Ad
Inputs (2)
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Output transaction:
Settlement height:
Value:
176.15 ERG
Tokens:
Loading assets...
Outputs (4)
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
176.13 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
190.89
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 3.08 KB
Received time: 4/10/2024 01:37:55 PM
Included in blocks: 1,239,992
Confirmations: 528,659
Total coins transferred: 176.15 ERG
Fees: 0.005 ERG
Fees per byte: 0.000001583 ERG
Raw Transaction Data
{
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  "blockId": "7124d82647ec37c3a62ed481ec4ff1886fb9df4d89e70850d3b94df33417294a",
  "inclusionHeight": 1239992,
  "timestamp": 1712756275172,
  "index": 41,
  "globalIndex": 6990592,
  "numConfirmations": 528659,
  "inputs": [
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      "address": "9fPgLW8jYUbpNxvXA2sCLKaw1t1ULiE4PWMK2XPoY5jcWzEmUAw",
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  "outputs": [
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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: 0\n33: 2\n34: 10\n35: 3\n36: 0\n37: 1000\n38: 2\n39: 1000\n40: 0\n41: 3\n42: 3\n43: 0\n44: 0\n45: false\n46: true\n47: 0\n48: 1\n49: 0\n50: 1\n51: 0\n52: 1\n53: 0\n54: 0\n55: 0\n56: 1\n57: 0\n58: 1\n59: 2\n60: 0\n61: false\n62: 0\n63: 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.getOrElse(placeholder[Int](32))\n                if ((i52 < placeholder[Int](33)) || (i52 >= placeholder[Int](34))) {(\n                  val box53 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n                  val tuple54 = box53.tokens.getOrElse(placeholder[Int](36), (coll2, box53.value))\n                  ((tuple54._2 >= l10 * i52.toLong / placeholder[Long](37)) && (tuple54._1 == coll9)) && (box53.propositionBytes == box42.propositionBytes)\n                )} else { if ((i52 == placeholder[Int](38)) && 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](39)) }).slice(placeholder[Int](40), i54) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i54).map({(box55: Box) =>\n                        val tuple57 = box55.tokens.getOrElse(placeholder[Int](43), (coll2, box55.value))\n                        if (tuple57._1 == coll9) { (box55.propositionBytes, tuple57._2) } else { (coll2, placeholder[Long](44)) }\n                      })\n                  )} else { placeholder[Boolean](45) } }\n              )} else { placeholder[Boolean](46) } && (blake2b256(box42.bytes) == tuple51._1))))\n      )} else {(\n        val box32 = OUTPUTS(placeholder[Int](47))\n        val coll33 = box32.tokens\n        val tuple34 = coll33.getOrElse(placeholder[Int](48), (coll2, box32.value))\n        val l35 = tuple34._2\n        val bool36 = l17 > placeholder[Long](49)\n        val coll37 = box18.R7[Coll[Long]].get\n        val box38 = OUTPUTS(placeholder[Int](50))\n        val tuple39 = box38.tokens.getOrElse(placeholder[Int](51), (coll2, box38.value))\n        allOf(Coll[Boolean](bool31, tuple34._1 == coll9, (l35 >= if (bool11) { l8 } else { l10 + coll7(placeholder[Int](52)) }) || (bool36 && (l35 >= l17)), coll1(placeholder[Int](53)) == coll33(placeholder[Int](54)), 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](55))) { l16 + coll37(placeholder[Int](56)) } else { l16 }) }, box32.R6[Coll[Long]] == opt6, box32.R7[Coll[Byte]].get == coll9, coll33.size == if (coll9.size == placeholder[Int](57)) { placeholder[Int](58) } else { placeholder[Int](59) }, box38.propositionBytes == coll30, ((tuple39._1 == coll9) && (tuple39._2 >= l10)) || (l10 == placeholder[Long](60))))\n      )} } else { placeholder[Boolean](61) }) && sigmaProp(box18.tokens(placeholder[Int](62))._1 == placeholder[Coll[Byte]](63))\n}",
      "address": "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",
      "assets": [
        {
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          "index": 0,
          "amount": 1,
          "name": "CyberBober",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "5980abd683d963e0c7b4d5db63",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1712756280000,1713110422000]"
        },
        "R6": {
          "serializedValue": "11028090dfc04a80c8afa025",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,5000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd0272eef9f3de497d5f76e15c9d7f8a91bfc87610899196f8677989876e83e354d1",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd0272eef9f3de497d5f76e15c9d7f8a91bfc87610899196f8677989876e83e354d1"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd0272eef9f3de497d5f76e15c9d7f8a91bfc87610899196f8677989876e83e354d1",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd0272eef9f3de497d5f76e15c9d7f8a91bfc87610899196f8677989876e83e354d1"
        }
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      "spentTransactionId": "84d592e818b8422370fe2e4bb649ce7e1ecddebfd4a98d8f54f72fa953febe2f",
      "mainChain": true
    },
    {
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      "transactionId": "4c34f26b79ebdaf3102245f0914caf5ac7b7c4dbe99fd9422926c5216d2e6bd4",
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      "index": 1,
      "globalIndex": 39082904,
      "creationHeight": 1239990,
      "settlementHeight": 1239992,
      "ergoTree": "0008cd0272eef9f3de497d5f76e15c9d7f8a91bfc87610899196f8677989876e83e354d1",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(72eef9,ea055a,...)))}",
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