Transaction
ID: 4de76aee75...9020
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.279 ERG
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.268 ERG
Transaction Details
Confirmations: 23,994
Total coins transferred: 0.289 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000331 ERG
Raw Transaction Data
{
"id": "4de76aee75d0ed19e7e02e85ea1b3f59149fa1cd3bd51302aa6b1d6f506e9020",
"blockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"inclusionHeight": 1735084,
"timestamp": 1772686889677,
"index": 2,
"globalIndex": 10398663,
"numConfirmations": 23994,
"inputs": [
{
"boxId": "446541b3639e7eba76df7a13bcdfbe6841b50c9e08e0688fdeebe8a096d7bbf7",
"value": 10000000,
"index": 0,
"spendingProof": "91b34a3ff50f555921a73b85c61729a5c083c384c28606dfbc2ad1b6a20686d0118c124063ca8c357e924a3c028f5fdb2b24de1296f11b1f",
"outputBlockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"outputTransactionId": "626a45932fc6794e8317dd998632e124f1670e05d720186fb76c32a52aeff086",
"outputIndex": 0,
"outputGlobalIndex": 53955929,
"outputCreatedAt": 1735082,
"outputSettledAt": 1735084,
"ergoTree": "18ef11cc010400040004000442044404460440058080801005000580040580800805000580040580040500058004043605000580040500042e04300432042c058080801005000580040580800805000580040580040500058004043a043c043e0438058080801005000580040580800805000580040580040500058004041204340500058004050004000402040404060408040a040c040e0410041204140404040205800405000580040410041204000402040404060408040a040c040e04020400040404020580040500058004040c040404020406040804420444044604480448042e04300432042c05808080100500058004058080080500058004058004050005800404340436043a043c043e0438058080801005000580040580800805000580040580040500058004040204080101041001010414050005000500050005000500050005000101050104000402040404060408040a040c040e0500050005000500056405c80104000402040404060408040a040c040e05000500050005000500040e04100500050004120500050005a09c0105a09c0101010414041401010440058080801005000580040580800805000580040580040500058004010105000580040500058004051405000580040502050205000580040502051404020404d83bd601e4c6a70408d602b2a5730000d60393e4e301047301d604e4e3020ed605e4e3030ed606e4c6a70564d607e4e3000ed608b2db6501fe730200d609e4e30504d60ae4c672080411d60b7ea305d60ce4e3040ed60d7eb2720c73030005d60e7eb2720c73040005d60f7eb2720c73050005d6109a9a9a9c7eb2720c7306000573079c958f720d73089a720d7309720d730a9c958f720e730b9a720e730c720e730d958f720f730e9a720f730f720fd6117eb2720c73100005d612958f721173119a721173127211d6139172127313d6147eb2720c73140005d6157eb2720c73150005d6167eb2720c73160005d6179a9a9a9c7eb2720c7317000573189c958f721473199a7214731a7214731b9c958f7215731c9a7215731d7215731e958f7216731f9a721673207216d6187eb2720c73210005d6197eb2720c73220005d61a7eb2720c73230005d61b9a9a9a9c7eb2720c7324000573259c958f721873269a72187327721873289c958f721973299a7219732a7219732b958f721a732c9a721a732d721ad61c92720b9a721bb2720a732e00d61d7eb2720c732f0005d61e958f721d73309a721d7331721dd61f95721c7332721ed620830b047333733473357336733773387339733a733b733c733dd621ad7220d9012104d802d6239c7221733ed6247eb2720c9a7223733f00059a9c7eb2720c722300057340958f722473419a722473427224d622b27221734300d623b27221734400d62483080473457346734773487349734a734b734cd625b2e4c67208061d997209734d00d626b27225734e00d627ad7220d9012704d802d6299c7227734fd62a7eb272059a7229735000059a9c7eb27205722900057351958f722a73529a722a7353722ad628b2720a735400d629b27225735500d62ab27225735600d62b9a7222b27225735700d62c9a7223b27225735800d62d7eb2720573590005d62e7eb27205735a0005d62f7eb27205735b0005d6307eb27205735c0005d6317eb2720c735d0005d6327eb27205735e0005d6337eb27205735f0005d6347eb2720573600005d6359a9a9a9c7eb272057361000573629c958f723273639a72327364723273659c958f723373669a7233736772337368958f723473699a7234736a7234d6367eb27205736b0005d6377eb27205736c0005d6387eb27205736d0005d6397eb27205736e0005d63a7eb27205736f0005d63b9a9a9a9c7eb272057370000573719c958f723873729a72387373723873749c958f723973759a7239737672397377958f723a73789a723a7379723aea027201d1edededededededededededededededededededededed93c27202c2a792c17202c1a793db6401e4c672020564db6401957203e4dc640c72060283013c0e0e8602720472057207e4dc640d72060283013c0e0e8602720472057207aedb63087208d9013c4d0e938c723c01e4e3060eed927209737a907e720905b2720a737b0092720b7210957213737c92720b9a7217b2720a737d00957213737e8f721fb2720a737f00957203ededededededed937222738001937223738101af7224d9013c0493b27221723c0073820193721773830193721e73840193721273850193721b73860193721073870173880195937226738901af830804738a01738b01738c01738d01738e01738f01739001739101d9013c0493b27221723c00b27227723c00d806d63cb272217d72260400d63d997228723cd63e9590723d7392017393019d9c7229723d7228d63fb272217d722a0400d640997228723fd641959072407394017395019d9c9d9c722973960173970172407228af830804739801739901739a01739b01739c01739d01739e01739f01d9014204d801d6447e72420595937244722693b272277242009a723c9591723e723d723d958f723e73a00173a101723e95937244722a93b272277242009a723f9591724172407240958f724173a20173a301724193b27221724200b27227724200af7224d9013c0490b27227723c00722890b0722473a401d9013c41049a8c723c01b272278c723c0200b2720a73a5010093b2722773a60100958f722b73a70173a801722b93b2722773a90100958f722c73aa0173ab019591722c73ac0173ad01722c95720373ae0193b2722773af0100b2722173b0010095720373b101939a9a9a9c7eb2720573b201000573b3019c958f722d73b4019a722d73b501722d73b6019c958f722e73b7019a722e73b801722e73b901958f722f73ba019a722f73bb01722f721095720373bc0193958f723073bd019a723073be017230958f723173bf019a723173c00172319572139372357217ed92723599720b73c101907235720b93958f723673c2019a723673c3017236957213721e95721c73c4019a721f73c50193958f723773c6019a723773c701723795721399721273c801721295721393723b721b95721ced92723b99720b73c90190723b720b93723b721b93e4c672020408720192c1b2a573ca0100b2720a73cb0100",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 33\n4: 34\n5: 35\n6: 32\n7: 16777216\n8: 0\n9: 256\n10: 65536\n11: 0\n12: 256\n13: 256\n14: 0\n15: 256\n16: 27\n17: 0\n18: 256\n19: 0\n20: 23\n21: 24\n22: 25\n23: 22\n24: 16777216\n25: 0\n26: 256\n27: 65536\n28: 0\n29: 256\n30: 256\n31: 0\n32: 256\n33: 29\n34: 30\n35: 31\n36: 28\n37: 16777216\n38: 0\n39: 256\n40: 65536\n41: 0\n42: 256\n43: 256\n44: 0\n45: 256\n46: 9\n47: 26\n48: 0\n49: 256\n50: 0\n51: 0\n52: 1\n53: 2\n54: 3\n55: 4\n56: 5\n57: 6\n58: 7\n59: 8\n60: 9\n61: 10\n62: 2\n63: 1\n64: 256\n65: 0\n66: 256\n67: 8\n68: 9\n69: 0\n70: 1\n71: 2\n72: 3\n73: 4\n74: 5\n75: 6\n76: 7\n77: 1\n78: 0\n79: 2\n80: 1\n81: 256\n82: 0\n83: 256\n84: 6\n85: 2\n86: 1\n87: 3\n88: 4\n89: 33\n90: 34\n91: 35\n92: 36\n93: 36\n94: 23\n95: 24\n96: 25\n97: 22\n98: 16777216\n99: 0\n100: 256\n101: 65536\n102: 0\n103: 256\n104: 256\n105: 0\n106: 256\n107: 26\n108: 27\n109: 29\n110: 30\n111: 31\n112: 28\n113: 16777216\n114: 0\n115: 256\n116: 65536\n117: 0\n118: 256\n119: 256\n120: 0\n121: 256\n122: 1\n123: 4\n124: true\n125: 8\n126: true\n127: 10\n128: 0\n129: 0\n130: 0\n131: 0\n132: 0\n133: 0\n134: 0\n135: 0\n136: true\n137: -1\n138: 0\n139: 1\n140: 2\n141: 3\n142: 4\n143: 5\n144: 6\n145: 7\n146: 0\n147: 0\n148: 0\n149: 0\n150: 50\n151: 100\n152: 0\n153: 1\n154: 2\n155: 3\n156: 4\n157: 5\n158: 6\n159: 7\n160: 0\n161: 0\n162: 0\n163: 0\n164: 0\n165: 7\n166: 8\n167: 0\n168: 0\n169: 9\n170: 0\n171: 0\n172: 10000\n173: 10000\n174: true\n175: 10\n176: 10\n177: true\n178: 32\n179: 16777216\n180: 0\n181: 256\n182: 65536\n183: 0\n184: 256\n185: 256\n186: 0\n187: 256\n188: true\n189: 0\n190: 256\n191: 0\n192: 256\n193: 10\n194: 0\n195: 256\n196: 1\n197: 1\n198: 0\n199: 256\n200: 1\n201: 10\n202: 1\n203: 2",
"ergoTreeScript": "{\n val prop1 = SELF.R4[SigmaProp].get\n val box2 = OUTPUTS(placeholder[Int](0))\n val bool3 = getVar[Int](1.toByte).get == placeholder[Int](1)\n val coll4 = getVar[Coll[Byte]](2.toByte).get\n val coll5 = getVar[Coll[Byte]](3.toByte).get\n val avlTree6 = SELF.R5[AvlTree].get\n val coll7 = getVar[Coll[Byte]](0.toByte).get\n val box8 = CONTEXT.dataInputs(placeholder[Int](2))\n val i9 = getVar[Int](5.toByte).get\n val coll10 = box8.R4[Coll[Long]].get\n val l11 = HEIGHT.toLong\n val coll12 = getVar[Coll[Byte]](4.toByte).get\n val l13 = coll12(placeholder[Int](3)).toLong\n val l14 = coll12(placeholder[Int](4)).toLong\n val l15 = coll12(placeholder[Int](5)).toLong\n val l16 = coll12(placeholder[Int](6)).toLong * placeholder[Long](7) + if (l13 < placeholder[Long](8)) { l13 + placeholder[Long](9) } else {\n l13\n } * placeholder[Long](10) + if (l14 < placeholder[Long](11)) { l14 + placeholder[Long](12) } else { l14 } * placeholder[Long](13) + if (l15 < placeholder[\n Long\n ](14)) { l15 + placeholder[Long](15) } else { l15 }\n val l17 = coll12(placeholder[Int](16)).toLong\n val l18 = if (l17 < placeholder[Long](17)) { l17 + placeholder[Long](18) } else { l17 }\n val bool19 = l18 > placeholder[Long](19)\n val l20 = coll12(placeholder[Int](20)).toLong\n val l21 = coll12(placeholder[Int](21)).toLong\n val l22 = coll12(placeholder[Int](22)).toLong\n val l23 = coll12(placeholder[Int](23)).toLong * placeholder[Long](24) + if (l20 < placeholder[Long](25)) { l20 + placeholder[Long](26) } else {\n l20\n } * placeholder[Long](27) + if (l21 < placeholder[Long](28)) { l21 + placeholder[Long](29) } else { l21 } * placeholder[Long](30) + if (l22 < placeholder[\n Long\n ](31)) { l22 + placeholder[Long](32) } else { l22 }\n val l24 = coll12(placeholder[Int](33)).toLong\n val l25 = coll12(placeholder[Int](34)).toLong\n val l26 = coll12(placeholder[Int](35)).toLong\n val l27 = coll12(placeholder[Int](36)).toLong * placeholder[Long](37) + if (l24 < placeholder[Long](38)) { l24 + placeholder[Long](39) } else {\n l24\n } * placeholder[Long](40) + if (l25 < placeholder[Long](41)) { l25 + placeholder[Long](42) } else { l25 } * placeholder[Long](43) + if (l26 < placeholder[\n Long\n ](44)) { l26 + placeholder[Long](45) } else { l26 }\n val bool28 = l11 >= l27 + coll10(placeholder[Int](46))\n val l29 = coll12(placeholder[Int](47)).toLong\n val l30 = if (l29 < placeholder[Long](48)) { l29 + placeholder[Long](49) } else { l29 }\n val l31 = if (bool28) { placeholder[Long](50) } else { l30 }\n val coll32 = Coll[Int](\n placeholder[Int](51), placeholder[Int](52), placeholder[Int](53), placeholder[Int](54), placeholder[Int](55), placeholder[Int](56), placeholder[Int](\n 57\n ), placeholder[Int](58), placeholder[Int](59), placeholder[Int](60), placeholder[Int](61)\n )\n val coll33 = coll32.map({(i33: Int) =>\n val i35 = i33 * placeholder[Int](62)\n val l36 = coll12(i35 + placeholder[Int](63)).toLong\n coll12(i35).toLong * placeholder[Long](64) + if (l36 < placeholder[Long](65)) { l36 + placeholder[Long](66) } else { l36 }\n })\n val l34 = coll33(placeholder[Int](67))\n val l35 = coll33(placeholder[Int](68))\n val coll36 = Coll[Int](\n placeholder[Int](69), placeholder[Int](70), placeholder[Int](71), placeholder[Int](72), placeholder[Int](73), placeholder[Int](74), placeholder[Int](\n 75\n ), placeholder[Int](76)\n )\n val coll37 = box8.R6[Coll[Coll[Long]]].get(i9 - placeholder[Int](77))\n val l38 = coll37(placeholder[Int](78))\n val coll39 = coll32.map({(i39: Int) =>\n val i41 = i39 * placeholder[Int](79)\n val l42 = coll5(i41 + placeholder[Int](80)).toLong\n coll5(i41).toLong * placeholder[Long](81) + if (l42 < placeholder[Long](82)) { l42 + placeholder[Long](83) } else { l42 }\n })\n val l40 = coll10(placeholder[Int](84))\n val l41 = coll37(placeholder[Int](85))\n val l42 = coll37(placeholder[Int](86))\n val l43 = l34 + coll37(placeholder[Int](87))\n val l44 = l35 + coll37(placeholder[Int](88))\n val l45 = coll5(placeholder[Int](89)).toLong\n val l46 = coll5(placeholder[Int](90)).toLong\n val l47 = coll5(placeholder[Int](91)).toLong\n val l48 = coll5(placeholder[Int](92)).toLong\n val l49 = coll12(placeholder[Int](93)).toLong\n val l50 = coll5(placeholder[Int](94)).toLong\n val l51 = coll5(placeholder[Int](95)).toLong\n val l52 = coll5(placeholder[Int](96)).toLong\n val l53 = coll5(placeholder[Int](97)).toLong * placeholder[Long](98) + if (l50 < placeholder[Long](99)) { l50 + placeholder[Long](100) } else {\n l50\n } * placeholder[Long](101) + if (l51 < placeholder[Long](102)) { l51 + placeholder[Long](103) } else { l51 } * placeholder[Long](104) + if (l52 < placeholder[\n Long\n ](105)) { l52 + placeholder[Long](106) } else { l52 }\n val l54 = coll5(placeholder[Int](107)).toLong\n val l55 = coll5(placeholder[Int](108)).toLong\n val l56 = coll5(placeholder[Int](109)).toLong\n val l57 = coll5(placeholder[Int](110)).toLong\n val l58 = coll5(placeholder[Int](111)).toLong\n val l59 = coll5(placeholder[Int](112)).toLong * placeholder[Long](113) + if (l56 < placeholder[Long](114)) { l56 + placeholder[Long](115) } else {\n l56\n } * placeholder[Long](116) + if (l57 < placeholder[Long](117)) { l57 + placeholder[Long](118) } else { l57 } * placeholder[Long](119) + if (l58 < placeholder[\n Long\n ](120)) { l58 + placeholder[Long](121) } else { l58 }\n prop1 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((box2.propositionBytes == SELF.propositionBytes) && (box2.value >= SELF.value)) && (\n box2.R5[AvlTree].get.digest == if (bool3) {\n avlTree6.insert(Coll[(Coll[Byte], Coll[Byte])]((coll4, coll5)), coll7).get\n } else { avlTree6.update(Coll[(Coll[Byte], Coll[Byte])]((coll4, coll5)), coll7).get }.digest\n )\n ) && box8.tokens.exists({(tuple60: (Coll[Byte], Long)) => tuple60._1 == getVar[Coll[Byte]](6.toByte).get })\n ) && ((i9 >= placeholder[Int](122)) && (i9.toLong <= coll10(placeholder[Int](123))))\n ) && (l11 >= l16)\n ) && if (bool19) { placeholder[Boolean](124) } else { l11 >= l23 + coll10(placeholder[Int](125)) }\n ) && if (bool19) { placeholder[Boolean](126) } else { l31 < coll10(placeholder[Int](127)) }\n ) && if (bool3) {\n (\n (\n (\n (\n (\n ((l34 == placeholder[Long](128)) && (l35 == placeholder[Long](129))) && coll36.forall(\n {(i60: Int) => coll33(i60) == placeholder[Long](130) }\n )\n ) && (l23 == placeholder[Long](131))\n ) && (l30 == placeholder[Long](132))\n ) && (l18 == placeholder[Long](133))\n ) && (l27 == placeholder[Long](134))\n ) && (l16 == placeholder[Long](135))\n } else { placeholder[Boolean](136) }\n ) && if (l38 == placeholder[Long](137)) {\n Coll[Int](\n placeholder[Int](138), placeholder[Int](139), placeholder[Int](140), placeholder[Int](141), placeholder[Int](\n 142\n ), placeholder[Int](143), placeholder[Int](144), placeholder[Int](145)\n ).forall({(i60: Int) => coll33(i60) == coll39(i60) })\n } else {(\n val l60 = coll33(l38.toInt)\n val l61 = l40 - l60\n val l62 = if (l61 <= placeholder[Long](146)) { placeholder[Long](147) } else { l41 * l61 / l40 }\n val l63 = coll33(l42.toInt)\n val l64 = l40 - l63\n val l65 = if (l64 <= placeholder[Long](148)) { placeholder[Long](149) } else {\n l41 * placeholder[Long](150) / placeholder[Long](151) * l64 / l40\n }\n Coll[Int](\n placeholder[Int](152), placeholder[Int](153), placeholder[Int](154), placeholder[Int](155), placeholder[Int](\n 156\n ), placeholder[Int](157), placeholder[Int](158), placeholder[Int](159)\n ).forall({(i66: Int) =>\n val l68 = i66.toLong\n if (l68 == l38) { coll39(i66) == l60 + if (l62 > l61) { l61 } else { if (l62 < placeholder[Long](160)) { placeholder[Long](161) } else { l62 } } } else { if (l68 == l42) { coll39(i66) == l63 + if (l65 > l64) { l64 } else { if (l65 < placeholder[Long](162)) { placeholder[Long](163) } else { l65 } } } else { coll33(i66) == coll39(i66) } }\n })\n )}\n ) && coll36.forall({(i60: Int) => coll39(i60) <= l40 })\n ) && (\n coll36.fold(placeholder[Long](164), {(tuple60: (Long, Int)) => tuple60._1 + coll39(tuple60._2) }) <= coll10(placeholder[Int](165))\n )\n ) && (coll39(placeholder[Int](166)) == if (l43 < placeholder[Long](167)) { placeholder[Long](168) } else { l43 })\n ) && (\n coll39(placeholder[Int](169)) == if (l44 < placeholder[Long](170)) { placeholder[Long](171) } else {\n if (l44 > placeholder[Long](172)) { placeholder[Long](173) } else { l44 }\n }\n )\n ) && if (bool3) { placeholder[Boolean](174) } else { coll39(placeholder[Int](175)) == coll33(placeholder[Int](176)) }\n ) && if (bool3) { placeholder[Boolean](177) } else {\n coll5(placeholder[Int](178)).toLong * placeholder[Long](179) + if (l45 < placeholder[Long](180)) { l45 + placeholder[Long](181) } else {\n l45\n } * placeholder[Long](182) + if (l46 < placeholder[Long](183)) { l46 + placeholder[Long](184) } else { l46 } * placeholder[Long](\n 185\n ) + if (l47 < placeholder[Long](186)) { l47 + placeholder[Long](187) } else { l47 } == l16\n }\n ) && if (bool3) { placeholder[Boolean](188) } else {\n if (l48 < placeholder[Long](189)) { l48 + placeholder[Long](190) } else { l48 } == if (l49 < placeholder[Long](191)) {\n l49 + placeholder[Long](192)\n } else { l49 }\n }\n ) && if (bool19) { l53 == l23 } else { (l53 >= l11 - placeholder[Long](193)) && (l53 <= l11) }\n ) && (\n if (l54 < placeholder[Long](194)) { l54 + placeholder[Long](195) } else { l54 } == if (bool19) { l30 } else {\n if (bool28) { placeholder[Long](196) } else { l31 + placeholder[Long](197) }\n }\n )\n ) && (if (l55 < placeholder[Long](198)) { l55 + placeholder[Long](199) } else { l55 } == if (bool19) { l18 - placeholder[Long](200) } else { l18 })\n ) && if (bool19) { l59 == l27 } else { if (bool28) { (l59 >= l11 - placeholder[Long](201)) && (l59 <= l11) } else { l59 == l27 } }\n ) && (box2.R4[SigmaProp].get == prop1)\n ) && (OUTPUTS(placeholder[Int](202)).value >= coll10(placeholder[Int](203)))\n )\n}",
"address": "2VVqGk9FecboPph58C7qSshAdipD5W5wZ3VuDbmp2Z6go9ddEvvhP8qMW6hnkEpEyytNAnBZSb21srBw5uvNiRvxJnxzUSsENmgB69A9kPpJTmQr9rosgqFhecwDZsK5RCqE5V6qm83e4vQW98PGnZrpi2DZfd7NNPcDFhMuPiV3v7WHoRskDomFWvU75ttN6HJ1NEuDABQPLQtCBC1NMY3fFPPqTH56qzVY4SQtW4iMoBqD5ECFsSVdLkFFGr6roBbZNZPUdU3j54jbDhooQfeUeT5n6kxpvhg3narUs1wHkejfsz58aPgRVeHZccpChgEkdihQAE7TByoQ6ii3DsshqDGFdk3QYe2WvYTcEGUsijdDPo5AMPPfSUc3XjgUDvAiZjiuc3s4NxZpgAyXMTqyDed2rwV2jSid9iKMWpupdgojKtXGqr5e5656mJpdxWeCLRUkcBQpkf3LrixagFcPzYD1Jem3d1hpxeikrHoj8XiEfuDiDoa49faRLfuyH8QVj5JeDxFiwvym4ShgWsomJF87okajhPjmNzUtbKmW4A71a3GftHPX8w2Kj18oH1HpvADAHQnUGJfhKz1iyV1hZEePERhQa7bKtLhHqZvo4LtkzpJ442vSyRecti9YvHxUy9y7ona1uAotGpez1Y3yErEMXnfY7vL8KVPV1LUZas5ubBqqNnrkeMHm8mcBWvNFed45DfkAoPwFoSvFEHc6ekf4DYWudyUmz7gmmb9SA8AXcx2AQhaeoHPw7Ufr72vV1R2u3PtbYV5ARzEGiuwchCXwdVJkzErZvD9HY9hvnjhneM1jb79CH7BDTY8sHeTahsHrbKy5EoGZuhgHNups7kjK9KbPDSFLZopxnBfZZhJnKXgPm49e3Nxi1tBHw255yEsEUxsvWy6rWuBnQTbpt3cBWjGVRDppbnVPygcVrSUCUEiCSfZDzE4SGczJuKraXY9gaC6vPHLN9zh46pwBb2XPnuaQQNA5k4QprsPRqQReiU26NJN8BYeoR3WGxgpWpsg3dYYnvpyyGquHLsp3p2WyYveuZv9E6dgzynyLjRgxTyzQD1inQEvGMEBhKehfKVnsZrKAWFkXSg86buLZXXwYAdD5BjCtAFbiwrEk4TJxN6eMJxySSgV9mjHJ2NoQsT9RHcZBRnrZmxJhDPtZojfMw9ShuFw2A6cfEbAQBoSZt8hMWXHHff6CHxdrCwUf6crXdwWry2SAgNjjywn16Vxk6Vm7M2ik91wn7wt32Q5oEKYj2mFHxmcaLtnugKa9CF3kBo6BdSWckypuJB3os8nARnWxF7113FG8t3fBPnESoxcyMyE6d7DmnuvBN6eVhBGc4VAyPfJn5YUqJFdvtfSgpBeMPPJu8VNHTz3T4r4NeXHZYnowNCZE17xBs3pftgy9LFnyrr11taWPfJd1pFZMenhZRJ4fQk7QtPmrKXgzFoePnjQ2MmiZvaHEPmxrW1ehK5SEaCgtiPZwaDQfZbtjmnC2tbuLzk54GctQJFZG9ctv1msehiX9MDQWSvob69cz6etZmmjyBrpiwWx2XuCxVeqVpX4UkwGFKBzQyYnZdZ9B3X5NXUVGkzbgyyLd9zgTRp4TvftrdpPaYDco1t2os8Hmu3trzRxTzegPPpk8W2XVjYP35t6JQJsFYMuHqUru8Cyj6qpmWkVZQuKGBuibWGGqEkVf8A37h2gidycjMPDyVZDv4YNLoVSnSJc2rzRKaVg38pwfpWJhaAmKmJTsE2UMNkRx6dqp7iM7CZj6ddXQ74YrpBErew9skXR7MiwDCdnHKXZUcmAEPznhgz1ED28C7Qh8CmiBZ6S8juu2hKarp6bwKGuF7naGeAcSKkz73V4Q75ApKCF2p1fHxKasLEFwQNLTHvkw5jmvuxU7Aag4e41No2zGhbh3A5p2Nc5SEqHtPCFfCMiRtGy6MPF2r5BtzQdmVgrYPS2zfcH3mdQjT6KjdEBFeRVLC7vkLYsxBxnutr5Ba78uFw1CD2EjpTpGJu7zx5ASGcPcuT9YxJm3KP2ZMzAVpGB1k3S9yHhdYqJr5aqodF8Q2pqHxW4Ujuf2XKoRjwi9oDmSJ9j9ywcYxu4mRAWuXiyJbbJbo3bHXfnLfynmj8WtpTukCxkugVBHHTyTnrK2XvrVE8ssBAiNnyyd7ZfWB5RfntWam3WGa8vz4Z1nF67F12AC4pvgdha4GThgu8Q2uspWhwGHNniK6n5gn3H4PhdLXfoKpt9yhEu5RLxkqqBJiEDq1bMMAKdyGC5GwSLQXJyF8J4ZrgYugsBuV4J2AZBrAtcrnve4wtj7oggXK76CBwVT5ZS8M7sgKpSpBWbjmiZZS8hedqNw7ECqmthNZjehofVYU3bQoiXoogQy9HJtqGekDzLma9HW1KfCLE8Hf2Cx3JCBYz9sRrv3w7baKr3J5ti9sAqJPajEji5hea11iqKbkZAk71btknA9yuyn3Y2xRuJY54Vo3rTemHs23pXJG5oHKneL2CHe8sj1t1KJGrxF8ZAJxRKYabsPWGUNkGgR9KxP29UTbnJ9f5K5S7d1SJoQD6UVsS3KGZpEyD5dqrkXqMRMEXaSy2aNYVSpgjE1mkxrcY8S7mokW3epHAjPKgZktY4VMtYygWZpWTMUgUj31hpoPtaKN3R5EgoxhZtiZ382jN6VqhHfcC3tLvMx32oc9xPL1VQFr5eLcwu6H9hMdDKz1cXUdJU32wn3Z5UyDFCTZ2Ew5kpt3pZxKFDz3xmnbLeCbqrJwx7gxhqKCqoL9arpyGeeMn8aVhgoK67QnTWMV9pGHPXkEaE4a3EBsgpaKPm6VBjs9MePvs9H9SuxD5PeWLtRdfAtCYhHdG35BsE7TEG8uxcYJ7syRks6NrViaSX1QLFTEso5U8UJNv1568RnRdYGBfCRLBbM9nP5HZ5gDujDbNrCGgMnFi8dgmTFTXb4rVJWCfNCcrM2SoT6jGriGE1qTDDRmUjxGrfoe4W3TZFJBkLKSfR2tcfsR8VEXTY3NV91AUGj8wsJb5dGVSEi3RVdCW77WMkFpofN8rfva9zJuaP7eMLmcwE8aXbUbCUVhiD7AStqAL3QKCzgKZGCkEaxu6y3B4BsTaTzBpndTy2bztdYmSepvM",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "08cd02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a",
"sigmaType": "SSigmaProp",
"renderedValue": "02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a"
},
"R5": {
"serializedValue": "644ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "0099370924b80243e578acd98ff86d5a610a9c6c9743dbb90285596f45a7cb19",
"value": 279000000,
"index": 1,
"spendingProof": "321cd1e9fbff668d5d76df7a4cdc4dd167e08b68921594d70e1a64db394bbeb0d9830d0ef03caf94f85eb84d8a5c9981ed0804be423852c0",
"outputBlockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"outputTransactionId": "626a45932fc6794e8317dd998632e124f1670e05d720186fb76c32a52aeff086",
"outputIndex": 2,
"outputGlobalIndex": 53955931,
"outputCreatedAt": 1735082,
"outputSettledAt": 1735084,
"ergoTree": "0008cd02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(afe418,bb3ad0,...)))}",
"address": "9frXR12ZVMBVLt2i74SsYYGToDooP9TUqwTabhTzGKLAYonS31h",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "509dbffef38162fd3fe3c7e2b3ff7945de3b1804276fa7c666fbb2cfc8c21616",
"value": 500000000,
"index": 0,
"outputBlockId": "15691192e238c0c714c93ab43da1d4c81dbd1b590b2f0346542cee8786aecf13",
"outputTransactionId": "2345ccbcc2ad29f7c4fc22272469ecb0c23e8151afc987beebecd7b595385cb6",
"outputIndex": 0,
"ergoTree": "18e7010c040204000418041604000400040204040580897a040e050008cd02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6ad802d6017ea305d602e4c6a7041195927201b27202730000d803d603b2a5730100d604c1a7d605e4c672030711d1edededededed93e4c672030411720293db6401e4c672030964db6401e4c6a7056492c172039a7204b2720273020092e4c6720306059a7201b27202730300aedb63087203d901064d0e938c7206018cb2db6308a773040001909a9ab27205730500b27205730600b27205730700997204730893b27205730900730a730b",
"address": "4TBTuCLiNTDFUCBWjA1rf3B6LFumDddJxZ9kSsT6bNf59XbR7rg4UgSG21qwqg2N1fQ9Yt71vbqQYWMfVeWZgH6ZpFB83MTHLU7NBFboqKR7tL9vj7SBf2aLpnFRBgqkzHDswwsovjJ5iURCCd54bdpoadmQMnsChTFJB2e9ajMidYLzvdpBG7GsvsT2wYwqXiowwJzkdPFQz2BrNyVLXePsaRfy1EPmqwfUWJt3UntEadEND6zTJWRWyfXCLqtPPjNJ4AfZBizFBE33yJVQ9wni7vCJj7FTc4EC8YnpuEvis6GjRHhZ7tMwGJSgWCYZPgm9ZP",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "644ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R6": {
"serializedValue": "1d07050006e807e012e707050208e807e012d704050400e807e0120005060ae807e012e807050802e807e0128f03050a04e807e012b817050101008727b817",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[0,3,500,1200,-500],[1,4,500,1200,-300],[2,0,500,1200,0],[3,5,500,1200,500],[4,1,500,1200,-200],[5,2,500,1200,1500],[-1,-1,0,-2500,1500]]"
},
"R8": {
"serializedValue": "1d05083c0a143c0a1e0000081e3c140a3c1e000008141e3c0a143c00000828281e1e1e14000008141432141e3c0000",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[30,5,10,30,5,15,0,0],[15,30,10,5,30,15,0,0],[10,15,30,5,10,30,0,0],[20,20,15,15,15,10,0,0],[10,10,25,10,15,30,0,0]]"
},
"R7": {
"serializedValue": "1d0306e80202a01f000080ade20406d00502c03e04904e80dac40906a00b040004f02e80b48913",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[180,1,2000,0,0,5000000],[360,1,4000,2,5000,10000000],[720,2,0,2,3000,20000000]]"
},
"R9": {
"serializedValue": "110678a001aa01be01c801f001",
"sigmaType": "Coll[SLong]",
"renderedValue": "[60,80,85,95,100,120]"
},
"R4": {
"serializedValue": "111700f2e7d30180dac40980c2d72f0e06807de0d403e802a00b04148084af5f50463200000000000a0c",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1735161,10000000,50000000,7,3,8000,30000,180,720,2,10,100000000,40,35,25,0,0,0,0,0,5,6]"
}
}
}
],
"outputs": [
{
"boxId": "22cd974536f83420ec4bb9af8a817f287a694bb305353130fdccfc8596fa5f35",
"transactionId": "4de76aee75d0ed19e7e02e85ea1b3f59149fa1cd3bd51302aa6b1d6f506e9020",
"blockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"value": 10000000,
"index": 0,
"globalIndex": 53955932,
"creationHeight": 1735082,
"settlementHeight": 1735084,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 33\n4: 34\n5: 35\n6: 32\n7: 16777216\n8: 0\n9: 256\n10: 65536\n11: 0\n12: 256\n13: 256\n14: 0\n15: 256\n16: 27\n17: 0\n18: 256\n19: 0\n20: 23\n21: 24\n22: 25\n23: 22\n24: 16777216\n25: 0\n26: 256\n27: 65536\n28: 0\n29: 256\n30: 256\n31: 0\n32: 256\n33: 29\n34: 30\n35: 31\n36: 28\n37: 16777216\n38: 0\n39: 256\n40: 65536\n41: 0\n42: 256\n43: 256\n44: 0\n45: 256\n46: 9\n47: 26\n48: 0\n49: 256\n50: 0\n51: 0\n52: 1\n53: 2\n54: 3\n55: 4\n56: 5\n57: 6\n58: 7\n59: 8\n60: 9\n61: 10\n62: 2\n63: 1\n64: 256\n65: 0\n66: 256\n67: 8\n68: 9\n69: 0\n70: 1\n71: 2\n72: 3\n73: 4\n74: 5\n75: 6\n76: 7\n77: 1\n78: 0\n79: 2\n80: 1\n81: 256\n82: 0\n83: 256\n84: 6\n85: 2\n86: 1\n87: 3\n88: 4\n89: 33\n90: 34\n91: 35\n92: 36\n93: 36\n94: 23\n95: 24\n96: 25\n97: 22\n98: 16777216\n99: 0\n100: 256\n101: 65536\n102: 0\n103: 256\n104: 256\n105: 0\n106: 256\n107: 26\n108: 27\n109: 29\n110: 30\n111: 31\n112: 28\n113: 16777216\n114: 0\n115: 256\n116: 65536\n117: 0\n118: 256\n119: 256\n120: 0\n121: 256\n122: 1\n123: 4\n124: true\n125: 8\n126: true\n127: 10\n128: 0\n129: 0\n130: 0\n131: 0\n132: 0\n133: 0\n134: 0\n135: 0\n136: true\n137: -1\n138: 0\n139: 1\n140: 2\n141: 3\n142: 4\n143: 5\n144: 6\n145: 7\n146: 0\n147: 0\n148: 0\n149: 0\n150: 50\n151: 100\n152: 0\n153: 1\n154: 2\n155: 3\n156: 4\n157: 5\n158: 6\n159: 7\n160: 0\n161: 0\n162: 0\n163: 0\n164: 0\n165: 7\n166: 8\n167: 0\n168: 0\n169: 9\n170: 0\n171: 0\n172: 10000\n173: 10000\n174: true\n175: 10\n176: 10\n177: true\n178: 32\n179: 16777216\n180: 0\n181: 256\n182: 65536\n183: 0\n184: 256\n185: 256\n186: 0\n187: 256\n188: true\n189: 0\n190: 256\n191: 0\n192: 256\n193: 10\n194: 0\n195: 256\n196: 1\n197: 1\n198: 0\n199: 256\n200: 1\n201: 10\n202: 1\n203: 2",
"ergoTreeScript": "{\n val prop1 = SELF.R4[SigmaProp].get\n val box2 = OUTPUTS(placeholder[Int](0))\n val bool3 = getVar[Int](1.toByte).get == placeholder[Int](1)\n val coll4 = getVar[Coll[Byte]](2.toByte).get\n val coll5 = getVar[Coll[Byte]](3.toByte).get\n val avlTree6 = SELF.R5[AvlTree].get\n val coll7 = getVar[Coll[Byte]](0.toByte).get\n val box8 = CONTEXT.dataInputs(placeholder[Int](2))\n val i9 = getVar[Int](5.toByte).get\n val coll10 = box8.R4[Coll[Long]].get\n val l11 = HEIGHT.toLong\n val coll12 = getVar[Coll[Byte]](4.toByte).get\n val l13 = coll12(placeholder[Int](3)).toLong\n val l14 = coll12(placeholder[Int](4)).toLong\n val l15 = coll12(placeholder[Int](5)).toLong\n val l16 = coll12(placeholder[Int](6)).toLong * placeholder[Long](7) + if (l13 < placeholder[Long](8)) { l13 + placeholder[Long](9) } else {\n l13\n } * placeholder[Long](10) + if (l14 < placeholder[Long](11)) { l14 + placeholder[Long](12) } else { l14 } * placeholder[Long](13) + if (l15 < placeholder[\n Long\n ](14)) { l15 + placeholder[Long](15) } else { l15 }\n val l17 = coll12(placeholder[Int](16)).toLong\n val l18 = if (l17 < placeholder[Long](17)) { l17 + placeholder[Long](18) } else { l17 }\n val bool19 = l18 > placeholder[Long](19)\n val l20 = coll12(placeholder[Int](20)).toLong\n val l21 = coll12(placeholder[Int](21)).toLong\n val l22 = coll12(placeholder[Int](22)).toLong\n val l23 = coll12(placeholder[Int](23)).toLong * placeholder[Long](24) + if (l20 < placeholder[Long](25)) { l20 + placeholder[Long](26) } else {\n l20\n } * placeholder[Long](27) + if (l21 < placeholder[Long](28)) { l21 + placeholder[Long](29) } else { l21 } * placeholder[Long](30) + if (l22 < placeholder[\n Long\n ](31)) { l22 + placeholder[Long](32) } else { l22 }\n val l24 = coll12(placeholder[Int](33)).toLong\n val l25 = coll12(placeholder[Int](34)).toLong\n val l26 = coll12(placeholder[Int](35)).toLong\n val l27 = coll12(placeholder[Int](36)).toLong * placeholder[Long](37) + if (l24 < placeholder[Long](38)) { l24 + placeholder[Long](39) } else {\n l24\n } * placeholder[Long](40) + if (l25 < placeholder[Long](41)) { l25 + placeholder[Long](42) } else { l25 } * placeholder[Long](43) + if (l26 < placeholder[\n Long\n ](44)) { l26 + placeholder[Long](45) } else { l26 }\n val bool28 = l11 >= l27 + coll10(placeholder[Int](46))\n val l29 = coll12(placeholder[Int](47)).toLong\n val l30 = if (l29 < placeholder[Long](48)) { l29 + placeholder[Long](49) } else { l29 }\n val l31 = if (bool28) { placeholder[Long](50) } else { l30 }\n val coll32 = Coll[Int](\n placeholder[Int](51), placeholder[Int](52), placeholder[Int](53), placeholder[Int](54), placeholder[Int](55), placeholder[Int](56), placeholder[Int](\n 57\n ), placeholder[Int](58), placeholder[Int](59), placeholder[Int](60), placeholder[Int](61)\n )\n val coll33 = coll32.map({(i33: Int) =>\n val i35 = i33 * placeholder[Int](62)\n val l36 = coll12(i35 + placeholder[Int](63)).toLong\n coll12(i35).toLong * placeholder[Long](64) + if (l36 < placeholder[Long](65)) { l36 + placeholder[Long](66) } else { l36 }\n })\n val l34 = coll33(placeholder[Int](67))\n val l35 = coll33(placeholder[Int](68))\n val coll36 = Coll[Int](\n placeholder[Int](69), placeholder[Int](70), placeholder[Int](71), placeholder[Int](72), placeholder[Int](73), placeholder[Int](74), placeholder[Int](\n 75\n ), placeholder[Int](76)\n )\n val coll37 = box8.R6[Coll[Coll[Long]]].get(i9 - placeholder[Int](77))\n val l38 = coll37(placeholder[Int](78))\n val coll39 = coll32.map({(i39: Int) =>\n val i41 = i39 * placeholder[Int](79)\n val l42 = coll5(i41 + placeholder[Int](80)).toLong\n coll5(i41).toLong * placeholder[Long](81) + if (l42 < placeholder[Long](82)) { l42 + placeholder[Long](83) } else { l42 }\n })\n val l40 = coll10(placeholder[Int](84))\n val l41 = coll37(placeholder[Int](85))\n val l42 = coll37(placeholder[Int](86))\n val l43 = l34 + coll37(placeholder[Int](87))\n val l44 = l35 + coll37(placeholder[Int](88))\n val l45 = coll5(placeholder[Int](89)).toLong\n val l46 = coll5(placeholder[Int](90)).toLong\n val l47 = coll5(placeholder[Int](91)).toLong\n val l48 = coll5(placeholder[Int](92)).toLong\n val l49 = coll12(placeholder[Int](93)).toLong\n val l50 = coll5(placeholder[Int](94)).toLong\n val l51 = coll5(placeholder[Int](95)).toLong\n val l52 = coll5(placeholder[Int](96)).toLong\n val l53 = coll5(placeholder[Int](97)).toLong * placeholder[Long](98) + if (l50 < placeholder[Long](99)) { l50 + placeholder[Long](100) } else {\n l50\n } * placeholder[Long](101) + if (l51 < placeholder[Long](102)) { l51 + placeholder[Long](103) } else { l51 } * placeholder[Long](104) + if (l52 < placeholder[\n Long\n ](105)) { l52 + placeholder[Long](106) } else { l52 }\n val l54 = coll5(placeholder[Int](107)).toLong\n val l55 = coll5(placeholder[Int](108)).toLong\n val l56 = coll5(placeholder[Int](109)).toLong\n val l57 = coll5(placeholder[Int](110)).toLong\n val l58 = coll5(placeholder[Int](111)).toLong\n val l59 = coll5(placeholder[Int](112)).toLong * placeholder[Long](113) + if (l56 < placeholder[Long](114)) { l56 + placeholder[Long](115) } else {\n l56\n } * placeholder[Long](116) + if (l57 < placeholder[Long](117)) { l57 + placeholder[Long](118) } else { l57 } * placeholder[Long](119) + if (l58 < placeholder[\n Long\n ](120)) { l58 + placeholder[Long](121) } else { l58 }\n prop1 && sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((box2.propositionBytes == SELF.propositionBytes) && (box2.value >= SELF.value)) && (\n box2.R5[AvlTree].get.digest == if (bool3) {\n avlTree6.insert(Coll[(Coll[Byte], Coll[Byte])]((coll4, coll5)), coll7).get\n } else { avlTree6.update(Coll[(Coll[Byte], Coll[Byte])]((coll4, coll5)), coll7).get }.digest\n )\n ) && box8.tokens.exists({(tuple60: (Coll[Byte], Long)) => tuple60._1 == getVar[Coll[Byte]](6.toByte).get })\n ) && ((i9 >= placeholder[Int](122)) && (i9.toLong <= coll10(placeholder[Int](123))))\n ) && (l11 >= l16)\n ) && if (bool19) { placeholder[Boolean](124) } else { l11 >= l23 + coll10(placeholder[Int](125)) }\n ) && if (bool19) { placeholder[Boolean](126) } else { l31 < coll10(placeholder[Int](127)) }\n ) && if (bool3) {\n (\n (\n (\n (\n (\n ((l34 == placeholder[Long](128)) && (l35 == placeholder[Long](129))) && coll36.forall(\n {(i60: Int) => coll33(i60) == placeholder[Long](130) }\n )\n ) && (l23 == placeholder[Long](131))\n ) && (l30 == placeholder[Long](132))\n ) && (l18 == placeholder[Long](133))\n ) && (l27 == placeholder[Long](134))\n ) && (l16 == placeholder[Long](135))\n } else { placeholder[Boolean](136) }\n ) && if (l38 == placeholder[Long](137)) {\n Coll[Int](\n placeholder[Int](138), placeholder[Int](139), placeholder[Int](140), placeholder[Int](141), placeholder[Int](\n 142\n ), placeholder[Int](143), placeholder[Int](144), placeholder[Int](145)\n ).forall({(i60: Int) => coll33(i60) == coll39(i60) })\n } else {(\n val l60 = coll33(l38.toInt)\n val l61 = l40 - l60\n val l62 = if (l61 <= placeholder[Long](146)) { placeholder[Long](147) } else { l41 * l61 / l40 }\n val l63 = coll33(l42.toInt)\n val l64 = l40 - l63\n val l65 = if (l64 <= placeholder[Long](148)) { placeholder[Long](149) } else {\n l41 * placeholder[Long](150) / placeholder[Long](151) * l64 / l40\n }\n Coll[Int](\n placeholder[Int](152), placeholder[Int](153), placeholder[Int](154), placeholder[Int](155), placeholder[Int](\n 156\n ), placeholder[Int](157), placeholder[Int](158), placeholder[Int](159)\n ).forall({(i66: Int) =>\n val l68 = i66.toLong\n if (l68 == l38) { coll39(i66) == l60 + if (l62 > l61) { l61 } else { if (l62 < placeholder[Long](160)) { placeholder[Long](161) } else { l62 } } } else { if (l68 == l42) { coll39(i66) == l63 + if (l65 > l64) { l64 } else { if (l65 < placeholder[Long](162)) { placeholder[Long](163) } else { l65 } } } else { coll33(i66) == coll39(i66) } }\n })\n )}\n ) && coll36.forall({(i60: Int) => coll39(i60) <= l40 })\n ) && (\n coll36.fold(placeholder[Long](164), {(tuple60: (Long, Int)) => tuple60._1 + coll39(tuple60._2) }) <= coll10(placeholder[Int](165))\n )\n ) && (coll39(placeholder[Int](166)) == if (l43 < placeholder[Long](167)) { placeholder[Long](168) } else { l43 })\n ) && (\n coll39(placeholder[Int](169)) == if (l44 < placeholder[Long](170)) { placeholder[Long](171) } else {\n if (l44 > placeholder[Long](172)) { placeholder[Long](173) } else { l44 }\n }\n )\n ) && if (bool3) { placeholder[Boolean](174) } else { coll39(placeholder[Int](175)) == coll33(placeholder[Int](176)) }\n ) && if (bool3) { placeholder[Boolean](177) } else {\n coll5(placeholder[Int](178)).toLong * placeholder[Long](179) + if (l45 < placeholder[Long](180)) { l45 + placeholder[Long](181) } else {\n l45\n } * placeholder[Long](182) + if (l46 < placeholder[Long](183)) { l46 + placeholder[Long](184) } else { l46 } * placeholder[Long](\n 185\n ) + if (l47 < placeholder[Long](186)) { l47 + placeholder[Long](187) } else { l47 } == l16\n }\n ) && if (bool3) { placeholder[Boolean](188) } else {\n if (l48 < placeholder[Long](189)) { l48 + placeholder[Long](190) } else { l48 } == if (l49 < placeholder[Long](191)) {\n l49 + placeholder[Long](192)\n } else { l49 }\n }\n ) && if (bool19) { l53 == l23 } else { (l53 >= l11 - placeholder[Long](193)) && (l53 <= l11) }\n ) && (\n if (l54 < placeholder[Long](194)) { l54 + placeholder[Long](195) } else { l54 } == if (bool19) { l30 } else {\n if (bool28) { placeholder[Long](196) } else { l31 + placeholder[Long](197) }\n }\n )\n ) && (if (l55 < placeholder[Long](198)) { l55 + placeholder[Long](199) } else { l55 } == if (bool19) { l18 - placeholder[Long](200) } else { l18 })\n ) && if (bool19) { l59 == l27 } else { if (bool28) { (l59 >= l11 - placeholder[Long](201)) && (l59 <= l11) } else { l59 == l27 } }\n ) && (box2.R4[SigmaProp].get == prop1)\n ) && (OUTPUTS(placeholder[Int](202)).value >= coll10(placeholder[Int](203)))\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "08cd02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a",
"sigmaType": "SSigmaProp",
"renderedValue": "02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a"
},
"R5": {
"serializedValue": "6419c68552d7585410b87ba96f8a14673bdd680b5f73e676a7f1d19cd4bd73732101072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "5a826f883545357c37c72b870551c3c63234fad1774191eae4476fc7743bcec8",
"mainChain": true
},
{
"boxId": "9a6f8ff0ccdc4ffafe01ed6b716b1d92607117f3f8786a115279ddaf36fe2e56",
"transactionId": "4de76aee75d0ed19e7e02e85ea1b3f59149fa1cd3bd51302aa6b1d6f506e9020",
"blockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"value": 10000000,
"index": 1,
"globalIndex": 53955933,
"creationHeight": 1735082,
"settlementHeight": 1735084,
"ergoTree": "0008cd02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(afe418,bb3ad0,...)))}",
"address": "9frXR12ZVMBVLt2i74SsYYGToDooP9TUqwTabhTzGKLAYonS31h",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "85137a4ec67da3698c73b544e0771d593c49e0fcfdff31fa9b8cfcc1fb2610ba",
"mainChain": true
},
{
"boxId": "3b9d04059ce45bf9f3a0bf5b1dc044e12bc4073e8f63a9317212e56825b036f2",
"transactionId": "4de76aee75d0ed19e7e02e85ea1b3f59149fa1cd3bd51302aa6b1d6f506e9020",
"blockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"value": 1000000,
"index": 2,
"globalIndex": 53955934,
"creationHeight": 1735082,
"settlementHeight": 1735084,
"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": "46d4d64acc528504d0d60be5e78a373b00fa6d4a613289b283aacfd102ad94ff",
"mainChain": true
},
{
"boxId": "37649828a3dc0716ed1fea46b34db120551c7999ae9905782aa6980eed383d3c",
"transactionId": "4de76aee75d0ed19e7e02e85ea1b3f59149fa1cd3bd51302aa6b1d6f506e9020",
"blockId": "2b3a7860efc1bb9f067316a037cb03ac4fd82ff8dbe47e990573f02830d7511b",
"value": 268000000,
"index": 3,
"globalIndex": 53955935,
"creationHeight": 1735082,
"settlementHeight": 1735084,
"ergoTree": "0008cd02afe418c057a023b10079d17237eabb8abf0b6c139f287eee1aee4e30fac51a6a",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(afe418,bb3ad0,...)))}",
"address": "9frXR12ZVMBVLt2i74SsYYGToDooP9TUqwTabhTzGKLAYonS31h",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "5a826f883545357c37c72b870551c3c63234fad1774191eae4476fc7743bcec8",
"mainChain": true
}
],
"size": 3019,
"isUnconfirmed": false
}