Transaction
ID: 972cfca576...167c
Inputs (11)
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:
18,090,000.08
Spent
Address:
Output transaction:
Settlement height:
Value:
1.98 ERG
Tokens:
Loading assets...
Outputs (3)
Unspent
Address:
Settlement height:
Value:
0.0099 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.98 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 695,832
Total coins transferred: 1.99 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000589 ERG
Raw Transaction Data
{
"id": "972cfca576083048d7f6ff4f2245b7be7fe3aaaacdcd06d76dad2e9a9af9167c",
"blockId": "3aeafce7ddb03e65a7ea106770f964f162e5ffd9cd31f6dbb7e4325404cc4312",
"inclusionHeight": 1065261,
"timestamp": 1691577033193,
"index": 7,
"globalIndex": 5643494,
"numConfirmations": 695832,
"inputs": [
{
"boxId": "fb7532c58f105ba41959245738b07766158b5ba4293461b7df6e328d017ff4a2",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "d88845438faa135703bf9ae3a8a5ab9962dac3d667b2b33125166dfa2f5c39f5",
"outputTransactionId": "95e5176ccb4f4da58828ecabfcfc9d7d7d0fcb10b7e5300e68f0f25b8de7572c",
"outputIndex": 1,
"outputGlobalIndex": 31640889,
"outputCreatedAt": 1065205,
"outputSettledAt": 1065208,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(115,120,71,67,81,9,-28,9,88,-75,53,-64,30,8,-72,-73,-72,-50,-14,-59,-89,68,25,127,-10,72,-123,14,13,34,-26,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "36afc697123a9ab2b8fcc220c0a8031f5933a06998683a17f931435dbb45f253",
"index": 0,
"amount": 10000,
"name": "rptconfCardanoRWTV1",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01207f2ece1fa522a7cea01af48e6b73ef64f2600f92cd0c514c9543c2f17fb58513",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[7f2ece1fa522a7cea01af48e6b73ef64f2600f92cd0c514c9543c2f17fb58513]"
},
"R5": {
"serializedValue": "1a012057abaf320e2cce3fa3ce953cbce48e1fd8f088c573e7df7d4c99044aa8253f30",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[57abaf320e2cce3fa3ce953cbce48e1fd8f088c573e7df7d4c99044aa8253f30]"
},
"R6": {
"serializedValue": "0e2048cb250b27d0fd46d4953eb46f1c42eca7856b0176073ca7fc1164a53d147b79",
"sigmaType": "Coll[SByte]",
"renderedValue": "48cb250b27d0fd46d4953eb46f1c42eca7856b0176073ca7fc1164a53d147b79"
},
"R7": {
"serializedValue": "0e20137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73",
"sigmaType": "Coll[SByte]",
"renderedValue": "137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73"
}
}
},
{
"boxId": "0d4ea8babd249b5687aecfff6cce2179067ffcbf7cf9c24d2216d754c4340025",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "d88845438faa135703bf9ae3a8a5ab9962dac3d667b2b33125166dfa2f5c39f5",
"outputTransactionId": "ccfd4071d21abaa0446444e19076e3f9884475a33572d85a9eddcaecf310be5f",
"outputIndex": 1,
"outputGlobalIndex": 31640893,
"outputCreatedAt": 1065205,
"outputSettledAt": 1065208,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(115,120,71,67,81,9,-28,9,88,-75,53,-64,30,8,-72,-73,-72,-50,-14,-59,-89,68,25,127,-10,72,-123,14,13,34,-26,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "36afc697123a9ab2b8fcc220c0a8031f5933a06998683a17f931435dbb45f253",
"index": 0,
"amount": 10000,
"name": "rptconfCardanoRWTV1",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a012023152a40001d97709623d31029acfc5374df08f27fab050b3844b02bc8d0743e",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[23152a40001d97709623d31029acfc5374df08f27fab050b3844b02bc8d0743e]"
},
"R5": {
"serializedValue": "1a012057abaf320e2cce3fa3ce953cbce48e1fd8f088c573e7df7d4c99044aa8253f30",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[57abaf320e2cce3fa3ce953cbce48e1fd8f088c573e7df7d4c99044aa8253f30]"
},
"R6": {
"serializedValue": "0e20e2db195978508e0f233d30defd946e6577f85ba1679520fbb7b76c514b340529",
"sigmaType": "Coll[SByte]",
"renderedValue": "e2db195978508e0f233d30defd946e6577f85ba1679520fbb7b76c514b340529"
},
"R7": {
"serializedValue": "0e20137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73",
"sigmaType": "Coll[SByte]",
"renderedValue": "137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73"
}
}
},
{
"boxId": "76c214d3a7c3e58d1840295a0e0cd21cc760926af1f61c1bbc0eea8c98b012a2",
"value": 1100000,
"index": 2,
"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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == 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 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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{
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"sigmaType": "Coll[Coll[SByte]]",
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"sigmaType": "Coll[SByte]",
"renderedValue": "f9e759f2c2420ba252954bbee4e4a57f35de8515b6495c4b3fa41e37ea433405"
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"R7": {
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"sigmaType": "Coll[SByte]",
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{
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"spendingProof": null,
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"outputTransactionId": "fa09b1bdbf2d9653c7e8cd9eab2c068156ba080d00f70a4048263bdc6317de02",
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"ergoTreeConstants": "0: 0\n1: Coll(115,120,71,67,81,9,-28,9,88,-75,53,-64,30,8,-72,-73,-72,-50,-14,-59,-89,68,25,127,-10,72,-123,14,13,34,-26,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == 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 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == 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": "17d1d23b45f593c3bb672157e4063a7f4dd246ad0d6bc0b529d591253262e61b",
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"ergoTreeConstants": "0: 0\n1: Coll(115,120,71,67,81,9,-28,9,88,-75,53,-64,30,8,-72,-73,-72,-50,-14,-59,-89,68,25,127,-10,72,-123,14,13,34,-26,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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{
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(115,120,71,67,81,9,-28,9,88,-75,53,-64,30,8,-72,-73,-72,-50,-14,-59,-89,68,25,127,-10,72,-123,14,13,34,-26,-88)\n2: 0\n3: 0\n4: 1\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 3\n12: 2\n13: 1\n14: 1\n15: 100\n16: 0\n17: 0\n18: 0\n19: 0\n20: 1\n21: 0\n22: 0\n23: 0\n24: 0\n25: 1\n26: 0\n27: 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 coll12 = INPUTS.filter({(box12: Box) => SELF.propositionBytes == box12.propositionBytes })\n val i13 = coll12.size\n val l14 = i13.toLong\n val box15 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll16 = box15.R6[Coll[Long]].get\n val l17 = coll16(placeholder[Int](11))\n val l18 = coll16(placeholder[Int](12)) + coll16(placeholder[Int](13)) * box15.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](14) / placeholder[\n Long\n ](15)\n val tuple19 = SELF.tokens(placeholder[Int](16))\n val l20 = coll16(placeholder[Int](17))\n val tuple21 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box10.value >= coll12.map({(box22: Box) => box22.value }).fold(\n placeholder[Long](19), {(tuple22: (Long, Long)) => tuple22._1 + tuple22._2 }\n ), coll12.filter({(box22: Box) => box22.R4[Coll[Coll[Byte]]].get == coll4 }).size == placeholder[Int](20), coll6.exists(\n {(coll22: Coll[Byte]) => Coll[Coll[Byte]](coll22) == coll4 }\n ), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, coll6.size == i13, blake2b256(coll9.append(coll4(placeholder[Int](21)))) == SELF.R6[\n Coll[Byte]\n ].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[Coll[Byte]](blake2b256(coll7(placeholder[Int](22)))), l14 > if (l17 < l18) { l17 } else {\n l18\n }, tuple19._2 == l20, tuple21._2 == l20 * l14, tuple21._1 == tuple19._1\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](23))\n val tuple13 = SELF.tokens(placeholder[Int](24))\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](25)\n ).tokens(placeholder[Int](26))._1 == coll4(placeholder[Int](27)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "36afc697123a9ab2b8fcc220c0a8031f5933a06998683a17f931435dbb45f253",
"index": 0,
"amount": 10000,
"name": "rptconfCardanoRWTV1",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a01201db8e5a389490f1bcb8e17dfd414d6251d1f3707d38a1361d7a2045764d281fe",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[1db8e5a389490f1bcb8e17dfd414d6251d1f3707d38a1361d7a2045764d281fe]"
},
"R5": {
"serializedValue": "1a012057abaf320e2cce3fa3ce953cbce48e1fd8f088c573e7df7d4c99044aa8253f30",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[57abaf320e2cce3fa3ce953cbce48e1fd8f088c573e7df7d4c99044aa8253f30]"
},
"R6": {
"serializedValue": "0e20df46a22cf61adaafe690fcc281da00f5716451614578a15128113cb1415e882c",
"sigmaType": "Coll[SByte]",
"renderedValue": "df46a22cf61adaafe690fcc281da00f5716451614578a15128113cb1415e882c"
},
"R7": {
"serializedValue": "0e20137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73",
"sigmaType": "Coll[SByte]",
"renderedValue": "137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73"
}
}
},
{
"boxId": "984ccbf54678e17535b19df1a2c71b081fd80579f57192128312514ddd1dc9ed",
"value": 1100000,
"index": 9,
"spendingProof": "b793c2414733df0190782f06cc3472673cb6bbc6687bf1fb2bde305cbc9b60c3301b17e547cb940058d79a7aac329efc8615394cb62b3747",
"outputBlockId": "c7ebaadbdd85ace7071bd3907ce9c6d92aacd4872f8eb80352373766fd1d4f78",
"outputTransactionId": "98634a3f31f7febbe69e8feb4071859567c78a453adb627b6aed31fb2d925437",
"outputIndex": 1,
"outputGlobalIndex": 31640938,
"outputCreatedAt": 1065207,
"outputSettledAt": 1065211,
"ergoTree": "0008cd03d72a6a62aa181efc2e9328275ddb1a97dfa3b0dd4fa8e61aa9ebcb9f4b1d6113",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d72a6a,353379,...)))}",
"address": "9i6ZowRVZQKAydZEydrXNBpMyA2nqX4PE6WF5wEenSd3X1n6Yi8",
"assets": [
{
"tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
"index": 0,
"amount": 18090000080,
"name": "rptconfRSNV1",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "fccb9bc6a499cf4f2a4cf96c1ec43b0f169f6293e019a1900e6a935f97bf9a43",
"value": 1975800000,
"index": 10,
"spendingProof": "3625b4a53e8b70a70e2aee7364507ba1b2049acb0ee8ed7b16c7beb6322868f57977dd8794a178e851add1cbdf6cbc7b63a5abd3daca7960",
"outputBlockId": "bb2aa526a277fd6b9fa9787e62cd30f6f485df63680cd3438c6afbe0c22e3760",
"outputTransactionId": "c39755aff9e424b828481f095d8a4a08672f9eadbd5294ed0312cd4443c80c59",
"outputIndex": 1,
"outputGlobalIndex": 31642064,
"outputCreatedAt": 1065212,
"outputSettledAt": 1065236,
"ergoTree": "0008cd03d72a6a62aa181efc2e9328275ddb1a97dfa3b0dd4fa8e61aa9ebcb9f4b1d6113",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d72a6a,353379,...)))}",
"address": "9i6ZowRVZQKAydZEydrXNBpMyA2nqX4PE6WF5wEenSd3X1n6Yi8",
"assets": [
{
"tokenId": "5121ff1832cfc2e0a05111faf65416318b030d27e9d6a972adddd4da1f017262",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "b47a356397d591f333ee5b75f68806477618482881cf005ebae1adfa4d3ca557",
"value": 1100000,
"index": 0,
"outputBlockId": "4b203beda084c3e28b30c0bc731666d0b8e5fa117d39566add9b370ecfb8087a",
"outputTransactionId": "295f814ec1fa48efaa911d69b4835cacff0ee106c0ddc123948e0e211b18b171",
"outputIndex": 0,
"ergoTree": "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",
"address": "5qwczr7KdspNWq5dg6FZJZSDJ9YGcYDsCVi53E6M9gPamGjQTee9Zp5HLbJXQvWJ49ksh9Ao9YK3VcjHZjVVN2rP74YoYUwCo1xY25jJQRvmqF7tMJdUYAWxB1mg3U5xrcYxUBnGVCzHojWsrF8EoLKoAGtv9MeyFspPSEr9H77V7crUojiQUTSgxqTKb8LjLgyfuCQrdwx67N5cpwZqeVwbjLnXwPwUdpaYm6JzHgmtqsZhUC14g8R47kEPYCsxQYGx16zq85VYm2xTSL1oetcrYQTjr7AGPhfMpZy4GTW6WNtxrtAY6ZEW8P1xWL9T2sDZAithfhY9YjJLzUpj4KXkeXER53vu1WDViQgkKChwEGUmwM5ooucMcsDssr2B68ydYJ4HS9x8oqwaM4m4JromaStDvFBBVjQ59iPLUe5WDxx58pLqRSfG8JVDcRTHGyp2NdYFCZMMukfJaeybgYVVobsTWa2NL9ogdoEFYUfe3Vz8hkGbeP1Ki86LNswYVeF84Hbf8rDiVHQzNQeiNgHKt3Pu5Lixf9q44qoVKCRcdWvwj8KR86e57t4T3HyVrSZ1n7yxfJL4eWx6LHxozEt9Jy6dedDeKeizThhwiUWdTZsk2VMBq8wkXYHHAgYUGq14EZywTJ8nuXtaTVu9Jg7D4qkUGcT4r6Ei51uUGkBshwA5sxbYvzwR8xSVZv4jgVGn88GArGM87CJ8pMEs2J8RQPsGTX8qGjFUjvUDu9XYw3y4X2ncSSwsh5iQrDUqssXv3PT7GZvZMCFxdGaB1VMitE5SmmkujEF65j6qzyvBDFzpPNG9WZYvYBKQQjmDiJtgwkEuRmmm4bKhy76DEFafkSorsGHUjdSaEtsjZSLeKMqB9bGgBTyqLmS6ePZqmQzuhR4QF45qZN1gpm7BJsLXnoxjhs3uTpQ9CeraeujUPXRJXdZMcbBayDXygEaAjVHvbbkSZou969hbzeozrXCeqrrVdjKDWTXLfk8hM4Ai5SkabRXNNW6q9Uu8mhacKFrZNcqqv6wXjvCQer4mHE5Nr3Cg5adNM3ACFKJNSkLnT8X7Z59oNoXDvREdQp5uorwA92EPcNoATHCvaNQ5KCpa323kU9c2z3U8a7jTW4Poah8CUowKPMzSt1oUCQvUG83EDKM9Pi2QTm7qfCkHj5q9Lo3t3iK9QkfrggTmEZwvWoFzKwNG27qH7jJGAYX7zyWoB2jENZgcSXomopCKRdZmw3tHxExd4uH3kG8VmpXrjF5kf6rFxa7Jp2co5D5h61LvubvQFKY5syLAqiJdtavQtPwbQya6fnTfrSiBe4WzL8M777ReP4dEFwk6G78ZUx2ixHCk5uB9DRds84A76yvfbQbLi4GYzk4tnBJxC55aWtuvBySwz7m8dmmUHXdNgW3c7wae4qNE47j4WcR9",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[63617264616e6f,143d16a70d742c065738439cd0b00ae64bc3e1ae2647277f1b746e411f582cba,0d1661fab46180353cd01b5b88176f278b8609e1cecc2e3f5cc1e2582615ba18,db6dc2e82fe45bcd43f92386a12df41bef815ef6713267754ff3043e48b3f43e,1db8e5a389490f1bcb8e17dfd414d6251d1f3707d38a1361d7a2045764d281fe,23152a40001d97709623d31029acfc5374df08f27fab050b3844b02bc8d0743e,5121ff1832cfc2e0a05111faf65416318b030d27e9d6a972adddd4da1f017262,af3703fef3b2d5b0f0d6c1f6b73335086978be00856caa46ba58e8d6b38fa6f5,3c0a102ee3cd6b5408367928049da15c1cb495b2dabfde36dce92c7931a96080,1cdb34530d8927b5c06d5a7e9f45ac253bc07685200e9df7fddde424288bf71d,7f2ece1fa522a7cea01af48e6b73ef64f2600f92cd0c514c9543c2f17fb58513]"
},
"R5": {
"serializedValue": "110b0080b4891380dac40980dac40980dac40980dac40980dac40980dac40980dac40980dac4098092f401",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,20000000,10000000,10000000,10000000,10000000,10000000,10000000,10000000,10000000,2000000]"
},
"R6": {
"serializedValue": "1106a09c018c01022880a8d6b90780d0acf30e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000,70,1,20,1000000000,2000000000]"
}
}
}
],
"outputs": [
{
"boxId": "a98de40a57947d4707d2aeff9842bc22981067f8753af4c18195088bdb865625",
"transactionId": "972cfca576083048d7f6ff4f2245b7be7fe3aaaacdcd06d76dad2e9a9af9167c",
"blockId": "3aeafce7ddb03e65a7ea106770f964f162e5ffd9cd31f6dbb7e4325404cc4312",
"value": 9900000,
"index": 0,
"globalIndex": 31643258,
"creationHeight": 1065226,
"settlementHeight": 1065261,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: Coll(76,-101,108,101,90,80,34,115,52,-118,-109,108,-71,47,-78,27,91,-107,-127,-31,-92,76,-20,-69,62,-29,119,-118,121,57,-38,-88)\n7: 1\n8: 0\n9: Coll(85,117,50,75,-121,11,-118,5,95,68,-37,27,-50,104,-50,33,-79,-18,-8,102,105,64,82,-9,26,6,-35,105,70,119,91,27)\n10: 7200\n11: Coll(70,36,70,31,-62,-119,64,54,-23,-68,80,103,-65,-15,-28,103,-108,42,-46,-17,42,-11,33,-114,-92,83,108,-75,23,-64,14,43)",
"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": "BRNzuPCshtnBeoxCJ8iQiVa4y4RnVi4LmakNPhL8c7NDpVnUX5zAnVoAPGcQJhTYCTPUPLixP3cXGkuw27T7GtzURCdfGqTggfxNo4UJJmhkM1TcfqqF1EjEm12FTZUBzP2MRfh8RNsV84boTDArm1jnUVmbK72LG9BRtag4JtkSDMmm6KjLACQtVLd6GLxRgC3fGA6ePb62aqorp6Hu5rN3NZzB4gk4oYA96Sm6rpTr4irLY7FvksD6PdGGmEFJCNGAEXS6Hq6GJ3v5QgiqaUXWesi52LN9Jvc1jQYaDV2zNWpgFEmhaauyrySM2spPs7hqyjXKrhBZPwRxfXSP5HTuq6STaywZBfXb9bj8axaadgk1oNmRM9tYghvJsBKoCFiU5JWP4PyZ3qg8ahYMS7dnB7GzdrH9Hz385uMG9DGUrYZHJDxzAUeNK9boZeo5ho",
"assets": [
{
"tokenId": "36afc697123a9ab2b8fcc220c0a8031f5933a06998683a17f931435dbb45f253",
"index": 0,
"amount": 90000,
"name": "rptconfCardanoRWTV1",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[7f2ece1fa522a7cea01af48e6b73ef64f2600f92cd0c514c9543c2f17fb58513,23152a40001d97709623d31029acfc5374df08f27fab050b3844b02bc8d0743e,af3703fef3b2d5b0f0d6c1f6b73335086978be00856caa46ba58e8d6b38fa6f5,5121ff1832cfc2e0a05111faf65416318b030d27e9d6a972adddd4da1f017262,3c0a102ee3cd6b5408367928049da15c1cb495b2dabfde36dce92c7931a96080,db6dc2e82fe45bcd43f92386a12df41bef815ef6713267754ff3043e48b3f43e,143d16a70d742c065738439cd0b00ae64bc3e1ae2647277f1b746e411f582cba,0d1661fab46180353cd01b5b88176f278b8609e1cecc2e3f5cc1e2582615ba18,1db8e5a389490f1bcb8e17dfd414d6251d1f3707d38a1361d7a2045764d281fe]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[35383530386665383566373765656334336437343866323237306338356139336162626631303432356435623065346364356635373234366363633765376130,63617264616e6f,6572676f,616464723171396e77676c6c6c74376a3030796634307776656163327467746d787879377930366e74757273366c3833776e39673337646a6c6e7a35686d6d6d6b78656e786c386d77716c366839366775377a74706867786a66306e67776866717761646d3764,396763724b6e374c354c6e337252736a466f53456b45736f76556462354a523564366f327648515635464358584e6b6b454144,000000000016588e,000000000081b320,0000000000002328,6c6f76656c616365,36636265656330346166366135303437643838313865616332616336653262323865316537346130643333396366663936663736343161316130633363613962,30303333376361356533386565666431376562386565623066363430623339353365643866383236326164656261303765303438653339336635353033646638,00000000008b6b11]"
},
"R6": {
"serializedValue": "0e20137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73",
"sigmaType": "Coll[SByte]",
"renderedValue": "137984a29fd08728a3708c475a715d08ebc6e97dd337632342d0d2a7c7dd0d73"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "375d156cf99aa6ea8b3c264ab9576619107d0f57badb7694d0e50371c0c68cfc",
"transactionId": "972cfca576083048d7f6ff4f2245b7be7fe3aaaacdcd06d76dad2e9a9af9167c",
"blockId": "3aeafce7ddb03e65a7ea106770f964f162e5ffd9cd31f6dbb7e4325404cc4312",
"value": 1975800000,
"index": 1,
"globalIndex": 31643259,
"creationHeight": 1065226,
"settlementHeight": 1065261,
"ergoTree": "0008cd03d72a6a62aa181efc2e9328275ddb1a97dfa3b0dd4fa8e61aa9ebcb9f4b1d6113",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(d72a6a,353379,...)))}",
"address": "9i6ZowRVZQKAydZEydrXNBpMyA2nqX4PE6WF5wEenSd3X1n6Yi8",
"assets": [
{
"tokenId": "5121ff1832cfc2e0a05111faf65416318b030d27e9d6a972adddd4da1f017262",
"index": 0,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
"index": 1,
"amount": 18090000080,
"name": "rptconfRSNV1",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "38e2954cb6c43f71c714667401d1064da288b44b82a64e3568f9f33961fdd699",
"mainChain": true
},
{
"boxId": "6775746d4d6029fcffbae5fb024830a8dfd119515e618ca06a265137258204f9",
"transactionId": "972cfca576083048d7f6ff4f2245b7be7fe3aaaacdcd06d76dad2e9a9af9167c",
"blockId": "3aeafce7ddb03e65a7ea106770f964f162e5ffd9cd31f6dbb7e4325404cc4312",
"value": 1100000,
"index": 2,
"globalIndex": 31643260,
"creationHeight": 1065226,
"settlementHeight": 1065261,
"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": "3e6f8c283d0e76c86b4875c722c563539ef2f4637a8af95d19c087784b45b527",
"mainChain": true
}
],
"size": 1867,
"isUnconfirmed": false
}