Transaction
ID: 2e4cc5d20c...4ac0
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.320832376 ERG
Outputs (12)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0003 ERG
Tokens:
0
Unspent
Unspent
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.159266188 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.159266188 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 168,174
Total coins transferred: 0.330832376 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000262 ERG
Raw Transaction Data
{
"id": "2e4cc5d20c366fc4c4fc5a89823aa66ff5753a788da8c3e9f58e30771ff44ac0",
"blockId": "a14e1abe7c4b03bfecc789be5d45052c740772184f9b2b4c897d575ded7935cc",
"inclusionHeight": 1593201,
"timestamp": 1755515557198,
"index": 22,
"globalIndex": 9367019,
"numConfirmations": 168174,
"inputs": [
{
"boxId": "21f44df1dbcc43be0b38055e04bb86975f7aa52148d5a92b7c2bec790ddd10e6",
"value": 10000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "43a51fee995d295a56b59e42eac9fc89242bb8dc38b0addf959e1191e4ef9b85",
"outputTransactionId": "ff2120f75bee8c849f21af06988f37f500953aa2851d28de26e9a7ddddf11942",
"outputIndex": 0,
"outputGlobalIndex": 49406068,
"outputCreatedAt": 1588919,
"outputSettledAt": 1588921,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: Coll(-80,14,-17,-45,-25,-25,-4,-62,78,17,-85,54,-86,-26,-125,-73,70,-62,-26,40,-71,57,90,-36,0,53,98,-45,20,11,44,-87)\n10: 1\n11: 0\n12: Coll(-78,12,95,-2,-58,0,-102,-82,-96,-37,-25,-70,-1,-118,-69,-84,-20,115,-9,-91,-54,25,64,-2,-86,13,90,2,105,-88,-57,44)\n13: 10\n14: Coll(9,-81,-23,48,20,-10,-106,10,-86,-61,7,28,-111,-102,-31,-125,0,-15,92,117,-92,109,-45,-78,47,-79,-8,-64,30,101,-9,91)",
"ergoTreeScript": "{\n val i1 = SELF.R7[Int].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == SELF.tokens(placeholder[Int](2))._1)\n }).slice(placeholder[Int](3), i1)\n val coll3 = OUTPUTS(placeholder[Int](4)).propositionBytes\n val coll4 = blake2b256(coll3)\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll2.size == i1, SELF.R4[Coll[Byte]].get == blake2b256(\n coll2.map({(box5: Box) => box5.R4[Coll[Byte]].get }).fold(Coll[Byte](), {(tuple5: (Coll[Byte], Coll[Byte])) => tuple5._1.append(tuple5._2) })\n ), coll2.forall(\n {(box5: Box) =>\n ((box5.propositionBytes == coll3) && (box5.tokens(placeholder[Int](5))._1 == SELF.tokens(placeholder[Int](6))._1)) && (\n box5.tokens(placeholder[Int](7))._2 == SELF.tokens(placeholder[Int](8))._2 / i1.toLong\n )\n }\n ), if (coll4 == placeholder[Coll[Byte]](9)) {\n allOf(\n Coll[Boolean](\n INPUTS(placeholder[Int](10)).tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), HEIGHT - placeholder[Int](13) >= SELF.creationInfo._1\n )\n )\n } else {\n allOf(\n Coll[Boolean](INPUTS.exists({(box5: Box) => blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](14) }), coll4 == SELF.R6[Coll[Byte]].get)\n )\n }\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "b5c6663aadb8491819a0505e8fa90d9c2fe57375c52b0fca85dedcf6f1522a71",
"index": 0,
"amount": 5000,
"name": "RosenBinanceRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207cf529eaa39754129259918593a06816d7d02e531ebe15b0091bd8f0270fe393",
"sigmaType": "Coll[SByte]",
"renderedValue": "7cf529eaa39754129259918593a06816d7d02e531ebe15b0091bd8f0270fe393"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[307863636137623364383832633334663462343562643130353439336230383236653535303166326462383235356331326630383864366234376561336234336161,62696e616e6365,6572676f,307830646538316237326233363665633966303031353834383935366161646536653234633038316162,396647727a45376735537a5972387552474356787632556a6245734d64573650726656544b4259355a77437956783155335558,0000000000139e54,00000000000ae62e,000000000008b825,626e62,38326637636563366436383265386130643936356536643933646536366563313839333366373231383163353961356438353830326630666532616663393863,307835663034653666313635643165313765653639373337336663353064653137356330393135666139623562353266326163323130613265303739383863346564,00000000036ad06b]"
},
"R6": {
"serializedValue": "0e200f8f5b933bef08b4ae2b4155045fc50a3eb08a35c30aa76f05377840bf0041ca",
"sigmaType": "Coll[SByte]",
"renderedValue": "0f8f5b933bef08b4ae2b4155045fc50a3eb08a35c30aa76f05377840bf0041ca"
},
"R7": {
"serializedValue": "040a",
"sigmaType": "SInt",
"renderedValue": "5"
}
}
},
{
"boxId": "54719ecbf21832dfd2a08c34d1fcfadc7306d8203a17701b570e913da1dbc82f",
"value": 320832376,
"index": 1,
"spendingProof": "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",
"outputBlockId": "c0baa643bddce87e026a451966d7bafc51afab54bc181ec185f00b71ffa4e2c2",
"outputTransactionId": "c9ba6e40c29f6621e58aa066023992e7362e46d023ec141bb26c4aeb6f856126",
"outputIndex": 9,
"outputGlobalIndex": 49375430,
"outputCreatedAt": 1587596,
"outputSettledAt": 1587601,
"ergoTree": "100304000e20a2d7f41b79f98bcaef08214b9e6bf0f3b803e446a9ef5949da799739555165aa0400d801d601b2db6501fe730000ea02d1aedb63087201d901024d0e938c720201730198b2e4c672010510730200ade4c67201041ad901020ecdee7202",
"ergoTreeConstants": "0: 0\n1: Coll(-94,-41,-12,27,121,-7,-117,-54,-17,8,33,75,-98,107,-16,-13,-72,3,-28,70,-87,-17,89,73,-38,121,-105,57,85,81,101,-86)\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": "nB3L2PD3L6537eX5AD1cyBwCejh2jt8nMhuonRWUSfpS43fakUpHT1uZyioPnVQ5EJdVPPskaWygfdxiDqbv3js6LR4TDkJXpRdKDm3Kk2x1cUmvy1ma9cD9H8tap7rRNWcMnJD75fptM",
"assets": [
{
"tokenId": "36cd0ff2a2e12fd9ede563b07808684dbe6bb4b85ce831b92c23cc8322ca784c",
"index": 0,
"amount": 854,
"name": "Euclid",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "45c1c80de3ca1c0f0d21cb9862032894496671071aa923289c6dee1576478e23",
"index": 1,
"amount": 30910,
"name": "Foxtrot",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "21d2cd3c488d530bb7d2c8f3e9c1f495ee5a4f30ab798b83b481c978ece75f83",
"index": 2,
"amount": 1072723433652,
"name": "rpnDoge",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "01c4809f78c0210e4d1406e025abf27ef8df51639355184e8ac891fa9e6d201b",
"index": 3,
"amount": 8,
"name": "Avicenna",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "d8ed061f2eb0a50ad7db8970e347356247faefe8ec5c3c786b0f7b55a5279465",
"index": 4,
"amount": 5435629433,
"name": "rpnAoS",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "b2dcea48caf0e73309138d659f6eb69d7ec8793dee989670c72dd4ffde7ebeb3",
"index": 5,
"amount": 5435943572,
"name": "rpnBTC",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "08779df8d22fe096de6b382264af0ed6859326a47212484fffffe3fb212d7a1f",
"index": 6,
"amount": 24461047423,
"name": "rpnADA",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "bbcb0dc09acb34c09d767aa43683ff2a360fdb4496344988ea10ff5d93ac348a",
"index": 7,
"amount": 139500,
"name": "eRSN-Pandora",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "6cf0dd0ebd2c791c2aa8c2a083c16d15fc0e7b609d1dbddb553f319754acfcc1",
"index": 8,
"amount": 65231284862,
"name": "rpnETH",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "82f7cec6d682e8a0d965e6d93de66ec18933f72181c59a5d85802f0fe2afc98c",
"index": 9,
"amount": 108718788971,
"name": "rpnBNB",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "d752bede1a85891fff344604431fd6dc30ba685b382f2e0fe15da8141d36e34e",
"index": 10,
"amount": 72,
"name": "RSN-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "14ae6f77e133093b899493bc79a41e09a2f720294349059d9d11a6dd863c0a5c",
"value": 1100000,
"index": 0,
"outputBlockId": "7fe8cc68cce31821ec041885d336e1de47642c1aa1053db4eabd83e0592bd41b",
"outputTransactionId": "c4fce7f3470e36d086d290ae64cdf7f723a095a33df5c8e33ebe06483feaf3d3",
"outputIndex": 0,
"ergoTree": "100804000400040004000400040004020402d802d601b2db6308b2a5730000730100d602b2db6308a7730200ea02d19683030193b1b5a4d9010363d801d605db63087203ed91b172057303938cb27205730400018cb2db6308a7730500017306938c7201018c720201938c7201028c72020298b2e4c6a70510730700ade4c6a7041ad901030ecdee7203",
"address": "3FBpC6dt4xNpexUbLSZDR4YbuMWwLyKDUjbnHPCQf6VpUfqqLGzQ6P6uKkfoF1Eudh9YSU9uTEwYYJ3J8hDERT2mhM6wvCciz4HvZPLMUtdjeg5mCtJMyi6Wy2wTeQQ6UxyuwKCNGxU669QN1HNz7MF5JMg1xy84cEFVcTCcU2rKqiYpHNotatUq6uP6K3fAraF",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1a06210361cddbc4a332f3dfc8b9b8a8850c63d737f6f0782a700aac7f0a9c15c5822d3e2103b04238bbacd33f2200b534b4e64e51e54d41983713786024e4158c7ddcdbc07421025c5cdbfefe114a69d3fc476b0ee0ef337cdd857c0dec0020755510ffa64ce3a721032ad9cb72e098195233335bed22f091018fb83e22c3899b39682365a940eeee8421024e1a4a35b076e0fcc4c72dcf612e710a294d3101325a22a14ee4357e6b8f0cf721026be313e8ec5d06cd07fbee24a2a3d36019bfdb0b4928889aef9314ae74a04c54",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[0361cddbc4a332f3dfc8b9b8a8850c63d737f6f0782a700aac7f0a9c15c5822d3e,03b04238bbacd33f2200b534b4e64e51e54d41983713786024e4158c7ddcdbc074,025c5cdbfefe114a69d3fc476b0ee0ef337cdd857c0dec0020755510ffa64ce3a7,032ad9cb72e098195233335bed22f091018fb83e22c3899b39682365a940eeee84,024e1a4a35b076e0fcc4c72dcf612e710a294d3101325a22a14ee4357e6b8f0cf7,026be313e8ec5d06cd07fbee24a2a3d36019bfdb0b4928889aef9314ae74a04c54]"
},
"R5": {
"serializedValue": "1002080a",
"sigmaType": "Coll[SInt]",
"renderedValue": "[4,5]"
}
}
}
],
"outputs": [
{
"boxId": "3533e0c01392e0454916e86a0c74688afa0e3b895ac4b180cd2f09048056eeba",
"transactionId": "2e4cc5d20c366fc4c4fc5a89823aa66ff5753a788da8c3e9f58e30771ff44ac0",
"blockId": "a14e1abe7c4b03bfecc789be5d45052c740772184f9b2b4c897d575ded7935cc",
"value": 2000000,
"index": 0,
"globalIndex": 49521264,
"creationHeight": 1588928,
"settlementHeight": 1593201,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\n8: 3\n9: 0\n10: 2\n11: 1\n12: 0\n13: 1\n14: 2\n15: 0\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: Coll(31,96,68,30,-44,31,-68,-55,41,-73,77,-57,-108,54,-19,-44,-79,-80,-57,-101,24,95,124,34,-59,-18,-3,-87,-7,-36,106,-33)\n23: 2\n24: 0",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.R4[Coll[Byte]].get\n val l6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n ((coll8.size > placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == SELF.tokens(placeholder[Int](4))._1)) && (box6.propositionBytes == SELF.propositionBytes)\n }).map({(box6: Box) => box6.tokens(placeholder[Int](5))._2 }).fold(placeholder[Long](6), {(tuple6: (Long, Long)) => tuple6._1 + tuple6._2 })\n if (coll4 == placeholder[Coll[Byte]](7)) {(\n val tuple7 = INPUTS(placeholder[Int](8)).tokens(placeholder[Int](9))\n val box8 = OUTPUTS(placeholder[Int](10))\n val coll9 = box8.tokens\n val l10 = coll2(placeholder[Int](11))._2 - INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._2\n sigmaProp(\n allOf(\n Coll[Boolean](\n tuple7._1 == coll5, tuple7._2 >= placeholder[Long](14), if ((coll9.size > placeholder[Int](15)) && (\n coll9(placeholder[Int](16))._1 == SELF.tokens(placeholder[Int](17))._1\n )) {\n allOf(Coll[Boolean](l6 - l10 == coll9(placeholder[Int](18))._2, box8.propositionBytes == SELF.propositionBytes, coll5 == box8.R4[Coll[Byte]].get))\n } else { l6 == l10 }\n )\n )\n )\n )} else {(\n val coll7 = SELF.tokens(placeholder[Int](19))._1\n val box8 = OUTPUTS(placeholder[Int](20))\n val tuple9 = box8.tokens(placeholder[Int](21))\n val coll10 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll4 == coll7, tuple9._2 == l6 - tuple3._2, tuple9._1 == coll7, blake2b256(box8.propositionBytes) == placeholder[Coll[Byte]](22), box8.R5[\n Coll[Byte]\n ].isDefined, box8.R6[Coll[Byte]].isDefined, box8.R7[Coll[Byte]].get == blake2b256(coll10), box8.R4[\n Coll[Byte]\n ].get == coll5, box1.propositionBytes == coll10, box1.R4[Coll[Byte]].get == coll5, OUTPUTS(placeholder[Int](23)).tokens(\n placeholder[Int](24)\n )._1 == coll5\n )\n )\n )\n )}\n}",
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"name": "RosenBinanceRWT-Pandora",
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"amount": 7000,
"name": "eRSN-Pandora",
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"sigmaType": "Coll[SByte]",
"renderedValue": "de4d99b087f4df95c0b53ed0c0af8b49c556c8996e5449ca7392eb4941792815"
}
},
"spentTransactionId": "3eb9c96cb25763d9a8c06fa5705655364a7e623c8cdd259b31776ca0dddff7c5",
"mainChain": true
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{
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\n8: 3\n9: 0\n10: 2\n11: 1\n12: 0\n13: 1\n14: 2\n15: 0\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: Coll(31,96,68,30,-44,31,-68,-55,41,-73,77,-57,-108,54,-19,-44,-79,-80,-57,-101,24,95,124,34,-59,-18,-3,-87,-7,-36,106,-33)\n23: 2\n24: 0",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.R4[Coll[Byte]].get\n val l6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n ((coll8.size > placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == SELF.tokens(placeholder[Int](4))._1)) && (box6.propositionBytes == SELF.propositionBytes)\n }).map({(box6: Box) => box6.tokens(placeholder[Int](5))._2 }).fold(placeholder[Long](6), {(tuple6: (Long, Long)) => tuple6._1 + tuple6._2 })\n if (coll4 == placeholder[Coll[Byte]](7)) {(\n val tuple7 = INPUTS(placeholder[Int](8)).tokens(placeholder[Int](9))\n val box8 = OUTPUTS(placeholder[Int](10))\n val coll9 = box8.tokens\n val l10 = coll2(placeholder[Int](11))._2 - INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._2\n sigmaProp(\n allOf(\n Coll[Boolean](\n tuple7._1 == coll5, tuple7._2 >= placeholder[Long](14), if ((coll9.size > placeholder[Int](15)) && (\n coll9(placeholder[Int](16))._1 == SELF.tokens(placeholder[Int](17))._1\n )) {\n allOf(Coll[Boolean](l6 - l10 == coll9(placeholder[Int](18))._2, box8.propositionBytes == SELF.propositionBytes, coll5 == box8.R4[Coll[Byte]].get))\n } else { l6 == l10 }\n )\n )\n )\n )} else {(\n val coll7 = SELF.tokens(placeholder[Int](19))._1\n val box8 = OUTPUTS(placeholder[Int](20))\n val tuple9 = box8.tokens(placeholder[Int](21))\n val coll10 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll4 == coll7, tuple9._2 == l6 - tuple3._2, tuple9._1 == coll7, blake2b256(box8.propositionBytes) == placeholder[Coll[Byte]](22), box8.R5[\n Coll[Byte]\n ].isDefined, box8.R6[Coll[Byte]].isDefined, box8.R7[Coll[Byte]].get == blake2b256(coll10), box8.R4[\n Coll[Byte]\n ].get == coll5, box1.propositionBytes == coll10, box1.R4[Coll[Byte]].get == coll5, OUTPUTS(placeholder[Int](23)).tokens(\n placeholder[Int](24)\n )._1 == coll5\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[SByte]",
"renderedValue": "06c057f46b6993cd064eab41ebf79b0174f8ae1cab2f3f5166e570b95ade9d85"
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{
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\n8: 3\n9: 0\n10: 2\n11: 1\n12: 0\n13: 1\n14: 2\n15: 0\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: Coll(31,96,68,30,-44,31,-68,-55,41,-73,77,-57,-108,54,-19,-44,-79,-80,-57,-101,24,95,124,34,-59,-18,-3,-87,-7,-36,106,-33)\n23: 2\n24: 0",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.R4[Coll[Byte]].get\n val l6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n ((coll8.size > placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == SELF.tokens(placeholder[Int](4))._1)) && (box6.propositionBytes == SELF.propositionBytes)\n }).map({(box6: Box) => box6.tokens(placeholder[Int](5))._2 }).fold(placeholder[Long](6), {(tuple6: (Long, Long)) => tuple6._1 + tuple6._2 })\n if (coll4 == placeholder[Coll[Byte]](7)) {(\n val tuple7 = INPUTS(placeholder[Int](8)).tokens(placeholder[Int](9))\n val box8 = OUTPUTS(placeholder[Int](10))\n val coll9 = box8.tokens\n val l10 = coll2(placeholder[Int](11))._2 - INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._2\n sigmaProp(\n allOf(\n Coll[Boolean](\n tuple7._1 == coll5, tuple7._2 >= placeholder[Long](14), if ((coll9.size > placeholder[Int](15)) && (\n coll9(placeholder[Int](16))._1 == SELF.tokens(placeholder[Int](17))._1\n )) {\n allOf(Coll[Boolean](l6 - l10 == coll9(placeholder[Int](18))._2, box8.propositionBytes == SELF.propositionBytes, coll5 == box8.R4[Coll[Byte]].get))\n } else { l6 == l10 }\n )\n )\n )\n )} else {(\n val coll7 = SELF.tokens(placeholder[Int](19))._1\n val box8 = OUTPUTS(placeholder[Int](20))\n val tuple9 = box8.tokens(placeholder[Int](21))\n val coll10 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll4 == coll7, tuple9._2 == l6 - tuple3._2, tuple9._1 == coll7, blake2b256(box8.propositionBytes) == placeholder[Coll[Byte]](22), box8.R5[\n Coll[Byte]\n ].isDefined, box8.R6[Coll[Byte]].isDefined, box8.R7[Coll[Byte]].get == blake2b256(coll10), box8.R4[\n Coll[Byte]\n ].get == coll5, box1.propositionBytes == coll10, box1.R4[Coll[Byte]].get == coll5, OUTPUTS(placeholder[Int](23)).tokens(\n placeholder[Int](24)\n )._1 == coll5\n )\n )\n )\n )}\n}",
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"name": "RosenBinanceRWT-Pandora",
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"type": "EIP-004"
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"sigmaType": "Coll[SByte]",
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\n8: 3\n9: 0\n10: 2\n11: 1\n12: 0\n13: 1\n14: 2\n15: 0\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: Coll(31,96,68,30,-44,31,-68,-55,41,-73,77,-57,-108,54,-19,-44,-79,-80,-57,-101,24,95,124,34,-59,-18,-3,-87,-7,-36,106,-33)\n23: 2\n24: 0",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.R4[Coll[Byte]].get\n val l6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n ((coll8.size > placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == SELF.tokens(placeholder[Int](4))._1)) && (box6.propositionBytes == SELF.propositionBytes)\n }).map({(box6: Box) => box6.tokens(placeholder[Int](5))._2 }).fold(placeholder[Long](6), {(tuple6: (Long, Long)) => tuple6._1 + tuple6._2 })\n if (coll4 == placeholder[Coll[Byte]](7)) {(\n val tuple7 = INPUTS(placeholder[Int](8)).tokens(placeholder[Int](9))\n val box8 = OUTPUTS(placeholder[Int](10))\n val coll9 = box8.tokens\n val l10 = coll2(placeholder[Int](11))._2 - INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._2\n sigmaProp(\n allOf(\n Coll[Boolean](\n tuple7._1 == coll5, tuple7._2 >= placeholder[Long](14), if ((coll9.size > placeholder[Int](15)) && (\n coll9(placeholder[Int](16))._1 == SELF.tokens(placeholder[Int](17))._1\n )) {\n allOf(Coll[Boolean](l6 - l10 == coll9(placeholder[Int](18))._2, box8.propositionBytes == SELF.propositionBytes, coll5 == box8.R4[Coll[Byte]].get))\n } else { l6 == l10 }\n )\n )\n )\n )} else {(\n val coll7 = SELF.tokens(placeholder[Int](19))._1\n val box8 = OUTPUTS(placeholder[Int](20))\n val tuple9 = box8.tokens(placeholder[Int](21))\n val coll10 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll4 == coll7, tuple9._2 == l6 - tuple3._2, tuple9._1 == coll7, blake2b256(box8.propositionBytes) == placeholder[Coll[Byte]](22), box8.R5[\n Coll[Byte]\n ].isDefined, box8.R6[Coll[Byte]].isDefined, box8.R7[Coll[Byte]].get == blake2b256(coll10), box8.R4[\n Coll[Byte]\n ].get == coll5, box1.propositionBytes == coll10, box1.R4[Coll[Byte]].get == coll5, OUTPUTS(placeholder[Int](23)).tokens(\n placeholder[Int](24)\n )._1 == coll5\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[SByte]",
"renderedValue": "77ceb05d4a8adb83b8fc29f497e1907215fe58000b602d60e0ceb53252853d82"
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"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\n8: 3\n9: 0\n10: 2\n11: 1\n12: 0\n13: 1\n14: 2\n15: 0\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: Coll(31,96,68,30,-44,31,-68,-55,41,-73,77,-57,-108,54,-19,-44,-79,-80,-57,-101,24,95,124,34,-59,-18,-3,-87,-7,-36,106,-33)\n23: 2\n24: 0",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.R4[Coll[Byte]].get\n val l6 = INPUTS.filter({(box6: Box) =>\n val coll8 = box6.tokens\n ((coll8.size > placeholder[Int](2)) && (coll8(placeholder[Int](3))._1 == SELF.tokens(placeholder[Int](4))._1)) && (box6.propositionBytes == SELF.propositionBytes)\n }).map({(box6: Box) => box6.tokens(placeholder[Int](5))._2 }).fold(placeholder[Long](6), {(tuple6: (Long, Long)) => tuple6._1 + tuple6._2 })\n if (coll4 == placeholder[Coll[Byte]](7)) {(\n val tuple7 = INPUTS(placeholder[Int](8)).tokens(placeholder[Int](9))\n val box8 = OUTPUTS(placeholder[Int](10))\n val coll9 = box8.tokens\n val l10 = coll2(placeholder[Int](11))._2 - INPUTS(placeholder[Int](12)).tokens(placeholder[Int](13))._2\n sigmaProp(\n allOf(\n Coll[Boolean](\n tuple7._1 == coll5, tuple7._2 >= placeholder[Long](14), if ((coll9.size > placeholder[Int](15)) && (\n coll9(placeholder[Int](16))._1 == SELF.tokens(placeholder[Int](17))._1\n )) {\n allOf(Coll[Boolean](l6 - l10 == coll9(placeholder[Int](18))._2, box8.propositionBytes == SELF.propositionBytes, coll5 == box8.R4[Coll[Byte]].get))\n } else { l6 == l10 }\n )\n )\n )\n )} else {(\n val coll7 = SELF.tokens(placeholder[Int](19))._1\n val box8 = OUTPUTS(placeholder[Int](20))\n val tuple9 = box8.tokens(placeholder[Int](21))\n val coll10 = SELF.propositionBytes\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll4 == coll7, tuple9._2 == l6 - tuple3._2, tuple9._1 == coll7, blake2b256(box8.propositionBytes) == placeholder[Coll[Byte]](22), box8.R5[\n Coll[Byte]\n ].isDefined, box8.R6[Coll[Byte]].isDefined, box8.R7[Coll[Byte]].get == blake2b256(coll10), box8.R4[\n Coll[Byte]\n ].get == coll5, box1.propositionBytes == coll10, box1.R4[Coll[Byte]].get == coll5, OUTPUTS(placeholder[Int](23)).tokens(\n placeholder[Int](24)\n )._1 == coll5\n )\n )\n )\n )}\n}",
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"sigmaType": "Coll[SByte]",
"renderedValue": "b8401bc86e06e507cc93b311ff85321f4d9430b0942f9956d2ad0509bc02dece"
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"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6374c2,7e7f67,...)))}",
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"sigmaType": "Coll[SByte]",
"renderedValue": ""
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"mainChain": true
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{
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(c5fc06,b3e6b2,...)))}",
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{
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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}",
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{
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}
],
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}