Transaction
ID: fafafb2c80...946b
Inputs (92)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00101 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001020304 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00595 ERG
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.180030304 ERG
Tokens:
273,000
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0039 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00205 ERG
Transaction Details
Confirmations: 303,706
Total coins transferred: 0.185980304 ERG
Fees: 0.00205 ERG
Fees per byte: 0.000000475 ERG
Raw Transaction Data
{
"id": "fafafb2c8002a399d5492667cec4f5b45496e3a9d9dd8fedbaf31f142a49946b",
"blockId": "73e2f1ae9235ac752c9cc1daa5f78f2594adf14f1e03fdb6992e9289b6e3065c",
"inclusionHeight": 1465765,
"timestamp": 1740078474059,
"index": 23,
"globalIndex": 8610926,
"numConfirmations": 303706,
"inputs": [
{
"boxId": "0b0058adf76ab590d6aaaa6cad1f75beb40a1d7bdc27f2137d7552e52ad502fe",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "b964a0fe804970292edaebc6cac5d280579fd35eb5f4cbdf16f37455c612a60b",
"outputTransactionId": "3098922f50ccbed99e14ba6e951ad4b404baf83c07f64a0323b6380f7b2d5659",
"outputIndex": 1,
"outputGlobalIndex": 46394796,
"outputCreatedAt": 1465751,
"outputSettledAt": 1465753,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ea17a62c608a9475a30f1ba345b82c2dd2c799d27dc4d4c9ba84bf7f282de3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea17a62c608a9475a30f1ba345b82c2dd2c799d27dc4d4c9ba84bf7f282de3d5"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20149848bca1d83714d2f66e2e51cfb30f850c374feca9c9819aea6c793fb82b2c",
"sigmaType": "Coll[SByte]",
"renderedValue": "149848bca1d83714d2f66e2e51cfb30f850c374feca9c9819aea6c793fb82b2c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "71d3009f32a66139645a1f653a752075149a348082cae85923d9bd97ea770828",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "b964a0fe804970292edaebc6cac5d280579fd35eb5f4cbdf16f37455c612a60b",
"outputTransactionId": "ba524d7775d2a0f3bb211d5c7e9cb90a94e1cb6dda4345e7b34652a745804ac3",
"outputIndex": 1,
"outputGlobalIndex": 46394801,
"outputCreatedAt": 1465751,
"outputSettledAt": 1465753,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20059e38729e1d06a02358f46a27bde7d5c77cfe1e8af9922a91b541386c009af2",
"sigmaType": "Coll[SByte]",
"renderedValue": "059e38729e1d06a02358f46a27bde7d5c77cfe1e8af9922a91b541386c009af2"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20cd0d0e1e9bc69af82e2eaf54384c825916301411906371f1e41f1ba85d8b34bd",
"sigmaType": "Coll[SByte]",
"renderedValue": "cd0d0e1e9bc69af82e2eaf54384c825916301411906371f1e41f1ba85d8b34bd"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "90891e13feca899c501015481cfc0b7a4986fbf94c613def4fd6ea8e0ffc76fb",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "b964a0fe804970292edaebc6cac5d280579fd35eb5f4cbdf16f37455c612a60b",
"outputTransactionId": "f423af3c792c6819509b6b3f6c7052836704e95c878db9be6876e72941b92ac1",
"outputIndex": 1,
"outputGlobalIndex": 46394806,
"outputCreatedAt": 1465751,
"outputSettledAt": 1465753,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ddcf399a712ddfea9b6a311d602f88c29475b115e7f995d432459c44f098c035",
"sigmaType": "Coll[SByte]",
"renderedValue": "ddcf399a712ddfea9b6a311d602f88c29475b115e7f995d432459c44f098c035"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20f2e36e017621fbc29c5c131fd9e1d6aefccf7ead8a0c8d593c0418efea233c26",
"sigmaType": "Coll[SByte]",
"renderedValue": "f2e36e017621fbc29c5c131fd9e1d6aefccf7ead8a0c8d593c0418efea233c26"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "06cccbe826fcb9d0ae8787fef157a2a140db4ec573075725e1feb0a4d52aa31c",
"value": 1010000,
"index": 3,
"spendingProof": null,
"outputBlockId": "b964a0fe804970292edaebc6cac5d280579fd35eb5f4cbdf16f37455c612a60b",
"outputTransactionId": "0026f9b1fab705734c5d21c9d5155192d23aeb54e0ccdd0c1633e27576e0dd8f",
"outputIndex": 1,
"outputGlobalIndex": 46394814,
"outputCreatedAt": 1465751,
"outputSettledAt": 1465753,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "3766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20135ef2b020442cfb980975d553b3592a67f5eebc35d75692b89bbb002befdc29",
"sigmaType": "Coll[SByte]",
"renderedValue": "135ef2b020442cfb980975d553b3592a67f5eebc35d75692b89bbb002befdc29"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "b82f38360e2f824bacf0e70b6848d8c08f1ae0c842b41011b741eaf45330a9e4",
"value": 1020304,
"index": 4,
"spendingProof": null,
"outputBlockId": "b964a0fe804970292edaebc6cac5d280579fd35eb5f4cbdf16f37455c612a60b",
"outputTransactionId": "d9672903d58e44dd8079a4386330d82cf66d8181badcb0e92c12898e61a3f5bf",
"outputIndex": 1,
"outputGlobalIndex": 46394819,
"outputCreatedAt": 1465751,
"outputSettledAt": 1465753,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c532a3c38a2d3648edf44a602cfd2f99192c95b3b8e94192a68ed60ac5fbd8c0",
"sigmaType": "Coll[SByte]",
"renderedValue": "c532a3c38a2d3648edf44a602cfd2f99192c95b3b8e94192a68ed60ac5fbd8c0"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20b124d2f63ccccb22f047c6883176f8e239e34822f396ab9b5bee059aed3617fc",
"sigmaType": "Coll[SByte]",
"renderedValue": "b124d2f63ccccb22f047c6883176f8e239e34822f396ab9b5bee059aed3617fc"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "28eaceace0ad27d0600d223a32244e9400f63ab9946420ef873979c8e3812df3",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "d9c0ca2ac2281236326a3f5fe32ffadfffec990b213c3df3adde80cd277dcf7b",
"outputTransactionId": "8eac5d7cc66405605ea3f4f13da209b4edb58901d2bc9b00ca3552731a3c3ac8",
"outputIndex": 1,
"outputGlobalIndex": 46394833,
"outputCreatedAt": 1465753,
"outputSettledAt": 1465755,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200088840f331eedf07d309096c075208670801d18d730ba3fb2bb341bd5c094ca",
"sigmaType": "Coll[SByte]",
"renderedValue": "0088840f331eedf07d309096c075208670801d18d730ba3fb2bb341bd5c094ca"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20d875827d6c4360dd21da214f4884b19465d31a04fce87c525eee454ba1812c65",
"sigmaType": "Coll[SByte]",
"renderedValue": "d875827d6c4360dd21da214f4884b19465d31a04fce87c525eee454ba1812c65"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "f78bd46518f4752bac873ae99728010c2b61962dfcf54c9ec5341540a5d5315b",
"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "7ef2872887c8dac992a7ddd94e8ee3e63e0691c8f10fe85d29e929b0aacccfa0",
"outputTransactionId": "cb100c3c0425ed8445d687277d41fef4f5b24e2f4ff4fe7f9ec879084b661c6a",
"outputIndex": 1,
"outputGlobalIndex": 46397080,
"outputCreatedAt": 1465755,
"outputSettledAt": 1465757,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e203649d2616ef383c8a94cf2a8096647aa3484c3487253c9269e7a650f3a85aaf8",
"sigmaType": "Coll[SByte]",
"renderedValue": "3649d2616ef383c8a94cf2a8096647aa3484c3487253c9269e7a650f3a85aaf8"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "7ef2872887c8dac992a7ddd94e8ee3e63e0691c8f10fe85d29e929b0aacccfa0",
"outputTransactionId": "e4c0f3743bf648d094cbe204b7cb455f724869107fe0089ab76b4426eaa006d0",
"outputIndex": 1,
"outputGlobalIndex": 46397085,
"outputCreatedAt": 1465755,
"outputSettledAt": 1465757,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "58ec05eee5edfec787f4551d48a80005515d0ea3192675ca9a12d50a9b032cc6"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "843c0c5407ee6724cf0586f07fe6712b8230b61601df54fd378796a33f66aca9"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "4379601b002fe92f16bb719b386a1992aa05395fe82183bcc8a80947ad555a2e",
"value": 2000000,
"index": 8,
"spendingProof": null,
"outputBlockId": "7ef2872887c8dac992a7ddd94e8ee3e63e0691c8f10fe85d29e929b0aacccfa0",
"outputTransactionId": "3eb694597ec9303b2f5295c3bc2fcb7289593342bb99ed7365d8cad47093c70e",
"outputIndex": 1,
"outputGlobalIndex": 46397090,
"outputCreatedAt": 1465753,
"outputSettledAt": 1465757,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20742aab33ec1d5b1e29d0d76c31b75d93e60ab3a71f978bcf14e369c2134b3e4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "742aab33ec1d5b1e29d0d76c31b75d93e60ab3a71f978bcf14e369c2134b3e4b"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20c63d78796abcdbf3b3f3c8eb50b0d2fc0084162fbd6817105ba40e7a72ee9cc7",
"sigmaType": "Coll[SByte]",
"renderedValue": "c63d78796abcdbf3b3f3c8eb50b0d2fc0084162fbd6817105ba40e7a72ee9cc7"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "01af448e772c6465e346c2e0653a5be0c93d70129f9a9958521ebbe61281be59",
"value": 2000000,
"index": 9,
"spendingProof": null,
"outputBlockId": "7ef2872887c8dac992a7ddd94e8ee3e63e0691c8f10fe85d29e929b0aacccfa0",
"outputTransactionId": "606a0ddfb1db502ac78e843fcdad3b9d4e2679ff8e2dfe6ccc0bf5fab50f31fb",
"outputIndex": 1,
"outputGlobalIndex": 46397095,
"outputCreatedAt": 1465754,
"outputSettledAt": 1465757,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206696280d3218decd0ba11a5a954542de86db8915e6ed6210b02ad6edb5d15ff5",
"sigmaType": "Coll[SByte]",
"renderedValue": "6696280d3218decd0ba11a5a954542de86db8915e6ed6210b02ad6edb5d15ff5"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e202ad66559639cd6807039214a707ab7e55c519930c18ad7d499ef6122ca40cc5a",
"sigmaType": "Coll[SByte]",
"renderedValue": "2ad66559639cd6807039214a707ab7e55c519930c18ad7d499ef6122ca40cc5a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "9b27938e9fc1f3a7354ecc93f3ee8c4cba7dd94c812566b7966d336197962d95",
"value": 2000000,
"index": 10,
"spendingProof": null,
"outputBlockId": "7f2fb2b48f1e987d4d5664988ba31dfbf759e029cb9a58aacb5d76c2ec56e360",
"outputTransactionId": "4f43baf96d87c4ae8d7f3d1f6d173d86dbed20aee4bf04aab87b92246bd45c66",
"outputIndex": 1,
"outputGlobalIndex": 46397124,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465758,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20b13004a9942db9a9cd5489b88eb80d34e24c0d1a52e6277aa48fdd66574aa4ca",
"sigmaType": "Coll[SByte]",
"renderedValue": "b13004a9942db9a9cd5489b88eb80d34e24c0d1a52e6277aa48fdd66574aa4ca"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "d09a20feb92c561392c1c3d03396c8b9f64ba4387de93707bac6832fe994d599",
"value": 2000000,
"index": 11,
"spendingProof": null,
"outputBlockId": "7f2fb2b48f1e987d4d5664988ba31dfbf759e029cb9a58aacb5d76c2ec56e360",
"outputTransactionId": "6c4b7a20a20fda61cc32edab62a0d1d5d27c52a76dda7e4e085800e422abf4f8",
"outputIndex": 1,
"outputGlobalIndex": 46397129,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465758,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2077b15cdeebe0239ed033afdaf82d79243e646ebf402f0c7e4717637298f6c469",
"sigmaType": "Coll[SByte]",
"renderedValue": "77b15cdeebe0239ed033afdaf82d79243e646ebf402f0c7e4717637298f6c469"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20214efb528d592d61cf08d1f55dc70547b6b22e52ad576d3fd835bddd38cc8570",
"sigmaType": "Coll[SByte]",
"renderedValue": "214efb528d592d61cf08d1f55dc70547b6b22e52ad576d3fd835bddd38cc8570"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e986cbd4dfd183ee4c407f82b9264b492f3d9ee457e18942a1b91f6e111439a3",
"value": 2000000,
"index": 12,
"spendingProof": null,
"outputBlockId": "7f2fb2b48f1e987d4d5664988ba31dfbf759e029cb9a58aacb5d76c2ec56e360",
"outputTransactionId": "d55b161d193504e37a720960272f7c91ebe4f3dbb32017e81f1afe67dd58065f",
"outputIndex": 1,
"outputGlobalIndex": 46397134,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465758,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c",
"sigmaType": "Coll[SByte]",
"renderedValue": "5bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20183e59d532ddd9fb2585566d5aceb9716184cef722c6747f2d9ed0a5338f740f",
"sigmaType": "Coll[SByte]",
"renderedValue": "183e59d532ddd9fb2585566d5aceb9716184cef722c6747f2d9ed0a5338f740f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "03fb7dc5af9c845d432ce9a983d8b65e2bdaaea551ba163737f21c10e3775e87",
"value": 2000000,
"index": 13,
"spendingProof": null,
"outputBlockId": "b76c69db8e9fd8400f3c7126743ae3f38958a31fdee34fa7bd257e3666e6d938",
"outputTransactionId": "b8420ddffb9c42e9de596c2dc1ef82fe45f15d9cb28b4d93fb6fe69224e4888c",
"outputIndex": 1,
"outputGlobalIndex": 46397142,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465759,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f",
"sigmaType": "Coll[SByte]",
"renderedValue": "581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2051e5a3696de6da5bf47ea9b761bf14d495e425308ccf1ffce3f41f46147b44d2",
"sigmaType": "Coll[SByte]",
"renderedValue": "51e5a3696de6da5bf47ea9b761bf14d495e425308ccf1ffce3f41f46147b44d2"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "fb49544187705b420135060850ad32ce81b25dbd66f30af124d3bb5ea4191e4a",
"value": 2000000,
"index": 14,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "03f65c536d9317b9af9fa5653859fbb6bf90fc535711936c55fe2c28c249ca9a",
"outputIndex": 1,
"outputGlobalIndex": 46397150,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465760,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b188db683fdbacca5a356503878c7a4f017030569aed3dd1b665403f64e245c4",
"sigmaType": "Coll[SByte]",
"renderedValue": "b188db683fdbacca5a356503878c7a4f017030569aed3dd1b665403f64e245c4"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e203e8f794b066ebf42be1928511e0bb0b0c7d69d1db483a179e4bbd2f7401638ee",
"sigmaType": "Coll[SByte]",
"renderedValue": "3e8f794b066ebf42be1928511e0bb0b0c7d69d1db483a179e4bbd2f7401638ee"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "067a37db538f79273c7a9c588a8198d3a024499b8ad6a61b20b2bc42667a4057",
"value": 2000000,
"index": 15,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "12c3c7bf8de7963aa9d2d0daefd21c63c67e7d764cac16482e65c3205a6efebd",
"outputIndex": 1,
"outputGlobalIndex": 46397155,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0ff70804ecefd7694c7279d71436adca777feb13bf94a0028fb497d91098f1f7"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "ea9011f3bba025313aa9f2d5d0bf576bfdf1b7af75a71f81d166176303e58099",
"value": 2000000,
"index": 16,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "3a44851e1cb71670e121ea1d43c9c342d33939db4a19e875dca0bb954a390caa",
"outputIndex": 1,
"outputGlobalIndex": 46397160,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20d364140820b1e4bfced1b692d17a0858965f0843b9a38b697ae53ccbb6ad53c7",
"sigmaType": "Coll[SByte]",
"renderedValue": "d364140820b1e4bfced1b692d17a0858965f0843b9a38b697ae53ccbb6ad53c7"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "5e76dafa9fedb0bd4fc0ff5b6f1d41b81d3b31a8503ee002d677e73c4a46ef3b",
"value": 2000000,
"index": 17,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "608461fc6db1aac192ece5206d85d80be68f0beccccdd1d0309ceedbf26a11cd",
"outputIndex": 1,
"outputGlobalIndex": 46397165,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2050ae9ce5c7a659a4b57c1313a0606055e231e7801e30b0bd90867f14cbc1366b",
"sigmaType": "Coll[SByte]",
"renderedValue": "50ae9ce5c7a659a4b57c1313a0606055e231e7801e30b0bd90867f14cbc1366b"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2069191a110b144511eaeb73deb485e05096ef54ad2cc13fd712ff8e2a4230ba84",
"sigmaType": "Coll[SByte]",
"renderedValue": "69191a110b144511eaeb73deb485e05096ef54ad2cc13fd712ff8e2a4230ba84"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ffd2dd607061a504afb2fcab565498f5b41a971c825427dbc34f16aeaee5813c",
"value": 2000000,
"index": 18,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "68a30a4bb33d0af82c2d85cf784420076f0e1470d6fdb23fdc1beca5424ea151",
"outputIndex": 1,
"outputGlobalIndex": 46397170,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6a572ba3399722fc5020dfe1443990135cd044893c9e7a72056d613232fa61e8"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "4d2cc09ec0887dca4198bada578a00c82a70bd00e9fd336d79de293e087af9e8"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 19,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "8dae3ed8af08cc957e49f12175689f2f9a06e9d54b98ae0ebe32cfe02c0fd3bf",
"outputIndex": 1,
"outputGlobalIndex": 46397175,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "75ddd9e9a8a3f4335fbb317bff875c40b49104fad2564662d8eef0faa6e1f207"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "45f1e55bde7a6e635eb738bcdd3486e51fe1fa78bcca9cd1597212115f6d8593",
"value": 2000000,
"index": 20,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "a14baf71a0ac1983e3d7ad5bfb76f3145da13600228fca5aca80a1ec0e1c9fdb",
"outputIndex": 1,
"outputGlobalIndex": 46397180,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20cd3863c3556e8da87295be7fc2c1d61fd0189a324d323bf60e607553f4a4e2f9",
"sigmaType": "Coll[SByte]",
"renderedValue": "cd3863c3556e8da87295be7fc2c1d61fd0189a324d323bf60e607553f4a4e2f9"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20bb4e151d5d580e1f7a8158d89627c240d221ad51ba61b6a5597cd382a0c14cd0",
"sigmaType": "Coll[SByte]",
"renderedValue": "bb4e151d5d580e1f7a8158d89627c240d221ad51ba61b6a5597cd382a0c14cd0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e96171a466e687f3da7284d33584fd905a7e39b7fa32dfc398a6059e795a6b73",
"value": 2000000,
"index": 21,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "a8c019e93d4a99085f6cde32ca32abef96ee3ed1412d9a6e1b721b863c1610c9",
"outputIndex": 1,
"outputGlobalIndex": 46397185,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207d2f5dd0dce52c5e42b935cb986095bdfac1c6102018f4c715d830e736d96876",
"sigmaType": "Coll[SByte]",
"renderedValue": "7d2f5dd0dce52c5e42b935cb986095bdfac1c6102018f4c715d830e736d96876"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20aed9008d686ff1ded692bce7b5fa744f45b9fb520bc9b75afd2041d4c3013171",
"sigmaType": "Coll[SByte]",
"renderedValue": "aed9008d686ff1ded692bce7b5fa744f45b9fb520bc9b75afd2041d4c3013171"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "b77812292d1505bcb05519fdef2535798956de8c5deb7ba27509fa4de164dd49",
"value": 2000000,
"index": 22,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "d6136d57d3183bafb2137be312fb030562d2b5cc25fd00c3373a8bb37e7d631f",
"outputIndex": 1,
"outputGlobalIndex": 46397190,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32",
"sigmaType": "Coll[SByte]",
"renderedValue": "bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20382295a7448afed7c2250ae092133f184d34f5c7ba189a19f4e6a4ccd32cc308",
"sigmaType": "Coll[SByte]",
"renderedValue": "382295a7448afed7c2250ae092133f184d34f5c7ba189a19f4e6a4ccd32cc308"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "87af92c02f92ebe4d23bdc0e8e2d5fd42085faa252c72f29d3eefc8756c1173d",
"value": 2000000,
"index": 23,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "e5c83ef8b27cc321afcced455cc2ff3728f7349e419dd89b0efde4e836e5e164",
"outputIndex": 1,
"outputGlobalIndex": 46397195,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201a0f3106b93d5720b1d9e423e0a5f69e293bc01f673d28fac737975811322b26",
"sigmaType": "Coll[SByte]",
"renderedValue": "1a0f3106b93d5720b1d9e423e0a5f69e293bc01f673d28fac737975811322b26"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e209478ecbff3b0319194b47c136c5ba349e1b3444052f25b3a4f1a50bb9945119e",
"sigmaType": "Coll[SByte]",
"renderedValue": "9478ecbff3b0319194b47c136c5ba349e1b3444052f25b3a4f1a50bb9945119e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "64bfb7233b61815c630a13be9ff90334b74fd3185d0f4c4d2c76d6858430e357",
"value": 2000000,
"index": 24,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "f65113ff3a247c0f00edba49e9e580e6716b81496605580b4e42184c88f3bef1",
"outputIndex": 1,
"outputGlobalIndex": 46397200,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308",
"sigmaType": "Coll[SByte]",
"renderedValue": "f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e203926207f59dccf9c942b20766908312c930b19e9e1c0cbcbf568c44fed3cae21",
"sigmaType": "Coll[SByte]",
"renderedValue": "3926207f59dccf9c942b20766908312c930b19e9e1c0cbcbf568c44fed3cae21"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "d6aaa180d1f9981e976b5b5a77c7c77405040e1b166068256da6191d8617edc7",
"value": 2000000,
"index": 25,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "2676c0622fe227c814067b0981eef580a47e6ea9f76bcbe8008d3e24db670e31",
"outputIndex": 1,
"outputGlobalIndex": 46397205,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d",
"sigmaType": "Coll[SByte]",
"renderedValue": "f76916ee079267eac485fc60b0c6461e4063ff7e97417919cc24f96b0791ec9d"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e209ef36c004fac481359a0acc580647bdc79f53c35e7c8ac6dd352b1162f04d53c",
"sigmaType": "Coll[SByte]",
"renderedValue": "9ef36c004fac481359a0acc580647bdc79f53c35e7c8ac6dd352b1162f04d53c"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "f6228190c072da98e080dbd731bb032c5a0da5011ba51e3e75302f98e18a6f2d",
"value": 2000000,
"index": 26,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "48c18e13482117a00c2fc28f3e5ee3d74bd0865163312c2c578120bc1cafc7d6",
"outputIndex": 1,
"outputGlobalIndex": 46397210,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d114141aca72e56eab859e29d74690560ac900b38169c4fe21439ee824ddb9cb",
"sigmaType": "Coll[SByte]",
"renderedValue": "d114141aca72e56eab859e29d74690560ac900b38169c4fe21439ee824ddb9cb"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20095ca7d6b0375eecf4429db08a3357fba32f0c0ec53c4dfbff2b6d04b18c3cca",
"sigmaType": "Coll[SByte]",
"renderedValue": "095ca7d6b0375eecf4429db08a3357fba32f0c0ec53c4dfbff2b6d04b18c3cca"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "8ff0141b294940ce789bf17aca3ebf1873e372b06e90ddd5bb6272af941d9fb9",
"value": 2000000,
"index": 27,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "a93944e55840f28d21cde618b665c6ba3b4beeece9e2f010e956d6da421e48da",
"outputIndex": 1,
"outputGlobalIndex": 46397215,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20194f861466cf65effd1a8772e958cdcc2318d6e0d7972d9c9f7b8179b5cd8da8",
"sigmaType": "Coll[SByte]",
"renderedValue": "194f861466cf65effd1a8772e958cdcc2318d6e0d7972d9c9f7b8179b5cd8da8"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "af7ce66b715de42c2c4c3f391a01d205f22fd3b3db9708e076e72f737a6e4e0b",
"value": 2000000,
"index": 28,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "f1b3993b4395d338c7d06c8124fcbf48b3d559a51e79564b1b27ead1b1e0b55b",
"outputIndex": 1,
"outputGlobalIndex": 46397220,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2019b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29",
"sigmaType": "Coll[SByte]",
"renderedValue": "19b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "688464242a27bf9c7461c6f2cdf05c3caae4fc0c26879f73e20284be181d0cf0"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "40a7ace74494be2f426f61dc53e0360b199300cb5b42f77ab4c462e1a3c3021d",
"value": 2000000,
"index": 29,
"spendingProof": null,
"outputBlockId": "0973c37d526a02bcece3d954eaf7720a268b98703cc9b89ba49808345e63a210",
"outputTransactionId": "ed010ae18b91701b81e3b1ea35e0d7c2bce6baf6b90e1ec2ab6ceab929014716",
"outputIndex": 1,
"outputGlobalIndex": 46397225,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465760,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206e3897f1a1c06dd2eeebd4ec9287dc0abd119e7f0a03c7938c181ba21fcddc96",
"sigmaType": "Coll[SByte]",
"renderedValue": "6e3897f1a1c06dd2eeebd4ec9287dc0abd119e7f0a03c7938c181ba21fcddc96"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e204ca658801f79f66d135d1d55d176f802038d8244cee8b80434ce4d10c39fb4ea",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ca658801f79f66d135d1d55d176f802038d8244cee8b80434ce4d10c39fb4ea"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "dbecaa3341ed684cae2f54ca0cadc772139e8854d8ce45a73dbc1954fbad9fdb",
"value": 2000000,
"index": 30,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "0483513c74d77ecc3f13455a811671175f417f9799cbbf7074f5aa49102f90b3",
"outputIndex": 1,
"outputGlobalIndex": 46397233,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2002be1c4ccec3eea820ed799182cd010ad9b830402c83b5ca9aa14658b81d6f08",
"sigmaType": "Coll[SByte]",
"renderedValue": "02be1c4ccec3eea820ed799182cd010ad9b830402c83b5ca9aa14658b81d6f08"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ff99879becf6649020307c3a5135dfbfe8f8a2a77eb91fd0f72c0f7ffbf4bd6b",
"value": 2000000,
"index": 31,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "115b05f6aae8a03667f768e2c0c0ee0622a879260e24c68ffbd7dee79c6b159c",
"outputIndex": 1,
"outputGlobalIndex": 46397238,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2009a22d2ec41eda22d4eb20e2591830b2fe3c9a53cb8df64a9da93e6699ffb306",
"sigmaType": "Coll[SByte]",
"renderedValue": "09a22d2ec41eda22d4eb20e2591830b2fe3c9a53cb8df64a9da93e6699ffb306"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e202ec1041a3b76807bcededf28edd6f17bfe6151b0138f00bf3f419bf2ee0a7873",
"sigmaType": "Coll[SByte]",
"renderedValue": "2ec1041a3b76807bcededf28edd6f17bfe6151b0138f00bf3f419bf2ee0a7873"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "96277e6ec71b9c4c1e7e023b8155b954d1dd4b266fdc81d59a11bcab5655dd72",
"value": 2000000,
"index": 32,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "1a1421a48624c2cc0da971d28b88364bd392cc29a9e8ab4380eb4b72706a1cc9",
"outputIndex": 1,
"outputGlobalIndex": 46397243,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691",
"sigmaType": "Coll[SByte]",
"renderedValue": "916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e206eb5b720e353817f350b9b4b7593a5fedfdf5b28b411883c9ef7e274e362651f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6eb5b720e353817f350b9b4b7593a5fedfdf5b28b411883c9ef7e274e362651f"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3a9e3ecd647b99d7dabec60bf12c1c3b7bd28557fcdf597ff2b7020482d1dd98",
"value": 2000000,
"index": 33,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "2113b8a13027e2653d346c49f12c213e1da317c03986519f37da1e07647a1f0e",
"outputIndex": 1,
"outputGlobalIndex": 46397248,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "dd6e1620c63423f28efdbed8f59fb5109dab5adaa70c0e7dcecc7abb2ae7fa9e"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "11737fb3d17c5915093e18e80b7746d2015376ae1fb6289e6a0c0e6c6ceb1d1f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 34,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "378513c5af6a5e90c212d803ce560907241cebb7190ad129e77bc44c8afd6dd7",
"outputIndex": 1,
"outputGlobalIndex": 46397253,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "e43e14cd752393432876c906d976cfa52b2dabedda878c6dd8373c7f707e6cbf"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8d8b62b0545c65fe4f75436837e7a2acb36841a5f9fd3b9367f30122daad7986"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "738330a77718c2da6c7a67f71844876bfaffba95cfb327f9eb4fae6b5cbb112e",
"value": 2000000,
"index": 35,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "3d969fe4cf5fbf98f2ba98a18bd6d08225d3759caf692a3de9384ccc9591772d",
"outputIndex": 1,
"outputGlobalIndex": 46397258,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5",
"sigmaType": "Coll[SByte]",
"renderedValue": "d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20a5fd627eb3f8e9c8db35a6a7ed5ffae41c25cf390c09d1848c7de15236e6e1ea",
"sigmaType": "Coll[SByte]",
"renderedValue": "a5fd627eb3f8e9c8db35a6a7ed5ffae41c25cf390c09d1848c7de15236e6e1ea"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "b25c382b78ea47885acd9cc98e88ed19e8a6292e7365e34a41097109fd719fe4",
"value": 2000000,
"index": 36,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "51a41976ecaad7012f01e4d6ab02711eeeff2c07862471f7d910a32bb0d40e47",
"outputIndex": 1,
"outputGlobalIndex": 46397263,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20aa7c8b3b2504769432f5dfc91219e733d1b2ae9c88a6e479c2c600170bf5757d",
"sigmaType": "Coll[SByte]",
"renderedValue": "aa7c8b3b2504769432f5dfc91219e733d1b2ae9c88a6e479c2c600170bf5757d"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e208c80724e33319a94a26160b77e6f58bbaf60fe11fd60960261280266aa7ba992",
"sigmaType": "Coll[SByte]",
"renderedValue": "8c80724e33319a94a26160b77e6f58bbaf60fe11fd60960261280266aa7ba992"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "aafd6d6af4a5adbd41deba39727b3c7cec64b87ff40a707b7d9ce0eaf3abfb09",
"value": 2000000,
"index": 37,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "55b77b7f0c6a4a837e348776b94301e401dead32960c4eb7dacc5fe24e785017",
"outputIndex": 1,
"outputGlobalIndex": 46397268,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2039d94126ab6b84bd0de5d562d8b1b1f0b1e2e1e11352afc971812ca155bd01d7",
"sigmaType": "Coll[SByte]",
"renderedValue": "39d94126ab6b84bd0de5d562d8b1b1f0b1e2e1e11352afc971812ca155bd01d7"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e203a539d1a6953ffe2a71829b7ed8f71f5016f189b315e9287dbb1bb8ad4816afc",
"sigmaType": "Coll[SByte]",
"renderedValue": "3a539d1a6953ffe2a71829b7ed8f71f5016f189b315e9287dbb1bb8ad4816afc"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "bc66d7b09a89f126fa81fa9b0d4764bffb1a1b430e8c57b28e7f26e61519a24e",
"value": 2000000,
"index": 38,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "5977c0bff9cd9d0208626ae64079fa93c25a4fa3e9bd44a1cdc931debe237b9f",
"outputIndex": 1,
"outputGlobalIndex": 46397273,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2074d14ee349bc54781627bafddea455bf045eac5941d64e2175704a150b8a070d",
"sigmaType": "Coll[SByte]",
"renderedValue": "74d14ee349bc54781627bafddea455bf045eac5941d64e2175704a150b8a070d"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2065524f9a9434763735e7fb5c9aed39c2d01b0c87634b3b4be8e22d051a17c0e8",
"sigmaType": "Coll[SByte]",
"renderedValue": "65524f9a9434763735e7fb5c9aed39c2d01b0c87634b3b4be8e22d051a17c0e8"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "03b9d47f0d8fa23bbaa66280a560041f3426fecd3a6a77771719db5c0c830400",
"value": 2000000,
"index": 39,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "5c051026506337ad935d40954549dff8f9c4abf56e46eb0a4c4e6accf43e86a7",
"outputIndex": 1,
"outputGlobalIndex": 46397278,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "dc9aaa6c02c4b1db7f949eb7f70ea4d60e696f78ba623234f4aaefd235860cbd"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e20d55a6ccb71e9743c49e96799683c5033e955ca044d44b4610384e3cfadda4459",
"sigmaType": "Coll[SByte]",
"renderedValue": "d55a6ccb71e9743c49e96799683c5033e955ca044d44b4610384e3cfadda4459"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "fb489cd64571bdd55eae13887e585e63e32cab8c768f340167ab9e3e9de02418",
"value": 2000000,
"index": 40,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "82076aa46f53eca567ae762324324056c4319fc5385f8578f0b67b233c936347",
"outputIndex": 1,
"outputGlobalIndex": 46397283,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2099eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0",
"sigmaType": "Coll[SByte]",
"renderedValue": "99eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ce7a1e3bf0f51f88375f69e60ed0103b3c8ee1cdd7c289931b4957a343f4970c"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "6584c2e4b368934d374e4150b306190bf5038a0e0616be7fb173d3b85750100b",
"value": 2000000,
"index": 41,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "8c1db43898e06b36c7b7f6cf4339e5e3032b60d8cf6e04a1e23850f55b103bee",
"outputIndex": 1,
"outputGlobalIndex": 46397288,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fc006570d8d139f226b125ea406665d4023a94f0329b91ad850c72ed3cf41388",
"sigmaType": "Coll[SByte]",
"renderedValue": "fc006570d8d139f226b125ea406665d4023a94f0329b91ad850c72ed3cf41388"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2001542fcc3368723e9d74997181676fa8499bcd51689534bd56e5f8fc63be2b08",
"sigmaType": "Coll[SByte]",
"renderedValue": "01542fcc3368723e9d74997181676fa8499bcd51689534bd56e5f8fc63be2b08"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "667620093319998d82ff4b273330c8ace222be9e5fa7d0fead2b2879b5235564",
"value": 2000000,
"index": 42,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "b1c676f39e474ff13de18f1e5dcb0dc679a8b041f6481d2fc5be595320732ebe",
"outputIndex": 1,
"outputGlobalIndex": 46397293,
"outputCreatedAt": 1465756,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20db8e71a8aa08bc0c7630f53d6189aff5e2c5e6c97d794b7617c0e41701a26c70",
"sigmaType": "Coll[SByte]",
"renderedValue": "db8e71a8aa08bc0c7630f53d6189aff5e2c5e6c97d794b7617c0e41701a26c70"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20668c9b9ea80af14f9210865624a1cb880b507458a458cd3b969fa9870d01e922",
"sigmaType": "Coll[SByte]",
"renderedValue": "668c9b9ea80af14f9210865624a1cb880b507458a458cd3b969fa9870d01e922"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "d0d4e2a4371df9a4d9bd90f0284e601b5c921f21ecbd1454443aa4020b7590dc",
"value": 2000000,
"index": 43,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "d085dd78c93c729d839f0065a5ce0f2c897ce2029bd4f7fa3896b52f8ead833d",
"outputIndex": 1,
"outputGlobalIndex": 46397298,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "da6c926ce60759b4c2f566e6c47ee847a6c67d882413ef06bd4cb37a5d6af4d7"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e20d157fcb25b77455c78806bc49fd5acb76d142ede30b9ce2f4aa20e387dbb83e4",
"sigmaType": "Coll[SByte]",
"renderedValue": "d157fcb25b77455c78806bc49fd5acb76d142ede30b9ce2f4aa20e387dbb83e4"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "0422888dac11550ed8281e60faecd24dd44c250b09faad3cfde7dd8deda3a4bb",
"value": 2000000,
"index": 44,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "d3f6852cb6743a1c4ebba8b2337106a7ca5f59bb46cff5c713e8d6dc3cec78c9",
"outputIndex": 1,
"outputGlobalIndex": 46397303,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206b5101757d087080d80e846662dbdae5bc43f477c35182005eb05fa036ae4040",
"sigmaType": "Coll[SByte]",
"renderedValue": "6b5101757d087080d80e846662dbdae5bc43f477c35182005eb05fa036ae4040"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20002bcee03995bdd65513d6aadea713fc051c9701a38507d659b06263a6cfa051",
"sigmaType": "Coll[SByte]",
"renderedValue": "002bcee03995bdd65513d6aadea713fc051c9701a38507d659b06263a6cfa051"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6df424005cb417db142747279eb4b6a28ba0617a50795734b68be8d1ee741a23",
"value": 2000000,
"index": 45,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "efe6013a34359940794b63193d78d6e0e9c4e540a96135681d59aa9bdab96e9b",
"outputIndex": 1,
"outputGlobalIndex": 46397308,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1f2544ae82ab043f2889c81ac9db7ab9d74bb4af631631b5ef2200879ee7fdb3"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "063f85be94fd4201af80a29eed1914d7657162e7f2d5978eab33de743f2f3a4c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "8cb1ff78588ec003f7a912805aec60092225cf5ced356254c00283a6900bac10",
"value": 2000000,
"index": 46,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "f3ac151ea952f499ef983f54afd6e5c7a7220f4870db944c93fc4cb7d17762bd",
"outputIndex": 1,
"outputGlobalIndex": 46397313,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "38813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b24b0321aef0b2df6c2fc78d52235a670a410485f975ed7bb1e99ee382eae5e9"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "245f0b09fa67af3bd966c8d1dade4725d34bd22e74daf777bee4974901854806",
"value": 2000000,
"index": 47,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "f46cb5d3e9b8c3a9aa2fa93336b7b7eceba4d619dbb594b91cbbb8f4350ccc8e",
"outputIndex": 1,
"outputGlobalIndex": 46397318,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2088708d05bd78d4d8b4195f210903fc8bccb2eacd2c3bba6c8c7302ddba29ca92",
"sigmaType": "Coll[SByte]",
"renderedValue": "88708d05bd78d4d8b4195f210903fc8bccb2eacd2c3bba6c8c7302ddba29ca92"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20e1e2062e5e9b89e0aaa0cf37d52cb15320cdab1a74d4a28916d41e1a0a1e37e7",
"sigmaType": "Coll[SByte]",
"renderedValue": "e1e2062e5e9b89e0aaa0cf37d52cb15320cdab1a74d4a28916d41e1a0a1e37e7"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2dd689447bb759ae22afa9d39a0846ab9c9db5755c34775b3eba5218cc295ff5",
"value": 2000000,
"index": 48,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "fd95966caa728fd8e222c0dc190e1eb675e472a539422934065915590d795381",
"outputIndex": 1,
"outputGlobalIndex": 46397323,
"outputCreatedAt": 1465757,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d82b50d7cd359c35b7aab6fe55999f1d8cc5ec5f671eea0577c39f6f8c691ce4",
"sigmaType": "Coll[SByte]",
"renderedValue": "d82b50d7cd359c35b7aab6fe55999f1d8cc5ec5f671eea0577c39f6f8c691ce4"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20031276b0a58e076d9a12a35c357b4e4dd1b724b11077b587ff86d72bcf43c70b",
"sigmaType": "Coll[SByte]",
"renderedValue": "031276b0a58e076d9a12a35c357b4e4dd1b724b11077b587ff86d72bcf43c70b"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "84af0ffe1611c2077d9bb3e133ac2d9416942138a08384dab460b191ceb83118",
"value": 2000000,
"index": 49,
"spendingProof": null,
"outputBlockId": "630195da18c18d825dadd5931c93769b9f6722fd778a32138a3f2ad106e54870",
"outputTransactionId": "42a669b1f42f1208b23363750101c8efc404e761442c0566a5435731733a7373",
"outputIndex": 1,
"outputGlobalIndex": 46397328,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465761,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20575300d92a22ebd476a6365a414ca4d9f7cd863dabff90f9bec080eeb1c0aa05",
"sigmaType": "Coll[SByte]",
"renderedValue": "575300d92a22ebd476a6365a414ca4d9f7cd863dabff90f9bec080eeb1c0aa05"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "55ef4b0ea95deae548050c1c56f8b1f9f46283bb8b564a9c94e26d6b9c83790a"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "80c665398d18ec7343638c21092fffa6c7eaf34efaa62a23aa2724a4c86cdf24",
"value": 2000000,
"index": 50,
"spendingProof": null,
"outputBlockId": "4b943463a316a9f8de011283cfa36ac572d1e9b505c42a96b0b2a61b77b8cee2",
"outputTransactionId": "0afcd69b2e1069ca41245e48d7cbab9fdc993cfb86216b12a3e51fa6be584a9c",
"outputIndex": 1,
"outputGlobalIndex": 46397336,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465762,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2053e28b29c76583401b17e47678a76aa24b7a84ed4cd26f5766b944b9627636fb",
"sigmaType": "Coll[SByte]",
"renderedValue": "53e28b29c76583401b17e47678a76aa24b7a84ed4cd26f5766b944b9627636fb"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20426598bb263fd822e1b0effda6d1167f31f10bf2cd2338f60c40f3f2d64a27a1",
"sigmaType": "Coll[SByte]",
"renderedValue": "426598bb263fd822e1b0effda6d1167f31f10bf2cd2338f60c40f3f2d64a27a1"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1ef94d18656e2fe45d6b393e9d818cce59eca8e73659c5dad463bafd5513fb9a",
"value": 2000000,
"index": 51,
"spendingProof": null,
"outputBlockId": "4b943463a316a9f8de011283cfa36ac572d1e9b505c42a96b0b2a61b77b8cee2",
"outputTransactionId": "7d27e1fcd218d83962a84936e3e6c9ed8765d79f7f9d658a76bf026de7aded2c",
"outputIndex": 1,
"outputGlobalIndex": 46397341,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465762,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "50578332ebb8fb95c5b1a62410257c9982a0bd25d93b1ae6787ea95bb94e9757"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b03ed9e337118974509cd838059ef7f2e023389ce667f4e87c4b6beed1ec7d5a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 52,
"spendingProof": null,
"outputBlockId": "4b943463a316a9f8de011283cfa36ac572d1e9b505c42a96b0b2a61b77b8cee2",
"outputTransactionId": "a5eb935a0b9114820b21f9186fb0d8d41379a166f7daf7848f6489112788fb8b",
"outputIndex": 1,
"outputGlobalIndex": 46397346,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465762,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1390ca2e1a75a4ee79b796529b11e6770c68b19c1c3c4851d71009554cb3f3d1"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 53,
"spendingProof": null,
"outputBlockId": "4b943463a316a9f8de011283cfa36ac572d1e9b505c42a96b0b2a61b77b8cee2",
"outputTransactionId": "af48ab08a6731f0ed11125a0c00b102c99ee38b1ab9cf41edfaf541ab4ef470e",
"outputIndex": 1,
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"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205b2f71b4f694115bd565d05668bb6537d47eb28c40961c5afcc6486771ee5ac6",
"sigmaType": "Coll[SByte]",
"renderedValue": "5b2f71b4f694115bd565d05668bb6537d47eb28c40961c5afcc6486771ee5ac6"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20f63ca5d1662d6896419ca914631d72f09f00906695ccb5f3ffe0a20283f3336d",
"sigmaType": "Coll[SByte]",
"renderedValue": "f63ca5d1662d6896419ca914631d72f09f00906695ccb5f3ffe0a20283f3336d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "2fe95f0d5ee8935e8bba3ad46fbfc85e68bf9bdf5b0396775c07cd0c6cfdb4b1",
"value": 2000000,
"index": 54,
"spendingProof": null,
"outputBlockId": "4b943463a316a9f8de011283cfa36ac572d1e9b505c42a96b0b2a61b77b8cee2",
"outputTransactionId": "d90c66b3b0069f06974e218ac00eae39fe88655f232ba3a2bb1e27cd9c853669",
"outputIndex": 1,
"outputGlobalIndex": 46397356,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465762,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ecc0cb035d591d6b9e2678985903773ffeb0189af4da648472cb85a574b86fb6"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e20659b8754ffe06820c94c43879fe78fe8dd2d16cbd337ce8a0ca0d66be60154bb",
"sigmaType": "Coll[SByte]",
"renderedValue": "659b8754ffe06820c94c43879fe78fe8dd2d16cbd337ce8a0ca0d66be60154bb"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "7c5d8e8e0f5d166dc384531d7f7c904dd09ea2e250a211aaeb65cedf878aab8d",
"value": 2000000,
"index": 55,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "123e2b5748de507940381c11468f580cb93a6b17dad5fb4c62a25539d8e0b2db",
"outputIndex": 1,
"outputGlobalIndex": 46397385,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e201cebf17e8687c5b8038094a1241961c54c65773e30c4970389ee39fa9dc956ea",
"sigmaType": "Coll[SByte]",
"renderedValue": "1cebf17e8687c5b8038094a1241961c54c65773e30c4970389ee39fa9dc956ea"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20079584b498c9e9956bbfe57fa3ae27087fbb2c18e58aaf8853f6f444025c4b71",
"sigmaType": "Coll[SByte]",
"renderedValue": "079584b498c9e9956bbfe57fa3ae27087fbb2c18e58aaf8853f6f444025c4b71"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "21a9cde1a22064c71b5fe67716afe359577521b4a2435281610ea456e5907de4",
"value": 2000000,
"index": 56,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "840261cc241ae363dfd99de904ac70ee5477c043457c33beb196136dda271581",
"outputIndex": 1,
"outputGlobalIndex": 46397389,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202ab8f5990a72893dc39fe796e0da8373827b397b1c043a0424d7426c28341a61",
"sigmaType": "Coll[SByte]",
"renderedValue": "2ab8f5990a72893dc39fe796e0da8373827b397b1c043a0424d7426c28341a61"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20c63d15aafafdcc4ff9e7806b5c158238924919c2b0da5773b92a655f4400c1da",
"sigmaType": "Coll[SByte]",
"renderedValue": "c63d15aafafdcc4ff9e7806b5c158238924919c2b0da5773b92a655f4400c1da"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c8801ac804e1b31dd6fb1e13a61733461e9bbd67aaa31f501d084720a29dd0f1",
"value": 2000000,
"index": 57,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "0ab528079f7fcbad277e84772a0b27d51c1592150a216d67f195a0c2a6b56106",
"outputIndex": 1,
"outputGlobalIndex": 46397394,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5e9116ec8a5fe109fcb28d46fc9b3f5e6aa8a37d88cdbf0ba1d6f7f0c974b0f7"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "afbfcc83adf838ba46db4b212bc0941170963499e8ff3f711acb3ce30ed89321"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "5bc5d4fe5d8b9b9265e379d4872b6d23180ce703a311b98b0319df75446046d7",
"value": 2000000,
"index": 58,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "55770270617f22159c5b773afc817333dcf51e539614f7d08a172e1cdbd377e0",
"outputIndex": 1,
"outputGlobalIndex": 46397399,
"outputCreatedAt": 1465761,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20bfc372a6d2ac00cc08dbe822ee10e55a15ac224b15255f6fd884a488ed515220",
"sigmaType": "Coll[SByte]",
"renderedValue": "bfc372a6d2ac00cc08dbe822ee10e55a15ac224b15255f6fd884a488ed515220"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "059c337decd1e5551f340cc68f168ce907678077d53d0991ddb880f661b87a48"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "24a07f2c3ad8b74eddf6c7b56d286cecaad72d9b5bf96c1a43a246fb8dc1043e",
"value": 2000000,
"index": 59,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "8c64ff1a2097f370339f958e9ebcfb5c2fe5359c2738591905b1d7900a33d10f",
"outputIndex": 1,
"outputGlobalIndex": 46397404,
"outputCreatedAt": 1465761,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20386d1c70deb3315854bda324ecf573fc224ab8b78b3c9bb62309592450c91047",
"sigmaType": "Coll[SByte]",
"renderedValue": "386d1c70deb3315854bda324ecf573fc224ab8b78b3c9bb62309592450c91047"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20649bedd5f17cd95064e7bbf35c20174eb52d04ec7a09f6aea27726e414734c4c",
"sigmaType": "Coll[SByte]",
"renderedValue": "649bedd5f17cd95064e7bbf35c20174eb52d04ec7a09f6aea27726e414734c4c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "40eae08f2ed78ef5a7c2b6f1631bf9d6722105f66e9878d803c7453062cf721e",
"value": 2000000,
"index": 60,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "b50f4d24d50b14173b96bb7592042a3646b5b343c07749aa3b165483fc3fe796",
"outputIndex": 1,
"outputGlobalIndex": 46397409,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f3ed92c3f867beec54f5dff6dd8682854eefb9eed2fa9c22f4d2ec5d8fdd050"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e2072340caa59317978beba0e0cd19b931ab6755bd21ebfda23a929846d95697b04",
"sigmaType": "Coll[SByte]",
"renderedValue": "72340caa59317978beba0e0cd19b931ab6755bd21ebfda23a929846d95697b04"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "594fdf9edfeb119cd651ef7cd13a0657554c6f192866d9fe07dc21f62884901f",
"value": 2000000,
"index": 61,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "f097b8b3d0de74e53c5a416c2f6163aec1dca3f3a2a149a6b28be3f9f6b39208",
"outputIndex": 1,
"outputGlobalIndex": 46397414,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "29beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f092b86255220b32d808293806c94d73ebce856e0455bd4fe9bd84f1153e17f6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "e28165149a7a13269fc77bf4fed75a21d72fee06c466bfbe7f997a8dd75cc6fc",
"value": 2000000,
"index": 62,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "0571f1cf18a6b6bad8d98b2335ff7d8b8e97b0ac528ee1eeeae3caaf32730a02",
"outputIndex": 1,
"outputGlobalIndex": 46397419,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e208fec0a9930a4a1c38469bd87d5b2f353d2b84570664f5c8f7b2a848d9a419cac",
"sigmaType": "Coll[SByte]",
"renderedValue": "8fec0a9930a4a1c38469bd87d5b2f353d2b84570664f5c8f7b2a848d9a419cac"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2014e90225c1d14a1c77fc390ae5e8297c372160b9b2a82089064809837340632a",
"sigmaType": "Coll[SByte]",
"renderedValue": "14e90225c1d14a1c77fc390ae5e8297c372160b9b2a82089064809837340632a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "4aaeb76fc65a04af7be54b24fd159abfce5ecabbf97744fcdc642ee6164856cd",
"value": 2000000,
"index": 63,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "0fb057c3f8505221d9e65b1cdc0267dcf5a83b18248af26ee21a70bd5bdb193f",
"outputIndex": 1,
"outputGlobalIndex": 46397424,
"outputCreatedAt": 1465760,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "03166c64bca93e04603e621ce6672a699532e45735f210df7bf986f69dcac1c8"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20f9ebfe4969870634f00542db8eb924f4a993cbfb822ee3295bfb0ab0999c5cbe",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9ebfe4969870634f00542db8eb924f4a993cbfb822ee3295bfb0ab0999c5cbe"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "e3d6053c7ef9de133b3289c20357eb785f2f2d99182562aa8728c4d5b52d9045",
"value": 2000000,
"index": 64,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "14c803299b5dc8006639219774eca3d16adfe3dd93da16557ebc4a4d6695fd23",
"outputIndex": 1,
"outputGlobalIndex": 46397429,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9e8e898d814c6fa197d363a3b86c9dc83cf7da0653b34053ba9b7ad4a9915d3a"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7bbcd7069f08c2cbc4535827de4d6c3e71c607a2e9f12600c883a245640d9398"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "dc969173ba4fc9cd7c98257f810a76e6f02a959d4183492a785bec17b6ab6f75",
"value": 2000000,
"index": 65,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "179336704a1de38a97e18db8c26ac5204609a352ad39385d093ccf76a46a523d",
"outputIndex": 1,
"outputGlobalIndex": 46397434,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20bb5f676dea40d456552f6cbdb963e0426387c7c0c64c7512b5d35418f3759d0d",
"sigmaType": "Coll[SByte]",
"renderedValue": "bb5f676dea40d456552f6cbdb963e0426387c7c0c64c7512b5d35418f3759d0d"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20d870244d0e7e39b77fc379904af04ccc90beb417f903fe3a03ce1dfa486f0eaf",
"sigmaType": "Coll[SByte]",
"renderedValue": "d870244d0e7e39b77fc379904af04ccc90beb417f903fe3a03ce1dfa486f0eaf"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d6cc36f3b0a666807ef6d2da68b313df9d407279620469773c9570c27ead0fc9",
"value": 2000000,
"index": 66,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "1cf4e147d033df748000f5a7080fcfe52d086433b69b3161436e5488992db48f",
"outputIndex": 1,
"outputGlobalIndex": 46397439,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200d31882f3ba9acf919452b3b06edb1c3f438ba343b2cb511fa3e4f97ac52f47c",
"sigmaType": "Coll[SByte]",
"renderedValue": "0d31882f3ba9acf919452b3b06edb1c3f438ba343b2cb511fa3e4f97ac52f47c"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e203b2dd2039c0172a48af3a70cff306042a539ef118366fa131f3779417be25178",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b2dd2039c0172a48af3a70cff306042a539ef118366fa131f3779417be25178"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ee4b65d68f821946c544e3219c917b35b7e1d9b48c606730086a6421e88150d2",
"value": 2000000,
"index": 67,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "1ef4ad4667224864289b66786f27efe5abdb99184cbbb73e0f87283289a2d921",
"outputIndex": 1,
"outputGlobalIndex": 46397444,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698",
"sigmaType": "Coll[SByte]",
"renderedValue": "ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c16f0f2b193b10045cdaa6980c2ac419e42ca3d80c94c5f3c97118a472e5408b"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "4119d53a1478d52e12b36d7312a2b12ad4fa101fb58ba694cfe09c1c4d370396",
"value": 2000000,
"index": 68,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "3dac1eb96a3fa984d86f374720baee4fb5a0e5af54063d8e206b71b133590e48",
"outputIndex": 1,
"outputGlobalIndex": 46397449,
"outputCreatedAt": 1465758,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202d6d1cd76c7477c1315af705ac2158abe950d99373defff0ea79aec47bb68d0e",
"sigmaType": "Coll[SByte]",
"renderedValue": "2d6d1cd76c7477c1315af705ac2158abe950d99373defff0ea79aec47bb68d0e"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2047f513a6c3037eea0e0602ff41474940a3d8bf5dc5587aa5318dc472ab7d427c",
"sigmaType": "Coll[SByte]",
"renderedValue": "47f513a6c3037eea0e0602ff41474940a3d8bf5dc5587aa5318dc472ab7d427c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "5c873ef4a6621f0991fbbd7d46a368a0c0158c9797c685cb00173a62e67ce464",
"value": 2000000,
"index": 69,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "53774c8033b091857f25b7b31b3cef775eb424a3b11a6e371e9677f307320616",
"outputIndex": 1,
"outputGlobalIndex": 46397454,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9d57b0fed60a6f7c06e57cdf6c8fe88f5df4f44dbd41d5f43ed4b971aa13c017"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20c711977e128c838d7ac980a33b9cf5100cae141abb1dd0b913a3f2559897bf76",
"sigmaType": "Coll[SByte]",
"renderedValue": "c711977e128c838d7ac980a33b9cf5100cae141abb1dd0b913a3f2559897bf76"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "d3cd1f3effa2326401d6f6902a59b86130ca96a9f6f78c9bdd24b5b52c846f14",
"value": 2000000,
"index": 70,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "63ef437c2a44134597701dde1a9cd1d8e3391fd6ff765855b2e44bcef34e8b0b",
"outputIndex": 1,
"outputGlobalIndex": 46397459,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "92a7c171364ecec3926817b320af35a4830041fb3d9e71dbc38fbf5b177ab22f"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "60a8fdbfb7ade0cef0f66a9c9ad06d02cd844d71e407fbfcdfde026ed989a30e"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "652dbaca300f6d7336ded1ddf2b4ebda789d5ead4948019e4c99354f7ed62bd0",
"value": 2000000,
"index": 71,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "79d7c6debb6574f89facab79996bcd4c490670651061d67f4b61df2cad982812",
"outputIndex": 1,
"outputGlobalIndex": 46397464,
"outputCreatedAt": 1465760,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20f7d76a44e55423b2eaecf31c5d623eaeb17237637973420493412a1c7f2f1a7e",
"sigmaType": "Coll[SByte]",
"renderedValue": "f7d76a44e55423b2eaecf31c5d623eaeb17237637973420493412a1c7f2f1a7e"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e2eee78d3f24c76c711244f1c89ab93a545987441e1aa9a7e01591285a297c31",
"value": 2000000,
"index": 72,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "7cc1ac8c8a6a05acb606ca1d068b3cdf2fa209a4649498678fc463113daeb663",
"outputIndex": 1,
"outputGlobalIndex": 46397469,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3aa7ed9864521180387dcc059e46225ada5116a86758bc2b958873bbd7d19366"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "dbd39b220b6705dc816d659e2649c62e3a25a99312f55d1b23153d049285b7f3"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "a55ff0aadfd638f9d87a9a9550bb6d913b0cc833d23be940b3cf4b49463170cc",
"value": 2000000,
"index": 73,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "898de9c313bc8c2fa19e495d225be172f54f8ab22aada53b16a4524846fa3660",
"outputIndex": 1,
"outputGlobalIndex": 46397474,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f1b10ea6e49e1941763df44f38cd87c0429a459329c1a10493d51b805dbf05e4"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "c5ca322d458061ec575ff066ad36dc176857df9a5794bac8e95e546e60274604",
"value": 2000000,
"index": 74,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "90d896f3f4d678d19ae95b4f24364ff4ffdd02f6b6e9b1539aea3ceb9b30f963",
"outputIndex": 1,
"outputGlobalIndex": 46397479,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2024da25ed1e25e6d87ab1d9c9fe70d657c9b472dc9a176a69e210cb5c5e07aff6",
"sigmaType": "Coll[SByte]",
"renderedValue": "24da25ed1e25e6d87ab1d9c9fe70d657c9b472dc9a176a69e210cb5c5e07aff6"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e205d2ed8bee04004eb766cbf8e6fa3b5d13f59d891129b3b1a954b8b575c4d1759",
"sigmaType": "Coll[SByte]",
"renderedValue": "5d2ed8bee04004eb766cbf8e6fa3b5d13f59d891129b3b1a954b8b575c4d1759"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6d6743353414cc7e46f927ddd77b2c8dd4a82433cce8a409a1c7f285c5db5eef",
"value": 2000000,
"index": 75,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "967a884885b45664538444ffce118b0be666e369560847f2a517a8b7f574fd3c",
"outputIndex": 1,
"outputGlobalIndex": 46397484,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e200abe040506082ea251726777dd7e2fc8ec76cc46b220603995002f4d3505cc12",
"sigmaType": "Coll[SByte]",
"renderedValue": "0abe040506082ea251726777dd7e2fc8ec76cc46b220603995002f4d3505cc12"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "8f55f284e30b3539a4c32859366f93e8b8b68c5823857176143e5c4b28cc4c82",
"value": 2000000,
"index": 76,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "9add100c2fe780c98e17ac2b4eb2f7b9c17a6be097656c7d4a055e528aa9a4d4",
"outputIndex": 1,
"outputGlobalIndex": 46397489,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "77e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20c24931df9b5a4581a4a445dafc1bd7523d86467a385a0072ac1626f74f20671d",
"sigmaType": "Coll[SByte]",
"renderedValue": "c24931df9b5a4581a4a445dafc1bd7523d86467a385a0072ac1626f74f20671d"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "aa07b933c9c382d9361fec4e54342f4879ce14f5a352d37fbfd3ce2120037d83",
"value": 2000000,
"index": 77,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "9bcbcd6e8bd26a1724595a24b29b4c116489c4db09965c0f3556c172384dc3a7",
"outputIndex": 1,
"outputGlobalIndex": 46397494,
"outputCreatedAt": 1465761,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2094dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865",
"sigmaType": "Coll[SByte]",
"renderedValue": "94dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2030d689e057941d84707ab8cae233477d984c63dd2fa3f4d35502a76b270b66c9",
"sigmaType": "Coll[SByte]",
"renderedValue": "30d689e057941d84707ab8cae233477d984c63dd2fa3f4d35502a76b270b66c9"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1630e1f56e139fb80a02ea8656a6b1a340d4b856eeb4a69c386332b32d006c1a",
"value": 2000000,
"index": 78,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "9cc6d391f452c3e08670c35d2dbd95c1918fe07efc61606685360450e322b296",
"outputIndex": 1,
"outputGlobalIndex": 46397499,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20f9f53533ac2e6bc2965c9a6b6daff832a22cca3df388dd3caf0aeed146abcca6",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9f53533ac2e6bc2965c9a6b6daff832a22cca3df388dd3caf0aeed146abcca6"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e204bd9478c5cd7c74e5e69862702b025f737fe2e163cd223c7a1c3ed4ced128372",
"sigmaType": "Coll[SByte]",
"renderedValue": "4bd9478c5cd7c74e5e69862702b025f737fe2e163cd223c7a1c3ed4ced128372"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "609dd60bcfafdccee7fa16058902f6f5ea81aac63a22eadf2de5905a5eafe3af",
"value": 2000000,
"index": 79,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "acd78e89ef9205c726729fa9e0d057c88ec80a88935e292066839ef4acb2784e",
"outputIndex": 1,
"outputGlobalIndex": 46397504,
"outputCreatedAt": 1465761,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "cacc2b189e0300a41a77a080699ff25b933eb71bad64297ecb56eeeea5855439"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "dfab8092d1a9acef5b21fb7bbc502e315c4ca9e365edae3320de19e1967f3aec"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "74ef23cfb56cac7e2661ac9add3eef6fdff728e0dff4c96e7d761c2fc0782eea",
"value": 2000000,
"index": 80,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "b3e1912d0521841ca5eaa98c57b3d4a4909b8268af1840c329ba93dd3935ccce",
"outputIndex": 1,
"outputGlobalIndex": 46397509,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2093d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9",
"sigmaType": "Coll[SByte]",
"renderedValue": "93d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e207cc48fcd8147d423d1d9a08dc30170991a3889e01a1dcfb15bd05c029a331552",
"sigmaType": "Coll[SByte]",
"renderedValue": "7cc48fcd8147d423d1d9a08dc30170991a3889e01a1dcfb15bd05c029a331552"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3d908bfcdfa97bd9bad203d43cf41deb960a81bb36553bf380c42cbd5f235c50",
"value": 2000000,
"index": 81,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "b3e5c831d562193598ede36ba185d7e5dca1d8f2e2b3ed2716fc9dfdd5990045",
"outputIndex": 1,
"outputGlobalIndex": 46397514,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "451e6a391af3b38336460dfab25c283697256a195638eeb9627b3b687f42009a"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e200c2700c499e9a76e4065e44d0632920905bffb97a0816dbe4203489bad3568ce",
"sigmaType": "Coll[SByte]",
"renderedValue": "0c2700c499e9a76e4065e44d0632920905bffb97a0816dbe4203489bad3568ce"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "2e120725a021d337fef811dcf6893590776f0d253d1ef625ffe277828307e260",
"value": 2000000,
"index": 82,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "d2d38d1f63adacdf13a8d07a9d7ca5c8b5b717d442398a89f5708231c821df2c",
"outputIndex": 1,
"outputGlobalIndex": 46397519,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "88ddc08ffd8bec81549ea136fc51ef021bc76d5922069251615513b3f859af8e"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "880fd6e87eedb323992f2065b5917b9b6aa2a2098b43152fbce822718cd5935a",
"value": 2000000,
"index": 83,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "d5646e359d10ff576eab2b25479d3ef527f81948a25541a23d710848900dcec9",
"outputIndex": 1,
"outputGlobalIndex": 46397524,
"outputCreatedAt": 1465761,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a44a68f2039b3b7f15f08c58dcb5e4c5105a094b9b0d0a0e3ef314384a04a612",
"sigmaType": "Coll[SByte]",
"renderedValue": "a44a68f2039b3b7f15f08c58dcb5e4c5105a094b9b0d0a0e3ef314384a04a612"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e202926c5cef81dd8ef6046b6c914b7b450c503d9fcadf414489cdc882c71ef5775",
"sigmaType": "Coll[SByte]",
"renderedValue": "2926c5cef81dd8ef6046b6c914b7b450c503d9fcadf414489cdc882c71ef5775"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3ef90c022d802eb114764542c080a9eddd190c5aae88e85bda4161aa312912be",
"value": 2000000,
"index": 84,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "e95b3ac5036ba9ab6ff7b3b2fa4191f6a94e8882d5860e9d0cb17dd292ba21c4",
"outputIndex": 1,
"outputGlobalIndex": 46397529,
"outputCreatedAt": 1465760,
"outputSettledAt": 1465763,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e205d1865a3ef5cb3060172a0d9d1945b51445af140a1e26bd3bd3b7b3200f407c1",
"sigmaType": "Coll[SByte]",
"renderedValue": "5d1865a3ef5cb3060172a0d9d1945b51445af140a1e26bd3bd3b7b3200f407c1"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "7c4c1e4a5554f7ecbc7caa3b2bdf6213cd1282ac7a0e25e9574dfb3bcfaf6cca",
"value": 2000000,
"index": 85,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "ef4d977f017d58f6c008023242b43d02efa2292a6471bfad2fedd3d0b9e963ae",
"outputIndex": 1,
"outputGlobalIndex": 46397534,
"outputCreatedAt": 1465761,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "93d73a59f111c37a6e9853fb85ba075264f330dc3b416d2778b7939e3bb6591e"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
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"R6": {
"serializedValue": "0e203948cf01b6cb15281fd4d5cdc883ccac9d499fdf3bc5b0ad129673ae7444efe6",
"sigmaType": "Coll[SByte]",
"renderedValue": "3948cf01b6cb15281fd4d5cdc883ccac9d499fdf3bc5b0ad129673ae7444efe6"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "16478f46865d5b7868ef3040fe24046e7562b7e4705394e8dce5666a683abfe3",
"value": 2000000,
"index": 86,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "efd42fbf3c41628264e9d4b4e089e17a65e6b218e0af3a71880a9b145ea27c3f",
"outputIndex": 1,
"outputGlobalIndex": 46397539,
"outputCreatedAt": 1465759,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e208e4ad9d51dc7163937eaeb6760c53bfb4d64d7369580d056ae32df6795c2dd4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "8e4ad9d51dc7163937eaeb6760c53bfb4d64d7369580d056ae32df6795c2dd4b"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e2012ed02028dc78c7973da06c165f7a5d3bc944a7d1414b336a70824b0d74f36ce",
"sigmaType": "Coll[SByte]",
"renderedValue": "12ed02028dc78c7973da06c165f7a5d3bc944a7d1414b336a70824b0d74f36ce"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "a3f350cf3ee8341e4ebff010c0bd1a1b1a64304ef78bb91a0a152fb96ff9177c",
"value": 2000000,
"index": 87,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "fee0d58529e1ee447c86e8a57158f1d104d52e36555127cbaf3eeddf6feb3752",
"outputIndex": 1,
"outputGlobalIndex": 46397544,
"outputCreatedAt": 1465760,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2097ccaa554d7918228e3ba22f0ae54c71c17ab70eab7087c994df6d9a3fe6f0b1",
"sigmaType": "Coll[SByte]",
"renderedValue": "97ccaa554d7918228e3ba22f0ae54c71c17ab70eab7087c994df6d9a3fe6f0b1"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20433fc43c4c6b6d95aca746552e956239a2eb0fe20d37fac358e3b3988252de60",
"sigmaType": "Coll[SByte]",
"renderedValue": "433fc43c4c6b6d95aca746552e956239a2eb0fe20d37fac358e3b3988252de60"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "18fd34ad3c41fa7dc02a30e7783650f21ab0b1ec04729489a328e6a1bdb267d4",
"value": 2000000,
"index": 88,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "40628a03c98aaf53dd5482427b6e6b1675d0caf4e91dd4420ece5a14cbc83f66",
"outputIndex": 1,
"outputGlobalIndex": 46397549,
"outputCreatedAt": 1465759,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e207ec35e4a4a66e2662ad8fa705473576eeac02680c39985b5127472b66e1407ad",
"sigmaType": "Coll[SByte]",
"renderedValue": "7ec35e4a4a66e2662ad8fa705473576eeac02680c39985b5127472b66e1407ad"
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"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20a952f4b4b313ca6cd062dbbf917514cfb673bf37ace0044e684fdcf6f7f4e8fc",
"sigmaType": "Coll[SByte]",
"renderedValue": "a952f4b4b313ca6cd062dbbf917514cfb673bf37ace0044e684fdcf6f7f4e8fc"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "460966a40b77755874dab2c43fca4c58732a8f20e6a80f5e482e0e3e5902a508",
"value": 2000000,
"index": 89,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "f7b7ead381d5bd6f3bbd723c695dfbcca4415cd98c7dcac1be76c8865d9f0156",
"outputIndex": 1,
"outputGlobalIndex": 46397554,
"outputCreatedAt": 1465758,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20793848c21ce3e6a7bdfa8613f66f9f99879304a3a4b7fc233228fa959c113fd8",
"sigmaType": "Coll[SByte]",
"renderedValue": "793848c21ce3e6a7bdfa8613f66f9f99879304a3a4b7fc233228fa959c113fd8"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20c81d694b399d8b0c23a375c184469253c2b202dc9ce3ffba31ef54d1fb33e025",
"sigmaType": "Coll[SByte]",
"renderedValue": "c81d694b399d8b0c23a375c184469253c2b202dc9ce3ffba31ef54d1fb33e025"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e1e87abc0a85a0e49611fc5d0f8e125a1df7b1512a77607394232291db7670a7",
"value": 2000000,
"index": 90,
"spendingProof": null,
"outputBlockId": "d73700c329339bc49eaec4ed572aca958d5a19b5715e2e5f2a67e26103554f40",
"outputTransactionId": "63e5cb4816f3641650cb9da4ed1c5281a5914ae352385cd85b0b0a8d600b5bef",
"outputIndex": 1,
"outputGlobalIndex": 46397559,
"outputCreatedAt": 1465761,
"outputSettledAt": 1465763,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c277386130fd55abf920acd70292ad016f836d031543c02dc1e423bdf4b22a98",
"sigmaType": "Coll[SByte]",
"renderedValue": "c277386130fd55abf920acd70292ad016f836d031543c02dc1e423bdf4b22a98"
},
"R5": {
"serializedValue": "0e2098c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c8318347b0ea174ebe799003d7173f25a1bab0fe26fa6257dba9a8613ab33e"
},
"R6": {
"serializedValue": "0e20cfaa1f72dda9d4da0677d64bbf0bf312b868cf1eb9cb468f24d0f7b8636a1e6a",
"sigmaType": "Coll[SByte]",
"renderedValue": "cfaa1f72dda9d4da0677d64bbf0bf312b868cf1eb9cb468f24d0f7b8636a1e6a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1c8e2904fd835728417a7def49b577f393db1066964da3a42ebf4a095f5873e3",
"value": 5950000,
"index": 91,
"spendingProof": "5722f8b3be4a80d848d91235c56ace47f6ad407cebe321cc9b312f7ed02c367e034de111e2c1e16575ac62c602c2d6adb32b5350c8d37679",
"outputBlockId": "250cd9cf9170448a516e5f20aae487ae572cf0deedd17e0eb5ee3b70eea7616e",
"outputTransactionId": "0fef1ae7d5cf12db121f7f1da92e03a37eb6142c103f094114ce8a30e74075c1",
"outputIndex": 2,
"outputGlobalIndex": 46328046,
"outputCreatedAt": 1464201,
"outputSettledAt": 1464204,
"ergoTree": "0008cd02bc36526424f81343d527f67b3c696fa352aed56587a1577965a004b0e2f835da",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bc3652,b9f885,...)))}",
"address": "9fwx9F5D72kft9Ji1Ez8QNLwHxVaCELphuZdMRy6vR5mejFrP5u",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "a0f81c737b38ec451dc072369bc74609896b3bd245762140f44edbd5a934f90d",
"value": 1100000,
"index": 0,
"outputBlockId": "9cd9da9a7bebc91af8af522b342397f6f0cb88719817b60aa0cb53a9758daccf",
"outputTransactionId": "a0029995fad90f6b31ac46d0ad4e823a8349c16a413f885c829c74a840107a3b",
"outputIndex": 1,
"ergoTree": "100604000400040004000e2055bf993b4376ba132264d084f06fe033321ab43c68db1435a0e7e0bf77ddb7350402d803d601b2db6501fe730000d602b2db6308b2a5730100730200d603b2db6308a7730300ea02d196830301aedb63087201d901044d0e938c7204017304938c7202018c720301938c7202028c72030298b2e4c672010510730500ade4c67201041ad901040ecdee7204",
"address": "prufxZid3SJMyUVhAPFAF4uLyCZbEMWCMXRSyuMEvDUHZf81JcGcmu1EW1U9hUuJerWer5vmjhiJMmjbCqDwPMKRy169SPaLTxDp5tZ2rCrKjiv7xVAsnmphxSNBpj6qqB8fs1rWJGn9dN7t74qvx6oVHZny8KNMrqfEDjcWRv7wP21sZFP4rie4YhWJs8Z6swQ3DA28B5bzMZkMqfR7",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1106809bee027802c8018080babbc82e808ece1c",
"sigmaType": "Coll[SLong]",
"renderedValue": "[3000000,60,1,100,800000000000,30000000]"
}
}
},
{
"boxId": "50204d3c4704da04cbd05d9893642bbc0915c256bd64f74bcf84755f566eb91b",
"value": 2000000,
"index": 1,
"outputBlockId": "70bba1ed2facbf3d7294d506c45ee6636451b9b70f843e07b63e80e02004efa8",
"outputTransactionId": "456b4e7b2e05afa137221c233b4864656eb6511c865dc7e45f854cde945b21a8",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "058c02",
"sigmaType": "SLong",
"renderedValue": "134"
}
}
}
],
"outputs": [
{
"boxId": "b8e38487a89c7db197a01ad2d35db6db63ac0d635c5c87548fea9648f0a79141",
"transactionId": "fafafb2c8002a399d5492667cec4f5b45496e3a9d9dd8fedbaf31f142a49946b",
"blockId": "73e2f1ae9235ac752c9cc1daa5f78f2594adf14f1e03fdb6992e9289b6e3065c",
"value": 180030304,
"index": 0,
"globalIndex": 46397673,
"creationHeight": 1465763,
"settlementHeight": 1465765,
"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(61,77,106,-65,36,-120,39,27,1,109,101,-87,-13,74,9,45,48,68,77,113,-89,14,-91,30,1,-42,-90,-15,-73,98,118,115)\n10: 1\n11: 0\n12: Coll(82,-43,103,29,47,-108,82,-33,-82,-22,-125,-66,-113,-62,-1,0,-115,58,113,109,-76,-77,-112,-34,-78,119,5,-41,60,96,-108,-22)\n13: 21600\n14: Coll(-98,-6,68,-25,-102,33,112,49,-105,-94,-40,-120,-4,32,76,-10,67,87,17,-51,-17,-49,-33,91,-53,-113,-71,41,-27,9,27,-70)",
"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": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 273000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20684b6daf7b97c874347991d966a37370f157ce1b297264ae9f8cd6ce724df5f1",
"sigmaType": "Coll[SByte]",
"renderedValue": "684b6daf7b97c874347991d966a37370f157ce1b297264ae9f8cd6ce724df5f1"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[61643562306535346638346133666363386536653066383031353566646439663835396333316566653062623936653535383633376435316139326437366265,6572676f,63617264616e6f,3968643766674843464d6235457a503334514c3350394b746b6b6e4d62626d4b483563464675674a4477764c4d747232656750,616464723171386e376172616c76356c7373636c36386879766d766871647673717a7a7376307a796437366d6e6b74727166666d3465737a666361376a70616e6b706b746e38637164727571363470336664726864736761643270377272353571336364733033,00003faa25226000,000000517da02c00,000000009e75b75f,657267,30346239353336383339336338323166313830646565653832323966626439343162616166396264373438656263646266376164626231342e37323733343535323437,64313163393431363963376232313965333236373333343535376330383430623731313263373730616436313865336433396232323563656336363333663462,0000000000165d91]"
},
"R6": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
},
"R7": {
"serializedValue": "04b601",
"sigmaType": "SInt",
"renderedValue": "91"
}
},
"spentTransactionId": "87c55c7c6c5d66d7862620c3a585c06a7ac6ba9f623c65a82a534b9ff0f04387",
"mainChain": true
},
{
"boxId": "167a1e7207dd9b47bba5bcf5c6c5405b10ded728bdfe11c42661b0c289144816",
"transactionId": "fafafb2c8002a399d5492667cec4f5b45496e3a9d9dd8fedbaf31f142a49946b",
"blockId": "73e2f1ae9235ac752c9cc1daa5f78f2594adf14f1e03fdb6992e9289b6e3065c",
"value": 3900000,
"index": 1,
"globalIndex": 46397674,
"creationHeight": 1465763,
"settlementHeight": 1465765,
"ergoTree": "0008cd02bc36526424f81343d527f67b3c696fa352aed56587a1577965a004b0e2f835da",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(bc3652,b9f885,...)))}",
"address": "9fwx9F5D72kft9Ji1Ez8QNLwHxVaCELphuZdMRy6vR5mejFrP5u",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "173757fdd97fa6981b323c2bc87d817c3716eb9fd6abab62a44f10a62bf68bba",
"mainChain": true
},
{
"boxId": "efbd692a3f9304ec71c32c6f7392eb632312e8a26e54e5014bbea436b6a69545",
"transactionId": "fafafb2c8002a399d5492667cec4f5b45496e3a9d9dd8fedbaf31f142a49946b",
"blockId": "73e2f1ae9235ac752c9cc1daa5f78f2594adf14f1e03fdb6992e9289b6e3065c",
"value": 2050000,
"index": 2,
"globalIndex": 46397675,
"creationHeight": 1465763,
"settlementHeight": 1465765,
"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": "0067c1f49b953660a208210e6692873d1dd4f2130bec72618a55be06c2f3dd3e",
"mainChain": true
}
],
"size": 4312,
"isUnconfirmed": false
}