Ad
Inputs (1)
Output transaction:
Settlement height:
Value:
26.37 ERG
Tokens:
Loading assets...
Outputs (4)
Spent in transaction:
Settlement height:
Value:
0.015 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
26.2 ERG
Tokens:
Loading assets...
Spent in transaction:
Settlement height:
Value:
0.15 ERG
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Transaction Details
Status: Confirmed
Size: 3.42 KB
Received time: 8/5/2023 09:53:36 AM
Included in blocks: 1,062,377
Confirmations: 714,087
Total coins transferred: 26.37 ERG
Fees: 0.005 ERG
Fees per byte: 0.000001428 ERG
Raw Transaction Data
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  "inclusionHeight": 1062377,
  "timestamp": 1691229216917,
  "index": 8,
  "globalIndex": 5622870,
  "numConfirmations": 714087,
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      "ergoTree": "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",
      "ergoTreeConstants": "0: 1\n1: 0\n2: 0\n3: 0\n4: 2\n5: 0\n6: 1\n7: 0\n8: 0\n9: 0\n10: 1\n11: 3\n12: 0\n13: 3\n14: 0\n15: 2\n16: 1\n17: 1000\n18: 0\n19: 2\n20: 10\n21: 2\n22: 0\n23: 0\n24: 0\n25: 0\n26: 0\n27: 3\n28: 0\n29: 1000\n30: 1000\n31: 1000\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: 1\n48: 0\n49: 1\n50: 0\n51: 0\n52: 0\n53: 0\n54: 1\n55: 0\n56: 1\n57: 2\n58: 0\n59: false\n60: 0\n61: 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 coll11 = SELF.R4[Coll[Byte]].get\n  val l12 = CONTEXT.preHeader.timestamp\n  val tuple13 = SELF.R5[(Long, Long)].get\n  val l14 = tuple13._1\n  val l15 = tuple13._2\n  val box16 = CONTEXT.dataInputs(placeholder[Int](3))\n  val i17 = box16.R4[Int].get\n  val box18 = OUTPUTS.getOrElse(placeholder[Int](4), SELF)\n  val coll19 = box18.tokens\n  val l20 = box18.value\n  val tuple21 = (coll2, l20)\n  val tuple22 = coll19.getOrElse(placeholder[Int](5), tuple21)\n  val box23 = OUTPUTS.getOrElse(placeholder[Int](6), SELF)\n  val coll24 = box23.tokens\n  val l25 = box23.value\n  val tuple26 = (coll2, l25)\n  val tuple27 = coll24.getOrElse(placeholder[Int](7), tuple26)\n  val coll28 = SELF.R8[Coll[Byte]].get\n  val bool29 = INPUTS(placeholder[Int](8)).id == SELF.id\n  val box30 = OUTPUTS(placeholder[Int](9))\n  val coll31 = box30.tokens\n  val l32 = box30.value\n  val tuple33 = (coll2, l32)\n  val tuple34 = coll31.getOrElse(placeholder[Int](10), tuple33)\n  val l35 = tuple34._2\n  val l36 = coll7.getOrElse(placeholder[Int](11), placeholder[Long](12))\n  sigmaProp(l10 < l8) && proveDlog(decodePoint(coll11.slice(placeholder[Int](13), coll11.size))) || sigmaProp(if (l12 > l14) { if (l12 > l15) {(\n        val i37 = OUTPUTS.size\n        val box38 = OUTPUTS(placeholder[Int](14))\n        val l39 = placeholder[Long](15) * box16.R6[Long].get\n        val box40 = box18\n        val coll41 = coll19\n        val l42 = l20\n        val tuple43 = tuple21\n        val tuple44 = tuple22\n        val box45 = box23\n        val box46 = box45.R4[Box].getOrElse(OUTPUTS(i37 - placeholder[Int](16)))\n        val opt47 = box46.R4[Int]\n        val bool48 = opt47.isDefined\n        val i49 = placeholder[Int](17) - i17 - if (bool48) {(\n          val i49 = opt47.getOrElse(placeholder[Int](18))\n          if ((i49 < placeholder[Int](19)) || (i49 >= placeholder[Int](20))) { i49 } else { if ((i49 == placeholder[Int](21)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) { box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]()).fold(placeholder[Int](22), {(tuple50: (Int, (Coll[Byte], Int))) => tuple50._1 + tuple50._2._2 }) } else { placeholder[Int](23) } }\n        )} else { placeholder[Int](24) }\n        val coll50 = coll24\n        val l51 = l25\n        val tuple52 = tuple26\n        val tuple53 = tuple27\n        val box54 = OUTPUTS.getOrElse(placeholder[Int](25), SELF)\n        val tuple55 = coll1(placeholder[Int](26))\n        ((l10 < l8) && allOf(Coll[Boolean](i37 == placeholder[Int](27), box38.tokens == coll1, box38.value >= l3 - l39, box38.propositionBytes == coll11))) || ((l10 >= l8) && allOf(Coll[Boolean](bool29, ((box40.propositionBytes == coll11) && (tuple44._2 >= if (coll9.size > placeholder[Int](28)) { l10 * i49.toLong / placeholder[Long](29) } else { l10 * i49.toLong / placeholder[Long](30) - l39 })) && (tuple44._1 == coll9), ((box45.propositionBytes == box16.R5[Coll[Byte]].get) && (tuple53._2 >= l10 * i17.toLong / placeholder[Long](31))) && (tuple53._1 == coll9), box54.propositionBytes == coll28, tuple55 == box54.tokens(placeholder[Int](32)), if (bool48) {(\n                val i56 = opt47.get\n                if ((i56 < placeholder[Int](33)) || (i56 >= placeholder[Int](34))) {(\n                  val box57 = OUTPUTS.getOrElse(placeholder[Int](35), SELF)\n                  val tuple58 = box57.tokens.getOrElse(placeholder[Int](36), (coll2, box57.value))\n                  ((tuple58._2 >= l10 * i56.toLong / placeholder[Long](37)) && (tuple58._1 == coll9)) && (box57.propositionBytes == box46.propositionBytes)\n                )} else { if ((i56 == placeholder[Int](38)) && box46.R5[Coll[(Coll[Byte], Int)]].isDefined) {(\n                    val coll57 = box46.R5[Coll[(Coll[Byte], Int)]].getOrElse(Coll[(Coll[Byte], Int)]())\n                    val i58 = coll57.size\n                    coll57.map({(tuple59: (Coll[Byte], Int)) => (tuple59._1, tuple59._2.toLong * l10 / placeholder[Long](39)) }).slice(placeholder[Int](40), i58) == OUTPUTS.slice(placeholder[Int](41), placeholder[Int](42) + i58).map({(box59: Box) =>\n                        val tuple61 = box59.tokens.getOrElse(placeholder[Int](43), (coll2, box59.value))\n                        if (tuple61._1 == coll9) { (box59.propositionBytes, tuple61._2) } else { (coll2, placeholder[Long](44)) }\n                      })\n                  )} else { placeholder[Boolean](45) } }\n              )} else { placeholder[Boolean](46) } && (blake2b256(box46.bytes) == tuple55._1))))\n      )} else {(\n        val box37 = box30\n        val coll38 = coll31\n        val l39 = l32\n        val tuple40 = tuple33\n        val tuple41 = tuple34\n        val coll42 = box16.R7[Coll[Long]].get\n        val box43 = OUTPUTS(placeholder[Int](47))\n        val tuple44 = box43.tokens.getOrElse(placeholder[Int](48), (coll2, box43.value))\n        allOf(Coll[Boolean](bool29, tuple41._1 == coll9, l35 >= max(l10 + coll7(placeholder[Int](49)), l8), coll1(placeholder[Int](50)) == coll38(placeholder[Int](51)), box37.propositionBytes == SELF.propositionBytes, box37.R4[Coll[Byte]].get == coll11, box37.R5[(Long, Long)].get == (l14, if ((l36 > placeholder[Long](52)) && \n                val l45 = l35\n                l45 >= l36\n              ) { l12 } else { if (l15 - l12 <= coll42(placeholder[Int](53))) { l15 + coll42(placeholder[Int](54)) } else { l15 } }), box37.R6[Coll[Long]] == opt6, box37.R7[Coll[Byte]].get == coll9, coll38.size == if (coll9.size == placeholder[Int](55)) { placeholder[Int](56) } else { placeholder[Int](57) }, box43.propositionBytes == coll28, ((tuple44._1 == coll9) && (tuple44._2 >= l10)) || (l10 == placeholder[Long](58))))\n      )} } else { placeholder[Boolean](59) }) && sigmaProp(box16.tokens(placeholder[Int](60))._1 == placeholder[Coll[Byte]](61))\n}",
      "address": "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",
      "assets": [
        {
          "tokenId": "67154b2098110089f5c6904c9183bfb18fcca6334bb70e70bed70275691fa2bb",
          "index": 0,
          "amount": 1,
          "name": "Peperg #5",
          "decimals": 0,
          "type": "EIP-004"
        }
      ],
      "additionalRegisters": {
        "R5": {
          "serializedValue": "59d6d6afd2b862a0f4c6c3b962",
          "sigmaType": "(SLong, SLong)",
          "renderedValue": "[1691229746603,1691348426000]"
        },
        "R6": {
          "serializedValue": "11028090dfc04a80a8d6b907",
          "sigmaType": "Coll[SLong]",
          "renderedValue": "[10000000000,1000000000]"
        },
        "R8": {
          "serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
        },
        "R7": {
          "serializedValue": "0e00",
          "sigmaType": "Coll[SByte]",
          "renderedValue": ""
        },
        "R4": {
          "serializedValue": "0e240008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
          "sigmaType": "Coll[SByte]",
          "renderedValue": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5"
        }
      },
      "spentTransactionId": "519859ed97bd8020aa2116b5fb60aed9d6ca20824a59551d4b59782dccb48a3d",
      "mainChain": true
    },
    {
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      "transactionId": "7974fae71ba33d57c879ea68db1211c627a6866c1e1090cb6ced3a8a87922245",
      "blockId": "fd3d708d6a7a3d290b939be286295ba3ca8b84dcba81bff7c69182044796952a",
      "value": 26197296698,
      "index": 1,
      "globalIndex": 31535453,
      "creationHeight": 1062375,
      "settlementHeight": 1062377,
      "ergoTree": "0008cd023296cab9de6fa54812445e3a2b30b6bb7476d4a0b444dc3042202011ff85a8c5",
      "ergoTreeConstants": "",
      "ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3296ca,9154f2,...)))}",
      "address": "9euLk6oVwEKSCQxCE6qj1vKcFjzk9Toy4YPyC9JB5uPmtLnpHj7",
      "assets": [
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          "decimals": 0,
          "type": "EIP-004"
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          "decimals": 0,
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          "decimals": 0,
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