Transaction
ID: 71ea22254e...40e8
Inputs (11)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
10
Spent
Address:
Output transaction:
Settlement height:
Value:
2.61 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
100
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.61 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 625,550
Total coins transferred: 2.62 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000624 ERG
Raw Transaction Data
{
"id": "71ea22254e9c2c49acf65ca082e1c7de0d8c4e799887a3991770f5c4410440e8",
"blockId": "d841e6638c00c793b2106123802c7937ac2f313442e068047e403d1ff6fd3ca6",
"inclusionHeight": 1142792,
"timestamp": 1700982403353,
"index": 9,
"globalIndex": 6174758,
"numConfirmations": 625550,
"inputs": [
{
"boxId": "b80ed934e68eba37a9522e470ff840de63acdc64f4a3e7ab767546b9b3d2e7d6",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "81f20e9a21a666006813960bae8be6ea498e6695af35b27551daa0c6a24027dc",
"outputTransactionId": "ae6114ae86b73781b9c21ae69c691fcfe6987c6f60917fb94f4645b88dbb1fac",
"outputIndex": 1,
"outputGlobalIndex": 34577323,
"outputCreatedAt": 1142780,
"outputSettledAt": 1142784,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "01553e0f9122ce7a8dc696fa227d6b09a63dc7eb20a351bfa4f1108c14238895",
"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01209619de151da8f361043383a8ed1b4793d275d5de01c4c20a82e7f30305ffde70",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9619de151da8f361043383a8ed1b4793d275d5de01c4c20a82e7f30305ffde70]"
},
"R5": {
"serializedValue": "1a0120e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f]"
},
"R6": {
"serializedValue": "0e202d76c8adf63821fab6653fcc5bed39ca4e519bbb9244a778491eed0a7621c0f8",
"sigmaType": "Coll[SByte]",
"renderedValue": "2d76c8adf63821fab6653fcc5bed39ca4e519bbb9244a778491eed0a7621c0f8"
},
"R7": {
"serializedValue": "0e20a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849",
"sigmaType": "Coll[SByte]",
"renderedValue": "a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849"
}
}
},
{
"boxId": "76e1471702afc7fff7d1071f1a3971ea01f4339f44ed6d9506e8bc2ddc8283bf",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "81f20e9a21a666006813960bae8be6ea498e6695af35b27551daa0c6a24027dc",
"outputTransactionId": "476fd0e305f2729a3f84b35f5bb2d2b307b8e2c63e7051789e08b95e0fa8ea50",
"outputIndex": 1,
"outputGlobalIndex": 34577362,
"outputCreatedAt": 1142780,
"outputSettledAt": 1142784,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "01553e0f9122ce7a8dc696fa227d6b09a63dc7eb20a351bfa4f1108c14238895",
"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[620af66be09e0cb5948e2666154979935e10b15f2faff1c9a89a1f7a35dedb5d]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f]"
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"sigmaType": "Coll[SByte]",
"renderedValue": "54f4d16041ce50c102300b371b10fa16392611cd89e76e62dd7299dec4835875"
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"sigmaType": "Coll[SByte]",
"renderedValue": "a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849"
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"index": 2,
"spendingProof": null,
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"outputGlobalIndex": 34577367,
"outputCreatedAt": 1142780,
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"ergoTree": "101f04000e20f28a05677bce5adf234c00e423cab1acdd1d3f23610a82e8bc0a5f658eda8aa80400020004020400040004000400040004000400040604040402050205c8010400040004000e20923aa955f4f1b67409044ee28b78bb6caff649c9de45a192fd313703743dd8e30402050004020400040004000400040204000400d80ad601b2a4730000d6027301d60393cbc272017202d604e4c6a7041ad6059572037201b2a5730200d606e4c67205041ad607e4c67205051ad608b072078301027303d901083c0e0eb38c7208018c720802d609b472087304b17208d60ab2a5730500957203d803d60bb2b5a5d9010b63d801d60dc6720b041aede6720d93e4720d7204730600d60cb2db6308720b730700d60db2db6308a7730800d19683050193cbc2720be4c6a7070e938c720c018c720d01938c720c028c720d02efae7206d9010e0e93720483010e720e93cbb37209b27204730900e4c6a7060ed801d60bcbc2720a9593720b7202d80cd60cb2db6501fe730a00d60ddb6308720cd60eb2db6308a7730b00d60f8c720e01d610b5a4d901106393c2a7c27210d611b17210d6127e721105d613e4c6720c0611d614b27213730c00d6159ab27213730d009d9cb27213730e00997eb1e4c6720c041a05730f7310d616b27213731100d617b2db63087205731200d196830d01938cb2720d731300017314938cb2720d73150001720f92c1720ab0ad7210d9011863c172187316d90118599a8c7218018c72180293b1b57210d901186393e4c67218041a72047317ae7206d901180e9383010e7218720493e4c67205060ee4c6a7070e93b17206721193cbb37209b27204731800e4c6a7060e93e4c6a7051a83010ecbb27207731900917212958f7214721572147215938c720e027216938c7217029c72167212938c721701720fd802d60cb2db6308720a731a00d60db2db6308a7731b00d19683060193c5a7c57201938c720c018c720d01938c720c028c720d0293e4c6720a041a7204938cb2db6308b2a4731c00731d0001b27204731e0093720be4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "1a012087c369e9cba6a1875f41e9cf58e0ddd67907d31ccb4592714c41a2e9a0616fcb",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[87c369e9cba6a1875f41e9cf58e0ddd67907d31ccb4592714c41a2e9a0616fcb]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f]"
},
"R6": {
"serializedValue": "0e2007f5a2772eb9f99e4443a7a6ec2fa593398c070da51a223b98ad8821e4868a4b",
"sigmaType": "Coll[SByte]",
"renderedValue": "07f5a2772eb9f99e4443a7a6ec2fa593398c070da51a223b98ad8821e4868a4b"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849"
}
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{
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"value": 1100000,
"index": 3,
"spendingProof": null,
"outputBlockId": "81f20e9a21a666006813960bae8be6ea498e6695af35b27551daa0c6a24027dc",
"outputTransactionId": "d359d4a27e0cb1ff1be1ac29f2b057aaeff846a4097f708bfd34d0d9e7cb387c",
"outputIndex": 1,
"outputGlobalIndex": 34577372,
"outputCreatedAt": 1142780,
"outputSettledAt": 1142784,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "01553e0f9122ce7a8dc696fa227d6b09a63dc7eb20a351bfa4f1108c14238895",
"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "1a0120b93488e537f0597ff58be00fff65f290459fbf7917840c589746d96f5f1c1f6d",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[b93488e537f0597ff58be00fff65f290459fbf7917840c589746d96f5f1c1f6d]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f]"
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"sigmaType": "Coll[SByte]",
"renderedValue": "a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849"
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"index": 4,
"spendingProof": null,
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"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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
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"sigmaType": "Coll[Coll[SByte]]",
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f]"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "35e0aeea3812a401acd505566db30b98c21e094d733537cb2413acbd4f2c94c0"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849"
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{
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"value": 1100000,
"index": 5,
"spendingProof": null,
"outputBlockId": "81f20e9a21a666006813960bae8be6ea498e6695af35b27551daa0c6a24027dc",
"outputTransactionId": "33a1ae3bdd7852f5b271633372921a10b5993b75b0dffcca5c44683eb6403efd",
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"outputGlobalIndex": 34577392,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
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"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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"index": 0,
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"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
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"sigmaType": "Coll[SByte]",
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"R7": {
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"sigmaType": "Coll[SByte]",
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"index": 7,
"spendingProof": null,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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{
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"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
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{
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"spendingProof": null,
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"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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
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"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[6a8162f121d36bfe4204870885979014ce0d1a644f965398b1a53333b934dd52]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[e502c8d7d1b508fbb8074fde34fd7dbbc97feb43e19644f40b6cba24f8d6874f]"
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"R6": {
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"sigmaType": "Coll[SByte]",
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"R7": {
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"sigmaType": "Coll[SByte]",
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"value": 1100000,
"index": 9,
"spendingProof": null,
"outputBlockId": "81f20e9a21a666006813960bae8be6ea498e6695af35b27551daa0c6a24027dc",
"outputTransactionId": "928bcc0dcb313a75d73cbf24cf27ae18d32b66515a26fb66b580e09355002256",
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-14,-118,5,103,123,-50,90,-33,35,76,0,-28,35,-54,-79,-84,-35,29,63,35,97,10,-126,-24,-68,10,95,101,-114,-38,-118,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 3\n13: 2\n14: 1\n15: 1\n16: 100\n17: 0\n18: 0\n19: 0\n20: Coll(-110,58,-87,85,-12,-15,-74,116,9,4,78,-30,-117,120,-69,108,-81,-10,73,-55,-34,69,-95,-110,-3,49,55,3,116,61,-40,-29)\n21: 1\n22: 0\n23: 1\n24: 0\n25: 0\n26: 0\n27: 0\n28: 1\n29: 0\n30: 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[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"index": 0,
"amount": 10000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
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"spendingProof": "1f352cd55e8bf07032bee7a0035c29e9c9ae20c9c2fd3e81bfc2d51161c0d6ee3ed260b7e21587bf621864597e33af104d43f4c3955e2f5e",
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2db1e7,61f44d,...)))}",
"address": "9esBjMR99man7D2h24LR7oyR2h6bDbRoZx9MPT8ZcBZH2Jd2p1o",
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"amount": 1,
"name": "WID-2Jd2p1o",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "2db393f1a886baf8c881d039a19e6d293587444ae87f8da1be9e123fedf21e1a",
"value": 1100000,
"index": 0,
"outputBlockId": "9f8a4f4430978213d02d061849e0d344ec1e0cdb672c3e48d35717443bbf3a23",
"outputTransactionId": "39e6487f84bc58123c9b308946e97cad34b09b5e6d81e083cb5bbe7dd210ccb4",
"outputIndex": 0,
"ergoTree": "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",
"address": "LXwmG9jPiXvaSL1s7VyAp1WyJDAVu1fYyBWu3p6w9La1nKe8Xa83brDxkgBz8GahTFJJKMjM21rwkHwuUBuGQ2ksNYZY4HNRqzuuoCzmuV6v6Coh3rFnropRJn1Z1XEzY3mM3Cq2Xr2Aj98xZYE2SCmFo7BDuMLLCt5khd4J3r7TUgnFV1Qd4RLDocVh2UhGZwWKMqo6yfcYHauhvNXzCveBVnTyd3AAU7e5tyRepWtcQAtQ4uJQf1WWRLzdaVCatoY9SxjxNvPzjFPQu2UCbrk3nTxb7pH2Qra6aDSSDeizG9yWsKKG9zZ5pCDfRoHmaTEYmr4QW9kM6ZA7LmbFqGB2p9T4pYbKXrFSoXujRTLY4S1Si4qLRPifsHgUg9joCSkNbEpqX9vPyw4TXeNUGAaM1x1o5dr4DjCGZdFcHiGP2A6GDgupSgVYnLAvWKfJEdV9eDk1uJMnVfig3oPt9XGmaoZiT6Ahmd7yCPuiNBNSiUFc1dbiAmgfXm4nJ7QYSemJ9oUrM7v1oPVjWiwWJXEZbqzfxyibe8Mbwxu2JtvUuGm8gU1tisWWT41Hr7QDXZ47BgApVbx9wmhstx8S5PYYUPAJENVpevBu2Y6KRwM7mh2ZFwXWD1PGN5kPTa4gBWkkXDeHpTrGcYfXKhtQBsbQELejf7KPndCzbhtg389VgnYam1KdYki5c1Cfp8i5wfexPqPXWhm7nrPzv1BgEtsJDDgJtYuk6tG9LxA71XacbWBRmH7p7CP5oTqAaoAeDCmrM4zqb1CMZQdSF3ugBydzsdfRVGqj5dsmvxLPM6pdf68CveKPxexxC3J8GHtEv5HvMnWujLjun4C8j3fbypE5acVKMaAgV2pUVzino5ozrBZq8uZBUpXQ6mKk8uHvya1KS1QxTxEzdr3ojvUWqsBb6uiGre3WKa9Vmnxvyb7XjnaaHdSPkXLhtDke9VqxFmVqxwxMJmLNz8YQEE2WXLMQa8a3aFFeQRqm3ELAH6LLRzDPkGTHkYCBSpVQvJUt678r3JNrwKjgLHsWymLgf63gJ9zzcUjzjmDsWsoBPaz6iKs2R9hHWcAcPcSb6ES7fUViyAiProzaqWb48cVcjTiMzDWNyfFans9mcVn2YzbSSdxY589Fxa1NSxcBFiY93VMc5vW6ySKJuzVcrLnVtXzEnDjYrgq14wp9sMipD94zEea4PDrPsAhxLxowsHQGzPFriV2KJ7wzHXFkA4UYtKG23uEcLcb3sJ4qyPRCenareRzSAjELrweMbro87QkzcJsUrneU8BupVtam84vS3wbc3wrTJTUZYUqVnFwzqoiYSfjgQpBdTadMQfaqikyfzphRbCdw4dGt4dThXPPwoJrGsyvmELKQVLfSvnq5np5QhVxc3VK4ZZKTR6rSrADeaQ9U5U",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63617264616e6f,08301e5c818abc014ecf2b674fea5f8121a13c11e19dfd6d5e4114fd6e33dc22,8ec26fb45dc1bef88e05a9ddb37399c97dedf9395a1415e4aa54618ffbcf853d,87c369e9cba6a1875f41e9cf58e0ddd67907d31ccb4592714c41a2e9a0616fcb,9619de151da8f361043383a8ed1b4793d275d5de01c4c20a82e7f30305ffde70,818f8212780151192d7398599368acac539525e32e5f73cf47644090d98a8bb9,6a8162f121d36bfe4204870885979014ce0d1a644f965398b1a53333b934dd52,6cd3e0aee75b946a179db3148c2ab43446b3abd6b10ec82b6c17c7fcdd4bd3a7,b93488e537f0597ff58be00fff65f290459fbf7917840c589746d96f5f1c1f6d,620af66be09e0cb5948e2666154979935e10b15f2faff1c9a89a1f7a35dedb5d,e0af70c5eaa93c74ee17ea9263d464bbc31af44d94e068dd253810d50161c48c]"
},
"R5": {
"serializedValue": "110b0080897a80897a80897a80897a80897a80897a80897a80897a80897a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000]"
},
"R6": {
"serializedValue": "1106a09c018c0102288084af5f80d0acf30e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000,70,1,20,100000000,2000000000]"
}
}
}
],
"outputs": [
{
"boxId": "389dc4ea3d9a7370dbb39f8663daef735150b521531d890c5734651ac12934f9",
"transactionId": "71ea22254e9c2c49acf65ca082e1c7de0d8c4e799887a3991770f5c4410440e8",
"blockId": "d841e6638c00c793b2106123802c7937ac2f313442e068047e403d1ff6fd3ca6",
"value": 11000000,
"index": 0,
"globalIndex": 34577516,
"creationHeight": 1142790,
"settlementHeight": 1142792,
"ergoTree": "100c0400040004000400040004000e20772538f248dc921f10ad8a6ecf5889deb9831d1861060e92663be5bdcba17ced040204000e200ca1d31e93b42f9e44e5290e3411aaa2ba67aac158e57916e645612d110729f504c0700e20c5a029f593a106e1594dda1e5435ae44b347fa4ddf8fa03ccd057afc28b7dd38d805d601e4c6a7041ad602b17201d603b4a573007202d604c2b2a5730100d605cb7204d196830301937202b17203afdc0c1d7201017203d901063c0e63d801d6088c720602ededed9383010e8c720601e4c67208041a93c272087204938cb2db63087208730200018cb2db6308a773030001938cb2db63087208730400029d8cb2db6308a7730500027e72020595937205730696830201938cb2db6308b2a47307007308000173099299a3730a8cc7a70196830201aea4d901066393cbc27206730b937205e4c6a7060e",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: Coll(119,37,56,-14,72,-36,-110,31,16,-83,-118,110,-49,88,-119,-34,-71,-125,29,24,97,6,14,-110,102,59,-27,-67,-53,-95,124,-19)\n7: 1\n8: 0\n9: Coll(12,-95,-45,30,-109,-76,47,-98,68,-27,41,14,52,17,-86,-94,-70,103,-86,-63,88,-27,121,22,-26,69,97,45,17,7,41,-11)\n10: 7200\n11: Coll(-59,-96,41,-11,-109,-95,6,-31,89,77,-38,30,84,53,-82,68,-77,71,-6,77,-33,-113,-96,60,-51,5,122,-4,40,-73,-35,56)",
"ergoTreeScript": "{\n val coll1 = SELF.R4[Coll[Coll[Byte]]].get\n val i2 = coll1.size\n val coll3 = OUTPUTS.slice(placeholder[Int](0), i2)\n val coll4 = OUTPUTS(placeholder[Int](1)).propositionBytes\n val coll5 = blake2b256(coll4)\n sigmaProp(allOf(Coll[Boolean](i2 == coll3.size, coll1.zip(coll3).forall({(tuple6: (Coll[Byte], Box)) =>\n val box8 = tuple6._2\n (((Coll[Coll[Byte]](tuple6._1) == box8.R4[Coll[Coll[Byte]]].get) && (box8.propositionBytes == coll4)) && (box8.tokens(placeholder[Int](2))._1 == SELF.tokens(placeholder[Int](3))._1)) && (box8.tokens(placeholder[Int](4))._2 == SELF.tokens(placeholder[Int](5))._2 / i2.toLong)\n }), if (coll5 == placeholder[Coll[Byte]](6)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](7)).tokens(placeholder[Int](8))._1 == placeholder[Coll[Byte]](9), HEIGHT - placeholder[Int](10) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](11) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
"address": "BRNzuPCshtnBeoxCJ8iQiVb78U7vRX6K6qwuSDauDzTF5ARRi7EqxFxHJwyEspfFcA8fdNUV7gzv9T7v6Dt8KBHZxXrb3rLvX7s45oYovhe8GRs98ZBk2UNNRrRcssVErfbEhQypJpUARoniQo3uUBksqczE4v1ks5ycVwgAj2HoHQEDfbTAsJA7iLZ72GAUZHGjLrdHtgNm9ZHoN6u7f3d7qwFMpRQYxEPNfZFXwXjmH6LnP4RatYCLRaRnq8THR8mQRvmrcm7nXiUKFhAypqHRc4Pp8vod2FAZuEo7v2C9paky93rqhEBSKmDF6NBbkdVUqc3gXypYQA4Y3oKvEiMRtXXRPf7RtNiqWrWZTNYztRaNAwnz46mBkTfvYDnQPirpcj2Q5nVRSM2BJ1NxFu4eviCUTsh4aBGM4ArMQ1v6WcD9BERV6x3UC3g7LAhtbb",
"assets": [
{
"tokenId": "01553e0f9122ce7a8dc696fa227d6b09a63dc7eb20a351bfa4f1108c14238895",
"index": 0,
"amount": 100000,
"name": "cRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9619de151da8f361043383a8ed1b4793d275d5de01c4c20a82e7f30305ffde70,620af66be09e0cb5948e2666154979935e10b15f2faff1c9a89a1f7a35dedb5d,87c369e9cba6a1875f41e9cf58e0ddd67907d31ccb4592714c41a2e9a0616fcb,b93488e537f0597ff58be00fff65f290459fbf7917840c589746d96f5f1c1f6d,818f8212780151192d7398599368acac539525e32e5f73cf47644090d98a8bb9,08301e5c818abc014ecf2b674fea5f8121a13c11e19dfd6d5e4114fd6e33dc22,6cd3e0aee75b946a179db3148c2ab43446b3abd6b10ec82b6c17c7fcdd4bd3a7,8ec26fb45dc1bef88e05a9ddb37399c97dedf9395a1415e4aa54618ffbcf853d,6a8162f121d36bfe4204870885979014ce0d1a644f965398b1a53333b934dd52,e0af70c5eaa93c74ee17ea9263d464bbc31af44d94e068dd253810d50161c48c]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[39333765313036363161333339653164623435316362653637306138626161613930656134366166356138376339373735383963373731333139643864643631,63617264616e6f,6572676f,61646472317138686d70357a6a7a7676377337706d67656d7a336d76726b64326e7537363039687767737161306175663668376833723678366a6e327a727438,396944356a4d6f4c6a4b39617a546469677954387a3151593671487241366756724a616d4d46384d4a3271743435704a704463,000000000100e5ad,000000000067c475,00000000000084d3,616461,30626634376331396534393934346133383934386336333563306165663933643839373337616136386466356164383831623037633866396136336533393864,61323262306263316162653361313936313330353838383635616563633138386566653566373865386664393735616633323831393263656235393931396164,000000000092698b]"
},
"R6": {
"serializedValue": "0e20a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849",
"sigmaType": "Coll[SByte]",
"renderedValue": "a9a728b0a25d7089a11ca087a855d1ca189d4cf755ae0ec7c900395ea089b849"
}
},
"spentTransactionId": "7c140e1c874a1f79245a5d07cc44f8c88e1d215bed1c3e33e21fdbdc07f44e10",
"mainChain": true
},
{
"boxId": "0213e930c6d6ee49fa32273891219bbd28a28488f0f613437598cc4ab105ff04",
"transactionId": "71ea22254e9c2c49acf65ca082e1c7de0d8c4e799887a3991770f5c4410440e8",
"blockId": "d841e6638c00c793b2106123802c7937ac2f313442e068047e403d1ff6fd3ca6",
"value": 2612840000,
"index": 1,
"globalIndex": 34577517,
"creationHeight": 1142790,
"settlementHeight": 1142792,
"ergoTree": "0008cd022db1e7ce847be1e892bda6bfd0b8ea5f12497bd2f075d7aad5ab37d327dbfcf8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(2db1e7,61f44d,...)))}",
"address": "9esBjMR99man7D2h24LR7oyR2h6bDbRoZx9MPT8ZcBZH2Jd2p1o",
"assets": [
{
"tokenId": "e0af70c5eaa93c74ee17ea9263d464bbc31af44d94e068dd253810d50161c48c",
"index": 0,
"amount": 1,
"name": "WID-2Jd2p1o",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e454b5cab47c0402dea3ae4a5b4e5b3337d8fd7448927b4e54be99c579cb0b4b",
"mainChain": true
},
{
"boxId": "9716512124c22110ef5043203e90928c7384611f26e455a9f5005927b132f556",
"transactionId": "71ea22254e9c2c49acf65ca082e1c7de0d8c4e799887a3991770f5c4410440e8",
"blockId": "d841e6638c00c793b2106123802c7937ac2f313442e068047e403d1ff6fd3ca6",
"value": 1100000,
"index": 2,
"globalIndex": 34577518,
"creationHeight": 1142790,
"settlementHeight": 1142792,
"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": "ef9556be9292dd3ce8a0495af8c71560e3332781f5d5be5fe56cefa8383b1576",
"mainChain": true
}
],
"size": 1762,
"isUnconfirmed": false
}