Transaction
ID: 9b6b5086f2...0a68
Inputs (7)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
14
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Transaction Details
Confirmations: 331,338
Total coins transferred: 0.014 ERG
Fees: 0.002 ERG
Fees per byte: 0.000001387 ERG
Raw Transaction Data
{
"id": "9b6b5086f2cd0ee208c4b322c3c22d7f109f6563ecaeadc68e3da8a28ed60a68",
"blockId": "8d045ff91fdcb1856d7d108f1663a5d374eebf7f850264f1db175bb586a73a9e",
"inclusionHeight": 1431315,
"timestamp": 1735910130239,
"index": 3,
"globalIndex": 8372074,
"numConfirmations": 331338,
"inputs": [
{
"boxId": "a7a576278ca8d880522b01c28d7774c7f9051bc71969883396553303ac0a978c",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "3299212b3914308fd24c3cb0a4cf4207472aacdf5204adfe36a7e31375392e49",
"outputTransactionId": "192c0bf918ca559f112a8d3748dbb78da7ec7f9af01158bff6ea3ac3f94485ec",
"outputIndex": 1,
"outputGlobalIndex": 45314311,
"outputCreatedAt": 1431305,
"outputSettledAt": 1431307,
"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"
},
"R5": {
"serializedValue": "0e20d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9",
"sigmaType": "Coll[SByte]",
"renderedValue": "d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9"
},
"R6": {
"serializedValue": "0e200b9d11005ca98e7e482d9264db2da09d10584564b3d83fc7b8086de91893e5dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "0b9d11005ca98e7e482d9264db2da09d10584564b3d83fc7b8086de91893e5dd"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "7f00187d2547d8605527b60272125bc70ff2c7b7f29a39c11cfa2d96701a277c",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "98fae7e172972f514ec1ce26d89f2111c534dc9efcca0d92243efe10f3eeeb2c",
"outputTransactionId": "bdd456e9d3dfb7b38d218dafb56dff738f1d70e25206c1b4eb38f215c6045b28",
"outputIndex": 1,
"outputGlobalIndex": 45314336,
"outputCreatedAt": 1431305,
"outputSettledAt": 1431308,
"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": "0e20143f7c38a3e10ba24ccb7c4975dd091d0a9b916304c57db6a0534c4b493ce208",
"sigmaType": "Coll[SByte]",
"renderedValue": "143f7c38a3e10ba24ccb7c4975dd091d0a9b916304c57db6a0534c4b493ce208"
},
"R5": {
"serializedValue": "0e20d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9",
"sigmaType": "Coll[SByte]",
"renderedValue": "d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9"
},
"R6": {
"serializedValue": "0e20320812def0137618741e8cf6625c240b738f9da9341729164e158d3ab161206d",
"sigmaType": "Coll[SByte]",
"renderedValue": "320812def0137618741e8cf6625c240b738f9da9341729164e158d3ab161206d"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "aa8bb0990cccc1b89ea6f2d2334f13f66a0a4e0d013e6fb688821ce02c2416ff",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "98fae7e172972f514ec1ce26d89f2111c534dc9efcca0d92243efe10f3eeeb2c",
"outputTransactionId": "dc9b78ac30b152385cd31eb1e58f5d65d5f73d74a3d218f86aae26662e383990",
"outputIndex": 1,
"outputGlobalIndex": 45314341,
"outputCreatedAt": 1431305,
"outputSettledAt": 1431308,
"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": "5ivrmzxYZYBHWVcmjndfS3F1g11Z2nxtzwrtzGLeesX6BGtSkk2sfVr9PY1G9AWhmMFZ1NE9Qmt6rEJPnVhYHdHHtjGVjScc1kXMnv2bk3PPU3sgKTNRpKGR1GFZikT52tFYioZjbZeZmVLbF3HQqwKYzhqfu54VyApQoZSRJcaiP7gyAtZiWVkqrL8giqbATFeyaKwC63iBzyJ5o7u8jgf51GsnZB3HYDoCuW2yE1nqH1UaBYuKvtpBoQiqEG7WqzQCsbW2jReFJfyWtK37t7ompt6E8oStB9RF418Lp8zAjewcaatxgtbxvyVZRvABV7cwxkNfuY23PrgsXNhV6Xu5yMycCBjG5AUNcuZKh7Z8a68NaxiQisjrwjbs5NAemPKp1GbUEhdkjpR5muJjs4UnpePEiugpdbpDShn9QiazLeExHKefHW7DxaNLYneVaXZKrtWLXtuAcpcZ71zD23gSoWYKDwAa6QeX7981njAp8zqrtb7Xf9XwZUPdf9vA6hJVcspUPpAzapj8PCuoQMFBFjxx9wGLLr7mTZL1YWsvjhSomGwECp7r47uthgYvdhpj6LoToqcY4Q8jWU4eCB2v3dzNVruKqFosgvQnamu9vWrQQosShiU5pPsqL6NjJ27Nw5VRrcKitYywRoVNutWEqNc3uDpkGejYJkjTBGzgt6jREPGMy35t96wQL6zVjMUsL8gNJTQa29RpNDtrSjtkgF3N8NrnnV9ZzyQZs1iFpZ6QRCN95V6tohrSopKp1XyeG3kj9ptivzwodhMomyhMWhGdsytsKJ8rspKNBaBL5sNpa3gtg53bxpM9vP7tYGKa6ejn9JJe1ncpXQyGnAnsz5WVwmnGGLro6bNme835n32gCaYp5ZE2N5X8ztUpxEF4ZfmmmWy3un9AU4HRZqspnRKMR8fz3u3cscGwMvgHbZ6Hb5kTTB57qmE1RUDXHG9jY7Gdpc2gzyvSShxYW9KyydZyC8JHjLSq6wY5jegcfS6wt3FiDJs53FX8C98u2gKsnJf9wmMrVM5pv2NMX2a8HoADq1pJVT58CvT4S4VV1wB1AWynP7NcyEsEfHQRTZYvVaqYY7SkzncJaaictouXkGUy8Dtd5cHzuJTVxiRjRScNgruqVYH6BBeDjCQKfNtned3X8ayprRgTx44fdx2KRSM6X9aqZ3ukaZuPeAuU3h2ym6Sdz2FKoK7LgxcQdNQ5FJpz66Dk7XBRYnJQfUUpm7nMJASnuYQk6HoXUmUJcfNGSHKyhe6RWFNuNCEbfWzBJYdXRqZoZ9kUKeA7b",
"assets": [
{
"tokenId": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20195bd457085e48b0e1467da99f011fc67827480c8a991b9a1ba53a6d2bb135d4",
"sigmaType": "Coll[SByte]",
"renderedValue": "195bd457085e48b0e1467da99f011fc67827480c8a991b9a1ba53a6d2bb135d4"
},
"R5": {
"serializedValue": "0e20d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9",
"sigmaType": "Coll[SByte]",
"renderedValue": "d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9"
},
"R6": {
"serializedValue": "0e209c95dea5393ff55c4195324e87405b3c4a128787ee1cb0546ad2ad94829c1f89",
"sigmaType": "Coll[SByte]",
"renderedValue": "9c95dea5393ff55c4195324e87405b3c4a128787ee1cb0546ad2ad94829c1f89"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "7e99c6c248572d123d55c5eafae4a7526c4a454671b47adf374dc3d7b5d3ad9d",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "98fae7e172972f514ec1ce26d89f2111c534dc9efcca0d92243efe10f3eeeb2c",
"outputTransactionId": "e6fa1072c2a51cdeced190af1800184393e10f3499cb49bafb186aff62386c11",
"outputIndex": 1,
"outputGlobalIndex": 45314346,
"outputCreatedAt": 1431305,
"outputSettledAt": 1431308,
"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"
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"R5": {
"serializedValue": "0e20d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9",
"sigmaType": "Coll[SByte]",
"renderedValue": "d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9"
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"R6": {
"serializedValue": "0e20e00e40f069ea3f91f09dd92d2e5a19a6d28277b10be37bc5433948e9bcdb18c0",
"sigmaType": "Coll[SByte]",
"renderedValue": "e00e40f069ea3f91f09dd92d2e5a19a6d28277b10be37bc5433948e9bcdb18c0"
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"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
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}
},
{
"boxId": "f43d09606426f31d6e1bb84ab20eb9d27e1e259f1d0e00ba12ff19f174d33662",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "98fae7e172972f514ec1ce26d89f2111c534dc9efcca0d92243efe10f3eeeb2c",
"outputTransactionId": "ff98a511f8911f933705cf69766e9cdf7239ae74033d73b64c15921020cb139c",
"outputIndex": 1,
"outputGlobalIndex": 45314351,
"outputCreatedAt": 1431305,
"outputSettledAt": 1431308,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(43,-89,62,-101,-117,101,-108,19,96,120,-43,-30,-96,88,72,72,-15,-6,-107,-106,-119,27,-63,-18,-24,4,-74,36,-43,101,104,121)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(86,-101,29,-7,120,-75,-75,118,25,-84,13,30,-21,40,21,42,10,-76,-55,6,-39,125,-63,34,11,-14,-88,56,-30,55,5,-107)\n26: 0\n27: Coll(-84,123,-65,-1,126,-61,-123,42,-6,-31,49,83,-87,-91,-80,99,-84,38,-4,67,-89,-128,-86,52,104,-50,-56,-55,-51,-47,118,-77)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 0",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 1000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a482c6a3fc2ee79314f23dd94060fb7b1996319d7c2587545600752376393115",
"sigmaType": "Coll[SByte]",
"renderedValue": "a482c6a3fc2ee79314f23dd94060fb7b1996319d7c2587545600752376393115"
},
"R5": {
"serializedValue": "0e20d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9",
"sigmaType": "Coll[SByte]",
"renderedValue": "d05213e38b711073541c9ffc41375e8135cea194659a40e558d61a98a7515cc9"
},
"R6": {
"serializedValue": "0e203b0443457acee6fdc1a7aa6ac6d29fc0d57c5e620f51aac9410e174ddf03be9c",
"sigmaType": "Coll[SByte]",
"renderedValue": "3b0443457acee6fdc1a7aa6ac6d29fc0d57c5e620f51aac9410e174ddf03be9c"
},
"R7": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
}
}
},
{
"boxId": "82d36c7a5d95e0c052f44390d3e5e6be54c4fc9fac7e135e5e7d1f92081598e8",
"value": 2000000,
"index": 5,
"spendingProof": "ee76c0378dd6aa284da8fef5dd35c781dc42334ebae20e6985c7b9830c1074043e93365f14356f2ffb40c354134ead4242c8834269b6dc08",
"outputBlockId": "a162c47a23375cd270c78c74741a30f9d011ebd3c9ec7d2c8803d50ce7984d1c",
"outputTransactionId": "20a87dea8ce1a7fa0da3edb2117d0d09328acc0575cacfb791660c262eaab575",
"outputIndex": 3,
"outputGlobalIndex": 45165401,
"outputCreatedAt": 1426986,
"outputSettledAt": 1426989,
"ergoTree": "0008cd026abf1bf8e2edb6309bd3e363654b15dc987e9ed8c6fd7612eb608c6d27c5a23a",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6abf1b,b6ef8c,...)))}",
"address": "9fL5DEA51CCVT5aeeSzE7T1F1EvJfEysEEFW1DE3RCSoocpg44X",
"assets": [
{
"tokenId": "bbcb0dc09acb34c09d767aa43683ff2a360fdb4496344988ea10ff5d93ac348a",
"index": 0,
"amount": 7000,
"name": "eRSN-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "7ff584350c1a7c72fb15999b7c4cbbc6840942cb569678284a9118ad643cc937",
"value": 2000000,
"index": 6,
"spendingProof": "0f95c81b475004f74d4765488904cb566cb77aa25ab4f62d821a973046b3881cc6989762e5c464cbd10c59e022b9afa71a821785f9fabf19",
"outputBlockId": "c2f264d283de05d457e5f5109dcd6741be8bf78884af66fdd808091d9c7d9687",
"outputTransactionId": "831f36dc46cb82ff639e106b15055edc50df1e3996a13f1003cb5e81931dbdf6",
"outputIndex": 3,
"outputGlobalIndex": 45212131,
"outputCreatedAt": 1428591,
"outputSettledAt": 1428593,
"ergoTree": "0008cd026abf1bf8e2edb6309bd3e363654b15dc987e9ed8c6fd7612eb608c6d27c5a23a",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6abf1b,b6ef8c,...)))}",
"address": "9fL5DEA51CCVT5aeeSzE7T1F1EvJfEysEEFW1DE3RCSoocpg44X",
"assets": [
{
"tokenId": "bbcb0dc09acb34c09d767aa43683ff2a360fdb4496344988ea10ff5d93ac348a",
"index": 0,
"amount": 7000,
"name": "eRSN-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "2ca6961f893294c9f610d14e821246ea082f91dc85fa3ff6a5d424597bc66842",
"value": 1100000,
"index": 0,
"outputBlockId": "cc658e91e71a55cf8bba1ad8e59158f7334cacf77dd49c73735a3757b5cf9be0",
"outputTransactionId": "4404adbad11917061fcdc5057c7b9f836143e2ab2d124567d2c867de08be873a",
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"ergoTree": "100604000400040004000e20a2d7f41b79f98bcaef08214b9e6bf0f3b803e446a9ef5949da799739555165aa0402d803d601b2db6501fe730000d602b2db6308b2a5730100730200d603b2db6308a7730300ea02d196830301aedb63087201d901044d0e938c7204017304938c7202018c720301938c7202028c72030298b2e4c672010510730500ade4c67201041ad901040ecdee7204",
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"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1106d00f78022880dac409d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1000,60,1,20,10000000,1000]"
}
}
},
{
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"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "050a",
"sigmaType": "SLong",
"renderedValue": "5"
}
}
}
],
"outputs": [
{
"boxId": "b1edba1fdbd2e3da769a377ac07c0897d32da1be102499f98651ea11df10911e",
"transactionId": "9b6b5086f2cd0ee208c4b322c3c22d7f109f6563ecaeadc68e3da8a28ed60a68",
"blockId": "8d045ff91fdcb1856d7d108f1663a5d374eebf7f850264f1db175bb586a73a9e",
"value": 10000000,
"index": 0,
"globalIndex": 45314454,
"creationHeight": 1431312,
"settlementHeight": 1431315,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: Coll(102,106,3,-81,2,114,104,-27,91,-80,-88,89,15,85,-107,-57,-56,-58,125,-28,-97,-91,126,-103,-76,126,-65,57,105,-103,-118,41)\n10: 1\n11: 0\n12: Coll(-113,-66,-52,-97,79,105,104,-79,-127,-41,13,51,127,51,114,-98,-101,60,-75,-111,-1,-49,-113,-54,22,40,44,-53,-60,-121,-91,-121)\n13: 10\n14: Coll(9,-81,-23,48,20,-10,-106,10,-86,-61,7,28,-111,-102,-31,-125,0,-15,92,117,-92,109,-45,-78,47,-79,-8,-64,30,101,-9,91)",
"ergoTreeScript": "{\n val i1 = SELF.R7[Int].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == SELF.tokens(placeholder[Int](2))._1)\n }).slice(placeholder[Int](3), i1)\n val coll3 = OUTPUTS(placeholder[Int](4)).propositionBytes\n val coll4 = blake2b256(coll3)\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll2.size == i1, SELF.R4[Coll[Byte]].get == blake2b256(\n coll2.map({(box5: Box) => box5.R4[Coll[Byte]].get }).fold(Coll[Byte](), {(tuple5: (Coll[Byte], Coll[Byte])) => tuple5._1.append(tuple5._2) })\n ), coll2.forall(\n {(box5: Box) =>\n ((box5.propositionBytes == coll3) && (box5.tokens(placeholder[Int](5))._1 == SELF.tokens(placeholder[Int](6))._1)) && (\n box5.tokens(placeholder[Int](7))._2 == SELF.tokens(placeholder[Int](8))._2 / i1.toLong\n )\n }\n ), if (coll4 == placeholder[Coll[Byte]](9)) {\n allOf(\n Coll[Boolean](\n INPUTS(placeholder[Int](10)).tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), HEIGHT - placeholder[Int](13) >= SELF.creationInfo._1\n )\n )\n } else {\n allOf(\n Coll[Boolean](INPUTS.exists({(box5: Box) => blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](14) }), coll4 == SELF.R6[Coll[Byte]].get)\n )\n }\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "34529f875cad2bf58c5ffb4a9056d26c590f0c35f77958a68dcdb4aa39b437aa",
"index": 0,
"amount": 5000,
"name": "RosenErgoRWT-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f5d24cd99ff999d8d470e50e984953a5097a61c6a7b1915d4fb0a2425aa6356b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f5d24cd99ff999d8d470e50e984953a5097a61c6a7b1915d4fb0a2425aa6356b"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[30636539666661386662376566313734393632333737636262333032383037623137616562646338313764356336303061616665626534663961643966323262,6572676f,62696e616e6365,39686167776e65484b4d424a484e37706e5238574c7744326e65354e5170575745434c45647778625339426d336969676d6b5a,307837623265623836376639366432656534623838326332636239646635343261386365616535303963,00000000001a286d,00000000000ae62e,00000000000186a0,38326637636563366436383265386130643936356536643933646536366563313839333366373231383163353961356438353830326630666532616663393863,626e62,30333263383032626561353538666165653333623265343836383337663630396461633134653339393737376366633864643933643039343964326461376263,000000000015d700]"
},
"R6": {
"serializedValue": "0e20eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94",
"sigmaType": "Coll[SByte]",
"renderedValue": "eae77168549514eb08e36857b4b26a9fe9f03104eed6c432e4c8331ea63e0e94"
},
"R7": {
"serializedValue": "040a",
"sigmaType": "SInt",
"renderedValue": "5"
}
},
"spentTransactionId": "9322a9d7e6fabe045447321863fa3ee294f23c5b674034bd1dd6cf484ffa8759",
"mainChain": true
},
{
"boxId": "67c798c30ac59245e7d1d77b643c113505889b81ef208c9696898e40ddb041de",
"transactionId": "9b6b5086f2cd0ee208c4b322c3c22d7f109f6563ecaeadc68e3da8a28ed60a68",
"blockId": "8d045ff91fdcb1856d7d108f1663a5d374eebf7f850264f1db175bb586a73a9e",
"value": 2000000,
"index": 1,
"globalIndex": 45314455,
"creationHeight": 1431312,
"settlementHeight": 1431315,
"ergoTree": "0008cd026abf1bf8e2edb6309bd3e363654b15dc987e9ed8c6fd7612eb608c6d27c5a23a",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6abf1b,b6ef8c,...)))}",
"address": "9fL5DEA51CCVT5aeeSzE7T1F1EvJfEysEEFW1DE3RCSoocpg44X",
"assets": [
{
"tokenId": "bbcb0dc09acb34c09d767aa43683ff2a360fdb4496344988ea10ff5d93ac348a",
"index": 0,
"amount": 14000,
"name": "eRSN-Pandora",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "aa4e80c1409dcd5148fc523b9e59bef953529966a45d1b45d09a8ba3c08ad4a0",
"mainChain": true
},
{
"boxId": "012cc00631aada3390d9bbcceca2e3975bbfc01e95e8a7825da0029cb1b51528",
"transactionId": "9b6b5086f2cd0ee208c4b322c3c22d7f109f6563ecaeadc68e3da8a28ed60a68",
"blockId": "8d045ff91fdcb1856d7d108f1663a5d374eebf7f850264f1db175bb586a73a9e",
"value": 2000000,
"index": 2,
"globalIndex": 45314456,
"creationHeight": 1431312,
"settlementHeight": 1431315,
"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": "9fdd9a7b293e971d5a6ec7d9e59a4ba77f477857f442436027c46af446c89531",
"mainChain": true
}
],
"size": 1442,
"isUnconfirmed": false
}