Transaction
ID: a66d2667cf...09ea
Inputs (9)
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:
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:
0.280985898 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.016 ERG
Tokens:
Unspent
Address:
Settlement height:
Value:
0.278985898 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 938
Total coins transferred: 0.296985898 ERG
Fees: 0.002 ERG
Fees per byte: 0.000001239 ERG
Raw Transaction Data
{
"id": "a66d2667cfb883eaa7d5a7ac3013e3a4c680595fae94dfc18cb3d14b365b09ea",
"blockId": "d8d02d9c863028004c96e7420068319b774a79e316c9cde03b1ce3e3c5e4af1f",
"inclusionHeight": 1773839,
"timestamp": 1777380106233,
"index": 15,
"globalIndex": 10665547,
"numConfirmations": 938,
"inputs": [
{
"boxId": "15978f88da231354e6952235c1c67edcec38a94e0733320956f6d2919e333790",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "9aa89ce458b4a40fb2d6949809e033ca1d09520345c24dfb31ef38a739fe1b00",
"outputTransactionId": "6f334b4fd313dc5dbb956693f466c3f9d380ec0b41c8b382fb8ea062b8bb5240",
"outputIndex": 1,
"outputGlobalIndex": 54986426,
"outputCreatedAt": 1773828,
"outputSettledAt": 1773830,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c9ac18b3cb5dac057ecc5121a8f4e3c5ac214ee7d8f32a8fef1fab57da9fd293",
"sigmaType": "Coll[SByte]",
"renderedValue": "c9ac18b3cb5dac057ecc5121a8f4e3c5ac214ee7d8f32a8fef1fab57da9fd293"
},
"R5": {
"serializedValue": "0e208226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0",
"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
},
"R6": {
"serializedValue": "0e202468f1649e6e64600764c896adad4c6d5d55a0ad0ae48bdec52c6ef82b813a17",
"sigmaType": "Coll[SByte]",
"renderedValue": "2468f1649e6e64600764c896adad4c6d5d55a0ad0ae48bdec52c6ef82b813a17"
},
"R7": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
}
}
},
{
"boxId": "610c2e200f33d6b0a37a2c1b78b0ddb596d60458159e4a880af7fe3fc89364a5",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "9aa89ce458b4a40fb2d6949809e033ca1d09520345c24dfb31ef38a739fe1b00",
"outputTransactionId": "8b633df9e78e65f89ca1a6a1e1806e947a7bf08efcbf51d0de800c5db59ddfe9",
"outputIndex": 1,
"outputGlobalIndex": 54986431,
"outputCreatedAt": 1773828,
"outputSettledAt": 1773830,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205755edc9df9ac908c1e6972a11313fd4265d5dd5686b6cebe659da6066b42bc1",
"sigmaType": "Coll[SByte]",
"renderedValue": "5755edc9df9ac908c1e6972a11313fd4265d5dd5686b6cebe659da6066b42bc1"
},
"R5": {
"serializedValue": "0e208226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0",
"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
},
"R6": {
"serializedValue": "0e20e152a20038decb5818deb6d2ad796bb6388fb8394cda69380f23712d777ea9b1",
"sigmaType": "Coll[SByte]",
"renderedValue": "e152a20038decb5818deb6d2ad796bb6388fb8394cda69380f23712d777ea9b1"
},
"R7": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
}
}
},
{
"boxId": "72be2ff8543a798dbf867ff482d594735ab0c9acf03db1e11b6dd428918eb0c1",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "9aa89ce458b4a40fb2d6949809e033ca1d09520345c24dfb31ef38a739fe1b00",
"outputTransactionId": "f58ed8166dd90117355216b4a801fa2d205f9047f746c02d933a505edbf1a7f7",
"outputIndex": 1,
"outputGlobalIndex": 54986436,
"outputCreatedAt": 1773828,
"outputSettledAt": 1773830,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5ac40753ae38e6188c77fa78c983f7bb846f8c1d565e53f3aa1e32d74887a84b"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
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"R6": {
"serializedValue": "0e205b7a0ea44088523470a54583e19eb298dc1267cabfcfb1a9c3560dd7d4a4baad",
"sigmaType": "Coll[SByte]",
"renderedValue": "5b7a0ea44088523470a54583e19eb298dc1267cabfcfb1a9c3560dd7d4a4baad"
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"R7": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
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{
"boxId": "aa4d244fcd5eac72616cfa18c0fabbdcc954c09fbc96f890e6014f26c3e768a3",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "f2afa4e7e82e3d467633249d3e5b7dd1b75c50b64a68eb4ac15506129bc16ad1",
"outputTransactionId": "eac11340a3e130706f0fc26c87d978b5b1b74921648fddeafa848082f79eca71",
"outputIndex": 1,
"outputGlobalIndex": 54986489,
"outputCreatedAt": 1773831,
"outputSettledAt": 1773832,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1869438ac48258d19200d77ca9f7a9bd2f44dade01454fa12982f9453528eed0"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6bcc186ad0e2999895092f35af13b83d320f079f7ab26e004fc04446eee2b691"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
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},
{
"boxId": "d1f45ed785113252e8bbc818841b54546cbc63af99495272a8a344e83270255c",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "6ba506fe75950c58ad5337cacc82b9638d7d568e3f30f58e45925c559493f281",
"outputTransactionId": "576bbd3774f031dc29b30f01e79fbd4928e7e5092eea397388e769f56b5ba757",
"outputIndex": 1,
"outputGlobalIndex": 54986506,
"outputCreatedAt": 1773831,
"outputSettledAt": 1773833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207ce5c0009246f4b7cdad9db921fe3ef102a355c528695a1bd2f971f0b2e09785",
"sigmaType": "Coll[SByte]",
"renderedValue": "7ce5c0009246f4b7cdad9db921fe3ef102a355c528695a1bd2f971f0b2e09785"
},
"R5": {
"serializedValue": "0e208226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0",
"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
},
"R6": {
"serializedValue": "0e20ae3ed4ad37e5dead082481e20ae42a3047e5844d1ab5b037a82bef657b94e596",
"sigmaType": "Coll[SByte]",
"renderedValue": "ae3ed4ad37e5dead082481e20ae42a3047e5844d1ab5b037a82bef657b94e596"
},
"R7": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
}
}
},
{
"boxId": "bbba5f84c31dc1f0cfb18440929d43f99bb0957459dedeb7617705a913344cb4",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "6ba506fe75950c58ad5337cacc82b9638d7d568e3f30f58e45925c559493f281",
"outputTransactionId": "c2a70ad334bf0c9c76c346c423a2c637bcfa8527c303c62fda9ad83807c54bcc",
"outputIndex": 1,
"outputGlobalIndex": 54986511,
"outputCreatedAt": 1773831,
"outputSettledAt": 1773833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a769b0b03c4190ce4982232ab8de5ae4e44a44f9f114edfeceed7d6aca53a23b"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9537d2b592a03732d8150045ece8679b87ce33b086ac9b38c4fddef4a30ccb51"
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"R7": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
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{
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"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "6ba506fe75950c58ad5337cacc82b9638d7d568e3f30f58e45925c559493f281",
"outputTransactionId": "9f271d21a599ed1c7ae5a173d36fb8a3c564b7ab43bcc14ef41ebd607ffc9af7",
"outputIndex": 1,
"outputGlobalIndex": 54986516,
"outputCreatedAt": 1773831,
"outputSettledAt": 1773833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a643c3da641d39920572a23ffc3bad29b75bf900da3d4c96271ae097ca838d68"
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"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
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"sigmaType": "Coll[SByte]",
"renderedValue": "2501004916f3fc13c1aa72e4591035ff289b2c89b6c7f30e2dfbc1893b27e5f5"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
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{
"boxId": "c21a517c6753773d6728ab83b91ecb45b3396611c811735ff21dfef045d5ef0f",
"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "6ba506fe75950c58ad5337cacc82b9638d7d568e3f30f58e45925c559493f281",
"outputTransactionId": "a3ce9a921bde41fe591e55660fa5e30f009f778f8956a0249edb0a672cd39ffd",
"outputIndex": 1,
"outputGlobalIndex": 54986521,
"outputCreatedAt": 1773831,
"outputSettledAt": 1773833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-21,16,62,105,32,-13,-28,99,-104,-111,59,-88,-96,-71,98,95,58,-2,78,41,-102,-26,-125,36,27,13,-17,94,25,25,70,102)\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(-32,11,-3,-91,40,-73,95,-59,-6,-66,-109,-49,-24,-17,-102,-12,86,-98,-112,40,-8,120,-33,-59,47,127,121,111,75,-93,27,-101)\n26: 0\n27: Coll(37,-26,116,48,120,-63,43,-38,-1,114,117,26,67,-31,106,-74,9,-82,-122,-71,-120,89,-66,75,-21,4,-41,-72,-90,74,-37,-74)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d0fad9e1a14419c21268ab34bd6f0e69ddd139a7b3138ebdc88a389e4eeb9afc",
"sigmaType": "Coll[SByte]",
"renderedValue": "d0fad9e1a14419c21268ab34bd6f0e69ddd139a7b3138ebdc88a389e4eeb9afc"
},
"R5": {
"serializedValue": "0e208226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0",
"sigmaType": "Coll[SByte]",
"renderedValue": "8226f7bf13b879625052d9b37199bd864914ad5a897703839b5f07172d8487e0"
},
"R6": {
"serializedValue": "0e20ae8797fb15302f1bbe417720984a63c7d9bb6ecb24bb9cc31ffa8260f5e4192a",
"sigmaType": "Coll[SByte]",
"renderedValue": "ae8797fb15302f1bbe417720984a63c7d9bb6ecb24bb9cc31ffa8260f5e4192a"
},
"R7": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
}
}
},
{
"boxId": "4833c93489b8c9da5159eeb030538df111e80b19be4eece830da531fda3f0469",
"value": 280985898,
"index": 8,
"spendingProof": "3cf349ab0a71b1793a019b9146dca22db7f87fbe69c33ae494615b5dacb2f681bb94e3c583e650de702f57aa3825196ad161d0d946ab4ae6",
"outputBlockId": "f2afa4e7e82e3d467633249d3e5b7dd1b75c50b64a68eb4ac15506129bc16ad1",
"outputTransactionId": "eac11340a3e130706f0fc26c87d978b5b1b74921648fddeafa848082f79eca71",
"outputIndex": 2,
"outputGlobalIndex": 54986490,
"outputCreatedAt": 1773831,
"outputSettledAt": 1773832,
"ergoTree": "0008cd03493df5985b25b2d5a7a4f1a1e7e324b8e19b08454f2bb374cd553c55251ec5eb",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(493df5,f7da54,...)))}",
"address": "9h24ZUeax6r5CYm5LJ1yraCs9n6wcbWMeSLbsZ8mbFqhrwCd9UB",
"assets": [
{
"tokenId": "1869438ac48258d19200d77ca9f7a9bd2f44dade01454fa12982f9453528eed0",
"index": 0,
"amount": 3,
"name": "WID-8eed0-rwCd9UB",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "f10ceec0a7c10326696297eb514f9323a067bc670f58e493410d1152beac75fd",
"value": 1100000,
"index": 0,
"outputBlockId": "df01d684c2f07b40acb9e645675f1356c2e6c791a6c5a3fde18f1105cf1faa31",
"outputTransactionId": "466d7a9d2d7cadee4262d89a354fde684ac926118e8b72b1051aca60b6be7f39",
"outputIndex": 1,
"ergoTree": "100604000400040004000e20a2d7f41b79f98bcaef08214b9e6bf0f3b803e446a9ef5949da799739555165aa0402d803d601b2db6501fe730000d602b2db6308b2a5730100730200d603b2db6308a7730300ea02d196830301aedb63087201d901044d0e938c7204017304938c7202018c720301938c7202028c72030298b2e4c672010510730500ade4c67201041ad901040ecdee7204",
"address": "prufxZid3SJMyUVhBMkLFHpReSPj7knVLihVSxxh55yh3X39NhP6cKMVYZYf6cFuP7267DEtkrWxFSbYqfX6zj2qY57ZBCNkFEQnJVGxvyjXnNJ1Nrj5YiymeX2SAb66uYfHxZJQTv9R7S6PE4vvnUp5oC4LbGaC4bo8HkGCUzpvpSLm9qeSzwFXdznsJketE6n6HLGLqNXQ3KZXNaG8",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1106d00f78022880dac409d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000,60,1,20,10000000,1000]"
}
}
},
{
"boxId": "3d2174170260745d199723b5d2a7c65d410f7a66c8a73273c707b922d456cdb5",
"value": 1100000,
"index": 1,
"outputBlockId": "877e9fcc0f82852dbc862b25d2836ce31a3e2e99eb793a1e5d44c9584bc1f5fc",
"outputTransactionId": "dfc56e8457686f2f6736b7975ffc1f7f54f557cdfeec6d58108a175bc77ee906",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "0510",
"sigmaType": "SLong",
"renderedValue": "8"
}
}
}
],
"outputs": [
{
"boxId": "bac65697b46c92f33c377cc84a797f5c78572d7e767c21276daff9f99ebb67f7",
"transactionId": "a66d2667cfb883eaa7d5a7ac3013e3a4c680595fae94dfc18cb3d14b365b09ea",
"blockId": "d8d02d9c863028004c96e7420068319b774a79e316c9cde03b1ce3e3c5e4af1f",
"value": 16000000,
"index": 0,
"globalIndex": 54986658,
"creationHeight": 1773837,
"settlementHeight": 1773839,
"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(15,-84,35,-48,-31,-37,105,58,-10,17,-26,123,-48,103,20,100,-94,-46,57,75,102,-31,112,-121,-43,-99,18,-94,99,110,-88,109)\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": "2f3b244636a930132609f9ba6e3c42b276520aeaf7f12c291748bbe330f17ae6",
"index": 0,
"amount": 8000,
"name": "RosenErgoRWT-PandoraV2",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20107cab0a49f02c943af7d4b164137978685ce6eecca2f0dc68c98b90ae6c5c8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "107cab0a49f02c943af7d4b164137978685ce6eecca2f0dc68c98b90ae6c5c8b"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[33363834323237653862363633616435346535343835626335383337336133356131326130656437353138343435303034616334376265636637306161306261,6572676f,63617264616e6f,39686167776e65484b4d424a484e37706e5238574c7744326e65354e5170575745434c45647778625339426d336969676d6b5a,61646472317179646a616c6d30723864666337723274306a6a6e7068796c32796777343835336c77677963757377306a746e716e756866337a666b7a35377178376a3370676c75717a6663356834346474777561706e6d7430346a7176677230717764396d716b,00000000000927c0,00000000000021ad,000000000000435a,34356331633830646533636131633066306432316362393836323033323839343439363637313037316161393233323839633664656531353736343738653233,33313635626536356130643463343936643065373765373536393631383234306461383531333565643335663332646232313263633933352e3732373036653436366637383734373236663734,66303362323365323138636539363134366566373530663864663831646132653831366166666362623137613039306262353833393934626461663661303733,00000000001b10f8]"
},
"R6": {
"serializedValue": "0e20ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75",
"sigmaType": "Coll[SByte]",
"renderedValue": "ab27e8b16c5ead1747b27e6631bced1250922009f56731caa7a739b1f7ba0b75"
},
"R7": {
"serializedValue": "0410",
"sigmaType": "SInt",
"renderedValue": "8"
}
},
"spentTransactionId": "d7b122800282dac54617342f2cae3091ab34995e0af716d75e3924b6fd905ce1",
"mainChain": true
},
{
"boxId": "ab1ec42e1071edce6729545f9a9480c3703d574b073edcdd3cf1ada24b06f2c8",
"transactionId": "a66d2667cfb883eaa7d5a7ac3013e3a4c680595fae94dfc18cb3d14b365b09ea",
"blockId": "d8d02d9c863028004c96e7420068319b774a79e316c9cde03b1ce3e3c5e4af1f",
"value": 278985898,
"index": 1,
"globalIndex": 54986659,
"creationHeight": 1773837,
"settlementHeight": 1773839,
"ergoTree": "0008cd03493df5985b25b2d5a7a4f1a1e7e324b8e19b08454f2bb374cd553c55251ec5eb",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(493df5,f7da54,...)))}",
"address": "9h24ZUeax6r5CYm5LJ1yraCs9n6wcbWMeSLbsZ8mbFqhrwCd9UB",
"assets": [
{
"tokenId": "1869438ac48258d19200d77ca9f7a9bd2f44dade01454fa12982f9453528eed0",
"index": 0,
"amount": 3,
"name": "WID-8eed0-rwCd9UB",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "c62cac18d929e922f7c9d31fce8803b38ad52de3d02c86601f28ad235087f884",
"transactionId": "a66d2667cfb883eaa7d5a7ac3013e3a4c680595fae94dfc18cb3d14b365b09ea",
"blockId": "d8d02d9c863028004c96e7420068319b774a79e316c9cde03b1ce3e3c5e4af1f",
"value": 2000000,
"index": 2,
"globalIndex": 54986660,
"creationHeight": 1773837,
"settlementHeight": 1773839,
"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": "a7c5d26d63bb7fb22d6e5e4f7c830309e0160174c7400e290228f2376f920b68",
"mainChain": true
}
],
"size": 1614,
"isUnconfirmed": false
}