Transaction
ID: 64ba33b881...d4e0
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
437.99 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
554,447.25
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Unspent
Address:
Settlement height:
Value:
437.98 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 276,112
Total coins transferred: 437.99 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000231 ERG
Raw Transaction Data
{
"id": "64ba33b8814c4023bdf737fe6d3b105547556dc1306dcda37ad0300939d5d4e0",
"blockId": "77cfd3b833e7aeaf01b2d74034e24e94b92cd1f40df305a14739b7302534a618",
"inclusionHeight": 1500828,
"timestamp": 1744329103753,
"index": 8,
"globalIndex": 8822695,
"numConfirmations": 276112,
"inputs": [
{
"boxId": "19378cf323be0cd768be3e374ed25f626a62af6c3d8acf09126cebf515e2ab1b",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "8e78a9af4b77878908b79278999b2f1da6faf5e7540fb6ad3167199bc4e61647",
"outputTransactionId": "d7f7b0b1a99006bc75b2be0e7df563f7874efc3161991de4470bb3554d675a64",
"outputIndex": 2,
"outputGlobalIndex": 47201146,
"outputCreatedAt": 1497233,
"outputSettledAt": 1497236,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(74,-5,-92,1,76,41,-114,-110,-94,20,-54,-22,34,-93,-39,-67,87,36,4,73,-64,63,90,19,98,103,-103,-116,-8,-27,-67,-119)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.tokens(0) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val preHeader3 = CONTEXT.preHeader\n val coll4 = placeholder[Coll[Byte]](1)\n val func5 = {(tuple5: (Coll[Box], Coll[Byte])) =>\n tuple5._1.filter({(box7: Box) => box7.tokens.exists({(tuple9: (Coll[Byte], Long)) => tuple9._1 == tuple5._2 }) })\n }\n val func6 = {(box6: Box) => box6.R4[Coll[Long]].get(0) }\n val func7 = {(box7: Box) => box7.R4[Coll[Long]].get(1) }\n val func8 = {(box8: Box) => box8.R4[Coll[Long]].get(3) }\n val func9 = {(box9: Box) => box9.R4[Coll[Long]].get(2) }\n val func10 = {(box10: Box) => box10.R5[Coll[Box]].get }\n val func11 = {(box11: Box) => box11.R4[Coll[Long]].get(4) }\n val func12 = {(l12: Long) =>\n if (l12 < 128L) { 1 } else {\n if (l12 < 16384L) { 2 } else {\n if (l12 < 2097152L) { 3 } else {\n if (l12 < 268435456L) { 4 } else {\n if (l12 < 34359738368L) { 5 } else {\n if (l12 < 4398046511104L) { 6 } else { if (l12 < 562949953421312L) { 7 } else { if (l12 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n val func13 = {(box13: Box) =>\n val coll15 = box13.bytesWithoutRef\n val i16 = func12(box13.value) + box13.propositionBytes.size\n coll15.slice(0, i16).append(coll15.slice(i16 + func12(box13.creationInfo._1.toLong), coll15.size))\n }\n val func14 = {(coll14: Coll[Box]) =>\n coll14.flatMap({(box16: Box) => box16.tokens }).fold(0L, {(tuple16: (Long, (Coll[Byte], Long))) => tuple16._1 + tuple16._2._2 })\n }\n if (getVar[Byte](0.toByte).get == 12.toByte) {\n sigmaProp(\n {(coll15: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll15.forall({(coll17: Coll[Byte]) => !func2((OUTPUTS, coll17)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n )\n } else {(\n val coll15 = CONTEXT.dataInputs\n val box16 = func5((coll15, coll4))(0)\n val l17 = func9(SELF)\n val bool18 = l17 > 0L\n val coll19 = func10(SELF)\n val i20 = coll19.size\n val i21 = OUTPUTS.size\n val box22 = OUTPUTS(i21 - 1)\n val bool23 = blake2b256(box22.propositionBytes) == {(opt23: Option[Coll[Byte]]) => opt23.get.slice(1, 33) }(\n {(box23: Box) => box23.R4[AvlTree].get }(func5((coll15, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n -57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte\n )\n ), getVar[Coll[Byte]](1.toByte).get\n )(0)\n )\n val box24 = if (bool23) { OUTPUTS(i21 - 2) } else { box22 }\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n {(box25: Box) => box25.tokens(0) }(box16)._1 == coll4, {(box25: Box) => box25.R4[Coll[Int]].get(0) }(box16).toLong == func6(SELF), {(\n box25: Box\n ) => box25.R4[Coll[Int]].get(1) }(box16).toLong == func7(SELF)\n )\n ), preHeader3.timestamp >= func8(SELF), if (bool18) {(\n val coll25 = func10(SELF)\n val box26 = OUTPUTS(coll25.size)\n val l27 = func11(SELF)\n allOf(\n Coll[Boolean](\n box26.value == SELF.value, box26.tokens == SELF.tokens, func6(box26) == func6(SELF), func7(box26) == func7(SELF), func9(\n box26\n ) == l17 - 1L, func8(box26) == func8(SELF) + l27, func11(box26) == l27, func10(box26) == coll25, box26.propositionBytes == SELF.propositionBytes\n )\n )\n )} else { !func2((OUTPUTS, func1(SELF)._1)) }, coll19.zip(OUTPUTS.slice(0, i20)).forall(\n {(tuple25: (Box, Box)) => func13(tuple25._1) == func13(tuple25._2) }\n ), i21 == i20 + if (bool18) { 1 } else { 0 } + if (bool23) { 2 } else { 1 }, func14(INPUTS) == func14(OUTPUTS) + if (bool18) { 0L } else {\n 1L\n }, allOf(Coll[Boolean](box24.value <= 5000000L, box24.tokens.size == 0))\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "97f262a9dde3bb81a680e9716e79c0b4e6e4e88b13f785acc917604fc02425b8",
"index": 0,
"amount": 1,
"name": "Walrus DAO Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "110504020080c5a7a1c46500",
"sigmaType": "Coll[SLong]",
"renderedValue": "[2,1,0,1744328520000,0]"
},
"R5": {
"serializedValue": "0c6301c0b19f050008cd036a496ea24cd4ad8465166161832ff49a98a9033956f0ccee63aade73b53c97d991b15b01007fd64d1ee54d78dd269c8930a38286caa28d3f29d27cadcb796418ab15c28385dfe7d31400b7c7c1afd59cde2aea4ad7682a65f4c9231ec54c0661dc2f6e6cb502fca876e600",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "c948f35bc9dfd748a7749c611a9fb3e68c1572d4938eae293dbf3c6fb6d20b8a",
"value": 437986000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "d778eb18e11e6683536c76a83203115a93069eac4e0b1bfce20166e6fabe309c",
"outputTransactionId": "d03b56fc413180c2463f10738de19dba32fa475d5164945ab84f24213c8dbdf9",
"outputIndex": 2,
"outputGlobalIndex": 46406824,
"outputCreatedAt": 1466083,
"outputSettledAt": 1466085,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-105,-14,98,-87,-35,-29,-69,-127,-90,-128,-23,113,110,121,-64,-76,-26,-28,-24,-117,19,-9,-123,-84,-55,23,96,79,-64,36,37,-72,-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte), Coll[Byte](79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "fdab6f04f783de26d8ce2ab99b7b9aa4deeeb5cd56ffd01e7ef1374d6037b642",
"value": 1000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "42ea511690548159db2f959f326aa7bd4c1579810e82b1be0633214bfef2fc59",
"outputTransactionId": "39446de0b6e98a99e5376a5d425af822ae0d20cdc98bcf071be0ab97694185b5",
"outputIndex": 0,
"outputGlobalIndex": 47103465,
"outputCreatedAt": 1492294,
"outputSettledAt": 1492297,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-105,-14,98,-87,-35,-29,-69,-127,-90,-128,-23,113,110,121,-64,-76,-26,-28,-24,-117,19,-9,-123,-84,-55,23,96,79,-64,36,37,-72,-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte), Coll[Byte](79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "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",
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{
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"index": 0,
"amount": 5544472453,
"name": "EXLE",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "01dce8a5632d19799950ff90bca3b5d0ca3ebfa8aaafd06f0cc6dd1e97150e7f",
"index": 1,
"amount": 84604500,
"name": "CYPX",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "3693ee6a800bfa5310a7aee5b63870989537a4681ebddce8a211062d79a61148",
"value": 1000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "1784590e1010954587aad0cb9b0ae1d9fd8d223f62b6496e054e76886d3aea5d",
"outputTransactionId": "25c4bc8e72ac4b1a482e82cb273b43cf65112c6bbc99ecc5b34923463fc9616f",
"outputIndex": 0,
"outputGlobalIndex": 46553902,
"outputCreatedAt": 1471316,
"outputSettledAt": 1471319,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-105,-14,98,-87,-35,-29,-69,-127,-90,-128,-23,113,110,121,-64,-76,-26,-28,-24,-117,19,-9,-123,-84,-55,23,96,79,-64,36,37,-72,-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte), Coll[Byte](79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "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",
"assets": [
{
"tokenId": "42553c5d6dc3da173a0ea48dd183879d18221c9e97330638ee0fb3f2eaddbeb0",
"index": 0,
"amount": 1,
"name": "Cybercitizen #600",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "01dce8a5632d19799950ff90bca3b5d0ca3ebfa8aaafd06f0cc6dd1e97150e7f",
"index": 1,
"amount": 100000000,
"name": "CYPX",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "5ba2214a70f0109781353eb6d8729e7d479882a0c3d89f2ebb34a285d88621db",
"value": 1000000000,
"index": 0,
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"outputTransactionId": "8da1f966022432fd7fc772f5936e1f332d6af56bc0d56f699d90a634c5c5840c",
"outputIndex": 0,
"ergoTree": "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",
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"R4": {
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"sigmaType": null,
"renderedValue": null
}
}
},
{
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"value": 2000000,
"index": 1,
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"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "10020402",
"sigmaType": "Coll[SInt]",
"renderedValue": "[2,1]"
},
"R5": {
"serializedValue": "1104de92f29ec465c0a90700c0a907",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1744325985455,60000,0,60000]"
},
"R6": {
"serializedValue": "64653194f482af58777cfd0b2878a285f5ddfaca749048263f4334072417c8602501072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e0f446973747269627574652045584c45",
"sigmaType": "Coll[SByte]",
"renderedValue": "446973747269627574652045584c45"
}
}
}
],
"outputs": [
{
"boxId": "d8ad9cfbad0436186304a6a594b9cd8a3662cbb3801a6b3ad3a34c32b741d6aa",
"transactionId": "64ba33b8814c4023bdf737fe6d3b105547556dc1306dcda37ad0300939d5d4e0",
"blockId": "77cfd3b833e7aeaf01b2d74034e24e94b92cd1f40df305a14739b7302534a618",
"value": 11000000,
"index": 0,
"globalIndex": 47292099,
"creationHeight": 1500825,
"settlementHeight": 1500828,
"ergoTree": "0008cd036a496ea24cd4ad8465166161832ff49a98a9033956f0ccee63aade73b53c97d9",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6a496e,ce0996,...)))}",
"address": "9hGceS9rTZDDmsnioJGWykfUAzk8ZbCuuadNLvoeG7hN9bM3kNP",
"assets": [
{
"tokenId": "007fd64d1ee54d78dd269c8930a38286caa28d3f29d27cadcb796418ab15c283",
"index": 0,
"amount": 5544472453,
"name": "EXLE",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1967a00adade20d6b19ed3dcef5bf94a6714573cbc84b5418f4e85edb6e5b95b",
"mainChain": true
},
{
"boxId": "6ae5ef5b5f01a42a8f9d87ee9d6cbcb1d9135eb0e46362dc649d67432b1c3f47",
"transactionId": "64ba33b8814c4023bdf737fe6d3b105547556dc1306dcda37ad0300939d5d4e0",
"blockId": "77cfd3b833e7aeaf01b2d74034e24e94b92cd1f40df305a14739b7302534a618",
"value": 1000000,
"index": 1,
"globalIndex": 47292100,
"creationHeight": 1500825,
"settlementHeight": 1500828,
"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": "2ea1863ea2fb5ca7c7ade201dae1bd89e4988629c518c176378168c7eff406e0",
"mainChain": true
},
{
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"transactionId": "64ba33b8814c4023bdf737fe6d3b105547556dc1306dcda37ad0300939d5d4e0",
"blockId": "77cfd3b833e7aeaf01b2d74034e24e94b92cd1f40df305a14739b7302534a618",
"value": 437978000000,
"index": 2,
"globalIndex": 47292101,
"creationHeight": 1500825,
"settlementHeight": 1500828,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(-104,-70,111,12,-4,119,88,99,61,82,-22,48,-126,-82,59,-117,56,-76,93,-65,-24,-89,36,125,-23,102,-36,-74,8,-71,0,-114)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-105,-14,98,-87,-35,-29,-69,-127,-90,-128,-23,113,110,121,-64,-76,-26,-28,-24,-117,19,-9,-123,-84,-55,23,96,79,-64,36,37,-72,-89,-10,-44,-52,-15,40,-118,43,121,-29,-40,116,30,30,32,56,40,19,90,18,-71,47,-115,-60,-14,-46,30,64,115,-114,14,1)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte), Coll[Byte](79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "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",
"assets": [
{
"tokenId": "42553c5d6dc3da173a0ea48dd183879d18221c9e97330638ee0fb3f2eaddbeb0",
"index": 0,
"amount": 1,
"name": "Cybercitizen #600",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "01dce8a5632d19799950ff90bca3b5d0ca3ebfa8aaafd06f0cc6dd1e97150e7f",
"index": 1,
"amount": 184604500,
"name": "CYPX",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
}
],
"size": 4333,
"isUnconfirmed": false
}