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Transaction

6/13/2022 08:00:05 PM
ID: 9faa69e346...2caf
Inputs (2)
#0
fef53b755608...6fba
Spent
Address:
Vek63kH3dkZ6...d8oe
Output transaction:
dd6911ec08cd...cd19
Settlement height:
771,299
Value:
0.001 ERG
Tokens:
Loading assets...
#1
5c78d85a3e80...e7c4
Spent
Address:
9gUibHoaeiwK...cGoU
Output transaction:
6d119454c4a1...933e
Settlement height:
771,307
Value:
63.01 ERG
Outputs (24)
#0
69f50a9a10a0...8f9f
Spent
Address:
Vek63kH3dkZ6...d8oe
Spent in transaction:
246534e6fe40...7348
Settlement height:
771,307
Value:
0.001 ERG
Tokens:
Loading assets...
#1
b908c6a7a571...a626
Spent
Address:
9gdLf3Zg1QHg...V29T
Spent in transaction:
9badecb8a56d...fabb
Settlement height:
771,307
Value:
60.92 ERG
#2
f56a6846c556...bb1c
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
c40a8f048703...e40c
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
910.83
#3
5747ee16cf3e...780f
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
0ed1525bf4ce...2f14
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
504.23
#4
4861630dbcad...5881
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
05dfb42ee029...3659
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
1,820.67
#5
5ba2b0c59b63...4e2d
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
29c181a4522c...28e9
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
377.35
#6
24afab92eba6...25da
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
806febf04f9a...e4ce
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
805.53
#7
ec8c6a5585d8...88ba
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
5e5fcfd939e9...9f0c
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
583.09
#8
423870113ae5...07dc
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
f460c5fe8bc0...20ec
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
743.05
#9
7698b65bb1fa...0364
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
7f3ea9eaeb2c...b9b3
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
694.53
#10
44a038e62e97...34d1
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
808e30088535...3ecc
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
329.14
#11
7a9172949d9c...648e
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
e15a20be604a...a9d2
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
848.09
#12
3b83f022cdda...1062
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
c58bc2c19042...2a44
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
253.69
#13
ba9c23e72c72...82b5
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
302a4ffd28bb...0353
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
1,608.54
#14
eba3875f73c0...e33b
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
d9891de4d35e...c91b
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
316.67
#15
148d681d557f...635e
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
de7201de5256...75fd
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
216.16
#16
4d0c0fadc9d1...c646
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
7f3178e07e68...2425
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
757.20
#17
d128a54cf47c...b58d
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
cc3da9af748b...b971
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
487.30
#18
faa7a61abcc7...0c0d
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
b6a9718e5e5f...47fc
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
538.36
#19
e6f010ac5991...f315
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
60855b3a91ad...0ab3
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
755.71
#20
03ddec50b4be...3b42
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
fcf5640feae7...b007
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
955.43
#21
71875d6d1d68...e0e2
Spent
Address:
2x459aECGv9N...VsAy
Spent in transaction:
cc9282d7c36d...d837
Settlement height:
771,307
Value:
0.01 ERG
Tokens:
NETA
790.65
#22
b41ba4e7985c...baf1
Spent
Address:
Ergo Platform (Miner Fee)
Spent in transaction:
0aae942db88c...d5b3
Settlement height:
771,307
Value:
0.433333333 ERG
#23
6bb8812a4f0e...c410
Spent
Address:
9fMLVMsG8U1P...fc3Q
Spent in transaction:
2344f32cf6ec...0a95
Settlement height:
771,307
Value:
1.46 ERG
Tokens:
NETA
0
Transaction Details
Status: Confirmed
Size: 22.25 KB
Received time: 6/13/2022 08:00:05 PM
Included in blocks: 771,307
Confirmations: 997,054
Total coins transferred: 63.01 ERG
Fees: 0.433333333 ERG
Fees per byte: 0.000019018 ERG
Raw Transaction Data
{
  "id": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
  "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
  "inclusionHeight": 771307,
  "timestamp": 1655150405728,
  "index": 3,
  "globalIndex": 3353779,
  "numConfirmations": 997054,
  "inputs": [
    {
      "boxId": "fef53b755608ee4948cbd053396c42e337da62f31d2b0e112e7288e6d04d6fba",
      "value": 1000000,
      "index": 0,
      "spendingProof": "4c174ab4406c786b87e53564e2c8b1edf6ce865c2658f6d2830d8b960446d804cc3c74a0399806bc2e0050f5ea88a2ccdfa0eb772bb6cd25",
      "outputBlockId": "0a51f07822c0a2a1a41f97d990ebebe2c9e926426ea749f644b9c7562ca56116",
      "outputTransactionId": "dd6911ec08cd3aa3a0b4d91565fbea478d36c7c3054962d21133b614820fcd19",
      "outputIndex": 0,
      "outputGlobalIndex": 17850203,
      "outputCreatedAt": 771297,
      "outputSettledAt": 771299,
      "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": 9850723728000,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "05e0d702",
          "sigmaType": "SLong",
          "renderedValue": "22000"
        },
        "R5": {
          "serializedValue": "05f02e",
          "sigmaType": "SLong",
          "renderedValue": "3000"
        }
      }
    },
    {
      "boxId": "5c78d85a3e807311bd995fb38ff3509b0549c965e623fdf508085e80211ee7c4",
      "value": 63013200000,
      "index": 1,
      "spendingProof": "c77cf7e59a73737b2cc264893634b0cb6003ac9c9e09bea0009dc679e01b05b0ff4dd0572481505558aa3d2bd36ccd2b6f5389eb98400564",
      "outputBlockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "outputTransactionId": "6d119454c4a11ebbacaf3f09a3b100fdbc6781d87bbb1f3c5d7e1d022b71933e",
      "outputIndex": 0,
      "outputGlobalIndex": 17851091,
      "outputCreatedAt": 771305,
      "outputSettledAt": 771307,
      "ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
      "address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
      "assets": [],
      "additionalRegisters": {}
    }
  ],
  "dataInputs": [
    {
      "boxId": "9bd660a9376715a36f7aa5cc69b0fe5d5e5991080aa4923c4987e8bd5e8686fb",
      "value": 47430021821189,
      "index": 0,
      "outputBlockId": "770054e5336a41df195e4c20262798299f7334e32cd1d1441176e9fad8f3843e",
      "outputTransactionId": "3f558afa0a34b870005a32a420544fa6bf70ed38fa12b03f32d518095f69a660",
      "outputIndex": 0,
      "ergoTree": "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",
      "address": "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",
      "assets": [],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "04c80f",
          "sigmaType": "SInt",
          "renderedValue": "996"
        }
      }
    }
  ],
  "outputs": [
    {
      "boxId": "69f50a9a10a0063154d53fc314e888268dfc87467d8dd81ea04522e5d2238f9f",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 1000000,
      "index": 0,
      "globalIndex": 17851097,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "ergoTree": "102004000e20472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e804040400040205c8010504050304020e20c41e9136c73fb2ee389aa8440ec3da421cea3d29588e8b8f24cdb0be5920d81905c09a0c0580dac40905c09a0c05c09a0c040205a09c0105d00f05c09a0c05c09a0c05c09a0c0e207d2e28431063cbb1e9e14468facc47b984d962532c19b0b14f74d0ce9ed459be040004000400040205f02e0500050004000580dac40908cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d62708cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7d812d601b2db6501fe730000d602db63087201d6037301d604b27202730200d605b2a5730300d606db63087205d607db6308a7d608b27206730400d609d9010959d802d60b8c720902d60c9d9c998c720901720b7305720bed8f720c730691720c7307d60ac1b2a4730800d60bb5a5d9010b6393cbc2720b7309d60c9999720a9d9c720ae4c6a70505730a9c7eb1720b05730bd60d9c720c7ee4c67201040405d60ec17201d60f9c9d9c9d8c720402730c9d720d730d9d9a9c9a720e9d9c720e7e730e05730f7310720d73117312d610e4c6a70405d6119a720f9d9c720f72107313d612e4c672050505ea02d1ededed968302019373148cb27202731500019372038c7204019683080193c27205c2a7938cb27206731600018cb2720773170001938c7208017203da72090186028c720802998cb2720773180002721193c17205c1a793e4c67205040572109072127319927212731a96830201da7209018602b0720b731bd9011341639a8c7213018cb2db63088c721302731c00027211af720bd901136393c17213731daea5d9011363edda7209018602c17213720c93c27213d0731e731f",
      "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": 9836427524000,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R4": {
          "serializedValue": "05e0d702",
          "sigmaType": "SLong",
          "renderedValue": "22000"
        },
        "R5": {
          "serializedValue": "05f02e",
          "sigmaType": "SLong",
          "renderedValue": "3000"
        }
      },
      "spentTransactionId": "246534e6fe40db621612b9c5a0a9d9017fd29691f03f988646afd5b6647d7348",
      "mainChain": true
    },
    {
      "boxId": "b908c6a7a5718fc3c9dd9f152bdc0e0830ff6be8590df1ece35da02bf40ca626",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 60922804000,
      "index": 1,
      "globalIndex": 17851098,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "ergoTree": "0008cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d627",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))}",
      "address": "9gdLf3Zg1QHgH3BYjFrMA2DSm19CqPNKi9vTCeCT5NSmNZfV29T",
      "assets": [],
      "additionalRegisters": {},
      "spentTransactionId": "9badecb8a56d044941c7f92486845776162fc2b90c0a49d50e93f6b1f4bffabb",
      "mainChain": true
    },
    {
      "boxId": "f56a6846c556af2dd0dfc9e7a6be7fee401dd43c9d897176e113e805b97abb1c",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 2,
      "globalIndex": 17851099,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 910825001,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "c40a8f048703cdbbf2c9a2d9a361bc655084f197e641dab0f454a8c629a4e40c",
      "mainChain": true
    },
    {
      "boxId": "5747ee16cf3e06d2fb56dad8f10c5931140186c11b7c08c489a4a188da70780f",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 3,
      "globalIndex": 17851100,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 504234779,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "0ed1525bf4ce90800ed7411e89e77cd7ccda338f507c8e0ec60c52e1ce5e2f14",
      "mainChain": true
    },
    {
      "boxId": "4861630dbcadd5d9bc5b3e097e9383d81e2f4c0f606bbd62ee6a7cc8953c5881",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 4,
      "globalIndex": 17851101,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 1820669268,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "05dfb42ee0298fd9542f46ed952b1926125ac31ad9ea5e00b2c967d4ab483659",
      "mainChain": true
    },
    {
      "boxId": "5ba2b0c59b63b7dcc5f0aa03f34c7cdbe226c6805396e94eaab00aef65954e2d",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 5,
      "globalIndex": 17851102,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 377351181,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "29c181a4522c7d77c59f8bad8922702834bd4c8b10b235fc09dbb38fc9f428e9",
      "mainChain": true
    },
    {
      "boxId": "24afab92eba682d64b9c8b67cf52f1e951275a233b716c1f6cdfc9d92f9625da",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 6,
      "globalIndex": 17851103,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 805531858,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "806febf04f9aa6c5a0dce3b834470c3e4ce335cc2c98a89552aef9831b36e4ce",
      "mainChain": true
    },
    {
      "boxId": "ec8c6a5585d8fe50d35d3669ca497d16c1c21b19f6a1928bad9d9f670c2a88ba",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 7,
      "globalIndex": 17851104,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 583088120,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "5e5fcfd939e9f8ab6f420685a65dd46ccae05baabc2bf2c68f1430b03d639f0c",
      "mainChain": true
    },
    {
      "boxId": "423870113ae5e09beff119f758d4e9f4eeaaca6eb79e58de0da0188600f707dc",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 8,
      "globalIndex": 17851105,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 743045060,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "f460c5fe8bc06f35bcd127ace061c47eb36c5f70767432c5a01d217583f220ec",
      "mainChain": true
    },
    {
      "boxId": "7698b65bb1fa7b7877b412cc6a95ddb8acf0cb584adbd360e6fa00b992610364",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 9,
      "globalIndex": 17851106,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 694531584,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "7f3ea9eaeb2c1c678dddcd77c3572d532a42ea77bd1309b2167195161422b9b3",
      "mainChain": true
    },
    {
      "boxId": "44a038e62e9788ff78fd327edf4d4826905e50b454015c7842d1e9e986a734d1",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 10,
      "globalIndex": 17851107,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 329140789,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "808e3008853558ca07a9bfbc6dd6f80f4fbe039fe01db935c4856a307ede3ecc",
      "mainChain": true
    },
    {
      "boxId": "7a9172949d9cbbf8dca014c8ee99788b7622bc485c5815a26601e43e0fed648e",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 11,
      "globalIndex": 17851108,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 848089445,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "e15a20be604a47d7dcab30cbaf22c00f14c9e7fd95bd4076ff8a6ee22ffea9d2",
      "mainChain": true
    },
    {
      "boxId": "3b83f022cdda78708bdc9dcefff13e3ff6a7978c31cab65546463eb9720b1062",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 12,
      "globalIndex": 17851109,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 253689996,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "c58bc2c19042dd1a92c51eb9600905fb347d7fb02168fe3ec7825c7cce5c2a44",
      "mainChain": true
    },
    {
      "boxId": "ba9c23e72c72306812ba61d4283da0d1963db63842777ac3709678e5658282b5",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 13,
      "globalIndex": 17851110,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 1608536109,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "302a4ffd28bba4eaaf953cc5b625f195ce54e4c89b9bc9347fbf1cb83f880353",
      "mainChain": true
    },
    {
      "boxId": "eba3875f73c0ed3a272a0ed277dddd159f80120f3510054c723312f51715e33b",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 14,
      "globalIndex": 17851111,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 316671450,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "d9891de4d35e43f8b57eb8f37d6f119724099a08125be0726098efac73aac91b",
      "mainChain": true
    },
    {
      "boxId": "148d681d557f57b9d38138c49e5f1a95fb47036daf25934e7924c210f5bd635e",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 15,
      "globalIndex": 17851112,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 216159030,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "de7201de5256b21daf68d199a72146f1cbf55daafd27ce82e6693bf2fbee75fd",
      "mainChain": true
    },
    {
      "boxId": "4d0c0fadc9d147dc9024b95daef83b9ebe03c4f9f5a8d70e2dc23adb3276c646",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 16,
      "globalIndex": 17851113,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 757195658,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "7f3178e07e68f9777a99d8374fea3431a9968ea0bc52a9c4b537dbcc4ea02425",
      "mainChain": true
    },
    {
      "boxId": "d128a54cf47c6a83a3f1a5364136a397d1ae5773ac100b1f91e7f06238a8b58d",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 17,
      "globalIndex": 17851114,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 487299238,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "cc3da9af748b402d18a51e8872474e72f3ff77f4e088f01852eee76637deb971",
      "mainChain": true
    },
    {
      "boxId": "faa7a61abcc7e5a0a6eb6ab5c19c2ab09fffe16d31ed4b611ace7bc089970c0d",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 18,
      "globalIndex": 17851115,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 538360337,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "b6a9718e5e5f79a76d18d0bc9fdecb71363483418d737441a7085c291ade47fc",
      "mainChain": true
    },
    {
      "boxId": "e6f010ac599118741ad8d87bdb0f7329431c4ce52faeab1ad1cc1f42bad1f315",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 19,
      "globalIndex": 17851116,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 755705970,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "60855b3a91ad35a9213ef1087abb4427a8f8236ee159d572a38c9d8bc9940ab3",
      "mainChain": true
    },
    {
      "boxId": "03ddec50b4beefd6f735c3832d22ead55cc050176d13bf8710b17636cc8a3b42",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 20,
      "globalIndex": 17851117,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 955432695,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "fcf5640feae7c6e47136ad7b66a93aee82449cd36fb255e6d504e1d0bc2fb007",
      "mainChain": true
    },
    {
      "boxId": "71875d6d1d68d030ad20d9d742a5c45c976c0037eac96af2965f7eb3ded3e0e2",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 10000000,
      "index": 21,
      "globalIndex": 17851118,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": 790646424,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "cc9282d7c36df21a6ecdd900df6fa03793cad6cfaf810505a0e81047f97ed837",
      "mainChain": true
    },
    {
      "boxId": "b41ba4e7985ce0f89f237913aeb9a1de0a39f3805c3e2cdcace256a0afdfbaf1",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 433333333,
      "index": 22,
      "globalIndex": 17851119,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "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": "0aae942db88c95c8b2aab338f05eca52db1b3cbdaca83f9a3f85d8880abcd5b3",
      "mainChain": true
    },
    {
      "boxId": "6bb8812a4f0eadf206336980ed680322d77c1703dd579b15ec354dc72fafc410",
      "transactionId": "9faa69e346f4876537a9a2fb86e48d25de12024b77e2d0728761992ace132caf",
      "blockId": "95eb51887809c7200e264882fa96957fa6caf48fadfd58b645bc8a6dad48175d",
      "value": 1457062667,
      "index": 23,
      "globalIndex": 17851120,
      "creationHeight": 771305,
      "settlementHeight": 771307,
      "ergoTree": "0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6d9d81,e53882,...)))}",
      "address": "9fMLVMsG8U1PHqHZ8JDQ4Yn6q5wPdruVn2ctwqaqCXVLfWxfc3Q",
      "assets": [
        {
          "tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
          "index": 0,
          "amount": 8,
          "name": "NETA",
          "decimals": 6,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {},
      "spentTransactionId": "2344f32cf6ec63bffc1a730b9bb5ca6f597501d9351b4bbb1523dacd81970a95",
      "mainChain": true
    }
  ],
  "size": 22786,
  "isUnconfirmed": false
}