83299373ad8f4bebeae2f21401993500ae",
"transactionId": "354a2b4f8fd83174769910c7facc20739feeffe660809d61fa9b6fe502ce9bed",
"blockId": "c947f0b9a59bbb4e5a9d060b436dc1b29e5a74bf977f5555080a51b9bb49aed4",
"value": 2006400000,
"index": 0,
"globalIndex": 54345174,
"creationHeight": 1749897,
"settlementHeight": 1749898,
"ergoTree": 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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: 0\n8: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n9: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n10: 10\n11: 4\n12: 6\n13: 1000000\n14: false\n15: 5\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 720\n26: 1\n27: 0\n28: 0\n29: 1\n30: 0\n31: 1\n32: 2\n33: 1\n34: 3\n35: 0\n36: 1000000\n37: 0\n38: 0\n39: 0\n40: 17\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 0\n48: 0\n49: 1000\n50: 100\n51: 1000\n52: 0\n53: 100\n54: 0\n55: 2\n56: 0\n57: 17\n58: 1\n59: 2\n60: 17\n61: 0\n62: 17\n63: 1000000\n64: 0\n65: 3\n66: 2000000\n67: 1\n68: 1\n69: 1\n70: 1\n71: 2\n72: 1\n73: 1000000\n74: 0\n75: 1\n76: 2\n77: 1\n78: 0\n79: false\n80: 1\n81: 3\n82: 1000000\n83: 1\n84: 1000000\n85: 1\n86: 1\n87: false\n88: 0\n89: 0\n90: 0\n91: 0\n92: 0\n93: 1000000\n94: 1000000\n95: 0\n96: 0\n97: 1000\n98: 0\n99: 17\n100: 0\n101: 17\n102: 2\n103: 1\n104: 2\n105: 0\n106: true\n107: 1\n108: 2\n109: 0\n110: true\n111: false\n112: 1\n113: 0\n114: 1\n115: 0\n116: 0\n117: 0\n118: 0\n119: 1000000\n120: 0\n121: Coll(49,-126,103,79,7,-37,-71,-115,105,109,56,-19,-91,62,99,-21,59,-11,-2,87,15,113,-34,-24,94,-71,84,-42,-49,-112,59,-70)\n122: 0\n123: 0\n124: 0\n125: true\n126: false\n127: 2\n128: false",
"ergoTreeScript": "{\n val coll1 = SELF.R9[Coll[Coll[Byte]]].get\n val prop2 = proveDlog(decodePoint(coll1(placeholder[Int](0))))\n val coll3 = SELF.tokens\n val tuple4 = (Coll[Byte](), placeholder[Long](1))\n val tuple5 = coll3.getOrElse(placeholder[Int](2), tuple4)\n val coll6 = tuple5._1\n val coll7 = SELF.R7[Coll[Byte]].get\n val bool8 = coll6 == coll7\n val bool9 = !bool8\n val box10 = OUTPUTS(placeholder[Int](3))\n val coll11 = box10.propositionBytes\n val coll12 = prop2.propBytes\n val coll13 = SELF.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = coll13(placeholder[Int](5))\n val coll16 = placeholder[Coll[Byte]](6)\n val l17 = coll13(placeholder[Int](7))\n val coll18 = placeholder[Coll[Byte]](8)\n val coll19 = placeholder[Coll[Byte]](9)\n val l20 = coll13(placeholder[Int](10))\n val l21 = coll13(placeholder[Int](11))\n val l22 = coll13(placeholder[Int](12))\n val l23 = l22 + placeholder[Long](13)\n val coll24 = SELF.R5[Coll[Byte]].get\n val bool25 = if (coll11 == SELF.propositionBytes) {\n (\n (\n (((box10.value >= l23) && (box10.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box10.R5[Coll[Byte]].get == coll24)) && (\n box10.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get\n )\n ) && (box10.R8[Coll[Long]].get == coll13)\n ) && (box10.R9[Coll[Coll[Byte]]].get == coll1)\n } else { placeholder[Boolean](14) }\n val coll26 = SELF.id\n val l27 = coll13(placeholder[Int](15))\n val coll28 = box10.tokens\n val tuple29 = coll28.getOrElse(placeholder[Int](16), tuple4)\n val coll30 = tuple29._1\n val tuple31 = coll28.getOrElse(placeholder[Int](17), tuple4)\n val l32 = tuple5._2\n val l33 = coll13(placeholder[Int](18))\n val l34 = tuple29._2\n val coll35 = tuple31._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l32 == placeholder[Long](21))\n val tuple40 = coll3.getOrElse(placeholder[Int](22), tuple4)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple4)\n val l42 = HEIGHT.toLong\n val l43 = coll13(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll13(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val l49 = tuple46._1\n if (box48.id != coll26) { box48.tokens.fold(l49, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) } else { l49 }\n })\n val bool47 = ((bool25 && (box10.R7[Coll[Byte]].get == coll7)) && \n val coll47 = coll30\n coll47 == coll6\n ) && (l34 == placeholder[Long](29))\n val bool48 = OUTPUTS.fold(placeholder[Long](30), {(tuple48: (Long, Box)) => tuple48._2.tokens.fold(tuple48._1, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) }) == placeholder[Long](31)\n val l49 = tuple31._2\n prop2 && sigmaProp((bool9 && (OUTPUTS.size == placeholder[Int](32))) && (coll11 == coll12)) || sigmaProp(\n (((if ((bool9 && (INPUTS.size == placeholder[Int](33))) && (OUTPUTS.size == placeholder[Int](34))) {(\n val bool50 = l14 == placeholder[Long](35)\n val l51 = l21 * l20 / placeholder[Long](36)\n val bool52 = l51 > placeholder[Long](37)\n ((((((((((if (bool50) {(\n val box53 = CONTEXT.dataInputs(placeholder[Int](38))\n val i54 = l15.toInt\n val l55 = box53.R5[Coll[Long]].get(i54)\n val bool56 = box53.tokens(placeholder[Int](39))._1 == coll16\n val coll57 = box53.R4[Coll[Coll[Byte]]].get(i54)\n if (l15 == placeholder[Long](40)) { bool56 && (l55 > placeholder[Long](41)) } else { if (l17 == placeholder[Long](42)) { ((bool56 && (coll57.size > placeholder[Int](43))) && (l55 > placeholder[Long](44))) && (coll3(placeholder[Int](45))._1 == coll57) } else { (bool56 && (coll57.size > placeholder[Int](46))) && (l55 > placeholder[Long](47)) } }\n )} else {(\n val coll53 = coll3(placeholder[Int](48))._1\n (coll53 == coll18) || (coll53 == coll19)\n )} && if (bool50) { (l20 == placeholder[Long](49)) || (l20 == placeholder[Long](50)) } else { ((l20 == placeholder[Long](51)) && (coll3(placeholder[Int](52))._1 == coll18)) || ((l20 == placeholder[Long](53)) && (coll3(placeholder[Int](54))._1 == coll19)) }) && bool52) && bool25) && (box10.R7[Coll[Byte]].get == coll26)) && (box10.value == SELF.value - l22 - l27)) && (box10.value >= placeholder[Long](55) * l23)) && (coll30 == coll26)) && \n val bool53 = l17 == placeholder[Long](56)\n ((((((((bool53 && bool50) && (l15 != placeholder[Long](57))) && \n val coll54 = coll35\n coll54 == coll24\n ) && (tuple31 == tuple5)) && (l34 == l32 / l33 + placeholder[Long](58))) && (coll28.size == placeholder[Int](59))) || (((bool53 && bool50) && (l15 == placeholder[Long](60))) && \n val l54 = l33 * CONTEXT.dataInputs(placeholder[Int](61)).R5[Coll[Long]].get(placeholder[Int](62)) / placeholder[Long](63)\n val l55 = SELF.value\n (((l54 > placeholder[Long](64)) && (l34 == l55 - placeholder[Long](65) * l22 - l27 - placeholder[Long](66) / l54 + placeholder[Long](67))) && (coll28.size == placeholder[Int](68))) && (box10.value >= l55 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](69)) && bool50) && (coll35 == coll24)) && (tuple31 == tuple5)) && bool52) && (l34 == l32 / l51 + placeholder[Long](70))) && (coll28.size == placeholder[Int](71)))) || ((l14 == placeholder[Long](72)) && \n val l54 = l36 * l20 / placeholder[Long](73)\n ((((l54 > placeholder[Long](74)) && (coll35 == coll24)) && (tuple31 == tuple5)) && (l34 == l32 / l54 + placeholder[Long](75))) && (coll28.size == placeholder[Int](76))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](77)))) && (coll38.size == placeholder[Int](78))) && (box37.value >= l27)\n )} else { placeholder[Boolean](79) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](80))) && (OUTPUTS.size == placeholder[Int](81))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](82)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](83))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](84))) && (coll38.size == placeholder[Int](85))) && (tuple41._1 == coll6)) && (tuple41._2 == l32 - placeholder[Long](86)) } else { placeholder[Boolean](87) }) || if ((bool45 && (l14 == placeholder[Long](88))) && (l46 > placeholder[Long](89))) {(\n val box50 = CONTEXT.dataInputs(placeholder[Int](90))\n val i51 = l15.toInt\n val l52 = box50.R5[Coll[Long]].get(i51)\n val bool53 = l52 > placeholder[Long](91)\n val bool54 = box50.tokens(placeholder[Int](92))._1 == coll16\n val l55 = l33 * l52 / placeholder[Long](93)\n val l56 = l21 * l20 / placeholder[Long](94)\n val bool57 = (l55 > placeholder[Long](95)) && (l56 > placeholder[Long](96))\n val l58 = l55 * l46\n val coll59 = if (l20 == placeholder[Long](97)) { coll18 } else { coll19 }\n val l60 = l56 * l46\n val coll61 = box50.R4[Coll[Coll[Byte]]].get(i51)\n val bool62 = (coll61.size > placeholder[Int](98)) || (l15 == placeholder[Long](99))\n if (l17 == placeholder[Long](100)) { if (l15 == placeholder[Long](101)) {(\n val box63 = OUTPUTS(placeholder[Int](102))\n ((((((bool54 && bool53) && bool57) && (box37.value >= l58)) && ((box63.propositionBytes == coll12) && box63.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll59) && (tuple64._2 >= l60) }))) && bool47) && bool48) && (box10.value >= SELF.value - l58 - l22)\n )} else {(\n val tuple63 = coll3(placeholder[Int](103))\n val box64 = OUTPUTS(placeholder[Int](104))\n ((((((((((bool54 && bool62) && bool53) && bool57) && (tuple63._1 == coll61)) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll61) && (tuple65._2 >= l58) })) && ((box64.propositionBytes == coll12) && box64.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll59) && (tuple65._2 >= l60) }))) && if (l49 > placeholder[Long](105)) { coll35 == coll61 } else { placeholder[Boolean](106) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l58)\n )} } else {(\n val tuple63 = coll3(placeholder[Int](107))\n val coll64 = tuple63._1\n val box65 = OUTPUTS(placeholder[Int](108))\n ((((((((((bool54 && bool62) && bool53) && bool57) && ((coll64 == coll18) || (coll64 == coll19))) && coll38.exists({(tuple66: (Coll[Byte], Long)) => (tuple66._1 == coll64) && (tuple66._2 >= l60) })) && ((box65.propositionBytes == coll12) && box65.tokens.exists({(tuple66: (Coll[Byte], Long)) => (tuple66._1 == coll61) && (tuple66._2 >= l58) }))) && if (l49 > placeholder[Long](109)) { coll35 == coll64 } else { placeholder[Boolean](110) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l60)\n )}\n )} else { placeholder[Boolean](111) }) || if ((bool45 && (l14 == placeholder[Long](112))) && (l46 > placeholder[Long](113))) {(\n val tuple50 = coll3(placeholder[Int](114))\n val coll51 = tuple50._1\n val box52 = CONTEXT.dataInputs(placeholder[Int](115))\n val l53 = box52.R8[Coll[Long]].get(l15.toInt)\n val l54 = if (l17 == placeholder[Long](116)) { if (l53 > l21) {(\n val l54 = l53 - l21\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](117) } } else { if (l53 < l21) {(\n val l54 = l21 - l53\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](118) } }\n val l55 = l54 * l20 / placeholder[Long](119)\n val l56 = l55 * l46\n ((((((((((coll51 == coll18) || (coll51 == coll19)) && (box52.tokens(placeholder[Int](120))._1 == placeholder[Coll[Byte]](121))) && (l54 > placeholder[Long](122))) && (l55 > placeholder[Long](123))) && coll38.exists({(tuple57: (Coll[Byte], Long)) => (tuple57._1 == coll51) && (tuple57._2 >= l56) })) && if (l49 > placeholder[Long](124)) { coll35 == coll51 } else { placeholder[Boolean](125) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple50._2 - l56)\n )} else { placeholder[Boolean](126) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](127)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](128) }\n )\n}",
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"assets": [
{
"tokenId": "71cb708c4c60b6295da134539c7e152674518fd501bcf0cf409bd4b062a1ad79",
"index": 0,
"amount": 3,
"name": "ERG Call $0.25",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110b000280897a8abad501a0c21e80dac40980c78c022200a0c21ec801",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,1000000,1748613,250000,10000000,2200000,17,0,250000,100]"
},
"R7": {
"serializedValue": "0e2071cb708c4c60b6295da134539c7e152674518fd501bcf0cf409bd4b062a1ad79",
"sigmaType": "Coll[SByte]",
"renderedValue": "71cb708c4c60b6295da134539c7e152674518fd501bcf0cf409bd4b062a1ad79"
},
"R9": {
"serializedValue": "1a022102795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73240008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73,0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8]"
},
"R4": {
"serializedValue": "0e0e4552472043616c6c2024302e3235",
"sigmaType": "Coll[SByte]",
"renderedValue": "4552472043616c6c2024302e3235"
}
},
"spentTransactionId": "d3fcb6438b78189845ee8de5de7243727b5549874365747aa6134d010f78a5e0",
"mainChain": true
},
{
"boxId": "496e315e0205ccb4f150f519d2c4dc5802585cc0f82e5a15a0c023998053275c",
"transactionId": "354a2b4f8fd83174769910c7facc20739feeffe660809d61fa9b6fe502ce9bed",
"blockId": "c947f0b9a59bbb4e5a9d060b436dc1b29e5a74bf977f5555080a51b9bb49aed4",
"value": 10000000,
"index": 1,
"globalIndex": 54345175,
"creationHeight": 1749897,
"settlementHeight": 1749898,
"ergoTree": "0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(383747,d85572,...)))}",
"address": "9ewpUXoFqTomiiAxkj7P5x1FLvQ5Ldsn95XZiTpJaVpgUr3VZeS",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "ebc82274ca2025f6f5e2f9dc403326db5f0b52703e1ecf109833ffe4779c8a4b",
"transactionId": "354a2b4f8fd83174769910c7facc20739feeffe660809d61fa9b6fe502ce9bed",
"blockId": "c947f0b9a59bbb4e5a9d060b436dc1b29e5a74bf977f5555080a51b9bb49aed4",
"value": 2200000,
"index": 2,
"globalIndex": 54345176,
"creationHeight": 1749897,
"settlementHeight": 1749898,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "6af35a41695a85058bed6dffa9ecdc9ecb70d0cb55a59cae71de57cba0871ab4",
"mainChain": true
}
],
"size": 2994,
"isUnconfirmed": false
}