Transaction
ID: 7329c43361...490e
Inputs (78)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001020304 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:
0.00101 ERG
Tokens:
3,000
Spent
Address:
Output transaction:
Settlement height:
Value:
3.29 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.152030304 ERG
Tokens:
231,000
Spent
Address:
Spent in transaction:
Settlement height:
Value:
3.29 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00205 ERG
Transaction Details
Confirmations: 243,907
Total coins transferred: 3.44 ERG
Fees: 0.00205 ERG
Fees per byte: 0.000000521 ERG
Raw Transaction Data
{
"id": "7329c4336150693739456adedda400e3e3ecc1f8f22e0fb257e1039ba5e7490e",
"blockId": "7da0b6fc9e3a9b5b92341ff79c31f1fceef779fd8bb053cf040680d5da1181eb",
"inclusionHeight": 1525841,
"timestamp": 1747353136262,
"index": 8,
"globalIndex": 8969159,
"numConfirmations": 243907,
"inputs": [
{
"boxId": "fc3833a81794f41cce7845d128beb3416c4fdef64d6061e29119f3109649d085",
"value": 1020304,
"index": 0,
"spendingProof": null,
"outputBlockId": "dac07fd226b6cc905815881028da96b9c277b043d090801b4d6123fdd85eab07",
"outputTransactionId": "dc4b2798a9148757ecc3f1dc5808525c019f1a37e4788e95ce57bdf7b09fcf00",
"outputIndex": 1,
"outputGlobalIndex": 47894167,
"outputCreatedAt": 1525824,
"outputSettledAt": 1525827,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203847d489ece2d3d5a35a1bf26e214f54ac7939411e70b0f547e6a610ca784736",
"sigmaType": "Coll[SByte]",
"renderedValue": "3847d489ece2d3d5a35a1bf26e214f54ac7939411e70b0f547e6a610ca784736"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20697eb72aa43ef6c0ec2f40d7507810c9d9e9c99e838be484c41b53062406e58a",
"sigmaType": "Coll[SByte]",
"renderedValue": "697eb72aa43ef6c0ec2f40d7507810c9d9e9c99e838be484c41b53062406e58a"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "463c914303932c73c9c3e123f0cda362bf8c4a53c825d52c5c7c45790a177ff4",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "9dc43f93a4f25f8363cc0c8e080c83179988559ad21b80b28c6892c2d099d7a1",
"outputTransactionId": "12591e05acd55fead3eb708f401ea8709b12c536c90657024e030c204e867d27",
"outputIndex": 1,
"outputGlobalIndex": 47894192,
"outputCreatedAt": 1525825,
"outputSettledAt": 1525828,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201de794fa1d9e574eb1f9330fd21df2e8258f0e0e5b6cf73a3b05ff5c633ea3d0",
"sigmaType": "Coll[SByte]",
"renderedValue": "1de794fa1d9e574eb1f9330fd21df2e8258f0e0e5b6cf73a3b05ff5c633ea3d0"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e200d90be56c204f7eebab4d42213abe15ac50d656735ab2d8fbd0cb21ecdacd0f1",
"sigmaType": "Coll[SByte]",
"renderedValue": "0d90be56c204f7eebab4d42213abe15ac50d656735ab2d8fbd0cb21ecdacd0f1"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "9d884af339098f7e8aefb9962982ea7d8274dbda8bafecb5835a073185c8d6cc",
"value": 2000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "9dc43f93a4f25f8363cc0c8e080c83179988559ad21b80b28c6892c2d099d7a1",
"outputTransactionId": "2e4cad206e89d804fc3c197e9982a33454181ff0cb235084897117bd8a9709ff",
"outputIndex": 1,
"outputGlobalIndex": 47894197,
"outputCreatedAt": 1525826,
"outputSettledAt": 1525828,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203030527c8fc3b92734b408d82f1c27e71e929fdfcd3938771f5877f456dc2d53",
"sigmaType": "Coll[SByte]",
"renderedValue": "3030527c8fc3b92734b408d82f1c27e71e929fdfcd3938771f5877f456dc2d53"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20bb979e2a19e903575ef345657bfa083a4ab3a6244298dd02881ac1a1aa527847",
"sigmaType": "Coll[SByte]",
"renderedValue": "bb979e2a19e903575ef345657bfa083a4ab3a6244298dd02881ac1a1aa527847"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "e6ba8fa8117c8c9e2378f46757edd596e8660ab0214e62d17c347b256f62c461",
"value": 2000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "eff6544ed1c6b522464a82b357dccc28891f4d0b75935da42a051ae0208739d1",
"outputTransactionId": "0323451cfbcedf94fd87cb06d16280ba65b57182707a7257925655cead766a11",
"outputIndex": 1,
"outputGlobalIndex": 47894211,
"outputCreatedAt": 1525827,
"outputSettledAt": 1525830,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2061808ded4a40a59ed6d9b7d55286770bc4d9ac0209dbcfd3ca5c5e91343b493a",
"sigmaType": "Coll[SByte]",
"renderedValue": "61808ded4a40a59ed6d9b7d55286770bc4d9ac0209dbcfd3ca5c5e91343b493a"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e204342cf94cd76bb68b76e74de0c117b6564fc0c3c2a1da66c704a79b8ac621e62",
"sigmaType": "Coll[SByte]",
"renderedValue": "4342cf94cd76bb68b76e74de0c117b6564fc0c3c2a1da66c704a79b8ac621e62"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "70dc7305c0a1c198e810a8e7dc49ba56dcdab029d243c3168826c60928d7de7a",
"value": 2000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "4949724570b9338d7d847fef009afebbf248b8f04e906ff41c20f1e5f7d888d2",
"outputIndex": 1,
"outputGlobalIndex": 47894267,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f8757736b25efe278b816e9e56fda430056e78002cacad962d28bf9fe2576509",
"sigmaType": "Coll[SByte]",
"renderedValue": "f8757736b25efe278b816e9e56fda430056e78002cacad962d28bf9fe2576509"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2009ff9673a61d635401a938df14dbe300407d5599d1979c2b5c52aff9ef828987",
"sigmaType": "Coll[SByte]",
"renderedValue": "09ff9673a61d635401a938df14dbe300407d5599d1979c2b5c52aff9ef828987"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "78cfff51ac5362a6563a068aea601da26dd88e91e5c0c8e7c90aea8e7c999c19",
"value": 2000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "fcf44fae930b492100a228b638a2d34ffefd6ea3971737ad705de74bfdd7e7cd",
"outputIndex": 1,
"outputGlobalIndex": 47894272,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201f5e0093911cdaa9258edb46ad972e5a91ed8addd75cfa1a2f51491c0ec5fcc3",
"sigmaType": "Coll[SByte]",
"renderedValue": "1f5e0093911cdaa9258edb46ad972e5a91ed8addd75cfa1a2f51491c0ec5fcc3"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20608c2303d1820d9123d754786301dc2b8654c9c21b019d05ffea4e2061168845",
"sigmaType": "Coll[SByte]",
"renderedValue": "608c2303d1820d9123d754786301dc2b8654c9c21b019d05ffea4e2061168845"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "c85ee731051fc6a0a4751a38fd88700bf31f7c025a4751260664e505d6ef0ce2",
"value": 2000000,
"index": 6,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "012ee37295b207f90a5a555e5db2be74ed9e446858b2955524be77ce763b361f",
"outputIndex": 1,
"outputGlobalIndex": 47894277,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20bc7cb8b5d2fd223b405caf56bb881115ccb7f967e0a776638f94c242c0507992",
"sigmaType": "Coll[SByte]",
"renderedValue": "bc7cb8b5d2fd223b405caf56bb881115ccb7f967e0a776638f94c242c0507992"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e208c2c3a0ba6ee24bd7c823f068aaa7569e366fa83e2c812e861b0c676c7561515",
"sigmaType": "Coll[SByte]",
"renderedValue": "8c2c3a0ba6ee24bd7c823f068aaa7569e366fa83e2c812e861b0c676c7561515"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "553b22d6460c88d0939b7015aa17c9eee70069be7b22bab62cb1713fdd803c6a",
"value": 2000000,
"index": 7,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "154b058dfa8b82396d66133e040ba2f4158704f52dbc4edf082998b57aa415b0",
"outputIndex": 1,
"outputGlobalIndex": 47894282,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200b8b089ac3fb8773a0213ef79ae3c9fee84d094be75c72a878d82fd1cd22db11",
"sigmaType": "Coll[SByte]",
"renderedValue": "0b8b089ac3fb8773a0213ef79ae3c9fee84d094be75c72a878d82fd1cd22db11"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20bd4136370332b3cc41312c30d901104a325d57adb0422004fb514a5e3391783b",
"sigmaType": "Coll[SByte]",
"renderedValue": "bd4136370332b3cc41312c30d901104a325d57adb0422004fb514a5e3391783b"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "7c14679093636637ecd6e4729872532def8f6e253a46265d273e475e58479c89",
"value": 2000000,
"index": 8,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "7158cf4564e93fb6f3a334b1ac535a1ad33552667763cd2fdbe1d29837635ddb",
"outputIndex": 1,
"outputGlobalIndex": 47894287,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "102404000e2043cc6134bf9ea1c1eee26380bb304d58430217ca5799366356819039a45abc24040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e2037aa6c6c414a85912b373ca9a3abe88a29b9c738a9c1b2bf8644c19dedc09ce004000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2061bcd37f584dbda1ba40a3c45c064c1e342c7c66527fec3404ffde34a013aa90",
"sigmaType": "Coll[SByte]",
"renderedValue": "61bcd37f584dbda1ba40a3c45c064c1e342c7c66527fec3404ffde34a013aa90"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20c9021aa522b8b1147d95aa3490081c728bfaa41942f0e77ce2d88c3d69a14572",
"sigmaType": "Coll[SByte]",
"renderedValue": "c9021aa522b8b1147d95aa3490081c728bfaa41942f0e77ce2d88c3d69a14572"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "c7cc7a9c6c9b2bad8d64968e664acc1c72332cc1467caeb67db6f921a22faf8c",
"value": 2000000,
"index": 9,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "a99833266b788b6289586a14d83b1d3fce5e1733a045e71262756f4bb7758a37",
"outputIndex": 1,
"outputGlobalIndex": 47894292,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b55efc007116cf73871bdef92c73ef379fb9b8ecf607dafbfec08ceb2becb4b9",
"sigmaType": "Coll[SByte]",
"renderedValue": "b55efc007116cf73871bdef92c73ef379fb9b8ecf607dafbfec08ceb2becb4b9"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20298efcff725443aa7d2747b92f7aa0a84355de159cabebc80d81d154d3c453b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "298efcff725443aa7d2747b92f7aa0a84355de159cabebc80d81d154d3c453b2"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "f3480cc415e545d136d95334896eff626c71b0982d8b18f0dfdadcf62644c42a",
"value": 2000000,
"index": 10,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "b05aa0ff4ba610f7049eea3f0c3ca5c51dd03b9769ff930dd17cea512b0347f3",
"outputIndex": 1,
"outputGlobalIndex": 47894297,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20816e06228aefd52d5c10755d98752a34b4b5c511e48028e7c731c6d29ae16586",
"sigmaType": "Coll[SByte]",
"renderedValue": "816e06228aefd52d5c10755d98752a34b4b5c511e48028e7c731c6d29ae16586"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e207c44689aec3aa17da4911abdcac868696c68a1b83a01aa13bb7c8cf3288de501",
"sigmaType": "Coll[SByte]",
"renderedValue": "7c44689aec3aa17da4911abdcac868696c68a1b83a01aa13bb7c8cf3288de501"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ce1e7a83298b964799167ad2e61ee3657705f71cd3efcc4aad2a6f397dfb1032",
"value": 2000000,
"index": 11,
"spendingProof": null,
"outputBlockId": "88962d9579bd550fe8f952ff71a54e9ed31768a96a45af161589efabed6d4d9c",
"outputTransactionId": "b3f9e3aa0bfdb5880ae6da5a99d572d323c670e61a0bb8ccc69304babf27acfc",
"outputIndex": 1,
"outputGlobalIndex": 47894302,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525833,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e204ee0ea8e491cee003b0106415d88dcca7ed0a303a0896eca3e2b4e6ddfcd3b62",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ee0ea8e491cee003b0106415d88dcca7ed0a303a0896eca3e2b4e6ddfcd3b62"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20fd4af85ce14868c1d5e2c4c60e54c1069d1208fa57972f29e62a1586de858919",
"sigmaType": "Coll[SByte]",
"renderedValue": "fd4af85ce14868c1d5e2c4c60e54c1069d1208fa57972f29e62a1586de858919"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "9ac9e9ee72b87dcc120c61e76fd55db1b451f410a092d405084a48052a8c2f02",
"value": 2000000,
"index": 12,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "9e86e3fbbb2e2da585e679b58f81356375f660dda7bb031dc743c161edc4d023",
"outputIndex": 1,
"outputGlobalIndex": 47894339,
"outputCreatedAt": 1525832,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e203a634dd9262752c0f025a5c481b47455b7314a54076e1c6678f987a08c0b3204",
"sigmaType": "Coll[SByte]",
"renderedValue": "3a634dd9262752c0f025a5c481b47455b7314a54076e1c6678f987a08c0b3204"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20fa97d36711814dc10660ddba7077976a27e932b41c5a30ca0bd6aa98997c873d",
"sigmaType": "Coll[SByte]",
"renderedValue": "fa97d36711814dc10660ddba7077976a27e932b41c5a30ca0bd6aa98997c873d"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "e4f80f52527028ecb15e5da1f61ac9197ebb150423c78a9f307ac4bab9534718",
"value": 2000000,
"index": 13,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "f5771c9a230329b47abcab98de36db151c463cb0a79f1c840b5b72a7603b91e7",
"outputIndex": 1,
"outputGlobalIndex": 47894344,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20bd3bad6ce30002617e15c0d552c018816adecff18e0597fac962422190c7e6c4",
"sigmaType": "Coll[SByte]",
"renderedValue": "bd3bad6ce30002617e15c0d552c018816adecff18e0597fac962422190c7e6c4"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20ce9a8f335c44a0f45d27fa2d0307168a8fa4cd4dd9b4463145b0cc4255c96261",
"sigmaType": "Coll[SByte]",
"renderedValue": "ce9a8f335c44a0f45d27fa2d0307168a8fa4cd4dd9b4463145b0cc4255c96261"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "8bba3027788ab0f427e16ad38a24b8183a9419015636e039aae679e1a3443576",
"value": 2000000,
"index": 14,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "0bd2d07c25227608310bd41077b3ce2a9ecb41447e183a919f83756bb38ff6be",
"outputIndex": 1,
"outputGlobalIndex": 47894349,
"outputCreatedAt": 1525832,
"outputSettledAt": 1525834,
"ergoTree": "102404000e2043cc6134bf9ea1c1eee26380bb304d58430217ca5799366356819039a45abc24040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e2037aa6c6c414a85912b373ca9a3abe88a29b9c738a9c1b2bf8644c19dedc09ce004000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fd80918bb386da1f3e8cf13178d6e80a28947f18d676bb703b1f3ab17715dc2b",
"sigmaType": "Coll[SByte]",
"renderedValue": "fd80918bb386da1f3e8cf13178d6e80a28947f18d676bb703b1f3ab17715dc2b"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20c9e81dfa041e6b734381b4206a10170d545332835f52d2c134a151367d1423ac",
"sigmaType": "Coll[SByte]",
"renderedValue": "c9e81dfa041e6b734381b4206a10170d545332835f52d2c134a151367d1423ac"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "7caf2cf1705319b54c86825e92bebdb3703a6f3554c0e4642da23d08727729e8",
"value": 2000000,
"index": 15,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "1f22e1a69e40a50bd5b13c09960c5b0d632d9070032ab6e932c19a63268a4cc3",
"outputIndex": 1,
"outputGlobalIndex": 47894354,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ea1a8d48ebf6ce2f907d0a2c235bd03382170fb417a23fa52e8ca40aedb6692c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea1a8d48ebf6ce2f907d0a2c235bd03382170fb417a23fa52e8ca40aedb6692c"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2045a32b6bbe5ab83f79258eaaa2b29fdede60b0d347604a467403fc9ce8c704c2",
"sigmaType": "Coll[SByte]",
"renderedValue": "45a32b6bbe5ab83f79258eaaa2b29fdede60b0d347604a467403fc9ce8c704c2"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "eba919541e99938da73b17df0133ea504beb8c90ddfaf4c6504d3a31a825a2e9",
"value": 2000000,
"index": 16,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "7e9e5e617cc1b0e1fbe7d0b521478a048c2da5fd085e3a79bc0669aa9d55db34",
"outputIndex": 1,
"outputGlobalIndex": 47894359,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205eb5f47a2cb427857032b032fca22c5c72a4214e5843c8a9eea2b226780fc451",
"sigmaType": "Coll[SByte]",
"renderedValue": "5eb5f47a2cb427857032b032fca22c5c72a4214e5843c8a9eea2b226780fc451"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2088d5ed704a6ef7eb0c0568f7563082aa6ed11a098930dcd834fcbb2694586f42",
"sigmaType": "Coll[SByte]",
"renderedValue": "88d5ed704a6ef7eb0c0568f7563082aa6ed11a098930dcd834fcbb2694586f42"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ee36678648bf50c1616372810be2374bf8e3d799bb872ca029651a8604c74dce",
"value": 2000000,
"index": 17,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "ccc1e8b0cbf89c3e38f3bd0815c902698e1fbe3f64f552af5b9fd5dbb81a32d8",
"outputIndex": 1,
"outputGlobalIndex": 47894364,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201682e2e0612780cd9d401b0de8ab76ceee4a07e58ac6ff350c14fb13ce9d7905",
"sigmaType": "Coll[SByte]",
"renderedValue": "1682e2e0612780cd9d401b0de8ab76ceee4a07e58ac6ff350c14fb13ce9d7905"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20ea892eaeea228ef70b93053bcfd70355ec55421da3908b09e2592b13927f0e3e",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea892eaeea228ef70b93053bcfd70355ec55421da3908b09e2592b13927f0e3e"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "0c3ef1ebf745705f34250a1f78be9bd6dbaeae0ae39662dd5ede5be251c99f8f",
"value": 2000000,
"index": 18,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "e1dc0a751b5769fed45a8ab3a5be263ad1d28aec247013a6bc81f467c087beee",
"outputIndex": 1,
"outputGlobalIndex": 47894369,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "102404000e2043cc6134bf9ea1c1eee26380bb304d58430217ca5799366356819039a45abc24040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e2037aa6c6c414a85912b373ca9a3abe88a29b9c738a9c1b2bf8644c19dedc09ce004000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2017356c3e70f96381e454acaf59325fd52855a25996c6eea6819b6686cf35e124",
"sigmaType": "Coll[SByte]",
"renderedValue": "17356c3e70f96381e454acaf59325fd52855a25996c6eea6819b6686cf35e124"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e204f37f9036762b41234fc33447084ec8d4fe8102c329fec1f55fa180be83451d8",
"sigmaType": "Coll[SByte]",
"renderedValue": "4f37f9036762b41234fc33447084ec8d4fe8102c329fec1f55fa180be83451d8"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "1b58d049dadeebb3ec2ad54b44196cab1a6a4a31853ccfd693a291574b96f6dd",
"value": 2000000,
"index": 19,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "c9d5c11255cfd0a124102fa57b5e40f9f7740d2fdd58cde63a51ca1a4e18a88a",
"outputIndex": 1,
"outputGlobalIndex": 47894374,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2051c49be545b1a83ac47316b0142e46ecd1363c392e2521feff44c2a7c5d3f4d4",
"sigmaType": "Coll[SByte]",
"renderedValue": "51c49be545b1a83ac47316b0142e46ecd1363c392e2521feff44c2a7c5d3f4d4"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20034875f3297ede8ce5da4ffa8b559746536ce879821537656ef6e2dad178e54e",
"sigmaType": "Coll[SByte]",
"renderedValue": "034875f3297ede8ce5da4ffa8b559746536ce879821537656ef6e2dad178e54e"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ba8c3caf03b220db15483837630209da3f43be9a841af251af9c2974b722447e",
"value": 2000000,
"index": 20,
"spendingProof": null,
"outputBlockId": "ede88f5c06da62c3be355203fd813909199585b01d66bea352e7063936a896df",
"outputTransactionId": "ecb53086d58e454b7974fcfd864d9db4d1f67549b3c6c43e7c6bb2d0ef6738b5",
"outputIndex": 1,
"outputGlobalIndex": 47894379,
"outputCreatedAt": 1525831,
"outputSettledAt": 1525834,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20977575ea724016bd32a53e56f1eed7e62e3a5a83e288774f454bd546d2ae1147",
"sigmaType": "Coll[SByte]",
"renderedValue": "977575ea724016bd32a53e56f1eed7e62e3a5a83e288774f454bd546d2ae1147"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20e3d38f3487700d94d82771faf058f3251f6aaabbf90896ac3aaf2a6f5294d699",
"sigmaType": "Coll[SByte]",
"renderedValue": "e3d38f3487700d94d82771faf058f3251f6aaabbf90896ac3aaf2a6f5294d699"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "3a94745991264ddf2105b92651338faf40a10582c1d8ea65255d85a424d50228",
"value": 2000000,
"index": 21,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "558ce8f4dd733fe28fda34f9673a29b6f2434614a12c1e536f089e89d09002e6",
"outputIndex": 1,
"outputGlobalIndex": 47894517,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202c6dd9f1d60c3d726315ef4e49426d6f54bad1201ff1d7037e670da2e7d6243b",
"sigmaType": "Coll[SByte]",
"renderedValue": "2c6dd9f1d60c3d726315ef4e49426d6f54bad1201ff1d7037e670da2e7d6243b"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20c5a74b14c1a1c81b6bb3c7a30a7575175f733a59c25e3af00433f4491c6c285a",
"sigmaType": "Coll[SByte]",
"renderedValue": "c5a74b14c1a1c81b6bb3c7a30a7575175f733a59c25e3af00433f4491c6c285a"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "63f3ded46e4053bcd5bc2ff67b01ae9a883ff40b45fa694524df1871ec0697c6",
"value": 2000000,
"index": 22,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "028a8c9649a5be94975023fe73a7a208327ae9e32dfd5d6b618e37b5134fc9fd",
"outputIndex": 1,
"outputGlobalIndex": 47894522,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a62134bd53d446c0c289aecf2749f266b5b2db6d65c3ba27dc34b5dc9692ab8d",
"sigmaType": "Coll[SByte]",
"renderedValue": "a62134bd53d446c0c289aecf2749f266b5b2db6d65c3ba27dc34b5dc9692ab8d"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2029045346c5e17c784dec9fdc06169df9b586073c7971ec4314cfb331cf6ec842",
"sigmaType": "Coll[SByte]",
"renderedValue": "29045346c5e17c784dec9fdc06169df9b586073c7971ec4314cfb331cf6ec842"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "56de01352c345cb9fe8518a19b57510ceb9724c4b77038dd228323a2c875a16b",
"value": 2000000,
"index": 23,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "4cff26df6bc48067e9515f5fb1dddc94727b285f18f569510bef5a4cd409371c",
"outputIndex": 1,
"outputGlobalIndex": 47894527,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d3a867a5cd6c938dbca54e6ecad783a618051888dbaeecb8479ab6875fd56287",
"sigmaType": "Coll[SByte]",
"renderedValue": "d3a867a5cd6c938dbca54e6ecad783a618051888dbaeecb8479ab6875fd56287"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20ee9172165e83780d7afe45388630d34c07f7fb63fd0c0227ac4fd89e44f040c4",
"sigmaType": "Coll[SByte]",
"renderedValue": "ee9172165e83780d7afe45388630d34c07f7fb63fd0c0227ac4fd89e44f040c4"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "c8274bbf375e07a7e333edb07ce955b9caa60eabe351e4679983dd5b6348e1c8",
"value": 2000000,
"index": 24,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "5ad00e92638d5e06420a91cc90734440f7db17ee312d9affe5d79c96a50f5e0d",
"outputIndex": 1,
"outputGlobalIndex": 47894532,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20dbc3c9c9d0055514b33be94d0baa712cfbbd4d539f0559d7e644b92e70db40db",
"sigmaType": "Coll[SByte]",
"renderedValue": "dbc3c9c9d0055514b33be94d0baa712cfbbd4d539f0559d7e644b92e70db40db"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2056cf21b9c8e5d5ca2c5c6f12af7d7a8002b24891de7a0ee441668cb020983e91",
"sigmaType": "Coll[SByte]",
"renderedValue": "56cf21b9c8e5d5ca2c5c6f12af7d7a8002b24891de7a0ee441668cb020983e91"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "dd2af757181303c9acabd5126c1af56ac30427f71e2907d682d45662ef4f5012",
"value": 2000000,
"index": 25,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "5ec5e845c891cfa2cb4ef0c32ac2d46be0aa819d52cbce26483bf47fdfb44482",
"outputIndex": 1,
"outputGlobalIndex": 47894537,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2006d578090dc9c7ce05b98f295be52219842f3264a4cc5fea284404fbb0104329",
"sigmaType": "Coll[SByte]",
"renderedValue": "06d578090dc9c7ce05b98f295be52219842f3264a4cc5fea284404fbb0104329"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2075127b881f5b65ec0659d7f3da79ba1c4eac271e126f5650525b518aacf08d43",
"sigmaType": "Coll[SByte]",
"renderedValue": "75127b881f5b65ec0659d7f3da79ba1c4eac271e126f5650525b518aacf08d43"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "3a76766657a0824c624e1731eab8bf4cdd56592b12c5d010536b172eabdccfb8",
"value": 2000000,
"index": 26,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "601f2cb22e96771dc8dddda841b52f92f153f445aa1ec49f19fb8aeae91190cf",
"outputIndex": 1,
"outputGlobalIndex": 47894542,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2008050389b4f96a3b204c8c298bcb8e7df84183b3219676d3d3b605cbb7a75be2",
"sigmaType": "Coll[SByte]",
"renderedValue": "08050389b4f96a3b204c8c298bcb8e7df84183b3219676d3d3b605cbb7a75be2"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2003f84bbeb8f707497bbd10c85b3c8500300a1d5c652ce87bee1145ce717c4da9",
"sigmaType": "Coll[SByte]",
"renderedValue": "03f84bbeb8f707497bbd10c85b3c8500300a1d5c652ce87bee1145ce717c4da9"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "117cc50322d6404430b761332b2de75d727ef45040191978230ee58a0a25077e",
"value": 2000000,
"index": 27,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "76ec6ce39e2072ca376d828560f529b7d1e0888c94aff2cbe1fcc35aa0af9f37",
"outputIndex": 1,
"outputGlobalIndex": 47894547,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20836bf73c061756e6c3ac7273dc127b6f2d2a90cbbf5487f1637949de7c621aa9",
"sigmaType": "Coll[SByte]",
"renderedValue": "836bf73c061756e6c3ac7273dc127b6f2d2a90cbbf5487f1637949de7c621aa9"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2035a1803728ba35a5c12dbf850910edcdbc3d977479ac8ea2856d7d9b078992de",
"sigmaType": "Coll[SByte]",
"renderedValue": "35a1803728ba35a5c12dbf850910edcdbc3d977479ac8ea2856d7d9b078992de"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "4b9da1eb537981e0c8612654ef0fe9b404250e869a509ee939984bc6e5890f9f",
"value": 2000000,
"index": 28,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "7dc9b2a3e37eab65d21f2d8b0d0adb241a0c277be5aed1ec3500f5489ef90f6f",
"outputIndex": 1,
"outputGlobalIndex": 47894552,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "102404000e2043cc6134bf9ea1c1eee26380bb304d58430217ca5799366356819039a45abc24040004000400040004000400040004000400040004020400040204000400040004060404040205c8010400040004000e2037aa6c6c414a85912b373ca9a3abe88a29b9c738a9c1b2bf8644c19dedc09ce004000e20eca7776f5dedd9ef238106e151f0eaf8b1a308190a2ee59652eceb28068c766004020402050004000400040004020400d809d601b2a4730000d6027301d60393cbc272017202d604e4c6a7040ed6059572037201b2a5730200d606e4c67205051ad607830002d608b072067207d901083c0e0eb38c7208018c720802d609b2a5730300957203d804d60ab2b5a5d9010a63d801d60cc6720a040eede6720c93e4720c7204730400d60bb2db6308720a730500d60cb2db6308a7730600d60d8c720c01d19683060193cbc2720ae4c6a7070e938c720b01720d938c720b028c720c02efaeadb4b5a5d9010e63d801d610db6308720eed91b172107307938cb2721073080001720d7309e4c672050704d9010e63e4c6720e040ed9010e0e937204720e93b1b5a4d9010e63d801d610db6308720eededed91b17210730a938cb27210730b0001720d93c2720ec2a793e4c6720e040e7204730c93cbb372087204e4c6a7060ed801d60acbc272099593720a7202d80ed60bdb6501fed60cb2720b730d00d60db2720b730e00d60edb6308720dd60fb2db6308a7730f00d6108c720f01d611b5a4d9011163eded93c2a7c2721191b1db630872117310938cb2db63087211731100017210d612b17211d6137e721205d614e4c6720c0411d615b27214731200d6169ab272147313009d9cb27214731400e4c6720d05057315d617b27214731600d618b2db63087205731700d196830e01938cb2db6308720c731800017319938cb2720e731a0001731b938cb2720e731c0001721093b1b57211d901196393e4c67219040e7204731d92c17205b0ad7211d9011963c17219731ed90119599a8c7219018c72190293e4c67205060ee4c6a7070e93e4c672050704721293e4c67205040ecbb0ad7211d9011963e4c67219040e7207d901193c0e0eb38c7219018c72190293cbb372087204e4c6a7060e93e4c6a7050ecbb27206731f00917213958f7215721672157216938c720f027217938c7218029c72177213938c7218017210d802d60bb2db63087209732000d60cb2db6308a7732100d19683060193c5a7c57201938c720b018c720c01938c720b028c720c0293e4c67209040e7204938cb2db6308b2a573220073230001720493720ae4c6a7070e",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207ad627001256877143f9f28be725c71ff041c46253bd50771ba239cb5f4673f9",
"sigmaType": "Coll[SByte]",
"renderedValue": "7ad627001256877143f9f28be725c71ff041c46253bd50771ba239cb5f4673f9"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20891bafe0d13f2b6362db22baf3998629d888aec03797b5ba29987286ce47d1b9",
"sigmaType": "Coll[SByte]",
"renderedValue": "891bafe0d13f2b6362db22baf3998629d888aec03797b5ba29987286ce47d1b9"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "1bbb7c8eac7f7297ce4c7f7208707a1a46325ed73ddf2649b145a6f7c82716a8",
"value": 2000000,
"index": 29,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "07f4ef43089338dce216d93e0fc79087cc1101d7ff25d41f7c5639a7f8679d6a",
"outputIndex": 1,
"outputGlobalIndex": 47894557,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2060b97e8766e5cd19936ba19225ec827d4af72962acf60596886dbec32c6760d2",
"sigmaType": "Coll[SByte]",
"renderedValue": "60b97e8766e5cd19936ba19225ec827d4af72962acf60596886dbec32c6760d2"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20d6ca71162920c556bf01b08d6dd637f69b7c44e4bd11bb62b260d99634183516",
"sigmaType": "Coll[SByte]",
"renderedValue": "d6ca71162920c556bf01b08d6dd637f69b7c44e4bd11bb62b260d99634183516"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "3116b4ecc094ec4db844be87e3a972e68fabcfb42b644d43b7a9e41c46880a30",
"value": 2000000,
"index": 30,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "08523d5bdfb1365d35aad65e419426301f3e5aafd56a6078d6d0be2060368bd9",
"outputIndex": 1,
"outputGlobalIndex": 47894562,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e204e464f285eed520fe57a9100ba5dd4aa1a56351862a99b9291097b2bcd42f1cf",
"sigmaType": "Coll[SByte]",
"renderedValue": "4e464f285eed520fe57a9100ba5dd4aa1a56351862a99b9291097b2bcd42f1cf"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2098c61d0a3e507584dc3e70e7e54474b86a128abb12776c6eab0cfffbe5bf72bb",
"sigmaType": "Coll[SByte]",
"renderedValue": "98c61d0a3e507584dc3e70e7e54474b86a128abb12776c6eab0cfffbe5bf72bb"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ed07b5a72990f1aba28557360df3506343a17ecee9da97d468df2a3e830db369",
"value": 2000000,
"index": 31,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "0e8fcbdf23213ffbff4d1b6c8f90e6261cb05a039b799ecb24d984d5a4a1eeb2",
"outputIndex": 1,
"outputGlobalIndex": 47894567,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200d9491b31d1dab5909f40011bcc9581ba8d8df1ebcb5a31077568f5c36855664",
"sigmaType": "Coll[SByte]",
"renderedValue": "0d9491b31d1dab5909f40011bcc9581ba8d8df1ebcb5a31077568f5c36855664"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20c575c72dfe6b13a978564ce25330198905cdeb4ec71e5017d1f3908df672101b",
"sigmaType": "Coll[SByte]",
"renderedValue": "c575c72dfe6b13a978564ce25330198905cdeb4ec71e5017d1f3908df672101b"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "6b051d23f3db8ec733dd6314362081360cf9a3cc91c550efee69999c4632eb60",
"value": 2000000,
"index": 32,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "147b72e6286a6a9ce20122b1f51bbe075571ed54a03aa82997acdc6329e463d2",
"outputIndex": 1,
"outputGlobalIndex": 47894572,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209646a8fce73640809babc7cfe05c3eb0ac55c276c70aa9c36aa88cb394d313e4",
"sigmaType": "Coll[SByte]",
"renderedValue": "9646a8fce73640809babc7cfe05c3eb0ac55c276c70aa9c36aa88cb394d313e4"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e206d84da7c1aac5f7ce58868c8facd7272cd797f1dbbb3abd8af143dd95faf1435",
"sigmaType": "Coll[SByte]",
"renderedValue": "6d84da7c1aac5f7ce58868c8facd7272cd797f1dbbb3abd8af143dd95faf1435"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "1714a64af602c95cd76b2b62041a6c7d651f3ba09d24ac33532c06fc19c81a94",
"value": 2000000,
"index": 33,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "1c9bf626eee6e92ee4ec404ad45b3eab46c3815f9169b0bee365b2fb0188c5de",
"outputIndex": 1,
"outputGlobalIndex": 47894577,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20afdf1813b7ade06cc3446ddf0f62b2f60bfda6f548f2d7f62363906a9bbead61",
"sigmaType": "Coll[SByte]",
"renderedValue": "afdf1813b7ade06cc3446ddf0f62b2f60bfda6f548f2d7f62363906a9bbead61"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e204e62ca48e29d97fdaae37af2801f0604f20dfaa2bda2b86f2d5aff18b79b93cd",
"sigmaType": "Coll[SByte]",
"renderedValue": "4e62ca48e29d97fdaae37af2801f0604f20dfaa2bda2b86f2d5aff18b79b93cd"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ce89d08670344143e77f6aa27604868539d735145bf89769fb8920b79b53636b",
"value": 2000000,
"index": 34,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "20839ee2d26ed3bff2b5b6430cd6fea740917dce1621d0747e541d5939e9e94c",
"outputIndex": 1,
"outputGlobalIndex": 47894582,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2058091a84ca567458d1867eb0f6da796eb5e660bc9475b6f3c8c219f5393de18e",
"sigmaType": "Coll[SByte]",
"renderedValue": "58091a84ca567458d1867eb0f6da796eb5e660bc9475b6f3c8c219f5393de18e"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2089c1c306a988b4571d698eb3509f9ec3e86bd4be277577986ddb75edfef3a57b",
"sigmaType": "Coll[SByte]",
"renderedValue": "89c1c306a988b4571d698eb3509f9ec3e86bd4be277577986ddb75edfef3a57b"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "db5eecfdec052b2899789060721f88033c4c7eafe264a97ee01382603fa74942",
"value": 2000000,
"index": 35,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "2e39cd063ba08ce285188e6183ac7888fa09db4b2c96ac7316c325e89acbac36",
"outputIndex": 1,
"outputGlobalIndex": 47894587,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e200841cdfbbc83ddb87cfec36d6d92990f5c189aede7c82a3da66b0fa1d6e8cb57",
"sigmaType": "Coll[SByte]",
"renderedValue": "0841cdfbbc83ddb87cfec36d6d92990f5c189aede7c82a3da66b0fa1d6e8cb57"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e202bd00cd60c1b1f0fada3f4e0da619a6163e7690e87857bd8190bc29adfc860f0",
"sigmaType": "Coll[SByte]",
"renderedValue": "2bd00cd60c1b1f0fada3f4e0da619a6163e7690e87857bd8190bc29adfc860f0"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "52bd4296f3c67cee46618e631894233ec32334897c24176143462dee3a2d3bce",
"value": 2000000,
"index": 36,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "328c377f84d1680efc38012ec0e7b9938c3058fa581e984f9ecc64ba7b11f73c",
"outputIndex": 1,
"outputGlobalIndex": 47894592,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20c72e9046f44e0869ea917e684b0d53bd062b164431722a8a1b03ed6ed750633e",
"sigmaType": "Coll[SByte]",
"renderedValue": "c72e9046f44e0869ea917e684b0d53bd062b164431722a8a1b03ed6ed750633e"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2061c9e9a60407f161d9866dbd998e694fc4f94031c3f3ff5d0138bda249b2b61d",
"sigmaType": "Coll[SByte]",
"renderedValue": "61c9e9a60407f161d9866dbd998e694fc4f94031c3f3ff5d0138bda249b2b61d"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "45a8d8c816d9634290ca6c7ea99d29d7c651caf2f3b235d02b9ff0f3372599fb",
"value": 2000000,
"index": 37,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "367d605ce15455d77418060bd9b6c5f8c5a5b8f7c0ad2a0cb8efb346368723d3",
"outputIndex": 1,
"outputGlobalIndex": 47894597,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fab1e9bb8c5009ec94aac1fcc5736723dce487c7966fdbe3095ae84b464aa6dd",
"sigmaType": "Coll[SByte]",
"renderedValue": "fab1e9bb8c5009ec94aac1fcc5736723dce487c7966fdbe3095ae84b464aa6dd"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e206422910efaa379ce0825068b94b8387ae03dc9ed8d7cc08fa27b106eccb853be",
"sigmaType": "Coll[SByte]",
"renderedValue": "6422910efaa379ce0825068b94b8387ae03dc9ed8d7cc08fa27b106eccb853be"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "58c81e8a9b7ea034ee3c758f281520988603e9494f85cb3c965e60f10615bc82",
"value": 2000000,
"index": 38,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "3a6585d57955987c907d127ea51439d68d94e695b0ce06ae6f92fc37f6eb908a",
"outputIndex": 1,
"outputGlobalIndex": 47894602,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20739d1860890b0dc708cfbfc0acc4de4e8315e0a8275fb1d3c2f792f63517c613",
"sigmaType": "Coll[SByte]",
"renderedValue": "739d1860890b0dc708cfbfc0acc4de4e8315e0a8275fb1d3c2f792f63517c613"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20202dbfcd7126ac8011f3a8d987538a1fc1e60757f3e8a57d30e4d88d6b482725",
"sigmaType": "Coll[SByte]",
"renderedValue": "202dbfcd7126ac8011f3a8d987538a1fc1e60757f3e8a57d30e4d88d6b482725"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "2acc307bf02473174bfa3e114c5aa307388ce4c380e65fb6d575ef04d89c38bc",
"value": 2000000,
"index": 39,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "3d592671cbe38632ba69f628cc6103d9428c0fb8287363fb71a49aefe2039a53",
"outputIndex": 1,
"outputGlobalIndex": 47894607,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2099246814103ba2765cd28d269d6251932d3cdcd121f0224b627470fcd1588c43",
"sigmaType": "Coll[SByte]",
"renderedValue": "99246814103ba2765cd28d269d6251932d3cdcd121f0224b627470fcd1588c43"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2063bd805552e36fa8731e0231f4944069ad0f925382f7a3c80258cd13a4e4d547",
"sigmaType": "Coll[SByte]",
"renderedValue": "63bd805552e36fa8731e0231f4944069ad0f925382f7a3c80258cd13a4e4d547"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "8214f164efeede6fd1019f636e8045f5118e013fc59c7bea751a5c4a2dff395c",
"value": 2000000,
"index": 40,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "416a18658d6f5538fb1c3f3b10e9083db9241ed1de94df8facad6e933c5dba83",
"outputIndex": 1,
"outputGlobalIndex": 47894612,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e208f556339cfddc339c968633ba2868e97820880b1d33868fbc6496b0688087a5d",
"sigmaType": "Coll[SByte]",
"renderedValue": "8f556339cfddc339c968633ba2868e97820880b1d33868fbc6496b0688087a5d"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20fc5d3316ecd0a67168063836a3979f7cace51acc104f83825b04cb4c6bd905ee",
"sigmaType": "Coll[SByte]",
"renderedValue": "fc5d3316ecd0a67168063836a3979f7cace51acc104f83825b04cb4c6bd905ee"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "5e3e0a5cefb0ad05b63907397c34b938c185128bc2ea45a0fae240e885525c9a",
"value": 2000000,
"index": 41,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "438fdbf9e4631cbd5489dc7339be22eb29c4b904b44d57676e2713ed0a2c29aa",
"outputIndex": 1,
"outputGlobalIndex": 47894617,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e207bc47d6130328253250d90408dc22f3ad88671688b988aff92def2d9a72d405e",
"sigmaType": "Coll[SByte]",
"renderedValue": "7bc47d6130328253250d90408dc22f3ad88671688b988aff92def2d9a72d405e"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20fab5b38794b13c9c3fdf47a47c7245b5a065e942547ee2c01de84fc4beacb7b3",
"sigmaType": "Coll[SByte]",
"renderedValue": "fab5b38794b13c9c3fdf47a47c7245b5a065e942547ee2c01de84fc4beacb7b3"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "bcb39dbd4e1fa7d8a6a9a55bf19f80488ac5a7f85140911d1530cefb28789e9a",
"value": 2000000,
"index": 42,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "4be23c6f8f50280cb5d8986b7d13ee85df90fa871ae81b10b77b071b33c607f0",
"outputIndex": 1,
"outputGlobalIndex": 47894622,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2048a17bba268c94ea3deb5bbee88e887e96f8b616e7c20de563875b5731b72dd9",
"sigmaType": "Coll[SByte]",
"renderedValue": "48a17bba268c94ea3deb5bbee88e887e96f8b616e7c20de563875b5731b72dd9"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20ea49b42521707a2c2f51d75f8c030b2d30424ef92ddbe03ab0db463193a50609",
"sigmaType": "Coll[SByte]",
"renderedValue": "ea49b42521707a2c2f51d75f8c030b2d30424ef92ddbe03ab0db463193a50609"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ca17a34bce9e8072b653618b33a33312d083aa83c2b1585c9378ce146a289434",
"value": 2000000,
"index": 43,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "4e8c4bd5d1dcb1be9466e28ead4e929887d2a9e50a65a0b15e1ff5f1e78f442d",
"outputIndex": 1,
"outputGlobalIndex": 47894627,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2076fe7b26bc1e22b39a7cf5abf7aba094261c41d1d62424440c90ccae31f1b43f",
"sigmaType": "Coll[SByte]",
"renderedValue": "76fe7b26bc1e22b39a7cf5abf7aba094261c41d1d62424440c90ccae31f1b43f"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20f632af113bdbb9be9ea44196400d649213d8e09501b30e22cc34d301c570390a",
"sigmaType": "Coll[SByte]",
"renderedValue": "f632af113bdbb9be9ea44196400d649213d8e09501b30e22cc34d301c570390a"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "99adf5e40b8180743da85d766d438fb58a9bf219560e173eda81eb5c1179f876",
"value": 2000000,
"index": 44,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "5155d76b2f469e79780d07df885aa051141d5a4693f058a2660e28d2375a394d",
"outputIndex": 1,
"outputGlobalIndex": 47894632,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202fc089936114823aafbfb605e317ae8aa01a6d67182910edd02fe97808afacd2",
"sigmaType": "Coll[SByte]",
"renderedValue": "2fc089936114823aafbfb605e317ae8aa01a6d67182910edd02fe97808afacd2"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20f6e2e4a72b16ecd56a7af3e7ae68fdcffd648889f623cdd23f3164eb9451240e",
"sigmaType": "Coll[SByte]",
"renderedValue": "f6e2e4a72b16ecd56a7af3e7ae68fdcffd648889f623cdd23f3164eb9451240e"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "9381a766c91e400665be4dca63ff0828672c54a93abd133c5a26478cc1b4175f",
"value": 2000000,
"index": 45,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "543a41b40851fbb266f1932631781d066d7d117b91a6bec463b91f6a49d053c6",
"outputIndex": 1,
"outputGlobalIndex": 47894637,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20331de059e9cb443c691e5229f84bdf1866c2b81d23d4ff75206ff83f80e6eb53",
"sigmaType": "Coll[SByte]",
"renderedValue": "331de059e9cb443c691e5229f84bdf1866c2b81d23d4ff75206ff83f80e6eb53"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20b20ce606287b6d17da156aa6d6c759c8899815a23ce1ddcee359f1211b0f7b1f",
"sigmaType": "Coll[SByte]",
"renderedValue": "b20ce606287b6d17da156aa6d6c759c8899815a23ce1ddcee359f1211b0f7b1f"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "692d0e879f8ceddb1d4bd03616943aa5b68c781eea7d36ca35ba2ed909ddbb4b",
"value": 2000000,
"index": 46,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "5d40f5c8f13b8304c4df597342b37cccc256cd5d95989da8d355bd31469e11a8",
"outputIndex": 1,
"outputGlobalIndex": 47894642,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20858364154eabe6054583c080acf9cd61a962a4f29e7fd33fa21bf20cf7de6012",
"sigmaType": "Coll[SByte]",
"renderedValue": "858364154eabe6054583c080acf9cd61a962a4f29e7fd33fa21bf20cf7de6012"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e203be5106d022f3183101370132065532f8ff0f1e9d3f03363513e9fcada851979",
"sigmaType": "Coll[SByte]",
"renderedValue": "3be5106d022f3183101370132065532f8ff0f1e9d3f03363513e9fcada851979"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "8d4c0dd9ad51582b0dd5d24d7dad76b5105bc01360e47d626d0cdc6c0e02fec7",
"value": 2000000,
"index": 47,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "5d7c4d5f5a734a255038600028349689ff20c10a60d9372b0e1532498d6025f8",
"outputIndex": 1,
"outputGlobalIndex": 47894647,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201ddc99601073b58e099ee8b99c53c961e5002458f074af83b5fd3ee50da68936",
"sigmaType": "Coll[SByte]",
"renderedValue": "1ddc99601073b58e099ee8b99c53c961e5002458f074af83b5fd3ee50da68936"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20a22182e7281f58d5acb98a6c2e53e5628d005607846066dfa7a1761c51642ebc",
"sigmaType": "Coll[SByte]",
"renderedValue": "a22182e7281f58d5acb98a6c2e53e5628d005607846066dfa7a1761c51642ebc"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ec7f4810d71dcade7d53a4e8444660e1e33f70c3d290ae4abdcffae66c17876a",
"value": 2000000,
"index": 48,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "69f573b15c97fb28b51b283d70be2f785285c354058f0174f7ce9c3e876e6dfb",
"outputIndex": 1,
"outputGlobalIndex": 47894652,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2034fed3111bdb785179a1737743d36109bec01fcf6891e4088ecfea5eeb342438",
"sigmaType": "Coll[SByte]",
"renderedValue": "34fed3111bdb785179a1737743d36109bec01fcf6891e4088ecfea5eeb342438"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20eac91284468486d605a491b8b0586e90a4ba1fa3e9f2e0698c95cce4c8b96a3c",
"sigmaType": "Coll[SByte]",
"renderedValue": "eac91284468486d605a491b8b0586e90a4ba1fa3e9f2e0698c95cce4c8b96a3c"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "6f17f7605a8fab43d8b89424a316fd94e8024256be813350078de0bbe215bbea",
"value": 2000000,
"index": 49,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "6eeb0fb2c010013c3a3e99607cbf95d18115f3aab8fd1cad62e6752809b269cd",
"outputIndex": 1,
"outputGlobalIndex": 47894657,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201966e4439107f92eda6f76b28e209d27d1874351ae81bde2d20b639b0c9ac275",
"sigmaType": "Coll[SByte]",
"renderedValue": "1966e4439107f92eda6f76b28e209d27d1874351ae81bde2d20b639b0c9ac275"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20bb22158624f0d63c40d57fd9a8b0e1c540e1d1b3b933c785ccdbe1ef77389239",
"sigmaType": "Coll[SByte]",
"renderedValue": "bb22158624f0d63c40d57fd9a8b0e1c540e1d1b3b933c785ccdbe1ef77389239"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "21eb3fde3fe5a1194d26f91c2507894ff93738f6ad1b16a892554fec11e174f8",
"value": 2000000,
"index": 50,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "7236e17b92f3fbf8de19d28bc1d7ac99e921949cf8ec09dc3a5a444bdb6013b3",
"outputIndex": 1,
"outputGlobalIndex": 47894662,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20f2e46f2673bd3f3ac486e74a518d32b7bf2390ee6df96e196a4a91e56968457c",
"sigmaType": "Coll[SByte]",
"renderedValue": "f2e46f2673bd3f3ac486e74a518d32b7bf2390ee6df96e196a4a91e56968457c"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20474d5bf8673bc00e1b3285cfb3e21098abf3e6086e5f050ec2e2e55ba47995b1",
"sigmaType": "Coll[SByte]",
"renderedValue": "474d5bf8673bc00e1b3285cfb3e21098abf3e6086e5f050ec2e2e55ba47995b1"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "a2afc9c4ed9d7ff141d1547180299e2f8d18a8ff1729e041973afef2db9d9ebd",
"value": 2000000,
"index": 51,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "7639b72ada176c03d475e2729873f2211f5437205d34d6888399806bd94ce4ca",
"outputIndex": 1,
"outputGlobalIndex": 47894667,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202c8067c785e1cf655336267573e8e5071143bc401fed2bbf5919c8fd56f9aca9",
"sigmaType": "Coll[SByte]",
"renderedValue": "2c8067c785e1cf655336267573e8e5071143bc401fed2bbf5919c8fd56f9aca9"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20386e5f954fada58f8acbf31bcc9f066cf4f96d2b90a36845c862fa6a37e10b6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "386e5f954fada58f8acbf31bcc9f066cf4f96d2b90a36845c862fa6a37e10b6c"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "f2b9815156f008b18e6295cef92f9f1bd4f8a86876e80d63e1307a7311255ecb",
"value": 2000000,
"index": 52,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "7bba8bb4899020146ea4fe1eabaac85ada8ebe0947a3a33d868fb0f67b1ff3fa",
"outputIndex": 1,
"outputGlobalIndex": 47894672,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2030a75690891a9cb8b81c193d1413a0eebf4fba5c4410e073ed2cb6f247154bb1",
"sigmaType": "Coll[SByte]",
"renderedValue": "30a75690891a9cb8b81c193d1413a0eebf4fba5c4410e073ed2cb6f247154bb1"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e208ae79d241865a07bbfebcc3f7d08169d2a54bc0ed29fc9a6b6d66629930ba1c3",
"sigmaType": "Coll[SByte]",
"renderedValue": "8ae79d241865a07bbfebcc3f7d08169d2a54bc0ed29fc9a6b6d66629930ba1c3"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "8aaaffe949167e4db20a921e8c1b243823ba23466028d18bdcf985d52b34c670",
"value": 2000000,
"index": 53,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "8ada2b325158c599d2f44eab848f4e1ff0c1cffac450a5972ec363cc1fd8c7e4",
"outputIndex": 1,
"outputGlobalIndex": 47894677,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20745badfc535a5f16c4c297ad76b925c310e57cb9126e00d8dc09b82d063ad9bb",
"sigmaType": "Coll[SByte]",
"renderedValue": "745badfc535a5f16c4c297ad76b925c310e57cb9126e00d8dc09b82d063ad9bb"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e202b433963311deebf913094e4d0e2abcea34be9a3d4a048a3fb9cfd3114e792a2",
"sigmaType": "Coll[SByte]",
"renderedValue": "2b433963311deebf913094e4d0e2abcea34be9a3d4a048a3fb9cfd3114e792a2"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "f89d859d59a4fa6f1fe8ccd056f351c1aebee42aed7c05d13ea39ac674483fcf",
"value": 2000000,
"index": 54,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "8fd75b52b8fbd5704a423a1604b46959caf21d847fc8589defac9b8078a0d4c9",
"outputIndex": 1,
"outputGlobalIndex": 47894682,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205e8dc156d2bd1824498266c5e9e28895038d90a4bfb2806f071c38fc02933897",
"sigmaType": "Coll[SByte]",
"renderedValue": "5e8dc156d2bd1824498266c5e9e28895038d90a4bfb2806f071c38fc02933897"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20c0fdf07161cc4b5d5b4514f0c012b9af360e9d2e08340ce1159a7b73aa9a1349",
"sigmaType": "Coll[SByte]",
"renderedValue": "c0fdf07161cc4b5d5b4514f0c012b9af360e9d2e08340ce1159a7b73aa9a1349"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "d3cb5b561a0a9594457c14c9156e53df8a0e4a750b20e7316f8c6cb7cd6f5b51",
"value": 2000000,
"index": 55,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "9121cbf32259683faff3d6c20223e0daf80a6988e6cd2e6d69c9f7d14d3623c4",
"outputIndex": 1,
"outputGlobalIndex": 47894687,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2014a952b5ac6ff89703754a6b97e323dd194b3edebc58569dcfe7ec1f49665d5d",
"sigmaType": "Coll[SByte]",
"renderedValue": "14a952b5ac6ff89703754a6b97e323dd194b3edebc58569dcfe7ec1f49665d5d"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20004458e6493411bd3a3da368406fb82e04cdf0019da73f6db622265f668ed683",
"sigmaType": "Coll[SByte]",
"renderedValue": "004458e6493411bd3a3da368406fb82e04cdf0019da73f6db622265f668ed683"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "b7bb595b7e4a27b570d899c70e08f4744a1681181d7525ba86729b10f39a9600",
"value": 2000000,
"index": 56,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "95373ec1e1d022371e94ddd30efaf5ec3b80bb5e0e5bf1058d3087ac8c77466c",
"outputIndex": 1,
"outputGlobalIndex": 47894692,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20936edc0bd9fb9ae481bb84fca9f4d4637d071f7afa95c46368a8617801d0cebd",
"sigmaType": "Coll[SByte]",
"renderedValue": "936edc0bd9fb9ae481bb84fca9f4d4637d071f7afa95c46368a8617801d0cebd"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e204ab337f97918ed2796e30a6325f746f7eeaa4ff8b8b1e66e3b565b22f583e917",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ab337f97918ed2796e30a6325f746f7eeaa4ff8b8b1e66e3b565b22f583e917"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "43a7dba9ba4db85b52d5416a7bacde677ab4b1e6c7c922a1f2a25c27170163a4",
"value": 2000000,
"index": 57,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "9a245f230ea604c688339996e9063045acb17bea4676c7d9e5a7ac8b4d1e6f1c",
"outputIndex": 1,
"outputGlobalIndex": 47894697,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2094cb08d7d7d4fa8c7a73bdecb7d658438442366c3c6f4f7214d43c5df2a05cae",
"sigmaType": "Coll[SByte]",
"renderedValue": "94cb08d7d7d4fa8c7a73bdecb7d658438442366c3c6f4f7214d43c5df2a05cae"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20b090a268b7d102dd8ad19ba59d927f59442c73b94db5f20f187b30236b8b9a81",
"sigmaType": "Coll[SByte]",
"renderedValue": "b090a268b7d102dd8ad19ba59d927f59442c73b94db5f20f187b30236b8b9a81"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "8a19515e0b2e777ee9d0c12a2d39c1fc8b3affccc320f67210ce7fae7136503d",
"value": 2000000,
"index": 58,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "a398d1a5338d4c1ba3f5a80b49b5818ecb0f2ba43e84326b042b03725dd83c5a",
"outputIndex": 1,
"outputGlobalIndex": 47894702,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e208c2a6503b6480ef984b67f085cfdc87b7d29003726ce9e4e726e3f1cf290c054",
"sigmaType": "Coll[SByte]",
"renderedValue": "8c2a6503b6480ef984b67f085cfdc87b7d29003726ce9e4e726e3f1cf290c054"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e203905d430950e4032280775379a9e53a0d7a0d0ead4fc440f28a66450b508ca1f",
"sigmaType": "Coll[SByte]",
"renderedValue": "3905d430950e4032280775379a9e53a0d7a0d0ead4fc440f28a66450b508ca1f"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ad9aa4c93176ac696611ce8b8515d9dd40e500440c6f8bfb2001d69c095eb27f",
"value": 2000000,
"index": 59,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "a8337fc2e92b7caafa41601cf82ab5cd7495c2b4a5d26a6c9d03fd78ab065607",
"outputIndex": 1,
"outputGlobalIndex": 47894707,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20fdcc8cd645392188bd37960f1afd7e1e2cb6a089af3be6c5b8d54924daf5cabe",
"sigmaType": "Coll[SByte]",
"renderedValue": "fdcc8cd645392188bd37960f1afd7e1e2cb6a089af3be6c5b8d54924daf5cabe"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e201f04d6ebbb949e5a40c4719ae54225abf190fcb012059eae3bca1beb097c8d8f",
"sigmaType": "Coll[SByte]",
"renderedValue": "1f04d6ebbb949e5a40c4719ae54225abf190fcb012059eae3bca1beb097c8d8f"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "dd50211001f0681061a2381965b4c3d9f89208f872a54427bd38a8fce7ca85d4",
"value": 2000000,
"index": 60,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "b2e048b7233ecdf973b0c977e407784a3aaffbe97eda7f494ab186590197f942",
"outputIndex": 1,
"outputGlobalIndex": 47894712,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d56cdd51140e2cec1fa0764c9e96645447c93e1ed113c82f5c8629d7e88a33c6",
"sigmaType": "Coll[SByte]",
"renderedValue": "d56cdd51140e2cec1fa0764c9e96645447c93e1ed113c82f5c8629d7e88a33c6"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2060bfabccaf7e0f5b518e487bb46431e5a397b2a0ff939a1affb43e60914949d2",
"sigmaType": "Coll[SByte]",
"renderedValue": "60bfabccaf7e0f5b518e487bb46431e5a397b2a0ff939a1affb43e60914949d2"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "e51920fb5bca01870a5ede5368294a692f100f47ed3fc85c6a93259ae590eabe",
"value": 2000000,
"index": 61,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "bb67311e2bcaf8cb9493d3d8dbb0eade2c5762faebd72d18ab272c65baadc8db",
"outputIndex": 1,
"outputGlobalIndex": 47894717,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "5ivrmzxYZc1s5aYrsy9uMd3wphLaHx4Kqrw7wVDwQdtj967D3qYpAw15uAr1CK4RbXKFW7kersNNe9tXu22iut2zG7tCmAP9TzSNgHMSJFBzR9y7vmqpmTGyFmn6poS81E8MzwaJ2MxkULFoS2nj7CwVsCMGweg84sJShZkGm81jxw6N65GHddQ4sJsBJb6MYFcVXeLxrgnEMPd3eFH7XoVj5uM97P6rsUAztZmeaA9hdUkc9Bz497j5BKQaiXyrFj8ghEtL1cemwfnGrsybkuq132QT9qsW7dNaG95D5wSYNUoAP7mVcziPas1PvEa5xRgMKnvE4ByYPT6BfkAMijYfXSDLzi1EbksurZGfC6jX7jfSgwuugXMNbjrUwhzj6657H9MsytUxRW8kNUKN7mwUphQGFS3nWLG4hzyas5BF8MnK7usWD7MJko7FaUWwNPVrRdatwB5uu6rUrY8UeAW9DPQMrL6VZWMKMWFmoY722pVYHdMdCsehR3CnsRDGDpZtvdqJnGgn2czeZ4AfK8o6aykw3HMTvNP2e6pxNt6FYgr2WZhbXsmeqA6bG7t9JNCw6H7tA8KJPAN1X6CYeZMitX5RWCrMtrSy2NEDepNvMgH3n4GD3tvS5Rs94gFVWHfLu4JM5BaTwfRTcdfirnwPQhYhtH6SEc8b5SgGkraojn4JgkKGp2ftszDUNyaKrY8XJQusuMG64Aoe96wr2AaRKKtUhAKfk7kUXHtGoV3h4MhDy5Wnbgb6hXcmQoMQ8HnT7JMAFWUUeWyveNn3hdNucDf2WtmXBsRpwUidapBJPD9Xukw6uEsWdkzsCNcdhZM4EqnkadRKziCubVx52TYoxDYqupyLssPc6JdaLUWny1Nh2vsEdnuNYXj82iX7AeJRaHJeyn8wytA7G8NwQXp2THTniwF6hPCWTub5khfdJ2g4VDTv14GRL88NA6w49N5FaG2ZWxqgRKYxbEJqgBE91KWHoXfsB4qvo6cGfMwpeJU5g6FTiexmXZqrNpRwmnnx1NTGK4TdqnksfaXZPMfPBbdJnQu1vfGwLuMkP5f5EvyfQ4KzazA67AxoabFYkKJk4pvVkRqaWUps9b3nkZhErUMAgxYR4raNtKHSUT13c9RMaGQmtV8viR4b7Z2JoKjqiEP9xGVoZBANhDpJ3EpihvRmDuy7MAZfy1qEm59spvdgdPPEiffw8GBv9MyDfsAGNSzsMhiP1f8WKXduWy7AdEJZTrBJkLZFPTaRHHyU9XvbRyzrxhV87thVrfRhv88hN6Viw2CyRdMJUPmVt",
"assets": [
{
"tokenId": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2024561a79bddd066a10f354bb8579ce2b0f0b97d1d3088205cf9f3cefe9bd069f",
"sigmaType": "Coll[SByte]",
"renderedValue": "24561a79bddd066a10f354bb8579ce2b0f0b97d1d3088205cf9f3cefe9bd069f"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20dc10987046ef8dd4f3cf7bea23a2e39ca6bbdaa09799faf05462170da8eaabde",
"sigmaType": "Coll[SByte]",
"renderedValue": "dc10987046ef8dd4f3cf7bea23a2e39ca6bbdaa09799faf05462170da8eaabde"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "ad3a533e85002c814258eea10c6516c6c353177b4b05c187664f31a0a320264e",
"value": 2000000,
"index": 62,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "c15d7702b3a24565ec178e1b68419d0adf027a65d2cadce49adb653288d29fe4",
"outputIndex": 1,
"outputGlobalIndex": 47894722,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ec9b08822c5093f714f75a898af6ecff7263e9209fe155b2eff730d6983be622",
"sigmaType": "Coll[SByte]",
"renderedValue": "ec9b08822c5093f714f75a898af6ecff7263e9209fe155b2eff730d6983be622"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2034be88a14ac2dc5142ce0fca739275bab703eb32c36808a3346ca03b53011bf6",
"sigmaType": "Coll[SByte]",
"renderedValue": "34be88a14ac2dc5142ce0fca739275bab703eb32c36808a3346ca03b53011bf6"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "cf287b9f41d4a1decef3eb4cf240964240e208d44931c32df5dda60b525a5f15",
"value": 2000000,
"index": 63,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "ce2ddb8ecd0b79f14bde7d03dc5d57de3373263ed4f8b56f69c8694841c87cd0",
"outputIndex": 1,
"outputGlobalIndex": 47894727,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2097a42eaee75fe6cf3cdf0df471b4439b630bc909a2cd49a16b4029570db522a4",
"sigmaType": "Coll[SByte]",
"renderedValue": "97a42eaee75fe6cf3cdf0df471b4439b630bc909a2cd49a16b4029570db522a4"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20ec62846dcfcc1d6be12e4b76e233eb7e338ed00fa0db5273b8ae87924bd627ec",
"sigmaType": "Coll[SByte]",
"renderedValue": "ec62846dcfcc1d6be12e4b76e233eb7e338ed00fa0db5273b8ae87924bd627ec"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "a94f2dcc5f2f66d9cea1a73920ec58dee579d9f7f04f5994d71f9fe6998cfa31",
"value": 2000000,
"index": 64,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "d298fe20ff6f5dcfc0ffde0e33c28f8efcce2395fa24d886640c8391bdc04da5",
"outputIndex": 1,
"outputGlobalIndex": 47894732,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202ab1c00b4fb07d620ba86addd523a7287c98fc4a933f009a130f1467a6bc49a0",
"sigmaType": "Coll[SByte]",
"renderedValue": "2ab1c00b4fb07d620ba86addd523a7287c98fc4a933f009a130f1467a6bc49a0"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20e1cd31edba126601c5b72473a1fc5abfa947aaeef1309645cb482578ff228ae6",
"sigmaType": "Coll[SByte]",
"renderedValue": "e1cd31edba126601c5b72473a1fc5abfa947aaeef1309645cb482578ff228ae6"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "f22b87a264177f44fec3b5d7720e2ac083ec2ae51778687911ec3d0dc2f944c9",
"value": 2000000,
"index": 65,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "d629176d9e7528f8f847752156a0690b3c1313d3ef375f0dbd042bc617380008",
"outputIndex": 1,
"outputGlobalIndex": 47894737,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209ca7b72de501ababe6cdf726447497fe63612dae437fc1e3e69aaa55ae8914c2",
"sigmaType": "Coll[SByte]",
"renderedValue": "9ca7b72de501ababe6cdf726447497fe63612dae437fc1e3e69aaa55ae8914c2"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20c6ced896835dbc22ea6abc55c909550d7be59931a573bdfcb49e395d27dce0fa",
"sigmaType": "Coll[SByte]",
"renderedValue": "c6ced896835dbc22ea6abc55c909550d7be59931a573bdfcb49e395d27dce0fa"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
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},
{
"boxId": "5f77453ad26f90b7a813d9029d81b281a1d0077a3afce28530bebc7ec7c49b32",
"value": 2000000,
"index": 66,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "d7ea93366fdcb367f23cb906af9e65503df1bc075e2401e806f1ffcb039ac0ad",
"outputIndex": 1,
"outputGlobalIndex": 47894742,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e2067a12c71b7dbf55988018c76119a51c1fc80ef9dc824fceceb60dec321d594be",
"sigmaType": "Coll[SByte]",
"renderedValue": "67a12c71b7dbf55988018c76119a51c1fc80ef9dc824fceceb60dec321d594be"
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"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2092b22644409054094f8b0a7682289a8388a5458323e646444ed02017d769d0fc",
"sigmaType": "Coll[SByte]",
"renderedValue": "92b22644409054094f8b0a7682289a8388a5458323e646444ed02017d769d0fc"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "38f3f9f063250c570f5fbb040c8f069d211ff6e8d54261dad1da944ba3fc79f7",
"value": 2000000,
"index": 67,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "e5f5c78ec0dd3b41d37713553bc15769781d20c4aa230bef2794e9bba809cdda",
"outputIndex": 1,
"outputGlobalIndex": 47894747,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20235a5bed6e9763ec430316fdb60d361bdf5087273a3ffa29132272f9c654dd97",
"sigmaType": "Coll[SByte]",
"renderedValue": "235a5bed6e9763ec430316fdb60d361bdf5087273a3ffa29132272f9c654dd97"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20dbdc092d54d5e15a7eff6d91ecbe70ceb21528c3bf15910706f23a155a36c38b",
"sigmaType": "Coll[SByte]",
"renderedValue": "dbdc092d54d5e15a7eff6d91ecbe70ceb21528c3bf15910706f23a155a36c38b"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "8816fc3800c2d6574390c000761500e418b00c867069c196f10cf6bc303d4944",
"value": 2000000,
"index": 68,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "ee63c7c461cd20876264b5ab8bdbce2ffdb550488ccce890882443ce14f97e9a",
"outputIndex": 1,
"outputGlobalIndex": 47894752,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20d4cde4088ed357a90cc7a28ca8de11c6906bfd6c014c83741b45ee6e12fe02cf",
"sigmaType": "Coll[SByte]",
"renderedValue": "d4cde4088ed357a90cc7a28ca8de11c6906bfd6c014c83741b45ee6e12fe02cf"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e201dcba619018932309fdb2c4b6f9d2535f02b7e8e593fb88283438e00a499112a",
"sigmaType": "Coll[SByte]",
"renderedValue": "1dcba619018932309fdb2c4b6f9d2535f02b7e8e593fb88283438e00a499112a"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "50b3d5e4c41cc828da44de6562e1b64f2915daeb031505dd25c04542534dbfeb",
"value": 2000000,
"index": 69,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "f13e5f0e95ddfc9ca0c244327e0fae96c97b1c7088f44fe8caa5c7389968976c",
"outputIndex": 1,
"outputGlobalIndex": 47894757,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20a4519b89da8f9b667e60508ba8e130555c9ee095d543e867f5048c33a2273a28",
"sigmaType": "Coll[SByte]",
"renderedValue": "a4519b89da8f9b667e60508ba8e130555c9ee095d543e867f5048c33a2273a28"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20f14e614dde44eb58b4af620ab5a3904bb92cb0393755fde7aedade6268602848",
"sigmaType": "Coll[SByte]",
"renderedValue": "f14e614dde44eb58b4af620ab5a3904bb92cb0393755fde7aedade6268602848"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "2a50e5197b5ed7366834676c6de4a335478a4b449b4308d721a21ecb4883406f",
"value": 2000000,
"index": 70,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "f592b9437aafad52198847e4b188f1141b8409c007b25ca8045325d3d8f65fa9",
"outputIndex": 1,
"outputGlobalIndex": 47894762,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b97e0b376b0fc040280d09fcb01a2df3197adca29169647b16e41fc032932ea8",
"sigmaType": "Coll[SByte]",
"renderedValue": "b97e0b376b0fc040280d09fcb01a2df3197adca29169647b16e41fc032932ea8"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2018cce99eff41824f4ae5fc6847a62ac1c1f4305ec707a3590aa4115b1e6df0f1",
"sigmaType": "Coll[SByte]",
"renderedValue": "18cce99eff41824f4ae5fc6847a62ac1c1f4305ec707a3590aa4115b1e6df0f1"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "12d31444206a71888376b24d4cfc66de8b95cfeca5671661a92c6a57c3be68dd",
"value": 2000000,
"index": 71,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "1cfef1c4da57bc0108490a107ad80bbf15ae814961b56f6b2111f9a627864622",
"outputIndex": 1,
"outputGlobalIndex": 47894767,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e205f3ebc8b1f39374e2a78d4f6608a3c49ba816392501df9209976c9ad8091fe97",
"sigmaType": "Coll[SByte]",
"renderedValue": "5f3ebc8b1f39374e2a78d4f6608a3c49ba816392501df9209976c9ad8091fe97"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20236f1ec218b22a7ebccd3d19af278f13ac3597372e54b9488e086c7d0fa9e2e4",
"sigmaType": "Coll[SByte]",
"renderedValue": "236f1ec218b22a7ebccd3d19af278f13ac3597372e54b9488e086c7d0fa9e2e4"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "e364e5e5ca0ac60087800549df6349d786a622c6c35225489d048ccf112e94dd",
"value": 2000000,
"index": 72,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "4433deb204e950e3de2b86dba9bd3dc9147f285be235007d0a3a98169cdaf8d4",
"outputIndex": 1,
"outputGlobalIndex": 47894772,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20b1719420acbc1261e2e413a586a11a52a46d6b446c7f761db25220a1a1b9290a",
"sigmaType": "Coll[SByte]",
"renderedValue": "b1719420acbc1261e2e413a586a11a52a46d6b446c7f761db25220a1a1b9290a"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2058bbdb265495ec8088813ec2eff451f74b5321e22f4057d01515e43e010f2014",
"sigmaType": "Coll[SByte]",
"renderedValue": "58bbdb265495ec8088813ec2eff451f74b5321e22f4057d01515e43e010f2014"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "6540cf23d28e1a97e37155b7a3333af341350b7eed05a3b2db3db79e3d2a404a",
"value": 2000000,
"index": 73,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "5baba57e54420572434339e9069450be21e32062a12f6317f58bc5e114455e8f",
"outputIndex": 1,
"outputGlobalIndex": 47894777,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e201ee6648479ea616040dc8c6d82e9676ca9fdca21454b0aeb2d00f80a4dc843ff",
"sigmaType": "Coll[SByte]",
"renderedValue": "1ee6648479ea616040dc8c6d82e9676ca9fdca21454b0aeb2d00f80a4dc843ff"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e207ccb12403204e7ec86058858c55f1c1574a2746b26f82d72728975bae836dce6",
"sigmaType": "Coll[SByte]",
"renderedValue": "7ccb12403204e7ec86058858c55f1c1574a2746b26f82d72728975bae836dce6"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "f8dc3bf57e0e443a32782f668dabbe6d81a1c1f7fa186af3d24a2c5cb4532602",
"value": 2000000,
"index": 74,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "67520a079ef1be885baddfaf5d38f1354839c0e24f39d6ee87f9805f18b16a7e",
"outputIndex": 1,
"outputGlobalIndex": 47894782,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20ae560ab6a7a5d79e75fad539789f2d995c03e426663beac1754bfc95e1155d6c",
"sigmaType": "Coll[SByte]",
"renderedValue": "ae560ab6a7a5d79e75fad539789f2d995c03e426663beac1754bfc95e1155d6c"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e204ac77b4c2dd00c672dd09dab618a1799cb6e1e3f7fa7be57d72fa58ecb1d619e",
"sigmaType": "Coll[SByte]",
"renderedValue": "4ac77b4c2dd00c672dd09dab618a1799cb6e1e3f7fa7be57d72fa58ecb1d619e"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "328bcf1f1922680e05a08c5fd660197a1b0d698db673356e87f600a722656191",
"value": 2000000,
"index": 75,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "85ff2424fae5ed48ab0b62c7b8ee8f3e11c9e4b815d3f2687eab04a89512a0dd",
"outputIndex": 1,
"outputGlobalIndex": 47894787,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e202cff108ab0b917e019171f059330ba7b3a05c4fdeeade47383f5892cbee92259",
"sigmaType": "Coll[SByte]",
"renderedValue": "2cff108ab0b917e019171f059330ba7b3a05c4fdeeade47383f5892cbee92259"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e20ff4d9bb85a86d21080e74cc875c86ef2d55b2a227bc59761dca8f46b9cbabb0e",
"sigmaType": "Coll[SByte]",
"renderedValue": "ff4d9bb85a86d21080e74cc875c86ef2d55b2a227bc59761dca8f46b9cbabb0e"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "6d765f161fbe30c9a36bfce39d9b832a9c4140d9209c047437448e05a9be521b",
"value": 1010000,
"index": 76,
"spendingProof": null,
"outputBlockId": "9aafcf9f57736ff62ef298b7e9b0b48c0b269530a1ddd766aaf2af01014d8c60",
"outputTransactionId": "14330def83906c5c5d316b32c58231af980cc3d7a4349bc431abd591be927711",
"outputIndex": 1,
"outputGlobalIndex": 47894792,
"outputCreatedAt": 1525838,
"outputSettledAt": 1525840,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(67,-52,97,52,-65,-98,-95,-63,-18,-30,99,-128,-69,48,77,88,67,2,23,-54,87,-103,54,99,86,-127,-112,57,-92,90,-68,36)\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(55,-86,108,108,65,74,-123,-111,43,55,60,-87,-93,-85,-24,-118,41,-71,-57,56,-87,-63,-78,-65,-122,68,-63,-99,-19,-64,-100,-32)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 3000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e20baad4116c4d4763e7760092c95b87c1a9186abe5c13b3274967886e1b2f4d49b",
"sigmaType": "Coll[SByte]",
"renderedValue": "baad4116c4d4763e7760092c95b87c1a9186abe5c13b3274967886e1b2f4d49b"
},
"R5": {
"serializedValue": "0e209f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f9b14a5b530a5c116574181adebf1a1e16f953d1ffdbbce1c7eb65871ca9c0b"
},
"R6": {
"serializedValue": "0e2097a17cf1b8fe861636b5d504bef65c2c33e644d81a15a0e0d213879acdc959ae",
"sigmaType": "Coll[SByte]",
"renderedValue": "97a17cf1b8fe861636b5d504bef65c2c33e644d81a15a0e0d213879acdc959ae"
},
"R7": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
}
}
},
{
"boxId": "14c248c5b9ac1a09cd95e0ea62561137bb535c75a8afad78f9c6f8064f854d2c",
"value": 3291585031,
"index": 77,
"spendingProof": "857af4955b1f436fd52164f15ba50dc46e3437952cddb254a10b452593a02c9629d7ad5920cedb9271eab2fc9cb75177edf4ec9a0897fc40",
"outputBlockId": "eff6544ed1c6b522464a82b357dccc28891f4d0b75935da42a051ae0208739d1",
"outputTransactionId": "85aa854fca3da33058b08c74cd0c37f47990736cf8af9f920248cf993feb0ec5",
"outputIndex": 2,
"outputGlobalIndex": 47894208,
"outputCreatedAt": 1525828,
"outputSettledAt": 1525830,
"ergoTree": "0008cd020b3b4e78e8fe3738a976679fb21c68e03c20066a179ebfb3392a0f60d6ee4409",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b3b4e7,447d43,...)))}",
"address": "9ec1Qu82zUCKzvCaAp5AQU4yu8W28ity1iNfRHnUmTRXPTgD6GN",
"assets": [
{
"tokenId": "3030527c8fc3b92734b408d82f1c27e71e929fdfcd3938771f5877f456dc2d53",
"index": 0,
"amount": 3,
"name": "WID-c2d53-PTgD6GN",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 1,
"amount": 1000,
"name": "RSN",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "5f2dcf975ff3e35d29c89b9d05764b74d68f5e700ae165a0ea427df7e7275e13",
"value": 1100000,
"index": 0,
"outputBlockId": "9cd9da9a7bebc91af8af522b342397f6f0cb88719817b60aa0cb53a9758daccf",
"outputTransactionId": "a0029995fad90f6b31ac46d0ad4e823a8349c16a413f885c829c74a840107a3b",
"outputIndex": 3,
"ergoTree": "100604000400040004000e2055bf993b4376ba132264d084f06fe033321ab43c68db1435a0e7e0bf77ddb7350402d803d601b2db6501fe730000d602b2db6308b2a5730100730200d603b2db6308a7730300ea02d196830301aedb63087201d901044d0e938c7204017304938c7202018c720301938c7202028c72030298b2e4c672010510730500ade4c67201041ad901040ecdee7204",
"address": "prufxZid3SJMyUVhAPFAF4uLyCZbEMWCMXRSyuMEvDUHZf81JcGcmu1EW1U9hUuJerWer5vmjhiJMmjbCqDwPMKRy169SPaLTxDp5tZ2rCrKjiv7xVAsnmphxSNBpj6qqB8fs1rWJGn9dN7t74qvx6oVHZny8KNMrqfEDjcWRv7wP21sZFP4rie4YhWJs8Z6swQ3DA28B5bzMZkMqfR7",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1106809bee027802c8018080babbc82e808ece1c",
"sigmaType": "Coll[SLong]",
"renderedValue": "[3000000,60,1,100,800000000000,30000000]"
}
}
},
{
"boxId": "5ad597c0983cb5767cfc0cecfb2957fefbb1722df69f9325d0af52df72f12ac5",
"value": 2000000,
"index": 1,
"outputBlockId": "e480c4bb1eed2afb5cf0aa286852c8110c65671da0bc206944c2efb9707af83c",
"outputTransactionId": "207daed9a7234736e461580298dcd36370abb16ba26d8e1bd404ef2f539b8d87",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "0e0763617264616e6f",
"sigmaType": "Coll[SByte]",
"renderedValue": "63617264616e6f"
},
"R5": {
"serializedValue": "05be01",
"sigmaType": "SLong",
"renderedValue": "95"
}
}
}
],
"outputs": [
{
"boxId": "31fe9b2b0e6f3d17b9b8eb8a9568f8a7a736bc29bea433bb1090d1193558f51d",
"transactionId": "7329c4336150693739456adedda400e3e3ecc1f8f22e0fb257e1039ba5e7490e",
"blockId": "7da0b6fc9e3a9b5b92341ff79c31f1fceef779fd8bb053cf040680d5da1181eb",
"value": 152030304,
"index": 0,
"globalIndex": 47894926,
"creationHeight": 1525840,
"settlementHeight": 1525841,
"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(-100,-40,-42,8,-67,7,83,-112,71,-26,-32,-54,31,-35,-93,-73,65,-83,76,86,-26,119,89,-19,-69,113,-76,14,86,-43,-62,-5)\n10: 1\n11: 0\n12: Coll(11,58,-99,21,-105,-66,-75,-57,-86,-62,-54,-90,83,-28,-96,63,76,-36,59,117,-72,-53,-13,9,-127,37,-99,-30,-4,115,113,104)\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": "ddb335d2b4f3764ddeae8411a14bec97f94d0057628bb96f98da9d95e74d02bc",
"index": 0,
"amount": 231000000,
"name": "rspv2CardanoRWT",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e206934c4d36a26aaf5ffd6b86c31afed01300a73b1587f369470cddf87b3edcf30",
"sigmaType": "Coll[SByte]",
"renderedValue": "6934c4d36a26aaf5ffd6b86c31afed01300a73b1587f369470cddf87b3edcf30"
},
"R5": {
"serializedValue": "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",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[34393965326666646262373935383034323535376461393066316332323733323431353430356162373565306238323161336461383235346332623038626239,63617264616e6f,62696e616e6365,6164647231713934793561756165617330646574306d7572373075383777636536303766306e353464666678343833323268737532646c79796b663474366132703467707877326864373236306c36617a37706b70336865716c767276783865736579776a3867,307839383165393063373863636462333231663036323934333632613730373934393134363430633038,000000a2fb405800,0000000111dbd255,0000000001ab9839,62376335636435353466336538336338616130393030613063393035333238346135333438323434643233643034303663323865616634642e35303431346334643061,307835303261363431646563666533326231653364303330653035656666623861653531343665363462,34356232306136343834613332663865373336316166643933626466333962633465316233383765633466343339666265383563363961363633663236393437,0000000000b51cea]"
},
"R6": {
"serializedValue": "0e201d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4",
"sigmaType": "Coll[SByte]",
"renderedValue": "1d2ba7e16dd669c06646f3541820f8c45b8f6795c573506830a0c9b6cc58f2b4"
},
"R7": {
"serializedValue": "049a01",
"sigmaType": "SInt",
"renderedValue": "77"
}
},
"spentTransactionId": "91a3f53be5341870d08ebbf5d8a7f3210baee24b71a5fce37993019e05242373",
"mainChain": true
},
{
"boxId": "ae7b9f28908368ba91c0336331b91f41d581ef6f14d5bd2138a16c28d2ab1c29",
"transactionId": "7329c4336150693739456adedda400e3e3ecc1f8f22e0fb257e1039ba5e7490e",
"blockId": "7da0b6fc9e3a9b5b92341ff79c31f1fceef779fd8bb053cf040680d5da1181eb",
"value": 3289535031,
"index": 1,
"globalIndex": 47894927,
"creationHeight": 1525840,
"settlementHeight": 1525841,
"ergoTree": "0008cd020b3b4e78e8fe3738a976679fb21c68e03c20066a179ebfb3392a0f60d6ee4409",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b3b4e7,447d43,...)))}",
"address": "9ec1Qu82zUCKzvCaAp5AQU4yu8W28ity1iNfRHnUmTRXPTgD6GN",
"assets": [
{
"tokenId": "3030527c8fc3b92734b408d82f1c27e71e929fdfcd3938771f5877f456dc2d53",
"index": 0,
"amount": 3,
"name": "WID-c2d53-PTgD6GN",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 1,
"amount": 1000,
"name": "RSN",
"decimals": 3,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "a6e20d17ca88237a3280adfc72a2d2992506450d8dff060146c9e2d760fa6271",
"mainChain": true
},
{
"boxId": "99e3a6f88c43daf6cb7c7831802aa178027d562b895fb6ac2307bdfb8fc138d7",
"transactionId": "7329c4336150693739456adedda400e3e3ecc1f8f22e0fb257e1039ba5e7490e",
"blockId": "7da0b6fc9e3a9b5b92341ff79c31f1fceef779fd8bb053cf040680d5da1181eb",
"value": 2050000,
"index": 2,
"globalIndex": 47894928,
"creationHeight": 1525840,
"settlementHeight": 1525841,
"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": "3d81cc42af082022327eacfa6f3630f8426c3092fe875690b2d22c71f59c3b9c",
"mainChain": true
}
],
"size": 3938,
"isUnconfirmed": false
}