Transaction
ID: 95d831fb0d...a783
Inputs (11)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
100
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
22.22
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0099 ERG
Tokens:
900
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 640,725
Total coins transferred: 0.0121 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000577 ERG
Raw Transaction Data
{
"id": "95d831fb0da441d8ceec413b3b353487680bc17fb87d5867e843c8bd09fda783",
"blockId": "04a3371dd617513cc84f8b316d80c26a40d0dfc9b457f07863ee3cbd4d851e2c",
"inclusionHeight": 1123121,
"timestamp": 1698598748820,
"index": 5,
"globalIndex": 6040466,
"numConfirmations": 640725,
"inputs": [
{
"boxId": "01b531fb975a50bc2f6eb13e8bbc805ace58bbd2ad67c98e992bfcea718f9f10",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "c58e83711f5611cef494fe7d682a1a6ed331d637a253e1ebfac9f316536be530",
"outputTransactionId": "38a4762173843cafc92404754dcaf6a3bd7dc1f3f5869efcfbc25162ac4a4998",
"outputIndex": 1,
"outputGlobalIndex": 33851170,
"outputCreatedAt": 1122975,
"outputSettledAt": 1122977,
"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": 100000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1a0120038a51fb732b5e46f139eb1f92ac773e4515eb9435df38259460c5316efea376",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[038a51fb732b5e46f139eb1f92ac773e4515eb9435df38259460c5316efea376]"
},
"R5": {
"serializedValue": "1a012074ccd137e6790581b70ee4308e1e5df762bfb424d2ad4eabdbc72a8f50a1b977",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[74ccd137e6790581b70ee4308e1e5df762bfb424d2ad4eabdbc72a8f50a1b977]"
},
"R6": {
"serializedValue": "0e20e7ccc73015a7488880b65852a2ee155eeaeeb7c50c4f4b2f51f834a046831fe4",
"sigmaType": "Coll[SByte]",
"renderedValue": "e7ccc73015a7488880b65852a2ee155eeaeeb7c50c4f4b2f51f834a046831fe4"
},
"R7": {
"serializedValue": "0e20df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
}
}
},
{
"boxId": "8affd544d9951a0145b470b9e27d99fb311a6054a4a5df998ba4c6bc68dedb67",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "c58e83711f5611cef494fe7d682a1a6ed331d637a253e1ebfac9f316536be530",
"outputTransactionId": "5f5d924d1316ab8688777d31c771c82b38becd0b7600205bd4d935a2394e5257",
"outputIndex": 1,
"outputGlobalIndex": 33851174,
"outputCreatedAt": 1122975,
"outputSettledAt": 1122977,
"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": 100000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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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": 100000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
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"R6": {
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
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"value": 1100000,
"index": 3,
"spendingProof": null,
"outputBlockId": "c58e83711f5611cef494fe7d682a1a6ed331d637a253e1ebfac9f316536be530",
"outputTransactionId": "24000f4b2545bd8ec265ecc314c390ff968e8ccb1123c26e4d98de5e629ce3d8",
"outputIndex": 1,
"outputGlobalIndex": 33851183,
"outputCreatedAt": 1122975,
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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": 100000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
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"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = placeholder[Coll[Byte]](1)\n val bool3 = blake2b256(box1.propositionBytes) == coll2\n val coll4 = SELF.R4[Coll[Coll[Byte]]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R4[Coll[Coll[Byte]]].get\n val coll7 = box5.R5[Coll[Coll[Byte]]].get\n val coll8 = coll7.fold(Coll[Byte](placeholder[Byte](3)), {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val coll9 = coll8.slice(placeholder[Int](4), coll8.size)\n val box10 = OUTPUTS(placeholder[Int](5))\n if (bool3) {(\n val box11 = OUTPUTS.filter({(box11: Box) =>\n val opt13 = box11.R4[Coll[Coll[Byte]]]\n opt13.isDefined && (opt13.get == coll4)\n })(placeholder[Int](6))\n val tuple12 = box11.tokens(placeholder[Int](7))\n val tuple13 = SELF.tokens(placeholder[Int](8))\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box11.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, !coll6.exists(\n {(coll14: Coll[Byte]) => coll4 == Coll[Coll[Byte]](coll14) }\n ), blake2b256(coll9.append(coll4(placeholder[Int](9)))) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll11 = blake2b256(box10.propositionBytes)\n if (coll11 == coll2) {(\n val box12 = CONTEXT.dataInputs(placeholder[Int](10))\n val coll13 = box12.tokens\n val tuple14 = SELF.tokens(placeholder[Int](11))\n val coll15 = tuple14._1\n val coll16 = INPUTS.filter({(box16: Box) => SELF.propositionBytes == box16.propositionBytes })\n val i17 = coll16.size\n val l18 = i17.toLong\n val coll19 = box12.R6[Coll[Long]].get\n val l20 = coll19(placeholder[Int](12))\n val l21 = coll19(placeholder[Int](13)) + coll19(placeholder[Int](14)) * box12.R4[Coll[Coll[Byte]]].get.size.toLong - placeholder[Long](15) / placeholder[\n Long\n ](16)\n val l22 = coll19(placeholder[Int](17))\n val tuple23 = box5.tokens(placeholder[Int](18))\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll13(placeholder[Int](19))._1 == placeholder[Coll[Byte]](20), coll13(placeholder[Int](21))._1 == coll15, box10.value >= coll16.map(\n {(box24: Box) => box24.value }\n ).fold(placeholder[Long](22), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 }), coll16.filter(\n {(box24: Box) => box24.R4[Coll[Coll[Byte]]].get == coll4 }\n ).size == placeholder[Int](23), coll6.exists({(coll24: Coll[Byte]) => Coll[Coll[Byte]](coll24) == coll4 }), box5.R6[Coll[Byte]].get == SELF.R7[\n Coll[Byte]\n ].get, coll6.size == i17, blake2b256(coll9.append(coll4(placeholder[Int](24)))) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Coll[Byte]]].get == Coll[\n Coll[Byte]\n ](blake2b256(coll7(placeholder[Int](25)))), l18 > if (l20 < l21) { l20 } else {\n l21\n }, tuple14._2 == l22, tuple23._2 == l22 * l18, tuple23._1 == coll15\n )\n )\n )\n )} else {(\n val tuple12 = box10.tokens(placeholder[Int](26))\n val tuple13 = SELF.tokens(placeholder[Int](27))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple12._1 == tuple13._1, tuple12._2 == tuple13._2, box10.R4[Coll[Coll[Byte]]].get == coll4, INPUTS(\n placeholder[Int](28)\n ).tokens(placeholder[Int](29))._1 == coll4(placeholder[Int](30)), coll11 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R7": {
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"sigmaType": "Coll[SByte]",
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"index": 5,
"spendingProof": null,
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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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"name": "eRWT-loen",
"decimals": 3,
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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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"name": "eRWT-loen",
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"sigmaType": "Coll[SByte]",
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"index": 7,
"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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"decimals": 3,
"type": "EIP-004"
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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}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 100000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[4dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7]"
},
"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[74ccd137e6790581b70ee4308e1e5df762bfb424d2ad4eabdbc72a8f50a1b977]"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "46a72cb23bfe53f5758af8029b281456b25bba22f52dceb2cf63e20a260332ee"
},
"R7": {
"serializedValue": "0e20df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
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},
{
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"value": 1100000,
"index": 9,
"spendingProof": "42e5716bc7bc5e2c507e61830f7458dcddc28c31fbb601f2abff0b20a605045e909abfb2d1b41f26a64b33a50384a8b56c55010472561076",
"outputBlockId": "47187bae26c4cf45f1fbb428ebce265181387104a10a9092027e2956529f8d48",
"outputTransactionId": "2da012f09a7a6ce98dfc4d977263aa710763e6fdc36ee77d65b10d45594f8c18",
"outputIndex": 1,
"outputGlobalIndex": 33681404,
"outputCreatedAt": 1119232,
"outputSettledAt": 1119234,
"ergoTree": "0008cd03349d9244648ed913f18110417ffde85cee2fca02c785932d8a229363b86896ed",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(349d92,9d6432,...)))}",
"address": "9grygda768RvJtBvabzBqgTAehr4R3bP8hn8AzCvki3GUKDRCe4",
"assets": [
{
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"index": 0,
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"name": "rptconfRSNV1",
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"type": "EIP-004"
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{
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{
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{
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"value": 1100000,
"index": 10,
"spendingProof": "389bd6b648d8fef1fe21ae5704a661b2d7be4ae4105faeb5c273a7f3acfb356a614ef5f06aef14ceb979c6f96edead2d2482be7fffed504d",
"outputBlockId": "f578714b9773d7e53a55fb2a17dc5102bc281c4d9b2b9da431eeea3c9c0605d3",
"outputTransactionId": "869e1bf2a4a692df8bded1d440801c9a7600849ac245cfc3ac3d1d00514c969f",
"outputIndex": 3,
"outputGlobalIndex": 33689159,
"outputCreatedAt": 1119315,
"outputSettledAt": 1119317,
"ergoTree": "0008cd03349d9244648ed913f18110417ffde85cee2fca02c785932d8a229363b86896ed",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(349d92,9d6432,...)))}",
"address": "9grygda768RvJtBvabzBqgTAehr4R3bP8hn8AzCvki3GUKDRCe4",
"assets": [
{
"tokenId": "cdf549fccbb09ab8f38ecbf9a5ed37c926707753adf8fed19b039684a0772bfe",
"index": 0,
"amount": 22222,
"name": "RSN-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "be5542a890cd195abe52550e8e3fe03381c7c638c55616141c34af23749ca5a5",
"value": 1100000,
"index": 0,
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"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[6572676f,94061a31b391252b06321d0ead9e76f9d7810d89fb4f2c28a9272539f8ccba44,038a51fb732b5e46f139eb1f92ac773e4515eb9435df38259460c5316efea376,648e596f85eff17ac596e8949c077351d0191a0ce8af91546f2f742c57fed862,f862fac848a53ec304cce627333413c80c63018c9728689ae63784ff133ad522,39b4e1000a80e27d901b680c04d39be2a89febafdf47749bf0d8e2fc548c28cb,4dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7,c3403069ad753d9f9ec2746f08d3bd6e7c9d4d45e4396d5494f7016b83977720,d4eac31b2de6142f9d7b56d3cddae5f8313b76a18294ba4324f45567a20ef251,129a7d756ebb65945d7543ef9291c0ac141476adb766c1a966d3d66e180a23ce,7231b4c2548c41e37f86fab15d9ba75e1e1b5011e621cc93406be6dbc65975b2,00e23ccdac6079bd1c3bb0a1e52944caa0918d03ef81c9d4565ed2d3417fa4fd]"
},
"R5": {
"serializedValue": "110c0080897a80897a80897a80897a80897a80897a80897a80897a80897a80897a80dac409",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,1000000,10000000]"
},
"R6": {
"serializedValue": "1106c09a0c8c01020a80d0dbc3f4028084af5f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000,70,1,5,50000000000,100000000]"
}
}
}
],
"outputs": [
{
"boxId": "475b5df2295ca1ddb7cba621e5e4d34503336acaef10c38e6387793838a2f6d2",
"transactionId": "95d831fb0da441d8ceec413b3b353487680bc17fb87d5867e843c8bd09fda783",
"blockId": "04a3371dd617513cc84f8b316d80c26a40d0dfc9b457f07863ee3cbd4d851e2c",
"value": 9900000,
"index": 0,
"globalIndex": 33856496,
"creationHeight": 1123119,
"settlementHeight": 1123121,
"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": 900000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[038a51fb732b5e46f139eb1f92ac773e4515eb9435df38259460c5316efea376,c3403069ad753d9f9ec2746f08d3bd6e7c9d4d45e4396d5494f7016b83977720,7231b4c2548c41e37f86fab15d9ba75e1e1b5011e621cc93406be6dbc65975b2,129a7d756ebb65945d7543ef9291c0ac141476adb766c1a966d3d66e180a23ce,648e596f85eff17ac596e8949c077351d0191a0ce8af91546f2f742c57fed862,39b4e1000a80e27d901b680c04d39be2a89febafdf47749bf0d8e2fc548c28cb,d4eac31b2de6142f9d7b56d3cddae5f8313b76a18294ba4324f45567a20ef251,f862fac848a53ec304cce627333413c80c63018c9728689ae63784ff133ad522,4dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[37343731643038333737386433313665613562646431646130633135613435316365396130373637616338383262313439343531313239356261396633613937,6572676f,63617264616e6f,396944356a4d6f4c6a4b39617a546469677954387a3151593671487241366756724a616d4d46384d4a3271743435704a704463,61646472317138686d70357a6a7a7676377337706d67656d7a336d76726b64326e7537363039687767737161306175663668376833723678366a6e327a727438787333656e633533663461716b733776356735743235346675326e38737a3277736c6132393361,00000002540be400,0000000076255eac,000000002959e123,657267,6173736574313932786d6a796a7578707764776735656d6b766466776671373937356832727377646b796879,36343031376236656262626239633734316330366137643865616564333063336334353064383530343739386663353665363866316532346636656337326135,000000000011229b]"
},
"R6": {
"serializedValue": "0e20df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
}
},
"spentTransactionId": "c6ae37916acc2defa791b6e80ce4cf838c3c788783d37fe0397a50b76550cb1b",
"mainChain": true
},
{
"boxId": "f3864ee38f622829b1cc3b09860d656ac52fc09a02ab000a96f20a69461ef9cb",
"transactionId": "95d831fb0da441d8ceec413b3b353487680bc17fb87d5867e843c8bd09fda783",
"blockId": "04a3371dd617513cc84f8b316d80c26a40d0dfc9b457f07863ee3cbd4d851e2c",
"value": 1100000,
"index": 1,
"globalIndex": 33856497,
"creationHeight": 1123119,
"settlementHeight": 1123121,
"ergoTree": "0008cd03349d9244648ed913f18110417ffde85cee2fca02c785932d8a229363b86896ed",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(349d92,9d6432,...)))}",
"address": "9grygda768RvJtBvabzBqgTAehr4R3bP8hn8AzCvki3GUKDRCe4",
"assets": [
{
"tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
"index": 0,
"amount": 25807,
"name": "rptconfRSNV1",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 1,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2228e54299db6c13479c6ced3705df36f2ed0e4e815ed7536ba99be14a13179d",
"index": 2,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "cdf549fccbb09ab8f38ecbf9a5ed37c926707753adf8fed19b039684a0772bfe",
"index": 3,
"amount": 22222,
"name": "RSN-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "4687dff1add059e0d0d430e7fe18dc7061f6d663051eed4659978c9ba686aaa4",
"mainChain": true
},
{
"boxId": "4b3573353a284d3335a157a92237159cb33da9aaf998f2750affe94b411ed335",
"transactionId": "95d831fb0da441d8ceec413b3b353487680bc17fb87d5867e843c8bd09fda783",
"blockId": "04a3371dd617513cc84f8b316d80c26a40d0dfc9b457f07863ee3cbd4d851e2c",
"value": 1100000,
"index": 2,
"globalIndex": 33856498,
"creationHeight": 1123119,
"settlementHeight": 1123121,
"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": "1187bb4c66c454f9aea01eaff324141d1a2f80e872089bc35cada36e600825b8",
"mainChain": true
}
],
"size": 1908,
"isUnconfirmed": false
}