Transaction
ID: dcd0906544...bb91
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0218 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0096 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0022 ERG
Transaction Details
Confirmations: 5,646
Total coins transferred: 0.0218 ERG
Fees: 0.0022 ERG
Fees per byte: 0.000000708 ERG
Raw Transaction Data
{
"id": "dcd09065446d95d7fb997da19ae3ad86bb72c51f9d830e34d0277fbbf256bb91",
"blockId": "5207a634f418d1320afac967d8682d57d7e8aeb66197b73ec9ddb80e98234c3e",
"inclusionHeight": 1756506,
"timestamp": 1775277511254,
"index": 2,
"globalIndex": 10544260,
"numConfirmations": 5646,
"inputs": [
{
"boxId": "aa005dd324c6caec9c14da83341c43e49eefb5a11553c982c4b1214ed94dbe40",
"value": 21800000,
"index": 0,
"spendingProof": "a4494c5778ae3d25ec3146685b9245cb8fa1ce33e297c3bc03241d4dd269eebef1028dfa1bc5cafdaaccf0bb5340ee32b900b1533744b64f",
"outputBlockId": "a4b9cccfa4d40474c02847548f277d0d4c043a79b0f46122df55890fe48283dc",
"outputTransactionId": "96d862221741069e42984fdc09c5633925be8f7d98b7b6c04a8ec38ad18a76a8",
"outputIndex": 0,
"outputGlobalIndex": 54521006,
"outputCreatedAt": 1756502,
"outputSettledAt": 1756503,
"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: 2\n18: 1\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: 0\n59: 1000000\n60: 0\n61: 1\n62: 2\n63: 17\n64: 0\n65: 17\n66: 1000000\n67: 0\n68: 3\n69: 2000000\n70: 1\n71: 1\n72: 1\n73: 1\n74: 2\n75: 1\n76: 1000000\n77: 0\n78: 1\n79: 2\n80: 1\n81: 0\n82: false\n83: 1\n84: 3\n85: 1000000\n86: 1\n87: 1000000\n88: 1\n89: 1\n90: false\n91: 0\n92: 0\n93: 0\n94: 0\n95: 0\n96: 1000000\n97: 1000000\n98: 0\n99: 0\n100: 1000\n101: 0\n102: 17\n103: 0\n104: 17\n105: 2\n106: 1\n107: 2\n108: 0\n109: true\n110: 1\n111: 2\n112: 0\n113: true\n114: false\n115: 1\n116: 0\n117: 1\n118: 0\n119: 0\n120: 0\n121: 0\n122: 1000000\n123: 0\n124: 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)\n125: 0\n126: 0\n127: 0\n128: true\n129: false\n130: 2\n131: 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 l31 = coll13(placeholder[Int](17))\n val tuple32 = coll28.getOrElse(placeholder[Int](18), tuple4)\n val l33 = tuple5._2\n val l34 = tuple29._2\n val coll35 = tuple32._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l33 == 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 = tuple32._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 l54 = l31 * CONTEXT.dataInputs(placeholder[Int](58)).R5[Coll[Long]].get(l15.toInt) / placeholder[Long](59)\n ((((l54 > placeholder[Long](60)) && \n val coll55 = coll35\n coll55 == coll24\n ) && (tuple32 == tuple5)) && (l34 == l33 / l54 + placeholder[Long](61))) && (coll28.size == placeholder[Int](62))\n ) || (((bool53 && bool50) && (l15 == placeholder[Long](63))) && \n val l54 = l31 * CONTEXT.dataInputs(placeholder[Int](64)).R5[Coll[Long]].get(placeholder[Int](65)) / placeholder[Long](66)\n val l55 = SELF.value\n (((l54 > placeholder[Long](67)) && (l34 == l55 - placeholder[Long](68) * l22 - l27 - placeholder[Long](69) / l54 + placeholder[Long](70))) && (coll28.size == placeholder[Int](71))) && (box10.value >= l55 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](72)) && bool50) && (coll35 == coll24)) && (tuple32 == tuple5)) && bool52) && (l34 == l33 / l51 + placeholder[Long](73))) && (coll28.size == placeholder[Int](74)))) || ((l14 == placeholder[Long](75)) && \n val l54 = l36 * l20 / placeholder[Long](76)\n ((((l54 > placeholder[Long](77)) && (coll35 == coll24)) && (tuple32 == tuple5)) && (l34 == l33 / l54 + placeholder[Long](78))) && (coll28.size == placeholder[Int](79))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](80)))) && (coll38.size == placeholder[Int](81))) && (box37.value >= l27)\n )} else { placeholder[Boolean](82) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](83))) && (OUTPUTS.size == placeholder[Int](84))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](85)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](86))) && (tuple32 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](87))) && (coll38.size == placeholder[Int](88))) && (tuple41._1 == coll6)) && (tuple41._2 == l33 - placeholder[Long](89)) } else { placeholder[Boolean](90) }) || if ((bool45 && (l14 == placeholder[Long](91))) && (l46 > placeholder[Long](92))) {(\n val box50 = CONTEXT.dataInputs(placeholder[Int](93))\n val i51 = l15.toInt\n val l52 = box50.R5[Coll[Long]].get(i51)\n val bool53 = l52 > placeholder[Long](94)\n val bool54 = box50.tokens(placeholder[Int](95))._1 == coll16\n val l55 = l31 * l52 / placeholder[Long](96)\n val l56 = l21 * l20 / placeholder[Long](97)\n val bool57 = (l55 > placeholder[Long](98)) && (l56 > placeholder[Long](99))\n val l58 = l55 * l46\n val coll59 = if (l20 == placeholder[Long](100)) { 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](101)) || (l15 == placeholder[Long](102))\n if (l17 == placeholder[Long](103)) { if (l15 == placeholder[Long](104)) {(\n val box63 = OUTPUTS(placeholder[Int](105))\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](106))\n val box64 = OUTPUTS(placeholder[Int](107))\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](108)) { coll35 == coll61 } else { placeholder[Boolean](109) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l58)\n )} } else {(\n val tuple63 = coll3(placeholder[Int](110))\n val coll64 = tuple63._1\n val box65 = OUTPUTS(placeholder[Int](111))\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](112)) { coll35 == coll64 } else { placeholder[Boolean](113) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l60)\n )}\n )} else { placeholder[Boolean](114) }) || if ((bool45 && (l14 == placeholder[Long](115))) && (l46 > placeholder[Long](116))) {(\n val tuple50 = coll3(placeholder[Int](117))\n val coll51 = tuple50._1\n val box52 = CONTEXT.dataInputs(placeholder[Int](118))\n val l53 = box52.R8[Coll[Long]].get(l15.toInt)\n val l54 = if (l17 == placeholder[Long](119)) { if (l53 > l21) {(\n val l54 = l53 - l21\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](120) } } else { if (l53 < l21) {(\n val l54 = l21 - l53\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](121) } }\n val l55 = l54 * l20 / placeholder[Long](122)\n val l56 = l55 * l46\n ((((((((((coll51 == coll18) || (coll51 == coll19)) && (box52.tokens(placeholder[Int](123))._1 == placeholder[Coll[Byte]](124))) && (l54 > placeholder[Long](125))) && (l55 > placeholder[Long](126))) && coll38.exists({(tuple57: (Coll[Byte], Long)) => (tuple57._1 == coll51) && (tuple57._2 >= l56) })) && if (l49 > placeholder[Long](127)) { coll35 == coll51 } else { placeholder[Boolean](128) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple50._2 - l56)\n )} else { placeholder[Boolean](129) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](130)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](131) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad",
"index": 0,
"amount": 62,
"name": "DexyGold",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e206122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad",
"sigmaType": "Coll[SByte]",
"renderedValue": "6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110b0002d00ffcbad60180a4e80380dac40980c78c02240080a4e803c801",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,1000,1756862,4000000,10000000,2200000,18,0,4000000,100]"
},
"R7": {
"serializedValue": "0e200000000000000000000000000000000000000000000000000000000000000000",
"sigmaType": "Coll[SByte]",
"renderedValue": "0000000000000000000000000000000000000000000000000000000000000000"
},
"R9": {
"serializedValue": "1a022102795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73240008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73,0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8]"
},
"R4": {
"serializedValue": "0e12476f6c642043616c6c2024343030302e3030",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6c642043616c6c2024343030302e3030"
}
}
}
],
"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": {
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"sigmaType": "SSigmaProp",
"renderedValue": "03bda2691a9f1a2adf122741390847e7dae2c75bd2eb3a0dc896388d4ec3e9577b"
}
}
}
],
"outputs": [
{
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"transactionId": "dcd09065446d95d7fb997da19ae3ad86bb72c51f9d830e34d0277fbbf256bb91",
"blockId": "5207a634f418d1320afac967d8682d57d7e8aeb66197b73ec9ddb80e98234c3e",
"value": 9600000,
"index": 0,
"globalIndex": 54521121,
"creationHeight": 1756504,
"settlementHeight": 1756506,
"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: 2\n18: 1\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: 0\n59: 1000000\n60: 0\n61: 1\n62: 2\n63: 17\n64: 0\n65: 17\n66: 1000000\n67: 0\n68: 3\n69: 2000000\n70: 1\n71: 1\n72: 1\n73: 1\n74: 2\n75: 1\n76: 1000000\n77: 0\n78: 1\n79: 2\n80: 1\n81: 0\n82: false\n83: 1\n84: 3\n85: 1000000\n86: 1\n87: 1000000\n88: 1\n89: 1\n90: false\n91: 0\n92: 0\n93: 0\n94: 0\n95: 0\n96: 1000000\n97: 1000000\n98: 0\n99: 0\n100: 1000\n101: 0\n102: 17\n103: 0\n104: 17\n105: 2\n106: 1\n107: 2\n108: 0\n109: true\n110: 1\n111: 2\n112: 0\n113: true\n114: false\n115: 1\n116: 0\n117: 1\n118: 0\n119: 0\n120: 0\n121: 0\n122: 1000000\n123: 0\n124: 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)\n125: 0\n126: 0\n127: 0\n128: true\n129: false\n130: 2\n131: 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 l31 = coll13(placeholder[Int](17))\n val tuple32 = coll28.getOrElse(placeholder[Int](18), tuple4)\n val l33 = tuple5._2\n val l34 = tuple29._2\n val coll35 = tuple32._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l33 == 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 = tuple32._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 l54 = l31 * CONTEXT.dataInputs(placeholder[Int](58)).R5[Coll[Long]].get(l15.toInt) / placeholder[Long](59)\n ((((l54 > placeholder[Long](60)) && \n val coll55 = coll35\n coll55 == coll24\n ) && (tuple32 == tuple5)) && (l34 == l33 / l54 + placeholder[Long](61))) && (coll28.size == placeholder[Int](62))\n ) || (((bool53 && bool50) && (l15 == placeholder[Long](63))) && \n val l54 = l31 * CONTEXT.dataInputs(placeholder[Int](64)).R5[Coll[Long]].get(placeholder[Int](65)) / placeholder[Long](66)\n val l55 = SELF.value\n (((l54 > placeholder[Long](67)) && (l34 == l55 - placeholder[Long](68) * l22 - l27 - placeholder[Long](69) / l54 + placeholder[Long](70))) && (coll28.size == placeholder[Int](71))) && (box10.value >= l55 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](72)) && bool50) && (coll35 == coll24)) && (tuple32 == tuple5)) && bool52) && (l34 == l33 / l51 + placeholder[Long](73))) && (coll28.size == placeholder[Int](74)))) || ((l14 == placeholder[Long](75)) && \n val l54 = l36 * l20 / placeholder[Long](76)\n ((((l54 > placeholder[Long](77)) && (coll35 == coll24)) && (tuple32 == tuple5)) && (l34 == l33 / l54 + placeholder[Long](78))) && (coll28.size == placeholder[Int](79))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](80)))) && (coll38.size == placeholder[Int](81))) && (box37.value >= l27)\n )} else { placeholder[Boolean](82) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](83))) && (OUTPUTS.size == placeholder[Int](84))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](85)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](86))) && (tuple32 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](87))) && (coll38.size == placeholder[Int](88))) && (tuple41._1 == coll6)) && (tuple41._2 == l33 - placeholder[Long](89)) } else { placeholder[Boolean](90) }) || if ((bool45 && (l14 == placeholder[Long](91))) && (l46 > placeholder[Long](92))) {(\n val box50 = CONTEXT.dataInputs(placeholder[Int](93))\n val i51 = l15.toInt\n val l52 = box50.R5[Coll[Long]].get(i51)\n val bool53 = l52 > placeholder[Long](94)\n val bool54 = box50.tokens(placeholder[Int](95))._1 == coll16\n val l55 = l31 * l52 / placeholder[Long](96)\n val l56 = l21 * l20 / placeholder[Long](97)\n val bool57 = (l55 > placeholder[Long](98)) && (l56 > placeholder[Long](99))\n val l58 = l55 * l46\n val coll59 = if (l20 == placeholder[Long](100)) { 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](101)) || (l15 == placeholder[Long](102))\n if (l17 == placeholder[Long](103)) { if (l15 == placeholder[Long](104)) {(\n val box63 = OUTPUTS(placeholder[Int](105))\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](106))\n val box64 = OUTPUTS(placeholder[Int](107))\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](108)) { coll35 == coll61 } else { placeholder[Boolean](109) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l58)\n )} } else {(\n val tuple63 = coll3(placeholder[Int](110))\n val coll64 = tuple63._1\n val box65 = OUTPUTS(placeholder[Int](111))\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](112)) { coll35 == coll64 } else { placeholder[Boolean](113) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple63._2 - l60)\n )}\n )} else { placeholder[Boolean](114) }) || if ((bool45 && (l14 == placeholder[Long](115))) && (l46 > placeholder[Long](116))) {(\n val tuple50 = coll3(placeholder[Int](117))\n val coll51 = tuple50._1\n val box52 = CONTEXT.dataInputs(placeholder[Int](118))\n val l53 = box52.R8[Coll[Long]].get(l15.toInt)\n val l54 = if (l17 == placeholder[Long](119)) { if (l53 > l21) {(\n val l54 = l53 - l21\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](120) } } else { if (l53 < l21) {(\n val l54 = l21 - l53\n if (l54 > l36) { l36 } else { l54 }\n )} else { placeholder[Long](121) } }\n val l55 = l54 * l20 / placeholder[Long](122)\n val l56 = l55 * l46\n ((((((((((coll51 == coll18) || (coll51 == coll19)) && (box52.tokens(placeholder[Int](123))._1 == placeholder[Coll[Byte]](124))) && (l54 > placeholder[Long](125))) && (l55 > placeholder[Long](126))) && coll38.exists({(tuple57: (Coll[Byte], Long)) => (tuple57._1 == coll51) && (tuple57._2 >= l56) })) && if (l49 > placeholder[Long](127)) { coll35 == coll51 } else { placeholder[Boolean](128) }) && bool47) && bool48) && (box10.value >= SELF.value - l22)) && (l49 >= tuple50._2 - l56)\n )} else { placeholder[Boolean](129) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](130)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](131) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "aa005dd324c6caec9c14da83341c43e49eefb5a11553c982c4b1214ed94dbe40",
"index": 0,
"amount": 3,
"name": "Gold Call $4000.00",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad",
"index": 1,
"amount": 62,
"name": "DexyGold",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e206122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad",
"sigmaType": "Coll[SByte]",
"renderedValue": "6122f7289e7bb2df2de273e09d4b2756cda6aeb0f40438dc9d257688f45183ad"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110b0002d00ffcbad60180a4e80380dac40980c78c02240080a4e803c801",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,1000,1756862,4000000,10000000,2200000,18,0,4000000,100]"
},
"R7": {
"serializedValue": "0e20aa005dd324c6caec9c14da83341c43e49eefb5a11553c982c4b1214ed94dbe40",
"sigmaType": "Coll[SByte]",
"renderedValue": "aa005dd324c6caec9c14da83341c43e49eefb5a11553c982c4b1214ed94dbe40"
},
"R9": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73,0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8]"
},
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "476f6c642043616c6c2024343030302e3030"
}
},
"spentTransactionId": "ceefbaf02ca8f56d221b01e6aa23775cad687a6c1f4f87a1321223e472aebfea",
"mainChain": true
},
{
"boxId": "c15c7cfb7aad940d6f3377cd3916b43dd4136bde266229906ac8a81c860e55f6",
"transactionId": "dcd09065446d95d7fb997da19ae3ad86bb72c51f9d830e34d0277fbbf256bb91",
"blockId": "5207a634f418d1320afac967d8682d57d7e8aeb66197b73ec9ddb80e98234c3e",
"value": 10000000,
"index": 1,
"globalIndex": 54521122,
"creationHeight": 1756504,
"settlementHeight": 1756506,
"ergoTree": "0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(383747,d85572,...)))}",
"address": "9ewpUXoFqTomiiAxkj7P5x1FLvQ5Ldsn95XZiTpJaVpgUr3VZeS",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "60f421e43de744b66f5d03d0a62cee96e36e4822e9ccbf26544a71e54d4e4c3e",
"mainChain": true
},
{
"boxId": "16e6fef8d2ad87ff523ebb3cd4a57b5bf4e3d9b5baf29f2005b1c6d34c9eb057",
"transactionId": "dcd09065446d95d7fb997da19ae3ad86bb72c51f9d830e34d0277fbbf256bb91",
"blockId": "5207a634f418d1320afac967d8682d57d7e8aeb66197b73ec9ddb80e98234c3e",
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"index": 2,
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"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)}",
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"additionalRegisters": {},
"spentTransactionId": "bbd2c95131b3310b06ad8b11470aeab9c07ef00426f71656c7bfe95ce4212c59",
"mainChain": true
}
],
"size": 3109,
"isUnconfirmed": false
}