Transaction
ID: 362ca231b8...2508
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
14.85 ERG
Tokens:
Loading assets...
Outputs (7)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00185 ERG
Unspent
Transaction Details
Confirmations: 53,114
Total coins transferred: 15.86 ERG
Fees: 0.00185 ERG
Fees per byte: 0.000000163 ERG
Raw Transaction Data
{
"id": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"inclusionHeight": 1714408,
"timestamp": 1770181376727,
"index": 19,
"globalIndex": 10250078,
"numConfirmations": 53114,
"inputs": [
{
"boxId": "3c267f943e62710c83949bf346e2af08eacecddd782baacd1d58bcf48cdd55f9",
"value": 1000000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "bf366e9c1475787ca2def8dec482ffeb5af4e209d1db875c8b5d0a21037bf134",
"outputTransactionId": "725924df57c161f94b5ae84082b210174a432ba2eeeaf2324d18abddf547fc89",
"outputIndex": 0,
"outputGlobalIndex": 53373263,
"outputCreatedAt": 1714187,
"outputSettledAt": 1714189,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(82,21,-96,77,68,76,-71,114,55,-24,-7,-126,-96,27,31,19,117,-107,-57,125,115,123,-52,119,-124,-94,-54,68,-127,21,25,-74)",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](\n -34.toByte, -82.toByte, -49.toByte, 91.toByte, 100.toByte, -70.toByte, -42.toByte, -11.toByte, 87.toByte, 11.toByte, -83.toByte, 10.toByte, 97.toByte, 12.toByte, 78.toByte, 72.toByte, 73.toByte, 87.toByte, -49.toByte, 71.toByte, -126.toByte, 48.toByte, -124.toByte, 0.toByte, -68.toByte, -112.toByte, 64.toByte, 76.toByte, 29.toByte, 20.toByte, 16.toByte, -38.toByte\n )\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val func3 = {(tuple3: (Coll[Box], Coll[Byte])) =>\n tuple3._1.filter({(box5: Box) => box5.tokens.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == tuple3._2 }) })\n }\n val box4 = func3((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)\n val opt5 = getVar[Coll[Byte]](1.toByte)\n val func6 = {(opt6: Option[Coll[Byte]]) => opt6.get.slice(1, 33) }\n val func7 = {(box7: Box) => box7.tokens(0) }\n val tuple8 = func7(SELF)\n val box9 = func3((OUTPUTS, tuple8._1))(0)\n val func10 = {(box10: Box) => box10.tokens(1) }\n val func11 = {(coll11: Coll[Byte]) =>\n val coll13 = func2(box4).getMany(Coll[Coll[Byte]](coll1, coll11), opt5.get)\n allOf(\n Coll[Boolean](\n {(tuple14: (Coll[Box], Coll[Byte])) => tuple14._1.filter({(box16: Box) => blake2b256(box16.propositionBytes) == tuple14._2 }) }(\n (INPUTS, func6(coll13(1)))\n ).size == 1, {(coll14: Coll[Byte]) =>\n allOf(Coll[Boolean](blake2b256(box9.propositionBytes) == coll14, func7(box9) == tuple8, func10(box9)._1 == func10(SELF)._1))\n }(func6(coll13(0)))\n )\n )\n }\n val b12 = getVar[Byte](0.toByte).get\n val i13 = INPUTS.indexOf(SELF, 0)\n val func14 = {(l14: Long) =>\n if (l14 < 128L) { 1 } else {\n if (l14 < 16384L) { 2 } else {\n if (l14 < 2097152L) { 3 } else {\n if (l14 < 268435456L) { 4 } else {\n if (l14 < 34359738368L) { 5 } else {\n if (l14 < 4398046511104L) { 6 } else { if (l14 < 562949953421312L) { 7 } else { if (l14 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b15: Byte) =>\n if (b15 == 0.toByte) {\n func11(\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 2.toByte) {\n func11(\n Coll[Byte](\n -117.toByte, -57.toByte, -113.toByte, 28.toByte, 106.toByte, -82.toByte, -55.toByte, 30.toByte, 98.toByte, -114.toByte, 21.toByte, -49.toByte, 102.toByte, -116.toByte, 22.toByte, -52.toByte, 30.toByte, -101.toByte, -40.toByte, -28.toByte, -71.toByte, -73.toByte, -31.toByte, 109.toByte, 99.toByte, 24.toByte, -75.toByte, -11.toByte, 35.toByte, -91.toByte, -23.toByte, -67.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 1.toByte) {\n func11(\n Coll[Byte](\n -120.toByte, 48.toByte, 97.toByte, 44.toByte, 82.toByte, 53.toByte, 95.toByte, 111.toByte, 40.toByte, 13.toByte, 18.toByte, -105.toByte, -15.toByte, -97.toByte, 103.toByte, -80.toByte, 120.toByte, -55.toByte, -38.toByte, -89.toByte, -41.toByte, -80.toByte, 75.toByte, 69.toByte, -100.toByte, -111.toByte, -52.toByte, 100.toByte, 73.toByte, 87.toByte, -62.toByte, -128.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 3.toByte) {\n func11(\n Coll[Byte](\n 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\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 4.toByte) {\n func11(\n Coll[Byte](\n -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\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 5.toByte) {\n func11(\n Coll[Byte](\n 58.toByte, 17.toByte, -107.toByte, 92.toByte, 71.toByte, 25.toByte, -27.toByte, -120.toByte, -68.toByte, -26.toByte, -89.toByte, 97.toByte, 29.toByte, 39.toByte, -67.toByte, 31.toByte, -33.toByte, -37.toByte, 87.toByte, 56.toByte, 92.toByte, -82.toByte, -30.toByte, 102.toByte, -40.toByte, 4.toByte, 12.toByte, -119.toByte, 79.toByte, 28.toByte, 46.toByte, 29.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 6.toByte) {\n func11(\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) => if (b15 == 7.toByte) { {(tuple17: (Coll[Byte], Box)) => if (i13 >= OUTPUTS.size) { false } else {(\n val box19 = OUTPUTS(i13)\n val l20 = box19.value\n val l21 = SELF.value\n val coll22 = box19.propositionBytes\n val coll23 = SELF.bytesWithoutRef\n val coll24 = SELF.propositionBytes\n val i25 = SELF.creationInfo._1\n val coll26 = box19.bytesWithoutRef\n val i27 = box19.creationInfo._1\n allOf(Coll[Boolean](l20 >= l21 - 2000000L, blake2b256(coll22) == func6(func2(tuple17._2).getMany(Coll[Coll[Byte]](tuple17._1), opt5.getOrElse(Coll[Byte]()))(0)), coll23.slice(func14(l21) + coll24.size + func14(i25.toLong), coll23.size) == coll26.slice(func14(l20) + coll22.size + func14(i27.toLong), coll26.size), anyOf(Coll[Boolean](i27 - i25 >= 504000, coll24 != coll22))))\n )} }((coll1, box4)) } else { false } }(b12)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "3b7fb49bc0a262ea890df52483fafe4b59bd376bb6788452796c13ae083b6f50",
"index": 0,
"amount": 1,
"name": "Autolykos Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e840e3bf0c4a3390d6ad9e3e9bcc14638e649feddcdd8d245f75b9738680fef6",
"index": 1,
"amount": 145480,
"name": "LYKOS",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "110788e6afbbd9668ee1111a028c9c010000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1764354292100,145479,13,1,9990,0,0]"
},
"R6": {
"serializedValue": "1d0501000100010001000100",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[0],[0],[0],[0],[0]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402d3ada5bab6c1fd20044a16e8c9de76ac9313a214d7d351e9035c4928b47b8fa6040720004b6c41ad04ddbf48391edd435a190ab4e2baf629c04663083e8236345b9a51cd01072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "7c1ac30f62427ad07c80aba8024c8ad7e250ac42c5308c856735b647e280f2ff",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "bf366e9c1475787ca2def8dec482ffeb5af4e209d1db875c8b5d0a21037bf134",
"outputTransactionId": "6fe3fa7497526a520eff048610f575feb3fc6a84f27bfa1ad0d5c3904a8c1d06",
"outputIndex": 1,
"outputGlobalIndex": 53373257,
"outputCreatedAt": 1714185,
"outputSettledAt": 1714189,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(82,21,-96,77,68,76,-71,114,55,-24,-7,-126,-96,27,31,19,117,-107,-57,125,115,123,-52,119,-124,-94,-54,68,-127,21,25,-74)\n1: Coll(59,127,-76,-101,-64,-94,98,-22,-119,13,-11,36,-125,-6,-2,75,89,-67,55,107,-74,120,-124,82,121,108,19,-82,8,59,111,80)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[Coll[Byte]]](0.toByte).get\n val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(CONTEXT.dataInputs(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n ), Coll[Byte](\n 61.toByte, -86.toByte, 102.toByte, -128.toByte, -114.toByte, 105.toByte, -62.toByte, 90.toByte, -23.toByte, 50.toByte, -35.toByte, 102.toByte, 97.toByte, 28.toByte, 95.toByte, 11.toByte, 60.toByte, -70.toByte, -54.toByte, -47.toByte, 18.toByte, 82.toByte, 3.toByte, -24.toByte, 125.toByte, -115.toByte, -60.toByte, -111.toByte, -122.toByte, 28.toByte, 113.toByte, -26.toByte\n )\n ), coll1(0)\n )\n val coll3 = coll1(9)\n val func4 = {(tuple4: (Coll[Box], Coll[Byte])) =>\n tuple4._1.filter({(box6: Box) => box6.tokens.exists({(tuple8: (Coll[Byte], Long)) => tuple8._1 == tuple4._2 }) })\n }\n val coll5 = placeholder[Coll[Byte]](1)\n val box6 = func4((OUTPUTS, coll5))(0)\n val box7 = func4((INPUTS, coll5))(0)\n val func8 = {(box8: Box) => box8.R4[Coll[AvlTree]].get(0) }\n val avlTree9 = func8(box7)\n val box10 = func4((INPUTS, {(opt10: Option[Coll[Byte]]) => opt10.get.slice(6, 38) }(coll2(1))))(0)\n val coll11 = avlTree9.get(coll3, coll1(2)).get\n val coll12 = longToByteArray(\n max({(box12: Box) => box12.R5[Coll[Long]].get(0) }(box10), {(coll12: Coll[Byte]) => byteArrayToLong(coll12.slice(0, 8)) }(coll11))\n ).append(coll11.slice(8, coll11.size))\n val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n val avlTree14 = func13(box7)\n val opt15 = avlTree14.get(coll3, coll1(4))\n val bool16 = opt15.isDefined\n val opt17 = {(box17: Box) => box17.R6[AvlTree].get }(box10).get(coll3, coll1(1))\n val bool18 = opt17.isDefined\n val l19 = if (bool16) { byteArrayToLong(opt15.get.slice(0, 8)) } else { 0L }\n val l20 = if (bool18) { l19 } else { l19 + 1L }\n val l21 = if (bool16) { byteArrayToLong(opt15.get.slice(8, 16)) } else { 0L }\n val coll22 = coll1(8)\n val l23 = coll22.indices.slice(0, coll22.size / 8).map({(i23: Int) => byteArrayToLong(coll22.slice(i23 * 8, i23 + 1 * 8)) }).fold(\n 0L, {(tuple23: (Long, Long)) => tuple23._1 + tuple23._2 }\n )\n val l24 = if (bool18) {(\n val coll24 = opt17.get\n max(\n l21 - coll24.indices.slice(0, coll24.size / 8).map({(i25: Int) => byteArrayToLong(coll24.slice(i25 * 8, i25 + 1 * 8)) }).fold(\n 0L, {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }\n ) + l23, 0L\n )\n )} else { l21 + l23 }\n val coll25 = longToByteArray(l20).append(longToByteArray(l24))\n val coll26 = coll1(5)\n val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(0) }\n val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(1) }\n val func29 = {(box29: Box) => box29.R5[Coll[Long]].get(2) }\n val func30 = {(box30: Box) => box30.R5[Coll[Long]].get(3) }\n val func31 = {(box31: Box) => box31.R5[Coll[Long]].get(4) }\n val func32 = {(box32: Box) =>\n val coll34 = box32.R5[Coll[Long]].get\n coll34.slice(5, coll34.size)\n }\n val func33 = {(box33: Box) => box33.R6[Coll[Coll[Long]]].get }\n val func34 = {(box34: Box) => box34.R7[Coll[(AvlTree, AvlTree)]].get }\n val func35 = {(box35: Box) => box35.R8[Coll[Long]].get }\n sigmaProp(\n allOf(\n Coll[Boolean](\n {(tuple36: (Coll[Box], Coll[Byte])) => tuple36._1.filter({(box38: Box) => blake2b256(box38.propositionBytes) == tuple36._2 }) }(\n (OUTPUTS, {(opt36: Option[Coll[Byte]]) => opt36.get.slice(1, 33) }(coll2(0)))\n )(0).value >= SELF.value, {(tuple36: (Coll[Box], Coll[Byte])) =>\n tuple36._1.exists({(box38: Box) => box38.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == tuple36._2 }) })\n }((OUTPUTS, coll3)), allOf(\n Coll[Boolean](\n box6.value == box7.value, box6.tokens == box7.tokens, func8(box6).digest == avlTree9.update(\n Coll[(Coll[Byte], Coll[Byte])]((coll3, coll12)), coll1(3)\n ).get.digest, func13(box6).digest == if (bool16) { avlTree14.update(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get } else {\n avlTree14.insert(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get\n }.digest, func27(box6) == func27(box7), func28(box6) == func28(box7), func29(box6) == func29(box7), func30(box6) == func30(\n box7\n ) + l20 - l19, func31(box6) == func31(box7) + l24 - l21, func32(box6) == func32(box7), func33(box6) == func33(box7), func34(box6) == func34(\n box7\n ), func35(box6) == func35(box7)\n )\n ), coll1(6) == coll12, coll1(7) == coll25\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "de08cb38b4df0983f8339df23ce01c3bfc549ade9400767588348e876b00995e",
"value": 5000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "bf366e9c1475787ca2def8dec482ffeb5af4e209d1db875c8b5d0a21037bf134",
"outputTransactionId": "6fe3fa7497526a520eff048610f575feb3fc6a84f27bfa1ad0d5c3904a8c1d06",
"outputIndex": 2,
"outputGlobalIndex": 53373258,
"outputCreatedAt": 1714185,
"outputSettledAt": 1714189,
"ergoTree": "10040e205215a04d444cb97237e8f982a01b1f137595c77d737bcc7784a2ca44811519b60e201b4b8b789fdd4a34c5f1cf73b4d99a5cacb8ccba75265f6edf4950893b162f070e201fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad4890e203b7fb49bc0a262ea890df52483fafe4b59bd376bb6788452796c13ae083b6f50d815d601d9010163b2db63087201040000d602d901023c0c630eae8c720201d9010463aedb63087204d901064d0e938c7206018c720202d603db6503fed604e4e30002d605d9010563d801d607e4c672050511b472070404b17207d606e30a4005d607860204030500d6087207d609e572067208d60a8c720901d60b8c720902d60cd9010c3c0c630eb58c720c01d9010e6393cbc2720e8c720c02d60dd9010d63b2e4c6720d0410040000d60ed9010e63b2e4c6720e0511040200d60fd9010f63e4c6720f0664d610d9011063b2e4c672100410040200d6117303d612d901123c0c630eb58c721201d9011463aedb63087214d901164d0e938c7216018c721202d613d9011363e4c672130464d614d901143c324159d805d6168c721402d6178c721601d6188c721602d6198c721801d61a8c721802e5dc24078c72140101d9011b0e9593b1721b0412d801d61d7cb4721b04020412958f721d721772179591721d72197219721d721a721ad615d9011563b2e4c672150511040000d197830301dad901160295937216020cdad901181a968303019199db690572038cc7a70104e09e60af7218d9011a0eefda7202018602a5721a93b1a404020183010e8cda720101a7010100017204dad901160295937216020dd80fd618da720501a7d619c2a7d61ab2da720c018602a5cb7219040000d61bc1721ad61cda720e01a7d61ddb6501fed61e830002d61fdc640bda721301b2da7212018602721d73000400000283020e83200202f602ff028b0272021002010255024502d402b302ac025f02c6020c02900280029202d0023502a102a10261025502c0022902e802d502110262027c027a022c83200202af0278025b020a02dd0280025c025c023102f102cc023a023e029602c80290020802fd0271022702320201020702a30278024b027f024902e9025602480242e5e3010e721ed62086020502860205ce0f05e807d6217206d6227207d6237208d6247209d625dc640bda721301b2da7212018602721d73010400000283020e83200202f50291028e02b402b00228023c0266029b02dd028a0219025602400276026c021902e4020a0269023a0266029702b7027502b0028e020902050225022302d48320020276027c02aa028002b9028e0249026a02d802a902f6028902c40241020a02e402530232027f020f029502e90250028402c002ae0220026302500279023b0277e5e3020e721ed626b2da720c018602a5dad9012632b4e472260402044201b2722504020004000096830501ededafdb0c0e7218d901270495937227720a93b27218722700720b90b27218722700720b91b17218720a92720a04009683090193c2721a721992721b99c1a705809bee0292721b058092f40193da720101721ada720101a793da720d01721ada720d01a793da720e01721a721c93da720501721a721893da720f01721ada720f01a793da721001721a95ed92721c9d9cdad9012763b2e4c67227051104020001b2da7212018602721d7211040000da7214018602b2721f040000722005d00fd801d627720b9272279d9c721cda7214018602b2721f040200722005d00f720a040391db69037203da721501a79683020192c172260580897a92dad901273c0c630eb0dc0c0f8c72270101d9012963db630872290500d90129414d0ed801d62b8c7229029a8c72290195938c722b018c7227028c722b02050001860283016372267302a18cb2db6308a7040200027cb4e4b272250400000402041293da721001a704010100017204dad9011602959372160206d80ed618e4e3011ad619b27218040800d61ab27218040600d61badb4db0c0e721a04009db1721a0410d9011b047cb4721a9c721b04109c9a721b04020410d61cb0721b0500d9011c599a8c721c018c721c02d61dc2a7d61eb2da720c018602a5cb721d040000d61fda721501a7d620da720f01a7d621dc640a7220027219b27218040000d622e67221d623b27218040200d624da720501a7d625da720501721e96830c01927cb4e4dc640adad9012663b2e4c67226040c6404000001b2da7212018602a47211040000027219b2721804040004100420721c93c2721e721d92c1721ec1a793db6308721edb6308a793da720d01721eda720d01a793da721001721eda721001a793da721501721e721f93db6401da720f01721edb6401957222e4dc640d72200283013c0e0e86027219721a7223e4dc640c72200283013c0e0e86027219721a72238fdb69037203721f957222d802d626e47221d627adb4db0c0e722604009db172260410d90127047cb472269c722704109c9a7227040204109683020193da720e01721e9a99da720e01a7b072270500d90128599a8c7228018c722802721c937225addc0c1d722401addc0c1d722701721bd9012859998c7228028c722801d90128599a8c7228018c7228029683020193da720e01721e9ada720e01a7721c937225addc0c1d722401721bd90126599a8c7226018c722602da7202018602a4721994722572240100017204",
"ergoTreeConstants": "0: Coll(82,21,-96,77,68,76,-71,114,55,-24,-7,-126,-96,27,31,19,117,-107,-57,125,115,123,-52,119,-124,-94,-54,68,-127,21,25,-74)\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(59,127,-76,-101,-64,-94,98,-22,-119,13,-11,36,-125,-6,-2,75,89,-67,55,107,-74,120,-124,82,121,108,19,-82,8,59,111,80)",
"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 b4 = getVar[Byte](0.toByte).get\n val func5 = {(box5: Box) =>\n val coll7 = box5.R5[Coll[Long]].get\n coll7.slice(2, coll7.size)\n }\n val opt6 = getVar[(Int, Long)](10.toByte)\n val tuple7 = (-2, 0L)\n val tuple8 = tuple7\n val tuple9 = opt6.getOrElse(tuple8)\n val i10 = tuple9._1\n val l11 = tuple9._2\n val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n val coll17 = placeholder[Coll[Byte]](3)\n val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n }\n val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple22 = tuple20._2\n val l23 = tuple22._1\n val tuple24 = tuple22._2\n val l25 = tuple24._1\n val l26 = tuple24._2\n tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n val l29 = byteArrayToLong(coll27.slice(1, 9))\n if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n )} else { l26 } }).getOrElse(l26)\n }\n val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b22: Byte) =>\n if (b22 == 12.toByte) {\n {(coll24: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n } else { false }\n }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n val coll24 = func5(SELF)\n val coll25 = SELF.propositionBytes\n val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n val l27 = box26.value\n val l28 = func14(SELF)\n val coll29 = CONTEXT.dataInputs\n val coll30 = Coll[Byte]()\n val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n val tuple32 = (1L, (999L, 500L))\n val opt33 = opt6\n val tuple34 = tuple7\n val tuple35 = tuple8\n val tuple36 = tuple9\n val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.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)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n val l39 = l11\n l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n val tuple43 = tuple41._2\n tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll25 = coll24(4)\n val coll26 = coll24(3)\n val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n val coll29 = SELF.propositionBytes\n val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n val l31 = func21(SELF)\n val avlTree32 = func15(SELF)\n val opt33 = avlTree32.get(coll25, coll24(0))\n val bool34 = opt33.isDefined\n val coll35 = coll24(1)\n val coll36 = func5(SELF)\n val coll37 = func5(box30)\n allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n val coll38 = opt33.get\n val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n )} else { false } }(b4)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 1,
"name": "Autolykos Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 1,
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"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10020001",
"sigmaType": "Coll[SInt]",
"renderedValue": "[0,-1]"
},
"R5": {
"serializedValue": "11048ec8c8ee87678c9c01008c9c01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1770581987847,9990,0,9990]"
},
"R6": {
"serializedValue": "64fa7ca82f3ba08805ba67b051a769a4cdd6e2dcc0bd3f005fa75b2559f715612601072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e0c576861742773204e6578743f",
"sigmaType": "Coll[SByte]",
"renderedValue": "576861742773204e6578743f"
}
}
},
{
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"value": 14852470404,
"index": 3,
"spendingProof": "e0eab83c0f9efbf39933cb55492d9b69d3d537c9130b7ccf16cc442049b429087828d5eb85eac8275ed1f6531e48f12f10329c307ef18615",
"outputBlockId": "dc3742ead9045e22e8de82c2687a2d358c4b36660f320da0c296bfb49c384eea",
"outputTransactionId": "f24853799bfbe4a1ca0dc64a026f39972613c3a1f0205dfdb5712209622fb83b",
"outputIndex": 2,
"outputGlobalIndex": 52043546,
"outputCreatedAt": 1670812,
"outputSettledAt": 1670814,
"ergoTree": "0008cd03912b861288c508d4d5ac377a74d2c85d329414a60d987fde1031c08bab89a509",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(912b86,32b8ba,...)))}",
"address": "9hZjs6qFPNqKTe8H9veR46i12S1NwN2acGqpXosWUsyjhGc8JYv",
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"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "644e21f9ad79f08e5f98666a3edc24c9e7666010ef45ebe3a209bffa170e14a76406072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "5737041a684bd72a6a4b5908fbca1da7eda6cb5ac86c9c9ae81d32b8c0414025",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 1000000000,
"index": 0,
"globalIndex": 53378777,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(82,21,-96,77,68,76,-71,114,55,-24,-7,-126,-96,27,31,19,117,-107,-57,125,115,123,-52,119,-124,-94,-54,68,-127,21,25,-74)",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](\n -34.toByte, -82.toByte, -49.toByte, 91.toByte, 100.toByte, -70.toByte, -42.toByte, -11.toByte, 87.toByte, 11.toByte, -83.toByte, 10.toByte, 97.toByte, 12.toByte, 78.toByte, 72.toByte, 73.toByte, 87.toByte, -49.toByte, 71.toByte, -126.toByte, 48.toByte, -124.toByte, 0.toByte, -68.toByte, -112.toByte, 64.toByte, 76.toByte, 29.toByte, 20.toByte, 16.toByte, -38.toByte\n )\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val func3 = {(tuple3: (Coll[Box], Coll[Byte])) =>\n tuple3._1.filter({(box5: Box) => box5.tokens.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == tuple3._2 }) })\n }\n val box4 = func3((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)\n val opt5 = getVar[Coll[Byte]](1.toByte)\n val func6 = {(opt6: Option[Coll[Byte]]) => opt6.get.slice(1, 33) }\n val func7 = {(box7: Box) => box7.tokens(0) }\n val tuple8 = func7(SELF)\n val box9 = func3((OUTPUTS, tuple8._1))(0)\n val func10 = {(box10: Box) => box10.tokens(1) }\n val func11 = {(coll11: Coll[Byte]) =>\n val coll13 = func2(box4).getMany(Coll[Coll[Byte]](coll1, coll11), opt5.get)\n allOf(\n Coll[Boolean](\n {(tuple14: (Coll[Box], Coll[Byte])) => tuple14._1.filter({(box16: Box) => blake2b256(box16.propositionBytes) == tuple14._2 }) }(\n (INPUTS, func6(coll13(1)))\n ).size == 1, {(coll14: Coll[Byte]) =>\n allOf(Coll[Boolean](blake2b256(box9.propositionBytes) == coll14, func7(box9) == tuple8, func10(box9)._1 == func10(SELF)._1))\n }(func6(coll13(0)))\n )\n )\n }\n val b12 = getVar[Byte](0.toByte).get\n val i13 = INPUTS.indexOf(SELF, 0)\n val func14 = {(l14: Long) =>\n if (l14 < 128L) { 1 } else {\n if (l14 < 16384L) { 2 } else {\n if (l14 < 2097152L) { 3 } else {\n if (l14 < 268435456L) { 4 } else {\n if (l14 < 34359738368L) { 5 } else {\n if (l14 < 4398046511104L) { 6 } else { if (l14 < 562949953421312L) { 7 } else { if (l14 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b15: Byte) =>\n if (b15 == 0.toByte) {\n func11(\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 2.toByte) {\n func11(\n Coll[Byte](\n -117.toByte, -57.toByte, -113.toByte, 28.toByte, 106.toByte, -82.toByte, -55.toByte, 30.toByte, 98.toByte, -114.toByte, 21.toByte, -49.toByte, 102.toByte, -116.toByte, 22.toByte, -52.toByte, 30.toByte, -101.toByte, -40.toByte, -28.toByte, -71.toByte, -73.toByte, -31.toByte, 109.toByte, 99.toByte, 24.toByte, -75.toByte, -11.toByte, 35.toByte, -91.toByte, -23.toByte, -67.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 1.toByte) {\n func11(\n Coll[Byte](\n -120.toByte, 48.toByte, 97.toByte, 44.toByte, 82.toByte, 53.toByte, 95.toByte, 111.toByte, 40.toByte, 13.toByte, 18.toByte, -105.toByte, -15.toByte, -97.toByte, 103.toByte, -80.toByte, 120.toByte, -55.toByte, -38.toByte, -89.toByte, -41.toByte, -80.toByte, 75.toByte, 69.toByte, -100.toByte, -111.toByte, -52.toByte, 100.toByte, 73.toByte, 87.toByte, -62.toByte, -128.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 3.toByte) {\n func11(\n Coll[Byte](\n 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\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 4.toByte) {\n func11(\n Coll[Byte](\n -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\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 5.toByte) {\n func11(\n Coll[Byte](\n 58.toByte, 17.toByte, -107.toByte, 92.toByte, 71.toByte, 25.toByte, -27.toByte, -120.toByte, -68.toByte, -26.toByte, -89.toByte, 97.toByte, 29.toByte, 39.toByte, -67.toByte, 31.toByte, -33.toByte, -37.toByte, 87.toByte, 56.toByte, 92.toByte, -82.toByte, -30.toByte, 102.toByte, -40.toByte, 4.toByte, 12.toByte, -119.toByte, 79.toByte, 28.toByte, 46.toByte, 29.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 6.toByte) {\n func11(\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) => if (b15 == 7.toByte) { {(tuple17: (Coll[Byte], Box)) => if (i13 >= OUTPUTS.size) { false } else {(\n val box19 = OUTPUTS(i13)\n val l20 = box19.value\n val l21 = SELF.value\n val coll22 = box19.propositionBytes\n val coll23 = SELF.bytesWithoutRef\n val coll24 = SELF.propositionBytes\n val i25 = SELF.creationInfo._1\n val coll26 = box19.bytesWithoutRef\n val i27 = box19.creationInfo._1\n allOf(Coll[Boolean](l20 >= l21 - 2000000L, blake2b256(coll22) == func6(func2(tuple17._2).getMany(Coll[Coll[Byte]](tuple17._1), opt5.getOrElse(Coll[Byte]()))(0)), coll23.slice(func14(l21) + coll24.size + func14(i25.toLong), coll23.size) == coll26.slice(func14(l20) + coll22.size + func14(i27.toLong), coll26.size), anyOf(Coll[Boolean](i27 - i25 >= 504000, coll24 != coll22))))\n )} }((coll1, box4)) } else { false } }(b12)\n )\n )\n )\n}",
"address": "3bseGypFdnej2F2zg7BM3AyjaAR9oq5LNSK6L3UuWYwcyCbG9HLCJcvgKD4aJ6SNZQwCWXRS3knpPqtjJpqstfeGkYtWVtwPxPbXZi8Qo4tQT3yAAQGbXj41CaJEhUXfgcxeo8MwpL2kkQAgKmCmR5JeCEaRrdicqtWVxs2JKSRsbB4Pwh7oWHoZVDq8KY6xXM74UsK9z2JE7VQB7pWvYRis3J7czNFEhAsV7nDMEKizbWPLRyKckCZaDBDABrWw2Bm4va6yypWqWKQn5qoBGhN92VB62SLh7M4mAVmeKzHoXbTbYgtytcca4cjvXa7YDxGddajkc48nwxQrjuHYmx2kvbHqN77QVA1qViiAd2LskwvWcjqrhXqkokorLkPjphiekAyn32YtQYQbzVW5B9EwzuHdXf2yUUU3emCquvA3zUuQzLz1JD14U9C7YYckQoixfUi2ZFzR8EbKekebNYw3ujX8VqnSBhwRW3ZZMUQrzdBWw72fCKP2Py5Luumon8nchZQdxPxikiDaEZkNQEB3NMpWM59KkNU8xi9GqakmHdfC3ETF3Znufj6ZmaYG3orneHrHjX8MV8hBvW6gg3HT12EgkweZs2PHauuGx7rPjhnDFvUyFyRHCWCjc9htPp6Wq598c6FU1pBmQNxXapwXxV4A2wzj3r9sRBRQbLWaiZzA7Uihk6CotmRasrvPGzgVza3hsZBSDFJx7sixtAPibCn5qWSqbH7keEYbR4wXwYSV7FAuXLYpK6x7vs7uwVpAfXCfsec1ihMQr1ZmsDjwgTLDNz2NqwTjCpxsJVdch8JiyYXLijGUKmPnX19XyiZUh45M888icjfgVDWSGbLz1r3QUzKAE46f7RB9qriJWYkwDi84Cdkq1maaunxFA5qvoiXjjmyEF1P4bT3mWMEa6Knb9dsCjFmV7qnML8EyxGLs8CJAoXUWbmvnQ7Jvii29ADENvPnmXFrDz5TMwjwuD232jpTr8YBDH2158bL6UVLTNWv6ZEZw5FUxPgMPfPQAiRfr6mfvEXqrMCcJjB5tTpuGb1KvatFSQmL4goXxWbYxmLgXBcQbwvxNN5as2kRZGtAzjRyMT3NhUQRfb3LUutHQs4nf2HaCtdX6EB2cKniBuHmURNReisVLhnnW2KZ9TzAcmoiYc64nzhKyo43driZ4Y1537Zu3W9z4a26GdUgK65iFo8TsaVNvDgVUPrK2kMAMrReY8qhXkngsVxuYVhKSwDoRg2uFiSAZxEWjktPZKSzzmkuysurhgkA3HfjkYfMYTSFgPwFUwwf93UXSWwfHNFqAFKAVKg5KXMqbC5XFNmRANAxJgt483skLQuFefagnWNYM7SffW6GK5XpnkMFfB7QdKjxNa4ACmR3r7eN13SLZ8mbpBTVhcmy6sDa2uN7fBB4s1MLTja3KjCwvNuSWphPtdD6Rb4hXhprGQnshaN2cuLEaKVDYTFtex6id7WuD5CoAUoyzDYhhUeDqzgoiCz3S9JimpvLNEWcs8RJD364tgeZiEyPFHTRiTGiPThdpeuHxjYpECKnqSFP7phuA5syRpQFHABKEwbE1GMnhS3hmFDEsJiNxsq5uLtWEJ4ifQutb6vW9fMGsRjhFaxdmD8uR2r9PpQyzMW6VuRdQvYEJLi1GguPBN2MRne28yRAbSpFhdedKxstq3BghkTBh8nuTyJU16V71Pf22aEHKinSABYiFiUdza1VjFWCFqrqAyD1jB2jKdziHryUmMpcdMX5LWb9qH59Kj48Lw4Y8hefadzG1m8JfcsfNAQmRv5y59tCr2bsSyHunwsBw",
"assets": [
{
"tokenId": "3b7fb49bc0a262ea890df52483fafe4b59bd376bb6788452796c13ae083b6f50",
"index": 0,
"amount": 1,
"name": "Autolykos Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e840e3bf0c4a3390d6ad9e3e9bcc14638e649feddcdd8d245f75b9738680fef6",
"index": 1,
"amount": 145480,
"name": "LYKOS",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "110788e6afbbd9668ee1111a0488ea010000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1764354292100,145479,13,2,14980,0,0]"
},
"R6": {
"serializedValue": "1d0501000100010001000100",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[0],[0],[0],[0],[0]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402700c2824d253dafe97b7fe25a5dcc1c3f73cafba57d528ca16588e3d07e5950e04072000dbf579333f05ad7a25f4019c5d0e4207baedafd4523d1e0f633c2f52bd20aabf02072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "53685b29247d5463da9aba4c11e6db59cc56ca8c2f17fa964d55e26bfadeae6d",
"mainChain": true
},
{
"boxId": "666aa2207ac14ca88f9c71e183321acdd10118f53a7ae5e553d3da1803399357",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 1000000,
"index": 1,
"globalIndex": 53378778,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(82,21,-96,77,68,76,-71,114,55,-24,-7,-126,-96,27,31,19,117,-107,-57,125,115,123,-52,119,-124,-94,-54,68,-127,21,25,-74)\n1: Coll(59,127,-76,-101,-64,-94,98,-22,-119,13,-11,36,-125,-6,-2,75,89,-67,55,107,-74,120,-124,82,121,108,19,-82,8,59,111,80)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[Coll[Byte]]](0.toByte).get\n val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(CONTEXT.dataInputs(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n ), Coll[Byte](\n 61.toByte, -86.toByte, 102.toByte, -128.toByte, -114.toByte, 105.toByte, -62.toByte, 90.toByte, -23.toByte, 50.toByte, -35.toByte, 102.toByte, 97.toByte, 28.toByte, 95.toByte, 11.toByte, 60.toByte, -70.toByte, -54.toByte, -47.toByte, 18.toByte, 82.toByte, 3.toByte, -24.toByte, 125.toByte, -115.toByte, -60.toByte, -111.toByte, -122.toByte, 28.toByte, 113.toByte, -26.toByte\n )\n ), coll1(0)\n )\n val coll3 = coll1(9)\n val func4 = {(tuple4: (Coll[Box], Coll[Byte])) =>\n tuple4._1.filter({(box6: Box) => box6.tokens.exists({(tuple8: (Coll[Byte], Long)) => tuple8._1 == tuple4._2 }) })\n }\n val coll5 = placeholder[Coll[Byte]](1)\n val box6 = func4((OUTPUTS, coll5))(0)\n val box7 = func4((INPUTS, coll5))(0)\n val func8 = {(box8: Box) => box8.R4[Coll[AvlTree]].get(0) }\n val avlTree9 = func8(box7)\n val box10 = func4((INPUTS, {(opt10: Option[Coll[Byte]]) => opt10.get.slice(6, 38) }(coll2(1))))(0)\n val coll11 = avlTree9.get(coll3, coll1(2)).get\n val coll12 = longToByteArray(\n max({(box12: Box) => box12.R5[Coll[Long]].get(0) }(box10), {(coll12: Coll[Byte]) => byteArrayToLong(coll12.slice(0, 8)) }(coll11))\n ).append(coll11.slice(8, coll11.size))\n val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n val avlTree14 = func13(box7)\n val opt15 = avlTree14.get(coll3, coll1(4))\n val bool16 = opt15.isDefined\n val opt17 = {(box17: Box) => box17.R6[AvlTree].get }(box10).get(coll3, coll1(1))\n val bool18 = opt17.isDefined\n val l19 = if (bool16) { byteArrayToLong(opt15.get.slice(0, 8)) } else { 0L }\n val l20 = if (bool18) { l19 } else { l19 + 1L }\n val l21 = if (bool16) { byteArrayToLong(opt15.get.slice(8, 16)) } else { 0L }\n val coll22 = coll1(8)\n val l23 = coll22.indices.slice(0, coll22.size / 8).map({(i23: Int) => byteArrayToLong(coll22.slice(i23 * 8, i23 + 1 * 8)) }).fold(\n 0L, {(tuple23: (Long, Long)) => tuple23._1 + tuple23._2 }\n )\n val l24 = if (bool18) {(\n val coll24 = opt17.get\n max(\n l21 - coll24.indices.slice(0, coll24.size / 8).map({(i25: Int) => byteArrayToLong(coll24.slice(i25 * 8, i25 + 1 * 8)) }).fold(\n 0L, {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }\n ) + l23, 0L\n )\n )} else { l21 + l23 }\n val coll25 = longToByteArray(l20).append(longToByteArray(l24))\n val coll26 = coll1(5)\n val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(0) }\n val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(1) }\n val func29 = {(box29: Box) => box29.R5[Coll[Long]].get(2) }\n val func30 = {(box30: Box) => box30.R5[Coll[Long]].get(3) }\n val func31 = {(box31: Box) => box31.R5[Coll[Long]].get(4) }\n val func32 = {(box32: Box) =>\n val coll34 = box32.R5[Coll[Long]].get\n coll34.slice(5, coll34.size)\n }\n val func33 = {(box33: Box) => box33.R6[Coll[Coll[Long]]].get }\n val func34 = {(box34: Box) => box34.R7[Coll[(AvlTree, AvlTree)]].get }\n val func35 = {(box35: Box) => box35.R8[Coll[Long]].get }\n sigmaProp(\n allOf(\n Coll[Boolean](\n {(tuple36: (Coll[Box], Coll[Byte])) => tuple36._1.filter({(box38: Box) => blake2b256(box38.propositionBytes) == tuple36._2 }) }(\n (OUTPUTS, {(opt36: Option[Coll[Byte]]) => opt36.get.slice(1, 33) }(coll2(0)))\n )(0).value >= SELF.value, {(tuple36: (Coll[Box], Coll[Byte])) =>\n tuple36._1.exists({(box38: Box) => box38.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == tuple36._2 }) })\n }((OUTPUTS, coll3)), allOf(\n Coll[Boolean](\n box6.value == box7.value, box6.tokens == box7.tokens, func8(box6).digest == avlTree9.update(\n Coll[(Coll[Byte], Coll[Byte])]((coll3, coll12)), coll1(3)\n ).get.digest, func13(box6).digest == if (bool16) { avlTree14.update(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get } else {\n avlTree14.insert(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get\n }.digest, func27(box6) == func27(box7), func28(box6) == func28(box7), func29(box6) == func29(box7), func30(box6) == func30(\n box7\n ) + l20 - l19, func31(box6) == func31(box7) + l24 - l21, func32(box6) == func32(box7), func33(box6) == func33(box7), func34(box6) == func34(\n box7\n ), func35(box6) == func35(box7)\n )\n ), coll1(6) == coll12, coll1(7) == coll25\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "53685b29247d5463da9aba4c11e6db59cc56ca8c2f17fa964d55e26bfadeae6d",
"mainChain": true
},
{
"boxId": "3215459224d4636215838d2c8e0d3368ba3ad2177cc7822107de0a0e73c1ff9f",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 5000000,
"index": 2,
"globalIndex": 53378779,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(82,21,-96,77,68,76,-71,114,55,-24,-7,-126,-96,27,31,19,117,-107,-57,125,115,123,-52,119,-124,-94,-54,68,-127,21,25,-74)\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(59,127,-76,-101,-64,-94,98,-22,-119,13,-11,36,-125,-6,-2,75,89,-67,55,107,-74,120,-124,82,121,108,19,-82,8,59,111,80)",
"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 b4 = getVar[Byte](0.toByte).get\n val func5 = {(box5: Box) =>\n val coll7 = box5.R5[Coll[Long]].get\n coll7.slice(2, coll7.size)\n }\n val opt6 = getVar[(Int, Long)](10.toByte)\n val tuple7 = (-2, 0L)\n val tuple8 = tuple7\n val tuple9 = opt6.getOrElse(tuple8)\n val i10 = tuple9._1\n val l11 = tuple9._2\n val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n val coll17 = placeholder[Coll[Byte]](3)\n val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n }\n val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple22 = tuple20._2\n val l23 = tuple22._1\n val tuple24 = tuple22._2\n val l25 = tuple24._1\n val l26 = tuple24._2\n tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n val l29 = byteArrayToLong(coll27.slice(1, 9))\n if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n )} else { l26 } }).getOrElse(l26)\n }\n val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b22: Byte) =>\n if (b22 == 12.toByte) {\n {(coll24: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n } else { false }\n }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n val coll24 = func5(SELF)\n val coll25 = SELF.propositionBytes\n val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n val l27 = box26.value\n val l28 = func14(SELF)\n val coll29 = CONTEXT.dataInputs\n val coll30 = Coll[Byte]()\n val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n val tuple32 = (1L, (999L, 500L))\n val opt33 = opt6\n val tuple34 = tuple7\n val tuple35 = tuple8\n val tuple36 = tuple9\n val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.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)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n val l39 = l11\n l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n val tuple43 = tuple41._2\n tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll25 = coll24(4)\n val coll26 = coll24(3)\n val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n val coll29 = SELF.propositionBytes\n val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n val l31 = func21(SELF)\n val avlTree32 = func15(SELF)\n val opt33 = avlTree32.get(coll25, coll24(0))\n val bool34 = opt33.isDefined\n val coll35 = coll24(1)\n val coll36 = func5(SELF)\n val coll37 = func5(box30)\n allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n val coll38 = opt33.get\n val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n )} else { false } }(b4)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "bf32c3308b7ffcb13ef37ff004aa3412d9e83d297e540733d62283e03fac9a43",
"index": 0,
"amount": 1,
"name": "Autolykos Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 5000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10020001",
"sigmaType": "Coll[SInt]",
"renderedValue": "[0,-1]"
},
"R5": {
"serializedValue": "11048ec8c8ee876788ea010088ea01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1770581987847,14980,0,14980]"
},
"R6": {
"serializedValue": "647ed451f7c9edc5b35aaa577734aae1f5b078c39b4e0fe60c81dea85a27b5acc502072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e0c576861742773204e6578743f",
"sigmaType": "Coll[SByte]",
"renderedValue": "576861742773204e6578743f"
}
},
"spentTransactionId": "53685b29247d5463da9aba4c11e6db59cc56ca8c2f17fa964d55e26bfadeae6d",
"mainChain": true
},
{
"boxId": "3aa005840db09ae51c3eeee39df427bc4d4a93ce2442f3fd912cb0756f73dd50",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 1000000,
"index": 3,
"globalIndex": 53378780,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"ergoTree": "0008cd03912b861288c508d4d5ac377a74d2c85d329414a60d987fde1031c08bab89a509",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(912b86,32b8ba,...)))}",
"address": "9hZjs6qFPNqKTe8H9veR46i12S1NwN2acGqpXosWUsyjhGc8JYv",
"assets": [
{
"tokenId": "444c1aaf08fde0dda7f9305dc038e9034d1487354df7fb8f4dce768bd427bc77",
"index": 0,
"amount": 1,
"name": "Autolykos Membership",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "1527f1c46a4456ccfc05f10e1a4f4779bed19cd60bc5f1303c04c36f3c710dad",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 50000000,
"index": 4,
"globalIndex": 53378781,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "3cc165796a568f3daefa39e981a174f9dd2dbfa18aaf267d8093edc5fdda4ed0",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 1850000,
"index": 5,
"globalIndex": 53378782,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"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": "7bd9c84911ddaef7734d6ad73f5cf72253cc35492d79b1112a3b36d98b6f9592",
"mainChain": true
},
{
"boxId": "9648d920ea716eec5d88e69893065c73b5b5d96a6e84f86fd8e1adf628276bae",
"transactionId": "362ca231b85862767ba68e926776f1dc2db71d2447bfb6d3b7dd87b0b6e92508",
"blockId": "00193c1de4b7fdcb14dd56ae56e0524a21ea4f728d715a9eef1e3799a761b1d1",
"value": 14799620404,
"index": 6,
"globalIndex": 53378783,
"creationHeight": 1714407,
"settlementHeight": 1714408,
"ergoTree": "0008cd03912b861288c508d4d5ac377a74d2c85d329414a60d987fde1031c08bab89a509",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(912b86,32b8ba,...)))}",
"address": "9hZjs6qFPNqKTe8H9veR46i12S1NwN2acGqpXosWUsyjhGc8JYv",
"assets": [
{
"tokenId": "b6b7725cd915850720c1dd19da139086b89d7822294a1fbb666a6dcf78eca10b",
"index": 0,
"amount": 1,
"name": "Paris",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a8bbe82bea3b39c667551dbc523fd5772579ff2fcc47a126bcc39d4b6394e1cd",
"index": 1,
"amount": 1,
"name": "Lysander #70",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "743788c4ba8477553f0c51be92a80a433c9ea2bb5b5a222d41cd01296034dfbb",
"index": 2,
"amount": 1,
"name": "Autolykos",
"decimals": 0,
"type": "EIP-004"
},
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