Transaction
ID: 4b12f6fdb4...0a92
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001200064 ERG
Tokens:
2,403.29
Spent
Address:
Output transaction:
Settlement height:
Value:
1,332.43 ERG
Tokens:
Loading assets...
Outputs (6)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.25 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1,332.17 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 1,034,942
Total coins transferred: 1,332.43 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000291 ERG
Raw Transaction Data
{
"id": "4b12f6fdb402a8a5ef697161a6a15a4ca99af6bb7d6166a084c9bfefcd8f0a92",
"blockId": "eb50a2754faa64f80682018d4e363b4b9d11c345a0e8c7e09f58a9092a85d20d",
"inclusionHeight": 727630,
"timestamp": 1649918651856,
"index": 12,
"globalIndex": 2989091,
"numConfirmations": 1034942,
"inputs": [
{
"boxId": "e662445b5e65698c029d8e212db8f4df808c37df610f647ddafa02164c72d778",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "d8494f8cc25c446b25aabbf794da029d8572a27a588c6cff5e68164ef7c3a103",
"outputTransactionId": "b62893ee72cbec7d0d905f82920f460a614fa862b5829acf240eb174130c4258",
"outputIndex": 0,
"outputGlobalIndex": 15521698,
"outputCreatedAt": 727601,
"outputSettledAt": 727604,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(-41,22,-109,-60,-102,-124,-5,-66,-51,73,8,-55,72,19,-76,101,20,-79,-117,103,-87,-103,82,-36,30,110,71,-111,85,109,-28,19)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(37,-73,72,107,26,120,100,122,-41,-43,10,40,126,94,-107,-117,78,69,42,75,-56,105,56,-55,66,24,-41,6,-68,55,127,-16)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(13,1,-14,-16,-77,37,75,74,23,49,-31,-74,26,-41,118,65,-2,84,-34,43,-42,-115,28,111,-63,-82,78,126,-99,-33,-78,18)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.tokens\n val tuple6 = coll5(placeholder[Int](2))\n val coll7 = tuple6._1\n val bool8 = coll4 == coll7\n val box9 = OUTPUTS(placeholder[Int](3))\n val coll10 = box9.R4[Coll[Long]].get\n val coll11 = SELF.R4[Coll[Long]].get\n val l12 = tuple6._2\n val coll13 = box9.tokens\n val tuple14 = coll13(placeholder[Int](4))\n val l15 = tuple14._2\n val l16 = CONTEXT.preHeader.timestamp\n val l17 = tuple3._2\n val coll18 = placeholder[Coll[Byte]](5)\n val tuple19 = coll13(placeholder[Int](6))\n val tuple20 = coll5(placeholder[Int](7))\n val l21 = coll11(placeholder[Int](8))\n val bool22 = allOf(\n Coll[Boolean](\n box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n placeholder[Int](9)\n ) == l21, coll13.size == placeholder[Int](10)\n )\n )\n if (bool8) {(\n val tuple23 = coll2(placeholder[Int](11))\n val l24 = tuple23._2\n val l25 = coll11(placeholder[Int](12))\n val coll26 = box1.R4[Coll[Long]].get\n val coll27 = box1.R5[Coll[Byte]].get\n val box28 = OUTPUTS(placeholder[Int](13))\n val tuple29 = box28.tokens(placeholder[Int](14))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n placeholder[Int](18)\n ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n Long\n ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n placeholder[Int](26)\n ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n 29\n ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n )\n )\n )\n )} else {(\n val box23 = INPUTS(placeholder[Int](32))\n val coll24 = box23.tokens\n val tuple25 = coll24(placeholder[Int](33))\n val coll26 = tuple25._1\n if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n val box27 = INPUTS(placeholder[Int](36))\n val coll28 = box27.R4[Coll[Long]].get\n val l29 = coll11(placeholder[Int](37))\n val l30 = coll10(placeholder[Int](38))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n placeholder[Int](43)\n ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n placeholder[Int](48)\n ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n )\n )\n )\n )} else {(\n val l27 = coll11(placeholder[Int](50))\n val l28 = coll10(placeholder[Int](51))\n if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n val coll33 = tuple31._2.tokens\n val l34 = tuple31._1\n if (coll33.size == placeholder[Int](54)) { l34 } else {(\n val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n val i36 = coll35.size\n if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n )}\n }) }\n val l30 = func29(INPUTS)\n val l31 = func29(OUTPUTS)\n val coll32 = box23.R4[Coll[Long]].get\n val l33 = coll32(placeholder[Int](59))\n val l34 = l16 - l33 / placeholder[Int](60).toLong\n val l35 = l27 - l28\n val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n l35 * placeholder[Long](72) / placeholder[Long](73)\n }\n }\n }\n }\n val box37 = INPUTS(placeholder[Int](74))\n val l38 = coll32(placeholder[Int](75))\n val l39 = coll11(placeholder[Int](76))\n val tuple40 = coll24(placeholder[Int](77))\n val l41 = tuple40._2 - l35\n val bool42 = l41 == placeholder[Long](78)\n val coll43 = tuple40._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n placeholder[Long](84)\n } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n placeholder[Long](88)\n } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n 90\n )) {(\n val box44 = OUTPUTS(placeholder[Int](91))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](92))\n val tuple47 = coll45(placeholder[Int](93))\n val coll48 = box44.R4[Coll[Long]].get\n allOf(\n Coll[Boolean](\n box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n Long\n ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n )\n )\n )} else { placeholder[Boolean](97) }\n )\n )\n )\n )} else { sigmaProp(placeholder[Boolean](98)) }\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "05cde13424a7972fbcd0b43fccbb5e501b1f75302175178fc86d8f243f3f3125",
"index": 0,
"amount": 1,
"name": "ergopad Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1028de73d018f0c9a374b71555c5b8f1390994f2f41633e7b9d68f77735782ee",
"index": 1,
"amount": 999998145,
"name": "ergopad Stake Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1105de9ba5e0215afe1cc8f69dc4846080f0b252",
"sigmaType": "Coll[SLong]",
"renderedValue": "[4530153199,45,1855,1649875860900,86400000]"
}
}
},
{
"boxId": "2e7f6b7473b7df4e9a7a31647fe60f58fbf1697981b758fbc1a0532cb7c0c348",
"value": 1200064,
"index": 1,
"spendingProof": "4eb0f97a1316409aa63d2c667db3e5e468b323a780c677fa0ff7af10ef902b552e0ce8154e2766e5dd230030092cfb303931aaa8580411d0",
"outputBlockId": "45af8a6c7ff562cda44f0683375c00aa70f7e149b598535c016535be30bd5a82",
"outputTransactionId": "67c87b0721235d93d35b803cb3c4edd3338efc13014016cb4b99a99e742f3b94",
"outputIndex": 1,
"outputGlobalIndex": 15522397,
"outputCreatedAt": 0,
"outputSettledAt": 727626,
"ergoTree": "0008cd024460cfd0d2ab33d4fb94af15858656886384fbf04d4211c418c4e69da418cfe2",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4460cf,66870b,...)))}",
"address": "9f3B9HRhJh6etR5KLDkcH2Zyexeo63JkNKNL31vHm3vx7rQPWTT",
"assets": [
{
"tokenId": "d71693c49a84fbbecd4908c94813b46514b18b67a99952dc1e6e4791556de413",
"index": 0,
"amount": 240329,
"name": "ergopad",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "8c477f0c7b36cccef9c230c1383e27ba2f005131c8b60dc672ffe9787ec1d9c9",
"value": 1332432368027,
"index": 2,
"spendingProof": "9ae1077ce7270946951cbc3791a2e86f0154a531c0ffafbc0760ca9f82cd7087d46950c076bd6d273102feff000e44ba2c51139ff7ab5427",
"outputBlockId": "917a32c503a7743df96e42dc93cd33e80a9a22db1aa6d5c34b836fe2f0cc1921",
"outputTransactionId": "dbcc5fec0d3ed322394d4907b4e5f17dd5ab64e87e7ee152859997e5a15dd33a",
"outputIndex": 1,
"outputGlobalIndex": 15522427,
"outputCreatedAt": 727626,
"outputSettledAt": 727628,
"ergoTree": "0008cd024460cfd0d2ab33d4fb94af15858656886384fbf04d4211c418c4e69da418cfe2",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(4460cf,66870b,...)))}",
"address": "9f3B9HRhJh6etR5KLDkcH2Zyexeo63JkNKNL31vHm3vx7rQPWTT",
"assets": [
{
"tokenId": "d71693c49a84fbbecd4908c94813b46514b18b67a99952dc1e6e4791556de413",
"index": 0,
"amount": 24179,
"name": "ergopad",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "472c3d4ecaa08fb7392ff041ee2e6af75f4a558810a74b28600549d5392810e8",
"index": 1,
"amount": 31311022940,
"name": "NETA",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "5d6aea9feb5654326c7c7e1c6a282d96ca4d71eb72660d42055f449cb2a83260",
"index": 2,
"amount": 1,
"name": "Paideia Strategic Round Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 3,
"amount": 13661202,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "82b8698ce2f522a2272948ec7242f6cd8b2b056b8eda8baf4bc1248ea6b2838b",
"index": 4,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "5a34d53ca483924b9a6aa0c771f11888881b516a8d1a9cdc535d063fe26d065e",
"index": 5,
"amount": 11488071581047,
"name": "LunaDog",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "150489fb57406614c52412ade6e2634abbca67f0ff96d71a27697edd0f20eb31",
"index": 6,
"amount": 1000,
"name": "Cul(t)inary Coin",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e91cbc48016eb390f8f872aa2962772863e2e840708517d1ab85e57451f91bed",
"index": 7,
"amount": 4800,
"name": "Ergold",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "30974274078845f263b4f21787e33cc99e9ec19a17ad85a5bc6da2cca91c5a2e",
"index": 8,
"amount": 800000000000,
"name": "WT_ADA",
"decimals": 8,
"type": "EIP-004"
},
{
"tokenId": "40006e02d7d7581e34e9cd9369e459fb35eb7eb5dcc911d2a801c212b07a012a",
"index": 9,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ef802b475c06189fdbf844153cdc1d449a5ba87cce13d11bb47b5a539f27f12b",
"index": 10,
"amount": 1600000000000,
"name": "WT_ERG",
"decimals": 9,
"type": "EIP-004"
},
{
"tokenId": "857f3dea8a24f6c53bad586b78aa88b8b14f90cf8c7ffb25b334edf9b24e3291",
"index": 11,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "36aba4b4a97b65be491cf9f5ca57b5408b0da8d0194f30ec8330d1e8946161c1",
"index": 12,
"amount": 218,
"name": "Erdoge",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "aeccea5041eca2e370bc80402ed11b9fe8914ca7fdc57a44d06ffd4730806582",
"index": 13,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0779ec04f2fae64e87418a1ad917639d4668f78484f45df962b0dec14a2591d2",
"index": 14,
"amount": 56858,
"name": "Mi Goreng ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "003bd19d0187117f130b62e1bcab0939929ff5c7709f843c5c4dd158949285d0",
"index": 15,
"amount": 86564,
"name": "SigRSV",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0cd8c9f416e5b1ca9f986a7f10a84191dfb85941619e49e53c0dc30ebf83324b",
"index": 16,
"amount": 663360,
"name": "COMET",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "e249780a22e14279357103749102d0a7033e0459d10b7f277356522ae9df779c",
"index": 17,
"amount": 307506086626,
"name": "ERG_NETA_LP",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "757c4e8c3722ce9d78fd95f555021d96ea8dfca45067edb13e0400a58d04c0b7",
"index": 18,
"amount": 1,
"name": "Drink Your Ovaltine",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fbbaac7337d051c10fc3da0ccb864f4d32d40027551e1c3ea3ce361f39b91e40",
"index": 19,
"amount": 4000,
"name": "kushti",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "be15e32fecf432c41413714dc4a3f8ac18b6bd85c2dc811df7c02bf778736fcf",
"index": 20,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "339431a39e2bbfab76130bcf3c2a3bc2748738c83defd98a0c4c45b853fb4792",
"index": 21,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "7c1cf137926926c21fd0bdf61a3b32bef108c4acc52ebbdca58da5d49619dbd0",
"transactionId": "4b12f6fdb402a8a5ef697161a6a15a4ca99af6bb7d6166a084c9bfefcd8f0a92",
"blockId": "eb50a2754faa64f80682018d4e363b4b9d11c345a0e8c7e09f58a9092a85d20d",
"value": 1000000,
"index": 0,
"globalIndex": 15522641,
"creationHeight": 727628,
"settlementHeight": 727630,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(-41,22,-109,-60,-102,-124,-5,-66,-51,73,8,-55,72,19,-76,101,20,-79,-117,103,-87,-103,82,-36,30,110,71,-111,85,109,-28,19)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(37,-73,72,107,26,120,100,122,-41,-43,10,40,126,94,-107,-117,78,69,42,75,-56,105,56,-55,66,24,-41,6,-68,55,127,-16)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(13,1,-14,-16,-77,37,75,74,23,49,-31,-74,26,-41,118,65,-2,84,-34,43,-42,-115,28,111,-63,-82,78,126,-99,-33,-78,18)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.tokens\n val tuple6 = coll5(placeholder[Int](2))\n val coll7 = tuple6._1\n val bool8 = coll4 == coll7\n val box9 = OUTPUTS(placeholder[Int](3))\n val coll10 = box9.R4[Coll[Long]].get\n val coll11 = SELF.R4[Coll[Long]].get\n val l12 = tuple6._2\n val coll13 = box9.tokens\n val tuple14 = coll13(placeholder[Int](4))\n val l15 = tuple14._2\n val l16 = CONTEXT.preHeader.timestamp\n val l17 = tuple3._2\n val coll18 = placeholder[Coll[Byte]](5)\n val tuple19 = coll13(placeholder[Int](6))\n val tuple20 = coll5(placeholder[Int](7))\n val l21 = coll11(placeholder[Int](8))\n val bool22 = allOf(\n Coll[Boolean](\n box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n placeholder[Int](9)\n ) == l21, coll13.size == placeholder[Int](10)\n )\n )\n if (bool8) {(\n val tuple23 = coll2(placeholder[Int](11))\n val l24 = tuple23._2\n val l25 = coll11(placeholder[Int](12))\n val coll26 = box1.R4[Coll[Long]].get\n val coll27 = box1.R5[Coll[Byte]].get\n val box28 = OUTPUTS(placeholder[Int](13))\n val tuple29 = box28.tokens(placeholder[Int](14))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n placeholder[Int](18)\n ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n Long\n ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n placeholder[Int](26)\n ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n 29\n ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n )\n )\n )\n )} else {(\n val box23 = INPUTS(placeholder[Int](32))\n val coll24 = box23.tokens\n val tuple25 = coll24(placeholder[Int](33))\n val coll26 = tuple25._1\n if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n val box27 = INPUTS(placeholder[Int](36))\n val coll28 = box27.R4[Coll[Long]].get\n val l29 = coll11(placeholder[Int](37))\n val l30 = coll10(placeholder[Int](38))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n placeholder[Int](43)\n ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n placeholder[Int](48)\n ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n )\n )\n )\n )} else {(\n val l27 = coll11(placeholder[Int](50))\n val l28 = coll10(placeholder[Int](51))\n if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n val coll33 = tuple31._2.tokens\n val l34 = tuple31._1\n if (coll33.size == placeholder[Int](54)) { l34 } else {(\n val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n val i36 = coll35.size\n if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n )}\n }) }\n val l30 = func29(INPUTS)\n val l31 = func29(OUTPUTS)\n val coll32 = box23.R4[Coll[Long]].get\n val l33 = coll32(placeholder[Int](59))\n val l34 = l16 - l33 / placeholder[Int](60).toLong\n val l35 = l27 - l28\n val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n l35 * placeholder[Long](72) / placeholder[Long](73)\n }\n }\n }\n }\n val box37 = INPUTS(placeholder[Int](74))\n val l38 = coll32(placeholder[Int](75))\n val l39 = coll11(placeholder[Int](76))\n val tuple40 = coll24(placeholder[Int](77))\n val l41 = tuple40._2 - l35\n val bool42 = l41 == placeholder[Long](78)\n val coll43 = tuple40._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n placeholder[Long](84)\n } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n placeholder[Long](88)\n } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n 90\n )) {(\n val box44 = OUTPUTS(placeholder[Int](91))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](92))\n val tuple47 = coll45(placeholder[Int](93))\n val coll48 = box44.R4[Coll[Long]].get\n allOf(\n Coll[Boolean](\n box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n Long\n ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n )\n )\n )} else { placeholder[Boolean](97) }\n )\n )\n )\n )} else { sigmaProp(placeholder[Boolean](98)) }\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "05cde13424a7972fbcd0b43fccbb5e501b1f75302175178fc86d8f243f3f3125",
"index": 0,
"amount": 1,
"name": "ergopad Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
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"sigmaType": "Coll[SLong]",
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},
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"ergoTreeConstants": "",
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"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(7c4f8d,597337,...)))}",
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{
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"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
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