Transaction
ID: 9da3e650f6...9a0f
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
12.88 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (13)
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
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:
9.87 ERG
Tokens:
Loading assets...
Transaction Details
Status: Confirmed
Size: 14.93 KB
Received time: 10/11/2024 10:14:25 AM
Included in blocks: 1,371,174
Confirmations: 395,329
Total coins transferred: 12.88 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000065 ERG
Raw Transaction Data
{
"id": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"inclusionHeight": 1371174,
"timestamp": 1728641665298,
"index": 1,
"globalIndex": 7894483,
"numConfirmations": 395329,
"inputs": [
{
"boxId": "a6ddbf7487710f9683c1b9fea88ffc243d49fa482bac0800f07a64cf998216bb",
"value": 1000000,
"index": 0,
"spendingProof": "b61714e748bce502d887db38119aee41ded09517a32dcf83f9dbd315eee26ebb7215bffd7df7308230b2492b68734e5e9d1e7e4bc81d5164",
"outputBlockId": "fd5afac42ff5893fec2dce573a101c5a378e95ca9fbfcce236f4e14c0a77899f",
"outputTransactionId": "e2bfa895c787044251931f264da27d12230854816eb873e14b9b822fd3116dde",
"outputIndex": 2,
"outputGlobalIndex": 42160533,
"outputCreatedAt": 1330568,
"outputSettledAt": 1330570,
"ergoTree": "0008cd02e4cb952261186ec0fd2dc4c2baa8dbfd9c8f6012c5efa9f702f9450a58fe221e",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e4cb95,7c781d,...)))}",
"address": "9gFpnLUGwRyohhoh5CXQS8eNdranNyNVGreCmc4xFYHPg5JUGWL",
"assets": [
{
"tokenId": "24b33d72bc82d430fd68b20dc22af598be6994189a96d1ee1eef78fd93b5f763",
"index": 0,
"amount": 1,
"name": "Paideia Stake Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "c4be471229666f15d06f94f5d8c65de4f22be60ed636c960ef18a137b8a45b43",
"value": 12876593686,
"index": 1,
"spendingProof": "815bff1b135b2f2993b9e58d7f59bfe9cedcb7657e600f538be60a2fef2f2d45181397ca8bba5f2ef48ce2361dc18914c3daebb54ab471a0",
"outputBlockId": "f5a4226225cf673fae3ee2eadbf73205a4e9b5dc4fff8c59d10aac2d8b87d463",
"outputTransactionId": "2a9a9803adcfe174d95b77309a1ba253caf7af8f2f321f33d67f7c33598832d3",
"outputIndex": 2,
"outputGlobalIndex": 42236452,
"outputCreatedAt": 1333573,
"outputSettledAt": 1333576,
"ergoTree": "0008cd02e4cb952261186ec0fd2dc4c2baa8dbfd9c8f6012c5efa9f702f9450a58fe221e",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e4cb95,7c781d,...)))}",
"address": "9gFpnLUGwRyohhoh5CXQS8eNdranNyNVGreCmc4xFYHPg5JUGWL",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 477727928648,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "7b976757ded023ccdffc1c6958376727fc392e60ed5627fb4e405177a8a090c1",
"index": 1,
"amount": 1,
"name": "Paideia Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "59ee24951ce668f0ed32bdb2e2e5731b6c36128748a3b23c28407c5f8ccbf0f6",
"index": 2,
"amount": 4,
"name": "WALRUS",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 3,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "045d2f3ae2f7c17c83bd6a56d9ea64209802a62598ee138ed5289ea947393eee",
"index": 4,
"amount": 9997,
"name": "RosenGuard",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00de06c61282578684b377ffd6314c38ce596f2c054107fe2314810677859269",
"index": 5,
"amount": 98698999999997,
"name": "MyFirstDAOToken",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "94073554b6fed07682cc819527a0188ab913698233fedd1bb908368e275a24b1",
"index": 6,
"amount": 1,
"name": "RosenGuards Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4679238680dadf89f6670c1d83563e87e16616407845ce7bdf5b9e3aee1ae8b8",
"index": 7,
"amount": 1,
"name": "Sigmanauts Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "669438571de1006db69e406bab15881b8c85f5b8a231b54c12db1923654b8220",
"index": 8,
"amount": 1,
"name": "MyFirstDAO Stake Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "510e05d9854eff54de17b558a120b700a222de31f6c1e945621a5195aecbd1ec",
"value": 1000000,
"index": 2,
"spendingProof": "837d57624c2c575269e0ee4b6c2c6cc6dc059fb39e0e2132125df9c25590c089f2c33b8744c26660f17df969ff773bca70f5c20a054bd919",
"outputBlockId": "480ed30be1c40f399cef0495d62b8fd9194bb74559d92451b164ef4749cb37c9",
"outputTransactionId": "5a81573d1a74f1219672c5d619b4b33bfe3d930402b6c3b704ba4e88f88952b7",
"outputIndex": 0,
"outputGlobalIndex": 43176413,
"outputCreatedAt": 1371163,
"outputSettledAt": 1371168,
"ergoTree": "0008cd02e4cb952261186ec0fd2dc4c2baa8dbfd9c8f6012c5efa9f702f9450a58fe221e",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e4cb95,7c781d,...)))}",
"address": "9gFpnLUGwRyohhoh5CXQS8eNdranNyNVGreCmc4xFYHPg5JUGWL",
"assets": [
{
"tokenId": "005a993f953394bb898f7a2de29757acee1f31b77db262e807d01553f3c1a062",
"index": 0,
"amount": 9223372036854776000,
"name": "Paideia Action",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00aa649808f01c850b4e022368fdfa836ddeabcf3c09d56d0d0fd19cf3f62302",
"index": 1,
"amount": 9223372036854776000,
"name": "Paideia Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00acf1fefff7181e8c4f9476112dd4400212a2c5856d10384f998ce86a8a4c78",
"index": 2,
"amount": 1,
"name": "Paideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00eecc3039d053630a03d8922ba8107bcfa1f503230ad20edbfc2212f5f7fce8",
"index": 3,
"amount": 9223372036854776000,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00f2d9d3555e183ee6625c9052be4dc8251f7c6ff6b1eee39eacbf3c098c2695",
"index": 4,
"amount": 1,
"name": "Paideia Origin",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00f8f5bbe544e16c5d51098f361ac5fd975beee0abca8ac76f0d7a388c32ef26",
"index": 5,
"amount": 1,
"name": "Paideia DAO Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "c6d4f55ad21a68eb125f22e24c6c40066f235f5bfbfaf98b3518a72115c0fcfa",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 0,
"globalIndex": 43176498,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "10020e2000f8f5bbe544e16c5d51098f361ac5fd975beee0abca8ac76f0d7a388c32ef260e200040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983d808d6017300d602d901023c0c630eb58c720201d9010463aedb63087204d901064d0e938c7206018c720202d603d9010363e4c672030464d604e3010ed605d9010532b4e4720504020442d606e4e30002d607dc0c1aa402a70400d608d9010805958f72080580020402958f7208058080020404958f720805808080020406958f72080580808080020408958f720805808080808002040a958f72080580808080808002040c958f7208058080808080808002040e958f72080580808080808080800204100412d197830201dad901090295937209020ed80bd60bb2a5040200d60cdb6308720bd60ddb6308a7d60eb2720c040200d60fb2720d040200d6108c720f01d611b2a5040000d612dc640bda720301b2da7202018602db6501fe72010400000283050e8320020272022902fd02af02bb02960211026f023c0288025e02bd0273021902a302290284024202ca02840200023802ee020c025e026d023202ea0273025e024a0216832002024602b30264020a02310273028402bd02aa025002b702a4022002cf028f023602a302b8027902fe024e02cc021202b60292024a02ce024502e7023502210223832002025b02e4024702c70213029202c4023002b00212026002480226029f029a0278028a02f3025502270275025f02ac02e902d2022902fd02860253020e023402f5832002021d02ec02b2024f020802f902ff0215022202b6025302a50256028e027202dd0242024d028a02980256021f023e02cf022e02ec02a102820232022502c702698320020276027c02aa028002b9028e0249026a02d802a902f6028902c40241020a02e402530232027f020f029502e90250028402c002ae0220026302500279023b0277e47204d613b2db63087211040000d614b2a5040400d615b2db63087214040000968304019683060193b2720c040000b2720d040000938c720e017210938c720e02998c720f02050293b1720c040493c2720bc2a792c1720bc1a79683030193cbc27211da720501b27212040400938c7213017210938c72130205029683040193cbc27214da720501b2721204080093c172149a7cb4e4b27212040000040204120580897a938c7215017301938c7215027cb4e4b272120402000402041293cbc2b2a4040000da720501b272120406000100017206dad9010902959372090207dad9010b3c0e6395927207b1a50100d809d60db2a5720700d60ec1720dd60fc1a7d610c2720dd611c4a7d612c2a7d6138cc7a701d614c4720dd6158cc7720d019683040192720e99720f058092f40193cb7210da720501b2dc640bda7203018c720b020283010e8c720b01e5720483000204000093b472119a9ada720801720fb17212da7208017e721305b17211b472149a9ada720801720eb17210da7208017e721505b17214978302019299721572130480c33d9472127210018602832002020802030287020f02c7028902a202d30222020702ab028102fc028102f4025a02440271021f022b0258020e02f602e702d2026002f5021602400234024d022bb2da7202018602db6501fe72010400000100017206",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,64,-82,101,12,78,-41,123,-51,32,57,20,-109,-85,-24,76,26,-101,-75,-114,-24,-114,-121,-15,86,112,-56,1,-30,-4,89,-125)",
"ergoTreeScript": "{\n val coll1 = placeholder[Coll[Byte]](0)\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 func3 = {(box3: Box) => box3.R4[AvlTree].get }\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(opt5: Option[Coll[Byte]]) => opt5.get.slice(1, 33) }\n val b6 = getVar[Byte](0.toByte).get\n val i7 = INPUTS.indexOf(SELF, 0)\n val func8 = {(l8: Long) =>\n if (l8 < 128L) { 1 } else {\n if (l8 < 16384L) { 2 } else {\n if (l8 < 2097152L) { 3 } else {\n if (l8 < 268435456L) { 4 } else {\n if (l8 < 34359738368L) { 5 } else {\n if (l8 < 4398046511104L) { 6 } else { if (l8 < 562949953421312L) { 7 } else { if (l8 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b9: Byte) => if (b9 == 14.toByte) {(\n val box11 = OUTPUTS(1)\n val coll12 = box11.tokens\n val coll13 = SELF.tokens\n val tuple14 = coll12(1)\n val tuple15 = coll13(1)\n val coll16 = tuple15._1\n val box17 = OUTPUTS(0)\n val coll18 = func3(func2((CONTEXT.dataInputs, coll1))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](114.toByte, 41.toByte, -3.toByte, -81.toByte, -69.toByte, -106.toByte, 17.toByte, 111.toByte, 60.toByte, -120.toByte, 94.toByte, -67.toByte, 115.toByte, 25.toByte, -93.toByte, 41.toByte, -124.toByte, 66.toByte, -54.toByte, -124.toByte, 0.toByte, 56.toByte, -18.toByte, 12.toByte, 94.toByte, 109.toByte, 50.toByte, -22.toByte, 115.toByte, 94.toByte, 74.toByte, 22.toByte), Coll[Byte](70.toByte, -77.toByte, 100.toByte, 10.toByte, 49.toByte, 115.toByte, -124.toByte, -67.toByte, -86.toByte, 80.toByte, -73.toByte, -92.toByte, 32.toByte, -49.toByte, -113.toByte, 54.toByte, -93.toByte, -72.toByte, 121.toByte, -2.toByte, 78.toByte, -52.toByte, 18.toByte, -74.toByte, -110.toByte, 74.toByte, -50.toByte, 69.toByte, -25.toByte, 53.toByte, 33.toByte, 35.toByte), Coll[Byte](91.toByte, -28.toByte, 71.toByte, -57.toByte, 19.toByte, -110.toByte, -60.toByte, 48.toByte, -80.toByte, 18.toByte, 96.toByte, 72.toByte, 38.toByte, -97.toByte, -102.toByte, 120.toByte, -118.toByte, -13.toByte, 85.toByte, 39.toByte, 117.toByte, 95.toByte, -84.toByte, -23.toByte, -46.toByte, 41.toByte, -3.toByte, -122.toByte, 83.toByte, 14.toByte, 52.toByte, -11.toByte), Coll[Byte](29.toByte, -20.toByte, -78.toByte, 79.toByte, 8.toByte, -7.toByte, -1.toByte, 21.toByte, 34.toByte, -74.toByte, 83.toByte, -91.toByte, 86.toByte, -114.toByte, 114.toByte, -35.toByte, 66.toByte, 77.toByte, -118.toByte, -104.toByte, 86.toByte, 31.toByte, 62.toByte, -49.toByte, 46.toByte, -20.toByte, -95.toByte, -126.toByte, 50.toByte, 37.toByte, -57.toByte, 105.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)), opt4.get)\n val tuple19 = box17.tokens(0)\n val box20 = OUTPUTS(2)\n val tuple21 = box20.tokens(0)\n allOf(Coll[Boolean](allOf(Coll[Boolean](coll12(0) == coll13(0), tuple14._1 == coll16, tuple14._2 == tuple15._2 - 1L, coll12.size == 2, box11.propositionBytes == SELF.propositionBytes, box11.value >= SELF.value)), allOf(Coll[Boolean](blake2b256(box17.propositionBytes) == func5(coll18(2)), tuple19._1 == coll16, tuple19._2 == 1L)), allOf(Coll[Boolean](blake2b256(box20.propositionBytes) == func5(coll18(4)), box20.value == byteArrayToLong(coll18(0).get.slice(1, 9)) + 1000000L, tuple21._1 == placeholder[Coll[Byte]](1), tuple21._2 == byteArrayToLong(coll18(1).get.slice(1, 9)))), blake2b256(INPUTS(0).propositionBytes) == func5(coll18(3))))\n )} else { false } }(b6), {(b9: Byte) => if (b9 == 7.toByte) { {(tuple11: (Coll[Byte], Box)) => if (i7 >= OUTPUTS.size) { false } else {(\n val box13 = OUTPUTS(i7)\n val l14 = box13.value\n val l15 = SELF.value\n val coll16 = box13.propositionBytes\n val coll17 = SELF.bytesWithoutRef\n val coll18 = SELF.propositionBytes\n val i19 = SELF.creationInfo._1\n val coll20 = box13.bytesWithoutRef\n val i21 = box13.creationInfo._1\n allOf(Coll[Boolean](l14 >= l15 - 2000000L, blake2b256(coll16) == func5(func3(tuple11._2).getMany(Coll[Coll[Byte]](tuple11._1), opt4.getOrElse(Coll[Byte]()))(0)), coll17.slice(func8(l15) + coll18.size + func8(i19.toLong), coll17.size) == coll20.slice(func8(l14) + coll16.size + func8(i21.toLong), coll20.size), anyOf(Coll[Boolean](i21 - i19 >= 504000, coll18 != coll16))))\n )} }((Coll[Byte](8.toByte, 3.toByte, -121.toByte, 15.toByte, -57.toByte, -119.toByte, -94.toByte, -45.toByte, 34.toByte, 7.toByte, -85.toByte, -127.toByte, -4.toByte, -127.toByte, -12.toByte, 90.toByte, 68.toByte, 113.toByte, 31.toByte, 43.toByte, 88.toByte, 14.toByte, -10.toByte, -25.toByte, -46.toByte, 96.toByte, -11.toByte, 22.toByte, 64.toByte, 52.toByte, 77.toByte, 43.toByte), func2((CONTEXT.dataInputs, coll1))(0))) } else { false } }(b6))))\n}",
"address": "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",
"assets": [
{
"tokenId": "00f2d9d3555e183ee6625c9052be4dc8251f7c6ff6b1eee39eacbf3c098c2695",
"index": 0,
"amount": 1,
"name": "Paideia Origin",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00eecc3039d053630a03d8922ba8107bcfa1f503230ad20edbfc2212f5f7fce8",
"index": 1,
"amount": 9223372036854776000,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "97c0e78cc83908cef561d900786f0b7d09864532ea671013864c0775e832a914",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000000,
"index": 1,
"globalIndex": 43176499,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n2: Coll(0,64,-82,101,12,78,-41,123,-51,32,57,20,-109,-85,-24,76,26,-101,-75,-114,-24,-114,-121,-15,86,112,-56,1,-30,-4,89,-125)\n3: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val coll1 = placeholder[Coll[Byte]](0)\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 func3 = {(box3: Box) => box3.R4[AvlTree].get }\n val coll4 = Coll[Byte](\n 3.toByte, -99.toByte, 42.toByte, 10.toByte, 33.toByte, -115.toByte, 124.toByte, 72.toByte, -56.toByte, -3.toByte, 70.toByte, -88.toByte, -46.toByte, -108.toByte, 49.toByte, -67.toByte, 5.toByte, 108.toByte, -124.toByte, -120.toByte, 42.toByte, 33.toByte, 106.toByte, 86.toByte, 115.toByte, 38.toByte, -61.toByte, -57.toByte, -104.toByte, 78.toByte, -56.toByte, 53.toByte\n )\n val func5 = {(opt5: Option[Coll[Byte]]) => opt5.get.slice(1, 33) }\n val func6 = {(box6: Box) => box6.tokens(0) }\n val func7 = {(box7: Box) => box7.tokens(1) }\n val func8 = {(box8: Box) => box8.tokens(2) }\n val func9 = {(tuple9: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple11 = tuple9._2\n val l12 = tuple11._1\n val tuple13 = tuple11._2\n val l14 = tuple13._1\n val l15 = tuple13._2\n tuple9._1.map({(coll16: Coll[Byte]) => if (coll16.size == 9) {(\n val l18 = byteArrayToLong(coll16.slice(1, 9))\n if (l18 < l12) { l12 } else { if (l18 > l14) { l14 } else { l18 } }\n )} else { l15 } }).getOrElse(l15)\n }\n val b10 = getVar[Byte](0.toByte).get\n val i11 = INPUTS.indexOf(SELF, 0)\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 sigmaProp(anyOf(Coll[Boolean]({(b13: Byte) => if (b13 == 11.toByte) {(\n val box15 = OUTPUTS(0)\n val coll16 = CONTEXT.dataInputs\n val box17 = getVar[Box](2.toByte).get\n val coll18 = box17.propositionBytes\n val coll19 = getVar[Coll[Box]](3.toByte).get\n val coll20 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll21 = func3(func2((coll16, coll1))(0)).getMany(Coll[Coll[Byte]](coll4, Coll[Byte](-16.toByte, 54.toByte, 125.toByte, -33.toByte, 52.toByte, 53.toByte, -104.toByte, 31.toByte, 74.toByte, -91.toByte, 87.toByte, 27.toByte, -111.toByte, -35.toByte, 70.toByte, -2.toByte, -127.toByte, 54.toByte, 103.toByte, -14.toByte, -120.toByte, -115.toByte, 79.toByte, -58.toByte, -111.toByte, -106.toByte, -113.toByte, -34.toByte, 21.toByte, -121.toByte, -101.toByte, -105.toByte), Coll[Byte](88.toByte, 30.toByte, -80.toByte, 92.toByte, -24.toByte, 20.toByte, -36.toByte, 63.toByte, 36.toByte, 121.toByte, -28.toByte, -80.toByte, 2.toByte, 125.toByte, -79.toByte, -59.toByte, 73.toByte, 79.toByte, -28.toByte, 32.toByte, 61.toByte, 117.toByte, -124.toByte, 18.toByte, 101.toByte, -10.toByte, -57.toByte, 82.toByte, -105.toByte, -43.toByte, -20.toByte, -63.toByte), 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, 112.toByte, 114.toByte, 111.toByte, 112.toByte, 111.toByte, 115.toByte, 97.toByte, 108.toByte, 46.toByte).append(coll18))).append(coll19.map({(box21: Box) => 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(box21.propositionBytes)) })), coll20(1))\n val tuple22 = func7(box15)\n val tuple23 = func7(SELF)\n val coll24 = tuple23._1\n val l25 = tuple23._2\n val tuple26 = func8(box15)\n val tuple27 = func8(SELF)\n val coll28 = tuple27._1\n val i29 = coll19.size\n val box30 = OUTPUTS(1)\n val l31 = box30.value\n val l32 = 9223372036854775807L - l25\n val tuple33 = {(box33: Box) => box33.tokens(0) }(box30)\n val tuple34 = {(box34: Box) => box34.tokens(1) }(box30)\n val coll35 = box30.propositionBytes\n val coll36 = OUTPUTS.slice(2, i29 + 2)\n val box37 = func2((coll16, placeholder[Coll[Byte]](3)))(0)\n val coll38 = coll20(2)\n allOf(Coll[Boolean](allOf(Coll[Boolean](blake2b256(box15.propositionBytes) == func5(coll21(0)), box15.value >= SELF.value, func6(box15) == func6(SELF), tuple22._1 == coll24, tuple22._2 == l25 - 1L, tuple26._1 == coll28, tuple26._2 == tuple27._2 - i29.toLong, box15.tokens.size == 3)), allOf(Coll[Boolean](l31 >= box17.value, l31 >= 5000000L, {(box39: Box) => box39.R4[Coll[Int]].get(0) }(box30).toLong == l32, tuple33._1 == coll24, tuple33._2 == 1L, tuple34._1 == placeholder[Coll[Byte]](2), tuple34._2 == func9((func3(func2((coll16, 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)), coll20(0))(0), (0L, (100000000000L, 1000L)))), coll35 == coll18, {(box39: Box) => box39.R5[Coll[Long]].get(0) }(box30) >= CONTEXT.preHeader.timestamp + func9((coll21(1), (43200000L, (2626560000L, 86400000L)))), blake2b256(coll35) == func5(coll21(3)), {(box39: Box) => box39.R5[Coll[Long]].get(1) }(box30) == 0L, {(box39: Box) =>\n val coll41 = box39.R5[Coll[Long]].get\n coll41.slice(2, coll41.size)\n }(box30).forall({(l39: Long) => l39 == 0L }))), coll36.indices.forall({(i39: Int) =>\n val box41 = coll36(i39)\n val l42 = box41.value\n val tuple43 = {(box43: Box) => box43.tokens(0) }(box41)\n allOf(Coll[Boolean](l42 >= coll19(i39).value, l42 >= 2000000L, tuple43._1 == coll28, tuple43._2 == 1L, {(box44: Box) => box44.R4[Coll[Long]].get(0) }(box41) == l32, {(box44: Box) => box44.R4[Coll[Long]].get(1) }(box41) > 0L, blake2b256(box41.propositionBytes) == coll21.slice(4, coll21.size).map({(opt44: Option[Coll[Byte]]) => func5(opt44) })(i39)))\n }), {(coll39: Coll[Byte]) => byteArrayToLong(coll39.slice(8, 16)) }({(box39: Box) => box39.R4[Coll[AvlTree]].get(0) }(box37).get(coll38, coll20(3)).get) >= func9((coll21(2), (0L, ({(box39: Box) => box39.R5[Coll[Long]].get(1) }(box37) / 2L, 0L)))), {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.exists({(box41: Box) => box41.tokens.exists({(tuple43: (Coll[Byte], Long)) => tuple43._1 == tuple39._2 }) }) }((OUTPUTS, coll38))))\n )} else { false } }(b10), {(b13: Byte) => if (b13 == 7.toByte) { {(tuple15: (Coll[Byte], Box)) => if (i11 >= OUTPUTS.size) { false } else {(\n val box17 = OUTPUTS(i11)\n val l18 = box17.value\n val l19 = SELF.value\n val coll20 = box17.propositionBytes\n val coll21 = SELF.bytesWithoutRef\n val coll22 = SELF.propositionBytes\n val i23 = SELF.creationInfo._1\n val coll24 = box17.bytesWithoutRef\n val i25 = box17.creationInfo._1\n allOf(Coll[Boolean](l18 >= l19 - 2000000L, blake2b256(coll20) == func5(func3(tuple15._2).getMany(Coll[Coll[Byte]](tuple15._1), getVar[Coll[Byte]](1.toByte).getOrElse(Coll[Byte]()))(0)), coll21.slice(func12(l19) + coll22.size + func12(i23.toLong), coll21.size) == coll24.slice(func12(l18) + coll20.size + func12(i25.toLong), coll24.size), anyOf(Coll[Boolean](i25 - i23 >= 504000, coll22 != coll20))))\n )} }((coll4, func2((CONTEXT.dataInputs, coll1))(0))) } else { false } }(b10))))\n}",
"address": "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",
"assets": [
{
"tokenId": "00eecc3039d053630a03d8922ba8107bcfa1f503230ad20edbfc2212f5f7fce8",
"index": 0,
"amount": 1,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00aa649808f01c850b4e022368fdfa836ddeabcf3c09d56d0d0fd19cf3f62302",
"index": 1,
"amount": 9223372036854776000,
"name": "Paideia Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "005a993f953394bb898f7a2de29757acee1f31b77db262e807d01553f3c1a062",
"index": 2,
"amount": 9223372036854776000,
"name": "Paideia Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9a44668272af2abf233ef9ad1bbdc99f941cd0e53c9b2bf941c6f04088202124",
"mainChain": true
},
{
"boxId": "12e426555f6c33009bfd57c7661064cc2acafa71c2ec7f002b7fe013372a5735",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000000,
"index": 2,
"globalIndex": 43176500,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,90,-103,63,-107,51,-108,-69,-119,-113,122,45,-30,-105,87,-84,-18,31,49,-73,125,-78,98,-24,7,-48,21,83,-13,-63,-96,98)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) =>\n tuple1._1.filter({(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == tuple1._2 }) })\n }\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val coll3 = Coll[Byte](\n -87.toByte, 85.toByte, -114.toByte, 65.toByte, -122.toByte, -53.toByte, -43.toByte, -86.toByte, 87.toByte, 35.toByte, -88.toByte, 82.toByte, -44.toByte, -63.toByte, -36.toByte, 101.toByte, 125.toByte, -98.toByte, -127.toByte, 67.toByte, -126.toByte, -1.toByte, -120.toByte, -115.toByte, 90.toByte, -118.toByte, -20.toByte, 82.toByte, 21.toByte, 49.toByte, 48.toByte, 29.toByte\n )\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(opt5: Option[Coll[Byte]]) => opt5.get.slice(1, 33) }\n val b6 = getVar[Byte](0.toByte).get\n val i7 = INPUTS.indexOf(SELF, 0)\n val func8 = {(l8: Long) =>\n if (l8 < 128L) { 1 } else {\n if (l8 < 16384L) { 2 } else {\n if (l8 < 2097152L) { 3 } else {\n if (l8 < 268435456L) { 4 } else {\n if (l8 < 34359738368L) { 5 } else {\n if (l8 < 4398046511104L) { 6 } else { if (l8 < 562949953421312L) { 7 } else { if (l8 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b9: Byte) => if (b9 == 8.toByte) {(\n val box11 = func1((OUTPUTS, {(box11: Box) => box11.tokens(0)._1 }(SELF)))(0)\n val coll12 = func2(box11).getMany(Coll[Coll[Byte]](coll3, 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(func1((INPUTS, placeholder[Coll[Byte]](0)))(0).propositionBytes))), opt4.get)\n allOf(Coll[Boolean](SELF.tokens == box11.tokens, SELF.value <= box11.value, blake2b256(box11.propositionBytes) == func5(coll12(0)), coll12(1).isDefined))\n )} else { false } }(b6), (b6 == 7.toByte) && {(tuple9: (Coll[Byte], Box)) => if (i7 >= OUTPUTS.size) { false } else {(\n val box11 = OUTPUTS(i7)\n val l12 = box11.value\n val l13 = SELF.value\n val coll14 = box11.propositionBytes\n val coll15 = SELF.bytesWithoutRef\n val coll16 = SELF.propositionBytes\n val i17 = SELF.creationInfo._1\n val coll18 = box11.bytesWithoutRef\n val i19 = box11.creationInfo._1\n allOf(Coll[Boolean](l12 >= l13 - 2000000L, blake2b256(coll14) == func5(func2(tuple9._2).getMany(Coll[Coll[Byte]](tuple9._1), opt4.getOrElse(Coll[Byte]()))(0)), coll15.slice(func8(l13) + coll16.size + func8(i17.toLong), coll15.size) == coll18.slice(func8(l12) + coll14.size + func8(i19.toLong), coll18.size), anyOf(Coll[Boolean](i19 - i17 >= 504000, coll16 != coll14))))\n )} }((coll3, SELF)))))\n}",
"address": "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",
"assets": [
{
"tokenId": "00f8f5bbe544e16c5d51098f361ac5fd975beee0abca8ac76f0d7a388c32ef26",
"index": 0,
"amount": 1,
"name": "Paideia DAO Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "642f01ed4a888da9262d9b904c3c1895c2d98a0fdf53285d4d467bf8ebb0d1826107072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": null,
"mainChain": true
},
{
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"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 3,
"globalIndex": 43176501,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val tuple2 = coll1(0)\n val coll3 = tuple2._1\n val func4 = {(coll4: Coll[Byte]) => byteArrayToLong(coll4.slice(8, 16)) }\n val coll5 = tuple2._2\n val l6 = func4(coll5)\n val func7 = {(box7: Box) => box7.R4[Coll[AvlTree]].get(0) }\n val func8 = {(tuple8: (Coll[Box], Coll[Byte])) =>\n tuple8._1.filter({(box10: Box) => box10.tokens.exists({(tuple12: (Coll[Byte], Long)) => tuple12._1 == tuple8._2 }) })\n }\n val coll9 = placeholder[Coll[Byte]](1)\n val box10 = func8((INPUTS, coll9))(0)\n val avlTree11 = func7(box10)\n val coll12 = getVar[Coll[Byte]](2.toByte).get\n val coll13 = avlTree11.get(coll3, coll12).get\n val l14 = func4(coll13)\n val l15 = l6 - l14\n val func16 = {(box16: Box) => box16.tokens(1) }\n val box17 = func8((OUTPUTS, coll9))(0)\n val func18 = {(box18: Box) => box18.R5[Coll[Long]].get(1) }\n val func19 = {(coll19: Coll[Byte]) => coll19.slice(0, coll19.size - 16 / 8).indices.map({(i21: Int) =>\n val i23 = i21 * 8\n byteArrayToLong(coll19.slice(i23 + 16, i23 + 8 + 16))\n }) }\n val coll20 = Coll[Long](l14).append(func19(coll13))\n val coll21 = Coll[Long](l6).append(func19(coll5))\n val coll22 = coll20.zip(coll21)\n val func23 = {(box23: Box) => box23.R4[Coll[AvlTree]].get(1) }\n val func24 = {(box24: Box) =>\n val coll26 = box24.R5[Coll[Long]].get\n coll26.slice(5, coll26.size)\n }\n val func25 = {(box25: Box) => box25.R5[Coll[Long]].get(0) }\n val func26 = {(box26: Box) => box26.R5[Coll[Long]].get(2) }\n val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(3) }\n val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(4) }\n val func29 = {(box29: Box) => box29.R6[Coll[Coll[Long]]].get }\n val func30 = {(box30: Box) => box30.R7[Coll[(AvlTree, AvlTree)]].get }\n val func31 = {(box31: Box) => box31.R8[Coll[Long]].get }\n sigmaProp(\n allOf(\n Coll[Boolean](\n {(tuple32: (Coll[Box], Coll[Byte])) =>\n tuple32._1.exists({(box34: Box) => box34.tokens.exists({(tuple36: (Coll[Byte], Long)) => tuple36._1 == tuple32._2 }) })\n }((OUTPUTS, coll3)), (l15 == func16(box17)._2 - func16(box10)._2) && (l15 == func18(box17) - func18(box10)), coll1.size == 1, avlTree11.update(\n coll1, coll12\n ).get.digest == func7(box17).digest, coll22.slice(1, coll22.size).forall({(tuple32: (Long, Long)) =>\n val l34 = tuple32._2\n (tuple32._1 >= l34) && (l34 >= 0L)\n }), coll20(1) - coll21(1) == box10.value - box17.value, {(tuple32: (Coll[Box], Coll[Byte])) =>\n tuple32._1.filter({(box34: Box) => blake2b256(box34.propositionBytes) == tuple32._2 })\n }(\n (\n OUTPUTS, {(opt32: Option[Coll[Byte]]) => opt32.get.slice(1, 33) }(\n {(box32: Box) => box32.R4[AvlTree].get }(func8((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n )\n )(0).value >= SELF.value, allOf(\n Coll[Boolean](\n func23(box17) == func23(box10), func24(box17) == func24(box10), func25(box17) == func25(box10), func26(box17) == func26(box10), func27(\n box17\n ) == func27(box10), func28(box17) == func28(box10), func29(box17) == func29(box10), func30(box17) == func30(box10), func31(box17) == func31(box10)\n )\n ), l6 >= l14\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "b5a7f1f8ff68ac3f862b4559ea82ddb56183ed6f67e7e85508743b5950ab712d",
"mainChain": true
},
{
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"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 4,
"globalIndex": 43176502,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) =>\n tuple1._1.filter({(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == tuple1._2 }) })\n }\n val coll2 = placeholder[Coll[Byte]](1)\n val box3 = func1((OUTPUTS, coll2))(0)\n val box4 = func1((INPUTS, coll2))(0)\n val func5 = {(box5: Box) =>\n val coll7 = box5.tokens\n coll7.slice(2, coll7.size)\n }\n val func6 = {(box6: Box) => box6.R4[Coll[AvlTree]].get(1) }\n val func7 = {(box7: Box) => box7.R5[Coll[Long]].get(0) }\n val func8 = {(box8: Box) => box8.R5[Coll[Long]].get(3) }\n val func9 = {(box9: Box) =>\n val coll11 = box9.R5[Coll[Long]].get\n coll11.slice(5, coll11.size)\n }\n val func10 = {(box10: Box) => box10.R6[Coll[Coll[Long]]].get }\n val func11 = {(box11: Box) => box11.R7[Coll[(AvlTree, AvlTree)]].get }\n val func12 = {(box12: Box) => box12.R8[Coll[Long]].get }\n val coll13 = INPUTS(0).id\n val coll14 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val tuple15 = coll14(0)\n val coll16 = tuple15._2\n val l17 = {(coll17: Coll[Byte]) => byteArrayToLong(coll17.slice(8, 16)) }(coll16)\n val func18 = {(box18: Box) => box18.tokens(1) }\n val func19 = {(box19: Box) => box19.R5[Coll[Long]].get(1) }\n val func20 = {(box20: Box) => box20.R4[Coll[AvlTree]].get(0) }\n val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(2) }\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n box3.value >= box4.value, func5(box3) == func5(box4), func6(box3) == func6(box4), func7(box3) == func7(box4), func8(box3) == func8(\n box4\n ), true, func9(box3) == func9(box4), func10(box3) == func10(box4), func11(box3) == func11(box4), func12(box3) == func12(box4)\n )\n ), coll13 == tuple15._1, {(tuple22: (Coll[Box], Coll[Byte])) =>\n tuple22._1.flatMap({(box24: Box) => box24.tokens }).fold(0L, {(tuple24: (Long, (Coll[Byte], Long))) =>\n val tuple26 = tuple24._2\n tuple24._1 + if (tuple26._1 == tuple22._2) { tuple26._2 } else { 0L }\n })\n }((OUTPUTS, coll13)) == 1L, (l17 == func18(box3)._2 - func18(box4)._2) && (l17 == func19(box3) - func19(box4)), coll14.size == 1, func20(box4).insert(\n coll14, getVar[Coll[Byte]](2.toByte).get\n ).get.digest == func20(box3).digest, {(coll22: Coll[Byte]) => coll22.slice(0, coll22.size - 16 / 8).indices.map({(i24: Int) =>\n val i26 = i24 * 8\n byteArrayToLong(coll22.slice(i26 + 16, i26 + 8 + 16))\n }) }(coll16).forall({(l22: Long) => l22 == 0L }), {(tuple22: (Coll[Box], Coll[Byte])) =>\n tuple22._1.filter({(box24: Box) => blake2b256(box24.propositionBytes) == tuple22._2 })\n }(\n (\n OUTPUTS, {(opt22: Option[Coll[Byte]]) => opt22.get.slice(1, 33) }(\n {(box22: Box) => box22.R4[AvlTree].get }(func1((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n )\n )(0).value >= SELF.value, func21(box4) + 1L == func21(box3), {(coll22: Coll[Byte]) => byteArrayToLong(coll22.slice(0, 8)) }(coll16) == 0L\n )\n )\n )\n}",
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"assets": [],
"additionalRegisters": {},
"spentTransactionId": "68a815debe59167fb912dc36cc01d290a0e656db033a7a55763eccf2f8626c61",
"mainChain": true
},
{
"boxId": "79be4e7b9a8a81c31e7d41894363be3fc4c3d6c021da0ebde7a3a509cafa52f5",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 5,
"globalIndex": 43176503,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.R4[Coll[AvlTree]].get(1) }\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 = placeholder[Coll[Byte]](1)\n val box4 = func2((OUTPUTS, coll3))(0)\n val box5 = func2((INPUTS, coll3))(0)\n val func6 = {(box6: Box) => box6.R5[Coll[Long]].get(0) }\n val func7 = {(box7: Box) => box7.R5[Coll[Long]].get(3) }\n val func8 = {(box8: Box) => box8.R5[Coll[Long]].get(4) }\n val func9 = {(box9: Box) =>\n val coll11 = box9.R5[Coll[Long]].get\n coll11.slice(5, coll11.size)\n }\n val func10 = {(box10: Box) => box10.R6[Coll[Coll[Long]]].get }\n val func11 = {(box11: Box) => box11.R7[Coll[(AvlTree, AvlTree)]].get }\n val func12 = {(box12: Box) => box12.R8[Coll[Long]].get }\n val coll13 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll14 = coll13(0)\n val func15 = {(box15: Box) => box15.R4[Coll[AvlTree]].get(0) }\n val avlTree16 = func15(box5)\n val coll17 = avlTree16.get(coll14, getVar[Coll[Byte]](2.toByte).get).get\n val l18 = {(coll18: Coll[Byte]) => byteArrayToLong(coll18.slice(8, 16)) }(coll17)\n val func19 = {(box19: Box) => box19.tokens(1) }\n val func20 = {(box20: Box) => box20.R5[Coll[Long]].get(1) }\n val coll21 = {(opt21: Option[Coll[Byte]]) => opt21.get.slice(1, 33) }(\n {(box21: Box) => box21.R4[AvlTree].get }(func2((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n val box22 = {(tuple22: (Coll[Box], Coll[Byte])) => tuple22._1.filter({(box24: Box) => blake2b256(box24.propositionBytes) == tuple22._2 }) }(\n (OUTPUTS, coll21)\n )(0)\n val func23 = {(box23: Box) => box23.R5[Coll[Long]].get(2) }\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n func1(box4) == func1(box5), func6(box4) == func6(box5), func7(box4) == func7(box5), func8(box4) == func8(box5), func9(box4) == func9(box5), func10(\n box4\n ) == func10(box5), func11(box4) == func11(box5), func12(box4) == func12(box5)\n )\n ), {(tuple24: (Coll[Box], Coll[Byte])) =>\n tuple24._1.exists({(box26: Box) => box26.tokens.exists({(tuple28: (Coll[Byte], Long)) => tuple28._1 == tuple24._2 }) })\n }((INPUTS, coll14)), allOf(Coll[Boolean](l18 == func19(box5)._2 - func19(box4)._2, l18 == func20(box5) - func20(box4))), {(coll24: Coll[Byte]) =>\n coll24.slice(0, coll24.size - 16 / 8).indices.map({(i26: Int) =>\n val i28 = i26 * 8\n byteArrayToLong(coll24.slice(i28 + 16, i28 + 8 + 16))\n })\n }(coll17)(0) == box5.value - box4.value, coll13.size == 1, avlTree16.remove(coll13, getVar[Coll[Byte]](3.toByte).get).get.digest == func15(\n box4\n ).digest, allOf(Coll[Boolean](blake2b256(box22.propositionBytes) == coll21, box22.value >= SELF.value)), func23(box5) - 1L == func23(\n box4\n ), CONTEXT.preHeader.timestamp > {(coll24: Coll[Byte]) => byteArrayToLong(coll24.slice(0, 8)) }(coll17)\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "ac0908096daa584169ca94e8ef4bb5985dd078fe6c6ecf28f78ed2a15fd1fc03",
"mainChain": true
},
{
"boxId": "7bb6ecb8dbdadd621863a9076882e007007e1add175d96a0e9616f52806c9ca2",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 6,
"globalIndex": 43176504,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) =>\n tuple1._1.filter({(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == tuple1._2 }) })\n }\n val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(func1((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), Coll[Byte](\n -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\n ), Coll[Byte](\n -101.toByte, 22.toByte, -79.toByte, -128.toByte, -127.toByte, 39.toByte, 77.toByte, -62.toByte, 47.toByte, 24.toByte, -24.toByte, 89.toByte, 25.toByte, -106.toByte, -94.toByte, 102.toByte, -45.toByte, -71.toByte, 33.toByte, -73.toByte, 113.toByte, -127.toByte, 12.toByte, -54.toByte, 12.toByte, -72.toByte, -25.toByte, 18.toByte, 74.toByte, -40.toByte, 8.toByte, -66.toByte\n ), Coll[Byte](\n 65.toByte, -13.toByte, -104.toByte, -128.toByte, 101.toByte, 82.toByte, -124.toByte, 94.toByte, 82.toByte, 0.toByte, -112.toByte, 50.toByte, 16.toByte, 95.toByte, 89.toByte, -27.toByte, -53.toByte, 44.toByte, -79.toByte, 65.toByte, -34.toByte, 99.toByte, -52.toByte, 115.toByte, 123.toByte, 109.toByte, -103.toByte, 87.toByte, 83.toByte, -61.toByte, 110.toByte, -127.toByte\n ), Coll[Byte](\n 40.toByte, -58.toByte, -124.toByte, 89.toByte, 62.toByte, 17.toByte, 78.toByte, 122.toByte, 82.toByte, 44.toByte, -90.toByte, -26.toByte, -112.toByte, -104.toByte, 119.toByte, -83.toByte, 10.toByte, 121.toByte, -82.toByte, -103.toByte, -37.toByte, 109.toByte, 108.toByte, -44.toByte, 56.toByte, 25.toByte, -93.toByte, 77.toByte, 80.toByte, 91.toByte, 55.toByte, -24.toByte\n ), Coll[Byte](\n 59.toByte, 8.toByte, 57.toByte, -57.toByte, -9.toByte, 126.toByte, -4.toByte, -122.toByte, -37.toByte, -96.toByte, -92.toByte, 95.toByte, -86.toByte, -51.toByte, 100.toByte, -90.toByte, 56.toByte, -74.toByte, -114.toByte, 10.toByte, -62.toByte, 106.toByte, -88.toByte, 10.toByte, 21.toByte, -116.toByte, -114.toByte, -66.toByte, 87.toByte, -82.toByte, 21.toByte, -125.toByte\n ), Coll[Byte](\n -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\n )\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val func3 = {(box3: Box) => box3.R5[Coll[Long]].get(1) }\n val coll4 = placeholder[Coll[Byte]](1)\n val box5 = func1((OUTPUTS, coll4))(0)\n val box6 = func1((INPUTS, coll4))(0)\n val l7 = func3(box6)\n val func8 = {(box8: Box) => box8.R5[Coll[Long]].get(2) }\n val func9 = {(box9: Box) => box9.R5[Coll[Long]].get(3) }\n val func10 = {(box10: Box) => box10.R5[Coll[Long]].get(4) }\n val func11 = {(box11: Box) => box11.R4[Coll[AvlTree]].get(0) }\n val coll12 = func11(box6).digest\n val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n val coll14 = Coll[Byte](\n 78.toByte, -58.toByte, 31.toByte, 72.toByte, 91.toByte, -104.toByte, -21.toByte, -121.toByte, 21.toByte, 63.toByte, 124.toByte, 87.toByte, -37.toByte, 79.toByte, 94.toByte, -51.toByte, 117.toByte, 85.toByte, 111.toByte, -35.toByte, -68.toByte, 64.toByte, 59.toByte, 65.toByte, -84.toByte, -8.toByte, 68.toByte, 31.toByte, -34.toByte, -114.toByte, 22.toByte, 9.toByte, 0.toByte\n )\n val func15 = {(tuple15: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple17 = tuple15._2\n val l18 = tuple17._1\n val tuple19 = tuple17._2\n val l20 = tuple19._1\n val l21 = tuple19._2\n tuple15._1.map({(coll22: Coll[Byte]) => if (coll22.size == 9) {(\n val l24 = byteArrayToLong(coll22.slice(1, 9))\n if (l24 < l18) { l18 } else { if (l24 > l20) { l20 } else { l24 } }\n )} else { l21 } }).getOrElse(l21)\n }\n val l16 = func15((coll2(1), (0L, (999999999999999L, 0L))))\n val func17 = {(box17: Box) => box17.R6[Coll[Coll[Long]]].get(0) }\n val coll18 = func17(box5)\n val i19 = coll18.size\n val i20 = i19 - 1\n val func21 = {(box21: Box) => box21.R6[Coll[Coll[Long]]].get(1) }\n val coll22 = func21(box5)\n val func23 = {(box23: Box) => box23.R6[Coll[Coll[Long]]].get(2) }\n val coll24 = func23(box5)\n val func25 = {(box25: Box) => box25.R6[Coll[Coll[Long]]].get(3) }\n val coll26 = func25(box5)\n val opt27 = coll2(4)\n val b28 = max(0.toByte, min(100.toByte, if (opt27.isDefined) { opt27.get(1) } else { 0.toByte }))\n val func29 = {(box29: Box) => box29.R6[Coll[Coll[Long]]].get(4) }\n val coll30 = func29(box5)\n val opt31 = coll2(5)\n val func32 = {(box32: Box) => box32.R7[Coll[(AvlTree, AvlTree)]].get }\n val coll33 = func32(box5)\n val tuple34 = coll33(i20)\n val coll35 = {(box35: Box) => box35.R8[Coll[Long]].get }(box5)\n val func36 = {(box36: Box) =>\n val coll38 = box36.R5[Coll[Long]].get\n coll38.slice(5, coll38.size)\n }\n val coll37 = func36(box6)\n val i38 = func15((coll2(2), (1L, (10L, 1L)))).toInt\n val coll39 = func32(box6)\n val i40 = min(coll39.size, i38)\n val i41 = i40 - 1\n val coll42 = func25(box6)\n val coll43 = func29(box6)\n val coll44 = func17(box6)\n val coll45 = func36(box5)\n val func46 = {(box46: Box) => box46.R5[Coll[Long]].get(0) }\n val l47 = func46(box6)\n sigmaProp(\n allOf(\n Coll[Boolean](\n {(tuple48: (Coll[Box], Coll[Byte])) => tuple48._1.filter({(box50: Box) => blake2b256(box50.propositionBytes) == tuple48._2 }) }(\n (OUTPUTS, {(opt48: Option[Coll[Byte]]) => opt48.get.slice(1, 33) }(coll2(0)))\n )(0).value >= SELF.value, allOf(\n Coll[Boolean](\n func3(box5) == l7, func8(box5) == func8(box6), func9(box5) == 0L, func10(box5) == 0L, func11(box5).digest == coll12, func13(box5).digest == coll14\n )\n ), box6.tokens.zip(box5.tokens).forall({(tuple48: ((Coll[Byte], Long), (Coll[Byte], Long))) =>\n val tuple50 = tuple48._1\n val coll51 = tuple50._1\n val tuple52 = tuple48._2\n if (coll51 == {(opt53: Option[Coll[Byte]]) => opt53.get.slice(6, 38) }(coll2(6))) { (tuple52._1 == coll51) && (tuple50._2 + l16 == tuple52._2) } else { tuple52 == tuple50 }\n }), allOf(\n Coll[Boolean](\n coll18(i20) == l7, coll22(i20) == func9(box6), coll24(i20) == func10(box6), coll26(i20) == b28.toLong, coll30(i20) == max(\n 0.toByte, min(100.toByte - b28, if (opt31.isDefined) { opt31.get(1) } else { 0.toByte })\n ).toLong, tuple34._1.digest == coll12, tuple34._2.digest == func13(box6).digest, coll35(0) == l16 + coll37(0)\n )\n ), if (i38 > i40) { coll33.slice(0, i38 - i40 - 1).indices.forall({(i48: Int) =>\n val i50 = i40 + i48\n allOf(Coll[Boolean](coll33(i50) == coll39(i41), coll22(i50) == 0L, coll24(i50) == 0L, coll26(i50) == coll42(i41), coll30(i50) == coll43(i41), coll18(i50) == coll44(i41)))\n }) } else { true }, allOf(\n Coll[Boolean](\n coll39(0)._1.digest == coll14, coll33.slice(0, i41) == coll39.slice(1, i40), coll22.slice(0, i41) == func21(box6).slice(1, i40), coll24.slice(\n 0, i41\n ) == func23(box6).slice(1, i40), coll26.slice(0, i41) == coll42.slice(1, i40), coll30.slice(0, i41) == coll43.slice(1, i40), coll18.slice(\n 0, i41\n ) == coll44.slice(1, i40)\n )\n ), coll35.slice(1, coll37.size).indices.forall({(i48: Int) =>\n val i50 = i48 + 1\n coll35(i50) == coll37(i50)\n }), allOf(\n Coll[Boolean](coll33.size == i38, i19 == i38, coll26.size == i38, coll30.size == i38, coll22.size == i38, coll24.size == i38)\n ), coll45.indices.forall({(i48: Int) => coll45(i48) == coll35(i48) }), func46(box5) == l47 + func15(\n (coll2(3), (3600000L, (999999999999999L, 86400000L)))\n ), l47 <= CONTEXT.preHeader.timestamp\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "41140f6cd527fa03338ec4d88673f24a5ef80f59f70a2a82a2ec6645d5043479",
"mainChain": true
},
{
"boxId": "acf456dfe3d1c71272d15268e92e49378c5ba976e8541c4756bef4ea90e34473",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 7,
"globalIndex": 43176505,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "10020e2000f8f5bbe544e16c5d51098f361ac5fd975beee0abca8ac76f0d7a388c32ef260e2000acf1fefff7181e8c4f9476112dd4400212a2c5856d10384f998ce86a8a4c78d834d601e4e3010c3c0e0ed602ad7201d901023c0e0e8c720201d603db0c0e7202d604d9010463b2e4c67204040c64040000d605d901053c0c630eb58c720501d9010763aedb63087207d901094d0e938c7209018c720502d6067301d607b2da7205018602a47206040000d608da7204017207d609dc640b7208027202e4e3020ed60ad9010a0e7cb4720a04100420d60bd9010b0eaddb0c0eb4720b04009d99b1720b04200410d9010d04d801d60f9c720d04107cb4720b9a720f04209a9a720f04100420d60cd9010c63d801d60ee4c6720c0511b4720e040ab1720ed60dda720c017207d60ead7209d9010e3295e6720ed801d610e4720eb3830105da720a017210da720b017210ad720dd90110050501d60fd9010f63e4c6720f070c3c6464d610da720f017207d611b27210040000d6128c721101d613addc640b7212027202e4e3030ed9011332da720a01e47213d614d9011463b2e4c67214061d040000d615b2dad9011563b2e4c67215061d040200017207040000d6169591721505007db2dad9011663b2e4c67216061d040600017207040000020200d617b2dad9011763b2e4c67217061d040400017207040000d6189591721705007db2dad9011863b2e4c67218061d040800017207040000020200d6199a72167218d61a95917e7219040400a2990264721902000264d61b060100d61c060100d61d9a7219721ad61e8c721102d61faddc640b721e027202e4e3050ed9011f3295e6721fd801d621e4721f86027cb47221040004107cb4722104100420860205000500d620d9012063e4c672200811d621da7220017207d622ad7201d901223c0e0ed801d6248c722202b3830105da720a017224da720b017224d623d901230e7cb4722304000410d624ad7209d901243295e67224da722301e472240501d625ad7201d901253c0e0eda7223018c722502d6268602adda7220017207d90126050601000101d627d9012763b2e4c672270511040200d628addb0c0e7221d9012804b0ad7203d9012a04d801d62cb2720e722a009592b2722c0400000500d801d62dadda7220017207d9012d05d801d62f7e722d069d9a9a9c9d9c7eb27213722a0006722f7eb2da7214017207040000067e721a0695917e72160404009c9d9c7e8cb2721f722a000106722f7e7215067e721606721b95917e72180404009c9d9c7e8cb2721f722a000206722f7e7217067e721806721c7e721d068602722ded93addc0c1d722c01722dd9012e41069a7e8c722e01068c722e02adb27222722a00d9012e057e722e0693b27224722a00b27225722a007226060100d9012a4249129a8c722a01b28c8c722a0201722800d629b2da7205018602a57206040000d62ada720f017229d62bb2722a040000d62cdb64018c722b01d62ddad9012d32b4e4722d0402044201b2dc640bdad9012d63e4c6722d046401b2da7205018602db6501fe73000400000283010e8320020289022e026f024702a1020d025c029002b8027a02d402860233025502ce02ad020002c302e202980232021702ee021502530232025302cd029a0260022502c2e4e3000e040000d62eb2dad9012e3c0c630eb58c722e01d901306393cbc272308c722e02018602a5722d040000d62fd9012f63b2e4c6722f040c64040200d630d9013063b2e4c672300511040000d631d9013163b2e4c672310511040400d632d9013263b2e4c672320511040600d633d9013363b2e4c672330511040800d634d9013463e4c67234061dd19683080196ad7203d9013504d801d637b2720e7235008c9592b272370400000500d801d638ad7221d9013805d801d63a7e7238069d9a9a9c9d9c7eb2721372350006723a7eb2da7214017207040000067e721a0695917e72160404009c9d9c7e8cb2721f7235000106723a7e7215067e721606721b95917e72180404009c9d9c7e8cb2721f7235000206723a7e7217067e721806721c7e721d0686027238ed93addc0c1d7237017238d9013941069a7e8c723901068c723902adb27222723500d90139057e72390693b27224723500b27225723500722602939a7eda722701720706b272280400007eda72270172290693db6401e4dc640e7212027202e4e3040e722c93db6401e4dc640d720802b57201d901353c0e0e91da720a018c7235020500e4e3060edb6401da72040172299683020193cbc2722e722d92c1722ec1a796830b0193c17229c1720793db63087229db6308720793db6401da722f017229db6401da722f017207938c722b02721e93b4722a0402b1722ab472100402b1721093da7230017229da723001720793da7231017229da723101720793da7232017229da723201720793da7233017229da723301720793da7234017229da723401720793da72200172297221ec92b17201041493722c832102024e02c6021f0248025b029802eb02870215023f027c025702db024f025e02cd02750255026f02dd02bc0240023b024102ac02f80244021f02de028e021602090200afdb0c0e720dd9013504937eb2da720c01722972350006997eb2720d72350006b27228723500",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll2 = coll1.map({(tuple2: (Coll[Byte], Coll[Byte])) => tuple2._1 })\n val coll3 = coll2.indices\n val func4 = {(box4: Box) => box4.R4[Coll[AvlTree]].get(0) }\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 coll6 = placeholder[Coll[Byte]](1)\n val box7 = func5((INPUTS, coll6))(0)\n val avlTree8 = func4(box7)\n val coll9 = avlTree8.getMany(coll2, getVar[Coll[Byte]](2.toByte).get)\n val func10 = {(coll10: Coll[Byte]) => byteArrayToLong(coll10.slice(8, 16)) }\n val func11 = {(coll11: Coll[Byte]) => coll11.slice(0, coll11.size - 16 / 8).indices.map({(i13: Int) =>\n val i15 = i13 * 8\n byteArrayToLong(coll11.slice(i15 + 16, i15 + 8 + 16))\n }) }\n val func12 = {(box12: Box) =>\n val coll14 = box12.R5[Coll[Long]].get\n coll14.slice(5, coll14.size)\n }\n val coll13 = func12(box7)\n val coll14 = coll9.map({(opt14: Option[Coll[Byte]]) => if (opt14.isDefined) {(\n val coll16 = opt14.get\n Coll[Long](func10(coll16)).append(func11(coll16))\n )} else { coll13.map({(l16: Long) => -1L }) } })\n val func15 = {(box15: Box) => box15.R7[Coll[(AvlTree, AvlTree)]].get }\n val coll16 = func15(box7)\n val tuple17 = coll16(0)\n val avlTree18 = tuple17._1\n val coll19 = avlTree18.getMany(coll2, getVar[Coll[Byte]](3.toByte).get).map({(opt19: Option[Coll[Byte]]) => func10(opt19.get) })\n val func20 = {(box20: Box) => box20.R6[Coll[Coll[Long]]].get(0) }\n val l21 = {(box21: Box) => box21.R6[Coll[Coll[Long]]].get(1) }(box7)(0)\n val b22 = if (l21 > 0L) { {(box22: Box) => box22.R6[Coll[Coll[Long]]].get(3) }(box7)(0).toByte } else { 0.toByte }\n val l23 = {(box23: Box) => box23.R6[Coll[Coll[Long]]].get(2) }(box7)(0)\n val b24 = if (l23 > 0L) { {(box24: Box) => box24.R6[Coll[Coll[Long]]].get(4) }(box7)(0).toByte } else { 0.toByte }\n val b25 = b22 + b24\n val b26 = if (b25.toInt > 0) { max(100.toByte - b25, 0.toByte) } else { 100.toByte }\n val bi27 = 0.toBigInt\n val bi28 = 0.toBigInt\n val b29 = b25 + b26\n val avlTree30 = tuple17._2\n val coll31 = avlTree30.getMany(coll2, getVar[Coll[Byte]](5.toByte).get).map({(opt31: Option[Coll[Byte]]) => if (opt31.isDefined) {(\n val coll33 = opt31.get\n (byteArrayToLong(coll33.slice(0, 8)), byteArrayToLong(coll33.slice(8, 16)))\n )} else { (0L, 0L) } })\n val func32 = {(box32: Box) => box32.R8[Coll[Long]].get }\n val coll33 = func32(box7)\n val coll34 = coll1.map({(tuple34: (Coll[Byte], Coll[Byte])) =>\n val coll36 = tuple34._2\n Coll[Long](func10(coll36)).append(func11(coll36))\n })\n val func35 = {(coll35: Coll[Byte]) => byteArrayToLong(coll35.slice(0, 8)) }\n val coll36 = coll9.map({(opt36: Option[Coll[Byte]]) => if (opt36.isDefined) { func35(opt36.get) } else { -1L } })\n val coll37 = coll1.map({(tuple37: (Coll[Byte], Coll[Byte])) => func35(tuple37._2) })\n val tuple38 = (func32(box7).map({(l38: Long) => 0.toBigInt }), true)\n val func39 = {(box39: Box) => box39.R5[Coll[Long]].get(1) }\n val coll40 = coll33.indices.map({(i40: Int) => coll3.map({(i42: Int) =>\n val coll44 = coll14(i42)\n if (coll44(0) >= 0L) {(\n val coll45 = func32(box7).map({(l45: Long) =>\n val bi47 = l45.toBigInt\n coll19(i42).toBigInt * bi47 / func20(box7)(0).toBigInt * b26.toBigInt + if (b22.toInt > 0) { coll31(i42)._1.toBigInt * bi47 / l21.toBigInt * b22.toBigInt } else { bi27 } + if (b24.toInt > 0) { coll31(i42)._2.toBigInt * bi47 / l23.toBigInt * b24.toBigInt } else { bi28 } / b29.toBigInt\n })\n (coll45, (coll44.zip(coll45).map({(tuple46: (Long, BigInt)) => tuple46._1.toBigInt + tuple46._2 }) == coll34(i42).map({(l46: Long) => l46.toBigInt })) && (coll36(i42) == coll37(i42)))\n )} else { tuple38 }\n }).fold(0.toBigInt, {(tuple42: (BigInt, (Coll[BigInt], Boolean))) => tuple42._1 + tuple42._2._1(i40) }) })\n val box41 = func5((OUTPUTS, coll6))(0)\n val coll42 = func15(box41)\n val tuple43 = coll42(0)\n val coll44 = tuple43._1.digest\n val coll45 = {(opt45: Option[Coll[Byte]]) => opt45.get.slice(1, 33) }(\n {(box45: Box) => box45.R4[AvlTree].get }(func5((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n val box46 = {(tuple46: (Coll[Box], Coll[Byte])) => tuple46._1.filter({(box48: Box) => blake2b256(box48.propositionBytes) == tuple46._2 }) }(\n (OUTPUTS, coll45)\n )(0)\n val func47 = {(box47: Box) => box47.R4[Coll[AvlTree]].get(1) }\n val func48 = {(box48: Box) => box48.R5[Coll[Long]].get(0) }\n val func49 = {(box49: Box) => box49.R5[Coll[Long]].get(2) }\n val func50 = {(box50: Box) => box50.R5[Coll[Long]].get(3) }\n val func51 = {(box51: Box) => box51.R5[Coll[Long]].get(4) }\n val func52 = {(box52: Box) => box52.R6[Coll[Coll[Long]]].get }\n sigmaProp(allOf(Coll[Boolean](allOf(coll3.map({(i53: Int) =>\n val coll55 = coll14(i53)\n if (coll55(0) >= 0L) {(\n val coll56 = coll33.map({(l56: Long) =>\n val bi58 = l56.toBigInt\n coll19(i53).toBigInt * bi58 / func20(box7)(0).toBigInt * b26.toBigInt + if (b22.toInt > 0) { coll31(i53)._1.toBigInt * bi58 / l21.toBigInt * b22.toBigInt } else { bi27 } + if (b24.toInt > 0) { coll31(i53)._2.toBigInt * bi58 / l23.toBigInt * b24.toBigInt } else { bi28 } / b29.toBigInt\n })\n (coll56, (coll55.zip(coll56).map({(tuple57: (Long, BigInt)) => tuple57._1.toBigInt + tuple57._2 }) == coll34(i53).map({(l57: Long) => l57.toBigInt })) && (coll36(i53) == coll37(i53)))\n )} else { tuple38 }._2\n })), func39(box7).toBigInt + coll40(0) == func39(box41).toBigInt, avlTree18.remove(coll2, getVar[Coll[Byte]](4.toByte).get).get.digest == coll44, avlTree8.update(coll1.filter({(tuple53: (Coll[Byte], Coll[Byte])) => func10(tuple53._2) > 0L }), getVar[Coll[Byte]](6.toByte).get).get.digest == func4(box41).digest, allOf(Coll[Boolean](blake2b256(box46.propositionBytes) == coll45, box46.value >= SELF.value)), allOf(Coll[Boolean](box41.value == box7.value, box41.tokens == box7.tokens, func47(box41).digest == func47(box7).digest, tuple43._2 == avlTree30, coll42.slice(1, coll42.size) == coll16.slice(1, coll16.size), func48(box41) == func48(box7), func49(box41) == func49(box7), func50(box41) == func50(box7), func51(box41) == func51(box7), func52(box41) == func52(box7), func32(box41) == coll33)), (coll1.size >= 10) || (coll44 == Coll[Byte](78.toByte, -58.toByte, 31.toByte, 72.toByte, 91.toByte, -104.toByte, -21.toByte, -121.toByte, 21.toByte, 63.toByte, 124.toByte, 87.toByte, -37.toByte, 79.toByte, 94.toByte, -51.toByte, 117.toByte, 85.toByte, 111.toByte, -35.toByte, -68.toByte, 64.toByte, 59.toByte, 65.toByte, -84.toByte, -8.toByte, 68.toByte, 31.toByte, -34.toByte, -114.toByte, 22.toByte, 9.toByte, 0.toByte)), coll13.indices.forall({(i53: Int) => func12(box41)(i53).toBigInt == coll13(i53).toBigInt - coll40(i53) }))))\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "c1ffe46584729d226e7ebec516d75861fd2c661a3d9515be854c2e3edd8bcb12",
"mainChain": true
},
{
"boxId": "6314cc36fcea35bb5f3111592550762436697c601e19fe5bd63da2d16666ec78",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 8,
"globalIndex": 43176506,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "10020e2000f8f5bbe544e16c5d51098f361ac5fd975beee0abca8ac76f0d7a388c32ef260e2000acf1fefff7181e8c4f9476112dd4400212a2c5856d10384f998ce86a8a4c78d823d601e4e3001ad602dc640bdad9010263e4c67202046401b2db6501fe0400000283020e83200202090282020f02cb0288027102fb0245020c023e020602b702cb025e022702b002450250028702a302660262021a029d02de0275028202a002190211021e023e832002023d02aa02660280028e026902c2025a02e9023202dd02660261021c025f020b023c02ba02ca02d102120252020302e8027d028d02c402910286021c027102e6b27201040000d603b27201041200d604d901043c0c630eb58c720401d9010663aedb63087206d901084d0e938c7208018c720402d6057301d606b2da7204018602a57205040000d607b2da7204018602a47205040000d608d9010863b2e4c67208040c64040000d609da7208017207d60ab2da7204018602a4dad9010a32b4e4720a040c044c01b27202040200040000d60be4dc640a7209027203b27201040400d60cb37aa2dad9010c63b2e4c6720c051104000001720adad9010c0e7cb4720c0400041001720bb4720b0410b1720bd60dd9010d63b2e4c6720d040c64040200d60eda720d017207d60fdc640a720e027203b27201040800d610e6720fd611dc640adad9011163e4c67211066401720a027203b27201040200d612e67211d6139572107cb4e4720f040004100500d61495721272139a72130502d6159572107cb4e4720f041004200500d616b27201041000d617b0adb4db0c0e721604009db172160410d90117047cb472169c721704109c9a7217040204100500d90117599a8c7217018c721702d618957212d801d618e47211a29a997215b0adb4db0c0e721804009db172180410d90119047cb472189c721904109c9a7219040204100500d90119599a8c7219018c721902721705009a72157217d619b37a72147a7218d61ab27201040a00d61bd9011b63b2e4c6721b0511040000d61cd9011c63b2e4c6721c0511040200d61dd9011d63b2e4c6721d0511040400d61ed9011e63b2e4c6721e0511040600d61fd9011f63b2e4c6721f0511040800d620d9012063d801d622e4c672200511b47222040ab17222d621d9012163e4c67221061dd622d9012263e4c67222070c3c6464d623d9012363e4c672230811d19683050192c1b2dad901243c0c630eb58c722401d901266393cbc272268c722402018602a5dad9012432b4e472240402044201b27202040000040000c1a7dad901243c0c630eae8c722401d9012663aedb63087226d901284d0e938c7228018c722402018602a5720396830d0193c17206c1720793db63087206db6308720793db6401da7208017206db6401e4dc640d72090283013c0e0e86027203720cb2720104060093db6401da720d017206db6401957210e4dc640d720e0283013c0e0e860272037219721ae4dc640c720e0283013c0e0e860272037219721a93da721b017206da721b01720793da721c017206da721c01720793da721d017206da721d01720793da721e017206999ada721e0172077214721393da721f017206999ada721f0172077218721593da7220017206da722001720793da7221017206da722101720793da7222017206da722201720793da7223017206da722301720793b27201040c00720c93b27201040e007219",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"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}",
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"assets": [],
"additionalRegisters": {},
"spentTransactionId": "b615ca8e1ad0fe7c5cf05f399cd9711a5367695a5b784be0af42fd112d8f36c8",
"mainChain": true
},
{
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"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 9,
"globalIndex": 43176507,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)\n1: Coll(0,-84,-15,-2,-1,-9,24,30,-116,79,-108,118,17,45,-44,64,2,18,-94,-59,-123,109,16,56,79,-103,-116,-24,106,-118,76,120)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.R4[Coll[AvlTree]].get(0) }\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 = placeholder[Coll[Byte]](1)\n val box4 = func2((OUTPUTS, coll3))(0)\n val box5 = func2((INPUTS, coll3))(0)\n val func6 = {(box6: Box) => box6.R4[Coll[AvlTree]].get(1) }\n val func7 = {(box7: Box) => box7.R5[Coll[Long]].get(0) }\n val func8 = {(box8: Box) => box8.R5[Coll[Long]].get(1) }\n val func9 = {(box9: Box) => box9.R5[Coll[Long]].get(2) }\n val func10 = {(box10: Box) => box10.R5[Coll[Long]].get(3) }\n val func11 = {(box11: Box) => box11.R5[Coll[Long]].get(4) }\n val func12 = {(box12: Box) => box12.R6[Coll[Coll[Long]]].get }\n val func13 = {(box13: Box) => box13.R7[Coll[(AvlTree, AvlTree)]].get }\n val func14 = {(box14: Box) => box14.R8[Coll[Long]].get }\n val l15 = box4.value - box5.value\n val func16 = {(box16: Box) =>\n val coll18 = box16.R5[Coll[Long]].get\n coll18.slice(5, coll18.size)\n }\n val func17 = {(box17: Box) => box17.tokens(1) }\n val l18 = func17(box4)._2 - func17(box5)._2\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n func1(box4) == func1(box5), func6(box4) == func6(box5), func7(box4) == func7(box5), func8(box4) == func8(box5), func9(box4) == func9(box5), func10(\n box4\n ) == func10(box5), func11(box4) == func11(box5), func12(box4) == func12(box5), func13(box4) == func13(box5), func14(box4) == func14(box5)\n )\n ), (l15 >= 0L) && (func16(box4)(1) - func16(box5)(1) == l15), (l18 >= 0L) && (\n func16(box4)(0) - func16(box5)(0) == l18\n ), box4.tokens.size >= box5.tokens.size, {(tuple19: (Coll[Box], Coll[Byte])) =>\n tuple19._1.filter({(box21: Box) => blake2b256(box21.propositionBytes) == tuple19._2 })\n }(\n (\n OUTPUTS, {(opt19: Option[Coll[Byte]]) => opt19.get.slice(1, 33) }(\n {(box19: Box) => box19.R4[AvlTree].get }(func2((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n )\n )(0).value >= SELF.value\n )\n )\n )\n}",
"address": "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",
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"mainChain": true
},
{
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"value": 1000000000,
"index": 10,
"globalIndex": 43176508,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(0,-8,-11,-69,-27,68,-31,108,93,81,9,-113,54,26,-59,-3,-105,91,-18,-32,-85,-54,-118,-57,111,13,122,56,-116,50,-17,38)",
"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": "00acf1fefff7181e8c4f9476112dd4400212a2c5856d10384f998ce86a8a4c78",
"index": 0,
"amount": 1,
"name": "Paideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 1,
"amount": 1,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "110780a4e6cbcf64000000000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1728669600000,0,0,0,0,0,0]"
},
"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": "0c64024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "68a815debe59167fb912dc36cc01d290a0e656db033a7a55763eccf2f8626c61",
"mainChain": true
},
{
"boxId": "e7be3adc60dcc8629d45708e3762890f0767438ba6c20980a2e6adc2ff4f174d",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 1000000,
"index": 11,
"globalIndex": 43176509,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"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": "f4860a90da6718ad3291bd50fbf8f148c919d8d1ba405e2fb22c042f247fc542",
"mainChain": true
},
{
"boxId": "397bbdf93e8bcc0621a0fb168dd2831159fff69e17a04ea1b06d2a4b4828e590",
"transactionId": "9da3e650f6a12ea1774f1426ff319278a3fa248f7d03c095422c3cfb9fa99a0f",
"blockId": "ad6d695020a4016837ca6edc556a7e514789803c100727fa99527bab90629d17",
"value": 9869593686,
"index": 12,
"globalIndex": 43176510,
"creationHeight": 1371169,
"settlementHeight": 1371174,
"ergoTree": "0008cd02e4cb952261186ec0fd2dc4c2baa8dbfd9c8f6012c5efa9f702f9450a58fe221e",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(e4cb95,7c781d,...)))}",
"address": "9gFpnLUGwRyohhoh5CXQS8eNdranNyNVGreCmc4xFYHPg5JUGWL",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 477727928647,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "7b976757ded023ccdffc1c6958376727fc392e60ed5627fb4e405177a8a090c1",
"index": 1,
"amount": 1,
"name": "Paideia Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "59ee24951ce668f0ed32bdb2e2e5731b6c36128748a3b23c28407c5f8ccbf0f6",
"index": 2,
"amount": 4,
"name": "WALRUS",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 3,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "045d2f3ae2f7c17c83bd6a56d9ea64209802a62598ee138ed5289ea947393eee",
"index": 4,
"amount": 9997,
"name": "RosenGuard",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00de06c61282578684b377ffd6314c38ce596f2c054107fe2314810677859269",
"index": 5,
"amount": 98698999999997,
"name": "MyFirstDAOToken",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "24b33d72bc82d430fd68b20dc22af598be6994189a96d1ee1eef78fd93b5f763",
"index": 6,
"amount": 1,
"name": "Paideia Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4679238680dadf89f6670c1d83563e87e16616407845ce7bdf5b9e3aee1ae8b8",
"index": 7,
"amount": 1,
"name": "Sigmanauts Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "94073554b6fed07682cc819527a0188ab913698233fedd1bb908368e275a24b1",
"index": 8,
"amount": 1,
"name": "RosenGuards Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "669438571de1006db69e406bab15881b8c85f5b8a231b54c12db1923654b8220",
"index": 9,
"amount": 1,
"name": "MyFirstDAO Stake Key",
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}
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}
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}