Transaction
ID: aaf869fed5...4734
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:
1.66 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:
1.66 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 621,807
Total coins transferred: 1.67 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000563 ERG
Raw Transaction Data
{
"id": "aaf869fed549d3cae937d7ac700e38cbece7cabc2ca9532f8caabbc75afd4734",
"blockId": "3ee02b3ff8dcfdf62b20c1d993df977add14d4ada267b3aa3ed1b3f7ae725bbc",
"inclusionHeight": 1140019,
"timestamp": 1700648640044,
"index": 14,
"globalIndex": 6156273,
"numConfirmations": 621807,
"inputs": [
{
"boxId": "bb42cffa9aff92488994b4582f5e180fa905a5c464a4dc8ff13d022bff6d1893",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "6993c606c16ba2a154e3611c566c6db386afc17b780357f6da220abc8e8d8301",
"outputTransactionId": "214969403c7e05350aab490eab401e535b9766ff68bbc93ea6798d71d9bf4491",
"outputIndex": 1,
"outputGlobalIndex": 34474436,
"outputCreatedAt": 1139997,
"outputSettledAt": 1140000,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "c5c6e337aa9bebf87b1f174e1bc1c3019be44ebf72de5b55fbbdcd1f659b4881",
"index": 0,
"amount": 10000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120a13224f4f3b2af78d22ea923c14aacc8c339afe3b1226cef38af37fa696f6c9f",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[a13224f4f3b2af78d22ea923c14aacc8c339afe3b1226cef38af37fa696f6c9f]"
},
"R5": {
"serializedValue": "1a0120d0a18a933575ddccb36ebce45b7b1293f1a21b6b8c429fca6e8097becde76d48",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d0a18a933575ddccb36ebce45b7b1293f1a21b6b8c429fca6e8097becde76d48]"
},
"R6": {
"serializedValue": "0e209e1abf7aefde240b071ec762031f29e324cef7233a57831c788bdded9865da3e",
"sigmaType": "Coll[SByte]",
"renderedValue": "9e1abf7aefde240b071ec762031f29e324cef7233a57831c788bdded9865da3e"
},
"R7": {
"serializedValue": "0e20630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3",
"sigmaType": "Coll[SByte]",
"renderedValue": "630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3"
}
}
},
{
"boxId": "79ee67b87c9fad4d2375612cb69d07f7e260e58c5af1466c1458ef31f18e5bff",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "6993c606c16ba2a154e3611c566c6db386afc17b780357f6da220abc8e8d8301",
"outputTransactionId": "cdb46d986eb9c518cad5d4cd1c080088538bf3f981aa43210e92858d79b1a2db",
"outputIndex": 1,
"outputGlobalIndex": 34474440,
"outputCreatedAt": 1139997,
"outputSettledAt": 1140000,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "c5c6e337aa9bebf87b1f174e1bc1c3019be44ebf72de5b55fbbdcd1f659b4881",
"index": 0,
"amount": 10000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[09e032f2e37568bd2899a6ebf102da05af9d2ac80691b3dba39cbb2d9f611afc]"
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d0a18a933575ddccb36ebce45b7b1293f1a21b6b8c429fca6e8097becde76d48]"
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"sigmaType": "Coll[SByte]",
"renderedValue": "1cf3412c79e3b49627fa6c7f282fef030b7481ac3befd83d4ff51c28c593853d"
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"sigmaType": "Coll[SByte]",
"renderedValue": "630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3"
}
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{
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"value": 1100000,
"index": 2,
"spendingProof": null,
"outputBlockId": "7f1ae05e1079dca1971cfea8bffd8438be1152a0aab5782a11a0b3dfcd520c2d",
"outputTransactionId": "0b3e1d141ac46e402fbf8712b428193fd7fe16fe0604adcc63fb8dd54e5e3540",
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"outputGlobalIndex": 34474927,
"outputCreatedAt": 1140009,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[5398b71ab3fdd8d70fde01e803881a8740955fc9ad259000bfe4afcd4a63d901]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d0a18a933575ddccb36ebce45b7b1293f1a21b6b8c429fca6e8097becde76d48]"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "cabe8f98a26df2f8eb5b9aa1c8e24e5ac157e27372a8f3a9187b3f45adf99115"
},
"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3"
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{
"boxId": "77258a6ff4808365a6933fe15a47ce2cf7ea9740cedd50e9625b9b125fdf990b",
"value": 1100000,
"index": 3,
"spendingProof": null,
"outputBlockId": "7f1ae05e1079dca1971cfea8bffd8438be1152a0aab5782a11a0b3dfcd520c2d",
"outputTransactionId": "3fced9d97ca9e8e1912ec492a13a2218e7bf21dba51308793642680a78c37773",
"outputIndex": 1,
"outputGlobalIndex": 34474931,
"outputCreatedAt": 1140009,
"outputSettledAt": 1140011,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "1a012008ba16b3ab8068a1691a098f9d9fed34e48e1dfed8a7c6304d0415f0695533f7",
"sigmaType": "Coll[Coll[SByte]]",
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"R5": {
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"sigmaType": "Coll[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 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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
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"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
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"value": 1100000,
"index": 5,
"spendingProof": null,
"outputBlockId": "7f1ae05e1079dca1971cfea8bffd8438be1152a0aab5782a11a0b3dfcd520c2d",
"outputTransactionId": "68e71a2de360fa378f06abb402b4c0f95162baacfa16ab7172620af82792dc27",
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"outputCreatedAt": 1140009,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
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"renderedValue": "630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3"
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"index": 6,
"spendingProof": null,
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"ergoTree": "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",
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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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[2cea3c916cd14eb768dbd74b90de04b2153296f5355d1adc8bc190fb137cbde1]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d0a18a933575ddccb36ebce45b7b1293f1a21b6b8c429fca6e8097becde76d48]"
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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": 7,
"spendingProof": null,
"outputBlockId": "7f1ae05e1079dca1971cfea8bffd8438be1152a0aab5782a11a0b3dfcd520c2d",
"outputTransactionId": "916b39cafd4558ebcc0b08a7ae395a44150814f3570b67145f0aad0b0fbbe6ee",
"outputIndex": 1,
"outputGlobalIndex": 34474947,
"outputCreatedAt": 1140009,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
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],
"additionalRegisters": {
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{
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"value": 1100000,
"index": 8,
"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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{
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"index": 0,
"amount": 10000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
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"sigmaType": "Coll[SByte]",
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"value": 1100000,
"index": 9,
"spendingProof": null,
"outputBlockId": "1985e8d7aa54350b548b23b47e338f241a7989d172813051ee72cd6519537cf7",
"outputTransactionId": "66d81ba2eb928c0a3862d5e66627e11cdd75df51bd76bdd693b405c49824588e",
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-120,34,-32,124,-13,51,94,66,-12,14,28,-37,-5,-64,46,59,30,-10,47,-88,91,19,-55,-126,40,42,-54,-37,82,101,2,10)\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": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
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"additionalRegisters": {
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"value": 1660540000,
"index": 10,
"spendingProof": "6f672752c83ac4f268b96150b7417a84964ed00047d46651ba7cc4fdd7bacc55b0c3fa6764b66010db4789a467f43da7b98720318a9b2628",
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"ergoTree": "0008cd02565b8db017f60afae03bbc4486c52f8f203cffe6d14b994556ff3fcb43e45adc",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(565b8d,86ff1d,...)))}",
"address": "9fB6QRzchPuRv2ZprD8iz5iG3WJJw1cfVp1mfQFNGzQP6PEwYoQ",
"assets": [
{
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"index": 0,
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"name": "WID-6PEwYoQ",
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"type": "EIP-004"
},
{
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},
{
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"index": 2,
"amount": 1,
"name": "WID-6PEwYoQ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "90829fb915dba5c834d14b0e1e1387f6c2e4760965b8cd338892e4ad13baab3d",
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"name": null,
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"type": null
},
{
"tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
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"name": "rptconfRSNV1",
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},
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 5,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "af3de7fbdff20163dcf030187dbd3dbc0e163b740fe733027eaa57db91cfc56d",
"value": 1100000,
"index": 0,
"outputBlockId": "5a131a2c0ba4f0f0144f663153e9390a4c8ec86d1017bdcea54778e244399390",
"outputTransactionId": "d429247a0226292d6746d95557bf2f40941a8667cd508c363202bfdfc29de621",
"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,d6eab062253b811f6e31fd9713c05ac84c0f9acd2cfc2e4fdda850856886a7a6,2cea3c916cd14eb768dbd74b90de04b2153296f5355d1adc8bc190fb137cbde1,a13224f4f3b2af78d22ea923c14aacc8c339afe3b1226cef38af37fa696f6c9f,09e032f2e37568bd2899a6ebf102da05af9d2ac80691b3dba39cbb2d9f611afc,fd7ef4874800f55a5c91cb14a54c63ccbef36dd1d62662c1e7d6333f39cfc55a,1737df427b67bba73b670abe9729272cee14f1e655b12a5aa75402873cda7947,08ba16b3ab8068a1691a098f9d9fed34e48e1dfed8a7c6304d0415f0695533f7,5398b71ab3fdd8d70fde01e803881a8740955fc9ad259000bfe4afcd4a63d901,40ca9bc90fd1497c5e1f96f8a2c9b730d2f845469c3e93255aca1f84f7160cfc,cd0d984c5a0751dabe31982ad359319f7ec13aede552a0438621275de644fef6]"
},
"R5": {
"serializedValue": "110b0080897a80897a80897a80897a80897a80897a80897a80897a80897a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000]"
},
"R6": {
"serializedValue": "1106a09c018c0102288084af5f80dac409",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000,70,1,20,100000000,10000000]"
}
}
}
],
"outputs": [
{
"boxId": "e2fee94af92851d0a3d9289b84bb3a47c44bfbcefbdfc515c9e63783904af5de",
"transactionId": "aaf869fed549d3cae937d7ac700e38cbece7cabc2ca9532f8caabbc75afd4734",
"blockId": "3ee02b3ff8dcfdf62b20c1d993df977add14d4ada267b3aa3ed1b3f7ae725bbc",
"value": 11000000,
"index": 0,
"globalIndex": 34475173,
"creationHeight": 1140017,
"settlementHeight": 1140019,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: Coll(-89,-76,32,59,120,-40,78,-124,-88,-57,48,-26,96,19,103,-29,-35,-7,58,24,66,91,-44,53,-58,71,-114,-5,-28,79,-20,84)\n7: 1\n8: 0\n9: Coll(-20,-94,-32,36,11,-22,-109,-59,52,12,-54,50,93,31,29,126,-22,118,10,-28,77,-68,-10,-69,60,47,53,-54,51,41,-77,62)\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": "BRNzuPCshtnBeoxCJ8iQiVcHoh4iza7Gw8rnoBFVjvMNAdCgaTCqewApGRZCcvzwPSN4kj8myhb2TVcbGP9jd3yyTaetsDdnqvUwXxdnywZSxFSC4uKgy4EhHGesWquZiSbN6LSLcrXQNL8dJxNGDQpaNXzEtvMTckytebfQwvDs8G3kSV8N36NF7YzJeTvSBgg4ruGkmtosNNZ8BPgf56xRgBgZ7hUXEYKM8K6egcVjwGL8ab26sFnXGtWgQgNuULhMD6K8nxPFfVxqiCBAyQHRUDfV6u8o36YEkAQm6czJVFjkVojj47DXL5qL3Af6msFPNWQWvSDF1T8pyok3YLS31t14LpEX97CtEZTYDUzZ3Tfvmjbk94HDrN5dSNRzHZLzuZgBCi5GpxBppZN6TvorRgtiBW4GZn75wCX4mYsY4so91sSTgge17TzJzjuDX9",
"assets": [
{
"tokenId": "c5c6e337aa9bebf87b1f174e1bc1c3019be44ebf72de5b55fbbdcd1f659b4881",
"index": 0,
"amount": 100000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[a13224f4f3b2af78d22ea923c14aacc8c339afe3b1226cef38af37fa696f6c9f,09e032f2e37568bd2899a6ebf102da05af9d2ac80691b3dba39cbb2d9f611afc,5398b71ab3fdd8d70fde01e803881a8740955fc9ad259000bfe4afcd4a63d901,08ba16b3ab8068a1691a098f9d9fed34e48e1dfed8a7c6304d0415f0695533f7,d6eab062253b811f6e31fd9713c05ac84c0f9acd2cfc2e4fdda850856886a7a6,1737df427b67bba73b670abe9729272cee14f1e655b12a5aa75402873cda7947,2cea3c916cd14eb768dbd74b90de04b2153296f5355d1adc8bc190fb137cbde1,fd7ef4874800f55a5c91cb14a54c63ccbef36dd1d62662c1e7d6333f39cfc55a,40ca9bc90fd1497c5e1f96f8a2c9b730d2f845469c3e93255aca1f84f7160cfc,cd0d984c5a0751dabe31982ad359319f7ec13aede552a0438621275de644fef6]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[31616362656562333132373139383535306436613834393361326631316430343036656638363738356563613935613839356135303565353037623933656336,6572676f,63617264616e6f,396944356a4d6f4c6a4b39617a546469677954387a3151593671487241366756724a616d4d46384d4a3271743435704a704463,61646472317138686d70357a6a7a7676377337706d67656d7a336d76726b64326e7537363039687767737161306175663668376833723678366a6e327a727438787333656e633533663461716b733776356735743235346675326e38737a3277736c6132393361,000000011b103f66,0000000076255eac,000000002959e123,657267,6173736574313932786d6a796a7578707764776735656d6b766466776671373937356832727377646b796879,62343330323334386562333132306430663532663763316631646230346236626232323737333039653831363362666666623964613937653664393063623932,0000000000116516]"
},
"R6": {
"serializedValue": "0e20630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3",
"sigmaType": "Coll[SByte]",
"renderedValue": "630b7b708eec54c2524611a5b3b5e91e8a71e807eb10058c0370e9eb43ddcbc3"
}
},
"spentTransactionId": "7697d845d1a57159fb6e9704126489a2a3375844ffd4dea2c070114a16e20104",
"mainChain": true
},
{
"boxId": "d3d0ae3acacaebe4e7fde6c1bb7548edb974af764adab7d4d034ae75e4eb8a2e",
"transactionId": "aaf869fed549d3cae937d7ac700e38cbece7cabc2ca9532f8caabbc75afd4734",
"blockId": "3ee02b3ff8dcfdf62b20c1d993df977add14d4ada267b3aa3ed1b3f7ae725bbc",
"value": 1659440000,
"index": 1,
"globalIndex": 34475174,
"creationHeight": 1140017,
"settlementHeight": 1140019,
"ergoTree": "0008cd02565b8db017f60afae03bbc4486c52f8f203cffe6d14b994556ff3fcb43e45adc",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(565b8d,86ff1d,...)))}",
"address": "9fB6QRzchPuRv2ZprD8iz5iG3WJJw1cfVp1mfQFNGzQP6PEwYoQ",
"assets": [
{
"tokenId": "08ba16b3ab8068a1691a098f9d9fed34e48e1dfed8a7c6304d0415f0695533f7",
"index": 0,
"amount": 1,
"name": "WID-6PEwYoQ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "cdf549fccbb09ab8f38ecbf9a5ed37c926707753adf8fed19b039684a0772bfe",
"index": 1,
"amount": 51548,
"name": "RSN-loen",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "4dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7",
"index": 2,
"amount": 1,
"name": "WID-6PEwYoQ",
"decimals": 0,
"type": "EIP-004"
},
{
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}