Transaction
ID: 4710198fb1...4fcd
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0036 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
2.11 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:
2 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.1 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0016 ERG
Unspent
Transaction Details
Confirmations: 552,799
Total coins transferred: 2.11 ERG
Fees: 0.0016 ERG
Fees per byte: 0.000000276 ERG
Raw Transaction Data
{
"id": "4710198fb1cbf200321e19df5fdf7dc05e4c84df15e58eb67e55e2a607654fcd",
"blockId": "12fe929682c58a21975effa73d099166af7a19ab0851eb0d9a41f714e7e0dbce",
"inclusionHeight": 1203880,
"timestamp": 1708387414744,
"index": 4,
"globalIndex": 6657860,
"numConfirmations": 552799,
"inputs": [
{
"boxId": "127de23073828fef4b82d693d61f5680857afbf07322e3acd499cb1ccd71306d",
"value": 3600000,
"index": 0,
"spendingProof": null,
"outputBlockId": "12fe929682c58a21975effa73d099166af7a19ab0851eb0d9a41f714e7e0dbce",
"outputTransactionId": "39f3bd9025ee0730e34b917fa80c5b3106a127c72e0f06cc1841a62b65e5c884",
"outputIndex": 1,
"outputGlobalIndex": 37036758,
"outputCreatedAt": 1203877,
"outputSettledAt": 1203880,
"ergoTree": 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"ergoTreeConstants": "0: 0\n1: 3\n2: 2\n3: Coll(9,-2,10,104,21,28,35,-117,-18,78,-52,-32,101,-17,41,-54,28,-119,111,-35,100,40,76,10,81,-24,12,-32,-59,-77,11,51)\n4: Coll(15,-124,122,-45,62,48,-13,-57,-29,-128,17,-3,106,-98,122,-74,-18,12,8,-123,3,52,105,-3,99,-49,-106,19,66,-71,21,127)\n5: 0\n6: 1\n7: SigmaProp(ProveDlog(ECPoint(f8b3c8,3fe7b0,...)))\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(-12,-127,105,59,-45,56,-11,-51,-63,33,-99,103,-71,-98,-36,-11,18,-20,-14,53,103,-40,-55,-6,-30,14,118,34,55,56,-123,-92)\n44: 0\n45: 0\n46: 0\n47: 0\n48: 1\n49: 1\n50: 106200000\n51: 1000000\n52: 0\n53: 1\n54: 106200000\n55: 2\n56: 1\n57: 5\n58: 4\n59: 1600000\n60: 2\n61: 1\n62: 6\n63: 5\n64: 1000000\n65: -1\n66: 106200000\n67: 1000000\n68: 0\n69: -1\n70: 106200000\n71: 2\n72: 1\n73: 5\n74: 4\n75: 1600000\n76: 2\n77: 1\n78: 6\n79: 5\n80: 1000000\n81: 2105200000\n82: 2000000000\n83: 2105200000\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: 106200000\n97: 1000000\n98: 0\n99: 1\n100: 106200000\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: 106200000\n114: 0\n115: 1\n116: 1\n117: -1\n118: 106200000\n119: 2\n120: 1\n121: 5\n122: 4\n123: 1600000\n124: 2\n125: 1\n126: 6\n127: 5\n128: 1000000\n129: 2105200000\n130: 2000000000\n131: 0\n132: 1\n133: 2105200000\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: 100000000\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": "0f847ad33e30f3c7e38011fd6a9e7ab6ee0c0885033469fd63cf961342b9157f",
"index": 0,
"amount": 1,
"name": "State Box Singleton",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "09fe0a68151c238bee4ecce065ef29ca1c896fdd64284c0a51e80ce0c5b30b33",
"index": 1,
"amount": 4932,
"name": "Rosen Trolls",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "647c6954f3cb0fae3a6655f19bb591446b78dc552c269e7570df00ecf398e23ebd0e072000",
"sigmaType": null,
"renderedValue": null
},
"R6": {
"serializedValue": "058801",
"sigmaType": "SLong",
"renderedValue": "68"
},
"R8": {
"serializedValue": "0d0740",
"sigmaType": "Coll[SBoolean]",
"renderedValue": "[false,false,false,false,false,false,true]"
},
"R7": {
"serializedValue": "5980f6c7b9b86301",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1708383600000,-1]"
},
"R9": {
"serializedValue": "1a03000000",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[,,]"
},
"R4": {
"serializedValue": "6475654f80abbfc364e320a8052fd5633301e52310e3900bbdc944a62dacef214e0e072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "b1cd152b551c700bcfb3656c48b9728c6a185bd7612a983999c4a6f11a8ee0e2",
"value": 2106200000,
"index": 1,
"spendingProof": null,
"outputBlockId": "67043751aa23cc4ca94797ecdd4578bb7290e3dec362787c21e1ea846b3ab5bd",
"outputTransactionId": "3daff9d0fe09c6ff64cb3e7ff2598c8dbb2c8d9feaa94563be480277dba234d0",
"outputIndex": 0,
"outputGlobalIndex": 37036600,
"outputCreatedAt": 1203875,
"outputSettledAt": 1203877,
"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": {
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"sigmaType": "SSigmaProp",
"renderedValue": "03b562aacf882a9c08386e8628fe8f3175e587d4fbd2007402d15d9850c60047a8"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0f847ad33e30f3c7e38011fd6a9e7ab6ee0c0885033469fd63cf961342b9157f"
}
}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "39353290484924ef29470ae59c1944c5f4dde26fa1c93cc63314176fb3cab34b",
"transactionId": "4710198fb1cbf200321e19df5fdf7dc05e4c84df15e58eb67e55e2a607654fcd",
"blockId": "12fe929682c58a21975effa73d099166af7a19ab0851eb0d9a41f714e7e0dbce",
"value": 2600000,
"index": 0,
"globalIndex": 37036763,
"creationHeight": 1203877,
"settlementHeight": 1203880,
"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": "09fe0a68151c238bee4ecce065ef29ca1c896fdd64284c0a51e80ce0c5b30b33",
"index": 0,
"amount": 1,
"name": "Rosen Trolls",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0c4c0e01240008cd030f8b3c804e11a1e3e7454401dbbcaf60976e888f4656ff236d47ec30ccfe53c6c801",
"sigmaType": "Coll[(Coll[SByte], SInt)]",
"renderedValue": "[[0008cd030f8b3c804e11a1e3e7454401dbbcaf60976e888f4656ff236d47ec30ccfe53c6,100]]"
},
"R6": {
"serializedValue": "3c0c3c0e0e3c0c3c0e580c3c0e580b0b4261636b67726f756e64730d4261636b67726f756e645f31360a43686172616374657273134261627954726f6c6c5f315f54726f6c6c5f34055761727473104261627954726f6c6c57617274735f390445796573134261627954726f6c6c5f315f457965735f31340448616972134261627954726f6c6c5f315f486169725f3230055368697274104261627954726f6c6c53686972745f36044c6f676f1c4261627954726f6c6c5f315f526f73656e42726964676553686972741145617272696e67735f4e65636b6c6163650d4261627954726f6c6c4e6f6e65044974656d114261627954726f6c6c5f315f4261675f32054d6f757468144261627954726f6c6c5f315f4d6f7574685f33310842726163656c65740e4164756c7454726f6c6c4e6f6e650000",
"sigmaType": null,
"renderedValue": null
},
"R8": {
"serializedValue": "0c3c0e0e01086578706c696369740100",
"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[6578706c69636974,00]]"
},
"R7": {
"serializedValue": "0e2009fe0a68151c238bee4ecce065ef29ca1c896fdd64284c0a51e80ce0c5b30b33",
"sigmaType": "Coll[SByte]",
"renderedValue": "09fe0a68151c238bee4ecce065ef29ca1c896fdd64284c0a51e80ce0c5b30b33"
},
"R9": {
"serializedValue": "4405cd03b562aacf882a9c08386e8628fe8f3175e587d4fbd2007402d15d9850c60047a88801",
"sigmaType": "(SSigmaProp, SLong)",
"renderedValue": "[03b562aacf882a9c08386e8628fe8f3175e587d4fbd2007402d15d9850c60047a8,68]"
},
"R4": {
"serializedValue": "0404",
"sigmaType": "SInt",
"renderedValue": "2"
}
},
"spentTransactionId": "7008e43f402cf168f0faf69b7ce3bc9f6c50b99c1f3b72111ba36236a1845cfc",
"mainChain": true
},
{
"boxId": "c9403b3fb44ff8454f3e255e56bc62ae100b1e429f8facb7487799559ea5935c",
"transactionId": "4710198fb1cbf200321e19df5fdf7dc05e4c84df15e58eb67e55e2a607654fcd",
"blockId": "12fe929682c58a21975effa73d099166af7a19ab0851eb0d9a41f714e7e0dbce",
"value": 3600000,
"index": 1,
"globalIndex": 37036764,
"creationHeight": 1203877,
"settlementHeight": 1203880,
"ergoTree": 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"ergoTreeConstants": "0: 0\n1: 3\n2: 2\n3: Coll(9,-2,10,104,21,28,35,-117,-18,78,-52,-32,101,-17,41,-54,28,-119,111,-35,100,40,76,10,81,-24,12,-32,-59,-77,11,51)\n4: Coll(15,-124,122,-45,62,48,-13,-57,-29,-128,17,-3,106,-98,122,-74,-18,12,8,-123,3,52,105,-3,99,-49,-106,19,66,-71,21,127)\n5: 0\n6: 1\n7: SigmaProp(ProveDlog(ECPoint(f8b3c8,3fe7b0,...)))\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(-12,-127,105,59,-45,56,-11,-51,-63,33,-99,103,-71,-98,-36,-11,18,-20,-14,53,103,-40,-55,-6,-30,14,118,34,55,56,-123,-92)\n44: 0\n45: 0\n46: 0\n47: 0\n48: 1\n49: 1\n50: 106200000\n51: 1000000\n52: 0\n53: 1\n54: 106200000\n55: 2\n56: 1\n57: 5\n58: 4\n59: 1600000\n60: 2\n61: 1\n62: 6\n63: 5\n64: 1000000\n65: -1\n66: 106200000\n67: 1000000\n68: 0\n69: -1\n70: 106200000\n71: 2\n72: 1\n73: 5\n74: 4\n75: 1600000\n76: 2\n77: 1\n78: 6\n79: 5\n80: 1000000\n81: 2105200000\n82: 2000000000\n83: 2105200000\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: 106200000\n97: 1000000\n98: 0\n99: 1\n100: 106200000\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: 106200000\n114: 0\n115: 1\n116: 1\n117: -1\n118: 106200000\n119: 2\n120: 1\n121: 5\n122: 4\n123: 1600000\n124: 2\n125: 1\n126: 6\n127: 5\n128: 1000000\n129: 2105200000\n130: 2000000000\n131: 0\n132: 1\n133: 2105200000\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: 100000000\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": "NXQNuo7KeCS5KGaHS3ypfz4QyVrwtqGA87hmaF9r1C5V6suAq8EqynDZWgwRpRWkjciPup8qx9XLMAKGzPJorwoLH3JtMKWS4QXJ57cCBm5wZBLRvk1est9WVZAKXEwiy7Yx6J1mkXGtAUFMpyFTS4iKfWUnt79ENjaVE3ebd5KQDbfnFTgi2TcP3qwqoTMiZFD3eergh23y7MJ4PSQyWUUNRNUBqZFVZsEtJsiSUpNKpGZ9Qkucc8HVRoWvrJBJmxUjEuQiS6vZpAoDCAyBita8rPS3NY8R5k3o6mtLqYxRFDjMNGs94YBPmxqow4YGcjrPFmbapcV5Qh9poCdcZwqinfUHBjMdxALyyC1TWwW8gwjwArAikpZVHiuaTotidRqrDWrak5gvEe8ztQeLMviYRb4m2uFoUJdnXZec5rp8cZjL8h9bnuwhXw3LLNnrjfVkVmhMUy5ZiHzMK8PwPoATM1RYS5XKsq7FnZJvQmghAwx487QktnRfBZRXDU2qnMgDUKuDYh5oAuLxQniHzWCrzMf9KcnFUXa2yiv6mLPRnWRSAQgFwkeQTt6iSham21uHwiheRAi3aB6ufRZvz8r8Umkc8WxFhS6TFPqGMYSCKqKh5mCLb3yJVQxf8yF8xSYFRxazEYoxaaLjpG2vzYZkL9vBFfv9TYGUGxcKm8R8XTWD7SwuYR3asPKtx6Fb5r3J54WkN2JyAdnDkb7ErssjjC3VqWYxTvgmP3tKbj265579ZpSyEV74GPDTQ4CJM4pViLtHEx4XqogLysntt5E1QzHL9VA8U2tRspRoVBu7FwUzJCMQrFVqVS96ikJ4e73u4cJwwuYkkvLqxRrqMooDa2WhA4o8gYEXHvW2H1xRQq9Be2PrQkZACu9fHCHJZpo9wMMM4EShVadC84TgTPKuztW5kcYbLt6BkhqoePXDGqSFyJxC2j4ZwDzRa8SJUnBzkRs6UMtgHGF9wwx51DtmCkZg26CSYmHyddR3h8XUAXHvvMRP6Kksfz1troEmuFcqoxWx3GhuB9gQtnJpg8BitxHqBFGFAoCvyMuCieVLmy1ohQnrQCGA29Hn8dNATwo4QL6HH6HVnBb74wSqZHfwPx9WLW6QqJ3GCCFArUjCM7dQBkYzSjMPWWoD2p625H1AtqCUUmp7gWtraWKt27Fy3ic9hY6JkUxizkXtpvE3KRBx1rHybmPxujL23nefQu9FkRW8pPksu3mNr2AS4vKN2VBdtJtM2U6sYkVvZimfH8NenLEWxiFEjpSamWpRWjb3HLj4KCu8VPNwDiwtZBWDmxoqqoqevkLFoqhoetSaaFjHg8ZyvEQ4yB7Ht6XJDQwLFJDW94n2qSRVvrhpKpnHjSieERpksUttuuhs4NdFNmAJ6hZW5cHRZYfGmsiN2NtZ5LoM21Z4ficZWE8u6un8vBTKzhbkRfdGVjmeU2ADAaNJVhqeH6Jxwb59T9baaGVYApHUNaizt9SwEjoLCBA6X17Nu2pzZSmane4UAr9Cf2hrswQmpdV5ed75gexEEc2x1QNKncftjt69SfGJZxukxErjUUcArXe3jRPKDRxD8UCvfPHaEuZLSKc27wiFxzoYRBQuSu3CFYZ7GSwD7MsHogEdw6XryUHFJZyQtbbAcRZj5vLSzLiXFpbtjxE8wbustwFWhH362h7nNsnqzuagRYSwck1ZDwLL4PuRwaz1gqvykc4wGvHXZCpPaiTjrY1yMfTwUxz21jQEqfLZcr98ifedcQfd2iFHAAVveFXwBLHgZZb7pJR3zVMNeJySBDs2TrBvKefwfUT7gWkruFJJHaCXQhRQY5ZWQbgiUXSopgV7VKjkmMGkpTKEQ3GYn82LBmgWsrNSMvw998PaqrcrADkp25EQcxraXpCMW9aGTvCx6p13XPeGcDYmHvLoEWFZ78SuguETrjHcGCcqV7DfbbZHh9uP6q1fusxtyvpaWrfxCtQBBBALyphpguZhVy4qihifwPgDBQhnNkq7aNiziycJarPgHMtm6gVAqpCg1gDJaR2jXHst2WtfFcvgC1tfv7sF4wFSkS5xHf13hkguCPSN13kTrMEbmcCgSqSoYHcDWzUmRhcvGDy9jW7zEUHy3Q87nRdzzxeDCh9bQG15xxTTVhoynqhjzK4GKyhv6QQvHcf3XYyTiQgnzAtUXtQ8m5Wusbm7sfeGSkY3xKAaPcmAVxLfPgnrmhfqJtdb3cdeayTchv39s3gYTyCLxbGQ2bb8LWvLacZcqahbbFd7UdE9iYA4cVx9cu1NLHdCZYcvFpo9AX4pSHRz26VDCkqvM7NLSrs4jfS78gGf865urN4bASxS5vCD5ereP5Q1HS1oee5WAQDKrKqeiogAN3Y3tnhqZNsuQkV8Bxck3aiQDcrRCk712WiTzQbuBNbnq3AboFq8baAcJqjCjoX6bVTeFHrr2mk3usSC5UREk5T1sWooLUjuEvBZDyLSqXjHgZL5YvnyhQMSGF4A6ZYaodLCCZFcEGDvUMK3Z9FjPuc5aZfu9fjqkjEiiQbnm1zzezUn15pU2kX6bo57Dd82LLxEeQpJF7W1BR4QQqcNFJEzfBc3uzByNTWBGf78oi6yEyiFJPC6Tzyx2eLv1h6RJsCXauiFSn9AFZieXWe3zxizgMVYpRPEx6durW9cnqLmcnJSy4VFKYRgFuddiR1va1TfjHLJRcgcigUGLzJG4B1WNCeYT5NupRjKxwYEEevF9N4bACfXU1Bj3aUomRJhgZNA9Jo5xVXCcAasmeaavyvd1trX6wqp7Luv6HzpMvo3vCLmtb23rMgiid6iqpYixAD9tXDKNLco2Sfy1qn4Lei28gL9ZJnJ6AWb2r2vBqbbBhAnmXxzviWzNHgrrmdVpHgtMxHTj1BkemmmQF2XZCcGZLvfgxqgiXyWfWhiLE43rjKAaE2cXzwfPFDfwxnF1yyXuR2zD9cLAvJ4dNuMZZaoQsMrsPERNkGepHzjDt3WfBQUwNj8gPDyGDNAj36GkERb4u7Ct1kNMvf7sGoA3sR4pJzYinKBaSP7eiR3HAkkArSxxafxDTsesbQDVR7in4ATZjUPEvd4LLP8xFX3tBgC6Z8MvnuZZXg4XjZNNTSPC3m3UFZNBVSgqBjpptAHyvziK6SK2BFUCfpgLp9rYGv8b8ittSQLNF9gfKQ7sXo8JLu6gZCPguPqQWfHWHKuoAp9FLMUbyLXRsnGjYzTHKAmyCtPYzYtKC15nQekYPBMyMkbZHJPNMg5Cz2bTCsf1SuRCNSY1DkgvGPRpEbFmAEtu6kHiSvuQ8bn3L56t9zny4ocWRAJ1kvMChxDuqMwA747fjppYYKyW4K4gnHCMS4bKwQVriPHzXQgn2rsHEh5Jh82eCJ2inqQJHWSnVK851RSK7DQVHui26T23p2RvZ2ok1EvkN55brqNPnPKpXm4kxNUMKnQJSEVaFGYKrT7uhnqUQbGKm6pocC6gbNjksxzmUxezvRhuXGdLNUZuob557RMF1YW3PL3Fnyma5C2jxGypbpQP6XpTKbW2fnpKwfboRCiVHXnGRfDwcZMZ7edwaA4wcLjUjvKWvhRVE4Ep38K2zJE3ywsR83NqrqLJpsrizUqkX4Y2tvZFFnbbRKfYTUX8zQtVSxvVRoZvKgnJBLvvXSMncCjNNgmvYF92Dp9Yo71fYhkrBbAUNQgoy2k1dnE8PqzWu67tBNz7tQB781WN7YBc58MeWLuWHqwKDuL5DHd5Hx88ksNvcbst9aT9aAUnxvuXuh9n2dbuWkhMKeWrygjXo7XYPuwaE8aBRJDroNMADJ5CHkWZzEwx5ra4Bofn8pmd1Cscz7aPwifHFoqDFnWoUVG6GEzJEKBggbwjXKzTXcdpkmbFvAdLZXZdhUPBsBRkJwaa3hCydXzdhS3B3DN1estY1hCdZjwXXKTk3KNvNToCbnQAPVdPKPk6K6zscaR8y4cUc71b6nD4i69mLhyAihJdx4LGwqtVBNEbTd2ActoJF6VxFJ3ZwDPdsgHpVrv1MpcKkUUBKrxNpwfHinnUJDKG6D8ShJoir3NfyHw8XwpcCGwKcqrBwaUtjStWeUGMUyLAMtbFVUVcMMLEPEDQU7FaoeepGy5VL8TEU3XrtecvEXURf79AsFtUzD9tTHX7ph8jSS6uvU2g7PmvCvrw2gBqJez1FWfco7qS9GzSXYRiJophKVidtakK9WyXLTFWETjDa6wPmnE6t4rc5p5BXR8nAkCWubAhFSwQLLc22oyQdCPRCbtUkcDBNdrQCMoivuCFGUECU9bjVqmA44T8kLbted5ZgMk6nzonZra",
"assets": [
{
"tokenId": "0f847ad33e30f3c7e38011fd6a9e7ab6ee0c0885033469fd63cf961342b9157f",
"index": 0,
"amount": 1,
"name": "State Box Singleton",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "09fe0a68151c238bee4ecce065ef29ca1c896fdd64284c0a51e80ce0c5b30b33",
"index": 1,
"amount": 4931,
"name": "Rosen Trolls",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": null,
"renderedValue": null
},
"R6": {
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"sigmaType": "SLong",
"renderedValue": "69"
},
"R8": {
"serializedValue": "0d0740",
"sigmaType": "Coll[SBoolean]",
"renderedValue": "[false,false,false,false,false,false,true]"
},
"R7": {
"serializedValue": "5980f6c7b9b86301",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1708383600000,-1]"
},
"R9": {
"serializedValue": "1a03000000",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[,,]"
},
"R4": {
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"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "c50fd1a3610923b22ab44cbf952df881bf5048380f70b77b0aaee1c9fc9cc86f",
"mainChain": true
},
{
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"transactionId": "4710198fb1cbf200321e19df5fdf7dc05e4c84df15e58eb67e55e2a607654fcd",
"blockId": "12fe929682c58a21975effa73d099166af7a19ab0851eb0d9a41f714e7e0dbce",
"value": 2000000000,
"index": 2,
"globalIndex": 37036765,
"creationHeight": 1203877,
"settlementHeight": 1203880,
"ergoTree": "0008cd030f8b3c804e11a1e3e7454401dbbcaf60976e888f4656ff236d47ec30ccfe53c6",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(f8b3c8,3fe7b0,...)))}",
"address": "9gaejqEmXu5PHQETxGpBWnpe8LqMWmTyTcLagcpSGZaNkBBjosD",
"assets": [],
"additionalRegisters": {},
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"mainChain": true
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{
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}