Transaction
ID: eab508c8e7...4682
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0036 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
18.38 ERG
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0026 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0036 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
17.5 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.875 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0016 ERG
Unspent
Transaction Details
Confirmations: 576,746
Total coins transferred: 18.38 ERG
Fees: 0.0016 ERG
Fees per byte: 0.000000293 ERG
Raw Transaction Data
{
"id": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"inclusionHeight": 1179930,
"timestamp": 1705490062930,
"index": 3,
"globalIndex": 6483670,
"numConfirmations": 576746,
"inputs": [
{
"boxId": "14d1f2b063c6a81d9ce461c2a2335d560c16a6bc68e5ef8695e933866ad89a89",
"value": 3600000,
"index": 0,
"spendingProof": null,
"outputBlockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"outputTransactionId": "a8b0470f0047aef9a142cd90f4a76cf1f866174d7d5b5a7633c02ab44c100527",
"outputIndex": 1,
"outputGlobalIndex": 36175793,
"outputCreatedAt": 1179927,
"outputSettledAt": 1179930,
"ergoTree": "10a3010400040604040e20b96b1a4b112782e3b6e94d0c6634016c2152e8c155a3be6e0c38697607edeff10e20605f80e54ae552510aac1293a38c4ea5c66a2e74cf334e697f22f2ff0c54261d0400040208cd026bbc157c325433b5f43d481e4035cc9f4c9ae580a833dd4e2a380473ffa71dc004040502010104080400040004040408040c040205010502040204000e087f000fbaf55fab7e04020400040204020400050205020400040005020402040404060ef901100c040004000400040005000500040001010e20e540cceffd3b8dd0f401193576cc413467039695969427df94454193dddfb375050005000580a8c301d802d601db6308b2a4730000d602e4c6a7040895ed91b172017301938cb2720173020001e4c6a7050ed1938ce4c6b2a5730300094405017202d802d603d07202d604db6308a7ea02d1968302019683020192b0ada5d90105639593c272057203c1720573047305d90105599a8c7205018c720502c1a79591b172047306aea5d9010563ed93db63087205720493c272057203730793b0ada5d90105639593cbc272057308c172057309730ad90105599a8c7205018c720502730b72020580b1bd020ee201100804000580a8c3010400050204000e013004020580a8c301d807d601b2a5730000d602e4c6a7094405d603e4c67201040ed604e4c67201050ed605e4c67201070ed606e4c67201080ed607e4c67201090ed1968302019683040193c1720199c1a7730193c27201d08c72020193b2db630872017302008602c5a773039683020193cbb3b3b3b3b3b3b3b3b37a7eb172030572037a7eb172040572047a7eb172050572057a7eb172060572067a7eb17207057207cbe4dc640ae4c6b2db6501fe730400046402cb7a8c720202e4e3000e93e4c67201060e730593c1b2a5730600730704000502040405000e201b2a58ccac0c8f6a4a1df9a4a8394739df70f45391d5708bf178734a31d1f7a20400040004000500050205020580aeb0c8060580897a040005020580aeb0c80604040502040a04080580a8c30104040502040c040a0580897a05010580aeb0c8060580897a040005010580aeb0c80604040502040a04080580a8c30104040502040c040a0580897a0580e1dcf888010580bca6b182010580e1dcf8880104040502040a04080580a8c30104040502040c040a0580897a010005020580aeb0c8060580897a040005020580aeb0c80604040502040a04080580a8c30104040502040c040a0580897a050205010580aeb0c80604000502040205010580aeb0c80604040502040a04080580a8c30104040502040c040a0580897a0580e1dcf888010580bca6b18201040005020580e1dcf8880104040502040a04080580a8c30104040502040c040a0580897a0100010001000580c3bbc20608cd0306b34156d30cadf134c7c0b245a5ff2debcbe42ff5c86859c74d4013ee9b482904000580a8c3010580897a04000400040205000500040004020580a8c30104040580897a0100d812d601e4c6a70759d602db6807b2db6502fe730000d603908c7201017202d604e4c6a7080dd605b27204730100d606b27204730200d6078c720102d6087303d6097304d60ae4c6a7091ad60bb2720a730500d60cb27204730600d60d7307d60ed9010e0195ec720e93e4c6b2a473080005057309730a938cb2db6308b2a5730b00730c00018cb2db6308a7730d0001d60fb2720a730e00d610b27204730f00d611b27204731000d612b2720a73110095ecec72037205720695ec91720772029372077312d80fd613e4e30163d614e4c6a70605d6159a72147313d616e4c672130905d617b2a4731400d618b2a5731500d619e4c67218063c0c3c0e0e3c0c3c0e580c3c0e58d61a8c721902d61b7316d61ce4c6a70564d61d9372157216d61eb2a5731700d61f95ef721dd805d61fdb6308721ed620b2721f731800d621db6308a7d622b2721f731900d623b27221731a009683040193722086028cb27221731b0001731c938c722001720993722286028c722301998c722302731d938c7222017208d802d61fdb6308721ed620b2721f731e009683030193722086028cb2db6308a7731f00017320938c722001720993b1721f7321d620b2a5732200d621b2a5732300d19683070193c572137208907215721693c2721773249683080193c17218732593c27218732693b2db6308721873270086027208732893e4c672180404732993cbb0e4c67218050c4c0e7a732ad901223c0e4c0ed801d6248c722202b3b38c7222018c7224017a7e8c72240205732b93cbb08c721a02b3b08c721a01b3b08c72190195937eb28cb2e4c67218080c3c0e0e732c0002732d0004732e7a732f7a7330d901223c0e3c0e0ed803d6248c722202d6258c722401d6268c722402b3b3b3b38c7222017a7eb172250572257a7eb17226057226721bd901223c0e3c0e58d803d6248c722202d6258c722401d6268c722402b3b3b3b38c7222017a7eb172250572257a7e8c722601057a7e8c72260205721bd901223c0e3c0e58d803d6248c722202d6258c722401d6268c722402b3b3b3b38c7222017a7eb172250572257a7e8c722601057a7e8c72260205cbe4dc640a721c02cb7a7214e4e3000e93e4c67218070e720893e4c672180944058602e4c672170408721495721d9683060193c1721ec1a793c2721ec2a7721f93db6401e4c6721e0464db6401e4c6a7046493db6401e4c6721e0564db6401721c93e4c6721e060572159683090193c1721ec1a793c2721ec2a7721f93db6401e4c6721e0464db6401e4c6a7046493db6401e4c6721e0564db6401721c93e4c6721e0605721593e4c6721e0759720193e4c6721e080d720493e4c6721e091a720a95720395ed720caedb63087217d901224d0e9372228602720b7331d802d622c17217d6238f72227332968304019683030193c17220733393b2db630872207334008602720b733593c27220d0720dda720e01927222733693c195ed722391e4c6b2a473370005057338b2a5733900b2a5733a00733b92c195ed722391e4c6b2a4733c000505733db2a5733e00b2a5733f00734095ed7210aedb63087217d901224d0eed938c722201720f928c7222027341d802d622c17217d6238f72227342968304019683030193c17220734393c27220d0720d93b2db630872207344008602720f7345da720e01927222734693c195ed722391e4c6b2a473470005057348b2a5734900b2a5734a00734b92c195ed722391e4c6b2a4734c000505734db2a5734e00b2a5734f007350957211d802d622c17217d6238f72227351968304019683020193c17220735293c27220d0720dda720e01927222735393c195ed722391e4c6b2a473540005057355b2a5735600b2a5735700735892c195ed722391e4c6b2a47359000505735ab2a5735b00b2a5735c00735d735e95ec7205ed7206720c95ed7206aedb63087217d901224d0e9372228602720b735fd802d622c17217d6238f72227360968304019683030193c17220736193b2db630872207362008602720b736393c27220d0720dda720e01927222736493c195ed722391e4c6b2a473650005057366b2a5736700b2a5736800736992c195ed722391e4c6b2a4736a000505736bb2a5736c00b2a5736d00736e95ed7205aedb63087217d901224d0e93722286027212736f95ed7210aedb63087217d901224d0eed938c722201720f928c7222027370d803d622db63087220d623c17217d6248f72237371968304019683030193b2722273720086027212737393b272227374008602720f737593c27220d0720dda720e01927223737693c195ed722491e4c6b2a473770005057378b2a5737900b2a5737a00737b92c195ed722491e4c6b2a4737c000505737db2a5737e00b2a5737f00738001957211d802d622c17217d6238f7222738101968304019683030193c1722073820193b2db63087220738301008602721273840193c27220d0720dda720e0192722273850193c195ed722391e4c6b2a4738601000505738701b2a573880100b2a573890100738a0192c195ed722391e4c6b2a4738b01000505738c01b2a5738d0100b2a5738e0100738f017390017391017392019683020193c1722173930193c27221d0739401d801d613b2a573950100d1968303019683030193c172139999c1a773960173970193c27213d0720d95b2720473980100d802d614b2db6308721373990100d615b2db6308a7739a0100968303019372147215938c721401720893b0ada5d9011663b0addb63087216d901184d0e8c721802739b01d90118599a8c7218018c721802739c01d90116599a8c7216018c7216028c721502afa5d901146393b1db63087214739d0193c1b2a5739e0100739f0192c1b2a573a0010073a101d173a201",
"ergoTreeConstants": "0: 0\n1: 3\n2: 2\n3: Coll(-71,107,26,75,17,39,-126,-29,-74,-23,77,12,102,52,1,108,33,82,-24,-63,85,-93,-66,110,12,56,105,118,7,-19,-17,-15)\n4: Coll(96,95,-128,-27,74,-27,82,81,10,-84,18,-109,-93,-116,78,-91,-58,106,46,116,-49,51,78,105,127,34,-14,-1,12,84,38,29)\n5: 0\n6: 1\n7: SigmaProp(ProveDlog(ECPoint(6bbc15,c866a0,...)))\n8: 2\n9: 1\n10: true\n11: 4\n12: 0\n13: 0\n14: 2\n15: 4\n16: 6\n17: 1\n18: -1\n19: 1\n20: 1\n21: 0\n22: Coll(127,0,15,-70,-11,95,-85,126)\n23: 1\n24: 0\n25: 1\n26: 1\n27: 0\n28: 1\n29: 1\n30: 0\n31: 0\n32: 1\n33: 1\n34: 2\n35: 3\n36: Coll(16,12,4,0,4,0,4,0,4,0,5,0,5,0,4,0,1,1,14,32,-27,64,-52,-17,-3,59,-115,-48,-12,1,25,53,118,-52,65,52,103,3,-106,-107,-106,-108,39,-33,-108,69,65,-109,-35,-33,-77,117,5,0,5,0,5,-128,-88,-61,1,-40,2,-42,1,-37,99,8,-78,-92,115,0,0,-42,2,-28,-58,-89,4,8,-107,-19,-111,-79,114,1,115,1,-109,-116,-78,114,1,115,2,0,1,-28,-58,-89)\n37: 2600000\n38: Coll(16,8,4,0,5,-128,-88,-61,1,4,0,5,2,4,0,14,1,48,4,2,5,-128,-88,-61,1,-40,7,-42,1,-78,-91,115,0,0,-42,2,-28,-58,-89,9,68,5,-42,3,-28,-58,114,1,4,14,-42,4,-28,-58,114,1,5,14,-42,5,-28,-58,114,1,7,14,-42,6,-28,-58,114,1,8,14,-42,7,-28,-58,114,1,9,14,-47,-106,-125,2,1,-106,-125,4,1,-109,-63,114,1,-103,-63,-89,115,1)\n39: 0\n40: 1\n41: 2\n42: 0\n43: Coll(27,42,88,-52,-84,12,-113,106,74,29,-7,-92,-88,57,71,57,-33,112,-12,83,-111,-43,112,-117,-15,120,115,74,49,-47,-9,-94)\n44: 0\n45: 0\n46: 0\n47: 0\n48: 1\n49: 1\n50: 881200000\n51: 1000000\n52: 0\n53: 1\n54: 881200000\n55: 2\n56: 1\n57: 5\n58: 4\n59: 1600000\n60: 2\n61: 1\n62: 6\n63: 5\n64: 1000000\n65: -1\n66: 881200000\n67: 1000000\n68: 0\n69: -1\n70: 881200000\n71: 2\n72: 1\n73: 5\n74: 4\n75: 1600000\n76: 2\n77: 1\n78: 6\n79: 5\n80: 1000000\n81: 18380200000\n82: 17500000000\n83: 18380200000\n84: 2\n85: 1\n86: 5\n87: 4\n88: 1600000\n89: 2\n90: 1\n91: 6\n92: 5\n93: 1000000\n94: false\n95: 1\n96: 881200000\n97: 1000000\n98: 0\n99: 1\n100: 881200000\n101: 2\n102: 1\n103: 5\n104: 4\n105: 1600000\n106: 2\n107: 1\n108: 6\n109: 5\n110: 1000000\n111: 1\n112: -1\n113: 881200000\n114: 0\n115: 1\n116: 1\n117: -1\n118: 881200000\n119: 2\n120: 1\n121: 5\n122: 4\n123: 1600000\n124: 2\n125: 1\n126: 6\n127: 5\n128: 1000000\n129: 18380200000\n130: 17500000000\n131: 0\n132: 1\n133: 18380200000\n134: 2\n135: 1\n136: 5\n137: 4\n138: 1600000\n139: 2\n140: 1\n141: 6\n142: 5\n143: 1000000\n144: false\n145: false\n146: false\n147: 875000000\n148: SigmaProp(ProveDlog(ECPoint(6b3415,1b9c7b,...)))\n149: 0\n150: 1600000\n151: 1000000\n152: 0\n153: 0\n154: 1\n155: 0\n156: 0\n157: 0\n158: 1\n159: 1600000\n160: 2\n161: 1000000\n162: false",
"ergoTreeScript": "{\n val tuple1 = SELF.R7[(Long, Long)].get\n val l2 = CONTEXT.headers(placeholder[Int](0)).timestamp\n val bool3 = tuple1._1 <= l2\n val coll4 = SELF.R8[Coll[Boolean]].get\n val bool5 = coll4(placeholder[Int](1))\n val bool6 = coll4(placeholder[Int](2))\n val l7 = tuple1._2\n val coll8 = placeholder[Coll[Byte]](3)\n val coll9 = placeholder[Coll[Byte]](4)\n val coll10 = SELF.R9[Coll[Coll[Byte]]].get\n val coll11 = coll10(placeholder[Int](5))\n val bool12 = coll4(placeholder[Int](6))\n val prop13 = placeholder[SigmaProp](7)\n val func14 = {(bool14: Boolean) =>\n if (bool14 || (INPUTS(placeholder[Int](8)).R5[Long].get == placeholder[Long](9))) { placeholder[Boolean](10) } else {\n OUTPUTS(placeholder[Int](11)).tokens(placeholder[Int](12))._1 == SELF.tokens(placeholder[Int](13))._1\n }\n }\n val coll15 = coll10(placeholder[Int](14))\n val bool16 = coll4(placeholder[Int](15))\n val bool17 = coll4(placeholder[Int](16))\n val coll18 = coll10(placeholder[Int](17))\n if ((bool3 || bool5) || bool6) { if ((l7 > l2) || (l7 == placeholder[Long](18))) {(\n val box19 = getVar[Box](1.toByte).get\n val l20 = SELF.R6[Long].get\n val l21 = l20 + placeholder[Long](19)\n val l22 = box19.R9[Long].get\n val box23 = INPUTS(placeholder[Int](20))\n val box24 = OUTPUTS(placeholder[Int](21))\n val tuple25 = box24.R6[(Coll[(Coll[Byte], Coll[Byte])], (Coll[(Coll[Byte], (Int, Int))], Coll[(Coll[Byte], (Int, Int))]))].get\n val tuple26 = tuple25._2\n val coll27 = placeholder[Coll[Byte]](22)\n val avlTree28 = SELF.R5[AvlTree].get\n val bool29 = l21 == l22\n val box30 = OUTPUTS(placeholder[Int](23))\n val bool31 = if (!bool29) {(\n val coll31 = box30.tokens\n val tuple32 = coll31(placeholder[Int](24))\n val coll33 = SELF.tokens\n val tuple34 = coll31(placeholder[Int](25))\n val tuple35 = coll33(placeholder[Int](26))\n allOf(Coll[Boolean](tuple32 == (coll33(placeholder[Int](27))._1, placeholder[Long](28)), tuple32._1 == coll9, tuple34 == (tuple35._1, tuple35._2 - placeholder[Long](29)), tuple34._1 == coll8))\n )} else {(\n val coll31 = box30.tokens\n val tuple32 = coll31(placeholder[Int](30))\n allOf(Coll[Boolean](tuple32 == (SELF.tokens(placeholder[Int](31))._1, placeholder[Long](32)), tuple32._1 == coll9, coll31.size == placeholder[Int](33)))\n )}\n val box32 = OUTPUTS(placeholder[Int](34))\n val box33 = OUTPUTS(placeholder[Int](35))\n sigmaProp(allOf(Coll[Boolean](box19.id == coll8, l21 <= l22, box23.propositionBytes == placeholder[Coll[Byte]](36), allOf(Coll[Boolean](box24.value == placeholder[Long](37), box24.propositionBytes == placeholder[Coll[Byte]](38), box24.tokens(placeholder[Int](39)) == (coll8, placeholder[Long](40)), box24.R4[Int].get == placeholder[Int](41), blake2b256(box24.R5[Coll[(Coll[Byte], Int)]].get.fold(longToByteArray(placeholder[Long](42)), {(tuple34: (Coll[Byte], (Coll[Byte], Int))) =>\n val tuple36 = tuple34._2\n tuple34._1.append(tuple36._1).append(longToByteArray(tuple36._2.toLong))\n })) == placeholder[Coll[Byte]](43), blake2b256(tuple26._2.fold(tuple26._1.fold(tuple25._1.fold(if (box24.R8[Coll[(Coll[Byte], Coll[Byte])]].get(placeholder[Int](44))._2(placeholder[Int](45)).toInt == placeholder[Int](46)) { longToByteArray(placeholder[Long](47)) } else { longToByteArray(placeholder[Long](48)) }, {(tuple34: (Coll[Byte], (Coll[Byte], Coll[Byte]))) =>\n val tuple36 = tuple34._2\n val coll37 = tuple36._1\n val coll38 = tuple36._2\n tuple34._1.append(longToByteArray(coll37.size.toLong)).append(coll37).append(longToByteArray(coll38.size.toLong)).append(coll38)\n }).append(coll27), {(tuple34: (Coll[Byte], (Coll[Byte], (Int, Int)))) =>\n val tuple36 = tuple34._2\n val coll37 = tuple36._1\n val tuple38 = tuple36._2\n tuple34._1.append(longToByteArray(coll37.size.toLong)).append(coll37).append(longToByteArray(tuple38._1.toLong)).append(longToByteArray(tuple38._2.toLong))\n }).append(coll27), {(tuple34: (Coll[Byte], (Coll[Byte], (Int, Int)))) =>\n val tuple36 = tuple34._2\n val coll37 = tuple36._1\n val tuple38 = tuple36._2\n tuple34._1.append(longToByteArray(coll37.size.toLong)).append(coll37).append(longToByteArray(tuple38._1.toLong)).append(longToByteArray(tuple38._2.toLong))\n })) == blake2b256(avlTree28.get(blake2b256(longToByteArray(l20)), getVar[Coll[Byte]](0.toByte).get).get), box24.R7[Coll[Byte]].get == coll8, box24.R9[(SigmaProp, Long)].get == (box23.R4[SigmaProp].get, l20))), if (bool29) { allOf(Coll[Boolean](box30.value == SELF.value, box30.propositionBytes == SELF.propositionBytes, bool31, box30.R4[AvlTree].get.digest == SELF.R4[AvlTree].get.digest, box30.R5[AvlTree].get.digest == avlTree28.digest, box30.R6[Long].get == l21)) } else { allOf(Coll[Boolean](box30.value == SELF.value, box30.propositionBytes == SELF.propositionBytes, bool31, box30.R4[AvlTree].get.digest == SELF.R4[AvlTree].get.digest, box30.R5[AvlTree].get.digest == avlTree28.digest, box30.R6[Long].get == l21, box30.R7[(Long, Long)].get == tuple1, box30.R8[Coll[Boolean]].get == coll4, box30.R9[Coll[Coll[Byte]]].get == coll10)) }, if (bool3) { if (bool12 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => tuple34 == (coll11, placeholder[Long](49)) })) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](50)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](51), box32.tokens(placeholder[Int](52)) == (coll11, placeholder[Long](53)), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](54)), if (bool35 && (INPUTS(placeholder[Int](55)).R5[Long].get > placeholder[Long](56))) { OUTPUTS(placeholder[Int](57)) } else { OUTPUTS(placeholder[Int](58)) }.value == placeholder[Long](59), if (bool35 && (INPUTS(placeholder[Int](60)).R5[Long].get > placeholder[Long](61))) { OUTPUTS(placeholder[Int](62)) } else { OUTPUTS(placeholder[Int](63)) }.value >= placeholder[Long](64)))\n )} else { if (bool16 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => (tuple34._1 == coll15) && (tuple34._2 >= placeholder[Long](65)) })) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](66)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](67), box32.propositionBytes == prop13.propBytes, box32.tokens(placeholder[Int](68)) == (coll15, placeholder[Long](69)))), func14(l34 >= placeholder[Long](70)), if (bool35 && (INPUTS(placeholder[Int](71)).R5[Long].get > placeholder[Long](72))) { OUTPUTS(placeholder[Int](73)) } else { OUTPUTS(placeholder[Int](74)) }.value == placeholder[Long](75), if (bool35 && (INPUTS(placeholder[Int](76)).R5[Long].get > placeholder[Long](77))) { OUTPUTS(placeholder[Int](78)) } else { OUTPUTS(placeholder[Int](79)) }.value >= placeholder[Long](80)))\n )} else { if (bool17) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](81)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](82), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](83)), if (bool35 && (INPUTS(placeholder[Int](84)).R5[Long].get > placeholder[Long](85))) { OUTPUTS(placeholder[Int](86)) } else { OUTPUTS(placeholder[Int](87)) }.value == placeholder[Long](88), if (bool35 && (INPUTS(placeholder[Int](89)).R5[Long].get > placeholder[Long](90))) { OUTPUTS(placeholder[Int](91)) } else { OUTPUTS(placeholder[Int](92)) }.value >= placeholder[Long](93)))\n )} else { placeholder[Boolean](94) } } } } else { if (bool5 || (bool6 && bool12)) { if (bool6 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => tuple34 == (coll11, placeholder[Long](95)) })) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](96)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](97), box32.tokens(placeholder[Int](98)) == (coll11, placeholder[Long](99)), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](100)), if (bool35 && (INPUTS(placeholder[Int](101)).R5[Long].get > placeholder[Long](102))) { OUTPUTS(placeholder[Int](103)) } else { OUTPUTS(placeholder[Int](104)) }.value == placeholder[Long](105), if (bool35 && (INPUTS(placeholder[Int](106)).R5[Long].get > placeholder[Long](107))) { OUTPUTS(placeholder[Int](108)) } else { OUTPUTS(placeholder[Int](109)) }.value >= placeholder[Long](110)))\n )} else { if (bool5 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => tuple34 == (coll18, placeholder[Long](111)) })) { if (bool16 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => (tuple34._1 == coll15) && (tuple34._2 >= placeholder[Long](112)) })) {(\n val coll34 = box32.tokens\n val l35 = box23.value\n val bool36 = l35 < placeholder[Long](113)\n allOf(Coll[Boolean](allOf(Coll[Boolean](coll34(placeholder[Int](114)) == (coll18, placeholder[Long](115)), coll34(placeholder[Int](116)) == (coll15, placeholder[Long](117)), box32.propositionBytes == prop13.propBytes)), func14(l35 >= placeholder[Long](118)), if (bool36 && (INPUTS(placeholder[Int](119)).R5[Long].get > placeholder[Long](120))) { OUTPUTS(placeholder[Int](121)) } else { OUTPUTS(placeholder[Int](122)) }.value == placeholder[Long](123), if (bool36 && (INPUTS(placeholder[Int](124)).R5[Long].get > placeholder[Long](125))) { OUTPUTS(placeholder[Int](126)) } else { OUTPUTS(placeholder[Int](127)) }.value >= placeholder[Long](128)))\n )} else { if (bool17) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](129)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](130), box32.tokens(placeholder[Int](131)) == (coll18, placeholder[Long](132)), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](133)), if (bool35 && (INPUTS(placeholder[Int](134)).R5[Long].get > placeholder[Long](135))) { OUTPUTS(placeholder[Int](136)) } else { OUTPUTS(placeholder[Int](137)) }.value == placeholder[Long](138), if (bool35 && (INPUTS(placeholder[Int](139)).R5[Long].get > placeholder[Long](140))) { OUTPUTS(placeholder[Int](141)) } else { OUTPUTS(placeholder[Int](142)) }.value >= placeholder[Long](143)))\n )} else { placeholder[Boolean](144) } } } else { placeholder[Boolean](145) } } } else { placeholder[Boolean](146) } }, allOf(Coll[Boolean](box33.value == placeholder[Long](147), box33.propositionBytes == placeholder[SigmaProp](148).propBytes)))))\n )} else {(\n val box19 = OUTPUTS(placeholder[Int](149))\n sigmaProp(allOf(Coll[Boolean](allOf(Coll[Boolean](box19.value == SELF.value - placeholder[Long](150) - placeholder[Long](151), box19.propositionBytes == prop13.propBytes, if (coll4(placeholder[Int](152))) {(\n val tuple20 = box19.tokens(placeholder[Int](153))\n val tuple21 = SELF.tokens(placeholder[Int](154))\n allOf(Coll[Boolean](tuple20 == tuple21, tuple20._1 == coll8, OUTPUTS.map({(box22: Box) => box22.tokens.map({(tuple24: (Coll[Byte], Long)) => tuple24._2 }).fold(placeholder[Long](155), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }) }).fold(placeholder[Long](156), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }) == tuple21._2))\n )} else { OUTPUTS.forall({(box20: Box) => box20.tokens.size == placeholder[Int](157) }) })), OUTPUTS(placeholder[Int](158)).value == placeholder[Long](159), OUTPUTS(placeholder[Int](160)).value >= placeholder[Long](161))))\n )} } else { sigmaProp(placeholder[Boolean](162)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "605f80e54ae552510aac1293a38c4ea5c66a2e74cf334e697f22f2ff0c54261d",
"index": 0,
"amount": 1,
"name": "State Box Singleton",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "b96b1a4b112782e3b6e94d0c6634016c2152e8c155a3be6e0c38697607edeff1",
"index": 1,
"amount": 181,
"name": "Comet holds on to dear life",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "64e747a9ee6aa29b5d4d661b681645663da4b012c7088c0ce02cda98d6cc4241150a072000",
"sigmaType": null,
"renderedValue": null
},
"R6": {
"serializedValue": "05de03",
"sigmaType": "SLong",
"renderedValue": "239"
},
"R8": {
"serializedValue": "0d074a",
"sigmaType": "Coll[SBoolean]",
"renderedValue": "[false,true,false,true,false,false,true]"
},
"R7": {
"serializedValue": "5980a4e5df866301",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1701712800000,-1]"
},
"R9": {
"serializedValue": "1a0320e322db18d2511388db75b6704a50f01350bb073c2d8f39a08ae0a3918d9d6f10206d2dc578dc297a4e35d4e143a694bc5989315494334118e6907cf27ac2cb1aad00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e322db18d2511388db75b6704a50f01350bb073c2d8f39a08ae0a3918d9d6f10,6d2dc578dc297a4e35d4e143a694bc5989315494334118e6907cf27ac2cb1aad,]"
},
"R4": {
"serializedValue": "643462a1c6c22b721fc318c0effad379a7483018fd3026ed88f4c32db17cc4a2680a072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "8d4d83f81348b14b2d33c41fc2ca9aedc9d0f01581798702b4692965a61f01c9",
"value": 18381200000,
"index": 1,
"spendingProof": null,
"outputBlockId": "fa97193a01a74e8ef212fd0e9b3f2f796aeace16a2b71df4fb0971746a744d43",
"outputTransactionId": "602b692136f6e7d7a7a9b7d213d836bd2ec85d88ae120e43699d4bf1113ec11b",
"outputIndex": 0,
"outputGlobalIndex": 36175724,
"outputCreatedAt": 1179924,
"outputSettledAt": 1179926,
"ergoTree": "100c040004000400040005000500040001010e20e540cceffd3b8dd0f401193576cc413467039695969427df94454193dddfb375050005000580a8c301d802d601db6308b2a4730000d602e4c6a7040895ed91b172017301938cb2720173020001e4c6a7050ed1938ce4c6b2a5730300094405017202d802d603d07202d604db6308a7ea02d1968302019683020192b0ada5d90105639593c272057203c1720573047305d90105599a8c7205018c720502c1a79591b172047306aea5d9010563ed93db63087205720493c272057203730793b0ada5d90105639593cbc272057308c172057309730ad90105599a8c7205018c720502730b7202",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: true\n8: Coll(-27,64,-52,-17,-3,59,-115,-48,-12,1,25,53,118,-52,65,52,103,3,-106,-107,-106,-108,39,-33,-108,69,65,-109,-35,-33,-77,117)\n9: 0\n10: 0\n11: 1600000",
"ergoTreeScript": "{\n val coll1 = INPUTS(placeholder[Int](0)).tokens\n val prop2 = SELF.R4[SigmaProp].get\n if ((coll1.size > placeholder[Int](1)) && (coll1(placeholder[Int](2))._1 == SELF.R5[Coll[Byte]].get)) {\n sigmaProp(OUTPUTS(placeholder[Int](3)).R9[(SigmaProp, Long)].get._1 == prop2)\n } else {(\n val coll3 = prop2.propBytes\n val coll4 = SELF.tokens\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n OUTPUTS.map({(box5: Box) => if (box5.propositionBytes == coll3) { box5.value } else { placeholder[Long](4) } }).fold(\n placeholder[Long](5), {(tuple5: (Long, Long)) => tuple5._1 + tuple5._2 }\n ) >= SELF.value, if (coll4.size > placeholder[Int](6)) {\n OUTPUTS.exists({(box5: Box) => (box5.tokens == coll4) && (box5.propositionBytes == coll3) })\n } else { placeholder[Boolean](7) }\n )\n ), OUTPUTS.map(\n {(box5: Box) => if (blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](8)) { box5.value } else { placeholder[Long](9) } }\n ).fold(placeholder[Long](10), {(tuple5: (Long, Long)) => tuple5._1 + tuple5._2 }) == placeholder[Long](11)\n )\n )\n ) && prop2\n )}\n}",
"address": "RShSy3CERS1Jt4duhhy4YjcYBvcMdN3VnV9aKETP9xs42JDPE4pjU9MCwCqfF58xnNpHNohcjJBTVULcHanBRA8WSrgKEAcSy2r72o7MyDio1VbxbfwPjtYT9MM5R65wRCRsQzGSRRHq3RaztyZ55jczx8f1rZbTzM8oRDjisei2eQwjsooAtsiwaCFNmNXHyDWmkpcYvqw3aTaXq6sPFVXtJSjgpxrK7e7oMHCEuLvtdX7HJJU9xCjdZzecj5TAujGjY4ne6yEgU8ZW4TPrydWCjYFhmScHsoAhFGHtSd4sPEqPdmDp9ro8WySqaSDMeahqTMD3p2iWDgGn92jTj9xXiC",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "08cd03b34e2663a960b1ea4691c2032779255e515d534d67d0746c27ce6b9428a183b2",
"sigmaType": "SSigmaProp",
"renderedValue": "03b34e2663a960b1ea4691c2032779255e515d534d67d0746c27ce6b9428a183b2"
},
"R5": {
"serializedValue": "0e20605f80e54ae552510aac1293a38c4ea5c66a2e74cf334e697f22f2ff0c54261d",
"sigmaType": "Coll[SByte]",
"renderedValue": "605f80e54ae552510aac1293a38c4ea5c66a2e74cf334e697f22f2ff0c54261d"
}
}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "f4ddfd5fb31b4d2c6dd6dbb523f5e2b88f4181cdad432a56a64ce4a5e2eabb46",
"transactionId": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"value": 2600000,
"index": 0,
"globalIndex": 36175801,
"creationHeight": 1179927,
"settlementHeight": 1179930,
"ergoTree": "100804000580a8c3010400050204000e013004020580a8c301d807d601b2a5730000d602e4c6a7094405d603e4c67201040ed604e4c67201050ed605e4c67201070ed606e4c67201080ed607e4c67201090ed1968302019683040193c1720199c1a7730193c27201d08c72020193b2db630872017302008602c5a773039683020193cbb3b3b3b3b3b3b3b3b37a7eb172030572037a7eb172040572047a7eb172050572057a7eb172060572067a7eb17207057207cbe4dc640ae4c6b2db6501fe730400046402cb7a8c720202e4e3000e93e4c67201060e730593c1b2a57306007307",
"ergoTreeConstants": "0: 0\n1: 1600000\n2: 0\n3: 1\n4: 0\n5: Coll(48)\n6: 1\n7: 1600000",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val tuple2 = SELF.R9[(SigmaProp, Long)].get\n val coll3 = box1.R4[Coll[Byte]].get\n val coll4 = box1.R5[Coll[Byte]].get\n val coll5 = box1.R7[Coll[Byte]].get\n val coll6 = box1.R8[Coll[Byte]].get\n val coll7 = box1.R9[Coll[Byte]].get\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n box1.value == SELF.value - placeholder[Long](1), box1.propositionBytes == tuple2._1.propBytes, box1.tokens(placeholder[Int](2)) == (\n SELF.id, placeholder[Long](3)\n ), allOf(\n Coll[Boolean](\n blake2b256(\n longToByteArray(coll3.size.toLong).append(coll3).append(longToByteArray(coll4.size.toLong)).append(coll4).append(\n longToByteArray(coll5.size.toLong)\n ).append(coll5).append(longToByteArray(coll6.size.toLong)).append(coll6).append(longToByteArray(coll7.size.toLong)).append(coll7)\n ) == blake2b256(\n CONTEXT.dataInputs(placeholder[Int](4)).R4[AvlTree].get.get(blake2b256(longToByteArray(tuple2._2)), getVar[Coll[Byte]](0.toByte).get).get\n ), box1.R6[Coll[Byte]].get == placeholder[Coll[Byte]](5)\n )\n )\n )\n ), OUTPUTS(placeholder[Int](6)).value == placeholder[Long](7)\n )\n )\n )\n}",
"address": "5d7kmvqYj49qiasgGd4989M3PvS4bExHcbtfzTpQqqd4T5hBAugn8s4U4zpcbntjKZVZF8SbFvxZrWZSSgyQiZbuKgL2Sh6CctK2UJKft7sBZNJNceTzNARq2vGxK6UJHZgyc28rofBzSGGp62N8A9YpmDRP9FucvQUqD1uX8oZ17UY29tdYYazSAESEmbqkL5TLLWdLzig9LMMFYL7QysUVBVeM7UDsMxrr7HhbT2XVHo35RYcscVpg2XLWAoezVUgUDGfWz6t4c8zNF2KzK2NptSaXVV4XNmQFweZqUxUkCpXU7ynEmbSJRd2",
"assets": [
{
"tokenId": "b96b1a4b112782e3b6e94d0c6634016c2152e8c155a3be6e0c38697607edeff1",
"index": 0,
"amount": 1,
"name": "Comet holds on to dear life",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0c4c0e02240008cd026bbc157c325433b5f43d481e4035cc9f4c9ae580a833dd4e2a380473ffa71dc064240008cd0201d9c1de450534a438c0487a3cdecad9d979d7dd20509600f26ad622ccb4c17928",
"sigmaType": "Coll[(Coll[SByte], SInt)]",
"renderedValue": "[[0008cd026bbc157c325433b5f43d481e4035cc9f4c9ae580a833dd4e2a380473ffa71dc0,50],[0008cd0201d9c1de450534a438c0487a3cdecad9d979d7dd20509600f26ad622ccb4c179,20]]"
},
"R6": {
"serializedValue": "3c0c3c0e0e3c0c3c0e580c3c0e58080b456e7669726f6e6d656e74084465657020736561044661636506546f6e67756507476c61737365730647726174656404426f64790744656661756c740a416e7461676f6e6973740c4b72616b656e2053717569640d4669727374204d7973746572790a546564647920626561720e5365636f6e64204d797374657279044e6f6e650d5468697264204d797374657279044e6f6e65010452616e6bc604c80600",
"sigmaType": null,
"renderedValue": null
},
"R8": {
"serializedValue": "0c3c0e0e01086578706c696369740100",
"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[6578706c69636974,00]]"
},
"R7": {
"serializedValue": "0e20b96b1a4b112782e3b6e94d0c6634016c2152e8c155a3be6e0c38697607edeff1",
"sigmaType": "Coll[SByte]",
"renderedValue": "b96b1a4b112782e3b6e94d0c6634016c2152e8c155a3be6e0c38697607edeff1"
},
"R9": {
"serializedValue": "4405cd03b34e2663a960b1ea4691c2032779255e515d534d67d0746c27ce6b9428a183b2de03",
"sigmaType": "(SSigmaProp, SLong)",
"renderedValue": "[03b34e2663a960b1ea4691c2032779255e515d534d67d0746c27ce6b9428a183b2,239]"
},
"R4": {
"serializedValue": "0404",
"sigmaType": "SInt",
"renderedValue": "2"
}
},
"spentTransactionId": "8a64d24d835d484a7b7a581e7e350739ab2faa777c72abeccc72ee54f023553a",
"mainChain": true
},
{
"boxId": "ca06e78987e5b89684f693406f60689e1c4ed9a65b67a019408ac0a9fd17941b",
"transactionId": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"value": 3600000,
"index": 1,
"globalIndex": 36175802,
"creationHeight": 1179927,
"settlementHeight": 1179930,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 3\n2: 2\n3: Coll(-71,107,26,75,17,39,-126,-29,-74,-23,77,12,102,52,1,108,33,82,-24,-63,85,-93,-66,110,12,56,105,118,7,-19,-17,-15)\n4: Coll(96,95,-128,-27,74,-27,82,81,10,-84,18,-109,-93,-116,78,-91,-58,106,46,116,-49,51,78,105,127,34,-14,-1,12,84,38,29)\n5: 0\n6: 1\n7: SigmaProp(ProveDlog(ECPoint(6bbc15,c866a0,...)))\n8: 2\n9: 1\n10: true\n11: 4\n12: 0\n13: 0\n14: 2\n15: 4\n16: 6\n17: 1\n18: -1\n19: 1\n20: 1\n21: 0\n22: Coll(127,0,15,-70,-11,95,-85,126)\n23: 1\n24: 0\n25: 1\n26: 1\n27: 0\n28: 1\n29: 1\n30: 0\n31: 0\n32: 1\n33: 1\n34: 2\n35: 3\n36: Coll(16,12,4,0,4,0,4,0,4,0,5,0,5,0,4,0,1,1,14,32,-27,64,-52,-17,-3,59,-115,-48,-12,1,25,53,118,-52,65,52,103,3,-106,-107,-106,-108,39,-33,-108,69,65,-109,-35,-33,-77,117,5,0,5,0,5,-128,-88,-61,1,-40,2,-42,1,-37,99,8,-78,-92,115,0,0,-42,2,-28,-58,-89,4,8,-107,-19,-111,-79,114,1,115,1,-109,-116,-78,114,1,115,2,0,1,-28,-58,-89)\n37: 2600000\n38: Coll(16,8,4,0,5,-128,-88,-61,1,4,0,5,2,4,0,14,1,48,4,2,5,-128,-88,-61,1,-40,7,-42,1,-78,-91,115,0,0,-42,2,-28,-58,-89,9,68,5,-42,3,-28,-58,114,1,4,14,-42,4,-28,-58,114,1,5,14,-42,5,-28,-58,114,1,7,14,-42,6,-28,-58,114,1,8,14,-42,7,-28,-58,114,1,9,14,-47,-106,-125,2,1,-106,-125,4,1,-109,-63,114,1,-103,-63,-89,115,1)\n39: 0\n40: 1\n41: 2\n42: 0\n43: Coll(27,42,88,-52,-84,12,-113,106,74,29,-7,-92,-88,57,71,57,-33,112,-12,83,-111,-43,112,-117,-15,120,115,74,49,-47,-9,-94)\n44: 0\n45: 0\n46: 0\n47: 0\n48: 1\n49: 1\n50: 881200000\n51: 1000000\n52: 0\n53: 1\n54: 881200000\n55: 2\n56: 1\n57: 5\n58: 4\n59: 1600000\n60: 2\n61: 1\n62: 6\n63: 5\n64: 1000000\n65: -1\n66: 881200000\n67: 1000000\n68: 0\n69: -1\n70: 881200000\n71: 2\n72: 1\n73: 5\n74: 4\n75: 1600000\n76: 2\n77: 1\n78: 6\n79: 5\n80: 1000000\n81: 18380200000\n82: 17500000000\n83: 18380200000\n84: 2\n85: 1\n86: 5\n87: 4\n88: 1600000\n89: 2\n90: 1\n91: 6\n92: 5\n93: 1000000\n94: false\n95: 1\n96: 881200000\n97: 1000000\n98: 0\n99: 1\n100: 881200000\n101: 2\n102: 1\n103: 5\n104: 4\n105: 1600000\n106: 2\n107: 1\n108: 6\n109: 5\n110: 1000000\n111: 1\n112: -1\n113: 881200000\n114: 0\n115: 1\n116: 1\n117: -1\n118: 881200000\n119: 2\n120: 1\n121: 5\n122: 4\n123: 1600000\n124: 2\n125: 1\n126: 6\n127: 5\n128: 1000000\n129: 18380200000\n130: 17500000000\n131: 0\n132: 1\n133: 18380200000\n134: 2\n135: 1\n136: 5\n137: 4\n138: 1600000\n139: 2\n140: 1\n141: 6\n142: 5\n143: 1000000\n144: false\n145: false\n146: false\n147: 875000000\n148: SigmaProp(ProveDlog(ECPoint(6b3415,1b9c7b,...)))\n149: 0\n150: 1600000\n151: 1000000\n152: 0\n153: 0\n154: 1\n155: 0\n156: 0\n157: 0\n158: 1\n159: 1600000\n160: 2\n161: 1000000\n162: false",
"ergoTreeScript": "{\n val tuple1 = SELF.R7[(Long, Long)].get\n val l2 = CONTEXT.headers(placeholder[Int](0)).timestamp\n val bool3 = tuple1._1 <= l2\n val coll4 = SELF.R8[Coll[Boolean]].get\n val bool5 = coll4(placeholder[Int](1))\n val bool6 = coll4(placeholder[Int](2))\n val l7 = tuple1._2\n val coll8 = placeholder[Coll[Byte]](3)\n val coll9 = placeholder[Coll[Byte]](4)\n val coll10 = SELF.R9[Coll[Coll[Byte]]].get\n val coll11 = coll10(placeholder[Int](5))\n val bool12 = coll4(placeholder[Int](6))\n val prop13 = placeholder[SigmaProp](7)\n val func14 = {(bool14: Boolean) =>\n if (bool14 || (INPUTS(placeholder[Int](8)).R5[Long].get == placeholder[Long](9))) { placeholder[Boolean](10) } else {\n OUTPUTS(placeholder[Int](11)).tokens(placeholder[Int](12))._1 == SELF.tokens(placeholder[Int](13))._1\n }\n }\n val coll15 = coll10(placeholder[Int](14))\n val bool16 = coll4(placeholder[Int](15))\n val bool17 = coll4(placeholder[Int](16))\n val coll18 = coll10(placeholder[Int](17))\n if ((bool3 || bool5) || bool6) { if ((l7 > l2) || (l7 == placeholder[Long](18))) {(\n val box19 = getVar[Box](1.toByte).get\n val l20 = SELF.R6[Long].get\n val l21 = l20 + placeholder[Long](19)\n val l22 = box19.R9[Long].get\n val box23 = INPUTS(placeholder[Int](20))\n val box24 = OUTPUTS(placeholder[Int](21))\n val tuple25 = box24.R6[(Coll[(Coll[Byte], Coll[Byte])], (Coll[(Coll[Byte], (Int, Int))], Coll[(Coll[Byte], (Int, Int))]))].get\n val tuple26 = tuple25._2\n val coll27 = placeholder[Coll[Byte]](22)\n val avlTree28 = SELF.R5[AvlTree].get\n val bool29 = l21 == l22\n val box30 = OUTPUTS(placeholder[Int](23))\n val bool31 = if (!bool29) {(\n val coll31 = box30.tokens\n val tuple32 = coll31(placeholder[Int](24))\n val coll33 = SELF.tokens\n val tuple34 = coll31(placeholder[Int](25))\n val tuple35 = coll33(placeholder[Int](26))\n allOf(Coll[Boolean](tuple32 == (coll33(placeholder[Int](27))._1, placeholder[Long](28)), tuple32._1 == coll9, tuple34 == (tuple35._1, tuple35._2 - placeholder[Long](29)), tuple34._1 == coll8))\n )} else {(\n val coll31 = box30.tokens\n val tuple32 = coll31(placeholder[Int](30))\n allOf(Coll[Boolean](tuple32 == (SELF.tokens(placeholder[Int](31))._1, placeholder[Long](32)), tuple32._1 == coll9, coll31.size == placeholder[Int](33)))\n )}\n val box32 = OUTPUTS(placeholder[Int](34))\n val box33 = OUTPUTS(placeholder[Int](35))\n sigmaProp(allOf(Coll[Boolean](box19.id == coll8, l21 <= l22, box23.propositionBytes == placeholder[Coll[Byte]](36), allOf(Coll[Boolean](box24.value == placeholder[Long](37), box24.propositionBytes == placeholder[Coll[Byte]](38), box24.tokens(placeholder[Int](39)) == (coll8, placeholder[Long](40)), box24.R4[Int].get == placeholder[Int](41), blake2b256(box24.R5[Coll[(Coll[Byte], Int)]].get.fold(longToByteArray(placeholder[Long](42)), {(tuple34: (Coll[Byte], (Coll[Byte], Int))) =>\n val tuple36 = tuple34._2\n tuple34._1.append(tuple36._1).append(longToByteArray(tuple36._2.toLong))\n })) == placeholder[Coll[Byte]](43), blake2b256(tuple26._2.fold(tuple26._1.fold(tuple25._1.fold(if (box24.R8[Coll[(Coll[Byte], Coll[Byte])]].get(placeholder[Int](44))._2(placeholder[Int](45)).toInt == placeholder[Int](46)) { longToByteArray(placeholder[Long](47)) } else { longToByteArray(placeholder[Long](48)) }, {(tuple34: (Coll[Byte], (Coll[Byte], Coll[Byte]))) =>\n val tuple36 = tuple34._2\n val coll37 = tuple36._1\n val coll38 = tuple36._2\n tuple34._1.append(longToByteArray(coll37.size.toLong)).append(coll37).append(longToByteArray(coll38.size.toLong)).append(coll38)\n }).append(coll27), {(tuple34: (Coll[Byte], (Coll[Byte], (Int, Int)))) =>\n val tuple36 = tuple34._2\n val coll37 = tuple36._1\n val tuple38 = tuple36._2\n tuple34._1.append(longToByteArray(coll37.size.toLong)).append(coll37).append(longToByteArray(tuple38._1.toLong)).append(longToByteArray(tuple38._2.toLong))\n }).append(coll27), {(tuple34: (Coll[Byte], (Coll[Byte], (Int, Int)))) =>\n val tuple36 = tuple34._2\n val coll37 = tuple36._1\n val tuple38 = tuple36._2\n tuple34._1.append(longToByteArray(coll37.size.toLong)).append(coll37).append(longToByteArray(tuple38._1.toLong)).append(longToByteArray(tuple38._2.toLong))\n })) == blake2b256(avlTree28.get(blake2b256(longToByteArray(l20)), getVar[Coll[Byte]](0.toByte).get).get), box24.R7[Coll[Byte]].get == coll8, box24.R9[(SigmaProp, Long)].get == (box23.R4[SigmaProp].get, l20))), if (bool29) { allOf(Coll[Boolean](box30.value == SELF.value, box30.propositionBytes == SELF.propositionBytes, bool31, box30.R4[AvlTree].get.digest == SELF.R4[AvlTree].get.digest, box30.R5[AvlTree].get.digest == avlTree28.digest, box30.R6[Long].get == l21)) } else { allOf(Coll[Boolean](box30.value == SELF.value, box30.propositionBytes == SELF.propositionBytes, bool31, box30.R4[AvlTree].get.digest == SELF.R4[AvlTree].get.digest, box30.R5[AvlTree].get.digest == avlTree28.digest, box30.R6[Long].get == l21, box30.R7[(Long, Long)].get == tuple1, box30.R8[Coll[Boolean]].get == coll4, box30.R9[Coll[Coll[Byte]]].get == coll10)) }, if (bool3) { if (bool12 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => tuple34 == (coll11, placeholder[Long](49)) })) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](50)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](51), box32.tokens(placeholder[Int](52)) == (coll11, placeholder[Long](53)), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](54)), if (bool35 && (INPUTS(placeholder[Int](55)).R5[Long].get > placeholder[Long](56))) { OUTPUTS(placeholder[Int](57)) } else { OUTPUTS(placeholder[Int](58)) }.value == placeholder[Long](59), if (bool35 && (INPUTS(placeholder[Int](60)).R5[Long].get > placeholder[Long](61))) { OUTPUTS(placeholder[Int](62)) } else { OUTPUTS(placeholder[Int](63)) }.value >= placeholder[Long](64)))\n )} else { if (bool16 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => (tuple34._1 == coll15) && (tuple34._2 >= placeholder[Long](65)) })) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](66)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](67), box32.propositionBytes == prop13.propBytes, box32.tokens(placeholder[Int](68)) == (coll15, placeholder[Long](69)))), func14(l34 >= placeholder[Long](70)), if (bool35 && (INPUTS(placeholder[Int](71)).R5[Long].get > placeholder[Long](72))) { OUTPUTS(placeholder[Int](73)) } else { OUTPUTS(placeholder[Int](74)) }.value == placeholder[Long](75), if (bool35 && (INPUTS(placeholder[Int](76)).R5[Long].get > placeholder[Long](77))) { OUTPUTS(placeholder[Int](78)) } else { OUTPUTS(placeholder[Int](79)) }.value >= placeholder[Long](80)))\n )} else { if (bool17) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](81)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](82), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](83)), if (bool35 && (INPUTS(placeholder[Int](84)).R5[Long].get > placeholder[Long](85))) { OUTPUTS(placeholder[Int](86)) } else { OUTPUTS(placeholder[Int](87)) }.value == placeholder[Long](88), if (bool35 && (INPUTS(placeholder[Int](89)).R5[Long].get > placeholder[Long](90))) { OUTPUTS(placeholder[Int](91)) } else { OUTPUTS(placeholder[Int](92)) }.value >= placeholder[Long](93)))\n )} else { placeholder[Boolean](94) } } } } else { if (bool5 || (bool6 && bool12)) { if (bool6 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => tuple34 == (coll11, placeholder[Long](95)) })) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](96)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](97), box32.tokens(placeholder[Int](98)) == (coll11, placeholder[Long](99)), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](100)), if (bool35 && (INPUTS(placeholder[Int](101)).R5[Long].get > placeholder[Long](102))) { OUTPUTS(placeholder[Int](103)) } else { OUTPUTS(placeholder[Int](104)) }.value == placeholder[Long](105), if (bool35 && (INPUTS(placeholder[Int](106)).R5[Long].get > placeholder[Long](107))) { OUTPUTS(placeholder[Int](108)) } else { OUTPUTS(placeholder[Int](109)) }.value >= placeholder[Long](110)))\n )} else { if (bool5 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => tuple34 == (coll18, placeholder[Long](111)) })) { if (bool16 && box23.tokens.exists({(tuple34: (Coll[Byte], Long)) => (tuple34._1 == coll15) && (tuple34._2 >= placeholder[Long](112)) })) {(\n val coll34 = box32.tokens\n val l35 = box23.value\n val bool36 = l35 < placeholder[Long](113)\n allOf(Coll[Boolean](allOf(Coll[Boolean](coll34(placeholder[Int](114)) == (coll18, placeholder[Long](115)), coll34(placeholder[Int](116)) == (coll15, placeholder[Long](117)), box32.propositionBytes == prop13.propBytes)), func14(l35 >= placeholder[Long](118)), if (bool36 && (INPUTS(placeholder[Int](119)).R5[Long].get > placeholder[Long](120))) { OUTPUTS(placeholder[Int](121)) } else { OUTPUTS(placeholder[Int](122)) }.value == placeholder[Long](123), if (bool36 && (INPUTS(placeholder[Int](124)).R5[Long].get > placeholder[Long](125))) { OUTPUTS(placeholder[Int](126)) } else { OUTPUTS(placeholder[Int](127)) }.value >= placeholder[Long](128)))\n )} else { if (bool17) {(\n val l34 = box23.value\n val bool35 = l34 < placeholder[Long](129)\n allOf(Coll[Boolean](allOf(Coll[Boolean](box32.value == placeholder[Long](130), box32.tokens(placeholder[Int](131)) == (coll18, placeholder[Long](132)), box32.propositionBytes == prop13.propBytes)), func14(l34 >= placeholder[Long](133)), if (bool35 && (INPUTS(placeholder[Int](134)).R5[Long].get > placeholder[Long](135))) { OUTPUTS(placeholder[Int](136)) } else { OUTPUTS(placeholder[Int](137)) }.value == placeholder[Long](138), if (bool35 && (INPUTS(placeholder[Int](139)).R5[Long].get > placeholder[Long](140))) { OUTPUTS(placeholder[Int](141)) } else { OUTPUTS(placeholder[Int](142)) }.value >= placeholder[Long](143)))\n )} else { placeholder[Boolean](144) } } } else { placeholder[Boolean](145) } } } else { placeholder[Boolean](146) } }, allOf(Coll[Boolean](box33.value == placeholder[Long](147), box33.propositionBytes == placeholder[SigmaProp](148).propBytes)))))\n )} else {(\n val box19 = OUTPUTS(placeholder[Int](149))\n sigmaProp(allOf(Coll[Boolean](allOf(Coll[Boolean](box19.value == SELF.value - placeholder[Long](150) - placeholder[Long](151), box19.propositionBytes == prop13.propBytes, if (coll4(placeholder[Int](152))) {(\n val tuple20 = box19.tokens(placeholder[Int](153))\n val tuple21 = SELF.tokens(placeholder[Int](154))\n allOf(Coll[Boolean](tuple20 == tuple21, tuple20._1 == coll8, OUTPUTS.map({(box22: Box) => box22.tokens.map({(tuple24: (Coll[Byte], Long)) => tuple24._2 }).fold(placeholder[Long](155), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }) }).fold(placeholder[Long](156), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }) == tuple21._2))\n )} else { OUTPUTS.forall({(box20: Box) => box20.tokens.size == placeholder[Int](157) }) })), OUTPUTS(placeholder[Int](158)).value == placeholder[Long](159), OUTPUTS(placeholder[Int](160)).value >= placeholder[Long](161))))\n )} } else { sigmaProp(placeholder[Boolean](162)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "605f80e54ae552510aac1293a38c4ea5c66a2e74cf334e697f22f2ff0c54261d",
"index": 0,
"amount": 1,
"name": "State Box Singleton",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "b96b1a4b112782e3b6e94d0c6634016c2152e8c155a3be6e0c38697607edeff1",
"index": 1,
"amount": 180,
"name": "Comet holds on to dear life",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "64e747a9ee6aa29b5d4d661b681645663da4b012c7088c0ce02cda98d6cc4241150a072000",
"sigmaType": null,
"renderedValue": null
},
"R6": {
"serializedValue": "05e003",
"sigmaType": "SLong",
"renderedValue": "240"
},
"R8": {
"serializedValue": "0d074a",
"sigmaType": "Coll[SBoolean]",
"renderedValue": "[false,true,false,true,false,false,true]"
},
"R7": {
"serializedValue": "5980a4e5df866301",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1701712800000,-1]"
},
"R9": {
"serializedValue": "1a0320e322db18d2511388db75b6704a50f01350bb073c2d8f39a08ae0a3918d9d6f10206d2dc578dc297a4e35d4e143a694bc5989315494334118e6907cf27ac2cb1aad00",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e322db18d2511388db75b6704a50f01350bb073c2d8f39a08ae0a3918d9d6f10,6d2dc578dc297a4e35d4e143a694bc5989315494334118e6907cf27ac2cb1aad,]"
},
"R4": {
"serializedValue": "643462a1c6c22b721fc318c0effad379a7483018fd3026ed88f4c32db17cc4a2680a072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "1312e076268f241da8cc86fc625fdc6150db60f23ba9c6e18b82367c70c03971",
"mainChain": true
},
{
"boxId": "95df0002480403da94490be1565656d8a095f0a5c273d59634eee3fe1448aea2",
"transactionId": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"value": 17500000000,
"index": 2,
"globalIndex": 36175803,
"creationHeight": 1179927,
"settlementHeight": 1179930,
"ergoTree": "0008cd026bbc157c325433b5f43d481e4035cc9f4c9ae580a833dd4e2a380473ffa71dc0",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6bbc15,c866a0,...)))}",
"address": "9fLWTFY8z2SdrJ9kGE84UmueFM5KUsum7mov2Adc9cCxALGo2SB",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "62bfab1afb5d8b17bcaf771e5cbcd0ec21b2777e70c27114d72b503b7f953d07",
"mainChain": true
},
{
"boxId": "78bb48601e888c9e638771cde2d8781b3d31087336ceeaa1b2fa397a0b653e10",
"transactionId": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"value": 875000000,
"index": 3,
"globalIndex": 36175804,
"creationHeight": 1179927,
"settlementHeight": 1179930,
"ergoTree": "0008cd0306b34156d30cadf134c7c0b245a5ff2debcbe42ff5c86859c74d4013ee9b4829",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6b3415,1b9c7b,...)))}",
"address": "9gWkqeBUdJxgPv9TYUM6mLY1RYkXHmJuHRhHnnM2UZ9qFqySotz",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "3ca83bae4e7cdc41e93d7b00673d169fc3a8dfbbee8adfca7fc4efb8be9e04ea",
"mainChain": true
},
{
"boxId": "af9117c8884ff029ef16dedd12e212e1d96d2a769b2cad0224436ae84e2109e7",
"transactionId": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"value": 1600000,
"index": 4,
"globalIndex": 36175805,
"creationHeight": 1179927,
"settlementHeight": 1179930,
"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": "1845e5736e262aa47464ecff3c97a42174752c066eb410265e6b4d7c6737239d",
"mainChain": true
},
{
"boxId": "4ba54fa9c190e8054a28ab7349c01d7aa3b2e6540e170641a1f7bec4ff38e6f0",
"transactionId": "eab508c8e79a5ebeb2123f44fdd8afeffbf8df31e0caae5717a8bd5bbfa34682",
"blockId": "f1fa3814bbe963c196cfd8313edda8f018c44300c12faa07e5eb7047215bb951",
"value": 2000000,
"index": 5,
"globalIndex": 36175806,
"creationHeight": 1179927,
"settlementHeight": 1179930,
"ergoTree": "0008cd0301465e5d092dd2f201667b1b88151facb2498364c333a2ba6109747304b4b98b",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(1465e5,12b208,...)))}",
"address": "9gUNFq1gAu2sb6KdF7jeQ1WKmTBx9J7WXA9ULsxve1BXmwmPmhL",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
}
],
"size": 5469,
"isUnconfirmed": false
}