Transaction
ID: b994fa55f4...9751
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
63.01 ERG
Outputs (74)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
60.42 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
177.45
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
129.10
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
353.60
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
152.22
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
1,046.55
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
190.80
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
201.83
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
117.54
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
135.12
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
222.99
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
149.18
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
187.22
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
346.88
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
171.91
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
319.70
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
481.87
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
286.51
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
355.17
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
115.66
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
421.71
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
140.36
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
215.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
99.66
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
609.11
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
351.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
183.78
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
542.95
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
305.33
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
257.22
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
109.58
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
280.10
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
267.67
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
375.32
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
322.59
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
112.47
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
220.41
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
582.94
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
375.32
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
392.66
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
305.57
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
280.18
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
107.55
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
529.44
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
265.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
372.97
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
109.57
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
455.70
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
161.33
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
175.42
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
198.23
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
170.66
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
369.22
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
148.87
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
441.79
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
264.16
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
554.43
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
86.45
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
787.59
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
255.49
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
250.41
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
164.96
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
141.29
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
582.24
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
259.55
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
196.44
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
189.02
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
162.15
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
183.94
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
193.70
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
2
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.683333333 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.21 ERG
Tokens:
0
Transaction Details
Confirmations: 994,124
Total coins transferred: 63.01 ERG
Fees: 0.683333333 ERG
Fees per byte: 0.000008904 ERG
Raw Transaction Data
{
"id": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"inclusionHeight": 774963,
"timestamp": 1655559451364,
"index": 2,
"globalIndex": 3386348,
"numConfirmations": 994124,
"inputs": [
{
"boxId": "e7338ab70af7570c7c12b7c75a152631307abf1ee54068604921e41dd8e564e4",
"value": 1000000,
"index": 0,
"spendingProof": "79f9e37707ad23285cb352a5083b9fbde5aac56e8a7074fc22e7748e9ad36e9e98dbe535e4f81eaf678338674488f4689ad0697775f56fbe",
"outputBlockId": "59d18cde0b40c3728e8e29c6fa8aaf23118dff5be9aeaf837e5e3b6a8c8fa1a1",
"outputTransactionId": "ce8f2477bf923d73a63fc19c86532a11deb21108430a80b65e50d80221e71005",
"outputIndex": 0,
"outputGlobalIndex": 18049032,
"outputCreatedAt": 774936,
"outputSettledAt": 774939,
"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": 9115448394000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "05e0d702",
"sigmaType": "SLong",
"renderedValue": "22000"
},
"R5": {
"serializedValue": "05f02e",
"sigmaType": "SLong",
"renderedValue": "3000"
}
}
},
{
"boxId": "0a86a8cef52842fba92792edbfe212b8527a801ebd11bd43d10bad2605dc8441",
"value": 63011100000,
"index": 1,
"spendingProof": "29fd2514e74913cfc8a65313120558acc832f10984e77e1193390d2da425d2bf9f3482926094d5ba2d265780a7a0e851357a3b419493ef72",
"outputBlockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"outputTransactionId": "2882d96acbadcdb9c49f5c0901dee58ac1b0e3b0ffc7f5eb0cd29c026a6773f8",
"outputIndex": 0,
"outputGlobalIndex": 18050736,
"outputCreatedAt": 774960,
"outputSettledAt": 774963,
"ergoTree": "0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))}",
"address": "9gUibHoaeiwKZSpyghZE6YMEZVJu9wsKzFS23WxRVq6nzTvcGoU",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "5920589ed60e2344977e27bf0d1e1599c05828b3958ccf6ca0d6cc302f9d3c2c",
"value": 40847091759003,
"index": 0,
"outputBlockId": "121207e660fe713a1340fa0c51eb7b96f65c4d99b92a15809e5a5c204024e0d7",
"outputTransactionId": "35ea369cdd2e46922e1536453477ccac2818c8227474b4c426a6b7572c70be2b",
"outputIndex": 0,
"ergoTree": "1999030f0400040204020404040405feffffffffffffffff0105feffffffffffffffff01050004d00f040004000406050005000580dac409d819d601b2a5730000d602e4c6a70404d603db63087201d604db6308a7d605b27203730100d606b27204730200d607b27203730300d608b27204730400d6099973058c720602d60a999973068c7205027209d60bc17201d60cc1a7d60d99720b720cd60e91720d7307d60f8c720802d6107e720f06d6117e720d06d612998c720702720fd6137e720c06d6147308d6157e721206d6167e720a06d6177e720906d6189c72117217d6199c72157217d1ededededededed93c27201c2a793e4c672010404720293b27203730900b27204730a00938c7205018c720601938c7207018c72080193b17203730b9593720a730c95720e929c9c721072117e7202069c7ef07212069a9c72137e7214067e9c720d7e72020506929c9c721372157e7202069c7ef0720d069a9c72107e7214067e9c72127e7202050695ed720e917212730d907216a19d721872139d72197210ed9272189c721672139272199c7216721091720b730e",
"address": "5vSUZRZbdVbnk4sJWjg2uhL94VZWRg4iatK9VgMChufzUgdihgvhR8yWSUEJKszzV7Vmi6K8hCyKTNhUaiP8p5ko6YEU9yfHpjVuXdQ4i5p4cRCzch6ZiqWrNukYjv7Vs5jvBwqg5hcEJ8u1eerr537YLWUoxxi1M4vQxuaCihzPKMt8NDXP4WcbN6mfNxxLZeGBvsHVvVmina5THaECosCWozKJFBnscjhpr3AJsdaL8evXAvPfEjGhVMoTKXAb2ZGGRmR8g1eZshaHmgTg2imSiaoXU5eiF3HvBnDuawaCtt674ikZ3oZdekqswcVPGMwqqUKVsGY4QuFeQoGwRkMqEYTdV2UDMMsfrjrBYQYKUBFMwsQGMNBL1VoY78aotXzdeqJCBVKbQdD3ZZWvukhSe4xrz8tcF3PoxpysDLt89boMqZJtGEHTV9UBTBEac6sDyQP693qT3nKaErN8TCXrJBUmHPqKozAg9bwxTqMYkpmb9iVKLSoJxG7MjAj72SRbcqQfNCVTztSwN3cRxSrVtz4p87jNFbVtFzhPg7UqDwNFTaasySCqM",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "04c80f",
"sigmaType": "SInt",
"renderedValue": "996"
}
}
}
],
"outputs": [
{
"boxId": "04196f04789c78c0a5fa2aec356ce596b7a785308ccf1fb49c25e65d56881aee",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 1000000,
"index": 0,
"globalIndex": 18050740,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 9095773454000,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "05e0d702",
"sigmaType": "SLong",
"renderedValue": "22000"
},
"R5": {
"serializedValue": "05f02e",
"sigmaType": "SLong",
"renderedValue": "3000"
}
},
"spentTransactionId": "454701d45f1ea5a1a4be575cdd8e0bc4eedea5677279e75d101263f04584183e",
"mainChain": true
},
{
"boxId": "38b553b8d3a0202f58b1e4975d3ca5034adaf02df7b8d265c0ef48a1bfb24113",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 60420767000,
"index": 1,
"globalIndex": 18050741,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "0008cd0315a5d99a010bf189b1abae2d9f21be6f3438803aca1e6aac739fbee31150d627",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(15a5d9,27c59b,...)))}",
"address": "9gdLf3Zg1QHgH3BYjFrMA2DSm19CqPNKi9vTCeCT5NSmNZfV29T",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "9badecb8a56d044941c7f92486845776162fc2b90c0a49d50e93f6b1f4bffabb",
"mainChain": true
},
{
"boxId": "2c126bc1d71bd37476bcf4400879b3fa96a097f3278bcb513a15d1f1b5f7939d",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 2,
"globalIndex": 18050742,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 177451699,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e1153b18fc66574e18d25473b194d6c58ca37f2df09b98e7973d596fd1976f15",
"mainChain": true
},
{
"boxId": "f1732a5fc5ca7996ab784237008487ae28d5be87b2416a6740cd661ef1186a9a",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 3,
"globalIndex": 18050743,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 129095491,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "c5434fc604f90df69a2886be2198d7af6d1d651004e9b179b79acbe9ba7d00f2",
"mainChain": true
},
{
"boxId": "5176bdf775a2dc2015ca0d142314c837680ed39b3cf70f4c40b58bab21f9939b",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 4,
"globalIndex": 18050744,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 353600835,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d54da569f59a153d0be4a573764ec29a81c9ea70fb061df58f8d0b8cbc27625d",
"mainChain": true
},
{
"boxId": "94181641e3079c46143cd54cc4ed64779426f77ecd3d141baced0d0ab2ab4e89",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 5,
"globalIndex": 18050745,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 152222887,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "c26c4d9e45cd01762f2b7349235c572084cfb5616237ba7d221088bc758c5a11",
"mainChain": true
},
{
"boxId": "ff79689905ab7bf863a5b10a39dd500834f9c60cc03735d124f7be578fa2385c",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 6,
"globalIndex": 18050746,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 1046553009,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "20186d5fe44dce0ef18fcbc6af086fc56307e4e076ed7430694339f1443f5fc4",
"mainChain": true
},
{
"boxId": "29894720e331c1484627d2930f4e5d0a0114b5a4689bac82d92937eaa43aa8f1",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 7,
"globalIndex": 18050747,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 190803963,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "997a8f2b55830fa0cf96f857d4d1ce2947ffa2c0cb782bb482315285c04409b9",
"mainChain": true
},
{
"boxId": "91529b138feece7b4540f7c724ac76836236ab05dabc75ec156faa57100a56bd",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 8,
"globalIndex": 18050748,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 201826565,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "5d468e5af92660e9552926ae65c5016f02c3f0c64f0ac46c842bfc6b116e4d13",
"mainChain": true
},
{
"boxId": "fde167fcf3971d39f86a7135ccca90ccc7e52d6b9acc9ced99d93359a5773806",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 9,
"globalIndex": 18050749,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 117537696,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d761c27238bb7c5f178c279df9ed5fe5c75a630eb943b92765617dc75148a9a6",
"mainChain": true
},
{
"boxId": "8c9f171fe97e4111a914493f8faef7104ffbce366a30e09646dd3d6035ed36e2",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 10,
"globalIndex": 18050750,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 135120341,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "461600f9c781158068b22158877aa5187eec45b8a66b006fbebbbd6ae9c714a7",
"mainChain": true
},
{
"boxId": "bb2af1b22fc62787682b1a3ae24e6809e691434734dd4fbc63679805a81255e1",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 11,
"globalIndex": 18050751,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 222994212,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0c75dd8a2089c33df944f1454b2fc43550c62ccb4b20cc4cca65be5fc02533af",
"mainChain": true
},
{
"boxId": "2da1b8a18811c89c2390e8efcf25d8eab58c3fc84617304cd9acb7ed85989a7c",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 12,
"globalIndex": 18050752,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 149180948,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "5a40aae6cabaf0db54e1f190da58123f649e41fa32111a88ac1845e491452d09",
"mainChain": true
},
{
"boxId": "8287eabc1038638f5e12124df283d3697de9a8ca614be0467e297ba8856371ab",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 13,
"globalIndex": 18050753,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 187218961,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ad90b1e27e81433808b14dd46b48e898bed20faa2acfabbdb0c3ae3356ccb4dd",
"mainChain": true
},
{
"boxId": "48235203d5798d897b0488cae32d946fad4321686f87f893eabd33bcc1da35bf",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 14,
"globalIndex": 18050754,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 346883384,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7df7f87fa1905b1a1c5b42644a2cfdc41c161e911b4d634da1b2d2b7ac38cd6b",
"mainChain": true
},
{
"boxId": "49fe128ead05ade1cef425aaec0918f9b3e56b0363493ea16b829a0c140764ee",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 15,
"globalIndex": 18050755,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 171906949,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "09db1380fac5fb9a730eb6ad7dd1ce1d2388912e42db6fc42c5aa0f1d1089ed9",
"mainChain": true
},
{
"boxId": "1526aa0137597e55d75f4b6d507369e8daa1199f6ba5beef150a0d9d546b0e61",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 16,
"globalIndex": 18050756,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
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"index": 0,
"amount": 319698757,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "fcb6283b160bc890991e06a6d06bbe7899cfd982ee433f8252639e35fe83448f",
"mainChain": true
},
{
"boxId": "00dfc59854dd9f4bb1cf671f974ac18b468516f005cd5acb80855bb37c4790bc",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 17,
"globalIndex": 18050757,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 481865992,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9e1d07d098603ca0e046778a0eb1c585324e355095374ba1926b909abba1a834",
"mainChain": true
},
{
"boxId": "227cad02e751f45c8797e3e65c72dc0c60ecb297769f85c9626f09b719a6d042",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 18,
"globalIndex": 18050758,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 286505023,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "79babcdfcb5a0745bd953c4db81eaa43c018c3f3df4647881c67edbbe14cf47c",
"mainChain": true
},
{
"boxId": "78abed9e6faa593bf6f13451d6585061f1a78f9519a36436c86ea94c38aad7f6",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 19,
"globalIndex": 18050759,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 355167060,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "90850cbc00725e5da2403fa0162339e3b199687eb6c36aea37c026803de7e069",
"mainChain": true
},
{
"boxId": "a215480c16bdbf4e03cc14d94422e590beba57b2b97e2dd13612a5b450b9c73d",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 20,
"globalIndex": 18050760,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 115664523,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1de5cab9bcf152eb820537ba2ce36055618cd8fca3b5d1e11e59f7b1665fe285",
"mainChain": true
},
{
"boxId": "68f17d51f9354d391e7b9c996145b10445d5f5ee9de1c5aa3ba2cb2268a0aa6b",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 21,
"globalIndex": 18050761,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 421711939,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "342b5feab3b503ad36093f28c1708889fbf88a0a96345283c7eed55aaff1cbb0",
"mainChain": true
},
{
"boxId": "e48c3615248c831348867b6f17be6d79ffd34adcb32d148e4a64433e75f30cbe",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 22,
"globalIndex": 18050762,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 140358143,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "472ba1a6bb00c591b38cfedf6d060d80f0c412e5d372f29307c6d87b845ed254",
"mainChain": true
},
{
"boxId": "75267d6c949fb97aad0878801ec5a46eb9de3a5e561ac5e29ba0081c9b6cac76",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 23,
"globalIndex": 18050763,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 215961941,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "fcc6e60cddf2bd1cc85fc6657c44a72d6a4f32def40a37dd884656fa4e3c33d0",
"mainChain": true
},
{
"boxId": "46e5b18d275fdcc0b72b5fb18e7d9e28355ae10deb7486bc03191afa5db23462",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 24,
"globalIndex": 18050764,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 99655974,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "29030f1c34af31a4084650f0384236fceecb4f246af58851dc758e9a15d110ee",
"mainChain": true
},
{
"boxId": "63ee9ad5406a1dea79bf8f64c2cd7d1086f567740bef906f91767883cebfe682",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 25,
"globalIndex": 18050765,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 609107986,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d85b050ec32570bae8f95474d4f9d121571d62e7caa79cd7aa937de4d4eaf99e",
"mainChain": true
},
{
"boxId": "a680d41c387ad2e62e10e3f1bc7c0e7868a3f5553f32293a4f15ff44daedabb9",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 26,
"globalIndex": 18050766,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 351959841,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f39fe6020ab71fe55f1e2f36de12001c4f0f2198380c9886f6afa52feacf051f",
"mainChain": true
},
{
"boxId": "d7bf8d6f30ee1f7697db867f69522000da6909b3ace3dce9ea8b1c39b88d0495",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 27,
"globalIndex": 18050767,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 183783498,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "97349d7f5042e020287a47fe2349ed5af975f5cded446c787360bae0d645a93b",
"mainChain": true
},
{
"boxId": "112486a6a73874bee97ee3ff238d79ae4bcd4821302a2e2974963d7601106e53",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 28,
"globalIndex": 18050768,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 542952696,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "85c388937b20a8a2b33b5a0ea443bba16b7144a36769c3184b20a490add82fdc",
"mainChain": true
},
{
"boxId": "698a0ffda7be0bef51176fa3c076fe17332aa60220688a40435d6797dde1b2c3",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 29,
"globalIndex": 18050769,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 305327267,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "fbd8881cf0cd32535a486dafc47fd7fc855fccb8cd249abf6f288eb76f854bf5",
"mainChain": true
},
{
"boxId": "463be636f7e95b9bed2c7c585b7ccff409ece3718e390b8876c84f4964dd65cc",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 30,
"globalIndex": 18050770,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 257218979,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "154ae8445296a2f9839b8b0166238ae0de6f3a6e01659972b4f3ebee40bd5581",
"mainChain": true
},
{
"boxId": "a7d90bd806973d62c760366e219e22c9e77f5f31fc1581a3d557dad1575e8aa8",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 31,
"globalIndex": 18050771,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 109576709,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "c19cae7b82f9e5857ef5bb1dd88391cd2b094de41e8f40a786a22b8f35421dae",
"mainChain": true
},
{
"boxId": "901543929d1632ed3a2095bd54c68eae6e5f87e116478c9ad0c1af53cc29781f",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 32,
"globalIndex": 18050772,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 280098455,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "2b1d343527b4837932e27ad99ca1f1a83574f478f26cf34ec6aebb3f9d6f37cd",
"mainChain": true
},
{
"boxId": "5f7cd838c18dde14e16eb04de1a971018404cb31b9bf29bf287d776780b98ecd",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 33,
"globalIndex": 18050773,
"creationHeight": 774960,
"settlementHeight": 774963,
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"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 267674907,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8ad920bd8ad96d87af9b1beb546c9b643a6750536bef089f0ccd6cd7717ace6d",
"mainChain": true
},
{
"boxId": "d8b846efa21b9ead15d949eb5a07fbbf060c341b50d7d31291949791a27a8322",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 34,
"globalIndex": 18050774,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 375319415,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f707a3a6816de23039c77db9bd79d717e8e7661fffb284848442562e8fdd229e",
"mainChain": true
},
{
"boxId": "d28b1e9306832fc1da0953f4bdb89953ac04ecbc927136cf2e41e781ce4dc6d2",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 35,
"globalIndex": 18050775,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 322587222,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d85b1bfa146afe2243335c4343d11c7b1cb75f429391449f2cc63bfc0c6ff202",
"mainChain": true
},
{
"boxId": "f71e0410cefe7841e90ebc8e062f67c4c9c455e32a75caffe05e812ff545ad90",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 36,
"globalIndex": 18050776,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 112465174,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "32eea9aea5068d2b949d641fddf456c88843a7c71462069d9600dfd1ac1f03ed",
"mainChain": true
},
{
"boxId": "f540d84e2c7af965e601d178539c48ecc44207e1759833f600509fa5b2137654",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 37,
"globalIndex": 18050777,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 220412696,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0b61300642027c9aebe3e8e191746122cd957840f78373ed554959fbca446b8c",
"mainChain": true
},
{
"boxId": "6f7ef4e2f3eb3b15cecd12e683962f8b36d4c18f0fb4d0c2394b74d8e7132d21",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 38,
"globalIndex": 18050778,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 582942587,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1413d88b96b9bc67ca2cd864c31510a5f1767442a1fbf411a83725afafdcb4fd",
"mainChain": true
},
{
"boxId": "0d11107fae17f28eb79fbd6ae6e61a538022f20721e8acc49230fd5ee26b1a8c",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 39,
"globalIndex": 18050779,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 375319415,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "14dcee36b09691e6d00a055a9aef161610883ceb1d4a7006d47298ba25d786ba",
"mainChain": true
},
{
"boxId": "4211584f51fd0f189724f320b1f11ec86dd8c57a206048dd67aeb68a9a5bf014",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 40,
"globalIndex": 18050780,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 392658075,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "29da82e02bea211956aac019aa8718cc83473f5a54160fdd246f144898d2cd28",
"mainChain": true
},
{
"boxId": "f229a98dc01939c2e48a29a6da2ac56f80b2e8ebe0d57c1303ffa44b7562354d",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 41,
"globalIndex": 18050781,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "103a04000502050005c801050605050500050205c8010506050504000e2030afb371a30d30f3d1180fbaf51440b9fa259b5d3b65fe2ddc988ab1e2a408e7040205000400040404020500040405c09a0c040004000400040004040402050004040400050004000400040204000404040104040401050001000401040105000100040105000400040104000580897a0100010105000400010104000100d806d601b2a4730000d602c2a7d603b5a4d901036393c272037202d6047301d605d9010559d80bd6078c720501d6088c720502d6099472087302d60a7208d60b957209720a7204d60c997207720bd60d9c720c7303d60e9d720d720bd60f8f720e7304d610d801d61091720e73057210d611ed720f72107211d606d9010659d803d6088c720602d60995947208730672087307d60a9d9c998c720601720973087209ed8f720a730991720a730ad195938cb2db63087201730b0001730cd80ad607e4c6b2a4730d00040c3c0e11d608e4c67201040c3c0e11d60999b07203730ed9010941639a8c7209018cb2db63088c720902730f0002b0b57208d901093c0e11d801d60b8c7209028fb2720b731000b2720b7311007312d90109413c0e119a8c720901b28c8c72090202731300d60aade4c67201050c4c0ed9010a4c0e86028c720a019d9c7e8c720a020572097314d60b8cb2db6308a773150001d60cb5b5a5d9010c6391b1db6308720c7316d9010c63938cb2db6308720c73170001720bd60dad720cd9010d63c2720dd60e7204d60fad720cd9010f638cb2db6308720f73180002d610b0b57207d901103c0e11d801d6128c7210028fb27212731900b27212731a00731bd90110413c0e119a8c721001b28c8c72100202731c00edededaf7207d901113c0e11d807d6138c721101d614dc0c1aad7208d901143c0e118c721401027213731dd6158c721102d616dad90116059d9cb0720a7209d90118414d0e998c7218018c8c721802027216b07207731ed90118413c0e119a8c721801b28c8c72180202731f0001b27215732000d617b27215732100d618dc0c1a720d0272137322d619b27215732300959472147324d801d61a9ab2b2ad7208d9011a3c0e118c721a0272140073250072169592721a7217959472187326d801d61b7205edda721b018602721ab2720f72180093721973277328ed9372187329da7205018602721a721995927216721795947218732aedda72050186027216b2720f721800937219732b732ced937218732dda720501860272167219af720ad901114d0ed801d6138c72110295917213732ed801d614dc0c1a720d028c721101732f959472147330d801d615b2720c721400edda720601860272138cb2db630872157331000293c17215733273337334959172107335ae720cd9011163edda720601860272108cb2db630872117336000293c2721172027337af7203d9011163938cb2db6308721173380001720b7339",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 305567317,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d5620e03c7a1445a44db9f80222823fc094274d0a4511ff0565e60112eebc5e8",
"mainChain": true
},
{
"boxId": "01c7a23efaf327615c8e055731c221c6b5900e559d8386857220b532a336834f",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 42,
"globalIndex": 18050782,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 280177159,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b85b18dd786e3ce9d500b98db97ed7b6cab0efb3f6c5a31f88edc92d2d07e1aa",
"mainChain": true
},
{
"boxId": "4bf1974e28462a89ff0282ba611f8fcbeaefef5f3d0c887641dce8b7ddbb6cc8",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 43,
"globalIndex": 18050783,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 107550062,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f382c363354555f35a2eefb9d945020f68aa2811caddcd07f5f190585b4c1994",
"mainChain": true
},
{
"boxId": "d44a3e1807598d8944f29438ae52d06ad31c41288847ae3828792bf5ceb9e57e",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 44,
"globalIndex": 18050784,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 529439087,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0f9e1bbfd73100f3473a99aaf2fe60c4d494b79b68b0c7294437e212446c9586",
"mainChain": true
},
{
"boxId": "5917cc5133c6b0a8827d73167a8f2f9da46cd84645a50583906fb77ecc517969",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 45,
"globalIndex": 18050785,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 265955208,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0c17e7ab7eefdfa894266c128cc932a48482b5a3b6560f7a1fc8f919eeb80c6b",
"mainChain": true
},
{
"boxId": "646fc31fd90b3ad46438b9e62fe418b9ad9b5abdc2b7077eb18390d7080b2bee",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 46,
"globalIndex": 18050786,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 372974013,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a27ce3997c581431326b6a123ef666f20d34149c1ff98ea6d8d27abb51a1d9d7",
"mainChain": true
},
{
"boxId": "42356a066d3e4bb32f391b815b4b695d0d9f0ce7c566dfdb8861096f3afe0288",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 47,
"globalIndex": 18050787,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 109572774,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "d4f59916fc2822f7ee3ab72c266ec0bd1f5f6159255516cd9013a337d0ba34cc",
"mainChain": true
},
{
"boxId": "3f5580a39df6f207ce227e34c6789ad2d726c7c62772f89613e0d0adbdf0222d",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 48,
"globalIndex": 18050788,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 455696657,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b92e14b7cfeaec4ddd4257c347d2303559694583798123bad80c3b1cbbe9f4a8",
"mainChain": true
},
{
"boxId": "6f5e627071d88395f51f495eae6b6d7eb03d40c97036f4d7f2a4b982c147e426",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 49,
"globalIndex": 18050789,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 161325093,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "0756556086e065b810da7fd9798ab3d64c51274fa49007857da0f88ae0238c68",
"mainChain": true
},
{
"boxId": "4350b5a99905b6fb4e87a147616e19384b5e501de5c52a88a4b2e8cc993c6bbc",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 50,
"globalIndex": 18050790,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 175421116,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "33576fdb81229273606a6d63d5acfcc4947c44ee536c6188ef4212561e6c4a3f",
"mainChain": true
},
{
"boxId": "753b9d1799d5d3635bc7874f6dddd958ea41136c7975c9101aee34a6522ffa58",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 51,
"globalIndex": 18050791,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 198229757,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "9c55162c204c167f6c6a9326c30819b810b234d22c0c8d21cac14de53a68623c",
"mainChain": true
},
{
"boxId": "da0dbf8d3061478c281fef6ccd86b1d5bf5e29d4864cd55218a1670eeabcd98b",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 52,
"globalIndex": 18050792,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 170655543,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bf4900b915b1433d436df81527cfe4839c8d7eccd616264e817877568b91bfc9",
"mainChain": true
},
{
"boxId": "7dcabbd7e5aceb15d7d06e99e7f1fd1954cb362b6b8ef4a2cc3473f24643721e",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 53,
"globalIndex": 18050793,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 369219796,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bffc40a1abf5e6e1be7e2eda7d32168333d207932639adf0a068484bfc0ea983",
"mainChain": true
},
{
"boxId": "3d3a4dcaca50fea069214208fbad8f280b7b438dc0fb2e5583b56afef76d06f6",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 54,
"globalIndex": 18050794,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 148870064,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "6c270911259b0753c96d124e4929de2bf9750b60dc7b3022853859a0275b5509",
"mainChain": true
},
{
"boxId": "0bbae465bf967a09339ad011f20c8475c46d9523a980baba7e3e86fea789cd0a",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 55,
"globalIndex": 18050795,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 441793460,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "901e1f3ec887cf0640a686a07be9707d97aa4e9f0e356b59b471133257d9cbc8",
"mainChain": true
},
{
"boxId": "f21db44cd49c15a8b7adaf791e6ed196872390f61974b3c507a1e13a41953f40",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 56,
"globalIndex": 18050796,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 264164675,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1186402759cfa85f00f43d3131cdef7d68b30e53cd050c8a7b7a31d8e5c86052",
"mainChain": true
},
{
"boxId": "b8c0fc87ad5cca0f2fb0cea7fac4eb41508697f5d92f121a8d231b67789cd8b9",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 57,
"globalIndex": 18050797,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 554427850,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ff484eeeda56d31194bc50373d3af10568c53673be487faeb13ad20b461f7007",
"mainChain": true
},
{
"boxId": "fc0c51e626c269e18af2ad09fbbd310021ace37d645527814dc33912fa484c23",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 58,
"globalIndex": 18050798,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 86453249,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "1716757081720ebff6183bdac936739d363ce8d92e630c2486ea73a3fe50e9b2",
"mainChain": true
},
{
"boxId": "ae8bea81b2032b1e3f4e331898295f95e06ec0ef984047a99efd955e25dc223d",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 59,
"globalIndex": 18050799,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 787594654,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a6b0edef7c7f67a7ec08f775b09c4a2142b4f92d86534a09fa30000d2bf6eb28",
"mainChain": true
},
{
"boxId": "c6e6117b78c1838691fac2a2d4ef79aa81ba6349bdae224188d8151fbc7afdcd",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 60,
"globalIndex": 18050800,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 255487474,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "42ba9ed82416c731c872ed6e2b67547983b6208cd30059cda5d26c9727214fd0",
"mainChain": true
},
{
"boxId": "3b747b1912176dfb680ca2f3a0595926034a435c93eaead71267e723471bef5f",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 61,
"globalIndex": 18050801,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
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"index": 0,
"amount": 250414952,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "09d311869d2321466cb62326c556f077800bcc9a72dd3016b948c8676ad12508",
"mainChain": true
},
{
"boxId": "2f728e80dfb1410531930c918fadb3d5629ae478d698b20a942766d1f3a62e51",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 62,
"globalIndex": 18050802,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 164957318,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e8bfce2c8751466556495f4c4c32ff5e23a7987ef7136b08db6368faab40c96f",
"mainChain": true
},
{
"boxId": "85ed0145e85c64d40d50dae3909ed1b107e85b381cab8fd570a6c91f3cc1ff64",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 63,
"globalIndex": 18050803,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 141290795,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "177badb12d98ae22508a4bd8280d54a3bfbd76eb44a5a2cd306d92a865e8a0d1",
"mainChain": true
},
{
"boxId": "b5a1a2c8a5e8d7779d37a888504c493b6b9371c9052d58204f13ed5287991688",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 64,
"globalIndex": 18050804,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 582242115,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b12b770ed25ef9bc813894b5924051603aa850c82b4d85a05ca843c84a8e20b2",
"mainChain": true
},
{
"boxId": "9f337dec2c30afc04d89b222e07530167012f63348f8a6bb030b121de22dec0d",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 65,
"globalIndex": 18050805,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 259552576,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "3d843360935be2d4dff1072e48264eb95e38cbeb5d4418edc5f192308f225c47",
"mainChain": true
},
{
"boxId": "640df9134f2f916eccc8d6073d7a9d683fcbce88caac3f440e12b89e0933a6b6",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 66,
"globalIndex": 18050806,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 196435289,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e8fd654d18e2eeb30ff149a62530a95e69b6db57a8a964d1eebb0bd61dcdb43f",
"mainChain": true
},
{
"boxId": "829c7f3f936deea3f41b5237cb6f38381c5dde5fcc614a5f122b9190a8914e2b",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 67,
"globalIndex": 18050807,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
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"index": 0,
"amount": 189021300,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "456405ff7ef90359f15f38026cda0d6a8cb0e7c8918782c274e2cae4cfc78f0a",
"mainChain": true
},
{
"boxId": "35b535a63d415d8ba9501eac4411e5694b971d9103432072872d34b7cd8a2aa5",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 68,
"globalIndex": 18050808,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "2x459aECGv9N81rY346AEZ7TdZgSEYZAZH99UDp9mii1yFfo9TUHvLeNJoXzfUjXYJP6ESKC2MVRcSZtVmhKVppPMn6857gNEcefko57Pukw1hyAoxmBK9YjT91T3wkBsF9i4BKQxiioho6RnZPFPVHdfwppj1ExTYqgzSedc2YwnFTp5njKtdKUfTAbEjyqDKdKf5YdJfjRar1adtEmJmBgaaZRn5K9BPyt7sNWBEWD5aQWsspHA1D57mFCbwBALU9Ae8YmxfvomJpfX31GHnNfwcBfpU7gMocWb7MbPcdnBYLyLgGJtXXQ2jvtWkEWRR9RzbSvUbM2pZ22QVdmyKC1hNuVf9dNmL5AVPhz3FtbBLKDrGzKjNRnpvnd93DJR4BYGTDhfzQVTHRQ5puSutpkXAgKe2APCe5AfUAUFzUSeHkFw1d1m75pAs3DRonvXP6Cuy4ABSeaXqxceniVvWje3G7E9zRFnjRZCSebGsmn2eHdbi5DHeqbZ8SGgEM5sYHD4ZWca4NWkERcak4jQjiNZSivAjvjTk9fQ5q7W296XU3snSq3uFpDHkx2Y6L4DCC5hfaD4tGYeja7gnKWSXnEbRgp3yxMkuR2YtjneJN1X7gWDkbAjReSXbox6kUGzKcTccDTD17Lk7mQpRjoiN8b1PeqLdMgEyxvuNQ4ADweipFNQUEF5abRBFm1WLxaJUP5VicWZqFKU7uhACYuMcSaxxmmprkVAYPoLUy8XEeqqZijZuNUzvYxeQfn8W2J145tDdqvvqJh6iVmCa7T1ndScdE1fqDjFF5Y1QATM52amD4f7Fgfo4yBsR8s9jQQekBPRgPABEzpAiSiF2QHfXTvUNQBMyWncuQm2423hrqZN4PSaZoYbzEnfgQ7sQLE8BginMZzjtj7mSektGtHtttinBCxJHDf8ND8bDFvoVS94WdQjVLu7Zbpbmou1X6iUN7i7PBPEDSXmeGusH11X9tmAo4unESX9NB1ivr2kFEZjn6beJUDiByL8uj9JgwSHQWvkb2FwGn1Hvsk9GNQcHWZ12HVrsEuY9wzS9hCc4fEeDJ9ALBrURJKN9qksHJL22px2tYS3yL5pXVxGkJmZAFBJAts8z14ji6uCyuyLxmC9dmiwxwpCxJAqBrQWM1CjUYBmxmX3dbCdjHibR7fPdNpfLM9jSZphvar4ufiUCzFBsVsB6CD71T2EbUG7PYn7dMhcJ8SEmfscRveCHu2EumCrRqrtmqP9RwX7myhnvYwP3JAfux5okYSAiCwgSxdDouPJLft9UnY1ZDs5FD826zzMBbaurnAGUJCbjGwhirGq9ZKZteVGp52FFLJmaRfiXnaUQyzXEkJZfUrYZUGi8xeyNSwHpZSqCgcWBrvK5AYWKnAZkgo7wqbtbKMKYhXje4mtg9TNwdbUNMQCuhqRUUVNhK2mKkxNztFbLWtLKCDopEVgVsAy",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 162151493,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "be0c816a614cc221215c6b3b704457043894551cf3279a16324593e6bf31ab2e",
"mainChain": true
},
{
"boxId": "d030217cccba484f935ba3799e45b98b4a63062ca96205b43b63e01d53745cb6",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 69,
"globalIndex": 18050809,
"creationHeight": 774960,
"settlementHeight": 774963,
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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": 183940907,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "7c22d169103fa69e2abbcc50be8f7560a358d98d80d8054cb2c3de08ca96315a",
"mainChain": true
},
{
"boxId": "361b733e3eda61405d5bc82f3cf63a497f94af9ac8ad406cac5156907c5225b1",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 70,
"globalIndex": 18050810,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 100\n4: 3\n5: -3\n6: 0\n7: 1\n8: 100\n9: 3\n10: -3\n11: 0\n12: Coll(48,-81,-77,113,-93,13,48,-13,-47,24,15,-70,-11,20,64,-71,-6,37,-101,93,59,101,-2,45,-36,-104,-118,-79,-30,-92,8,-25)\n13: 1\n14: 0\n15: 0\n16: 2\n17: 1\n18: 0\n19: 2\n20: 100000\n21: 0\n22: 0\n23: 0\n24: 0\n25: 2\n26: 1\n27: 0\n28: 2\n29: 0\n30: 0\n31: 0\n32: 0\n33: 1\n34: 0\n35: 2\n36: -1\n37: 2\n38: -1\n39: 0\n40: false\n41: -1\n42: -1\n43: 0\n44: false\n45: -1\n46: 0\n47: 0\n48: -1\n49: 0\n50: 1000000\n51: false\n52: true\n53: 0\n54: 0\n55: true\n56: 0\n57: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = SELF.propositionBytes\n val coll3 = INPUTS.filter({(box3: Box) => box3.propositionBytes == coll2 })\n val l4 = placeholder[Long](1)\n val func5 = {(tuple5: (Long, Long)) =>\n val l7 = tuple5._1\n val l8 = tuple5._2\n val bool9 = l8 != placeholder[Long](2)\n val l10 = l8\n val l11 = if (bool9) { l10 } else { l4 }\n val l12 = l7 - l11\n val l13 = l12 * placeholder[Long](3)\n val l14 = l13 / l11\n val bool15 = l14 < placeholder[Long](4)\n val bool16 = \n val bool16 = l14 > placeholder[Long](5)\n bool16\n \n val bool17 = bool15 && bool16\n bool17\n }\n val func6 = {(tuple6: (Long, Long)) =>\n val l8 = tuple6._2\n val l9 = if (l8 != placeholder[Long](6)) { l8 } else { placeholder[Long](7) }\n val l10 = tuple6._1 - l9 * placeholder[Long](8) / l9\n (l10 < placeholder[Long](9)) && (l10 > placeholder[Long](10))\n }\n sigmaProp(if (box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12)) {(\n val coll7 = INPUTS(placeholder[Int](13)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll8 = box1.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l9 = coll3.fold(placeholder[Long](14), {(tuple9: (Long, Box)) => tuple9._1 + tuple9._2.tokens(placeholder[Int](15))._2 }) - coll8.filter({(tuple9: (Coll[Byte], Coll[Long])) =>\n val coll11 = tuple9._2\n coll11(placeholder[Int](16)) < coll11(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple9: (Long, (Coll[Byte], Coll[Long]))) => tuple9._1 + tuple9._2._2(placeholder[Int](19)) })\n val coll10 = box1.R5[Coll[(Coll[Byte], Int)]].get.map({(tuple10: (Coll[Byte], Int)) => (tuple10._1, tuple10._2.toLong * l9 / placeholder[Long](20)) })\n val coll11 = SELF.tokens(placeholder[Int](21))._1\n val coll12 = OUTPUTS.filter({(box12: Box) => box12.tokens.size > placeholder[Int](22) }).filter({(box12: Box) => box12.tokens(placeholder[Int](23))._1 == coll11 })\n val coll13 = coll12.map({(box13: Box) => box13.propositionBytes })\n val l14 = l4\n val coll15 = coll12.map({(box15: Box) => box15.tokens(placeholder[Int](24))._2 })\n val l16 = coll7.filter({(tuple16: (Coll[Byte], Coll[Long])) =>\n val coll18 = tuple16._2\n coll18(placeholder[Int](25)) < coll18(placeholder[Int](26))\n }).fold(placeholder[Long](27), {(tuple16: (Long, (Coll[Byte], Coll[Long]))) => tuple16._1 + tuple16._2._2(placeholder[Int](28)) })\n ((coll7.forall({(tuple17: (Coll[Byte], Coll[Long])) =>\n val coll19 = tuple17._1\n val i20 = coll8.map({(tuple20: (Coll[Byte], Coll[Long])) => tuple20._1 }).indexOf(coll19, placeholder[Int](29))\n val coll21 = tuple17._2\n val l22 = {(l22: Long) => coll10.fold(l9, {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 - tuple24._2._2 }) * l22 / coll7.fold(placeholder[Long](30), {(tuple24: (Long, (Coll[Byte], Coll[Long]))) => tuple24._1 + tuple24._2._2(placeholder[Int](31)) }) }(coll21(placeholder[Int](32)))\n val l23 = coll21(placeholder[Int](33))\n val i24 = coll13.indexOf(coll19, placeholder[Int](34))\n val l25 = coll21(placeholder[Int](35))\n if (i20 != placeholder[Int](36)) {(\n val l26 = coll8.map({(tuple26: (Coll[Byte], Coll[Long])) => tuple26._2 })(i20)(placeholder[Int](37)) + l22\n if (l26 >= l23) { if (i24 != placeholder[Int](38)) {(\n val func27 = func5\n func27((l26, coll15(i24))) && (l25 == placeholder[Long](39))\n )} else { placeholder[Boolean](40) } } else { (i24 == placeholder[Int](41)) && func5((l26, l25)) }\n )} else { if (l22 >= l23) { if (i24 != placeholder[Int](42)) { func5((l22, coll15(i24))) && (l25 == placeholder[Long](43)) } else { placeholder[Boolean](44) } } else { (i24 == placeholder[Int](45)) && func5((l22, l25)) } }\n }) && coll10.forall({(tuple17: (Coll[Byte], Long)) =>\n val l19 = tuple17._2\n if (l19 > placeholder[Long](46)) {(\n val i20 = coll13.indexOf(tuple17._1, placeholder[Int](47))\n if (i20 != placeholder[Int](48)) {(\n val box21 = coll12(i20)\n func6((l19, box21.tokens(placeholder[Int](49))._2)) && (box21.value == placeholder[Long](50))\n )} else { placeholder[Boolean](51) }\n )} else { placeholder[Boolean](52) }\n })) && if (l16 > placeholder[Long](53)) { coll12.exists({(box17: Box) => func6((l16, box17.tokens(placeholder[Int](54))._2)) && (box17.propositionBytes == coll2) }) } else { placeholder[Boolean](55) }) && coll3.forall({(box17: Box) => box17.tokens(placeholder[Int](56))._1 == coll11 })\n )} else { placeholder[Boolean](57) })\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 193704233,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "b42ce00cd1412ae7397b2c2788a73015a4e692d26988fe8cde01b9050f2b1ef4",
"mainChain": true
},
{
"boxId": "3ff614d5becb32e6a72c59c55665c951cc61a3a03ba7eb16d9c125034f50ab68",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 10000000,
"index": 71,
"globalIndex": 18050811,
"creationHeight": 774960,
"settlementHeight": 774963,
"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": 2262762,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ee500f43d93a3411d94bdeecb244486fda03a407e2d8896caf0c4042743615b0",
"mainChain": true
},
{
"boxId": "9af1861b1f98c0007df55b8e891d1c08b0f8b9ee9d54a3e16e818365719804f5",
"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
"blockId": "780a8cbe406549bf956fc6de70730b6095684012ba91ed9d2ed4b56b284f7380",
"value": 683333333,
"index": 72,
"globalIndex": 18050812,
"creationHeight": 774960,
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"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",
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"additionalRegisters": {},
"spentTransactionId": "ee2960a29a4d3df910d1c20f52bc3bda8412fd8192b4da304fc3206842dae9bb",
"mainChain": true
},
{
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"transactionId": "b994fa55f4b56cc087bd18e3b02f9aaf12fe4d2150295422025ed095d70c9751",
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"value": 1206999667,
"index": 73,
"globalIndex": 18050813,
"creationHeight": 774960,
"settlementHeight": 774963,
"ergoTree": "0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6d9d81,e53882,...)))}",
"address": "9fMLVMsG8U1PHqHZ8JDQ4Yn6q5wPdruVn2ctwqaqCXVLfWxfc3Q",
"assets": [
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 0,
"amount": 38,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "c302f77459718cb669ef235a8f1f9afd39670b277d592b1735f0bfac434d2cf3",
"mainChain": true
}
],
"size": 76746,
"isUnconfirmed": false
}