Transaction
ID: dd77f6952f...99f3
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
14.13 ERG
Tokens:
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Outputs (15)
Spent
Address:
Spent in transaction:
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Value:
0.015 ERG
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Spent
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Spent in transaction:
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Value:
0.015 ERG
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Spent
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0.015 ERG
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Value:
0.015 ERG
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Spent
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Value:
0.015 ERG
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Spent
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Value:
0.015 ERG
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Spent
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0.015 ERG
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Spent
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0.015 ERG
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Spent
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0.015 ERG
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0.015 ERG
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0.015 ERG
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0.015 ERG
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Spent
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Value:
12.14 ERG
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Spent
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Value:
1.8 ERG
Spent
Address:
Spent in transaction:
Settlement height:
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0.005 ERG
Transaction Details
Confirmations: 696,247
Total coins transferred: 14.13 ERG
Fees: 0.005 ERG
Fees per byte: 0.000000253 ERG
Raw Transaction Data
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"sigmaType": "SLong",
"renderedValue": "100000000"
},
"R7": {
"serializedValue": "110280dddb0180fca402",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1800000,2400000]"
},
"R4": {
"serializedValue": "0428",
"sigmaType": "SInt",
"renderedValue": "20"
}
}
}
],
"outputs": [
{
"boxId": "edb5c3d4f09b2c3401b537683ac2522e37091ced97c9bcd1abe56679e7b3c0c4",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 0,
"globalIndex": 31851024,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "3NtW3QbiLwaF7f2h7NyiFZwSV3LqNwFNBH5HQgzeGtttvsLCS4e19bjkpDbuNbzBXtjvK3eyi94G9YNjeR94F4ix5iAXHSwmSsZ2ftbMCBfxf9JfgouBAvbrcKoDnioJmQdTfQLi8ubzsnzfi3aCE9sV1mXLxob6Dto5XCCGhuBXEB631qRpxaWkASSpgwHhAJdJQcM1ikTtfTXcVmx7n3rtQ83i1xvb4zaJYHA4SGBwT4je2dFd27k8gRpvTgk5RbxxzsiBTpdbyB1a2eEfHfyQztYrC7NPD6M94aiHKtfzCvXjGZPpFohMLsdV4H8yggtqeiay3Nxj2MctjkyTWfKkr1dbWit9bHGyT58fXMpPbBr96NQfZsPNgWFMpusN2VJo9LyMFaGZYZgDyzykTuD6UvwfC2GBLuW1bk12YvuTbqhszbxVaWjf47Kzm13xkotdseL6a7NTULKFbFv8uLUVindCiqu4Gbv26V6kh9xCSM9vPvbqw67uH4QXUcj2N2THFS8CjZkatjHBQhMzDngiAyd8jKfhqa9w6N87S2jJNnZoKT87tKqLXA5oyvVfz4BNFqhHANfGfrQvAXLfoiZ2nCRyYYcy1BCvQ8TWiwf48MPuhKcipa5UdrndgAe7EZrVB3SbFnP7a3KfHkX36LfZBxbH7V2g9C3a9JnkkFhAFM1wfBYrvbJbSN8siGqEusfPh3D6UFAwNNN9aAKiYXZE3H1u4zVb8trNawRp7Ye3Rr8bTBEqX65xs1jpdZCzHUzQMikjBsUaRrCtkWut3PEtmVeQXUVRKwz2eYFaE4sX2zUuMuswKY911Lw38jNHcmUdwXYXCEEZNGY4b2LbMjyMpFHcnM5PMdoAPtx21LTB2oSMqGGcDPr5kigNeYUacjxEjimhMSnxYiVhnoQPKjftvzJwtvdT55fewwLGcRUDP8Koa31pkjubLtpPbiXCyiZ4iXZ2c1M82Wpxsb6EpGvkuhm5iiUi6Kdj6Ya4fzJhmgZLJZu57TxxTr1AB3EfH4AYqnKhrJeBwb5jcv5YD8vtWVeZ53wDaBGyEgkCZxZvgff4rkX2yBu3pCpQZheTxUepQzykqNJck3Y2gMJcC8nxYyjbtpgckReo2LT4bZi5DKsyv6QNWruenSEd3KavrMuyaiBu3LFxxvKwGJFXfZiEku5pALnbi15npqHuxhmwXwhbQFXUVfwviHsJH71qY889oQjERkweQkEB9AFk8hkkLG5aGyWruGLJa3546CPc6Zvbqwt33CZGbpo7jcuuG4rP4G2dpefASG8H45A8NeiGcQq3LXCvAw9MyzLmkVpvFG71nqurqdJCexWcawiLC1QiQwis4AFn9qgf4TLNprpAHPWr1nYAXa78f8DiXy5ahCNjArVq1SdseuFG3S1aoCEP8hbTWmHzBeRmJVsGhJXpNi2h9UiePxWsBBzVm5usMpsaBuckmxxXJyQAantCqFCVXcB71ZLi3pUjTYv2E4Ldf8QEjuSHMqmUv8HWvUudHRiPpCnqoyxyzjQtjbbcqAaSo7zKF1i3d6swUQbcjyULQTkL2oPwYy6vB7yenYXrCEWmyV85iH3wdYzdJj6CYoD5vRKAoNh1kMxZ82nkyB7KoCqr3AePVdSoWned8LMURXdGDdGCpVr7QtcHBL2E3RY4A3drPYpc1DWct8gwPGbowLJkHLNhPwsxTuLReLuotmT7Gheyd6NYUFtz1aWM516uNdDDg5bEPGXzJAGEx1UjZArrStByZcMKRDYVMG6NtNjLvDJCZEvLgBRG1Bi79mgBBbV75",
"assets": [
{
"tokenId": "2131db395f674a0b0766bd0a8de101e1b25a6ccec1b5e2628d44ed1f6a79f643",
"index": 0,
"amount": 1,
"name": "Peperg #96",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "716a71a59c656a0da1a486a3e8af9f7111ef1197bc168404c5e3a1119b3698c7",
"mainChain": true
},
{
"boxId": "277f25da1b74bb2a1f6c6e55dc7dc63f1f62e8c89ae4e4c279e0be8a17690c1e",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 1,
"globalIndex": 31851025,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "3e493e7d12feb5232a23f95b9e6171a82f9a0f5fd5051de3d61f3f5e9349e6a7",
"index": 0,
"amount": 1,
"name": "Peperg #107",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "ccc4326436603f832fd7457abea1804fe4bfb2e2f0b52a475388c8740839ff08",
"mainChain": true
},
{
"boxId": "4c9f4f1303ecda442837405af95dbe66c615028debba693bdf4ae4c824574333",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 2,
"globalIndex": 31851026,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "0f0555a4aef95c644578f99dc3194a1d764b6941c73b08ff55ce5e884d1214e5",
"index": 0,
"amount": 1,
"name": "Peperg #89",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "3e708f21a25054a04b742aec824d5d696ee949da0e460a17d1cca69357859153",
"mainChain": true
},
{
"boxId": "8521f80c2feb789091eaacea233ba7ef48c98fb273453ab5bf2799225e40e56a",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 3,
"globalIndex": 31851027,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "64aff47cad39d2c8e1d63b601377d5af8b3db9a060b92232d46b97b2435aecf4",
"index": 0,
"amount": 1,
"name": "Peperg #133",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "8e6a492a45b85b9a800c611d05073190b2821be1bd9a9e2e1ffee3ae38588e40",
"mainChain": true
},
{
"boxId": "19fb3161b2da66715c34086ff1037871ffe7465f8f94fc919d10570e8d7943d3",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 4,
"globalIndex": 31851028,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "511af343e83b0df471cdaf0dfcae5021261a687026b21f9f719df6a34fcc6688",
"index": 0,
"amount": 1,
"name": "Peperg #103",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "c08e8e0143e7182a580a1821665e5cf54489998765c51c674ec2fb04fb366686",
"mainChain": true
},
{
"boxId": "301779bbfab20f6e0f0b7ee47e73b7b5cfdccc8809faf41a8f1a1823a38d1442",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 5,
"globalIndex": 31851029,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "49ee67dd421e372b807921f125f0182a7d60510e003429264a27f632c3909889",
"index": 0,
"amount": 1,
"name": "Peperg #56",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "f70161177cf89cc5b96544a3ab0093f7a8ccbef426226d36ce36dcef3950161f",
"mainChain": true
},
{
"boxId": "e5bf54a53036816b71357571ec07fc0e38abb8ce7276a29a2519664c549bda60",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 6,
"globalIndex": 31851030,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "94c927e7021b9ad11c7b91e9a55b9349da49e4908c437dad84cbad0c7c78191f",
"index": 0,
"amount": 1,
"name": "Peperg #61",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "e5a996d0e40fb2e3b275086d965ef54f78ef1929ab184599b5a634d42025ac6c",
"mainChain": true
},
{
"boxId": "8f287d44f182c6eb4a9a9b727e5d6e15f0af3f3684dba5e0d470e7689cda4842",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 7,
"globalIndex": 31851031,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "80dc7f7ddee570ade67cbe3c3aa47f3125f49434ba75f54ba3c94286c2a1a5ac",
"index": 0,
"amount": 1,
"name": "Peperg #95",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "48a4c60e3409f62238557ceb9040ab62095555c0ad6f5f15a10b549b370ad8b4",
"mainChain": true
},
{
"boxId": "468ee109a64a45b4d7f48f283b1a57b618b1eca9ebe6b74c12633e61e6d7bc94",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 8,
"globalIndex": 31851032,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "8f2610a2a03dcf9ff1dfd9afb47f8b2bc3420cb38f056b6b89c544310450b474",
"index": 0,
"amount": 1,
"name": "Peperg #114",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "bfb8b9aec88c527994ddc0329296973bc7e9f7652384f18104f83f84b6dfb834",
"mainChain": true
},
{
"boxId": "34b1c5c72f8d35f9e6cc5b9f8d966d1d6b86cc5e238d0e5348143dd962fb1d08",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 9,
"globalIndex": 31851033,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "103f040204000500040405000400040404000402040004000406050004000504040204d00f0400040404140404040004000400040004000406040005d00f05d00f05d00f0400040404140406040005d00f040405d00f040004060406040005000100010104000402050004020400040204000400040004020400040204040500010004000e209ebcd694bf34db4ee3e2ccea0087ca42970743b9e019a1e8d145e8560467c60ed81fd601db6308a7d602830002d603c1a7d604b27201730001860272027203d6058c720402d606c6a70611d607e47206d608b27207730100d609e4c6a7070ed60a95ec8f72057208948c720401720973027205d60b8f720a7208d60ce4c6a7040ed60ddb6903db6503fed60ee4c6a70559d60f8c720e01d6108c720e02d611b272077303017304d612b2db6501fe730500d613e4c672120404d614b2a5730601a7d615db63087214d616c17214d617860272027216d618b272157307017217d619b2a5730801a7d61adb63087219d61bc17219d61c86027202721bd61db2721a730901721cd61ee4c6a7080ed61f93c5b2a4730a00c5a7ea02eb02ea02d1720bcdeeb4720c730bb1720cd19591720d720f9591720d7210d814d620ec92720a7208ed917211730c92720a7211d621b1a5d622b2a5730d00d6239c730ee4c672120605d6247214d6257215d6267216d6277217d6287218d6297219d62ae5c672290463b2a5997221730f00d62bc6722a0404d62ce6722bd62d99997310721395722cd801d62de5722b731195ec8f722d731292722d7313722d95ed93722d7314e6c6722a050c4c0eb0e5c6722a050c4c0e83004c0e7315d9012e404c0e9a8c722e018c8c722e020273167317d62e721ad62f721bd630721cd631721dd632b2a5731801a7d633b27201731900ecedef722096830401937221731a93db63087222720192c17222997203722393c27222720ced722096830601721feded93c27224720c928c7228029591b17209731b9d9c720a7e722d05731c999d9c720a7e722d05731d7223938c7228017209eded93c27229e4c67212050e928c7231029d9c720a7e721305731e938c723101720993c27232721e937233b2db63087232731f00ed95722cd801d634e4722b95ec8f723473209272347321d802d635b2a5732201a7d636b2db6308723573230186027202c17235eded928c7236029d9c720a7e7234057324938c723601720993c27235c2722a95ed9372347325e6c6722a050c4c0ed802d635e5c6722a050c4c0e83004c0ed636b1723593b4ad7235d901374c0e86028c7237019d9c7e8c72370205720a732673277236adb4a573289a73297236d9013763d801d639b2db63087237732a0186027202c1723795938c72390172098602c272378c72390286027202732b732c732d93cbc3722a8c723301d808d620b2a5732e00d621db63087220d622b27221732f0186027202c17220d6238c722202d6249172117330d625e4c672120711d626b2a5733100d627b2db6308722673320186027202c1722696830c01721f938c7222017209ec92722395720b72089a720ab27207733300ed7224927223721193b27201733400b2722173350093c27220c2a793e4c67220040e720c95ed72249272237211d801d628e4c672200559ed938c722801720f908c722802720d93e4c6722005598602720f9590997210720db272257336009a7210b27225733700721093c672200611720693e4c67220070e720993b172219593b1720973387339733a93c27226721eeced938c7227017209928c722702720a93720a733b733cd1938cb2db63087212733d0001733e",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "809ae5b79446bb3451987c82ac06205eac4f1a02cb8eb2a39f69d80fe6ba0514",
"index": 0,
"amount": 1,
"name": "Peperg #125",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "f1c61023b0d5dc4c78ba38b01fe860613729d0d4c8553253124d9598cd231ca0",
"mainChain": true
},
{
"boxId": "38d34d18a338615154d13d3ee41a8d95bb432618301e4e1b10bdd27c33fc18fa",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 10,
"globalIndex": 31851034,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "7e6751f018d5dd6ebab692b67a302fdcfcd8a41f4cfd35a6053077019b29cde0",
"index": 0,
"amount": 1,
"name": "Peperg #127",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "b683d4a13fe3c93bcba4245980c994e6fff08414d17b9c518b1eb496cd0acd90",
"mainChain": true
},
{
"boxId": "ea428c9b82b97add65bbee571584fd08e2230ee3a180f56d517a96d6acc79710",
"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 15000000,
"index": 11,
"globalIndex": 31851035,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 2\n4: 0\n5: 0\n6: 2\n7: 0\n8: 1\n9: 0\n10: 0\n11: 3\n12: 0\n13: 0\n14: 2\n15: 1\n16: 1000\n17: 0\n18: 2\n19: 10\n20: 2\n21: 0\n22: 0\n23: 0\n24: 0\n25: 0\n26: 3\n27: 0\n28: 1000\n29: 1000\n30: 1000\n31: 0\n32: 2\n33: 10\n34: 3\n35: 0\n36: 1000\n37: 2\n38: 1000\n39: 0\n40: 3\n41: 3\n42: 0\n43: 0\n44: false\n45: true\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 1\n52: 0\n53: 0\n54: 0\n55: 1\n56: 0\n57: 1\n58: 2\n59: 0\n60: false\n61: 0\n62: Coll(-98,-68,-42,-108,-65,52,-37,78,-29,-30,-52,-22,0,-121,-54,66,-105,7,67,-71,-32,25,-95,-24,-47,69,-24,86,4,103,-58,14)",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val coll2 = Coll[Byte]()\n val l3 = SELF.value\n val tuple4 = coll1.getOrElse(placeholder[Int](0), (coll2, l3))\n val l5 = tuple4._2\n val opt6 = SELF.R6[Coll[Long]]\n val coll7 = opt6.get\n val l8 = coll7(placeholder[Int](1))\n val coll9 = SELF.R7[Coll[Byte]].get\n val l10 = if ((l5 < l8) || (tuple4._1 != coll9)) { placeholder[Long](2) } else { l5 }\n val bool11 = l10 < l8\n val coll12 = SELF.R4[Coll[Byte]].get\n val l13 = CONTEXT.preHeader.timestamp\n val tuple14 = SELF.R5[(Long, Long)].get\n val l15 = tuple14._1\n val l16 = tuple14._2\n val l17 = coll7.getOrElse(placeholder[Int](3), placeholder[Long](4))\n val box18 = CONTEXT.dataInputs(placeholder[Int](5))\n val i19 = box18.R4[Int].get\n val box20 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n val coll21 = box20.tokens\n val l22 = box20.value\n val tuple23 = (coll2, l22)\n val tuple24 = coll21.getOrElse(placeholder[Int](7), tuple23)\n val box25 = OUTPUTS.getOrElse(placeholder[Int](8), SELF)\n val coll26 = box25.tokens\n val l27 = box25.value\n val tuple28 = (coll2, l27)\n val tuple29 = coll26.getOrElse(placeholder[Int](9), tuple28)\n val coll30 = SELF.R8[Coll[Byte]].get\n val bool31 = INPUTS(placeholder[Int](10)).id == SELF.id\n sigmaProp(bool11) && proveDlog(decodePoint(coll12.slice(placeholder[Int](11), coll12.size))) || sigmaProp(if (l13 > l15) { if (l13 > l16) {(\n val bool32 = (l10 >= l8) || ((l17 > placeholder[Long](12)) && (l10 >= l17))\n val i33 = OUTPUTS.size\n val box34 = OUTPUTS(placeholder[Int](13))\n val l35 = placeholder[Long](14) * box18.R6[Long].get\n val box36 = box20\n val coll37 = coll21\n val l38 = l22\n val tuple39 = tuple23\n val tuple40 = tuple24\n val box41 = box25\n val box42 = box41.R4[Box].getOrElse(OUTPUTS(i33 - placeholder[Int](15)))\n val opt43 = box42.R4[Int]\n val bool44 = opt43.isDefined\n val i45 = placeholder[Int](16) - i19 - if (bool44) {(\n val i45 = opt43.getOrElse(placeholder[Int](17))\n if ((i45 < placeholder[Int](18)) || (i45 >= placeholder[Int](19))) { i45 } else { if ((i45 == placeholder[Int](20)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) { box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](21), {(tuple46: (Int, (Coll[Byte], Int))) => tuple46._1 + tuple46._2._2 }) } else { placeholder[Int](22) } }\n )} else { placeholder[Int](23) }\n val coll46 = coll26\n val l47 = l27\n val tuple48 = tuple28\n val tuple49 = tuple29\n val box50 = OUTPUTS.getOrElse(placeholder[Int](24), SELF)\n val tuple51 = coll1(placeholder[Int](25))\n ((!bool32) && allOf(Coll[Boolean](i33 == placeholder[Int](26), box34.tokens == coll1, box34.value >= l3 - l35, box34.propositionBytes == coll12))) || (bool32 && allOf(Coll[Boolean](bool31, ((box36.propositionBytes == coll12) && (tuple40._2 >= if (coll9.size > placeholder[Int](27)) { l10 * i45.toLong / placeholder[Long](28) } else { l10 * i45.toLong / placeholder[Long](29) - l35 })) && (tuple40._1 == coll9), ((box41.propositionBytes == box18.R5[Coll[Byte]].get) && (tuple49._2 >= l10 * i19.toLong / placeholder[Long](30))) && (tuple49._1 == coll9), box50.propositionBytes == coll30, tuple51 == box50.tokens(placeholder[Int](31)), if (bool44) {(\n val i52 = opt43.get\n if ((i52 < placeholder[Int](32)) || (i52 >= placeholder[Int](33))) {(\n val box53 = OUTPUTS.getOrElse(placeholder[Int](34), SELF)\n val tuple54 = box53.tokens.getOrElse(placeholder[Int](35), (coll2, box53.value))\n ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](36)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n )} else { if ((i52 == placeholder[Int](37)) && box42.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n val coll53 = box42.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n val i54 = coll53.size\n coll53.map({(tuple55: (Coll[Byte], Int)) => (tuple55._1, tuple55._2.toLong * l10 / placeholder[Long](38)) }).slice(placeholder[Int](39), i54) == OUTPUTS.slice(placeholder[Int](40), placeholder[Int](41) + i54).map({(box55: Box) =>\n val tuple57 = box55.tokens.getOrElse(placeholder[Int](42), (coll2, box55.value))\n if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](43)) }\n })\n )} else { placeholder[Boolean](44) } }\n )} else { placeholder[Boolean](45) } && (blake2b256(box42.bytes) == tuple51._1))))\n )} else {(\n val box32 = OUTPUTS(placeholder[Int](46))\n val coll33 = box32.tokens\n val tuple34 = coll33.getOrElse(placeholder[Int](47), (coll2, box32.value))\n val l35 = tuple34._2\n val bool36 = l17 > placeholder[Long](48)\n val coll37 = box18.R7[Coll[Long]].get\n val box38 = OUTPUTS(placeholder[Int](49))\n val tuple39 = box38.tokens.getOrElse(placeholder[Int](50), (coll2, box38.value))\n allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](51)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](52)) == coll33(placeholder[Int](53)), box32.propositionBytes == SELF.propositionBytes, box32.R4[Coll[Byte]].get == coll12, if (bool36 && (l35 >= l17)) {(\n val tuple40 = box32.R5[(Long, Long)].get\n (tuple40._1 == l15) && (tuple40._2 <= l13)\n )} else { box32.R5[(Long, Long)].get == (l15, if (l16 - l13 <= coll37(placeholder[Int](54))) { l16 + coll37(placeholder[Int](55)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](56)) { placeholder[Int](57) } else { placeholder[Int](58) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](59))))\n )} } else { placeholder[Boolean](60) }) && sigmaProp(box18.tokens(placeholder[Int](61))._1 == placeholder[Coll[Byte]](62))\n}",
"address": "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",
"assets": [
{
"tokenId": "85e0f42ebfe12076f4130f35790335321d4104d1473359f712650de988e7cad1",
"index": 0,
"amount": 1,
"name": "Peperg #132",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "59f0cef8fabf62f0ffb982c762",
"sigmaType": "(SLong, SLong)",
"renderedValue": "[1692211811256,1693159211000]"
},
"R6": {
"serializedValue": "11038090dfc04a80a8d6b90780e8eda1ba01",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000000,1000000000,25000000000]"
},
"R8": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
},
"R7": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R4": {
"serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
}
},
"spentTransactionId": "49b4c404f9b824c26bda29a3200d216666825873375d5ed1aa9545621ea26950",
"mainChain": true
},
{
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"transactionId": "dd77f6952f2fe40b87c32108b3f886ef9b345410b5f8601dcf11be0db6bf99f3",
"blockId": "ea0af8a9b16fed8d4991a68c6b8d490ea44aa7220c6a92f5c64ac193a0079154",
"value": 12142792795,
"index": 12,
"globalIndex": 31851036,
"creationHeight": 1070523,
"settlementHeight": 1070525,
"ergoTree": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3296ca,9154f2,...)))}",
"address": "9euLk6oVwEKSCQxCE6qj1vKcFjzk9Toy4YPyC9JB5uPmtLnpHj7",
"assets": [
{
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"type": "EIP-004"
},
{
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},
{
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},
{
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},
{
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},
{
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},
{
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},
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},
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},
{
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"decimals": 0,
"type": "EIP-004"
},
{
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},
{
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},
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"type": "EIP-004"
},
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},
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},
{
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},
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"type": "EIP-004"
},
{
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"type": "EIP-004"
},
{
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"decimals": 0,
"type": "EIP-004"
},
{
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"name": "Peperg #146",
"decimals": 0,
"type": "EIP-004"
},
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