Transaction
ID: dc31e082c6...e017
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:
0.00114 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0011 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0099 ERG
Tokens:
90
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00114 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 648,275
Total coins transferred: 0.01214 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000569 ERG
Raw Transaction Data
{
"id": "dc31e082c627a84e71ba00f45948618385d195fd7aaaa48a78b369ffee79e017",
"blockId": "e81b922ce9e9e1e389c695cb0965c93f6469c54595363ba23b6d1173ba0a98e4",
"inclusionHeight": 1119325,
"timestamp": 1698140528396,
"index": 36,
"globalIndex": 6008236,
"numConfirmations": 648275,
"inputs": [
{
"boxId": "13a35ea9a9913d891bcb178cea7beacbd449fb098fbff4a24b57b806846ddbac",
"value": 1100000,
"index": 0,
"spendingProof": null,
"outputBlockId": "f9de86a288d0387924ddd080c66698af55087b13cdda4b8f5711bd44da907bd5",
"outputTransactionId": "6207477d378fbc52960e6d0b101cf56ea34363e5955d8ee2e5b225b4aed02b11",
"outputIndex": 1,
"outputGlobalIndex": 33678175,
"outputCreatedAt": 1119198,
"outputSettledAt": 1119203,
"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": "1a0120648e596f85eff17ac596e8949c077351d0191a0ce8af91546f2f742c57fed862",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[648e596f85eff17ac596e8949c077351d0191a0ce8af91546f2f742c57fed862]"
},
"R5": {
"serializedValue": "1a01209594bbb16dea6e3a1144fa7803ce97aadd47a0f1e3a6de1c22f4e1381afc4170",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9594bbb16dea6e3a1144fa7803ce97aadd47a0f1e3a6de1c22f4e1381afc4170]"
},
"R6": {
"serializedValue": "0e20e945be379d3337467a518152a8ea255105237deb7a0f43397c26c491d6e28945",
"sigmaType": "Coll[SByte]",
"renderedValue": "e945be379d3337467a518152a8ea255105237deb7a0f43397c26c491d6e28945"
},
"R7": {
"serializedValue": "0e20df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
}
}
},
{
"boxId": "f283fa4cb434c3f7474d444e345687ae1e90862198cd229e0bed7f475f40c65b",
"value": 1100000,
"index": 1,
"spendingProof": null,
"outputBlockId": "f9de86a288d0387924ddd080c66698af55087b13cdda4b8f5711bd44da907bd5",
"outputTransactionId": "a27610724ac46629d927ff2964b4a8864c44d55612580342ca5622bac9b7f41d",
"outputIndex": 1,
"outputGlobalIndex": 33678179,
"outputCreatedAt": 1119198,
"outputSettledAt": 1119203,
"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": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[39b4e1000a80e27d901b680c04d39be2a89febafdf47749bf0d8e2fc548c28cb]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9594bbb16dea6e3a1144fa7803ce97aadd47a0f1e3a6de1c22f4e1381afc4170]"
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"sigmaType": "Coll[SByte]",
"renderedValue": "630eb075d6bec0329f08d221f4b14f7a699a3ffb858de1406009ab16d73d1251"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
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{
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"value": 1100000,
"index": 2,
"spendingProof": null,
"outputBlockId": "091756004b2558b97d79b60bd84a5dde2916cecfa338b9989f0debd6491779e7",
"outputTransactionId": "6ceeba613f16cf8e5f90421248aa8f15cfabf0b26250617569876e578d2582f4",
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"outputGlobalIndex": 33678241,
"outputCreatedAt": 1119198,
"outputSettledAt": 1119204,
"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": "1a01204dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[4dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7]"
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"R5": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[9594bbb16dea6e3a1144fa7803ce97aadd47a0f1e3a6de1c22f4e1381afc4170]"
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"R6": {
"serializedValue": "0e204f4c2822202ae8085c8df0d0b05ced41a3d002af6e06bd98b090aacc0bdd5c0c",
"sigmaType": "Coll[SByte]",
"renderedValue": "4f4c2822202ae8085c8df0d0b05ced41a3d002af6e06bd98b090aacc0bdd5c0c"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
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{
"boxId": "4753471d81ae45bb0bb370b93208802a82c1f48d9055627d23587310866e7bd6",
"value": 1100000,
"index": 3,
"spendingProof": null,
"outputBlockId": "79de596f64f95ee0ab7755c4a0b905998335d31ca1865b312115f10d0ca7b5e0",
"outputTransactionId": "bf3867feb1c338273229c9607e1f89bffcd0705fff25aa9a6ff92997afab69ae",
"outputIndex": 1,
"outputGlobalIndex": 33678544,
"outputCreatedAt": 1119201,
"outputSettledAt": 1119206,
"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]]",
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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[Coll[SByte]]",
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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": "c4d3d5e81bd3607055ec7ee5556ec81e7c851873d77db79feefaeb3f5c616ee4",
"outputTransactionId": "ee0324fd145e087855b2e0f6fde8c73ba6e09f007aa020eb17b1355fc3a25d65",
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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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"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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"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",
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}
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"additionalRegisters": {
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"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[d4eac31b2de6142f9d7b56d3cddae5f8313b76a18294ba4324f45567a20ef251]"
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"R5": {
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{
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"ergoTree": "0008cd0391d0eae1676bff284b1feaf7a11d7ea62cda233489157fff218aae8426fa3e43",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(91d0ea,ec80b5,...)))}",
"address": "9ha2NGr96WvhWB8hQ94vFa8rtJQGrZjoqeT57ggrp1gdhSHe9CF",
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"address": "9ha2NGr96WvhWB8hQ94vFa8rtJQGrZjoqeT57ggrp1gdhSHe9CF",
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{
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},
"R6": {
"serializedValue": "1106a09c018c01022880a8d6b90700",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000,70,1,20,1000000000,0]"
}
}
}
],
"outputs": [
{
"boxId": "e758cb02f2b22eb407a24b35caf5218bcf699bf8391a8c7e4875f30aa7a25430",
"transactionId": "dc31e082c627a84e71ba00f45948618385d195fd7aaaa48a78b369ffee79e017",
"blockId": "e81b922ce9e9e1e389c695cb0965c93f6469c54595363ba23b6d1173ba0a98e4",
"value": 9900000,
"index": 0,
"globalIndex": 33689522,
"creationHeight": 1119323,
"settlementHeight": 1119325,
"ergoTree": "100c0400040004000400040004000e20a7b4203b78d84e84a8c730e6601367e3ddf93a18425bd435c6478efbe44fec54040204000e20eca2e0240bea93c5340cca325d1f1d7eea760ae44dbcf6bb3c2f35ca3329b33e04c0700e20c5a029f593a106e1594dda1e5435ae44b347fa4ddf8fa03ccd057afc28b7dd38d805d601e4c6a7041ad602b17201d603b4a573007202d604c2b2a5730100d605cb7204d196830301937202b17203afdc0c1d7201017203d901063c0e63d801d6088c720602ededed9383010e8c720601e4c67208041a93c272087204938cb2db63087208730200018cb2db6308a773030001938cb2db63087208730400029d8cb2db6308a7730500027e72020595937205730696830201938cb2db6308b2a47307007308000173099299a3730a8cc7a70196830201aea4d901066393cbc27206730b937205e4c6a7060e",
"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": 90000,
"name": "eRWT-loen",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[648e596f85eff17ac596e8949c077351d0191a0ce8af91546f2f742c57fed862,39b4e1000a80e27d901b680c04d39be2a89febafdf47749bf0d8e2fc548c28cb,4dbcd6c106ea0342d984eded9a491816cb949d0e3c4c49fcef5e6b027cf3f4a7,c3403069ad753d9f9ec2746f08d3bd6e7c9d4d45e4396d5494f7016b83977720,038a51fb732b5e46f139eb1f92ac773e4515eb9435df38259460c5316efea376,f862fac848a53ec304cce627333413c80c63018c9728689ae63784ff133ad522,129a7d756ebb65945d7543ef9291c0ac141476adb766c1a966d3d66e180a23ce,7231b4c2548c41e37f86fab15d9ba75e1e1b5011e621cc93406be6dbc65975b2,d4eac31b2de6142f9d7b56d3cddae5f8313b76a18294ba4324f45567a20ef251]"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[31323739663261323739636663393436363465326535666433616436363333356433656532656432663461383330656230343462663632326330346631386134,6572676f,63617264616e6f,396944356a4d6f4c6a4b39617a546469677954387a3151593671487241366756724a616d4d46384d4a3271743435704a704463,61646472317138686d70357a6a7a7676377337706d67656d7a336d76726b64326e7537363039687767737161306175663668376833723678366a6e327a727438787333656e633533663461716b733776356735743235346675326e38737a3277736c6132393361,000000000057080c,000000000007a120,000000000002ab98,63646635343966636362623039616238663338656362663961356564333763393236373037373533616466386665643139623033393638346130373732626665,6173736574313438746163616b73766a6d63636d7875776d6e6a7864757774306565763274387468376d7938,39393838336364366162376231303537663661323439323464336230363236663962316365633637386539366165313764393432373032313237303539326437,00000000001113d8]"
},
"R6": {
"serializedValue": "0e20df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "df73d6176bb691ff12d47db22dc23f1f7003f02a56c95d6841685fe68469b3d5"
}
},
"spentTransactionId": "b6f2b7d85fbc8c99da16bdedebcb81f2d90d6af9e548d456b997e1b76b9f7c8b",
"mainChain": true
},
{
"boxId": "6fce78509271ebef5e307e774d53efde5d9f40a67aa7fce4cf1fef16a0055d9e",
"transactionId": "dc31e082c627a84e71ba00f45948618385d195fd7aaaa48a78b369ffee79e017",
"blockId": "e81b922ce9e9e1e389c695cb0965c93f6469c54595363ba23b6d1173ba0a98e4",
"value": 1140000,
"index": 1,
"globalIndex": 33689523,
"creationHeight": 1119323,
"settlementHeight": 1119325,
"ergoTree": "0008cd0391d0eae1676bff284b1feaf7a11d7ea62cda233489157fff218aae8426fa3e43",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(91d0ea,ec80b5,...)))}",
"address": "9ha2NGr96WvhWB8hQ94vFa8rtJQGrZjoqeT57ggrp1gdhSHe9CF",
"assets": [
{
"tokenId": "0fdb7ff8b37479b6eb7aab38d45af2cfeefabbefdc7eebc0348d25dd65bc2c91",
"index": 0,
"amount": 69,
"name": "$Lambo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f8fe64d3d94d4eb193ea9d6304646db67bd914ed42cebd3a4f614d9d9de75cf0",
"index": 1,
"amount": 1788,
"name": "rptconfRSNV1",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "aba9cf9df2a03cc07c1adc7515d4d70346c93bd7a250525536a90008f73d289d",
"index": 2,
"amount": 1,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {},
"spentTransactionId": "b8b6f7b9ab84ef2ea6e3351f8b0d010e284f4d1541c4954f3438500b105f499f",
"mainChain": true
},
{
"boxId": "d6e0089a1fe85293439c4b35e872567cf5799a7ed995ad50dd711fda3ce61ca0",
"transactionId": "dc31e082c627a84e71ba00f45948618385d195fd7aaaa48a78b369ffee79e017",
"blockId": "e81b922ce9e9e1e389c695cb0965c93f6469c54595363ba23b6d1173ba0a98e4",
"value": 1100000,
"index": 2,
"globalIndex": 33689524,
"creationHeight": 1119323,
"settlementHeight": 1119325,
"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": "87d4257d3f374ad88ca9cd73f219ee8e70ee07b811a73785c6ba1bd55e04b852",
"mainChain": true
}
],
"size": 1932,
"isUnconfirmed": false
}