Token
f3401d67eeddbe7b924297b2666c34c1e787827592a75a5439f9a94acfb34d65
ID
f3401d67eeddbe7b924297b2666c34c1e787827592a75a5439f9a94acfb34d65
Name
CALL_fakeUSD_ERG_772999999_2023-01-20_per_1
Emission amount
11
Decimals
0
Description
0
Type
EIP-004
Issuer Box
{
"boxId": "f3401d67eeddbe7b924297b2666c34c1e787827592a75a5439f9a94acfb34d65",
"transactionId": "294609a12563b7da8923022cd48ffbee87571a88ea6132a96db1dbe48f0a0cab",
"blockId": "b48270f369e22247695f1dc62815590565bb25af561cc198701cd25118dd75e9",
"value": 4200000,
"index": 0,
"globalIndex": 25294955,
"creationHeight": 911839,
"settlementHeight": 911841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 1\n3: 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)\n4: 0\n5: 0\n6: false\n7: 0\n8: 1\n9: 2\n10: 0\n11: 2100000\n12: 1\n13: 100\n14: 1\n15: 1\n16: 1\n17: Coll(48)\n18: Coll(48)\n19: false\n20: 6\n21: 0\n22: 0\n23: 0\n24: 86400000\n25: 2\n26: 1\n27: 3\n28: 86400000\n29: 2\n30: 1\n31: 1\n32: false\n33: 8\n34: 0\n35: 2\n36: 1100000\n37: 2\n38: 0\n39: false\n40: 14400000\n41: 2\n42: 5\n43: 1\n44: 0\n45: 0\n46: 0\n47: 0\n48: 1\n49: 1\n50: 100\n51: 10\n52: 10000\n53: 100\n54: 100000000000000\n55: 10000000\n56: 1\n57: 0\n58: 1\n59: 0\n60: 1\n61: 4\n62: 3\n63: 1775840000\n64: 0\n65: 4\n66: 1000\n67: 5\n68: 177584000\n69: 1000000\n70: 1000000\n71: 7\n72: 1000\n73: 0\n74: 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)\n75: 1\n76: 1100000\n77: 1\n78: 2\n79: 2\n80: 2\n81: 0\n82: 3\n83: 3\n84: 3\n85: 0\n86: 4\n87: 1100000\n88: 4\n89: 0\n90: false\n91: 2\n92: 4\n93: 0\n94: 1\n95: 2\n96: 2\n97: 2\n98: 0\n99: 3\n100: 1100000\n101: 3\n102: 0\n103: false\n104: 2\n105: 2\n106: 1100000\n107: 1\n108: 0\n109: 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 l4 = tuple3._2\n val tuple5 = coll1.getOrElse(placeholder[Int](2), tuple2)\n val l6 = tuple5._2\n val coll7 = placeholder[Coll[Byte]](3)\n val bool8 = if ((l4 > placeholder[Long](4)) && (l6 > placeholder[Long](5))) {\n ((tuple3._1 == coll7) && (tuple5._1 == SELF.R7[Box].get.id)) && (SELF.propositionBytes == SELF.R7[Box].get.propositionBytes)\n } else { placeholder[Boolean](6) }\n val box9 = if (bool8) { SELF.R7[Box].get } else { SELF }\n val prop10 = box9.R9[SigmaProp].get\n val bool11 = !bool8\n val box12 = OUTPUTS(placeholder[Int](7))\n val coll13 = box12.propositionBytes\n val coll14 = SELF.propositionBytes\n val box15 = OUTPUTS(placeholder[Int](8))\n val coll16 = box9.R8[Coll[Long]].get\n val l17 = coll16(placeholder[Int](9))\n val l18 = CONTEXT.preHeader.timestamp\n val l19 = l17 - l18\n val coll20 = box12.tokens\n val tuple21 = coll20.getOrElse(placeholder[Int](10), tuple2)\n val coll22 = tuple21._1\n val l23 = box12.value\n val bool24 = l23 >= placeholder[Long](11)\n val l25 = tuple21._2\n val l26 = coll16(placeholder[Int](12))\n val l27 = l26 * placeholder[Long](13)\n val tuple28 = coll20.getOrElse(placeholder[Int](14), tuple2)\n val l29 = tuple28._2\n val coll30 = box9.id\n val bool31 = if (coll13 == coll14) {\n (\n (\n (\n ((((bool24 && (coll22 == coll7)) && (l25 >= placeholder[Long](15))) && (tuple28._1 == coll30)) && (l29 >= placeholder[Long](16))) && (\n box12.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get\n )\n ) && (box12.R5[Coll[Byte]].get == placeholder[Coll[Byte]](17))\n ) && (box12.R6[Coll[Byte]].get == placeholder[Coll[Byte]](18))\n ) && (box12.R7[Box].get == box9)\n } else { placeholder[Boolean](19) }\n val coll32 = box9.R5[Coll[Byte]].get\n val coll33 = box15.tokens\n val bool34 = l18 <= l17\n val l35 = SELF.value\n val l36 = coll16(placeholder[Int](20))\n val bool37 = coll16(placeholder[Int](21)) == placeholder[Long](22)\n val tuple38 = coll33.getOrElse(placeholder[Int](23), tuple2)\n val coll39 = tuple38._1\n val l40 = tuple38._2\n val coll41 = prop10.propBytes\n val bool42 = l18 > l17\n val bool43 = if (bool37) { (bool8 && bool42) && (l18 < l17 + placeholder[Long](24)) } else { bool8 && bool34 }\n prop10 && sigmaProp(((bool11 && (OUTPUTS.size == placeholder[Int](25))) && (coll13 != coll14)) && (box15.propositionBytes != coll14)) || sigmaProp(\n (\n (\n if (((bool11 && (INPUTS.size == placeholder[Int](26))) && (OUTPUTS.size == placeholder[Int](27))) && (l19 >= placeholder[Long](28))) {\n (\n (\n (\n (\n (\n bool31 && if ((coll20.size == placeholder[Int](29)) && box12.R7[Box].isDefined) {\n (((bool24 && (coll22 == coll7)) && (l25 == l4)) && (l29 == l4 - placeholder[Long](30) / l27 + placeholder[Long](31))) && (\n box12.R7[Box].get == SELF\n )\n } else { placeholder[Boolean](32) }\n ) && (box15.propositionBytes == coll32)\n ) && (box15.value >= coll16(placeholder[Int](33)))\n ) && (coll33.size == placeholder[Int](34))\n ) && (OUTPUTS(placeholder[Int](35)).value == placeholder[Long](36))\n ) && (OUTPUTS(placeholder[Int](37)).tokens.size == placeholder[Int](38))\n } else { placeholder[Boolean](39) } || if ((\n ((bool34 && (!(bool34 && (l18 > l17 - placeholder[Long](40))))) && (INPUTS.size == placeholder[Int](41))) && (OUTPUTS.size == placeholder[Int](42))\n ) && (CONTEXT.dataInputs.size == placeholder[Int](43))) {(\n val box44 = CONTEXT.dataInputs(placeholder[Int](44))\n val l45 = l6 - l29\n val l46 = box44.R4[Long].get\n val l47 = l46 - l36\n val l48 = max(placeholder[Long](45), l47 * l26)\n val coll49 = Coll[(Long, Long)](\n (placeholder[Long](46), placeholder[Long](47)), (placeholder[Long](48), placeholder[Long](49)), (placeholder[Long](50), placeholder[Long](51)), (\n placeholder[Long](52), placeholder[Long](53)\n ), (placeholder[Long](54), placeholder[Long](55))\n )\n val i50 = coll49.map({(tuple50: (Long, Long)) => if (tuple50._1 >= l19) { placeholder[Long](56) } else { placeholder[Long](57) } }).indexOf(\n placeholder[Long](58), placeholder[Int](59)\n )\n val tuple51 = coll49(i50 - placeholder[Int](60))\n val l52 = tuple51._2\n val tuple53 = coll49(i50)\n val l54 = tuple51._1\n val l55 = l52 + tuple53._2 - l52 * l19 - l54 / tuple53._1 - l54\n val l56 = placeholder[Long](61) * coll16(placeholder[Int](62)) * l26 * l36 * l55 / placeholder[Long](63)\n val l57 = max(placeholder[Long](64), l56 - l56 * coll16(placeholder[Int](65)) * max(l47, l36 - l46) / placeholder[Long](66) * l36)\n val l58 = l45 * if (bool37) { l48 + l57 } else { l48 + l57 + l57 * coll16(placeholder[Int](67)) * l55 / placeholder[Long](68) }\n val l59 = max(placeholder[Long](69), l58)\n val l60 = max(placeholder[Long](70), l58 * coll16(placeholder[Int](71)) / placeholder[Long](72))\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((box44.tokens(placeholder[Int](73))._1 == placeholder[Coll[Byte]](74)) && bool31) && (l23 == l35)) && (\n box12.R7[Box].get == box9\n )\n ) && (box15.value >= INPUTS(placeholder[Int](75)).value - placeholder[Long](76) - l59 - l60)\n ) && (coll33.size == placeholder[Int](77))\n ) && (coll39 == coll30)\n ) && (l40 == l45)\n ) && (OUTPUTS(placeholder[Int](78)).propositionBytes == coll41)\n ) && (OUTPUTS(placeholder[Int](79)).value >= l59)\n ) && (OUTPUTS(placeholder[Int](80)).tokens.size == placeholder[Int](81))\n ) && (OUTPUTS(placeholder[Int](82)).propositionBytes == coll32)\n ) && (OUTPUTS(placeholder[Int](83)).value >= l60)\n ) && (OUTPUTS(placeholder[Int](84)).tokens.size == placeholder[Int](85))\n ) && (OUTPUTS(placeholder[Int](86)).value == placeholder[Long](87))\n ) && (OUTPUTS(placeholder[Int](88)).tokens.size == placeholder[Int](89))\n )} else { placeholder[Boolean](90) }\n ) || if (((bool43 && (INPUTS.size == placeholder[Int](91))) && (OUTPUTS.size == placeholder[Int](92))) && (\n CONTEXT.dataInputs.size == placeholder[Int](93)\n )) {(\n val l44 = l4 - l25\n (\n (\n (\n (\n ((((bool31 && (l29 == l6)) && (coll39 == coll7)) && (l40 == l44)) && (coll33.size == placeholder[Int](94))) && (\n OUTPUTS(placeholder[Int](95)).propositionBytes == coll41\n )\n ) && (OUTPUTS(placeholder[Int](96)).value >= l44 / l27 * l36 * l26)\n ) && (OUTPUTS(placeholder[Int](97)).tokens.size == placeholder[Int](98))\n ) && (OUTPUTS(placeholder[Int](99)).value == placeholder[Long](100))\n ) && (OUTPUTS(placeholder[Int](101)).tokens.size == placeholder[Int](102))\n )} else { placeholder[Boolean](103) }\n ) || if (((bool42 && (!bool43)) && (coll1.size == placeholder[Int](104))) && (OUTPUTS.size == placeholder[Int](105))) {\n (((((coll13 == coll41) && (l23 == l35 - placeholder[Long](106))) && (coll20.size == placeholder[Int](107))) && (coll22 == coll7)) && (l25 == l4)) && (\n coll33.size == placeholder[Int](108)\n )\n } else { placeholder[Boolean](109) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "777777e5051f8a6bc30827ee41dd39e04bca1dba35236b9a26b494e0bac84f33",
"index": 0,
"amount": 1001,
"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": "1109020280f0ccc7b961e807e807d804feac98e1050a80897a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1,1,1674172800000,500,500,300,772999999,5,1000000]"
},
"R7": {
"serializedValue": "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",
"sigmaType": null,
"renderedValue": null
},
"R9": {
"serializedValue": "08cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6",
"sigmaType": "SSigmaProp",
"renderedValue": "039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6"
},
"R4": {
"serializedValue": "0e2b43414c4c5f66616b655553445f4552475f3737323939393939395f323032332d30312d32305f7065725f31",
"sigmaType": "Coll[SByte]",
"renderedValue": "43414c4c5f66616b655553445f4552475f3737323939393939395f323032332d30312d32305f7065725f31"
}
},
"spentTransactionId": "12fbee21fb654cb7ccc2c2bf3fe71e8bf955c6e189900a4a88f38a1f6ab13193",
"mainChain": true
}