Transaction
ID: 7b19f95de2...106d
Inputs (5)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0015 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
1 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0015 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
9.94 ERG
Tokens:
Loading assets...
Outputs (15)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
Loading assets...
Unspent
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.5 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
5.96 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 833,048
Total coins transferred: 10.96 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000161 ERG
Raw Transaction Data
{
"id": "7b19f95de28698093351cc2e21f527b5a95162d99d84447a5bb1305cb350106d",
"blockId": "ca4fe6d29a54cb5c19605c82f66d6eb337fcc7127f40c01c16fb141a2be04c86",
"inclusionHeight": 935722,
"timestamp": 1675838473855,
"index": 16,
"globalIndex": 4728590,
"numConfirmations": 833048,
"inputs": [
{
"boxId": "ce9ff3a5ffcbba48a129c893e76cf55ae07a1c2c07c2cf39b0d81d33bed11a4d",
"value": 11000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "7e0e8c93d2ae56ac7cd4f86e4ccd1618dfa8f8b81afb742f5f3be72a223ef54a",
"outputTransactionId": "d17325edf50ec87366611af3509facec50956942a4fc0f411eafedfaf5a2b364",
"outputIndex": 0,
"outputGlobalIndex": 26356228,
"outputCreatedAt": 935692,
"outputSettledAt": 935696,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(10,-76,-39,-12,-34,6,-68,-85,-55,71,58,10,41,-35,11,-97,40,21,-110,38,-16,-85,-71,-43,-61,93,79,119,-58,-104,3,-31)\n3: 1\n4: 0\n5: Coll(-8,51,-9,86,-31,-65,-99,21,-72,-7,-124,-82,-6,100,72,32,64,-42,-56,-77,-20,33,123,43,-24,-72,-92,119,-24,45,-112,13)\n6: 7200\n7: Coll(106,26,12,-10,30,-60,20,-119,22,40,30,109,-126,-95,-47,122,96,-18,-41,-124,82,0,64,29,82,49,55,127,70,67,-70,103)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Coll[Byte]]].get\n val i2 = coll1.size\n val coll3 = OUTPUTS.slice(placeholder[Int](0), i2)\n val coll4 = OUTPUTS(placeholder[Int](1)).propositionBytes\n val coll5 = blake2b256(coll4)\n sigmaProp(allOf(Coll[Boolean](i2 == coll3.size, coll1.zip(coll3).forall({(tuple6: (Coll[Byte], Box)) =>\n val box8 = tuple6._2\n (Coll[Coll[Byte]](tuple6._1) == box8.R4[Coll[Coll[Byte]]].get) && (box8.propositionBytes == coll4)\n }), if (coll5 == placeholder[Coll[Byte]](2)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](3)).tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), HEIGHT - placeholder[Int](6) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](7) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
"address": "21oSXpSmAC6qWRafUZuukJvGaH5cWHsyZd4TyLmPq3rC5PDEEdMmk9Tn7iyYG4omoiPcwLqaHPTczj5EADDMEK8M2hX5ESrUQZ2E7V3Ca2yxRQ3RiyoGFN348Rrkp6MY5ExjdEPj9Tv6ygeRjcDTjwXGufdj51AKbFn8Jtx9jHCAR5vEpFFiJtV1FWCbc1tfVzgXojGkrBQjrazCsYaKm1Ed2zsC97He6RV5bPDLYMp4o9m6HDSXS3Ea9weh7PBWeLzUttV54AfGtAS3RQ7Wc2DvdRZYju1Kz7ZxiQEYmeSDzrrh3g6atG2RnbRXCJQrA3xFuSkc4ERCMcWojzy2YWrZcCQJC6SpXhnzQ8wJphWEutgtqo",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 10,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9dc9311055af1547a6739d7cdd5e17b75aa7338e8990f41fff40bbbe0d644446,9f3c93a1d23a8f9e7724c30d81bd3b8ba69f20c89753699a994b82bf6ae26925,484a851b92f503bdc4c28801003b2886980feebea479852fa9734dc82d176029,005740bfc12e8af70d5230c872be782a3201312108579c7461780ef590268168,f9f75e886f9f88a3ba0809ae60accd3de67ab0ce5ba3436524c5bf666dd3b1dc,0b5fe301668c691ba7310038a612e01b717f20062dd19c1a4552edb7b0037ce1,77e739069bedab7311ba06ad9fbd0c52fb5a09d9ffa21a31deca925b09773fbe,eddfa367686cacef732e2bda97ff2357fc8177997a89d94b1aa0b7e7a68fb23b,294bbe6ae9df2b402d93536ef7b741e0ccc7527f7d51a09ee50606b30491388f,8abfa5881954da4848d720847f3b4f1577682cf5738827388bf418f2487f4852]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[66386332613461343834343561336339663133383939396236326364323937336632633066386535643366306363383832366537333736393534646339363732,63617264616e6f,6572676f,616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d36,39685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47,000000012a05f200,000000001dcd6500,00000000001e8480,617373657431703430723065756e32616c737a6c78686a376b3475796c796134636a35346c786b6a6a6d736d,657267,33353430333363663063393833616264666463306234346165643562636436633666303963343065613133643062393838663938386331346337373832363238,00000000007fc062]"
},
"R6": {
"serializedValue": "0e20203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921",
"sigmaType": "Coll[SByte]",
"renderedValue": "203ace1f2606730afc938bf9a38d991bae1f99bc84a7ef66e850d66005a9d921"
}
}
},
{
"boxId": "036475fea35a8b6b0700fd1899e7cc9d66ef8c2af584207567a1d1456f295f84",
"value": 1500000,
"index": 1,
"spendingProof": "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",
"outputBlockId": "89ceb697066469a0f7ead066964e52bac93e33d40d5373b5272d70f4a8ada53c",
"outputTransactionId": "3883245d9f73827eddfa7e2a83be57c6bc0dd55e609297fa45ce1e6ce21c98f3",
"outputIndex": 0,
"outputGlobalIndex": 26354568,
"outputCreatedAt": 935668,
"outputSettledAt": 935670,
"ergoTree": "100304000e20a96b8049f0741c7255b60cf01954439d2e4b2d19ae7d8ebc688ecb190a33b5380400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LG4ydEj62n9aymRyPCEbkBdzaubgvCWDH2oxHxFBfAUy9GhWDvteDbbUh5qhXxnW8R46qmEiZfkej8gt4kZYvbeobZJADMrWXwFJTsZ17euEcoAp3KDk31Q26okFpgK9SKdi4",
"assets": [
{
"tokenId": "517c91b4ea680166ddd3f67b27b0274c20bbd2aeb82b60eaf5bf5471b37f684a",
"index": 0,
"amount": 10000,
"name": "Rosen Test Wrap Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a050763617264616e6f67616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d360332303004323030303339685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63617264616e6f,616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d36,323030,32303030,39685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47]"
}
}
},
{
"boxId": "ad1722da9f056816719145f1fc4fc1974cfaf722ebc685fa35b7e29fc57c05f5",
"value": 1000000000,
"index": 2,
"spendingProof": "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",
"outputBlockId": "1b84d22dbb5df0d252a7c4b24036febd4a78d17329eefc2c72bdccb56b3f8e14",
"outputTransactionId": "556e3503f196c8576e618040430da1a2336d3a0983f9e924d0216f02857e8df5",
"outputIndex": 0,
"outputGlobalIndex": 26354517,
"outputCreatedAt": 935667,
"outputSettledAt": 935669,
"ergoTree": "100304000e20a96b8049f0741c7255b60cf01954439d2e4b2d19ae7d8ebc688ecb190a33b5380400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LG4ydEj62n9aymRyPCEbkBdzaubgvCWDH2oxHxFBfAUy9GhWDvteDbbUh5qhXxnW8R46qmEiZfkej8gt4kZYvbeobZJADMrWXwFJTsZ17euEcoAp3KDk31Q26okFpgK9SKdi4",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a050763617264616e6f67616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d360731303030303030093230303030303030303339685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63617264616e6f,616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d36,31303030303030,323030303030303030,39685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47]"
}
}
},
{
"boxId": "ebb95c58b854ab6da9199ce6351c87c0760348079145e717d91fe6c1aea33ca7",
"value": 1500000,
"index": 3,
"spendingProof": "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",
"outputBlockId": "1b84d22dbb5df0d252a7c4b24036febd4a78d17329eefc2c72bdccb56b3f8e14",
"outputTransactionId": "df46a8ee8e92d2f2802060e7ef6e56c979a8bde6e63446d6cf60889f63e9180e",
"outputIndex": 0,
"outputGlobalIndex": 26354514,
"outputCreatedAt": 935667,
"outputSettledAt": 935669,
"ergoTree": "100304000e20a96b8049f0741c7255b60cf01954439d2e4b2d19ae7d8ebc688ecb190a33b5380400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LG4ydEj62n9aymRyPCEbkBdzaubgvCWDH2oxHxFBfAUy9GhWDvteDbbUh5qhXxnW8R46qmEiZfkej8gt4kZYvbeobZJADMrWXwFJTsZ17euEcoAp3KDk31Q26okFpgK9SKdi4",
"assets": [
{
"tokenId": "fc6c2070eb004fc08fcde1514dee56b1d0587477748d8af647179b098f52f559",
"index": 0,
"amount": 10000000,
"name": "RsADA",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a050763617264616e6f67616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d360634303030303007323030303030303339685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63617264616e6f,616464723171797267727068647379376c746132726165327075386870356d7732666e7076753873653030727861367a7a6d63347368346779666b646870776671386c6e68356c39353636336430396e337339637275746e63397977616d637671733565356d36,343030303030,32303030303030,39685a785633594e536662437153364745736573374468415653617476616f4e746473694e766b696d504747326338667a6b47]"
}
}
},
{
"boxId": "dff0637ed9c241a48482918c7465874f43176652a9b013b07c9ec6b430abf04c",
"value": 9944300002,
"index": 4,
"spendingProof": "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",
"outputBlockId": "7b5719b0a5eca57d095ed693071328a22826d70e144ffb7881f3549c483ad54f",
"outputTransactionId": "b9fbe692e9cd0108075c6f9e23e1826628a45e7c48c9fa9de48b159e56b8154a",
"outputIndex": 12,
"outputGlobalIndex": 26336311,
"outputCreatedAt": 935209,
"outputSettledAt": 935214,
"ergoTree": "100304000e20a96b8049f0741c7255b60cf01954439d2e4b2d19ae7d8ebc688ecb190a33b5380400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
"address": "nB3L2PD3LG4ydEj62n9aymRyPCEbkBdzaubgvCWDH2oxHxFBfAUy9GhWDvteDbbUh5qhXxnW8R46qmEiZfkej8gt4kZYvbeobZJADMrWXwFJTsZ17euEcoAp3KDk31Q26okFpgK9SKdi4",
"assets": [
{
"tokenId": "fc6c2070eb004fc08fcde1514dee56b1d0587477748d8af647179b098f52f559",
"index": 0,
"amount": 1026300001,
"name": "RsADA",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 1,
"amount": 1566660,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "517c91b4ea680166ddd3f67b27b0274c20bbd2aeb82b60eaf5bf5471b37f684a",
"index": 2,
"amount": 60815,
"name": "Rosen Test Wrap Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "350bff7491aa9bf828a922fd8f50df0191c6ae586cb077d84b9caef5dd96cfbc",
"value": 1100000,
"index": 0,
"outputBlockId": "a7aeaa064590253e9f07e63a64d86b5d08c9508f9da13ccac29723e98eb7a0d6",
"outputTransactionId": "e3f3794c3bfe63a88a2703a2588bce143bdc40fbd06bbdb469bbfaf00cf4eb35",
"outputIndex": 0,
"ergoTree": "100504000400040004000402d802d601c2a7d602b2a5730000ea02d196830301937201c2b2a473010093c272027201938cb2db63087202730200018cb2db6308a77303000198b2e4c6a70510730400ade4c6a7041ad901030ecdee7203",
"address": "MZ4DGXjbMTDYv4wnEPCSzRGp3infV4oBqQvJhnnePTb61wYrGaS2oiNAbesgJphKS3v5tA3cqaEXUdgRP5EsKBihXwSSogs4RNVhhsYyQiYHoWNo3jB7Fm2DDQSVLJZCf41sd",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02db3849f655693c28e3c44ededd546c6c3267b6f90c0f9ad9785061c387ca2e69,0249e1b4b331b93481cc812c024f1f8a198fe078895ad7f03ab890bd4e81fb5907,020e106e606e70e426a19900f42f3210420f53498c9956106d30b1837596dbc451,02ddd718f3080a04c2e9f2016dc13153f65d64da83ccfea433139c89236476e2b7,02e2c106d43c57936310f06d4fea9f6940dbf1c4e32cb99bdd7ac7b7714e545271,032bb38046b67ed49aa6f4d255bbe1c098ff2f7b682f9922a2a376862de266b16e,03c3374d06b092583835a3a93c7acbc6c449656881abff5d6b17df456a7f3d618b,02956d0fd87b81ebe8ea4763a64e126a548adef2eec3a9719683944100cb992bc5,02b980e0cbb817f80163485aea9ce59c3d6249d510733002a9fc6843718a540b07,03d7e6475ef5ceb9b0e9b0cad722c9cbfa3a13e8e94188ac963e11e4e66e9eaa2c]"
},
"R5": {
"serializedValue": "10020e10",
"sigmaType": "Coll[SInt]",
"renderedValue": "[7,8]"
}
}
}
],
"outputs": [
{
"boxId": "aacfda81c46fb0b0efbb375f372ae36e50b09ccd8de932454093640a0f4894aa",
"transactionId": "7b19f95de28698093351cc2e21f527b5a95162d99d84447a5bb1305cb350106d",
"blockId": "ca4fe6d29a54cb5c19605c82f66d6eb337fcc7127f40c01c16fb141a2be04c86",
"value": 300000,
"index": 0,
"globalIndex": 26357024,
"creationHeight": 935716,
"settlementHeight": 935722,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 1,
"amount": 1500,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01209dc9311055af1547a6739d7cdd5e17b75aa7338e8990f41fff40bbbe0d644446",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9dc9311055af1547a6739d7cdd5e17b75aa7338e8990f41fff40bbbe0d644446]"
}
},
"spentTransactionId": "a6847e213224ab08a5918dc3ae1db46e0481dc7a8c4e497b1dd578b841200d55",
"mainChain": true
},
{
"boxId": "19c3f2b4f676d693bb97ffb874b1bdb9329c615e1f3af2e21129b3720d184335",
"transactionId": "7b19f95de28698093351cc2e21f527b5a95162d99d84447a5bb1305cb350106d",
"blockId": "ca4fe6d29a54cb5c19605c82f66d6eb337fcc7127f40c01c16fb141a2be04c86",
"value": 300000,
"index": 1,
"globalIndex": 26357025,
"creationHeight": 935716,
"settlementHeight": 935722,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "1d9a45e047b45a4a4c565ac49e70b5e2f03f625975cbe41912833e9a547d060d",
"index": 0,
"amount": 1,
"name": "Cardano-RWT-V.beta",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "10278c102bf890fdab8ef5111e94053c90b3541bc25b0de2ee8aa6305ccec3de",
"index": 1,
"amount": 1500,
"name": "RSN-V.beta",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"name": "Cardano-RWT-V.beta",
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"sigmaType": "Coll[Coll[SByte]]",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(58,-56,-87,13,10,-88,-59,-59,14,-103,-35,37,-120,-87,-112,-3,55,-75,-45,-82,-25,14,50,-43,98,65,-12,30,-44,-98,-97,3)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(61,-29,117,6,-4,104,93,113,-86,-26,-56,-106,119,31,60,-127,-7,28,-78,124,-45,14,79,125,18,7,107,-78,-91,-70,106,56)\n17: 1\n18: true",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
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"globalIndex": 26357033,
"creationHeight": 935716,
"settlementHeight": 935722,
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"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = SELF.tokens(placeholder[Int](1))._1\n val bool3 = OUTPUTS.slice(placeholder[Int](2), OUTPUTS.size).filter({(box3: Box) => box3.tokens.size > placeholder[Int](3) }).exists(\n {(box3: Box) => box3.tokens.exists({(tuple5: (Coll[Byte], Long)) => tuple5._1 == coll2 }) }\n )\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = box5.tokens\n val bool7 = coll6.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == coll2 })\n if (box1.tokens(placeholder[Int](5))._1 == placeholder[Coll[Byte]](6)) {\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == coll4(placeholder[Int](9)), if (bool7) {\n allOf(Coll[Boolean](coll6(placeholder[Int](10))._1 == coll2, box5.propositionBytes == SELF.propositionBytes))\n } else { placeholder[Boolean](11) }\n )\n )\n )\n } else {(\n val coll8 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n !bool3, box1.propositionBytes == coll8, box1.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._1 == coll4(\n placeholder[Int](14)\n ), if (bool7) {(\n val tuple9 = coll6(placeholder[Int](15))\n allOf(\n Coll[Boolean](\n tuple9._1 == coll2, blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](16), box5.R5[Coll[Coll[Byte]]].isDefined, box5.R6[\n Coll[Byte]\n ].isDefined, box5.R7[Coll[Byte]].get == blake2b256(coll8), box5.R4[Coll[Coll[Byte]]].get == coll4, tuple9._2 == placeholder[Long](17)\n )\n )\n )} else { placeholder[Boolean](18) }\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[8abfa5881954da4848d720847f3b4f1577682cf5738827388bf418f2487f4852]"
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d0b75b,1b1e24,...)))}",
"address": "9g6ytenZVgR3RXYqXUG3vRcXLhmd12VtUKCuecFqL1P18axCErM",
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"ergoTree": "0008cd03cc76f1074a4477cd378329c4e902ee6145add72e9c26c82b4f2255e768d48811",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(cc76f1,d4ffcd,...)))}",
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"mainChain": true
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(91a9ff,14bf8d,...)))}",
"address": "9hZxV3YNSfbCqS6GEses7DhAVSatvaoNtdsiNvkimPGG2c8fzkG",
"assets": [],
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"mainChain": true
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{
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"index": 13,
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"ergoTreeConstants": "0: 0\n1: Coll(-87,107,-128,73,-16,116,28,114,85,-74,12,-16,25,84,67,-99,46,75,45,25,-82,125,-114,-68,104,-114,-53,25,10,51,-75,56)\n2: 0",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n sigmaProp(box1.tokens.exists({(tuple2: (Coll[Byte], Long)) => tuple2._1 == placeholder[Coll[Byte]](1) })) && atLeast(\n box1.R5[Coll[Int]].get(placeholder[Int](2)), box1.R4[Coll[Coll[Byte]]].get.map({(coll2: Coll[Byte]) => proveDlog(decodePoint(coll2)) })\n )\n}",
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"index": 0,
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"name": "Rosen Test Wrap Token",
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"amount": 1036300001,
"name": "RsADA",
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"index": 2,
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"mainChain": true
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{
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"index": 14,
"globalIndex": 26357038,
"creationHeight": 935716,
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"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
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"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)}",
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"spentTransactionId": "a564393d20f996b7a881c0905e90ed8e980954ef4e611ba3bf63fbc68776e7b9",
"mainChain": true
}
],
"size": 6848,
"isUnconfirmed": false
}