Token
ec3c44ae60ef227d0f18e5f09d5053960389a03a322157c40cfe67bb5cc04e5d
ID
ec3c44ae60ef227d0f18e5f09d5053960389a03a322157c40cfe67bb5cc04e5d
Name
Call_A_fakeUSD_ERG_110649999_2023-04-21_per_1
Emission amount
101
Decimals
0
Description
0
Type
EIP-004
Issuer Box
{
"boxId": "ec3c44ae60ef227d0f18e5f09d5053960389a03a322157c40cfe67bb5cc04e5d",
"transactionId": "0b94c891e1444b92c34514b838b72ca2b27aeb6b43adbad9046fd1f10baaa6c9",
"blockId": "cbbf95b711e555b523a26a4aa4d342658b52d3a59321879d1d9ca1356940fa3c",
"value": 4200000,
"index": 0,
"globalIndex": 25802704,
"creationHeight": 922453,
"settlementHeight": 922455,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 3\n4: 2100000\n5: 1\n6: 0\n7: 0\n8: 2\n9: 100\n10: 0\n11: 7\n12: Coll(119,119,119,-27,5,31,-118,107,-61,8,39,-18,65,-35,57,-32,75,-54,29,-70,53,35,107,-102,38,-76,-108,-32,-70,-56,79,51)\n13: Coll(48)\n14: 1\n15: 1\n16: false\n17: 1\n18: 1\n19: 0\n20: CBigInt(1000)\n21: 1\n22: 0\n23: CBigInt(1000000)\n24: 86400000\n25: 2\n26: 1\n27: 86400000\n28: 1\n29: 1\n30: 2\n31: 1\n32: 2100000\n33: 1\n34: 9\n35: false\n36: 14400000\n37: 2\n38: 0\n39: 0\n40: 0\n41: 0\n42: 0\n43: 100\n44: 500\n45: 1000\n46: 2000\n47: 4000\n48: 9000\n49: 13000\n50: 20000\n51: 30000\n52: 40000\n53: 50000\n54: 70000\n55: 110000\n56: 140000\n57: 170000\n58: 210000\n59: 250000\n60: 300000\n61: 500000\n62: 1000000\n63: 10000000\n64: 1\n65: 0\n66: 1\n67: 0\n68: 0\n69: 1\n70: CBigInt(1)\n71: CBigInt(0)\n72: 4\n73: 4\n74: 1775840000\n75: CBigInt(0)\n76: 5\n77: CBigInt(177584)\n78: 6\n79: 177584000\n80: 10000\n81: 0\n82: Coll(102,102,102,-116,-29,83,-2,-3,20,109,20,-76,20,-126,-43,38,-21,-14,106,90,125,32,79,54,87,12,89,-59,88,19,107,-125)\n83: 30\n84: 2\n85: 2\n86: 3\n87: 3\n88: 8\n89: false\n90: 2\n91: 4\n92: 0\n93: 1\n94: 0\n95: 2\n96: 0\n97: 0\n98: 1\n99: 0\n100: 0\n101: 1\n102: false\n103: 2100000\n104: 1\n105: 1\n106: 1100000\n107: false",
"ergoTreeScript": "{\n val coll1 = SELF.tokens\n val tuple2 = (Coll[Byte](), placeholder[Long](0))\n val tuple3 = coll1.getOrElse(placeholder[Int](1), tuple2)\n val box4 = SELF.R7[Box].get\n val bool5 = (tuple3._1 == box4.id) && (SELF.propositionBytes == box4.propositionBytes)\n val box6 = if (bool5) { box4 } else { SELF }\n val prop7 = box6.R9[SigmaProp].get\n val bool8 = !bool5\n val box9 = OUTPUTS(placeholder[Int](2))\n val coll10 = box9.propositionBytes\n val coll11 = prop7.propBytes\n val bool12 = coll10 == coll11\n val coll13 = box6.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](3))\n val l15 = CONTEXT.preHeader.timestamp\n val l16 = l14 - l15\n val l17 = box9.value\n val bool18 = l17 >= placeholder[Long](4)\n val coll19 = box9.tokens\n val tuple20 = coll19.getOrElse(placeholder[Int](5), tuple2)\n val l21 = tuple20._2\n val l22 = tuple3._2\n val bool23 = coll13(placeholder[Int](6)) == placeholder[Long](7)\n val l24 = coll13(placeholder[Int](8))\n val l25 = l24 * placeholder[Long](9)\n val tuple26 = coll19.getOrElse(placeholder[Int](10), tuple2)\n val l27 = tuple26._2\n val l28 = SELF.value\n val l29 = coll13(placeholder[Int](11))\n val coll30 = tuple26._1\n val coll31 = box6.id\n val coll32 = placeholder[Coll[Byte]](12)\n val coll33 = placeholder[Coll[Byte]](13)\n val bool34 = if (coll10 == SELF.propositionBytes) {\n (\n (\n (\n (\n (((coll30 == coll31) && (l27 >= placeholder[Long](14))) && bool18) && (\n ((bool23 && (tuple20._1 == coll32)) && (l21 >= placeholder[Long](15))) || (!bool23)\n )\n ) && (box9.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)\n ) && (box9.R5[Coll[Byte]].get == coll33)\n ) && (box9.R6[Coll[Byte]].get == coll33)\n ) && (box9.R7[Box].get == box6)\n } else { placeholder[Boolean](16) }\n val box35 = OUTPUTS(placeholder[Int](17))\n val coll36 = box6.R5[Coll[Byte]].get\n val bool37 = l15 <= l14\n val tuple38 = coll1.getOrElse(placeholder[Int](18), tuple2)\n val l39 = tuple38._2\n val coll40 = box35.tokens\n val tuple41 = coll40.getOrElse(placeholder[Int](19), tuple2)\n val coll42 = tuple41._1\n val l43 = tuple41._2\n val bi44 = placeholder[BigInt](20)\n val bool45 = coll13(placeholder[Int](21)) == placeholder[Long](22)\n val bi46 = placeholder[BigInt](23)\n val bool47 = l15 > l14\n val bool48 = if (bool45) { (bool5 && bool47) && (l15 < l14 + placeholder[Long](24)) } else { bool5 && bool37 }\n prop7 && sigmaProp((bool8 && (OUTPUTS.size == placeholder[Int](25))) && bool12) || sigmaProp(\n (\n (\n if ((bool8 && (INPUTS.size == placeholder[Int](26))) && (l16 >= placeholder[Long](27))) {\n (\n (\n bool34 && (\n (bool18 && (box9.R7[Box].get == SELF)) && (\n (\n ((bool23 && (l21 == l22)) && (l27 == l22 - placeholder[Long](28) / l25 + placeholder[Long](29))) && (coll19.size == placeholder[Int](30))\n ) || (((!bool23) && (coll19.size == placeholder[Int](31))) && (l27 == l28 - placeholder[Long](32) / l29 + placeholder[Long](33)))\n )\n )\n ) && (box35.propositionBytes == coll36)\n ) && (box35.value >= coll13(placeholder[Int](34)))\n } else { placeholder[Boolean](35) } || if (((!(bool37 && (l15 > l14 - placeholder[Long](36)))) && (INPUTS.size == placeholder[Int](37))) && (\n CONTEXT.dataInputs.size > placeholder[Int](38)\n )) {(\n val box49 = CONTEXT.dataInputs(placeholder[Int](39))\n val l50 = l22 - l27\n val l51 = box49.R4[Long].get\n val l52 = if (bool23) { max(placeholder[Long](40), l51 - l29 * l24) } else { max(placeholder[Long](41), l29 - l51 * l24) }\n val coll53 = Coll[Long](\n placeholder[Long](42), placeholder[Long](43), placeholder[Long](44), placeholder[Long](45), placeholder[Long](46), placeholder[Long](\n 47\n ), placeholder[Long](48), placeholder[Long](49), placeholder[Long](50), placeholder[Long](51), placeholder[Long](52), placeholder[Long](\n 53\n ), placeholder[Long](54), placeholder[Long](55), placeholder[Long](56), placeholder[Long](57), placeholder[Long](58), placeholder[Long](\n 59\n ), placeholder[Long](60), placeholder[Long](61), placeholder[Long](62), placeholder[Long](63)\n )\n val coll54 = coll53.map({(l54: Long) => l54 * l54 }).zip(coll53)\n val func55 = {(l55: Long) =>\n val i57 = coll54.map({(tuple57: (Long, Long)) => if (tuple57._1 >= l55) { placeholder[Long](64) } else { placeholder[Long](65) } }).indexOf(\n placeholder[Long](66), placeholder[Int](67)\n )\n val tuple58 = coll54(i57)\n if (i57.toLong > placeholder[Long](68)) {(\n val tuple59 = coll54(i57 - placeholder[Int](69))\n val l60 = tuple59._2\n val l61 = tuple59._1\n max(placeholder[BigInt](70), l60.toBigInt + tuple58._2 - l60.toBigInt * l55 - l61.toBigInt / tuple58._1 - l61.toBigInt)\n )} else { placeholder[BigInt](71) }\n }\n val bi56 = func55(l16)\n val bi57 = placeholder[Long](72) * coll13(placeholder[Int](73)).toBigInt * l24.toBigInt * l29.toBigInt * bi56 / placeholder[Int](74).toBigInt\n val bi58 = max(\n placeholder[BigInt](75), bi57 - bi57 * coll13(placeholder[Int](76)).toBigInt * func55(max(l51 - l29, l29 - l51)) * placeholder[BigInt](\n 77\n ) / bi44 * func55(l29) * bi56\n )\n val bi59 = if (bool45) { l52.toBigInt + bi58 } else {\n l52.toBigInt + bi58 + bi58 * coll13(placeholder[Int](78)).toBigInt * bi56 / placeholder[Int](79).toBigInt\n }\n val bi60 = max(bi46, bi59 - bi59 % placeholder[Long](80).toBigInt)\n val bi61 = l50.toBigInt * if (bool23) { min(l51 * l24.toBigInt, bi60) } else { min(l29 * l24.toBigInt, bi60) }\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (box49.tokens(placeholder[Int](81))._1 == placeholder[Coll[Byte]](82)) && (HEIGHT <= box49.R5[Int].get + placeholder[Int](83))\n ) && bool34\n ) && (l17 == l28)\n ) && (l21 == l39)\n ) && (coll42 == coll31)\n ) && (l43 == l50)\n ) && (OUTPUTS(placeholder[Int](84)).propositionBytes == coll11)\n ) && (OUTPUTS(placeholder[Int](85)).value.toBigInt >= max(bi46, bi61))\n ) && (OUTPUTS(placeholder[Int](86)).propositionBytes == coll36)\n ) && (OUTPUTS(placeholder[Int](87)).value.toBigInt >= max(bi46, bi61 * coll13(placeholder[Int](88)).toBigInt / bi44))\n )} else { placeholder[Boolean](89) }\n ) || if (((bool48 && (INPUTS.size == placeholder[Int](90))) && (OUTPUTS.size == placeholder[Int](91))) && (\n CONTEXT.dataInputs.size == placeholder[Int](92)\n )) {(\n val l49 = if (bool23) { l39 - l21 } else { l28 - l17 }\n val l50 = if (bool23) { l49 / l25 } else { l49 / l29 * l24 }\n val tuple51 = INPUTS(placeholder[Int](93)).tokens.getOrElse(placeholder[Int](94), tuple2)\n val box52 = OUTPUTS(placeholder[Int](95))\n val coll53 = box52.tokens\n val tuple54 = coll53.getOrElse(placeholder[Int](96), tuple2)\n (\n (((l50 == if (tuple51._1 == coll31) { tuple51._2 } else { placeholder[Long](97) }) && bool34) && (l27 == l22)) && (\n (\n ((((bool23 && (coll42 == coll32)) && (l43 == l49)) && (coll40.size == placeholder[Int](98))) && (box52.value >= l50 * l29 * l24)) && (\n coll53.size == placeholder[Int](99)\n )\n ) || (\n (((((!bool23) && (box35.value >= l49)) && (coll40.size == placeholder[Int](100))) && (tuple54._1 == coll32)) && (tuple54._2 >= l50 * l25)) && (\n coll53.size == placeholder[Int](101)\n )\n )\n )\n ) && (box52.propositionBytes == coll11)\n )} else { placeholder[Boolean](102) }\n ) || if ((bool47 && (!bool48)) || (((l28 == placeholder[Long](103)) && (l22 == placeholder[Long](104))) && (l39 <= placeholder[Long](105)))) {\n ((bool12 && (l17 >= l28 - placeholder[Long](106))) && (coll30 == tuple38._1)) && (l27 == l39)\n } else { placeholder[Boolean](107) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "777777e5051f8a6bc30827ee41dd39e04bca1dba35236b9a26b494e0bac84f33",
"index": 0,
"amount": 10001,
"name": "fakeUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e240008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110a00020280c0e291f461e807f80ac8019e8ac3690a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,1,1682035200000,500,700,100,110649999,5,1000000]"
},
"R7": {
"serializedValue": "63a0968001100205000502d19373007301e28f3800040e01200e01200e012063c0843d10010100d17300ce8f380000c29e8341fbb9884bc3c58559b49c529f5f9b2ff038b97f9e76976c92ba917b0f01bd0beef5b5e1eb164d6999d5d038f793954ebe93f82ea3bd0fa1b8c65edc41b100",
"sigmaType": null,
"renderedValue": null
},
"R9": {
"serializedValue": "08cd02042a3559387831c22aaec64a86969b6f2e4b7626b3f94cbec08123c5dc88d23e",
"sigmaType": "SSigmaProp",
"renderedValue": "02042a3559387831c22aaec64a86969b6f2e4b7626b3f94cbec08123c5dc88d23e"
},
"R4": {
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"sigmaType": "Coll[SByte]",
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