Transaction
ID: 7d37142d8f...f0ff
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
1.21 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.813423424 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0042 ERG
Tokens:
10.01
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.02 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 846,562
Total coins transferred: 2.02 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000327 ERG
Raw Transaction Data
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 1\n4: 3\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: 2100000\n16: 1\n17: false\n18: 0\n19: 1\n20: 0\n21: CBigInt(1000000)\n22: 86400000\n23: 2\n24: 1\n25: 86400000\n26: 2100000\n27: 1\n28: 1\n29: 2\n30: 1\n31: 2100000\n32: 9\n33: false\n34: 14400000\n35: 2\n36: 0\n37: 0\n38: 0\n39: 0\n40: 0\n41: 100\n42: 500\n43: 1000\n44: 2000\n45: 4000\n46: 9000\n47: 13000\n48: 20000\n49: 30000\n50: 40000\n51: 50000\n52: 70000\n53: 110000\n54: 140000\n55: 170000\n56: 210000\n57: 250000\n58: 300000\n59: 500000\n60: 1\n61: 0\n62: 1\n63: 0\n64: 1\n65: 4\n66: 4\n67: 1775840000\n68: CBigInt(0)\n69: 5\n70: 1000\n71: 6\n72: 177584000\n73: 10000\n74: 0\n75: 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)\n76: 30\n77: 1\n78: 2\n79: 2\n80: 3\n81: 3\n82: 8\n83: CBigInt(1000)\n84: false\n85: 2\n86: 4\n87: 0\n88: 1\n89: 0\n90: 2\n91: 0\n92: 0\n93: 1\n94: 0\n95: 0\n96: 1\n97: false\n98: 1100000\n99: 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 = SELF.propositionBytes\n val box12 = OUTPUTS(placeholder[Int](3))\n val coll13 = box6.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = CONTEXT.preHeader.timestamp\n val l16 = l14 - l15\n val coll17 = box9.tokens\n val tuple18 = coll17.getOrElse(placeholder[Int](5), tuple2)\n val l19 = tuple18._2\n val l20 = tuple3._2\n val bool21 = coll13(placeholder[Int](6)) == placeholder[Long](7)\n val l22 = coll13(placeholder[Int](8))\n val l23 = l22 * placeholder[Long](9)\n val tuple24 = coll17.getOrElse(placeholder[Int](10), tuple2)\n val l25 = tuple24._2\n val l26 = SELF.value\n val l27 = coll13(placeholder[Int](11))\n val coll28 = tuple24._1\n val coll29 = box6.id\n val coll30 = placeholder[Coll[Byte]](12)\n val coll31 = placeholder[Coll[Byte]](13)\n val bool32 = if (coll10 == coll11) {\n (\n (\n (\n (\n (((coll28 == coll29) && (l25 >= placeholder[Long](14))) && (box9.value >= placeholder[Long](15))) && (\n ((bool21 && (tuple18._1 == coll30)) && (l19 >= placeholder[Long](16))) || (!bool21)\n )\n ) && (box9.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)\n ) && (box9.R5[Coll[Byte]].get == coll31)\n ) && (box9.R6[Coll[Byte]].get == coll31)\n ) && (box9.R7[Box].get == box6)\n } else { placeholder[Boolean](17) }\n val coll33 = box6.R5[Coll[Byte]].get\n val bool34 = l15 <= l14\n val l35 = box9.value\n val coll36 = box12.tokens\n val tuple37 = coll36.getOrElse(placeholder[Int](18), tuple2)\n val coll38 = tuple37._1\n val l39 = tuple37._2\n val coll40 = prop7.propBytes\n val bool41 = coll13(placeholder[Int](19)) == placeholder[Long](20)\n val bi42 = placeholder[BigInt](21)\n val bool43 = l15 > l14\n val bool44 = if (bool41) { (bool5 && bool43) && (l15 < l14 + placeholder[Long](22)) } else { bool5 && bool34 }\n prop7 && sigmaProp(((bool8 && (OUTPUTS.size == placeholder[Int](23))) && (coll10 != coll11)) && (box12.propositionBytes != coll11)) || sigmaProp(\n (\n (\n if ((bool8 && (INPUTS.size == placeholder[Int](24))) && (l16 >= placeholder[Long](25))) {\n (\n (\n bool32 && (\n ((box9.value >= placeholder[Long](26)) && (box9.R7[Box].get == SELF)) && (\n (\n ((bool21 && (l19 == l20)) && (l25 == l20 - placeholder[Long](27) / l23 + placeholder[Long](28))) && (coll17.size == placeholder[Int](29))\n ) || (((!bool21) && (coll17.size == placeholder[Int](30))) && (l25 == l26 - placeholder[Long](31) / l27))\n )\n )\n ) && (box12.propositionBytes == coll33)\n ) && (box12.value >= coll13(placeholder[Int](32)))\n } else { placeholder[Boolean](33) } || if (((!(bool34 && (l15 > l14 - placeholder[Long](34)))) && (INPUTS.size == placeholder[Int](35))) && (\n CONTEXT.dataInputs.size > placeholder[Int](36)\n )) {(\n val box45 = CONTEXT.dataInputs(placeholder[Int](37))\n val l46 = l20 - l25\n val l47 = box45.R4[Long].get\n val l48 = if (bool21) { max(placeholder[Long](38), l47 - l27 * l22) } else { max(placeholder[Long](39), l27 - l47 * l22) }\n val coll49 = Coll[Long](\n placeholder[Long](40), placeholder[Long](41), placeholder[Long](42), placeholder[Long](43), placeholder[Long](44), placeholder[Long](\n 45\n ), placeholder[Long](46), placeholder[Long](47), placeholder[Long](48), placeholder[Long](49), placeholder[Long](50), placeholder[Long](\n 51\n ), placeholder[Long](52), placeholder[Long](53), placeholder[Long](54), placeholder[Long](55), placeholder[Long](56), placeholder[Long](\n 57\n ), placeholder[Long](58), placeholder[Long](59)\n )\n val coll50 = coll49.map({(l50: Long) => l50 * l50 }).zip(coll49)\n val i51 = coll50.map({(tuple51: (Long, Long)) => if (tuple51._1 >= l16) { placeholder[Long](60) } else { placeholder[Long](61) } }).indexOf(\n placeholder[Long](62), placeholder[Int](63)\n )\n val tuple52 = coll50(i51 - placeholder[Int](64))\n val l53 = tuple52._2\n val tuple54 = coll50(i51)\n val l55 = tuple52._1\n val bi56 = l53.toBigInt + tuple54._2 - l53.toBigInt * l16 - l55.toBigInt / tuple54._1 - l55.toBigInt\n val bi57 = placeholder[Long](65) * coll13(placeholder[Int](66)).toBigInt * l22.toBigInt * l27.toBigInt * bi56 / placeholder[Int](67).toBigInt\n val bi58 = max(\n placeholder[BigInt](68), bi57 - bi57 * coll13(placeholder[Int](69)).toBigInt * max(l47 - l27, l27 - l47).toBigInt / placeholder[Long](\n 70\n ) * l27.toBigInt\n )\n val bi59 = if (bool41) { l48.toBigInt + bi58 } else {\n l48.toBigInt + bi58 + bi58 * coll13(placeholder[Int](71)).toBigInt * bi56 / placeholder[Int](72).toBigInt\n }\n val bi60 = l46.toBigInt * bi59 - bi59 % placeholder[Long](73).toBigInt\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (box45.tokens(placeholder[Int](74))._1 == placeholder[Coll[Byte]](75)) && (HEIGHT <= box45.R5[Int].get + placeholder[Int](76))\n ) && bool32\n ) && (l35 == l26)\n ) && ((bool21 && (l19 == coll1.getOrElse(placeholder[Int](77), tuple2)._2)) || (!bool21))\n ) && (coll38 == coll29)\n ) && (l39 == l46)\n ) && (OUTPUTS(placeholder[Int](78)).propositionBytes == coll40)\n ) && (OUTPUTS(placeholder[Int](79)).value.toBigInt >= max(bi42, bi60))\n ) && (OUTPUTS(placeholder[Int](80)).propositionBytes == coll33)\n ) && (OUTPUTS(placeholder[Int](81)).value.toBigInt >= max(bi42, bi60 * coll13(placeholder[Int](82)).toBigInt / placeholder[BigInt](83)))\n )} else { placeholder[Boolean](84) }\n ) || if (((bool44 && (INPUTS.size == placeholder[Int](85))) && (OUTPUTS.size == placeholder[Int](86))) && (\n CONTEXT.dataInputs.size == placeholder[Int](87)\n )) {(\n val l45 = if (bool21) { l20 - l25 } else { l26 - l35 }\n val l46 = if (bool21) { l45 / l23 } else { l45 / l27 * l22 }\n val tuple47 = INPUTS(placeholder[Int](88)).tokens.getOrElse(placeholder[Int](89), tuple2)\n val box48 = OUTPUTS(placeholder[Int](90))\n val coll49 = box48.tokens\n val tuple50 = coll49.getOrElse(placeholder[Int](91), tuple2)\n (\n (((l46 == if (tuple47._1 == coll29) { tuple47._2 } else { placeholder[Long](92) }) && bool32) && (l25 == l20)) && (\n (\n ((((bool21 && (coll38 == coll30)) && (l39 == l45)) && (coll36.size == placeholder[Int](93))) && (box48.value >= l46 * l27 * l22)) && (\n coll49.size == placeholder[Int](94)\n )\n ) || (\n (((((!bool21) && (box12.value >= l45)) && (coll36.size == placeholder[Int](95))) && (tuple50._1 == coll30)) && (tuple50._2 >= l46 * l23)) && (\n coll49.size == placeholder[Int](96)\n )\n )\n )\n ) && (box48.propositionBytes == coll40)\n )} else { placeholder[Boolean](97) }\n ) || if (bool43 && (!bool44)) {\n ((coll10 == coll40) && ((bool21 && (coll28 == coll30)) && (l25 == l20))) || ((!bool21) && (l35 >= l26 - placeholder[Long](98)))\n } else { placeholder[Boolean](99) }\n )\n}",
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"assets": [
{
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"index": 0,
"amount": 1001,
"name": "fakeUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd039ed9a6df20fca487da2d3b58e822cdcc5bcfad4cca794eadf132afa3113f31a6"
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[0,1,1,1681603200000,500,500,300,1406499999,5,1000000]"
},
"R7": {
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"sigmaType": null,
"renderedValue": null
},
"R9": {
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"sigmaType": "SSigmaProp",
"renderedValue": "02042a3559387831c22aaec64a86969b6f2e4b7626b3f94cbec08123c5dc88d23e"
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"R4": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "43616c6c5f415f66616b655553445f4552475f313430363439393939395f323032332d30342d31365f7065725f31"
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},
"spentTransactionId": "4df062c3128f8f149051837a4fba145e7a4f01e164db6438f5873a9a0f7f5586",
"mainChain": true
},
{
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"transactionId": "7d37142d8f39c7f7e27b6d04d735f353db482d87f05f30d0c76a7473b48bf0ff",
"blockId": "b9cee45618680418395fe99a815311943a5d7815eab3666dc9dbd9adc5ebe563",
"value": 2015623423,
"index": 1,
"globalIndex": 25638591,
"creationHeight": 918793,
"settlementHeight": 918795,
"ergoTree": "0008cd02042a3559387831c22aaec64a86969b6f2e4b7626b3f94cbec08123c5dc88d23e",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(42a355,5a35ff,...)))}",
"address": "9eYtuDups24XXqzbYTn3qHoknh65EqbcFJhFU7pRNoXZo3hGish",
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