Transaction
ID: 2ccca6e525...bc8c
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
49.8 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
152.45 ERG
Tokens:
Loading assets...
Outputs (14)
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:
202.22 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 792,067
Total coins transferred: 202.27 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000184 ERG
Raw Transaction Data
{
"id": "2ccca6e5256dbdfccaf85aaece9539b95f0099ee4930604d1363ee1155debc8c",
"blockId": "d6a1ffd976ed13f3182e3d22a05c934bff6332af708f567a907be594d1954a82",
"inclusionHeight": 971085,
"timestamp": 1680120485466,
"index": 2,
"globalIndex": 4978533,
"numConfirmations": 792067,
"inputs": [
{
"boxId": "35adc3a83d4faac3a4de6ad132c0dc7bb253a0ca5d906f9277620cfc46ece583",
"value": 11000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "5666156e694e05f15c3f790b2c678c6a0eb36e57037f54db20ea70f1de171557",
"outputTransactionId": "25feb6c0c0b5d63c5584127728833c215d62168bdd935428fafe3687d1a13332",
"outputIndex": 0,
"outputGlobalIndex": 27866312,
"outputCreatedAt": 971024,
"outputSettledAt": 971026,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-67,102,62,43,69,125,66,119,20,61,66,-32,-38,-24,33,73,-18,15,41,-119,-44,14,-39,-97,67,86,78,-58,-10,-55,-33,-1)\n3: 1\n4: 0\n5: Coll(101,33,76,-91,63,-65,9,-64,-121,93,113,-10,127,40,-96,71,26,77,109,79,102,-61,-118,-28,123,106,65,126,100,95,104,-3)\n6: 7200\n7: Coll(-93,87,-80,5,86,-23,-23,60,104,-34,26,73,-30,-7,-41,-60,-110,93,-91,-62,118,103,2,-20,73,-79,-91,14,88,40,23,19)",
"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": "21oSXpSmAC6qpaSpnMff4uYgpsaCjJ6q8tnvnE3MGp5QjNrtqGSHjip4VcuDGGeuMVg1RH9dxfWhT4LwJZrnwBvTkztYv4wLTXRz8Cwr9ENigonokQBnQiT7d5GDyzuedPdYVKGezdqDWrL56BWRe9NZgP56x5r7kxw9koHjQFAJ9RJADQrUKyKnvyk9jHmK1auNUik23CMK2SxedeWg1HkEYhrdvucvfyJ6hJZqbMbhuh6uYY5XPXLfJuz6kNNnWXb7pv4FtoNZXnRbx4uZcVjYGLV88pETGTyCTpjK8e1VHxBTyY2zPF4efLnYxkvrG8YT31nn5ctrFtKtbDG5etZeomMT1f73aLS7Fu42cxhzvRouxL",
"assets": [
{
"tokenId": "9410db5b39388c6b515160e7248346d7ec63d5457292326da12a26cc02efb526",
"index": 0,
"amount": 10,
"name": "Ergo-RWT.V-test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[0e83836f818a16766ac7490c5eee7abdc9357e6bb955641ff8ac56412bf576d0,35f401c431c3adcd4675177be89cc05c70a45de782e93dc226c545e38e37b95c,0ea77346ecd826701113ef3596670f85ec0d4a000d37a06a762ba14623f360f3,e8d2e63d683f57b1dc19bd554a316954703b74b1ebf7459f8b9cb8316dc6e6ba,7dc9b5fd90c4343d48baddc8a7df8b005dd25a2765dadcabd6bfdcc337bcc292,ba094ca44078a94c780eb7df8e0e8ddcefda1d819bc026250c327b5f044fc100,549f37b65bf1c38e24132eeebe9053e8c1e8798a622cd0b3eccda1944ce9aad1,307f6f54ca9bd07e1d979beb6d2a35a19ef03339cad45d3f7a3f9aba327799ea,97a2dabcd974d69a07c3a03e20d05a36d13b986ffca5670302997484dd87e247,5cea78cd9e83ad6de5ae2b4a44494507dd74a8c13223621edfc553b902d5bf7e]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63313735326233303463383736313162333964626138356132386564313330306534383263636538353435353439333334663737353463323862393939373234,6572676f,63617264616e6f,396932364c663475326e4e4b4253717a5871436d4865354a5a4278563142374163726876744c48417137546e69573154484259,616464723171783075776d3678737134706c726767307778727770397a39646365736b6477616e683378673973336c38636b617263676d6d746b706c346b3270393370307932716e386e6535656b6e6e7135727a7870786a7868733635326e7873796578307034,0000000005f5e100,0000000002faf080,0000000000013880,657267,6173736574316a7935713561307670737475747135713664386367646d72643471753579656663646e6a677a,38623839633932306165666634373833343231653630633633393662393333306665323965313834323436656332643862623965613338343137323461653230,00000000000ed0f1]"
},
"R6": {
"serializedValue": "0e20fdd14a1fc1c52cdddd322f6cd2e9c6afa050691f0e48784570edd24d4dd2ca20",
"sigmaType": "Coll[SByte]",
"renderedValue": "fdd14a1fc1c52cdddd322f6cd2e9c6afa050691f0e48784570edd24d4dd2ca20"
}
}
},
{
"boxId": "eb798724d80c54844332afaa1aeeeaa33a9926dce7f5deba66cda029315f4a90",
"value": 49804895894,
"index": 1,
"spendingProof": "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",
"outputBlockId": "a428c343666a750ef95d051095a326e7b60c76bd1d5340a2757a9a7e2f3736cd",
"outputTransactionId": "7777d6c29376a9c029b997b2a45f0ed00fd356512da12884c86146b5df1898cd",
"outputIndex": 0,
"outputGlobalIndex": 27859239,
"outputCreatedAt": 970819,
"outputSettledAt": 970821,
"ergoTree": "100304000e20b039e4445337697deaad703fc8d1fcb129c4577e8673394fa2403e54d484eeda0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-80,57,-28,68,83,55,105,125,-22,-83,112,63,-56,-47,-4,-79,41,-60,87,126,-122,115,57,79,-94,64,62,84,-44,-124,-18,-38)\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": "nB3L2PD3LSRBnqR67yQfE5ZFAez3ySUzwouks1yjB696YSzRZ3D9BdFDntw4DAfp7yXKXykxAYE9sSBXmv9PRH1znnAWZAwzb6NDK4pn1S7LTU3omgYnuabg7VkiFxqqdY3bqw7UXeHB4",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "a03470f4a72564608ed1ab258593e988ee4f48882afb0eb3a9541baafbb5014a",
"value": 152451040466,
"index": 2,
"spendingProof": "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",
"outputBlockId": "7759f056ada8f35d9a3b48e85e13903930014a0dafe86bdf494bfc0795c10a0f",
"outputTransactionId": "08158781ec40d594e4ea80037fb047c600ecf366c5fef955b5b0ffd04430e28c",
"outputIndex": 12,
"outputGlobalIndex": 27863192,
"outputCreatedAt": 970901,
"outputSettledAt": 970905,
"ergoTree": "100304000e20b039e4445337697deaad703fc8d1fcb129c4577e8673394fa2403e54d484eeda0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-80,57,-28,68,83,55,105,125,-22,-83,112,63,-56,-47,-4,-79,41,-60,87,126,-122,115,57,79,-94,64,62,84,-44,-124,-18,-38)\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": "nB3L2PD3LSRBnqR67yQfE5ZFAez3ySUzwouks1yjB696YSzRZ3D9BdFDntw4DAfp7yXKXykxAYE9sSBXmv9PRH1znnAWZAwzb6NDK4pn1S7LTU3omgYnuabg7VkiFxqqdY3bqw7UXeHB4",
"assets": [
{
"tokenId": "c59e86ef9d0280de582d6266add18fca339a77dfb321268e83033fe47101dc4d",
"index": 0,
"amount": 499999996599999,
"name": "RST-Cardano-Token.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4ed6449240d166b0e44c529b5bf06d210796473d3811b9aa0e15329599164c24",
"index": 1,
"amount": 44999999996000000,
"name": "RST-ADA.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "51c1745883a62db6cf47f5765bd695317a01e54bcaaaeaa4aab0b517d2f46a24",
"index": 2,
"amount": 99999999979949860,
"name": "RSN.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a1143e81c5ab485a807e6f0f76af1dd70cc5359b29e0b1229d0edfe490d33b67",
"index": 3,
"amount": 906500000,
"name": "Ergo-Token.V-test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "6eccf30dc9e6d40e20f8dddc3d66e7ee45c82216906a2bacf14be9da8a811309",
"value": 1100000,
"index": 0,
"outputBlockId": "e9281ffbb4be4b17869a79f353c926eb9a8db781db891b16f8ab6bbb226ef0ff",
"outputTransactionId": "2d6baff61607166b03da7c68eec2d3ea4611ff88cbf36d964f648f64f8c2cfb8",
"outputIndex": 0,
"ergoTree": "100504000400040004000402d802d601c2a7d602b2a5730000ea02d196830301937201c2b2a473010093c272027201938cb2db63087202730200018cb2db6308a77303000198b2e4c6a70510730400ade4c6a7041ad901030ecdee7203",
"address": "MZ4DGXjbMTDYv4wnEPCSzRGp3infV4oBqQvJhnnePTb61wYrGaS2oiNAbesgJphKS3v5tA3cqaEXUdgRP5EsKBihXwSSogs4RNVhhsYyQiYHoWNo3jB7Fm2DDQSVLJZCf41sd",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[03c236922914cf80be4b642b3ea02f532ceb120a82b7bc5b75a8c2b7dc70810a27,02b1d6b33c5ef442fa140d52352cab3e80780e98a44bcf6826604f100dbe2cbec8,0217b8b16c47f83c6e96324f4d65434cd77aca1ab969878ba8293b87001c4f216f,024df46a0f95903d15cc8c4f390bb3d0f97dee85273591a88575206baf2d54812e,03aa26adb6a56132f52c0919a351b738beee0d2a240d6b5a82eff27a0f662f3459,02d64bd38b103af945c5786dfbd63577779f49e7166e69f622dc5c243dcbbdbab9,024f0556828a51b54a2b17bf9d4cc4c7fd9faa3226513193ae0aeaf9075bad4aca,02a8b0cc627e16301030b1a74fc33d49dd364a2b818d5d25e02b4d9e3bfc1f4aac,03380c129ffb41ccc52dd58a128082ac381bb449ef67d230255eea284255998524,023605f5625c0f1099c5966a58a9291d7a546d432faeb99d88a99fa6b745b1fd31]"
},
"R5": {
"serializedValue": "10020e10",
"sigmaType": "Coll[SInt]",
"renderedValue": "[7,8]"
}
}
}
],
"outputs": [
{
"boxId": "e731259fa6000b7af3f02662a6c3cc82ee8652994badb96fd33665864f1b8bed",
"transactionId": "2ccca6e5256dbdfccaf85aaece9539b95f0099ee4930604d1363ee1155debc8c",
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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": "[0e83836f818a16766ac7490c5eee7abdc9357e6bb955641ff8ac56412bf576d0]"
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"spentTransactionId": "6b99fe0238817b9b5ba501d5f2661b827dbdb5d373338a94be775b557dd29e80",
"mainChain": true
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{
"boxId": "db23f10763f871468129fe9aba0ccab28095bb955354fe97383b57d7ae3796e9",
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"index": 1,
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"creationHeight": 971072,
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"ergoTree": "10130400040004040400040204000e204b1e5bcfbd6763b9cea8411841213611258fabed16293af6aa8cd8200b7e12860404040004000400010104020400040004000e20c2eeb21a772554cc9733586df12f27d2f444f50e623c1f57cf89c09dc5097c5505020101d807d601b2a5730000d6028cb2db6308a773010001d603aeb5b4a57302b1a5d901036391b1db630872037303d9010363aedb63087203d901054d0e938c7205017202d604e4c6a7041ad605b2a5730400d606db63087205d607ae7206d901074d0e938c720701720295938cb2db63087201730500017306d196830301ef7203938cb2db6308b2a473070073080001b2720473090095720796830201938cb27206730a0001720293c27205c2a7730bd801d608c2a7d196830501ef720393c27201720893e4c67201041a7204938cb2db6308b2a4730c00730d0001b27204730e00957207d801d609b27206730f0096830701938c720901720293cbc272057310e6c67205051ae6c67205060e93e4c67205070ecb720893e4c67205041a7204938c72090273117312",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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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"assets": [
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"type": "EIP-004"
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[35f401c431c3adcd4675177be89cc05c70a45de782e93dc226c545e38e37b95c]"
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{
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"index": 2,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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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"index": 0,
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"type": "EIP-004"
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[0ea77346ecd826701113ef3596670f85ec0d4a000d37a06a762ba14623f360f3]"
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"spentTransactionId": "4df26fb82da767656c96f8aa66778898a4ef891c2b361f19373d102bca7409a8",
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{
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"index": 3,
"globalIndex": 27871393,
"creationHeight": 971072,
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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]]",
"renderedValue": "[7dc9b5fd90c4343d48baddc8a7df8b005dd25a2765dadcabd6bfdcc337bcc292]"
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"mainChain": true
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"creationHeight": 971072,
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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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"assets": [
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"index": 0,
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"type": "EIP-004"
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"index": 1,
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"serializedValue": "1a0120ba094ca44078a94c780eb7df8e0e8ddcefda1d819bc026250c327b5f044fc100",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[ba094ca44078a94c780eb7df8e0e8ddcefda1d819bc026250c327b5f044fc100]"
}
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"mainChain": true
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{
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"index": 6,
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"creationHeight": 971072,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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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"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": "[307f6f54ca9bd07e1d979beb6d2a35a19ef03339cad45d3f7a3f9aba327799ea]"
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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]]",
"renderedValue": "[97a2dabcd974d69a07c3a03e20d05a36d13b986ffca5670302997484dd87e247]"
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"ergoTreeConstants": "0: 0\n1: 0\n2: 2\n3: 0\n4: 1\n5: 0\n6: Coll(75,30,91,-49,-67,103,99,-71,-50,-88,65,24,65,33,54,17,37,-113,-85,-19,22,41,58,-10,-86,-116,-40,32,11,126,18,-122)\n7: 2\n8: 0\n9: 0\n10: 0\n11: true\n12: 1\n13: 0\n14: 0\n15: 0\n16: Coll(-62,-18,-78,26,119,37,84,-52,-105,51,88,109,-15,47,39,-46,-12,68,-11,14,98,60,31,87,-49,-119,-64,-99,-59,9,124,85)\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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"name": "RSN.V-test",
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"renderedValue": "[5cea78cd9e83ad6de5ae2b4a44494507dd74a8c13223621edfc553b902d5bf7e]"
}
},
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{
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d0b75b,1b1e24,...)))}",
"address": "9g6ytenZVgR3RXYqXUG3vRcXLhmd12VtUKCuecFqL1P18axCErM",
"assets": [
{
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"index": 0,
"amount": 1750,
"name": "RSN.V-test",
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"type": "EIP-004"
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],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[4df539cf07c3af9edc1b0621f21a6b9b2f483af7e15790895feb3c042f188d46]"
}
},
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"mainChain": true
},
{
"boxId": "2b14ba20a123d71cfadfc677fa18b23c682e74e9ac61b75e1f0156334b452190",
"transactionId": "2ccca6e5256dbdfccaf85aaece9539b95f0099ee4930604d1363ee1155debc8c",
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"index": 11,
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"creationHeight": 971072,
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"ergoTree": "0008cd03cc76f1074a4477cd378329c4e902ee6145add72e9c26c82b4f2255e768d48811",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(cc76f1,d4ffcd,...)))}",
"address": "9i1rTxaZpLprUkVHpY4YNyooksLuouiKqZ2v1J5nf8xFTXBCVcB",
"assets": [],
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"mainChain": true
},
{
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"index": 12,
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"creationHeight": 971072,
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"ergoTree": "100304000e20b039e4445337697deaad703fc8d1fcb129c4577e8673394fa2403e54d484eeda0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
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"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": "nB3L2PD3LSRBnqR67yQfE5ZFAez3ySUzwouks1yjB696YSzRZ3D9BdFDntw4DAfp7yXKXykxAYE9sSBXmv9PRH1znnAWZAwzb6NDK4pn1S7LTU3omgYnuabg7VkiFxqqdY3bqw7UXeHB4",
"assets": [
{
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"index": 0,
"amount": 499999996599999,
"name": "RST-Cardano-Token.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4ed6449240d166b0e44c529b5bf06d210796473d3811b9aa0e15329599164c24",
"index": 1,
"amount": 44999999996000000,
"name": "RST-ADA.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "51c1745883a62db6cf47f5765bd695317a01e54bcaaaeaa4aab0b517d2f46a24",
"index": 2,
"amount": 99999999979947360,
"name": "RSN.V-test",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a1143e81c5ab485a807e6f0f76af1dd70cc5359b29e0b1229d0edfe490d33b67",
"index": 3,
"amount": 906500000,
"name": "Ergo-Token.V-test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "64d501c216c0a45499375735e6fd607613c41f8c5ccaa94eef678d78399bfacf",
"mainChain": true
},
{
"boxId": "ef242a75dc7d04c02b99574d6d302a7df885752484f125bea8be0866a7c46171",
"transactionId": "2ccca6e5256dbdfccaf85aaece9539b95f0099ee4930604d1363ee1155debc8c",
"blockId": "d6a1ffd976ed13f3182e3d22a05c934bff6332af708f567a907be594d1954a82",
"value": 1100000,
"index": 13,
"globalIndex": 27871403,
"creationHeight": 971072,
"settlementHeight": 971085,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "68b362157ced007d6c8e486ad9e42b8f834d79c20732200e61e1cf6d6c9b5d46",
"mainChain": true
}
],
"size": 5975,
"isUnconfirmed": false
}