Transaction
ID: 55b03ce49c...f4a6
Inputs (7)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
21.01
826.44
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
35.01
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
56.03
826.44
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 245,972
Total coins transferred: 0.014 ERG
Fees: 0.002 ERG
Fees per byte: 0.000001241 ERG
Raw Transaction Data
{
"id": "55b03ce49c5fcb30ff604df444dd4b8213ceecff3ceb5a42fa4e9b047ef3f4a6",
"blockId": "1b435572ac1160b08b28e3bb612535dfda896f3b43029a71bfe892d38ffb130e",
"inclusionHeight": 1512668,
"timestamp": 1745761601122,
"index": 5,
"globalIndex": 8895422,
"numConfirmations": 245972,
"inputs": [
{
"boxId": "cb4519ad5c9bb2a57bbefe7b56a745e71a3e4001ea9cc5f76797696076665ea3",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "9dc7edf39b71eb215db552ab34f8937ade73ead6926d9990b88cb232d31af7a5",
"outputTransactionId": "fe091140fbb41c28dd8961bd3c6f58848ed77dd0a93d441a8f585a02dfbcb4da",
"outputIndex": 1,
"outputGlobalIndex": 47589376,
"outputCreatedAt": 1512659,
"outputSettledAt": 1512661,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(43,-89,62,-101,-117,101,-108,19,96,120,-43,-30,-96,88,72,72,-15,-6,-107,-106,-119,27,-63,-18,-24,4,-74,36,-43,101,104,121)\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(86,-101,29,-7,120,-75,-75,118,25,-84,13,30,-21,40,21,42,10,-76,-55,6,-39,125,-63,34,11,-14,-88,56,-30,55,5,-107)\n26: 0\n27: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\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": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20195bd457085e48b0e1467da99f011fc67827480c8a991b9a1ba53a6d2bb135d4",
"sigmaType": "Coll[SByte]",
"renderedValue": "195bd457085e48b0e1467da99f011fc67827480c8a991b9a1ba53a6d2bb135d4"
},
"R5": {
"serializedValue": "0e20485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc",
"sigmaType": "Coll[SByte]",
"renderedValue": "485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc"
},
"R6": {
"serializedValue": "0e20ea44a432fd6b371b3c0ff90d4c2218132e562d3d2840698d54e36fcc62483900",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea44a432fd6b371b3c0ff90d4c2218132e562d3d2840698d54e36fcc62483900"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "d3ca549f1bc44078ba49c90fc8ec7c6a93e0fbbd31d0b7c06e8c61c35966b62a",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "17ac30966d7c732b8979fd31db9f92649845bb6724fd9f9718599be60e03301d",
"outputTransactionId": "2aaf79a85aa5fe8eb51317239ddaa49e33f4bfa5bf46819e077e274c5d966a51",
"outputIndex": 1,
"outputGlobalIndex": 47589400,
"outputCreatedAt": 1512660,
"outputSettledAt": 1512662,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(43,-89,62,-101,-117,101,-108,19,96,120,-43,-30,-96,88,72,72,-15,-6,-107,-106,-119,27,-63,-18,-24,4,-74,36,-43,101,104,121)\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(86,-101,29,-7,120,-75,-75,118,25,-84,13,30,-21,40,21,42,10,-76,-55,6,-39,125,-63,34,11,-14,-88,56,-30,55,5,-107)\n26: 0\n27: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\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": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20700577946f4334199916bacf1ce3286404acd4f9476876e6ec7d5bf5a2184d3f",
"sigmaType": "Coll[SByte]",
"renderedValue": "700577946f4334199916bacf1ce3286404acd4f9476876e6ec7d5bf5a2184d3f"
},
"R5": {
"serializedValue": "0e20485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc",
"sigmaType": "Coll[SByte]",
"renderedValue": "485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc"
},
"R6": {
"serializedValue": "0e20c6fb9c399eb909c843be132e20ad172aace936f202250815e6a1799febd308ea",
"sigmaType": "Coll[SByte]",
"renderedValue": "c6fb9c399eb909c843be132e20ad172aace936f202250815e6a1799febd308ea"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "f2111a12e55ecc1bc69f7bdedd69a5984495f3be15d5c4a6c7c4917671e51393",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "17ac30966d7c732b8979fd31db9f92649845bb6724fd9f9718599be60e03301d",
"outputTransactionId": "2b0a35293ac68bca804df17eb3deb0a13392cd3ee404a1a2fc2af9181914061f",
"outputIndex": 1,
"outputGlobalIndex": 47589405,
"outputCreatedAt": 1512660,
"outputSettledAt": 1512662,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(43,-89,62,-101,-117,101,-108,19,96,120,-43,-30,-96,88,72,72,-15,-6,-107,-106,-119,27,-63,-18,-24,4,-74,36,-43,101,104,121)\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(86,-101,29,-7,120,-75,-75,118,25,-84,13,30,-21,40,21,42,10,-76,-55,6,-39,125,-63,34,11,-14,-88,56,-30,55,5,-107)\n26: 0\n27: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\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": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a482c6a3fc2ee79314f23dd94060fb7b1996319d7c2587545600752376393115",
"sigmaType": "Coll[SByte]",
"renderedValue": "a482c6a3fc2ee79314f23dd94060fb7b1996319d7c2587545600752376393115"
},
"R5": {
"serializedValue": "0e20485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc",
"sigmaType": "Coll[SByte]",
"renderedValue": "485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc"
},
"R6": {
"serializedValue": "0e200b95b42db3475b0619acd30b4cebd65059e5bf6be885c4630ab538990ac36736",
"sigmaType": "Coll[SByte]",
"renderedValue": "0b95b42db3475b0619acd30b4cebd65059e5bf6be885c4630ab538990ac36736"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "ae365be5e477024261258c5be8ad567c23e9f460214ea09a54d2bb7be4838fd2",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "17ac30966d7c732b8979fd31db9f92649845bb6724fd9f9718599be60e03301d",
"outputTransactionId": "4ab92bb067be962db67b892438b8f1ade2ad86000c420d4953b3ce98b988688c",
"outputIndex": 1,
"outputGlobalIndex": 47589410,
"outputCreatedAt": 1512659,
"outputSettledAt": 1512662,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(43,-89,62,-101,-117,101,-108,19,96,120,-43,-30,-96,88,72,72,-15,-6,-107,-106,-119,27,-63,-18,-24,4,-74,36,-43,101,104,121)\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(86,-101,29,-7,120,-75,-75,118,25,-84,13,30,-21,40,21,42,10,-76,-55,6,-39,125,-63,34,11,-14,-88,56,-30,55,5,-107)\n26: 0\n27: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\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": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20143f7c38a3e10ba24ccb7c4975dd091d0a9b916304c57db6a0534c4b493ce208",
"sigmaType": "Coll[SByte]",
"renderedValue": "143f7c38a3e10ba24ccb7c4975dd091d0a9b916304c57db6a0534c4b493ce208"
},
"R5": {
"serializedValue": "0e20485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc",
"sigmaType": "Coll[SByte]",
"renderedValue": "485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc"
},
"R6": {
"serializedValue": "0e205559c97d7d6d0e7ec55a1e89dfa2b5e3af0ff580c2e8378dc1d9bb7b045a7857",
"sigmaType": "Coll[SByte]",
"renderedValue": "5559c97d7d6d0e7ec55a1e89dfa2b5e3af0ff580c2e8378dc1d9bb7b045a7857"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "d7825b1ef98dd40c7ebf29849f2fdc2a61da35fef8a09ebe6a1aef892fb06976",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "17ac30966d7c732b8979fd31db9f92649845bb6724fd9f9718599be60e03301d",
"outputTransactionId": "73ed4f1099befa2eb1d9a3527b6ccd5cb60ed5442ac04309956c40588034cd45",
"outputIndex": 1,
"outputGlobalIndex": 47589415,
"outputCreatedAt": 1512660,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(43,-89,62,-101,-117,101,-108,19,96,120,-43,-30,-96,88,72,72,-15,-6,-107,-106,-119,27,-63,-18,-24,4,-74,36,-43,101,104,121)\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(86,-101,29,-7,120,-75,-75,118,25,-84,13,30,-21,40,21,42,10,-76,-55,6,-39,125,-63,34,11,-14,-88,56,-30,55,5,-107)\n26: 0\n27: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\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": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2092932311cd5401cd6690b8da274ff937b8f4196eda94fd45f33aca8d7593eb97",
"sigmaType": "Coll[SByte]",
"renderedValue": "92932311cd5401cd6690b8da274ff937b8f4196eda94fd45f33aca8d7593eb97"
},
"R5": {
"serializedValue": "0e20485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc",
"sigmaType": "Coll[SByte]",
"renderedValue": "485540315f1a4cd42d74f5c37aa08c8b89cda6f50eb07f1517084a7a84ebbbfc"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f8963121a58c965dfe5ebf4c21088b68804baf2e921142da8c8d4c71ebaa80ef"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
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{
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"value": 2000000,
"index": 5,
"spendingProof": "4998de656eadd4c950709642fa25e9ba660d3fb4633528709bf31b5a695f0fcac3ef170981d40b66c363099392e73177fbd1d516c3e96f8e",
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"outputTransactionId": "28f0e38d5ba30175f96bdaa8ff0f106cefbe58835271e5aa98db3cfa8e2f7793",
"outputIndex": 1,
"outputGlobalIndex": 46467022,
"outputCreatedAt": 1468374,
"outputSettledAt": 1468376,
"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
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"index": 0,
"amount": 21014,
"name": "eRSN-Pandora",
"decimals": 3,
"type": "EIP-004"
},
{
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"index": 1,
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{
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"spendingProof": "271615e823595ea8f5e520bbc889c157f211667d08f79b67efdd7a75942cc562b433f05a9e956f3a5f2e25590d77aec1854d6c4d46225b0d",
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"outputGlobalIndex": 46511788,
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"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
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"name": "eRSN-Pandora",
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],
"dataInputs": [
{
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"value": 1100000,
"index": 0,
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"sigmaType": "Coll[SLong]",
"renderedValue": "[1000,60,1,20,10000000,1000]"
}
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"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "050a",
"sigmaType": "SLong",
"renderedValue": "5"
}
}
}
],
"outputs": [
{
"boxId": "c49ad652af830ae3bae2113504f81b613fb659eef74c6bf67c558f356549517e",
"transactionId": "55b03ce49c5fcb30ff604df444dd4b8213ceecff3ceb5a42fa4e9b047ef3f4a6",
"blockId": "1b435572ac1160b08b28e3bb612535dfda896f3b43029a71bfe892d38ffb130e",
"value": 10000000,
"index": 0,
"globalIndex": 47589511,
"creationHeight": 1512666,
"settlementHeight": 1512668,
"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(102,106,3,-81,2,114,104,-27,91,-80,-88,89,15,85,-107,-57,-56,-58,125,-28,-97,-91,126,-103,-76,126,-65,57,105,-103,-118,41)\n10: 1\n11: 0\n12: Coll(-113,-66,-52,-97,79,105,104,-79,-127,-41,13,51,127,51,114,-98,-101,60,-75,-111,-1,-49,-113,-54,22,40,44,-53,-60,-121,-91,-121)\n13: 10\n14: Coll(9,-81,-23,48,20,-10,-106,10,-86,-61,7,28,-111,-102,-31,-125,0,-15,92,117,-92,109,-45,-78,47,-79,-8,-64,30,101,-9,91)",
"ergoTreeScript": "{\n val i1 = SELF.R7[Int].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == SELF.tokens(placeholder[Int](2))._1)\n }).slice(placeholder[Int](3), i1)\n val coll3 = OUTPUTS(placeholder[Int](4)).propositionBytes\n val coll4 = blake2b256(coll3)\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll2.size == i1, SELF.R4[Coll[Byte]].get == blake2b256(\n coll2.map({(box5: Box) => box5.R4[Coll[Byte]].get }).fold(Coll[Byte](), {(tuple5: (Coll[Byte], Coll[Byte])) => tuple5._1.append(tuple5._2) })\n ), coll2.forall(\n {(box5: Box) =>\n ((box5.propositionBytes == coll3) && (box5.tokens(placeholder[Int](5))._1 == SELF.tokens(placeholder[Int](6))._1)) && (\n box5.tokens(placeholder[Int](7))._2 == SELF.tokens(placeholder[Int](8))._2 / i1.toLong\n )\n }\n ), if (coll4 == placeholder[Coll[Byte]](9)) {\n allOf(\n Coll[Boolean](\n INPUTS(placeholder[Int](10)).tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), HEIGHT - placeholder[Int](13) >= SELF.creationInfo._1\n )\n )\n } else {\n allOf(\n Coll[Boolean](INPUTS.exists({(box5: Box) => blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](14) }), coll4 == SELF.R6[Coll[Byte]].get)\n )\n }\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 5000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ac6ee9ebcf4cb2af9f683745451bb4da7fd38cfda1166b2c1d689c7c3b8074fc",
"sigmaType": "Coll[SByte]",
"renderedValue": "ac6ee9ebcf4cb2af9f683745451bb4da7fd38cfda1166b2c1d689c7c3b8074fc"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[62626233343464393361636162313765346435646532666537306165373434303337386136666563633233366130303361653466373935663335643733326535,6572676f,63617264616e6f,39686167776e65484b4d424a484e37706e5238574c7744326e65354e5170575745434c45647778625339426d336969676d6b5a,61646472317179646a616c6d30723864666337723274306a6a6e7068796c32796777343835336c77677963757377306a746e716e756866337a666b7a35377178376a3370676c75717a6663356834346474777561706e6d7430346a7176677230717764396d716b,000000000000ca0e,000000000000435a,00000000000086b3,33366364306666326132653132666439656465353633623037383038363834646265366262346238356365383331623932633233636338333232636137383463,35376162653432663534393738346338386631346537383837323132376436326663306137626662656430616437643431653565623266622e373237303665343537353633366336393634,36653039383966653938333139326261373234653630643234663431316165333333626538303134306264323566616662656563343733666533663637636237,00000000001714cd]"
},
"R6": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
},
"R7": {
"serializedValue": "040a",
"sigmaType": "SInt",
"renderedValue": "5"
}
},
"spentTransactionId": "91c987182079b2b29ec2c1fbe114578c8bffabb0b402f7b404a7f56822e713f3",
"mainChain": true
},
{
"boxId": "af3a53cc2b03f9b94756670b4ada9d75bdaa43c49eaae67d3aca8595f2d72007",
"transactionId": "55b03ce49c5fcb30ff604df444dd4b8213ceecff3ceb5a42fa4e9b047ef3f4a6",
"blockId": "1b435572ac1160b08b28e3bb612535dfda896f3b43029a71bfe892d38ffb130e",
"value": 2000000,
"index": 1,
"globalIndex": 47589512,
"creationHeight": 1512666,
"settlementHeight": 1512668,
"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
"tokenId": "bbcb0dc09acb34c09d767aa43683ff2a360fdb4496344988ea10ff5d93ac348a",
"index": 0,
"amount": 56028,
"name": "eRSN-Pandora",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "d752bede1a85891fff344604431fd6dc30ba685b382f2e0fe15da8141d36e34e",
"index": 1,
"amount": 826442,
"name": "RSN-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "56e01fd8cd851e0b54205c4f2e0b76a1b9efb23c5db8dbc56c725c056dd1e6c2",
"mainChain": true
},
{
"boxId": "5d1b2d456ddca53704f881d827dede188721973f5ead22c25619b33fd50ac93e",
"transactionId": "55b03ce49c5fcb30ff604df444dd4b8213ceecff3ceb5a42fa4e9b047ef3f4a6",
"blockId": "1b435572ac1160b08b28e3bb612535dfda896f3b43029a71bfe892d38ffb130e",
"value": 2000000,
"index": 2,
"globalIndex": 47589513,
"creationHeight": 1512666,
"settlementHeight": 1512668,
"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": "fcd65aa49085ac49561fd53a0da272c2f2b5af1d18e2cd8401a725387d4304fe",
"mainChain": true
}
],
"size": 1612,
"isUnconfirmed": false
}