Transaction
ID: 2398cc6234...716d
Inputs (10)
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:
0.000045 ERG
Tokens:
710.50
Spent
Address:
Output transaction:
Settlement height:
Value:
0.000045 ERG
Tokens:
410.30
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
1,394.91
Spent
Address:
Output transaction:
Settlement height:
Value:
0.018 ERG
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.012 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01809 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 128,671
Total coins transferred: 0.03209 ERG
Fees: 0.002 ERG
Fees per byte: 0.000001122 ERG
Raw Transaction Data
{
"id": "2398cc6234d4343e87dc93ef590b85e44c4d8564b459a8486157ea35b9e6716d",
"blockId": "64046c0ae8e672a96997d89569d341ce3220ca12d803cb1df880de1877deaa65",
"inclusionHeight": 1628043,
"timestamp": 1759741639588,
"index": 3,
"globalIndex": 9577031,
"numConfirmations": 128671,
"inputs": [
{
"boxId": "5d2dfe274238875014375acab82c8cb7aaa7fab8013eb8b56b3e03799d074498",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "8832af7cf6805e5e773cb0f9289a934faaef99b7e0b1951c470caf5b7595c638",
"outputTransactionId": "1534a8ed78fd6e1b6bf3b6c728152e3ec27ee05e66bd9ea1689d16478159b09b",
"outputIndex": 1,
"outputGlobalIndex": 50670763,
"outputCreatedAt": 1628023,
"outputSettledAt": 1628024,
"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": "0e2063103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "63103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2"
},
"R6": {
"serializedValue": "0e2068cffeae3b9caaad0a8793a6ec3bbe38e6ed112a302101c080280da1ae8a47a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "68cffeae3b9caaad0a8793a6ec3bbe38e6ed112a302101c080280da1ae8a47a4"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "f807364b360e3d9a9e58d4986a3a63855d580d102cb25087ad32b094bfc14d02",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "e5f4650fde899f6cafee89d2e9152cb8169f23b12a5ff8abc13b248ffeb693ba",
"outputTransactionId": "14e9f8f0d7fc8a5ca03e003621e7bedf43bdf7e23e2a85ed04ff935bc6a0f5c1",
"outputIndex": 1,
"outputGlobalIndex": 50671208,
"outputCreatedAt": 1628039,
"outputSettledAt": 1628040,
"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": "0e2063103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "63103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2"
},
"R6": {
"serializedValue": "0e204f80e3feddbee2245dcf48383319b241d22f441dc9ab17ec0cfea1aabe6d5105",
"sigmaType": "Coll[SByte]",
"renderedValue": "4f80e3feddbee2245dcf48383319b241d22f441dc9ab17ec0cfea1aabe6d5105"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "bb3f6f371b4eae8648292e296791a2b12f2b8d8c16ac092e91f63e5bd5a62fe8",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "e5f4650fde899f6cafee89d2e9152cb8169f23b12a5ff8abc13b248ffeb693ba",
"outputTransactionId": "62d9de4fc6e8e6814dee22574bd23499847770d9cf89563fba664287a68cdbe3",
"outputIndex": 1,
"outputGlobalIndex": 50671212,
"outputCreatedAt": 1628039,
"outputSettledAt": 1628040,
"ergoTree": "102404000e202ba73e9b8b6594136078d5e2a0584848f1fa9596891bc1eee804b624d5656879040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20569b1df978b5b57619ac0d1eeb28152a0ab4c906d97dc1220bf2a838e237059504000e20ac7bbfff7ec3852afae13153a9a5b063ac26fc43a780aa3468cec8c9cdd176b304020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"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": "0e2076b4eda1bb0e30d47ad77d0da8889b7dafc3410a430426228abb1230fa1a5f30",
"sigmaType": "Coll[SByte]",
"renderedValue": "76b4eda1bb0e30d47ad77d0da8889b7dafc3410a430426228abb1230fa1a5f30"
},
"R5": {
"serializedValue": "0e2063103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "63103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2"
},
"R6": {
"serializedValue": "0e202567b568f5c792fd15bc96e00fa24c03a2f6a3ad0589931256d3f40ead281aa7",
"sigmaType": "Coll[SByte]",
"renderedValue": "2567b568f5c792fd15bc96e00fa24c03a2f6a3ad0589931256d3f40ead281aa7"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "2b587d3e0681fdac4114a9ab96e0a3769eea8fbb3dd0037dc61f9ae11efdf4b3",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "e5f4650fde899f6cafee89d2e9152cb8169f23b12a5ff8abc13b248ffeb693ba",
"outputTransactionId": "62ddfac3f65e3d58d923fb85493ca242784a82c6410bf6bc1e3f1550b8342213",
"outputIndex": 1,
"outputGlobalIndex": 50671216,
"outputCreatedAt": 1628039,
"outputSettledAt": 1628040,
"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": "0e2092932311cd5401cd6690b8da274ff937b8f4196eda94fd45f33aca8d7593eb97",
"sigmaType": "Coll[SByte]",
"renderedValue": "92932311cd5401cd6690b8da274ff937b8f4196eda94fd45f33aca8d7593eb97"
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"R5": {
"serializedValue": "0e2063103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "63103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2"
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"R6": {
"serializedValue": "0e202aa343c66b09f6e4155411e70bc7f54fcdea38ae9d0a0ad0e0aec3cd48a35e5c",
"sigmaType": "Coll[SByte]",
"renderedValue": "2aa343c66b09f6e4155411e70bc7f54fcdea38ae9d0a0ad0e0aec3cd48a35e5c"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
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},
{
"boxId": "8a2f0b1f510cec0b45a3e7b47c2319d8b131bdbf2c1cb65707d0ea020f113725",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "e5f4650fde899f6cafee89d2e9152cb8169f23b12a5ff8abc13b248ffeb693ba",
"outputTransactionId": "7b67266117fd16c6f81e6132983366946ef9a17c82ce323fb38f763dc8859ea8",
"outputIndex": 1,
"outputGlobalIndex": 50671220,
"outputCreatedAt": 1628039,
"outputSettledAt": 1628040,
"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": "0e20163dd94c65197844769bc5cffbe329a6ca1fef23dcbd2dd0694de846c2094b4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "163dd94c65197844769bc5cffbe329a6ca1fef23dcbd2dd0694de846c2094b4b"
},
"R5": {
"serializedValue": "0e2063103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "63103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2"
},
"R6": {
"serializedValue": "0e20838bf6db03df9d5817fe31bf9899e43b16db3873ec21043cd215f23a70a67e89",
"sigmaType": "Coll[SByte]",
"renderedValue": "838bf6db03df9d5817fe31bf9899e43b16db3873ec21043cd215f23a70a67e89"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "73207983d820ee8dbc3caec0b33d62a8ee20866b49aab9ea7c4fffea941730be",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "b1ba6c595f5a78f4e606e30a2301921fa5f97c53e0bd24beb0383e951b72f104",
"outputTransactionId": "7dec255d336f4c146ee1ff6dfc2982f62f07f6483eefdaf8f13d11f3bb705a37",
"outputIndex": 1,
"outputGlobalIndex": 50671270,
"outputCreatedAt": 1628039,
"outputSettledAt": 1628041,
"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": "0e20a482c6a3fc2ee79314f23dd94060fb7b1996319d7c2587545600752376393115",
"sigmaType": "Coll[SByte]",
"renderedValue": "a482c6a3fc2ee79314f23dd94060fb7b1996319d7c2587545600752376393115"
},
"R5": {
"serializedValue": "0e2063103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "63103ca0d68747fb682e5cdba347003c60a72095ea37ecf02801c80e2491c7b2"
},
"R6": {
"serializedValue": "0e202659056e885297596fc7e3d4180f96bc6480081e0fef1b1fb9935a8bc6f389f4",
"sigmaType": "Coll[SByte]",
"renderedValue": "2659056e885297596fc7e3d4180f96bc6480081e0fef1b1fb9935a8bc6f389f4"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
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"value": 45000,
"index": 6,
"spendingProof": "1adc8266f03d57500a894f7ce9d9f380ac9e564463fe1bd37d86c1124cf04e1620139aa4efc9c30ba507a5c1b57b399026e9255b3173346d",
"outputBlockId": "7e442f0d6e769cb2a68be27a1563e887243f9ceec0911afc427e3ef8e5e5f326",
"outputTransactionId": "48bf9cf0dfc9da286dd5961ef8a18943d68671c0002c086f2fca3cc9747b6498",
"outputIndex": 232,
"outputGlobalIndex": 50066853,
"outputCreatedAt": 1609290,
"outputSettledAt": 1609340,
"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
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"index": 0,
"amount": 7105,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
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"spendingProof": "6c4395253e8af23094c2d896f4b62b5704ba9de5e2571482cc6ea0e9c3ce582b22e8e063ba0b6baaf72ae4405ce0cc5e50f895712dc921c3",
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"outputIndex": 232,
"outputGlobalIndex": 50099343,
"outputCreatedAt": 1609357,
"outputSettledAt": 1609362,
"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
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"index": 0,
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"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
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"outputTransactionId": "c0d6434e7f4db75a123902029081e0096c55e7187555d61c35d4b9455bcb9300",
"outputIndex": 1,
"outputGlobalIndex": 50271550,
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"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
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"index": 0,
"amount": 1394905,
"name": "RSN-Pandora",
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"type": "EIP-004"
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},
{
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"outputGlobalIndex": 50448536,
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"ergoTreeConstants": "",
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}
],
"dataInputs": [
{
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"sigmaType": "Coll[SLong]",
"renderedValue": "[1000,60,1,20,10000000,1000]"
}
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"R5": {
"serializedValue": "0510",
"sigmaType": "SLong",
"renderedValue": "8"
}
}
}
],
"outputs": [
{
"boxId": "81db498ea4945e0c64f06b64c6ec923df7e7e851b5bf7e22d8d308002e890b59",
"transactionId": "2398cc6234d4343e87dc93ef590b85e44c4d8564b459a8486157ea35b9e6716d",
"blockId": "64046c0ae8e672a96997d89569d341ce3220ca12d803cb1df880de1877deaa65",
"value": 12000000,
"index": 0,
"globalIndex": 50671292,
"creationHeight": 1628041,
"settlementHeight": 1628043,
"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": 6000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20219ff7e6cd5d693e8c1a813fdc90aab76527420c0685f787326b31844251a632",
"sigmaType": "Coll[SByte]",
"renderedValue": "219ff7e6cd5d693e8c1a813fdc90aab76527420c0685f787326b31844251a632"
},
"R5": {
"serializedValue": "1a0c4032323662326132303337316365396535663637396334636330373238363361376438373066326661393334376233323631313065376637353039316538656666046572676f0762696e616e63653339686167776e65484b4d424a484e37706e5238574c7744326e65354e5170575745434c45647778625339426d336969676d6b5a2a307830646538316237326233363665633966303031353834383935366161646536653234633038316162080000000000002ee00800000000000021ad0800000000000004b740343563316338306465336361316330663064323163623938363230333238393434393636373130373161613932333238396336646565313537363437386532332a307863653533303764393638633564323938323339666662376136623061626433316162613537313265406531663266623665646637353233336331356236653864633536373233343564383530666236343430633965333363383862373462626435376661623462363308000000000018d755",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[32323662326132303337316365396535663637396334636330373238363361376438373066326661393334376233323631313065376637353039316538656666,6572676f,62696e616e6365,39686167776e65484b4d424a484e37706e5238574c7744326e65354e5170575745434c45647778625339426d336969676d6b5a,307830646538316237326233363665633966303031353834383935366161646536653234633038316162,0000000000002ee0,00000000000021ad,00000000000004b7,34356331633830646533636131633066306432316362393836323033323839343439363637313037316161393233323839633664656531353736343738653233,307863653533303764393638633564323938323339666662376136623061626433316162613537313265,65316632666236656466373532333363313562366538646335363732333435643835306662363434306339653333633838623734626264353766616234623633,000000000018d755]"
},
"R6": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
},
"R7": {
"serializedValue": "040c",
"sigmaType": "SInt",
"renderedValue": "6"
}
},
"spentTransactionId": "aaccf299046b302bbc0c16bd84e104706200ab5147708e98389fa898b2a17900",
"mainChain": true
},
{
"boxId": "1e4ebe6c2b0ff3c30597085e039297ac6117c80001918e097d7e3e69f0f280a7",
"transactionId": "2398cc6234d4343e87dc93ef590b85e44c4d8564b459a8486157ea35b9e6716d",
"blockId": "64046c0ae8e672a96997d89569d341ce3220ca12d803cb1df880de1877deaa65",
"value": 18090000,
"index": 1,
"globalIndex": 50671293,
"creationHeight": 1628041,
"settlementHeight": 1628043,
"ergoTree": "0008cd03feb53f5bf3db9676adcb5adabafbd7aa1234c562bc917c386154b1b5a1c25da3",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(feb53f,b54b68,...)))}",
"address": "9iPys9S5TSs52CCprKmopf2BNbvWEHZjhsNTXuG2CLW3GkcgVYg",
"assets": [
{
"tokenId": "31ac0f72b036502a17e27ff3bc9eb1b3ae4eef9aa4a3c3bd818475d6326cbd9f",
"index": 0,
"amount": 7105,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
"tokenId": "ed2197ebb2b958670cb568aeed54693617a3f3718d16d1a298b8c8d337193da0",
"index": 1,
"amount": 4103,
"name": "ClaimRSN.tech",
"decimals": 1,
"type": "EIP-004"
},
{
"tokenId": "d752bede1a85891fff344604431fd6dc30ba685b382f2e0fe15da8141d36e34e",
"index": 2,
"amount": 1394905,
"name": "RSN-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a4afdc922cde3a877649475c550ca8658ed1409f4fa84e2a2f778f96b569ace7",
"mainChain": true
},
{
"boxId": "54ac4d7edc4afda79c37f9b67ac227408d72bb827d2690ab5406c0163324d2a1",
"transactionId": "2398cc6234d4343e87dc93ef590b85e44c4d8564b459a8486157ea35b9e6716d",
"blockId": "64046c0ae8e672a96997d89569d341ce3220ca12d803cb1df880de1877deaa65",
"value": 2000000,
"index": 2,
"globalIndex": 50671294,
"creationHeight": 1628041,
"settlementHeight": 1628043,
"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": "9de985b83e496bc2ef7fd625846e2de6bb7f1d047a5c3de4d3b0fa5f5365e1d2",
"mainChain": true
}
],
"size": 1783,
"isUnconfirmed": false
}