Transaction
ID: cf85eefd2f...0a87
Inputs (90)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00101 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
4.1 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.17701 ERG
Tokens:
267,000
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.1 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00205 ERG
Transaction Details
Confirmations: 133,898
Total coins transferred: 4.28 ERG
Fees: 0.00205 ERG
Fees per byte: 0.000000489 ERG
Raw Transaction Data
{
"id": "cf85eefd2f9c371961a6b2214ef656d85f081fbaa160bf3d07b4816f58370a87",
"blockId": "5e6944504e9e4dcdd339d222cdde8cd00795fcedd4c1015283c50dc7f17ca71d",
"inclusionHeight": 1624237,
"timestamp": 1759274774167,
"index": 5,
"globalIndex": 9548297,
"numConfirmations": 133898,
"inputs": [
{
"boxId": "de53fd34ec06fb299b37bbe11d44984411efced7e8a52a6b4f423e5a237c7332",
"value": 2000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "b65dc435f42616f29a16f386a7332b27ab69d8897c269bd57fef19c758579df7",
"outputTransactionId": "bebed201138f8945f66d53b58f17b0f8829db92b8b00d00f8b0290c22e9a70e5",
"outputIndex": 1,
"outputGlobalIndex": 50555817,
"outputCreatedAt": 1624219,
"outputSettledAt": 1624221,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2029beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "29beed9c0f62f20b8bafca761a0d0665f66ec8ce4f8678ecb5d389584f6534a4"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e202d79856104f174596c5eeb21d22c52218c703b5806c594446fb2e586286ff22a",
"sigmaType": "Coll[SByte]",
"renderedValue": "2d79856104f174596c5eeb21d22c52218c703b5806c594446fb2e586286ff22a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "0810653623cc84efc1503d531270bc6ceed0f0ac60c5b433bb80ad5cbc4638b3",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "dc3d5da54d30ee37d45f9d9b3ac9bc5a2fb0387135d3ad55280f4820c6218b26",
"outputTransactionId": "7f20c638d51d2c629da3d520f44e72589cf2771fbf6062bb56759f60c15f17f0",
"outputIndex": 1,
"outputGlobalIndex": 50555893,
"outputCreatedAt": 1624223,
"outputSettledAt": 1624224,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206576e8c63376413c7590e342bf637a9cfb8c25eecf73edf78ed96d2668e0e557",
"sigmaType": "Coll[SByte]",
"renderedValue": "6576e8c63376413c7590e342bf637a9cfb8c25eecf73edf78ed96d2668e0e557"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20d94feab91a894e979fd936e3647c5af2bfccc1f4800396042250b650d5ef6691",
"sigmaType": "Coll[SByte]",
"renderedValue": "d94feab91a894e979fd936e3647c5af2bfccc1f4800396042250b650d5ef6691"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1edc591e3b9095237c1bda05ba57e6825dd035f9a33c437420d2c25174f27939",
"value": 1010000,
"index": 2,
"spendingProof": null,
"outputBlockId": "9265633c6ab27edd7fad11eb108436fc2363382f1f9ab6f3fcc2cd69465ef45f",
"outputTransactionId": "2d9a29a34d67c1eed1c6bf1e80d4da1a772242fb9fd39e33ed8998f0a38d3810",
"outputIndex": 1,
"outputGlobalIndex": 50555925,
"outputCreatedAt": 1624223,
"outputSettledAt": 1624226,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "3766d9edd8ed272e11c762e2bbc5b1a50aa0b7c38ca8f8aff280f3179fd19f8b"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e200998625a85067c3d69fe4b41344dc8243136254a6c1fc96fa0a03d6a906de63a",
"sigmaType": "Coll[SByte]",
"renderedValue": "0998625a85067c3d69fe4b41344dc8243136254a6c1fc96fa0a03d6a906de63a"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "8ac6e54d403e329cb0a878ee5610a95e5d21f82ff7633986a17cebe0da98df76",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "fbde82b1d6c4524da33282509a5bd668d16ddc96112306870ede527261244a46",
"outputTransactionId": "3cc0f511ca3fb7dd94d5a692d4bbbf3c30f717c822b3e4f3f5bb6f5bd4319a46",
"outputIndex": 1,
"outputGlobalIndex": 50556037,
"outputCreatedAt": 1624227,
"outputSettledAt": 1624229,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a841b23663f1548f4489e46978c6ee3ee6df43af85c2d907923b908e423b508d"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e20683f6b7ddf1272999e345ebf395f03800f4eb43b8dc2de4c7c11b8fe10a4d003",
"sigmaType": "Coll[SByte]",
"renderedValue": "683f6b7ddf1272999e345ebf395f03800f4eb43b8dc2de4c7c11b8fe10a4d003"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "8da6a91f639ae8f940ac18257992d99e88bbe603792e299c362f32eb87486243",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "fbde82b1d6c4524da33282509a5bd668d16ddc96112306870ede527261244a46",
"outputTransactionId": "768192cb8b6499982a89a44181e57b851388fc27bd68921b42b5705269736e5c",
"outputIndex": 1,
"outputGlobalIndex": 50556042,
"outputCreatedAt": 1624227,
"outputSettledAt": 1624229,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33",
"sigmaType": "Coll[SByte]",
"renderedValue": "b4cde26fe0c84cd229c5d5660f250690bc112e501a050aade9e77683b7cb2d33"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e2083fb37cf1c935ffc94eca3f363c093d3b1965db0d51ab19cdeb2ee7143c065d7",
"sigmaType": "Coll[SByte]",
"renderedValue": "83fb37cf1c935ffc94eca3f363c093d3b1965db0d51ab19cdeb2ee7143c065d7"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "0496b32a59f7473bee99eac66ae127ceb8057b0b4bfe0bd8a4f2e91ea2aeb58c",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "fbde82b1d6c4524da33282509a5bd668d16ddc96112306870ede527261244a46",
"outputTransactionId": "ab284f5d14f0430b3ae32c862b05b54a7ce01eae6bb53daa68d7f19417188f28",
"outputIndex": 1,
"outputGlobalIndex": 50556050,
"outputCreatedAt": 1624227,
"outputSettledAt": 1624229,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20cb2f19da29f4bee653709192e4912a0dee7cfa4d01a0cfe951212802f1d12ab4",
"sigmaType": "Coll[SByte]",
"renderedValue": "cb2f19da29f4bee653709192e4912a0dee7cfa4d01a0cfe951212802f1d12ab4"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e209d83633be3b13fed5d2402e4158b9d5d13df4042dd2e4c6fe1f8bd06d4d89751",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d83633be3b13fed5d2402e4158b9d5d13df4042dd2e4c6fe1f8bd06d4d89751"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ba4c32d43414e5aaa1544bd542e8a0bd1bbcded483eaf18265660c35622dffd0",
"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "3a987ccece437e44fc0f79ea535c1cb75f7ec083afe4bec4176ac97d4ff2ffc2",
"outputIndex": 1,
"outputGlobalIndex": 50556078,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "d7b7e5159efc9cd6a29c9ca4bb017b52bfdc26c0ebbbba8806a753e04849e2f5"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e2003fe6ccb8dc63423b49ddc340ecee24613d0441b3bab46565f36e8be839a9bf3",
"sigmaType": "Coll[SByte]",
"renderedValue": "03fe6ccb8dc63423b49ddc340ecee24613d0441b3bab46565f36e8be839a9bf3"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "7ee8e33b1a62b912088797f5e9c5274abff439a4f12d92540ebdd14545dd24fd",
"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "0d097d00156a2ad377a3abf9f0a6414c6dd31f042a41b6198d4c657e3dfafa1c",
"outputIndex": 1,
"outputGlobalIndex": 50556083,
"outputCreatedAt": 1624228,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce7dcc00b7759ccf97252cd5c994b2415a6b97c2580a5244bc9910ea34336a96"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "13ce4467dccb8153729bd3f32d2097be470a0205e90f397bc928f052194fa069"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "4f369b93ef176a16ece98a90250b27c32f96c2797a0ada79b22acf8ed69842de",
"value": 2000000,
"index": 8,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "318c3e7d4ca49b496595892f68f4444cdff3e800c460ad72b087a7a750110467",
"outputIndex": 1,
"outputGlobalIndex": 50556088,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20db521a1953cc84dfede6527b941a8bca07230aafdcf0056961d459aa7b1f4f7e",
"sigmaType": "Coll[SByte]",
"renderedValue": "db521a1953cc84dfede6527b941a8bca07230aafdcf0056961d459aa7b1f4f7e"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20dc103d6dac6d8bcd8a5612515f3d237b4710a59f3a9b27e9787088f1e03badca",
"sigmaType": "Coll[SByte]",
"renderedValue": "dc103d6dac6d8bcd8a5612515f3d237b4710a59f3a9b27e9787088f1e03badca"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "eb9ca61322f658569e02caef0e99fab20e9adbcc44157a9b2736ff26a8aa894e",
"value": 2000000,
"index": 9,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "3f56635b1d6dcac2c33e49ba3fb44fc05ef95b835f6b91f7d0d2106b6ca3006f",
"outputIndex": 1,
"outputGlobalIndex": 50556093,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "451e6a391af3b38336460dfab25c283697256a195638eeb9627b3b687f42009a"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "63cba6ab0aba7099beddb9b3d732307ca34e1d0a436bfa1e1b4810c00dbf547b"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "0dd5aa87b1c9531f39679ef7502da1a7d52a77bf88da39460af114037cb113f5",
"value": 2000000,
"index": 10,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "6377a6f9ff2bf13ed5df39b7c42db698a71ed3ce5a3dd1366413d44b7b8cb506",
"outputIndex": 1,
"outputGlobalIndex": 50556098,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20329d66895b8d9c84947bfe3d72335158ada0fdd8ac8643f836c81ec85785e01a",
"sigmaType": "Coll[SByte]",
"renderedValue": "329d66895b8d9c84947bfe3d72335158ada0fdd8ac8643f836c81ec85785e01a"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "d75469084620eef49db80fcc8479b46d01eb20077bb78905f127006594b1f4d8"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "09731c32691a288e1fc12c16d24ac6e1e60c43578d4a397233dcb0ea26d3939a",
"value": 2000000,
"index": 11,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "80280371dd702013a85172458a2373d6801e71bd1ef451375de10f57396f906d",
"outputIndex": 1,
"outputGlobalIndex": 50556103,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202248234c5efb1aa1731732d33f184c02a0fdc1a98c1f3380c65dd7f1fa6e48f1",
"sigmaType": "Coll[SByte]",
"renderedValue": "2248234c5efb1aa1731732d33f184c02a0fdc1a98c1f3380c65dd7f1fa6e48f1"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20b12e8bbcc5d865cf2dae7503be13948c8633cf45d48f5f3052a0bc1856548c97",
"sigmaType": "Coll[SByte]",
"renderedValue": "b12e8bbcc5d865cf2dae7503be13948c8633cf45d48f5f3052a0bc1856548c97"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "efa18142f7e3b12aa9056c74a776c9c40d4ad20720a6644980e843dfaa4ebb88",
"value": 2000000,
"index": 12,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "b91a175caf8e12f59fbe1a22a3cd555e122bd7f799dc40d979060615cb0f9a58",
"outputIndex": 1,
"outputGlobalIndex": 50556108,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fb50eeb02f090392ce61c8f7954b82e75a75256239721ad5fe30c7d902b2ded7",
"sigmaType": "Coll[SByte]",
"renderedValue": "fb50eeb02f090392ce61c8f7954b82e75a75256239721ad5fe30c7d902b2ded7"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e2094ae15fd05023ec386d351c7ec6556aadca06c96ed328efef013f62e8c587d0e",
"sigmaType": "Coll[SByte]",
"renderedValue": "94ae15fd05023ec386d351c7ec6556aadca06c96ed328efef013f62e8c587d0e"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "6202eaf3fb1787dccc8151289321cda1343cb7af45a7584b2dcdd3a9963d0d6a",
"value": 2000000,
"index": 13,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "c793c65ba55a0adc0d78f239bf113e4277ba977550613bc15761043031e85186",
"outputIndex": 1,
"outputGlobalIndex": 50556113,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e203684a6fc79378d5207e1dc5bc3f399d2367031b79a2fc76f8d0bfe2082c71be7",
"sigmaType": "Coll[SByte]",
"renderedValue": "3684a6fc79378d5207e1dc5bc3f399d2367031b79a2fc76f8d0bfe2082c71be7"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "685e1c13c4b0d21352601cb89e6b0a4aeb263e4d5e839767725d71ea714feb9d"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "ac8b86dbfa6e390cd3248108a4e39c921c51e568764d36eebd02dedc481025cc",
"value": 2000000,
"index": 14,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "cc86e44a8813c8b9f5a849b980c8230e10e4ee53c1afd351a8770404c9ba4fb5",
"outputIndex": 1,
"outputGlobalIndex": 50556118,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20315a9f8b06f0e39d5c1b4e5ef069cf75aedd27206e2f90dbc77eab0e1b18bfc1",
"sigmaType": "Coll[SByte]",
"renderedValue": "315a9f8b06f0e39d5c1b4e5ef069cf75aedd27206e2f90dbc77eab0e1b18bfc1"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20a73e5ce7a52d3350031de3efe5203b5812316470f5d66a52a8d3bd41017cbdc2",
"sigmaType": "Coll[SByte]",
"renderedValue": "a73e5ce7a52d3350031de3efe5203b5812316470f5d66a52a8d3bd41017cbdc2"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d49cdf47b5c1a46addc5712f19006831db006cd0ddcf0ded90679f213c8e24ec",
"value": 2000000,
"index": 15,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "eafa1f9dae6cf5e1aeeecb19e173f24e58fda92dbe09232c44fe057339f318ad",
"outputIndex": 1,
"outputGlobalIndex": 50556123,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7",
"sigmaType": "Coll[SByte]",
"renderedValue": "1fcbc0d9b62827ee208e42c618022a606983d1129f44ef62f28c3a48ecef60d7"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20d531dd49ff467e322d83e67392df0e23354dde4c771b6da791a8009640930846",
"sigmaType": "Coll[SByte]",
"renderedValue": "d531dd49ff467e322d83e67392df0e23354dde4c771b6da791a8009640930846"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "63f9545dbb330547553511bdaf3bce714a4e3d4f55a0b359b7aca8e490bda9ef",
"value": 2000000,
"index": 16,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "faa47f150d5a151de109be86286a32c95c78e8a9833e920bc0b44c343bc34dce",
"outputIndex": 1,
"outputGlobalIndex": 50556128,
"outputCreatedAt": 1624228,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c",
"sigmaType": "Coll[SByte]",
"renderedValue": "5bef0fc79b73761ed88d6486fc9a65075494418f4efa85859366d1bda286b17c"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20f448cf1e8413bee9e85ff071259ec2c62925e7c699a69d1a269cd094a0ae2c17",
"sigmaType": "Coll[SByte]",
"renderedValue": "f448cf1e8413bee9e85ff071259ec2c62925e7c699a69d1a269cd094a0ae2c17"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "28437a764dcd8de8c6d3f28762f4775e93e651a79d07179dc1440a4fe0f6b524",
"value": 2000000,
"index": 17,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "991bcd08a9298009523fbf7983f4221fc9589a3017735c301868e7fac36c60eb",
"outputIndex": 1,
"outputGlobalIndex": 50556133,
"outputCreatedAt": 1624228,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200ab09974c63962a46326ba99448da5c29bb826ddb4773ba4a2f0deb0204a1bf6",
"sigmaType": "Coll[SByte]",
"renderedValue": "0ab09974c63962a46326ba99448da5c29bb826ddb4773ba4a2f0deb0204a1bf6"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20c0cffb20d0cfccf242025e7bc58cb4a3b9027cf8ecd5f31207ff4b84f3b90a60",
"sigmaType": "Coll[SByte]",
"renderedValue": "c0cffb20d0cfccf242025e7bc58cb4a3b9027cf8ecd5f31207ff4b84f3b90a60"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1d439c7fc63c07714152b1b9fa048b975115d73d5c07b8d776f70d0bfdfd1216",
"value": 2000000,
"index": 18,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "a026bd9b1fa56ac0604a9b7f880b1f49d0ec87eebebac2fb8e6757332bc32696",
"outputIndex": 1,
"outputGlobalIndex": 50556138,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2018aeeab47d55f0f07f44e24687cd529b20feab32dda0ae9e1171d22abd9cde49",
"sigmaType": "Coll[SByte]",
"renderedValue": "18aeeab47d55f0f07f44e24687cd529b20feab32dda0ae9e1171d22abd9cde49"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5fc020432e915a3b3dcc54f1fcfd3fa218a92b41fe544fd1dd4b209132f50101"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "53f542254f983ce1babd055337984fe36b17f85697d909674ff4ae7b810cc841",
"value": 2000000,
"index": 19,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "fbb06bdcf50649953bf5f750e433591ed74a5a693d950ef82c7a6f39eaca7638",
"outputIndex": 1,
"outputGlobalIndex": 50556143,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f",
"sigmaType": "Coll[SByte]",
"renderedValue": "581d31c3561579b1d2de06186317bdf2fd57f626c274c1e3a83ff503257d400f"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e20c18fe99a71c45faadb2dcff59dc8ed6d4d883d26aae7faab149e75bb0a1d084e",
"sigmaType": "Coll[SByte]",
"renderedValue": "c18fe99a71c45faadb2dcff59dc8ed6d4d883d26aae7faab149e75bb0a1d084e"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "d8fc11149d0d5a456233697e7c2b7cabb776a69de94d6ad887d65c82e3f0ff43",
"value": 2000000,
"index": 20,
"spendingProof": null,
"outputBlockId": "a0ad7d38a0a34e4625002c8dd38e3cfb4a45d0981ace35007a2990f8123168f4",
"outputTransactionId": "2c4be682dc4b2f8075b62f2b3252001be4334e45edbe87abbe7aa406a9054e20",
"outputIndex": 1,
"outputGlobalIndex": 50556148,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206435f0cabc1b3081f365859bc6e0fe6535e6342e4e65bc5a6c3373d32f280594",
"sigmaType": "Coll[SByte]",
"renderedValue": "6435f0cabc1b3081f365859bc6e0fe6535e6342e4e65bc5a6c3373d32f280594"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20da9df3bf4917b96016514cbbb32f95dbdea14070eba61741c61272c2b6388ca7",
"sigmaType": "Coll[SByte]",
"renderedValue": "da9df3bf4917b96016514cbbb32f95dbdea14070eba61741c61272c2b6388ca7"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "c49e1d9de2cf7da214d2b0b768e0dd79434b53fc36fe52b494446e10475e4b53",
"value": 2000000,
"index": 21,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "35c3941914f767fb8430b4558b6b765d04abe005a05bc23abb8829cca90b55b3",
"outputIndex": 1,
"outputGlobalIndex": 50556173,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0b0ac5850cdf0b1164e9d59bb5db54d83d9b6bb73442822aeb7542862710017a"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5a3b7b67351c203de53419508baf0458451c842fc427a76731589cce929b4c84"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 22,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "e7dab074f393c77668cd92f91d50cacea24b95ce5173d7f99aa61c3d6b69415d",
"outputIndex": 1,
"outputGlobalIndex": 50556178,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ca2e79041d6386afb8ec6d6f74e579821cd3059f8c76db4c562c270ff1c9c698"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6c2c08a19cbf93c615ef53157a0315deff3316dd1ac29a6a702ec72742b76530"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 23,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "2f1a34a1c5060a59c4b7663c10dc4d5256ee1e818143e16ee58fba084d6edc93",
"outputIndex": 1,
"outputGlobalIndex": 50556183,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20e658bd869bc04c3e547c5634f0fcd46d5fb66c2ac10a6a0d41fb63b5ffb2bd18",
"sigmaType": "Coll[SByte]",
"renderedValue": "e658bd869bc04c3e547c5634f0fcd46d5fb66c2ac10a6a0d41fb63b5ffb2bd18"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20b46cc3466ef245626ecfe601518f0db6cbbfbc1851f3fa529a3dbea3567ff6ae",
"sigmaType": "Coll[SByte]",
"renderedValue": "b46cc3466ef245626ecfe601518f0db6cbbfbc1851f3fa529a3dbea3567ff6ae"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "1156216f8a02abc8a96277fcdfc0a0503c5bacaa43584a29603208aed26798ec",
"value": 2000000,
"index": 24,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "5526f0fde2dd0732e7371ee5d8feff7b5299ca441616292c9456d33ade525cb9",
"outputIndex": 1,
"outputGlobalIndex": 50556188,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6b50c862a12ddc14eb9669032f924327b6d32eb69a4c617016121243c64bd55c"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e207a146915417a46d41b8f0dc3d1f81e66712ebbc1d988662ff835d0c652798acd",
"sigmaType": "Coll[SByte]",
"renderedValue": "7a146915417a46d41b8f0dc3d1f81e66712ebbc1d988662ff835d0c652798acd"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "a96ac51695b0c7278a3ee592b977873d268d42738e8e84aea48fd9a1acc27a07",
"value": 2000000,
"index": 25,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "83c474b856b902385d948f6c78055b281ec4136c4198a2b53d0cbbcd2882fdf0",
"outputIndex": 1,
"outputGlobalIndex": 50556193,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20aa7c8b3b2504769432f5dfc91219e733d1b2ae9c88a6e479c2c600170bf5757d",
"sigmaType": "Coll[SByte]",
"renderedValue": "aa7c8b3b2504769432f5dfc91219e733d1b2ae9c88a6e479c2c600170bf5757d"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a1cce5c5d1a1aad764867395a23093bfec1c4230fe1f8cf9b2aa231f91c054cf"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "5558086336090d31f7ff9a327f6659dd2224982efe6cd65054a7539e50146f51",
"value": 2000000,
"index": 26,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "9ed0931badfa332564e7c60827c5b845eccbdd224b779890e7c514433f0d3637",
"outputIndex": 1,
"outputGlobalIndex": 50556198,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20775df6d6db0307212c5afa022c474b07e6b59c99b7156db272338a853735e2fb",
"sigmaType": "Coll[SByte]",
"renderedValue": "775df6d6db0307212c5afa022c474b07e6b59c99b7156db272338a853735e2fb"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e2050bf95b974582a928b2eda3eddf016ecc5c888a84e3c1f57808df00921480c87",
"sigmaType": "Coll[SByte]",
"renderedValue": "50bf95b974582a928b2eda3eddf016ecc5c888a84e3c1f57808df00921480c87"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "ccb421e7f3c7d673c912db3a370839accc70e89c5a544f013c9af11b0666d70d",
"value": 2000000,
"index": 27,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "b1886ca8ffbbf680319b45f1328effcf078149d794ccdfa5dcdce0ca32b92db1",
"outputIndex": 1,
"outputGlobalIndex": 50556203,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "db8e71a8aa08bc0c7630f53d6189aff5e2c5e6c97d794b7617c0e41701a26c70"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20246d16fcad46be109d676ac28f2d53635e1da41969b157ed5e495107d570abe9",
"sigmaType": "Coll[SByte]",
"renderedValue": "246d16fcad46be109d676ac28f2d53635e1da41969b157ed5e495107d570abe9"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "320b644546170a6c80c6d4fe421f8017585764c2894fde68978d002faddc50c3",
"value": 2000000,
"index": 28,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "d3cb86fb4520260ee3efc46215ed4aa8441d146f0386dd7f42d3f26c25617e96",
"outputIndex": 1,
"outputGlobalIndex": 50556208,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e202e044c831f37e35eb02d07a35879a58b35a5c890272e25f0db77fe0fb9e26277",
"sigmaType": "Coll[SByte]",
"renderedValue": "2e044c831f37e35eb02d07a35879a58b35a5c890272e25f0db77fe0fb9e26277"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c79d08b95086a91365c790495e8a27e664b7c3e9d125d68498bab1e9193356d6"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "46b187846c4ebb80e36b13ead106689357e29492010fd1af3ef7b89344d1c4f8",
"value": 2000000,
"index": 29,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "d49e37cecc17946b2cf5ee6f175165b9a8863f5a3ed80d1667870d71740d159b",
"outputIndex": 1,
"outputGlobalIndex": 50556213,
"outputCreatedAt": 1624229,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d289df8aee844cdc1a6b7c84efe280a8d7c51dc6412c3e36b64d4ee71f4cb916",
"sigmaType": "Coll[SByte]",
"renderedValue": "d289df8aee844cdc1a6b7c84efe280a8d7c51dc6412c3e36b64d4ee71f4cb916"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e203f21eb3b85809577cf49470ce1c00869afe19e0407d34d19012bc146b66ffa09",
"sigmaType": "Coll[SByte]",
"renderedValue": "3f21eb3b85809577cf49470ce1c00869afe19e0407d34d19012bc146b66ffa09"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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{
"boxId": "006e8639f5ca8810ec0f79f8f584e136f58bdcdeb63c31c40f1d8e698ae7fb73",
"value": 2000000,
"index": 30,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "e9b3d9a6015e0c6609d0c6a1f5cc55b1ed7775b78e471a85daec1513bc49b06d",
"outputIndex": 1,
"outputGlobalIndex": 50556218,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a1e2ea874ca07c83ad85e3e4e86e653a41a72acbdf96bedea9ea51f80e176c27"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "b4182423393597fa23757b718f55b8fe741cb9c20792b49beb65d4263eebc38a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 31,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "ed00c27f4c61b3b2aa2261997dce46c24e09638e0a9d054abbfaac6f2cc1d8ba",
"outputIndex": 1,
"outputGlobalIndex": 50556223,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a55e3276aa4fbbf26d5816e6702bd53f6bd99dfe6c9eac91d7caff4f2c61cc0b"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 32,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "f02b42404f7db1a1a7df5963e95ec9cc275411384cdb4cf40fc9282514dd2220",
"outputIndex": 1,
"outputGlobalIndex": 50556228,
"outputCreatedAt": 1624229,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f2c363d81912cc3d8785ea9c607efed83af3a9b3ceb451e9cb005e57e8837f2c",
"sigmaType": "Coll[SByte]",
"renderedValue": "f2c363d81912cc3d8785ea9c607efed83af3a9b3ceb451e9cb005e57e8837f2c"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e207b4b17a211b73e0d1671b158ac91f90383113bc8ed58050ca33be21bd17731f4",
"sigmaType": "Coll[SByte]",
"renderedValue": "7b4b17a211b73e0d1671b158ac91f90383113bc8ed58050ca33be21bd17731f4"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "92ba81361656fa0b90e6abb4cb3a4cb77a72596a265c6f6ae17d4e4bb5c9b08f",
"value": 2000000,
"index": 33,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "f1e2d263ec1fc8e9360daab5cede456106751cc7be74a1cc4fedcdb1b17116bb",
"outputIndex": 1,
"outputGlobalIndex": 50556233,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "21ec3089084258295d454c433a8659455cc2adbfd18d112c5251454082109ffc"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e20c5b84e874c1c6152c7aecaa29b4e705a617d7e519fd64db2ab7b31fe9917b0f6",
"sigmaType": "Coll[SByte]",
"renderedValue": "c5b84e874c1c6152c7aecaa29b4e705a617d7e519fd64db2ab7b31fe9917b0f6"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 34,
"spendingProof": null,
"outputBlockId": "5c5c0e1f19112918f1f467cdb2c69ca59efbd35bef9997c32f30d63a13ca4d0c",
"outputTransactionId": "f6a6ccd342835eb12922854f7ae73683ed297078f19f54e40165f86955ebd8ec",
"outputIndex": 1,
"outputGlobalIndex": 50556238,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624231,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "50a75984162dd74c8c9215e1561e88231b464d953ab87e14876a2528429dc50a"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "eb497a32543681a86de11b6f26fee2c1095772bae3f9825d4ef2b51a5f46cf02",
"value": 2000000,
"index": 35,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "5675323358cd6be6419cbe78439daef5c2b6428568d1d97e3b928b0ff9250532",
"outputIndex": 1,
"outputGlobalIndex": 50556252,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206ec9d6e697910811ff55128761de199db6f1bec294ae63402a9cf8c738691b9b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6ec9d6e697910811ff55128761de199db6f1bec294ae63402a9cf8c738691b9b"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e2030630bdaa68ede56d09959b7436e242c3db56dfb1c3f50bc86db072c9fffc0a5",
"sigmaType": "Coll[SByte]",
"renderedValue": "30630bdaa68ede56d09959b7436e242c3db56dfb1c3f50bc86db072c9fffc0a5"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "dbcdd8a93af8b2f5d9b25c3fcac27271b2e651fa884b3e9b91f9cdfab1f966a5",
"value": 2000000,
"index": 36,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "130a805826702066ae3023acba079dfd520da477f928ecef4c33e8ecabec800e",
"outputIndex": 1,
"outputGlobalIndex": 50556257,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
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"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "884a1b36838137057dc7e877db3131222ecc167c1a4a08ef7bb81c62a26f5715"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"sigmaType": "Coll[SByte]",
"renderedValue": "eb91c55a256bc733adf597e1e1a258fa78c73f3ee484da122f5f230d400ad867"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "f0de5c9573069a48095082a86bebb308f12c7e774dcc1f530273fc9479de9933",
"value": 2000000,
"index": 37,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "20959e1f1ce02157c0c0ee18a06b419edee90976f4abb913deb65ab27e1eef8e",
"outputIndex": 1,
"outputGlobalIndex": 50556262,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "f9f53533ac2e6bc2965c9a6b6daff832a22cca3df388dd3caf0aeed146abcca6"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7d4b494390e1475314ec325bd36be4e4257714b48483f7a4f6d2ff68645913ff"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "cd5886d8ff50fafa98fd7ec2611592de5778592f8e8be9bc579208672dee911e",
"value": 2000000,
"index": 38,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "28e6be1eba0599b1a7f5bae5d185c8245c9fcb4a27b09e5ab3f3e476773c4607",
"outputIndex": 1,
"outputGlobalIndex": 50556267,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b",
"sigmaType": "Coll[SByte]",
"renderedValue": "f4e63793560cb0c644d8d30cf9260a153e509bbbcb8e1885e66208e23c8f7d8b"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20377bb4fad9fe08ed1b96d321c7a830ba695ac0189356b3c9d0ca0fecaf95c489",
"sigmaType": "Coll[SByte]",
"renderedValue": "377bb4fad9fe08ed1b96d321c7a830ba695ac0189356b3c9d0ca0fecaf95c489"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "13a5e6fa74989f6b51e27b8fb47213ec18d5c4c5d4583791f1cbdea832fc4494",
"value": 2000000,
"index": 39,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "3eb480fc8d6b342b23c97e6f1069251db8dc94439f35ae59020cb5ba33404670",
"outputIndex": 1,
"outputGlobalIndex": 50556272,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3b2d29ce823c35d4a974fcb41aefe5fb31378870724bafba22cd281678ed47a5"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3540fee74764e701514a3a1e56dbd4ca1026345983071fb84bb660b587363fe2"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "f34c76607aa91edd91e24dc84b45876cf7258ae5e88d7fe55b84696c5bdcf809",
"value": 2000000,
"index": 40,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "5443a9c673be2d0e4d797666919e0e925999ad8fc74e01fff7bc28db2098c299",
"outputIndex": 1,
"outputGlobalIndex": 50556277,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9c9296e482c81b9725e516c1d121e2281ac0570e0e65438666be972e91758e6b"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "ce40f8c5051a5d872bd9faccdd311cf08f1b6f3fe7a49b33c5079ff7c4101eb8"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "de35d0c5d1e8cc92041572621b4367044a9f69ef990ee3ab1604804a845a00b2",
"value": 2000000,
"index": 41,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "66b8145361823073f00567e728ae4909efc7cf16c47d36ea010d9f611d2767c8",
"outputIndex": 1,
"outputGlobalIndex": 50556282,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2097ccaa554d7918228e3ba22f0ae54c71c17ab70eab7087c994df6d9a3fe6f0b1",
"sigmaType": "Coll[SByte]",
"renderedValue": "97ccaa554d7918228e3ba22f0ae54c71c17ab70eab7087c994df6d9a3fe6f0b1"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20991c07300f42a2e2ca5df7d9df4683fa17cbb8d400a6466a36751f08c04cdf3d",
"sigmaType": "Coll[SByte]",
"renderedValue": "991c07300f42a2e2ca5df7d9df4683fa17cbb8d400a6466a36751f08c04cdf3d"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3540ac2410e94f00c9a1334dbe78dab0a717189c6104cd3e19bade6d61b2802d",
"value": 2000000,
"index": 42,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "8d26c678d5c5319f15066bda900bfd7426b9010bd84b9976983694eeccc763a2",
"outputIndex": 1,
"outputGlobalIndex": 50556287,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206015f62700f812c2c79249ad2bfa3f378ad443fdf925666cbd02fdad481ff0a7",
"sigmaType": "Coll[SByte]",
"renderedValue": "6015f62700f812c2c79249ad2bfa3f378ad443fdf925666cbd02fdad481ff0a7"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20598dd84048e5264b839940eaf06bfe7e227661cc994d177b158bcc1b16b1df5c",
"sigmaType": "Coll[SByte]",
"renderedValue": "598dd84048e5264b839940eaf06bfe7e227661cc994d177b158bcc1b16b1df5c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "050a6fc850d6e3f5b19500211a19d96f4e4be3ad1b613aa7fdc2a50b71c5fee9",
"value": 2000000,
"index": 43,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "8dcd62f7817a2c0f2f157dbc05b0c6f0c4d6657f420f7cfab0cb9447acbaa79e",
"outputIndex": 1,
"outputGlobalIndex": 50556292,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fb78ce4375e2fe9b6abaf87e82c35528e8857be5ccf5b02de56c51bf20132be7",
"sigmaType": "Coll[SByte]",
"renderedValue": "fb78ce4375e2fe9b6abaf87e82c35528e8857be5ccf5b02de56c51bf20132be7"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "5b482e4d2fb973f17de7dd4b6c7e30f37f02496003e29fa3d5eaafbf5a23a55c"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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}
},
{
"boxId": "3e7f4858d1ee05498a5e2812d996b61f67119b0007546066d39e16688a82b809",
"value": 2000000,
"index": 44,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "8f5ebfa5b07933b1cb11893816a0c6153caee6ed2855bc4b5ff4c90a52861bdc",
"outputIndex": 1,
"outputGlobalIndex": 50556297,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2077e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5",
"sigmaType": "Coll[SByte]",
"renderedValue": "77e9bd8086ce0a6f1af17d9c01e053d253c45d7f40179d47de2c0a26754d4cf5"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20fb41ddd9f190830d9bbcf2ee2ee08203c52c07891a9195e3ec46abceab870923",
"sigmaType": "Coll[SByte]",
"renderedValue": "fb41ddd9f190830d9bbcf2ee2ee08203c52c07891a9195e3ec46abceab870923"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "a8531c733fc39606aeb619595267d7b60e22bd63e32bed7df1d1bd24f0ca8de9",
"value": 2000000,
"index": 45,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "9748bd17df3c75ee4baafe8b0c758a00e05c67d7a7bc8a42a3cb58927d85a0b9",
"outputIndex": 1,
"outputGlobalIndex": 50556302,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20177d2ab87b520ce087a394ae20fcc6f221e24f747f664f6c30961288c951d05a",
"sigmaType": "Coll[SByte]",
"renderedValue": "177d2ab87b520ce087a394ae20fcc6f221e24f747f664f6c30961288c951d05a"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e20301dfc03c30c3e5d9310a175aa80650c66d08bf5224098e696b8547d18456967",
"sigmaType": "Coll[SByte]",
"renderedValue": "301dfc03c30c3e5d9310a175aa80650c66d08bf5224098e696b8547d18456967"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "0055e5ab360414f88cb51a8b6e6d382a4cd835b9acb7e846d4fa9db80aed66a0",
"value": 2000000,
"index": 46,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "9796be93e095dfdf23985c7c3c134f60b230173a5d19d95a4b6eba759297b052",
"outputIndex": 1,
"outputGlobalIndex": 50556307,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3aa7ed9864521180387dcc059e46225ada5116a86758bc2b958873bbd7d19366"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e204dc1fad4737744e4a08a963917e2a118e3a8cd06907d8cc8ca2bc0d57920e460",
"sigmaType": "Coll[SByte]",
"renderedValue": "4dc1fad4737744e4a08a963917e2a118e3a8cd06907d8cc8ca2bc0d57920e460"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "e1462937c7b2dc8b57a9d82aeef6bc3d6ce91e3f68a9d1900532c527d1026e64",
"value": 2000000,
"index": 47,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "b2f19077093caee3b207abd0d61d42008c79ae0533bd9f72f075e447e183bd7e",
"outputIndex": 1,
"outputGlobalIndex": 50556312,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200230bc2fa5d72266f12a375fe531aa712b74723ba29d4a118a9920871f77d53a",
"sigmaType": "Coll[SByte]",
"renderedValue": "0230bc2fa5d72266f12a375fe531aa712b74723ba29d4a118a9920871f77d53a"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e2090f8d0e9ded172c92fccd12697577d688bf15ee727a6f05dd24924960bf72e99",
"sigmaType": "Coll[SByte]",
"renderedValue": "90f8d0e9ded172c92fccd12697577d688bf15ee727a6f05dd24924960bf72e99"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "49afc6696d20ea6cdae3c1fd16dbfc0cc57bd002b4c1015484ae47ec04acef16",
"value": 2000000,
"index": 48,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "b36a5ae4dac4f57af492aa3e16bf4356e65111574c144aab80780ee838fbf431",
"outputIndex": 1,
"outputGlobalIndex": 50556317,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9d1b0896da6db5d3c981594c5514383acf6155eeec792393ed39d06acdccadc"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e205c650784726fb6f57049b3500d4d2df7d305cf48888fac90a24de73ea5eec2ad",
"sigmaType": "Coll[SByte]",
"renderedValue": "5c650784726fb6f57049b3500d4d2df7d305cf48888fac90a24de73ea5eec2ad"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "60d6cfce83235e5b97c6bd7a3ebf5a413e50140218350e401194aba45e1e189b",
"value": 2000000,
"index": 49,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "d614caedaf5997c04fccba769192be00477bdf649cef9ca2da803c303111ef33",
"outputIndex": 1,
"outputGlobalIndex": 50556322,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e2017b791083d0d4a3532c9e7d9c46a7e397418453cda398c8abafa18aee8a705a7",
"sigmaType": "Coll[SByte]",
"renderedValue": "17b791083d0d4a3532c9e7d9c46a7e397418453cda398c8abafa18aee8a705a7"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e205f17e744fbfeaad3597323c82cec026be4758b31e81efb19be5810061b870f3a",
"sigmaType": "Coll[SByte]",
"renderedValue": "5f17e744fbfeaad3597323c82cec026be4758b31e81efb19be5810061b870f3a"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "1bba90ec1f95c337a084fa3f0583ee5d71bef1e45da0ebb573ce956cddb29727",
"value": 2000000,
"index": 50,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "eb281384f356e7d618a6139397d4046418c5c1932a13c82da945fbc7ec09285f",
"outputIndex": 1,
"outputGlobalIndex": 50556327,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206688602460b5e65381f6d3bd60ebe459b5bdc6ec3c1d4824b37a6edba227f400",
"sigmaType": "Coll[SByte]",
"renderedValue": "6688602460b5e65381f6d3bd60ebe459b5bdc6ec3c1d4824b37a6edba227f400"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20f018d82a0e11b0b9f503ee6861df24e91d95d3be7c125311a8abc6dbeaa1848c",
"sigmaType": "Coll[SByte]",
"renderedValue": "f018d82a0e11b0b9f503ee6861df24e91d95d3be7c125311a8abc6dbeaa1848c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "23ca0a75910e68081ee36f0812d48e09d3c60c253f7c0d3e5c96ef3f951f43bc",
"value": 2000000,
"index": 51,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "eef64da44c7ebc392e5ed13cb57a8de6667e6af3e73fd1bb560a1fe7e1cad0b8",
"outputIndex": 1,
"outputGlobalIndex": 50556332,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e201cebf17e8687c5b8038094a1241961c54c65773e30c4970389ee39fa9dc956ea",
"sigmaType": "Coll[SByte]",
"renderedValue": "1cebf17e8687c5b8038094a1241961c54c65773e30c4970389ee39fa9dc956ea"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "e99bd92c85d8c46cf19834b71f11f01184c031ebeaa1e30819c126444deed8e5"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 52,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "fb474288211141bd8fda88c169e175b8ac3fe5309d49dd1f07c69a6c002a90d6",
"outputIndex": 1,
"outputGlobalIndex": 50556337,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32",
"sigmaType": "Coll[SByte]",
"renderedValue": "bd65e8b53aca76f238b88882a85d021401bc6467cb97ace7179d29c5b5323e32"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "cb349de3ccb91bc964911f3edf75d1ce7922774481359870d65566ffbcf8da5a"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "192f6a7086a7807e3e1adecfcbb88ec510423d167b99820421a07f593fccef21",
"value": 2000000,
"index": 53,
"spendingProof": null,
"outputBlockId": "691e7901f6c7f22a620a8ec359e57bc31e17394fa3dff83bf84227406189993e",
"outputTransactionId": "7aa8c9406cf05dff094f2fd3d83ef95cd74823c23bbe808cd714334e0cb84a88",
"outputIndex": 1,
"outputGlobalIndex": 50556342,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624232,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d114141aca72e56eab859e29d74690560ac900b38169c4fe21439ee824ddb9cb",
"sigmaType": "Coll[SByte]",
"renderedValue": "d114141aca72e56eab859e29d74690560ac900b38169c4fe21439ee824ddb9cb"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e205deff3053002d0746df948c914fdaf0448a0b9ca1750460b2a4f698eb89a86cf",
"sigmaType": "Coll[SByte]",
"renderedValue": "5deff3053002d0746df948c914fdaf0448a0b9ca1750460b2a4f698eb89a86cf"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "d4fcaeb9d51109c24ca0bb6361836c28bf94a4c98ce408e838cf9257b17af2e7",
"value": 2000000,
"index": 54,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "31eb06a4afe46739039b3bf03383f0086ce1700e7fb771bf10e976b986310322",
"outputIndex": 1,
"outputGlobalIndex": 50556350,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "329629a6d99dd6f1a0aba033848f0ca356394f1416a8bf7c49e85b5164b1b14f"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "49a02e6af25d98638f1eac7e823cf1525867e76746a2f1f5129ef43ea182e239"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "3e21ece1ebf45879bebcac05389c9071238e78d1c38d57a386bb8a46f260f79f",
"value": 2000000,
"index": 55,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "04fd2bc238420d8248e8cf82a59174c9c039492dca73a933422efe293c8ed37c",
"outputIndex": 1,
"outputGlobalIndex": 50556355,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "87f5a101be45cefe086c96a68c92c8901806c3169c430dea014b640aabb0eac9"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c3dc83a697fda7f4a4a17af0de8d8f61efabee15802726700d28f047ee05ff5c"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "3f0fe73deb3388a324caffb1f6c0c0deedd2ea3794eb6298eeea8991ec2224b9",
"value": 2000000,
"index": 56,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "0af981157e3e87441067cd3ee908b3443fccb1881d6c29728d053bea596bab86",
"outputIndex": 1,
"outputGlobalIndex": 50556360,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2093d73a59f111c37a6e9853fb85ba075264f330dc3b416d2778b7939e3bb6591e",
"sigmaType": "Coll[SByte]",
"renderedValue": "93d73a59f111c37a6e9853fb85ba075264f330dc3b416d2778b7939e3bb6591e"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e202cdc74ee1f3d159bbe6d036300ce40f79846134ebf861fd4e97e178fd523e94c",
"sigmaType": "Coll[SByte]",
"renderedValue": "2cdc74ee1f3d159bbe6d036300ce40f79846134ebf861fd4e97e178fd523e94c"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "e0d0e1b678951fc37731335492bfdcf21bcd1504d3b00cc910c5d99464c1c09e",
"value": 2000000,
"index": 57,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "0bc341d6fb2985d838ed68fac9c0e9ef7199af1160d6e8f06c757a325b2d9061",
"outputIndex": 1,
"outputGlobalIndex": 50556365,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624233,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c652bb3c7ca4d20cc6f02a0aa5f06bdf9194925c99c867b0fe928151ecee0806"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "8c3a6c322dd99cff61f18927c8b354ec1d860f25e435220c8ddaeeee88798b75"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 58,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "1f546651333a27deb50814f6a451808dc596b06aeaec730d6d1ed982c0924bf1",
"outputIndex": 1,
"outputGlobalIndex": 50556370,
"outputCreatedAt": 1624231,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "94dae57d9bf0d20e561362750c29f17d6b298544b16614a8962be541e2061865"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"sigmaType": "Coll[SByte]",
"renderedValue": "005ad2b8b82871702cae89783c2830c69510b2264ae5ea6391ffb75aa1c73245"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "10a71618d56f8ba446836cbddd63893ff85e6aba92259663fb5e2e7cedd0e96a",
"value": 2000000,
"index": 59,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "2aebac73c3a4c5bc521b6281d7bc053908efad486cb078fe381ddfa00d8d3ec9",
"outputIndex": 1,
"outputGlobalIndex": 50556375,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20dada336c4564a1906c2b55a813173917df580aee389e714f08ef49fd181129b5",
"sigmaType": "Coll[SByte]",
"renderedValue": "dada336c4564a1906c2b55a813173917df580aee389e714f08ef49fd181129b5"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20625a06592bdc726d16daa1d09e8bb0b4cc541fb5c39a311bbc094a96b64fa25f",
"sigmaType": "Coll[SByte]",
"renderedValue": "625a06592bdc726d16daa1d09e8bb0b4cc541fb5c39a311bbc094a96b64fa25f"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "50555cd87f2083297707336d12d9bdf05c182617588092cfda57d7faeecd0cf1",
"value": 2000000,
"index": 60,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "4b73feafd577d398f3e5f6b00bf49df85565174c374f57cf4a40323941061ad8",
"outputIndex": 1,
"outputGlobalIndex": 50556380,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "309befbcdc22b7c549e1802f4a8e6036a64873a5c70395419f96cbd4b3b95ef5"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20b2fc99280eba415b44f3500d1c56d6ee6c4fad82cdd253727debb1e5c3196037",
"sigmaType": "Coll[SByte]",
"renderedValue": "b2fc99280eba415b44f3500d1c56d6ee6c4fad82cdd253727debb1e5c3196037"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 61,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "6358c3c322b14471044329c5edc3b4309adc7436493228e31d34ac597cdd88e6",
"outputIndex": 1,
"outputGlobalIndex": 50556385,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20ad24d3cb8c3161b97c75ab50883ca635368020088376b7a03e654a4673ff95e8",
"sigmaType": "Coll[SByte]",
"renderedValue": "ad24d3cb8c3161b97c75ab50883ca635368020088376b7a03e654a4673ff95e8"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "e58d5698c632d3e50a725255f594372eb8e484e2fa99845538399a349af0b2f4"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "681a1a35f5ac5b46540f951a4752813ab4fa80d21e68a83ace2b111236b250f6",
"value": 2000000,
"index": 62,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "780f36862bacb058ebd2f3502af59ac6705c1cad5bfe178a393d3985bd9e204e",
"outputIndex": 1,
"outputGlobalIndex": 50556390,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207381c9f36069e7048067d5ad4c25f6161c1969edd804fb76ac9805b626fca188",
"sigmaType": "Coll[SByte]",
"renderedValue": "7381c9f36069e7048067d5ad4c25f6161c1969edd804fb76ac9805b626fca188"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e203429c05cd607c011f71a5ed1184e4fbb758a1d94dfe50afffe4a844abaf5f812",
"sigmaType": "Coll[SByte]",
"renderedValue": "3429c05cd607c011f71a5ed1184e4fbb758a1d94dfe50afffe4a844abaf5f812"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "6b71dd3fa1f4e0582801a12c6f32f2cc320e7f343f53d7af3aa3cb7e89eeee42",
"value": 2000000,
"index": 63,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "9c217ff9116fdbc32ef7942d681f1949594968f5307b314f01a6430892066af7",
"outputIndex": 1,
"outputGlobalIndex": 50556395,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "fd143679ed97043e6728236f766050ebc56195273eabadd67eb5df2ae77757ee"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "3d1bf0067d82255798bde97f1787aeb24514acbb01c808a6109fc38e0c8159a2"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "4538098d69059b306e9c2f7d1d42d92b58de3ea877feba8790ace770b54fb95d",
"value": 2000000,
"index": 64,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "a986270e827f443bb5d3f85579c1249823cc1f4715c31d4fe301db8ceac26270",
"outputIndex": 1,
"outputGlobalIndex": 50556400,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "bf604d00656a110d0af06d25c0103af1f472f7eec6b664812cf29dbaab04e095"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "04d79928bba5fba09699b0d7f947ca5e5c4f6433b47762fc38bcd18c4674e922"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "727e2c0921d471708c4590a62d9e28269256895e51493e87d3163a5d0a7c6830",
"value": 2000000,
"index": 65,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "ea1d1ed1069d30ad03619d617bfebfbd24bf0c7eb1cc674f462932a1bc477ca6",
"outputIndex": 1,
"outputGlobalIndex": 50556405,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d1209681c63b24a4169589a7a9460a0adcc72ccd81bfe3b06f2198fec7b7a97"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20fed014108373c95b19a8aa19ea95c537df71ac0bf0c1ef23a1ec0cae845e4658",
"sigmaType": "Coll[SByte]",
"renderedValue": "fed014108373c95b19a8aa19ea95c537df71ac0bf0c1ef23a1ec0cae845e4658"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "265c8334d933537adec4c721e8ed94ec7fc0afddcd53c4b81c4254250ab3f6da",
"value": 2000000,
"index": 66,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "f6a930c6a4c5f0f238ba711c44891e84e3fe10a5b745d3ed107eb5523afbf807",
"outputIndex": 1,
"outputGlobalIndex": 50556410,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624233,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "bfc372a6d2ac00cc08dbe822ee10e55a15ac224b15255f6fd884a488ed515220"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "a9a83653ca5e3efaa2f4b73cd2591397e4165ffdf5e2bd7f6d55d98a78b3fd89"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "c0cd90ee1502a825b07954ee5fc504a81277f30c6aaaaa182c2b174dfe4886ae",
"value": 2000000,
"index": 67,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "2960322c8d99c33a0fea4d475c4f0ff5939744c6e2720c440db40647e9f335bd",
"outputIndex": 1,
"outputGlobalIndex": 50556415,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "fe93b88cc5fe9d945f31341803b9f739284b497165296efe23b50745cb787dd7"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "e3ca9e89b026b5f9e6a31939a86d62732f6c7f8fb5ab894d7afb487fcc0ee845"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "26535888480c78a0f96c96ccac178fdd2c697e01000254bda18651dd96e4e268",
"value": 2000000,
"index": 68,
"spendingProof": null,
"outputBlockId": "3a21105b1303c790e4119f3ec7ba93af5106534dfce17da8f2abf18d0c6e39c8",
"outputTransactionId": "b573d809aeee1699f5908b6208a98e50dab7b6bf8e0d1b37d6e671ce87212a18",
"outputIndex": 1,
"outputGlobalIndex": 50556420,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624233,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2019b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29",
"sigmaType": "Coll[SByte]",
"renderedValue": "19b9ce427e082d0ec1077a19db29ee8af2afadfa46e96d28d5d3e7ac56df7c29"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e2063ca017784c6d0fb97efe32a81ad9aa58e6f73d623d55238ff463db29978c2a0",
"sigmaType": "Coll[SByte]",
"renderedValue": "63ca017784c6d0fb97efe32a81ad9aa58e6f73d623d55238ff463db29978c2a0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "3e00fcfdc1ee6e8d1471bb04c7b50cb4c36486ece44ec7219c216b2745176b80",
"value": 2000000,
"index": 69,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "953cd25e314ea81ead620588933dae24a56a2e4426f914f0ede5a142d585d695",
"outputIndex": 1,
"outputGlobalIndex": 50556466,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20efd806919b55c5d5d9102b647af0fd2484cbd064c193da9cbe9cef75eb83dfe9",
"sigmaType": "Coll[SByte]",
"renderedValue": "efd806919b55c5d5d9102b647af0fd2484cbd064c193da9cbe9cef75eb83dfe9"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20f3088ebfd3a8df4a1fcb2fc8469dbbf2220db0f1ab3d3671c33bb49146605a5d",
"sigmaType": "Coll[SByte]",
"renderedValue": "f3088ebfd3a8df4a1fcb2fc8469dbbf2220db0f1ab3d3671c33bb49146605a5d"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "b12dfb65401978adaf39f784b73a24021a098c857a9a2274b018bf502b9c6981",
"value": 2000000,
"index": 70,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "9ea842cdb89380f6a42904ed6f527b0e0146cf54c67dbbc91bf5b272e9de5a11",
"outputIndex": 1,
"outputGlobalIndex": 50556471,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691",
"sigmaType": "Coll[SByte]",
"renderedValue": "916444e3aa3cbc0f76a394fb7596c5a5799ea78cfab775a158a5f436dbe03691"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20f9c0883f81bd02f9008b874c75ae283076f22e1f861c9df9d243285137e7866d",
"sigmaType": "Coll[SByte]",
"renderedValue": "f9c0883f81bd02f9008b874c75ae283076f22e1f861c9df9d243285137e7866d"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "b8f98c4f79a8b7499146f811ce865ecf9cb2a21ced41dfeab0ae44f444bdc8cc",
"value": 2000000,
"index": 71,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "b22ab25950434f70a386e86be7a6804e0c21403c05aea06383024cff63bddc20",
"outputIndex": 1,
"outputGlobalIndex": 50556476,
"outputCreatedAt": 1624231,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207fdb6e568e0adf674fa20a687c4e9147905bb6ad6f63c3777ccd227b6201e84b",
"sigmaType": "Coll[SByte]",
"renderedValue": "7fdb6e568e0adf674fa20a687c4e9147905bb6ad6f63c3777ccd227b6201e84b"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20f7765c4f87e1f5b3363d2c849be994174ef5c8b5222fdfb2b41747c945ac11d7",
"sigmaType": "Coll[SByte]",
"renderedValue": "f7765c4f87e1f5b3363d2c849be994174ef5c8b5222fdfb2b41747c945ac11d7"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2158ed7615b8221ea63ef41b69c44125faddf4158052d59a5ffb60922c27a055",
"value": 2000000,
"index": 72,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "13a58a4d89eba28d551ac23fa13646713b7491533ad1093bcb50d82d732902df",
"outputIndex": 1,
"outputGlobalIndex": 50556481,
"outputCreatedAt": 1624231,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e205b94fd2a70cac5a896f832d8a41020f80b8a2e3c400f49da364b759afd4f8ec1",
"sigmaType": "Coll[SByte]",
"renderedValue": "5b94fd2a70cac5a896f832d8a41020f80b8a2e3c400f49da364b759afd4f8ec1"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e204974b790f334757ef2cca0b5e14124b79381045726ea57a181fd422984bd7eaf",
"sigmaType": "Coll[SByte]",
"renderedValue": "4974b790f334757ef2cca0b5e14124b79381045726ea57a181fd422984bd7eaf"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "0ba81b78859d92b27da3685883fc07c7d5cb61571786937bbf589633482cca0a",
"value": 2000000,
"index": 73,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "2f198c250c910c593841c7b898e331c1e180d61df6adc29051ac2b6b6e6dd321",
"outputIndex": 1,
"outputGlobalIndex": 50556486,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e204e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916",
"sigmaType": "Coll[SByte]",
"renderedValue": "4e6060b5ef0c87bb71f0f57f7967da51ffbe7fe4fa3f40c3a3ce3e89fe7f7916"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6da628de705774510ec4105771adda2ca59960734c989e04e1a2f33516d1585f"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
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},
{
"boxId": "8a9099c67a4e0ebe845e3f350dee688eb9363ec58a64bc84f3fb1c5bb975891f",
"value": 2000000,
"index": 74,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "2faa551d8d13b66887954bc96f19fefc9c69c3b077992320666482ee286c4702",
"outputIndex": 1,
"outputGlobalIndex": 50556491,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2093d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9",
"sigmaType": "Coll[SByte]",
"renderedValue": "93d22cfec531423b8d7059ad6b0eacc4bcf10b2f852adbb94726bfd69e1adea9"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e2095f34318db05c60f72f96972c3794b1b130fd2c0724932bd355df7950f802189",
"sigmaType": "Coll[SByte]",
"renderedValue": "95f34318db05c60f72f96972c3794b1b130fd2c0724932bd355df7950f802189"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "fe9a64d71132e6189acb051907dd4acd7cdab599a940fc2bc2d93fb531db8d7b",
"value": 2000000,
"index": 75,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "48b42209c14d2db34be9d26094c4fb41c27dfedea9f6a011d6087217681dbf02",
"outputIndex": 1,
"outputGlobalIndex": 50556496,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308",
"sigmaType": "Coll[SByte]",
"renderedValue": "f09d0ef1a70f975be6fd96e4d8734b450d9c3b8aed185bdddc44784106970308"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e209b8882ff1326d6e543f2e53ef5514da6e1bac3b6ea70f3d2aa2de6bcf0f0c7ba",
"sigmaType": "Coll[SByte]",
"renderedValue": "9b8882ff1326d6e543f2e53ef5514da6e1bac3b6ea70f3d2aa2de6bcf0f0c7ba"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "befafe261af088525dc7da05fb0dc181ab3d5b32bff8bf80eb5a914701ac241c",
"value": 2000000,
"index": 76,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "4dcf09ea90ee76db2fa35b426904a985a48bb542c20aa4cdb5ef9a69f99113c9",
"outputIndex": 1,
"outputGlobalIndex": 50556501,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"serializedValue": "0e20ce985a97d78a34e8782801ca5cd997ccc63db2cdbfacda500f9f27f40efad3d5",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce985a97d78a34e8782801ca5cd997ccc63db2cdbfacda500f9f27f40efad3d5"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
"serializedValue": "0e20b06657e81f5550bcd64f346611c8c4e00fc6659c8b273e7db848da47c0e3439d",
"sigmaType": "Coll[SByte]",
"renderedValue": "b06657e81f5550bcd64f346611c8c4e00fc6659c8b273e7db848da47c0e3439d"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "3993fd57d4a2d31a579df3261ebf621a2628a2c3fd9690a0a3f6b8a1496f3801",
"value": 2000000,
"index": 77,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "627dee36f4f27045d12c44b417b280433bee870c376350e7f1c4a3c1c69171ce",
"outputIndex": 1,
"outputGlobalIndex": 50556506,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c2fa6283d1be597ef8ab3db6dfdf0111f56dce82303d094759fa58513955144d",
"sigmaType": "Coll[SByte]",
"renderedValue": "c2fa6283d1be597ef8ab3db6dfdf0111f56dce82303d094759fa58513955144d"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e203c87585603cbebe3dd4b6c8f3b8aeb0b13cfb1696f7b1549538347b085ad27a0",
"sigmaType": "Coll[SByte]",
"renderedValue": "3c87585603cbebe3dd4b6c8f3b8aeb0b13cfb1696f7b1549538347b085ad27a0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "2eb251fc4a3c27b9b66f37f6aa85038ffac17ad86a38b4b61b60f090ceb93daa",
"value": 2000000,
"index": 78,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "6d40d4f92e4a421d385cecf955bebe91ff3b1bedfd7e503ae2fa50fd2b984df4",
"outputIndex": 1,
"outputGlobalIndex": 50556511,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08",
"sigmaType": "Coll[SByte]",
"renderedValue": "3ef7e012d13731e902ebf19784d1ae3f8ee4cf35d3e2e078215ef3da5a806e08"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20233e1a3002d149f57943f50ea212147342e74e881e13c4413da970377d5ed151",
"sigmaType": "Coll[SByte]",
"renderedValue": "233e1a3002d149f57943f50ea212147342e74e881e13c4413da970377d5ed151"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
"boxId": "dd471f06f6b92fb7a52234ccbe2d0e9dc8256f8f2b1783721eac1ea66cc72c1e",
"value": 2000000,
"index": 79,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "6f165dd3c5591cb7a46be49419fd521a01c782d41c1657baf741092e736e23b0",
"outputIndex": 1,
"outputGlobalIndex": 50556516,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858",
"sigmaType": "Coll[SByte]",
"renderedValue": "327cd19bdc7934e00a67eca4f126b5246416f5d966b94af6c5eb2980e866d858"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e207820d0ba4177a67e7db65c6105d382f117c8989e31144847777ac31f51f67d38",
"sigmaType": "Coll[SByte]",
"renderedValue": "7820d0ba4177a67e7db65c6105d382f117c8989e31144847777ac31f51f67d38"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "9be418f5ec104352f861b2a6d575a7ab79e3277549e2e05c0ca0c2dbf8a9572e",
"value": 2000000,
"index": 80,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "788048af21505630c40cd8c88a1a113cb4e0420087ac75211fef69e0b913c179",
"outputIndex": 1,
"outputGlobalIndex": 50556521,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "5ivrmzxYZTDDDoKD1urVYrXZG96ijTUYXQJzE6SCRJ2RR6Kj1UPWL1iN1xeHgYJEQjnQ7m3Ld9tBRRYqjzrAVAqHyGbZB3otUWZW4sUxN4E11fNUZEMQ3kVwnZxFmeSaxcXhQiTFH1cvBYWuFMRRFfaA2UMfpEgm2WoqeiJxPCojp9D7h6yMV4br5EtWTQJKRtcopBRoUgDg9mrKPAXGPZZKTZbYotgLKQ4nzD8QB5hjYJswhLmePaY3zK5eJq7NTcdoAgbNPK9nQ9UpBUgrc8RB76P8evPHMXg6HrVdQ2z3rkvYFVZqH9SmCkE8KGiLYGX7hwaXYGvPExdoVDp7qsSctsPjwgt9Vts2G76dzJzfBhEunJ33vdTEkEXX3wkjK4ZE8g5YKCwGpcED5PhtRQQtJZaZMYTZV3TpbPWy57U49cD3HVeUGR7efxUHZxYybWJ7q8i6NDm3PUwKFN63HmPYQn7TMYGkvSoizTuTAUJomiKgSnvoz2DSUzukRSRmUFA1cLqdR6s7FbeJfpbaKWX4kUGM2Xh38FdqNE94SjkQMY9bv3H5N8MgwGL2La12e1GXAdMCKJCWKRe27vjdaHJWmsKrBLuXQegGN8BaqNuvJbhrmreHAjR9tVwVkxcTUsr8u8TGUzkzN7coV8HiQV9KBMVgQ24NXPYyoCuedwfCiNwYX7PSSbvve7Dgyy5e1S6qbVpEpVtjy9NzWfRaqr5CyGDqhkfjizNG71NZu543vkacjXrrfPWqtNoXMtTRyM1pzwW9ze9aoRX6e92mVaCUB8hTnfH3Q8EstRLDJygLmp63y45tKwBVBDjog7Z6pWhTfBapMBz8Q28pMfPAR8ywfz8qvtkyQcv9SuEZWfvpZREaS5PGhBuqU79eR9bwNwS6TLu9BZV5Y1ahVFA1fMUxhXTvX69hKnNHFgZ35fZdrVrSeU4U5yGvYX7ViTqL2oFk16HLoTXgNs6KQz7PPZr373gDeRh7PfXpX5jWyxw6SRreE3jB5SUiQnZxmAbpJNVkPzFbZXcrsrS3JHSfiVeqp1tk5uNaZcX39tQTXtu4bGrpv6EiMvYPkiDhCiKd5oAVeZ8VxEGN7SP94vF9WhS2oWUMCVLU1XW2DDHejZ36Zo1Ho8fHbUEaKNbRBozY3HYnkYyJuF4wer8xJ6q4KcPppDrS5jqfAaZF6YWsdtqgse7qMeWVUPj23Vr5XG2S9sYmWA7femKuZki71S6BqZGNfit7F4vrzqNZd1L5oyLSVCtuiv3DybRnu2YEaUtrmCphsmrpAFSEwJWtFKqcC",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c",
"sigmaType": "Coll[SByte]",
"renderedValue": "b5f4a5dd3d93cb51db4fe6d647d44054d97a06108f058a9907561a65957feb9c"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20b40728a28e82ef49c99b68923b4b4e532b4dd629ac24ed76c2d8686d9b3f4f2f",
"sigmaType": "Coll[SByte]",
"renderedValue": "b40728a28e82ef49c99b68923b4b4e532b4dd629ac24ed76c2d8686d9b3f4f2f"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "bba7d10d2fb661356c31e3abcc1df54f6dcf38c1e41642943adc936e182086c7",
"value": 2000000,
"index": 81,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "8ffe21beb619ff939f55943d82ee4f6683d228b569960a7e863ff9ccd0e9e3a8",
"outputIndex": 1,
"outputGlobalIndex": 50556526,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "99eaac5fcdb8ff2a9b4503b43964a5cb81471aae52242facbfef1f87b11457c0"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7cc4d5734960dd35a7e15d22d54d05754c5ca32d6e4143d169ff13f1b0523a06"
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"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 82,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "9f38c06909ba23fd76ac6e0b4a0b4b73a6506735bd78aabfe9d7d245fbaefea3",
"outputIndex": 1,
"outputGlobalIndex": 50556531,
"outputCreatedAt": 1624231,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"sigmaType": "Coll[SByte]",
"renderedValue": "6e72f74b1fe2a9417e822b3c32b8fb69a9a4e40c84e5dd5f21fa6e25b64025c4"
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 83,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "a1249bdb907edcd0f5db2303ad6f1252dc0bcff6bd05870a9cfddfba6b5be334",
"outputIndex": 1,
"outputGlobalIndex": 50556536,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2038813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e",
"sigmaType": "Coll[SByte]",
"renderedValue": "38813672b3e4ea3dd9e1592542d0997d2b56abeb47acadcfc09d3aa8d62a496e"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20073db48d109b0b9f9584d70a974ee4f276a3a06f33f0a25fadb9bf658cd0ccb0",
"sigmaType": "Coll[SByte]",
"renderedValue": "073db48d109b0b9f9584d70a974ee4f276a3a06f33f0a25fadb9bf658cd0ccb0"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "293f2e2c66ad2db5625a071ff6547968611f737a52693b8e47c5981b224f3bce",
"value": 2000000,
"index": 84,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "bdd7f7dd4bf8cb39edcd9af5474f755d7bfeb41767eadbf2a071445f926365a3",
"outputIndex": 1,
"outputGlobalIndex": 50556541,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "7c85fde0d6f95c49aeec5ac1117386c2b89717de5cdf20e82e86fe784e352cd2"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "cca03c47f5e7d0dbd4b6cc0172fd2eb4e3599a15b3fef7ca12f27d07f67b4a3b"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
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"value": 2000000,
"index": 85,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "d1a0b133b3c97edbe91087a26b8314276cdcc7da491aa1d2e8564707d4c161bd",
"outputIndex": 1,
"outputGlobalIndex": 50556546,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "102404000e200c67461b5771fac3fc417b9d7464ad2b9a374e4eac5a4c5eb149e50fcbe8288d040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e20c8dea5bd396984a17fc0aefafb11c46188a9a980caf2af12f7c893508db93a5b04000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "1f2544ae82ab043f2889c81ac9db7ab9d74bb4af631631b5ef2200879ee7fdb3"
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"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"sigmaType": "Coll[SByte]",
"renderedValue": "c79c94775c7c396e3508ad7e07b41266b20fd6ec5312731228875249ce638b91"
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"R7": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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},
{
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"value": 2000000,
"index": 86,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "d42e9494b49b9f6c39eeca4bc7e4eb34c6c596cd0f62d71bd03a8e5e48924a50",
"outputIndex": 1,
"outputGlobalIndex": 50556551,
"outputCreatedAt": 1624230,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2069cecf842b211bee823665b779bd0a4b93add45787e36d936bcdb7a7f7bbff2a",
"sigmaType": "Coll[SByte]",
"renderedValue": "69cecf842b211bee823665b779bd0a4b93add45787e36d936bcdb7a7f7bbff2a"
},
"R5": {
"serializedValue": "0e20add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e",
"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
},
"R6": {
"serializedValue": "0e20ea3bc9f4e4c1224e0df9b6b083fbd8ccee51238ed429beb6fc07108ff7801563",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea3bc9f4e4c1224e0df9b6b083fbd8ccee51238ed429beb6fc07108ff7801563"
},
"R7": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
}
}
},
{
"boxId": "45c39d915750f250b2d9ecc59431f4aea14a6a00998c58e82f82fc377386b9b4",
"value": 2000000,
"index": 87,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "fd9c3eb15840a356606d14adfaa057a23f573e48fefa4408bfbb4a8352abfeec",
"outputIndex": 1,
"outputGlobalIndex": 50556556,
"outputCreatedAt": 1624231,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "9d57b0fed60a6f7c06e57cdf6c8fe88f5df4f44dbd41d5f43ed4b971aa13c017"
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"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "c7feefb1e70e179a0cf86787cdcd447d9b59c18b85617bf34b08e0ffcd4b33d8"
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"R7": {
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"sigmaType": "Coll[SByte]",
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{
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"value": 2000000,
"index": 88,
"spendingProof": null,
"outputBlockId": "87d594488394669070fdbe490818a47c2d18da7d1893aba134dcfb62e63348cb",
"outputTransactionId": "2d76c05c0683540c7f3e9393a214bd6e61d29298c283239e9f9b0da1277c4e59",
"outputIndex": 1,
"outputGlobalIndex": 50556561,
"outputCreatedAt": 1624229,
"outputSettledAt": 1624234,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(12,103,70,27,87,113,-6,-61,-4,65,123,-99,116,100,-83,43,-102,55,78,78,-84,90,76,94,-79,73,-27,15,-53,-24,40,-115)\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 1\n13: 0\n14: 1\n15: 0\n16: 0\n17: 0\n18: 3\n19: 2\n20: 1\n21: 100\n22: 0\n23: 0\n24: 0\n25: Coll(-56,-34,-91,-67,57,105,-124,-95,127,-64,-82,-6,-5,17,-60,97,-120,-87,-87,-128,-54,-14,-81,18,-9,-56,-109,80,-115,-71,58,91)\n26: 0\n27: Coll(-20,-89,119,111,93,-19,-39,-17,35,-127,6,-31,81,-16,-22,-8,-79,-93,8,25,10,46,-27,-106,82,-20,-21,40,6,-116,118,96)\n28: 1\n29: 1\n30: 0\n31: 0\n32: 0\n33: 0\n34: 1\n35: 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[Byte]].get\n val box5 = if (bool3) { box1 } else { OUTPUTS(placeholder[Int](2)) }\n val coll6 = box5.R5[Coll[Coll[Byte]]].get\n val coll7 = Coll[Byte]()\n val coll8 = coll6.fold(coll7, {(tuple8: (Coll[Byte], Coll[Byte])) => tuple8._1.append(tuple8._2) })\n val box9 = OUTPUTS(placeholder[Int](3))\n if (bool3) {(\n val box10 = OUTPUTS.filter({(box10: Box) =>\n val opt12 = box10.R4[Coll[Byte]]\n opt12.isDefined && (opt12.get == coll4)\n })(placeholder[Int](4))\n val tuple11 = box10.tokens(placeholder[Int](5))\n val tuple12 = SELF.tokens(placeholder[Int](6))\n val coll13 = tuple12._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n blake2b256(box10.propositionBytes) == SELF.R7[Coll[Byte]].get, tuple11._1 == coll13, tuple11._2 == tuple12._2, !OUTPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (coll16.size > placeholder[Int](7)) && (coll16(placeholder[Int](8))._1 == coll13)\n }).slice(placeholder[Int](9), box5.R7[Int].get).map({(box14: Box) => box14.R4[Coll[Byte]].get }).exists(\n {(coll14: Coll[Byte]) => coll4 == coll14 }\n ), INPUTS.filter({(box14: Box) =>\n val coll16 = box14.tokens\n (((coll16.size > placeholder[Int](10)) && (coll16(placeholder[Int](11))._1 == coll13)) && (box14.propositionBytes == SELF.propositionBytes)) && (box14.R4[Coll[Byte]].get == coll4)\n }).size == placeholder[Int](12), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get\n )\n )\n )\n )} else {(\n val coll10 = blake2b256(box9.propositionBytes)\n if (coll10 == coll2) {(\n val coll11 = CONTEXT.dataInputs\n val box12 = coll11(placeholder[Int](13))\n val box13 = coll11(placeholder[Int](14))\n val coll14 = box13.tokens\n val tuple15 = SELF.tokens(placeholder[Int](15))\n val coll16 = tuple15._1\n val coll17 = INPUTS.filter(\n {(box17: Box) =>\n ((SELF.propositionBytes == box17.propositionBytes) && (box17.tokens.size > placeholder[Int](16))) && (box17.tokens(placeholder[Int](17))._1 == coll16)\n }\n )\n val i18 = coll17.size\n val l19 = i18.toLong\n val coll20 = box12.R4[Coll[Long]].get\n val l21 = coll20(placeholder[Int](18))\n val l22 = coll20(placeholder[Int](19)) + coll20(placeholder[Int](20)) * box13.R5[Long].get / placeholder[Long](21)\n val l23 = coll20(placeholder[Int](22))\n val tuple24 = box5.tokens(placeholder[Int](23))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box12.tokens(placeholder[Int](24))._1 == placeholder[Coll[Byte]](25), coll14(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), coll14(\n placeholder[Int](28)\n )._1 == coll16, coll17.filter({(box25: Box) => box25.R4[Coll[Byte]].get == coll4 }).size == placeholder[Int](29), box5.value >= coll17.map(\n {(box25: Box) => box25.value }\n ).fold(placeholder[Long](30), {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }), box5.R6[Coll[Byte]].get == SELF.R7[Coll[Byte]].get, box5.R7[\n Int\n ].get == i18, box5.R4[Coll[Byte]].get == blake2b256(\n coll17.map({(box25: Box) => box25.R4[Coll[Byte]].get }).fold(coll7, {(tuple25: (Coll[Byte], Coll[Byte])) => tuple25._1.append(tuple25._2) })\n ), blake2b256(coll8.append(coll4)) == SELF.R6[Coll[Byte]].get, SELF.R5[Coll[Byte]].get == blake2b256(\n coll6(placeholder[Int](31))\n ), l19 > if (l21 < l22) { l21 } else { l22 }, tuple15._2 == l23, tuple24._2 == l23 * l19, tuple24._1 == coll16\n )\n )\n )\n )} else {(\n val tuple11 = box9.tokens(placeholder[Int](32))\n val tuple12 = SELF.tokens(placeholder[Int](33))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.id == box1.id, tuple11._1 == tuple12._1, tuple11._2 == tuple12._2, box9.R4[Coll[Byte]].get == coll4, OUTPUTS(placeholder[Int](34)).tokens(\n placeholder[Int](35)\n )._1 == coll4, coll10 == SELF.R7[Coll[Byte]].get\n )\n )\n )\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 3000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
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"sigmaType": "Coll[SByte]",
"renderedValue": "add68ed0bd2cf3d877ebc935db518e4ec47d8f709d24dd187364a45ba8f8194e"
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"sigmaType": "Coll[SByte]",
"renderedValue": "0c3e8fb44c458bbc046f8d945ba3a98e0e90a63caf11f9488b6b5e12d8ae8c8a"
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"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
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{
"boxId": "4d97bf356b8f1768608198f5447d5f3b1e6b24fc2eda22c95067b7720a4b0125",
"value": 4104886456,
"index": 89,
"spendingProof": "3027d38ce3f412553d33e34317ec4b22cd866e6077c5b2b5b8169f978ced7a433d28eb07138ef961a88bc6af4a171dd036722ef90b0cc03a",
"outputBlockId": "fbde82b1d6c4524da33282509a5bd668d16ddc96112306870ede527261244a46",
"outputTransactionId": "3cc0f511ca3fb7dd94d5a692d4bbbf3c30f717c822b3e4f3f5bb6f5bd4319a46",
"outputIndex": 2,
"outputGlobalIndex": 50556038,
"outputCreatedAt": 1624227,
"outputSettledAt": 1624229,
"ergoTree": "0008cd03f9c83a107c742c552ee3f589313e59a65c8207cfb0a9ee19ef28103fb9a73363",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(f9c83a,6b0d0a,...)))}",
"address": "9iMp3KhUHRHEf4wQSxuN4bt3jvFytSgM31jGwLT2Cx7ju9dhNkW",
"assets": [
{
"tokenId": "a841b23663f1548f4489e46978c6ee3ee6df43af85c2d907923b908e423b508d",
"index": 0,
"amount": 1,
"name": "WID-b508d-u9dhNkW",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "a0f81c737b38ec451dc072369bc74609896b3bd245762140f44edbd5a934f90d",
"value": 1100000,
"index": 0,
"outputBlockId": "9cd9da9a7bebc91af8af522b342397f6f0cb88719817b60aa0cb53a9758daccf",
"outputTransactionId": "a0029995fad90f6b31ac46d0ad4e823a8349c16a413f885c829c74a840107a3b",
"outputIndex": 1,
"ergoTree": "100604000400040004000e2055bf993b4376ba132264d084f06fe033321ab43c68db1435a0e7e0bf77ddb7350402d803d601b2db6501fe730000d602b2db6308b2a5730100730200d603b2db6308a7730300ea02d196830301aedb63087201d901044d0e938c7204017304938c7202018c720301938c7202028c72030298b2e4c672010510730500ade4c67201041ad901040ecdee7204",
"address": "prufxZid3SJMyUVhAPFAF4uLyCZbEMWCMXRSyuMEvDUHZf81JcGcmu1EW1U9hUuJerWer5vmjhiJMmjbCqDwPMKRy169SPaLTxDp5tZ2rCrKjiv7xVAsnmphxSNBpj6qqB8fs1rWJGn9dN7t74qvx6oVHZny8KNMrqfEDjcWRv7wP21sZFP4rie4YhWJs8Z6swQ3DA28B5bzMZkMqfR7",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1106809bee027802c8018080babbc82e808ece1c",
"sigmaType": "Coll[SLong]",
"renderedValue": "[3000000,60,1,100,800000000000,30000000]"
}
}
},
{
"boxId": "9f538901a1dd44ec5e7880dedee5a282a9d4365390dfbe8e75c70bda31fb5758",
"value": 2000000,
"index": 1,
"outputBlockId": "ae81410da938661abd134b7a86c8a9149ef34622d32471558020cf05c737e899",
"outputTransactionId": "34f5394be6fb35d210ab2ca73a4ea3fcc15113fa6bc66473f413a36f78cd978a",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e046572676f",
"sigmaType": "Coll[SByte]",
"renderedValue": "6572676f"
},
"R5": {
"serializedValue": "05f401",
"sigmaType": "SLong",
"renderedValue": "122"
}
}
}
],
"outputs": [
{
"boxId": "3edafcf9f05cd066ffcec9b2f8812f1db254a77c33501d61245bc2390c97e85c",
"transactionId": "cf85eefd2f9c371961a6b2214ef656d85f081fbaa160bf3d07b4816f58370a87",
"blockId": "5e6944504e9e4dcdd339d222cdde8cd00795fcedd4c1015283c50dc7f17ca71d",
"value": 177010000,
"index": 0,
"globalIndex": 50556645,
"creationHeight": 1624234,
"settlementHeight": 1624237,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 0\n5: 0\n6: 0\n7: 0\n8: 0\n9: Coll(61,77,106,-65,36,-120,39,27,1,109,101,-87,-13,74,9,45,48,68,77,113,-89,14,-91,30,1,-42,-90,-15,-73,98,118,115)\n10: 1\n11: 0\n12: Coll(82,-43,103,29,47,-108,82,-33,-82,-22,-125,-66,-113,-62,-1,0,-115,58,113,109,-76,-77,-112,-34,-78,119,5,-41,60,96,-108,-22)\n13: 21600\n14: Coll(-98,-6,68,-25,-102,33,112,49,-105,-94,-40,-120,-4,32,76,-10,67,87,17,-51,-17,-49,-33,91,-53,-113,-71,41,-27,9,27,-70)",
"ergoTreeScript": "{\n val i1 = SELF.R7[Int].get\n val coll2 = OUTPUTS.filter({(box2: Box) =>\n val coll4 = box2.tokens\n (coll4.size > placeholder[Int](0)) && (coll4(placeholder[Int](1))._1 == SELF.tokens(placeholder[Int](2))._1)\n }).slice(placeholder[Int](3), i1)\n val coll3 = OUTPUTS(placeholder[Int](4)).propositionBytes\n val coll4 = blake2b256(coll3)\n sigmaProp(\n allOf(\n Coll[Boolean](\n coll2.size == i1, SELF.R4[Coll[Byte]].get == blake2b256(\n coll2.map({(box5: Box) => box5.R4[Coll[Byte]].get }).fold(Coll[Byte](), {(tuple5: (Coll[Byte], Coll[Byte])) => tuple5._1.append(tuple5._2) })\n ), coll2.forall(\n {(box5: Box) =>\n ((box5.propositionBytes == coll3) && (box5.tokens(placeholder[Int](5))._1 == SELF.tokens(placeholder[Int](6))._1)) && (\n box5.tokens(placeholder[Int](7))._2 == SELF.tokens(placeholder[Int](8))._2 / i1.toLong\n )\n }\n ), if (coll4 == placeholder[Coll[Byte]](9)) {\n allOf(\n Coll[Boolean](\n INPUTS(placeholder[Int](10)).tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), HEIGHT - placeholder[Int](13) >= SELF.creationInfo._1\n )\n )\n } else {\n allOf(\n Coll[Boolean](INPUTS.exists({(box5: Box) => blake2b256(box5.propositionBytes) == placeholder[Coll[Byte]](14) }), coll4 == SELF.R6[Coll[Byte]].get)\n )\n }\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "8a94d71b4a08058327fa8372aa69d95c337536c6577c31c8d994169a041e5fc0",
"index": 0,
"amount": 267000000,
"name": "rspv2ErgoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209701c81e057a55c4fc51b4a8aab0cd509711e9d7359564085cd6f8cfba3a369b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9701c81e057a55c4fc51b4a8aab0cd509711e9d7359564085cd6f8cfba3a369b"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[34376235393238653035666565653937666565663334366237373565616538326466613038646631343431323835613434626563393638643134313731636662,6572676f,62696e616e6365,396866555a3954393245754a56574446476a6753533544435154455a34706f4c6a4a51784c4b77753374667351755244704a47,307832633332393931666135613939316262393137396361336662666637373934313939353866366237,000000e9c3103800,000000031910b5d9,000000000817aa06,657267,307865306538613034323432663335623935646336346230376530656165323361386534336137386534,35316638373230386434303462626161346565393063353037366431303336616434373734396231666432623132333730636463376163643535623731653431,000000000018c899]"
},
"R6": {
"serializedValue": "0e206f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b",
"sigmaType": "Coll[SByte]",
"renderedValue": "6f8f73f2b846490d986a3d2c9f509fb56e2fd95fc0100c7a1f6a911f59ea763b"
},
"R7": {
"serializedValue": "04b201",
"sigmaType": "SInt",
"renderedValue": "89"
}
},
"spentTransactionId": "6605c92c136b0a12a5636ed7ec5a862f44111050d1be0cee67776b96e9158e56",
"mainChain": true
},
{
"boxId": "dd54d5439b5075d1cca0dad7c6d3b947a7f37e7d23601d95a0b0f84647d3ca44",
"transactionId": "cf85eefd2f9c371961a6b2214ef656d85f081fbaa160bf3d07b4816f58370a87",
"blockId": "5e6944504e9e4dcdd339d222cdde8cd00795fcedd4c1015283c50dc7f17ca71d",
"value": 4102836456,
"index": 1,
"globalIndex": 50556646,
"creationHeight": 1624234,
"settlementHeight": 1624237,
"ergoTree": "0008cd03f9c83a107c742c552ee3f589313e59a65c8207cfb0a9ee19ef28103fb9a73363",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(f9c83a,6b0d0a,...)))}",
"address": "9iMp3KhUHRHEf4wQSxuN4bt3jvFytSgM31jGwLT2Cx7ju9dhNkW",
"assets": [
{
"tokenId": "a841b23663f1548f4489e46978c6ee3ee6df43af85c2d907923b908e423b508d",
"index": 0,
"amount": 1,
"name": "WID-b508d-u9dhNkW",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f1811888630775d4e42319f11752c606ebeef3905105c27090dc91d1f38f8a3e",
"mainChain": true
},
{
"boxId": "71c92ae66027b5fcc73be4179e71465fa19d6e1c9313d41572aa4fea67f9c7eb",
"transactionId": "cf85eefd2f9c371961a6b2214ef656d85f081fbaa160bf3d07b4816f58370a87",
"blockId": "5e6944504e9e4dcdd339d222cdde8cd00795fcedd4c1015283c50dc7f17ca71d",
"value": 2050000,
"index": 2,
"globalIndex": 50556647,
"creationHeight": 1624234,
"settlementHeight": 1624237,
"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": "c95dc1459f27072057ef39b219f47b94ebda58b1b45ffec47f82ce6d580ba931",
"mainChain": true
}
],
"size": 4192,
"isUnconfirmed": false
}