Transaction
ID: 6f767331bb...9ae7
Inputs (12)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 765,539
Total coins transferred: 0.0132 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000608 ERG
Raw Transaction Data
{
"id": "6f767331bb2b6cb8e987c79a9ec7fcc72e557283a44960dbf62df59827979ae7",
"blockId": "5cc8378945f5fec8b412fc055976ee78b78c17b492d81fd313ef15d4224dbdcf",
"inclusionHeight": 991451,
"timestamp": 1682591396448,
"index": 7,
"globalIndex": 5106583,
"numConfirmations": 765539,
"inputs": [
{
"boxId": "82373f80236fe822cfae44499eaf9c4e3af4034a71adc2bfdf15ed1931027010",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "5dea6b41e851b701c72e5233ada8a90d29ae454e5e907bb3262db79e7135ec5d",
"outputTransactionId": "23adaf2e64d550c0ea7d8484c906c45595a4e3e02324184f6aa3d134a43d909a",
"outputIndex": 1,
"outputGlobalIndex": 28618485,
"outputCreatedAt": 991437,
"outputSettledAt": 991439,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(1,31,6,-51,-5,-120,-1,-128,101,119,-15,97,-109,85,-3,-83,44,85,77,-107,-43,99,119,109,23,93,-93,-102,122,-14,-20,-13)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 0\n20: 0\n21: 1\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 1\n28: 0\n29: 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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "bd7ec56095ce16501dff9331ba7eb687805904b1ef97100dc4b8abaf472366b3",
"index": 0,
"amount": 1,
"name": "Ergo-RWT.V-test2",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01209dd6c446fdc3ed4cb3518abd39fee9c2bf02cf49696d7f9d2ffef459947474d6",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9dd6c446fdc3ed4cb3518abd39fee9c2bf02cf49696d7f9d2ffef459947474d6]"
},
"R5": {
"serializedValue": "1a0120f7de9ce5a4ed2574ce9b2fdd74eda03b18c357ec0b296550d2d97076603a7ded",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[f7de9ce5a4ed2574ce9b2fdd74eda03b18c357ec0b296550d2d97076603a7ded]"
},
"R6": {
"serializedValue": "0e2022113876731995a11f7c2ddc1160f1ab302310713c849c8fd5ec68661d2eb54b",
"sigmaType": "Coll[SByte]",
"renderedValue": "22113876731995a11f7c2ddc1160f1ab302310713c849c8fd5ec68661d2eb54b"
},
"R7": {
"serializedValue": "0e206bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e",
"sigmaType": "Coll[SByte]",
"renderedValue": "6bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e"
}
}
},
{
"boxId": "5a5288d0aaccfde270594b8b685e430800471af50f8da7cecddafa131f9b4930",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "5dea6b41e851b701c72e5233ada8a90d29ae454e5e907bb3262db79e7135ec5d",
"outputTransactionId": "5309d9326bc3196ed2c9764bde383f8924358bc3fb4c23e68eab4bf3e25ca416",
"outputIndex": 1,
"outputGlobalIndex": 28618490,
"outputCreatedAt": 991437,
"outputSettledAt": 991439,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(1,31,6,-51,-5,-120,-1,-128,101,119,-15,97,-109,85,-3,-83,44,85,77,-107,-43,99,119,109,23,93,-93,-102,122,-14,-20,-13)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 0\n20: 0\n21: 1\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 1\n28: 0\n29: 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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "bd7ec56095ce16501dff9331ba7eb687805904b1ef97100dc4b8abaf472366b3",
"index": 0,
"amount": 1,
"name": "Ergo-RWT.V-test2",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120a27cf938ef70a2b562ea6b7af2f766e92ac5250eba5c75011bc3d48f27275db3",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[a27cf938ef70a2b562ea6b7af2f766e92ac5250eba5c75011bc3d48f27275db3]"
},
"R5": {
"serializedValue": "1a0120f7de9ce5a4ed2574ce9b2fdd74eda03b18c357ec0b296550d2d97076603a7ded",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[f7de9ce5a4ed2574ce9b2fdd74eda03b18c357ec0b296550d2d97076603a7ded]"
},
"R6": {
"serializedValue": "0e2059574c4b4393601df2fb83dadf5b0140670760c28e5681e4eb38be789fa02bc8",
"sigmaType": "Coll[SByte]",
"renderedValue": "59574c4b4393601df2fb83dadf5b0140670760c28e5681e4eb38be789fa02bc8"
},
"R7": {
"serializedValue": "0e206bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e",
"sigmaType": "Coll[SByte]",
"renderedValue": "6bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e"
}
}
},
{
"boxId": "2324b2a9a6400cff66fe3ed7691ceabb2a81b9f7f2dab741f085116c26a1cab7",
"value": 1100000,
"index": 2,
"spendingProof": null,
"outputBlockId": "5dea6b41e851b701c72e5233ada8a90d29ae454e5e907bb3262db79e7135ec5d",
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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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"sigmaType": "Coll[Coll[SByte]]",
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
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"spendingProof": null,
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"outputTransactionId": "ba93972ec5b1919290b34bff08a447d53b55bd5f2f8361d460fac9db3731e4c7",
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(1,31,6,-51,-5,-120,-1,-128,101,119,-15,97,-109,85,-3,-83,44,85,77,-107,-43,99,119,109,23,93,-93,-102,122,-14,-20,-13)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 0\n20: 0\n21: 1\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 1\n28: 0\n29: 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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"sigmaType": "Coll[SByte]",
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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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"assets": [
{
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"name": "Ergo-RWT.V-test2",
"decimals": 0,
"type": "EIP-004"
}
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"additionalRegisters": {
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"serializedValue": "1a012094b2e054e071a4a0b7c5c634176f1bb1b761695140f467219e00fc6406ace057",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[94b2e054e071a4a0b7c5c634176f1bb1b761695140f467219e00fc6406ace057]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[f7de9ce5a4ed2574ce9b2fdd74eda03b18c357ec0b296550d2d97076603a7ded]"
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"R6": {
"serializedValue": "0e20466366fbdb77ec5fedc90d83435c24372f33b7c4a9f148fc2040b87f3a445541",
"sigmaType": "Coll[SByte]",
"renderedValue": "466366fbdb77ec5fedc90d83435c24372f33b7c4a9f148fc2040b87f3a445541"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e"
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"spendingProof": null,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(1,31,6,-51,-5,-120,-1,-128,101,119,-15,97,-109,85,-3,-83,44,85,77,-107,-43,99,119,109,23,93,-93,-102,122,-14,-20,-13)\n2: 0\n3: 0\n4: 0\n5: 1\n6: 0\n7: false\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 3\n14: 2\n15: 1\n16: 1\n17: 100\n18: 0\n19: 0\n20: 0\n21: 1\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 1\n28: 0\n29: 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 opt7 = box5.R5[Coll[Coll[Byte]]]\n val bool8 = opt7.isDefined\n val coll9 = if (bool8) { opt7.get.fold(Coll[Byte](placeholder[Byte](3)), {(tuple9: (Coll[Byte], Coll[Byte])) => tuple9._1.append(tuple9._2) }) } else {\n Coll[Byte](placeholder[Byte](4))\n }\n val coll10 = coll9.slice(placeholder[Int](5), coll9.size)\n val box11 = OUTPUTS(placeholder[Int](6))\n if (bool3) {(\n val box12 = OUTPUTS.filter({(box12: Box) =>\n val opt14 = box12.R4[Coll[Coll[Byte]]]\n if (opt14.isDefined) { opt14.get == coll4 } else { placeholder[Boolean](7) }\n })(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box12.propositionBytes) == SELF.R7[Coll[Byte]].get, box12.tokens(placeholder[Int](9))._1 == SELF.tokens(\n placeholder[Int](10)\n )._1, !coll6.exists({(coll13: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll13) }), blake2b256(coll10.append(coll4(placeholder[Int](11)))) == SELF.R6[\n Coll[Byte]\n ].get\n )\n )\n )\n )} else {(\n val coll12 = blake2b256(box11.propositionBytes)\n if (coll12 == coll2) {(\n val coll13 = INPUTS.filter({(box13: Box) => SELF.propositionBytes == box13.propositionBytes })\n val i14 = coll6.size\n val i15 = coll13.size\n val box16 = CONTEXT.dataInputs(placeholder[Int](12))\n val coll17 = box16.R6[Coll[Long]].get\n val l18 = coll17(placeholder[Int](13))\n val l19 = coll17(placeholder[Int](14)) + coll17(placeholder[Int](15)) * box16.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](16) / placeholder[\n Long\n ](17)\n val tuple20 = box5.tokens(placeholder[Int](18))\n val tuple21 = SELF.tokens(placeholder[Int](19))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box11.value >= coll13.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](20), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll13.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](21), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, i14 == i15, blake2b256(coll10.append(coll4(placeholder[Int](22)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](\n if (bool8) { blake2b256(opt7.get(placeholder[Int](23))) } else { Coll[Byte](placeholder[Byte](24)) }\n ), i15.toLong > if (l18 < l19) { l18 } else { l19 }, tuple20._1 == tuple21._1, tuple20._2 >= tuple21._2 * i14.toLong\n )\n )\n )\n )} else {\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, box11.tokens(placeholder[Int](25))._1 == SELF.tokens(placeholder[Int](26))._1, box11.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](27)\n ).tokens(placeholder[Int](28))._1 == coll4(placeholder[Int](29)), coll12 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n }\n )}\n}",
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(26d2d4,1bc4eb,...)))}",
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"index": 0,
"outputBlockId": "bd0ff279d9cc4db8559cd4460250251be37579f5feae12968bd3df5903942821",
"outputTransactionId": "072930648ff86a527db31be3d265b202423fb434619889d91f2849da63cb6666",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[6572676f,9dd6c446fdc3ed4cb3518abd39fee9c2bf02cf49696d7f9d2ffef459947474d6,95915d95a1f7bfdf947a16cf689bebe6e9da4818bb318cebe59c5f28ef9890d6,72743d4c42bdd20a106230afefd47a0f6d381a9782638f0f032b56cd7816d288,a27cf938ef70a2b562ea6b7af2f766e92ac5250eba5c75011bc3d48f27275db3,94b2e054e071a4a0b7c5c634176f1bb1b761695140f467219e00fc6406ace057,c0d99fd3df85ae104721355c3391917df1890456ccc09401e67d68f89bd38ded,b1af3be747572fed2444ec914589b80a0f4274297a3af9127c5f3aefe8c87e00,324af5e13b9221a75f88958331e0b55becbd8c29f54d2d09dcb412acc89634fc,a3990b87fbe55cd9b45dc827952649e4e38180001804eb6a00a604b5e7105f01,de5fd2cf8d6793ac0eeb949d82bd757fbe3d02c50a3eedca0f79ff7f7a10ad11]"
},
"R5": {
"serializedValue": "110b00a09c01a09c01a09c01a09c01a09c01a09c01a09c01a09c01a09c01a09c01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,10000,10000,10000,10000,10000,10000,10000,10000,10000,10000]"
},
"R6": {
"serializedValue": "1104c8018c010228",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100,70,1,20]"
}
}
}
],
"outputs": [
{
"boxId": "cabafa4fc2598e68facc6131f9fcc9eeea3f1ad5d5ce4b233eefde364d802e08",
"transactionId": "6f767331bb2b6cb8e987c79a9ec7fcc72e557283a44960dbf62df59827979ae7",
"blockId": "5cc8378945f5fec8b412fc055976ee78b78c17b492d81fd313ef15d4224dbdcf",
"value": 11000000,
"index": 0,
"globalIndex": 28618953,
"creationHeight": 991449,
"settlementHeight": 991451,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-103,111,100,62,-106,73,90,-53,-85,119,-96,126,40,-118,13,3,-106,16,-88,9,44,-95,-47,92,-86,-119,-103,-19,-107,-85,81,-110)\n3: 1\n4: 0\n5: Coll(52,67,-107,5,85,-58,8,-118,75,63,-67,-103,-72,83,-95,-37,-119,118,92,-100,123,-29,24,-90,19,77,-78,-18,15,-114,-53,-54)\n6: 7200\n7: Coll(43,-62,101,33,114,37,29,97,92,1,-33,-22,-90,105,-107,67,5,50,-27,-81,13,83,-74,3,-80,-113,-79,-84,54,121,4,-33)",
"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)\n }), if (coll5 == placeholder[Coll[Byte]](2)) { allOf(Coll[Boolean](INPUTS(placeholder[Int](3)).tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), HEIGHT - placeholder[Int](6) >= SELF.creationInfo._1)) } else { allOf(Coll[Boolean](INPUTS.exists({(box6: Box) => blake2b256(box6.propositionBytes) == placeholder[Coll[Byte]](7) }), coll5 == SELF.R6[Coll[Byte]].get)) })))\n}",
"address": "21oSXpSmAC6qkvYUFMVCVau8CwPYUt3BoDtgJvvFnsw2bLmNZN8ZVV3cTUJFCTRnnyD8fHscr9P5rrXJNwX75FuqoPnfbocy7JaSrRZszkJgsFcTHqB3wGuWvSW9K4PFJmgpC4LX32TaNSfi5opXMp3e3tULzez42Qqce94YnSxsdxga5zvRL7g12ziVVEuTApwamEAQQ54gvmeceXUu1vkcYgwdPasNZsTzTb3Z1zGoGhtpzjuKbPcwhnmeb6CW9d9XEtG1ZVF3k3eEMLoeJJyoUgNWu2PttvXxhKe9V6p5N41QA3HxkvnH4DBs8AJKvFxBPFW7Q7Ucxv4R8ST4BqbcVzKuSen2jfYD9MGWGrGtTkMAzh",
"assets": [
{
"tokenId": "bd7ec56095ce16501dff9331ba7eb687805904b1ef97100dc4b8abaf472366b3",
"index": 0,
"amount": 10,
"name": "Ergo-RWT.V-test2",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9dd6c446fdc3ed4cb3518abd39fee9c2bf02cf49696d7f9d2ffef459947474d6,a27cf938ef70a2b562ea6b7af2f766e92ac5250eba5c75011bc3d48f27275db3,72743d4c42bdd20a106230afefd47a0f6d381a9782638f0f032b56cd7816d288,a3990b87fbe55cd9b45dc827952649e4e38180001804eb6a00a604b5e7105f01,de5fd2cf8d6793ac0eeb949d82bd757fbe3d02c50a3eedca0f79ff7f7a10ad11,324af5e13b9221a75f88958331e0b55becbd8c29f54d2d09dcb412acc89634fc,c0d99fd3df85ae104721355c3391917df1890456ccc09401e67d68f89bd38ded,95915d95a1f7bfdf947a16cf689bebe6e9da4818bb318cebe59c5f28ef9890d6,94b2e054e071a4a0b7c5c634176f1bb1b761695140f467219e00fc6406ace057,b1af3be747572fed2444ec914589b80a0f4274297a3af9127c5f3aefe8c87e00]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[36613161636166343464666338633565663566313964623936633734303266666436643864663463646135393866396465303430633264613033653165323962,6572676f,63617264616e6f,3967644150536e757a61374e61337573744b625167516343694a5a5246545174646235717573467a4c63506358764478694e46,616464723171386764746a7a7668306c33706e6778736a77677933376b723274363367676732646678346a636c6464633663367036613570783777376e3035646164616a747a35746a64726b616e37326d386b71747132353971683466366166736b3863377871,000000012a05f200,0000000077359400,000000002faf0800,657267,61737365743165707a37677a6a7167357079347872677073366363763235677a3767643676386535676d7878,34626438343237343330353562376261353161356431333135376634343733363438373061376238646664393134316339383633333838386636333263613562,00000000000f20b8]"
},
"R6": {
"serializedValue": "0e206bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e",
"sigmaType": "Coll[SByte]",
"renderedValue": "6bc550e571abd06490d773698fad27ead82b93c25d46caf58aec59b3a8fd095e"
}
},
"spentTransactionId": "b21ff736a57472d338b376c5c59030969be9c228ccd9e5114e83f25f350428ef",
"mainChain": true
},
{
"boxId": "31120352c555ad3f8c1b8b76e02a239aef84489ca7b7f3ad2a70658e7e1327f5",
"transactionId": "6f767331bb2b6cb8e987c79a9ec7fcc72e557283a44960dbf62df59827979ae7",
"blockId": "5cc8378945f5fec8b412fc055976ee78b78c17b492d81fd313ef15d4224dbdcf",
"value": 1100000,
"index": 1,
"globalIndex": 28618954,
"creationHeight": 991449,
"settlementHeight": 991451,
"ergoTree": "0008cd0326d2d4b3f61f32574e5e23e5618364b78b10468d964ec9be8ef7ec527a4876d4",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(26d2d4,1bc4eb,...)))}",
"address": "9gkuPQXhbFqcfhoaTpck3BCRQiwVRdYSK9txzJrAT9SwaMzaXy8",
"assets": [
{
"tokenId": "844e3cf44b3181b4cacbccbf7596d341f41147d73daf4b565ecaac983aba2508",
"index": 0,
"amount": 26,
"name": "RSN.V-test2",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "ca5520e45c700c29d4b57f216319108f23a6879e06953072b53a595fb4fc2a8e",
"mainChain": true
},
{
"boxId": "8967860dade388f3629af8189311462938eba704561892d0b417cb7afb550ba2",
"transactionId": "6f767331bb2b6cb8e987c79a9ec7fcc72e557283a44960dbf62df59827979ae7",
"blockId": "5cc8378945f5fec8b412fc055976ee78b78c17b492d81fd313ef15d4224dbdcf",
"value": 1100000,
"index": 2,
"globalIndex": 28618955,
"creationHeight": 991449,
"settlementHeight": 991451,
"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": "a6884cb7fc1d927d61c091d2aea46ec1d4d7618000e5440a6084df103cfadfa5",
"mainChain": true
}
],
"size": 1808,
"isUnconfirmed": false
}