Transaction
ID: 86fd53b146...eecb
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
63.06 ERG
Outputs (86)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
60.35 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
162.12
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
109.14
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
103.42
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
166.46
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,354.22
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
172.56
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
251.36
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
162.44
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
96.93
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
348.62
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
97.16
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
186.16
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
337.73
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
219.30
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
308.99
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
377.98
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
303.89
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
429.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
189.24
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
313.55
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
193.42
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
133.21
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
286.51
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
225.25
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
312.16
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
194.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
413.13
Spent
Address:
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Settlement height:
Value:
0.01 ERG
Tokens:
309.14
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
288.36
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
264.65
Spent
Address:
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Settlement height:
Value:
0.01 ERG
Tokens:
222.85
Spent
Address:
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Settlement height:
Value:
0.01 ERG
Tokens:
207.41
Spent
Address:
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Settlement height:
Value:
0.01 ERG
Tokens:
266.12
Spent
Address:
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Settlement height:
Value:
0.01 ERG
Tokens:
138.11
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
181.13
Spent
Address:
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Settlement height:
Value:
0.01 ERG
Tokens:
293.00
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
273.53
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
357.11
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
208.80
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
282.41
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
307.60
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
209.95
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
197.90
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
281.64
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
394.82
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
117.10
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
403.31
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
192.09
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
224.33
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
96.23
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
226.26
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
315.40
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
242.86
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
406.17
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
181.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
370.72
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
275.21
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,130.11
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
224.79
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
153.56
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
97.48
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
106.60
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
391.89
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
309.85
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
112.31
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
317.72
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
177.74
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
192.65
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
197.98
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
143.52
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
340.05
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
225.55
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
104.20
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
211.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
188.70
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
229.26
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
224.57
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
106.60
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
30.50
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
555.82
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
20.16
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
24.56
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.743333333 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.15 ERG
Tokens:
0
Transaction Details
Confirmations: 980,881
Total coins transferred: 63.07 ERG
Fees: 0.743333333 ERG
Fees per byte: 0.000008287 ERG
Raw Transaction Data
{
"id": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"inclusionHeight": 776515,
"timestamp": 1655756056602,
"index": 2,
"globalIndex": 3403013,
"numConfirmations": 980881,
"inputs": [
{
"boxId": "d9dbbbeffd723e61d7b5832481e1adcb0306e58e5cac796b1e229be9b73e22d4",
"value": 1000000,
"index": 0,
"spendingProof": "c5a41f22d5c792a0a482dd0421e8fe65dc1b6e648dcd90efb4b5f430acf815972dfb79e9102ef96b198744d5331f967341236b91a99acfc2",
"outputBlockId": "e6ff61e3e4e60ec2cea928af1f743353fb535a732f4cd14201954d43db132863",
"outputTransactionId": "bf7179cc3d6d9997ab480763b5cfe9954134fb324e4eac079818b2cea4bf37ae",
"outputIndex": 0,
"outputGlobalIndex": 18146253,
"outputCreatedAt": 776314,
"outputSettledAt": 776316,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,44,61,78,-54,-96,-113,-73,57,47,-16,65,-18,46,106,-9,95,74,85,-120,16,-89,75,40,96,5,73,-43,57,40,16,-24)\n2: 2\n3: 0\n4: 1\n5: 100\n6: 2\n7: -2\n8: 1\n9: Coll(-60,30,-111,54,-57,63,-78,-18,56,-102,-88,68,14,-61,-38,66,28,-22,61,41,88,-114,-117,-113,36,-51,-80,-66,89,32,-40,25)\n10: 100000\n11: 10000000\n12: 100000\n13: 100000\n14: 1\n15: 10000\n16: 1000\n17: 100000\n18: 100000\n19: 100000\n20: Coll(125,46,40,67,16,99,-53,-79,-23,-31,68,104,-6,-52,71,-71,-124,-39,98,83,44,25,-80,-79,79,116,-48,-50,-98,-44,89,-66)\n21: 0\n22: 0\n23: 0\n24: 1\n25: 3000\n26: 0\n27: 0\n28: 0\n29: 10000000\n30: SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))\n31: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val coll2 = box1.tokens\n val coll3 = placeholder[Coll[Byte]](1)\n val tuple4 = coll2(placeholder[Int](2))\n val box5 = OUTPUTS(placeholder[Int](3))\n val coll6 = box5.tokens\n val coll7 = SELF.tokens\n val tuple8 = coll6(placeholder[Int](4))\n val func9 = {(tuple9: (Long, Long)) =>\n val l11 = tuple9._2\n val l12 = tuple9._1 - l11 * placeholder[Long](5) / l11\n (l12 < placeholder[Long](6)) && (l12 > placeholder[Long](7))\n }\n val l10 = INPUTS(placeholder[Int](8)).value\n val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](9) })\n val l12 = l10 - l10 * SELF.R5[Long].get / placeholder[Long](10) - coll11.size.toLong * placeholder[Long](11)\n val l13 = l12 * box1.R4[Int].get.toLong\n val l14 = box1.value\n val l15 = tuple4._2 / placeholder[Long](12) * l13 / placeholder[Long](13) / l14 + l14 * placeholder[Int](14).toLong / placeholder[Long](15) * placeholder[\n Long\n ](16) + l13 / placeholder[Long](17) * placeholder[Long](18)\n val l16 = SELF.R4[Long].get\n val l17 = l15 + l15 * l16 / placeholder[Long](19)\n val l18 = box5.R5[Long].get\n sigmaProp(\n (\n (\n allOf(Coll[Boolean](placeholder[Coll[Byte]](20) == coll2(placeholder[Int](21))._1, coll3 == tuple4._1)) && allOf(\n Coll[Boolean](\n box5.propositionBytes == SELF.propositionBytes, coll6(placeholder[Int](22))._1 == coll7(placeholder[Int](23))._1, tuple8._1 == coll3, func9(\n (tuple8._2, coll7(placeholder[Int](24))._2 - l17)\n ), box5.value == SELF.value, box5.R4[Long].get == l16, l18 <= placeholder[Long](25), l18 >= placeholder[Long](26)\n )\n )\n ) && allOf(\n Coll[Boolean](\n func9((coll11.fold(placeholder[Long](27), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.tokens(placeholder[Int](28))._2 }), l17)), coll11.forall(\n {(box19: Box) => box19.value == placeholder[Long](29) }\n )\n )\n )\n ) && OUTPUTS.exists({(box19: Box) => func9((box19.value, l12)) && (box19.propositionBytes == placeholder[SigmaProp](30).propBytes) })\n ) && placeholder[SigmaProp](31)\n}",
"address": "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",
"assets": [
{
"tokenId": "01e0ae6997711e9fa0422287a82a8815f64f805c2735aec49fe2bb90ef5fbc78",
"index": 0,
"amount": 1,
"name": "NETA Emission Box NFT",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 1,
"amount": 8320211280000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "05e0d702",
"sigmaType": "SLong",
"renderedValue": "22000"
},
"R5": {
"serializedValue": "05f02e",
"sigmaType": "SLong",
"renderedValue": "3000"
}
}
},
{
"boxId": "c74179a4fc224a6dc0605fe67f08c5883d39723ee0d7e3aee5d15c888877a85d",
"value": 63064400000,
"index": 1,
"spendingProof": "a6cd01491c034fcb6ef391144df473f7ab533f94aee0de6d36105db657f95254cb38281419e01cdc8039cf10c47943eed4108d7121aaa0b9",
"outputBlockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"outputTransactionId": "2fc0e5d6a516f5943366c5b3fa7916bb5d1330b39b20402138e33d29ef7deeb8",
"outputIndex": 0,
"outputGlobalIndex": 18165417,
"outputCreatedAt": 776512,
"outputSettledAt": 776515,
"ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
"address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "d93fec3fcf4dc0ca78152dc65ba144fd2abbd8b74b733a1dbd4df95947de857c",
"value": 39528805708771,
"index": 0,
"outputBlockId": "ea6bd8cb56c7fb1ce11fdc64850f66da166eb5c4140bfe52d2d0e44d08d001c6",
"outputTransactionId": "4dcbd5a8a096702e3d57daeb79ebf8959f04c9423f3ffdd73d9eb90f61a79959",
"outputIndex": 0,
"ergoTree": "1999030f0400040204020404040405feffffffffffffffff0105feffffffffffffffff01050004d00f040004000406050005000580dac409d819d601b2a5730000d602e4c6a70404d603db63087201d604db6308a7d605b27203730100d606b27204730200d607b27203730300d608b27204730400d6099973058c720602d60a999973068c7205027209d60bc17201d60cc1a7d60d99720b720cd60e91720d7307d60f8c720802d6107e720f06d6117e720d06d612998c720702720fd6137e720c06d6147308d6157e721206d6167e720a06d6177e720906d6189c72117217d6199c72157217d1ededededededed93c27201c2a793e4c672010404720293b27203730900b27204730a00938c7205018c720601938c7207018c72080193b17203730b9593720a730c95720e929c9c721072117e7202069c7ef07212069a9c72137e7214067e9c720d7e72020506929c9c721372157e7202069c7ef0720d069a9c72107e7214067e9c72127e7202050695ed720e917212730d907216a19d721872139d72197210ed9272189c721672139272199c7216721091720b730e",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04c80f",
"sigmaType": "SInt",
"renderedValue": "996"
}
}
}
],
"outputs": [
{
"boxId": "790bb54d599fa1ce3679dc053eab5c180722cc9e7a6af16e4a2b57a13ee0f260",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 1000000,
"index": 0,
"globalIndex": 18165421,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(71,44,61,78,-54,-96,-113,-73,57,47,-16,65,-18,46,106,-9,95,74,85,-120,16,-89,75,40,96,5,73,-43,57,40,16,-24)\n2: 2\n3: 0\n4: 1\n5: 100\n6: 2\n7: -2\n8: 1\n9: Coll(-60,30,-111,54,-57,63,-78,-18,56,-102,-88,68,14,-61,-38,66,28,-22,61,41,88,-114,-117,-113,36,-51,-80,-66,89,32,-40,25)\n10: 100000\n11: 10000000\n12: 100000\n13: 100000\n14: 1\n15: 10000\n16: 1000\n17: 100000\n18: 100000\n19: 100000\n20: Coll(125,46,40,67,16,99,-53,-79,-23,-31,68,104,-6,-52,71,-71,-124,-39,98,83,44,25,-80,-79,79,116,-48,-50,-98,-44,89,-66)\n21: 0\n22: 0\n23: 0\n24: 1\n25: 3000\n26: 0\n27: 0\n28: 0\n29: 10000000\n30: SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))\n31: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val coll2 = box1.tokens\n val coll3 = placeholder[Coll[Byte]](1)\n val tuple4 = coll2(placeholder[Int](2))\n val box5 = OUTPUTS(placeholder[Int](3))\n val coll6 = box5.tokens\n val coll7 = SELF.tokens\n val tuple8 = coll6(placeholder[Int](4))\n val func9 = {(tuple9: (Long, Long)) =>\n val l11 = tuple9._2\n val l12 = tuple9._1 - l11 * placeholder[Long](5) / l11\n (l12 < placeholder[Long](6)) && (l12 > placeholder[Long](7))\n }\n val l10 = INPUTS(placeholder[Int](8)).value\n val coll11 = OUTPUTS.filter({(box11: Box) => blake2b256(box11.propositionBytes) == placeholder[Coll[Byte]](9) })\n val l12 = l10 - l10 * SELF.R5[Long].get / placeholder[Long](10) - coll11.size.toLong * placeholder[Long](11)\n val l13 = l12 * box1.R4[Int].get.toLong\n val l14 = box1.value\n val l15 = tuple4._2 / placeholder[Long](12) * l13 / placeholder[Long](13) / l14 + l14 * placeholder[Int](14).toLong / placeholder[Long](15) * placeholder[\n Long\n ](16) + l13 / placeholder[Long](17) * placeholder[Long](18)\n val l16 = SELF.R4[Long].get\n val l17 = l15 + l15 * l16 / placeholder[Long](19)\n val l18 = box5.R5[Long].get\n sigmaProp(\n (\n (\n allOf(Coll[Boolean](placeholder[Coll[Byte]](20) == coll2(placeholder[Int](21))._1, coll3 == tuple4._1)) && allOf(\n Coll[Boolean](\n box5.propositionBytes == SELF.propositionBytes, coll6(placeholder[Int](22))._1 == coll7(placeholder[Int](23))._1, tuple8._1 == coll3, func9(\n (tuple8._2, coll7(placeholder[Int](24))._2 - l17)\n ), box5.value == SELF.value, box5.R4[Long].get == l16, l18 <= placeholder[Long](25), l18 >= placeholder[Long](26)\n )\n )\n ) && allOf(\n Coll[Boolean](\n func9((coll11.fold(placeholder[Long](27), {(tuple19: (Long, Box)) => tuple19._1 + tuple19._2.tokens(placeholder[Int](28))._2 }), l17)), coll11.forall(\n {(box19: Box) => box19.value == placeholder[Long](29) }\n )\n )\n )\n ) && OUTPUTS.exists({(box19: Box) => func9((box19.value, l12)) && (box19.propositionBytes == placeholder[SigmaProp](30).propBytes) })\n ) && placeholder[SigmaProp](31)\n}",
"address": "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",
"assets": [
{
"tokenId": "01e0ae6997711e9fa0422287a82a8815f64f805c2735aec49fe2bb90ef5fbc78",
"index": 0,
"amount": 1,
"name": "NETA Emission Box NFT",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 1,
"amount": 8299207150000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "05e0d702",
"sigmaType": "SLong",
"renderedValue": "22000"
},
"R5": {
"serializedValue": "05f02e",
"sigmaType": "SLong",
"renderedValue": "3000"
}
},
"spentTransactionId": "509b3219f6522a3b52d4cb11167818cc1d825bc29aef275ef21f30b8fd20492c",
"mainChain": true
},
{
"boxId": "bc03b99fdb25c9619639fe26a99566fa731e0b7c29dba21ab81d36ba6383844d",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 60352468000,
"index": 1,
"globalIndex": 18165422,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "0008cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d627",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))}",
"address": "9gdLf3Zg1QHgH3BYjFrMA2DSm19CqPNKi9vTCeCT5NSmNZfV29T",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "9badecb8a56d044941c7f92486845776162fc2b90c0a49d50e93f6b1f4bffabb",
"mainChain": true
},
{
"boxId": "62d5476b3b233046e4e95053e03e3fcfe1e9af5ad207fbd3480975ff5eab2db8",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 2,
"globalIndex": 18165423,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 162121677,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "cc00f101ed0ffe47472591f457b8564af5e8def38f4125f64b54dad41143b763",
"mainChain": true
},
{
"boxId": "65a0e1c236ffd988235888926e6e6b778a8107e6b410d66385aeb842ba91b2ca",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 3,
"globalIndex": 18165424,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 109137003,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "299b80a34fca92ba7ad425fa3b254eb07c4eae2e336e82f6d5cffcb21df168b8",
"mainChain": true
},
{
"boxId": "4c86f39bebccc4ebe7e8f689f7b79378f6a29183c90371cb8e295b6de6275a23",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 4,
"globalIndex": 18165425,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 103415061,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e6a9d75bf6047519e9b3001fb21bea8ff548c6aca437f312a30006046994e55e",
"mainChain": true
},
{
"boxId": "e01ffac95f591539739469702ff33b01834295494f2d32e19c2c3d7d45420ea3",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 5,
"globalIndex": 18165426,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 166457245,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "21122ad824f5107725cf4e40a8dc09ff7e81fade9c6aaf47e5850ea307963a3d",
"mainChain": true
},
{
"boxId": "3ecb9cc6877b91a5689528cb5e95beeb8089b559d17786d317421536f448a59d",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 6,
"globalIndex": 18165427,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1354218044,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "5fa8510b37e1617b276d39a3a196b451c4ff885618f304710e04e3cf0edc88ac",
"mainChain": true
},
{
"boxId": "6e0aea2a20628c7fa6dca92f0fe50b98a0bd2a101e5e6c6ea67982844acaaaea",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 7,
"globalIndex": 18165428,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 172557289,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9f9dfe9838ed1258a05c384685ac306c6244d3a8dcee7b154a86908ce1c11f53",
"mainChain": true
},
{
"boxId": "a003922a027ae8fa732d875c6a8ec5705422115c734dfd903d253c3c772ec4d8",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 8,
"globalIndex": 18165429,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 251362120,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "fbba05823679a313d253203e16d6d0362c16cefe0d658456d7f554e9b138a1ba",
"mainChain": true
},
{
"boxId": "5721817b1eb36fd16cced0e70417657c22fa459233494208925e773f46a2c93a",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 9,
"globalIndex": 18165430,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 162440963,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2dd91c73389241fe1520a446f1a5c66d1069d814c73849e720efcdc4d648ea22",
"mainChain": true
},
{
"boxId": "d5eaba5c406fc451387a9d452422bb0ec5aa07d2c939701e8b81aadebe5a9e31",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 10,
"globalIndex": 18165431,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 96932714,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7f93d5055648a566a4d1f52c5b5c037207fb6648aa52c07e00ccf59f73f937c6",
"mainChain": true
},
{
"boxId": "89be02e6b424a97a7f64c392964e8d8afc7a68aa75f8388936779d061ce0c532",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 11,
"globalIndex": 18165432,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 348618322,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "81855fb11da70dcef765cfc40f85cf7a96f86817893f208a8ce92038bf867c63",
"mainChain": true
},
{
"boxId": "d6b77830c479f0a4adc2c46a6112b32e7d8444ec33932044a9c77a23bff3b5e7",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 12,
"globalIndex": 18165433,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 97163777,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "71f4c87ac0d113460b34eea55379deecd859fb41981334d6f0b215082761fa30",
"mainChain": true
},
{
"boxId": "fe626d2325cc1aa256a9d53ce0607f0606af5581a2ae12a42b3c77f271405766",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 13,
"globalIndex": 18165434,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 186156353,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2ee086ef221ab26c63892cacb6fbd0a7e00c03ea8ffda57b378c0c13b5b411de",
"mainChain": true
},
{
"boxId": "6de8052308647a0ebabf70997300469c9965b6dc8e713e50c5fb449b62fe0f8c",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 14,
"globalIndex": 18165435,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 337728988,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "c30dc1b70ff3ef79500728ab61102934d1249cf598fba1c386b508f700f5f450",
"mainChain": true
},
{
"boxId": "4b39bca675dbd6fe23d3d413057368e090a855eb4402d2a2968298f3d372c53d",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 15,
"globalIndex": 18165436,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 219299082,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "dc796cf5ea1b70e714ffbdde12ac49554d0f540ee7fa20ec47c431f26fa0eb0d",
"mainChain": true
},
{
"boxId": "a29306710dca9f2d37a8c4c6762b6c0b022459a0ddb23a8761e54a1a57735371",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 16,
"globalIndex": 18165437,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 308993247,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4c041853ce5ec77c24d04a8180f3a39ed3accb65072b323db13567aef4902517",
"mainChain": true
},
{
"boxId": "bb62a178a98e778d013479ace02ab79c70e1d8aa112a1a3f8009c2a221dee777",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 17,
"globalIndex": 18165438,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 377980032,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4aa232f3419ba74a123dbcaad64fe089e396f348d2a76c6d9f718abe4218ba5e",
"mainChain": true
},
{
"boxId": "ee309eb5f669b7bfee8584dfe6290398a8fa3f250494a56d3dbedca1e9451b7a",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 18,
"globalIndex": 18165439,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 303893072,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "6bfdb174671de78eaf3fe28c76b6b3c2bad75e16b0009220de6cc7120c083f77",
"mainChain": true
},
{
"boxId": "1d15213f69f1d32e2c734fc4e3cabe058c3774a365755a6e9df23274445ce361",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 19,
"globalIndex": 18165440,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 429960637,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a84654ebca89898e1b312dfb5306ad30c9b9637c9cb4856730336d8aa6276a71",
"mainChain": true
},
{
"boxId": "871f2435e6ac807183cb2ce4ae172c895754e7fd67ff101be6f063170d7bc8b4",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 20,
"globalIndex": 18165441,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 189244184,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "609dc85e989450e57a684d12eb30afe200c2a9d41bccbcdbe16959b7678ef509",
"mainChain": true
},
{
"boxId": "883b9ada83528bea4db751ee84868a711031f7071c634f394080c590defa56e9",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 21,
"globalIndex": 18165442,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 313547273,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a581b409104c58ec156991e2f66296ce4556b50a7f8ab3a15f8b08f578cd3b26",
"mainChain": true
},
{
"boxId": "9971d383a87f94c330fd43b8722600d380cf9f6061b8c9eac03ec7d199c5c608",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 22,
"globalIndex": 18165443,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 193420110,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "3676231d5e4b4f4b29a51145cc921d29d5ae793ddffe356d406d0786dfd285d6",
"mainChain": true
},
{
"boxId": "1e531345d87a0ff7407797f09b7203579572f5d1814ed370e4e940ca925c4029",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 23,
"globalIndex": 18165444,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 133205287,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4899345a32be495792a2e34d3d15193c75a32e59766823728aa32933c711dbdd",
"mainChain": true
},
{
"boxId": "ba7b2a54bd7941f26c6480cb439c46f9b03698a04677a6f92ea17e13cc02654f",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 24,
"globalIndex": 18165445,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 286508789,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b4ac7afb0a182f5958a7987b02c346294daefb583d761911a44a20d60e6e40e9",
"mainChain": true
},
{
"boxId": "49c0a5167b80c7c42bfafdaf9f14ccf5dbf06bcdcb5f07293225c7eb32b1aafe",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 25,
"globalIndex": 18165446,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 225247884,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "712c0c284ea53e0d719f2c9929a2652034a45e3f8eefef1e7a617b590e838bbd",
"mainChain": true
},
{
"boxId": "bd19ede152b228703dda62f2c1d22fd098e5abdfcd4820f48d460505a05ce967",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 26,
"globalIndex": 18165447,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 312156699,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "029aa0c2d885dd50ddb7144203c7b0e23fb616037389705de791d63942aae9cf",
"mainChain": true
},
{
"boxId": "6c377fb7ebb9563e0e820447ca6d4b0b6496b46300e338d9b2fe5b642cec4088",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 27,
"globalIndex": 18165448,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 194961925,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e02d3fb3456c64e73c22aa3800d5a1f01a5e3fea19a8d4346aa15abaf3dc4a0f",
"mainChain": true
},
{
"boxId": "8c1428073c5fbc55b04fb9b95d753cd5ddd2ec1fcaf4a2bb1b579846d2fdfb59",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 28,
"globalIndex": 18165449,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 413126701,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7d54b95df59ed850f9ee3d901d3086582b9a4386b6e9a71f220dab011b29b6f3",
"mainChain": true
},
{
"boxId": "27f8b4d3f388d46ba8ab5eecc88a460138040c5dd895147e5cfe2c64d5a974b6",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 29,
"globalIndex": 18165450,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 309140286,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "de9cfc6f578a06cc2f40de6dc14eec96b5fdc50ccecfd29e8da1eb3f4c7a424f",
"mainChain": true
},
{
"boxId": "8b3c928d70435c338ed5299c48ad282df44ea95933005810fd06b0c7d0da0cea",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 30,
"globalIndex": 18165451,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 288361488,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "fb7fbfd65c4a24249705fc4a169b63d4bd5e9a392a9dac95dc2241637c2716e3",
"mainChain": true
},
{
"boxId": "3311a210b819e4ec34cbf557f5869a0f3d93749420535db1fbe8b0196e4539b1",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 31,
"globalIndex": 18165452,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 264650300,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "964d65bb80e3f01b440d329294e27ee9dfe62d5bcc697215e84e07e4e782b61f",
"mainChain": true
},
{
"boxId": "ee653707f0fd622104e24768b2e03361e838214d1fc2d1e5383d6e79c91e5394",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 32,
"globalIndex": 18165453,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 222849038,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "060d8719cc0dd86321262db93587b691b2519facbc599d22a00f265583d84d54",
"mainChain": true
},
{
"boxId": "b38c939947e0f3fb253e9a39a62e09590f7a414c06c12d8b9ba0606397a3b1cc",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 33,
"globalIndex": 18165454,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 207409879,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2a83db5037735838ca47588f7a9deb455b22629b572f64837fef0d84f58cc6df",
"mainChain": true
},
{
"boxId": "e3ba974a1b33909870ff9ecdcca970a26f29446872f3a847b37b3f7e5bf4d11a",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 34,
"globalIndex": 18165455,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 266116495,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "cac27494f230a9fdb00fe8260eff9baa6abe032ae92da55bb1c0851905d7a19b",
"mainChain": true
},
{
"boxId": "40a528712503df1bc8c6d5b1a7bc0e7d7101c9a4928759baf472c19817c67d6e",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 35,
"globalIndex": 18165456,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 138108008,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "45c9b00db66cbb673ee18d898298732bc8b7ab9bf11a13c712c1cf6c7051fe32",
"mainChain": true
},
{
"boxId": "2d6ceb33627b0629dbb8597806349f928a42f3b1a444f15f4808d755952b0d44",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 36,
"globalIndex": 18165457,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 181127598,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a30148be1e65eb0131bc3d78474590aa73971a71dea1a657b1df788783f05631",
"mainChain": true
},
{
"boxId": "2b838dbc801c6d836d3276c0ee7222b74597fbf9edca36df3324e797e1ecd3e9",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 37,
"globalIndex": 18165458,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 292995336,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "658fa1be2ffef819e848aec88b2a6bb4592c081241e092c1daeca3c63c5f4bf2",
"mainChain": true
},
{
"boxId": "3af7d0ac81f3b239b7e6208095291551d1b3f5f1b03113b8de5b965b2fc04a5c",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 38,
"globalIndex": 18165459,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 273531493,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f712a9ccb3e96cd2ad6473f66b3f889cea0d34a6d5e266f3a51140951d6739d8",
"mainChain": true
},
{
"boxId": "b1b0966b2d4232a99bfbbfb1fac714828fa407e03f700a6abfcd97028484945e",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 39,
"globalIndex": 18165460,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 357113011,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "34dbfbf7d5c022b27bc168167f7037f95debe7cc5946f788855219efbd931c5c",
"mainChain": true
},
{
"boxId": "c1d9207690cb269f0fe22aa649b9001a7f02ec8d5fc6f7aa9a713b08ad6e4e7c",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 40,
"globalIndex": 18165461,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 208796252,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2ea73da5db4bfb9e52f94f91540c73974a8fc529f6672d422549c882af9b6077",
"mainChain": true
},
{
"boxId": "21327e0e8d578337a9034fe0bca5a9f298245dd6146a8db1712f55bedcd662a1",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 41,
"globalIndex": 18165462,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 282412685,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9ce790f9eea884974300e106619efa59de821be44d1477734d05643022a328a4",
"mainChain": true
},
{
"boxId": "2b9a10a449ba1cf2f7340fa7f460eab94e50aaaeaf2c869db72856dc87dc0128",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 42,
"globalIndex": 18165463,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 307598471,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0fe51053df367ff1731dcd0d68762f93da031894ff0b435eee5e0204a33e7ef7",
"mainChain": true
},
{
"boxId": "3ff09ae23a49d5261ccec344fd80f6e5cf39e6074d87084e1c818c45b1cc68eb",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 43,
"globalIndex": 18165464,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 209947362,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "46cca58b70aae2a639f09f9079af4330ae282ce5bca70884dcaf05faafc0c0a1",
"mainChain": true
},
{
"boxId": "6713bc436022f4547f3c78b5ff7f7946c0cba73ad827a5a0787214ee3186c2b2",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 44,
"globalIndex": 18165465,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 197898516,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "565e059e278f641b34328a822568ffcf2bbeb5c066f3a762ab219cd3038a4116",
"mainChain": true
},
{
"boxId": "2167c2ec83a43e6b63779d9fa312a8bb74572d3057f68381e10a1f1958f88471",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 45,
"globalIndex": 18165466,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 281639677,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b1bf36ce37c507412d2f116c393397d86128a2ce92b60be7aa859956648f5f4f",
"mainChain": true
},
{
"boxId": "af677013fbfa2335e1014e1fccdca1574e716a54dd05064415164144bccb7ed2",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 46,
"globalIndex": 18165467,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 394822370,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f5e4e5722f12e4fe0200d0bdd8308c416263c2426c063c0a779ee956636b0aa9",
"mainChain": true
},
{
"boxId": "f25737033116fe1e8685fcbd3d8183deba52cb86e629eec4dadf5171d4856da2",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 47,
"globalIndex": 18165468,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 117098147,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "58b0d6a174cf9321b38d4075c8eb17ad49dce916bfd4455ebe685ee6e6f6c024",
"mainChain": true
},
{
"boxId": "a884acab3b0bb030c5bc7e1b41f475425df97533ba43ee31cff6c3370391f677",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 48,
"globalIndex": 18165469,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 403308656,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d63340420e97514179d4c40a89878b239cd76246ff90a5bd668934af0a6f1d9e",
"mainChain": true
},
{
"boxId": "906c9bc30d56eda95a8b9d0f0e20d0ab84ef1fb048b08b452c3ad72c45a5f186",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 49,
"globalIndex": 18165470,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 192088351,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "be1e5a1b225a1b1cd52d7ae6b465feb24c7b54746fe9473f6a242f565e15def9",
"mainChain": true
},
{
"boxId": "3dc6868b26003e51ba390b0a5c61777b1e5cc502671fc2e4889b1d53012e8d8b",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 50,
"globalIndex": 18165471,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
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"index": 0,
"amount": 224332038,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "6d973c675497497a8cd6db082e2adf20757db95cf969cc6a869fde61abf4980a",
"mainChain": true
},
{
"boxId": "3078bff611c1cf3bc3251dea151925972d092889bb847d4faed25d3b8e403223",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 51,
"globalIndex": 18165472,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 96231125,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "76aff62fa1bdd0d02b94d70bf91dc286f39e3caef227b85ac1f77a8445f5568e",
"mainChain": true
},
{
"boxId": "8d0a49013f5ddb97b61a13b657cfb0bd61a20652bdf8228ab6e86a4567c8305d",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 52,
"globalIndex": 18165473,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 226256156,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "6263d17e462f754d3d3603ccb5ecc8c8faa7db28c97f68f8553038becadd1c51",
"mainChain": true
},
{
"boxId": "814b92ed46c14fd82a1125d0434354a6cb823f03e2137dd73836ceba508c5660",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 53,
"globalIndex": 18165474,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 315399973,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b1e208a0f3b7db8e9ba96b4f96992961793271820e427024753c47fe1a297d67",
"mainChain": true
},
{
"boxId": "ee94ac53357415a7eb1862e9e429778470ff08f145088bd09bfa58b098f6b307",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 54,
"globalIndex": 18165475,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 242863230,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "dc18723b51b0975a10aed7301b58ae57f5843218e4b67ad5759b43a45f2c86e4",
"mainChain": true
},
{
"boxId": "da81cf6ac53c14d353286154130cf066678b8c68af1f2e602dfecf25b602b577",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 55,
"globalIndex": 18165476,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 406173828,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0be62cdc40aadb78ca21c90ef37bc9e8760cd124e80ba72fa3b26d6ce8306ff5",
"mainChain": true
},
{
"boxId": "3b9d034cb26e20d1881d453575ca4451bb817302f8837fea905503421b84c031",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 56,
"globalIndex": 18165477,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 181955221,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "001f3ef529af90eab1534bbc1dbe17c807ba6d2b3fb37358a507981472f10f9b",
"mainChain": true
},
{
"boxId": "25a18146a36d99b5a9eb250d139883bc0fb61613f5fd71ef34f2bce728022e32",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 57,
"globalIndex": 18165478,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 370720477,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9430039455ae6301993e5bf07e051a5bb3cc42b9f021eb8fc217eba52b306480",
"mainChain": true
},
{
"boxId": "f8d6bb1562b1f36610597395fe5a3dc1e63c96790d97aebc175cf9f23bd2d1fe",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 58,
"globalIndex": 18165479,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 275207744,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "3b8ece67777dc8f5726976e0f4c51a7cedc8ccba1977e1c3672f6b898fc16e8e",
"mainChain": true
},
{
"boxId": "bcc79bc6622db8243192c2b445e5e4bedb02e826c857f74ae7d074d99fbe03b6",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 59,
"globalIndex": 18165480,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 1130112867,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b17c9fb932c845911a6954cce68af804919b0ce70e52df59695366620fe04687",
"mainChain": true
},
{
"boxId": "2908e0e21b80f910c1ca25068c60d23532ba95887c3b8fef34cc31e7519c27a8",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 60,
"globalIndex": 18165481,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 224789961,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f5b8ced009d283f3c3dddafa547441b7f3a7910ccbf8a9f979e4c1136ad05d6e",
"mainChain": true
},
{
"boxId": "04d52bca7a36030896440eeb0b4ca09cf298e543925cadf86a1c5eb8275762c9",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 61,
"globalIndex": 18165482,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 153559771,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "055e70468905d011c1977d0e0e3b6f45cd1da1e7163ac0876d3e071f4ed416ad",
"mainChain": true
},
{
"boxId": "b05fd39df3abed23c3a9e902efd398adb352c40cc668090ff3a17e926efd1159",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 62,
"globalIndex": 18165483,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 97483063,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1a23caaca143084bdc91a0b2231e011039a4afe8c98eddd894058e7cc56101eb",
"mainChain": true
},
{
"boxId": "c8f45b046740f68a5a592f0dc0e64b3564c30701d1e34c9d71142b48a4ea4e7e",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 63,
"globalIndex": 18165484,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 106595318,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "07c5b517f83ad42d89da14543cf2d87a313f1c96b15a68fa5fc60291e18f98ff",
"mainChain": true
},
{
"boxId": "5c207cd5271710a20cecc34dc3b8e7ed4077cec586f8c6c559fe44756534518a",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 64,
"globalIndex": 18165485,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 391885779,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "be7f7ba2fc007dfb22e9cad7cd5ac947e27660d01c1906c9ee7c45f0bc374197",
"mainChain": true
},
{
"boxId": "580ed04b69bb5dbe2f35082c4f8bed989ee765a8e656ab2475765bfaa3ea2dc1",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 65,
"globalIndex": 18165486,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 309846076,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "45f2324d08114f41be00eb6c869a068e5bd97131038810a13eec60e17ab184c5",
"mainChain": true
},
{
"boxId": "8a0303e45cb75e380a5c59e5f61f12521263f459015ebad677b169a9de239eac",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 66,
"globalIndex": 18165487,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 112308857,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "961c68d40046a704081c3cd0ccc992011f3ed99a0fd6145cc51dbb833a076014",
"mainChain": true
},
{
"boxId": "c95b055b7d2269d6e92dc10a12c83cf5d8aa5772be1d1ed3677751dfd6fdc4d2",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 67,
"globalIndex": 18165488,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 317723198,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4d972d98071ed3274f636efc713501c9b72eb5af00c4b606f04c55f204e110ed",
"mainChain": true
},
{
"boxId": "2cd5a27e114d563da23fbb73815ddd71b8493258d4701f963640de6d558b2583",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 68,
"globalIndex": 18165489,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 177737284,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d8135072a3b10a37d71a229c9275dbfcb73c350da2a33423d40efdc252686347",
"mainChain": true
},
{
"boxId": "d916991aa55837a38a0564049ae3fe1e0512ed8c8063981d26081f0258eb854a",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 69,
"globalIndex": 18165490,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 192647101,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "65e83c0522a36658bec43d7ee1afab60a09fe824c246f5e4aeda92e1bece5ee0",
"mainChain": true
},
{
"boxId": "5d1e6d2b79f934d956bb994484317fb52e5a0961ab8aa7727a2810e2946b7566",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 70,
"globalIndex": 18165491,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 197982539,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f308e712cc00f3cb398371fe832e6c59419a9889e773d0a387371583386fcaab",
"mainChain": true
},
{
"boxId": "eada9e74d53e6e70c9086d373a90f615ed6ebd983d5333405b7cbb78ec181990",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 71,
"globalIndex": 18165492,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 143519066,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1bc68f30fb57481637f92a0a8656187103cb22e64fc2145ca31b78525f8505fc",
"mainChain": true
},
{
"boxId": "a62b7cfa7551a98d79da2a0cdcee63448d1431f8b9de581a2078da54c124a060",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 72,
"globalIndex": 18165493,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 340048013,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ec7089e8adf995397c56f25c8135dde4c5a7f36978e1d7d648a8bd9650ce211f",
"mainChain": true
},
{
"boxId": "ee2c2423be7454b1a9fcae5967c8ff7ba264bc4f12dc3a37232a0acd84770e19",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 73,
"globalIndex": 18165494,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 225554567,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0d001550ebe0c7e91021c99ce6f96096b15d711da64aee4aca8c4d02719d0cef",
"mainChain": true
},
{
"boxId": "5e31d620d513287ec92ea7601044eae398ee63ce7859fc0eb28a6ac515ff6c59",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 74,
"globalIndex": 18165495,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 104200673,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d4b726e0b4d7e6554dc5a8d116e45ed62e16377410699042c9b01f600f2468a3",
"mainChain": true
},
{
"boxId": "12b684f5023eb08b52fb218f96453b9d39abbf5107c0869463e0248fb6a4f358",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 75,
"globalIndex": 18165496,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 211959704,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ee3bdec3ea7b3af93e497d84f880fd912bc58c8a74a2be6788f4fc943c29e1f2",
"mainChain": true
},
{
"boxId": "b8d378ef2f1c2b368e645015723d8071ed0d1d57cec15fffaf2b406fc44930e5",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 76,
"globalIndex": 18165497,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 188702238,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d6fd909458fd284b660393e9cf1880592357eef538f458af0d1e358ee9c92a32",
"mainChain": true
},
{
"boxId": "ca5771aa6aed6a31e3ce8c7798484787fe4f4a871f2693a334dc2af8fb2749b0",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 77,
"globalIndex": 18165498,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 229264166,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a532c15b3f9dc8766cc1fe7b6b9f5ccfef9950134921b97b2345f85b92c2dcb9",
"mainChain": true
},
{
"boxId": "ad3f4d79bb1eaf70bec8009802f190cc91664740f86cd2aba6bd9b5343dc0f77",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 78,
"globalIndex": 18165499,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 224567301,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "43a28ad38e4b0778b347f803ab899e1de4d12e57fea5e42d310d6c57dad529be",
"mainChain": true
},
{
"boxId": "785b8b618922725b3e08e92ec3a46f86a4386de11db6c71dcda180b04137b530",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 79,
"globalIndex": 18165500,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 106599519,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d4723e2ef4f9f93ac9adad9b05828293b49037f8d54d828209255a5e5a581dd8",
"mainChain": true
},
{
"boxId": "27d897761b6b2b4542f80d9216cc5257359092c6a7a869a8fbdb756253b93293",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 80,
"globalIndex": 18165501,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 30504418,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "54007c66b9072fdaa458d3b636a583ad538421f1b239259ff4c562612ee6c5b0",
"mainChain": true
},
{
"boxId": "ba224abc055d72683ca871918ced5ba35edb8a0e4a5ca361d6777fb5e1136de8",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 81,
"globalIndex": 18165502,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 555818145,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "64ae9979274362fbd0119ea7a6b792f61e318d44ae13eeb65f145010a49b9379",
"mainChain": true
},
{
"boxId": "178b742de45713204969f44d9aee135b3dba280b90854653a04b8ad0381f10df",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 82,
"globalIndex": 18165503,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 20157030,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "23ceaf5a43f32205e28a48ec4b07a425034c3fd6adf51059a75914448f0f5529",
"mainChain": true
},
{
"boxId": "38770de01ac9b1877f582f395800a0e98b143e80e552ed6b6b27274a1b1788a2",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 10000000,
"index": 83,
"globalIndex": 18165504,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 24555615,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "45a3a5074573854f5f9a10a73ee5045bcf3fc1b9b06a22e9f979fbbf543e8391",
"mainChain": true
},
{
"boxId": "d74a370b0f6f4e5ab39748f72f27d8ce4cd24e136f189254be0dcfbd22b06cde",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 743333333,
"index": 84,
"globalIndex": 18165505,
"creationHeight": 776512,
"settlementHeight": 776515,
"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": "f675623f2e93bd8d198ce6e40b1b43564a8423f77d9a2dd3d35daf7ca57ff25f",
"mainChain": true
},
{
"boxId": "5d64cf7f120641ed4edbc85751ef5cd0a5796a45de3260e384c311d9655206b1",
"transactionId": "86fd53b146a8d87ceb1de6a5c03b71783f1cd0e96cb3cb0c5905eb29ca16eecb",
"blockId": "3148a8650b07ac89202dfc85037608bf24c5dafaeeaa4dc8c364fc70114fcd3c",
"value": 1148598667,
"index": 85,
"globalIndex": 18165506,
"creationHeight": 776512,
"settlementHeight": 776515,
"ergoTree": "0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6d9d81,e53882,...)))}",
"address": "9fMLVMsG8U1PHqHZ8JDQ4Yn6q5wPdruVn2ctwqaqCXVLfWxfc3Q",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 42,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bb51c5e2d609e258bd18952e52d5a3a352c5e285ea2a9d2fac532cabc9a5c3ce",
"mainChain": true
}
],
"size": 89697,
"isUnconfirmed": false
}