Transaction
ID: f2ae7f6ceb...a4ec
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
4.24 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0021 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.24 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0011 ERG
Transaction Details
Confirmations: 582,033
Total coins transferred: 4.25 ERG
Fees: 0.0011 ERG
Fees per byte: 0.000000306 ERG
Raw Transaction Data
{
"id": "f2ae7f6ceb68fb40c75a66dad357a8e7fc8de44803e36278a63eb7f5599fa4ec",
"blockId": "b70d667774dce4302d6127f07afcd6761952f916ab31ff3f5eb62f8eaac02e5b",
"inclusionHeight": 1178016,
"timestamp": 1705254173669,
"index": 11,
"globalIndex": 6470107,
"numConfirmations": 582033,
"inputs": [
{
"boxId": "ed8f562b6b22593bf966e3c73681e5b3f09227b365608fa1bc4ed7d6a1e99a98",
"value": 4244118047,
"index": 0,
"spendingProof": "6b3c6edce477b2d0d6064904d6fde42ea30c27f95cfcf2a6fd499ceea156bc2143213ba1cd096d378b557b26debabe80925b7b813db5c611",
"outputBlockId": "57aa4f6766046a7af9489eafc935d486f311f105834e258a1b264b003bc2d0e9",
"outputTransactionId": "d67724dd94290d669d121efea0c5ce4f2764a74532b916d09e582809310d2431",
"outputIndex": 1,
"outputGlobalIndex": 36103121,
"outputCreatedAt": 1177999,
"outputSettledAt": 1178001,
"ergoTree": "0008cd03a7abc629961e781e824b8d0cff264a92197e7701a3907f987bb80540a9e9d49f",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(a7abc6,fb6941,...)))}",
"address": "9hjed2L2mpQod5s2XMmugypqzTLA69bkCkkA2Fb2jefwxXWavzT",
"assets": [
{
"tokenId": "8b08cdd5449a9592a9e79711d7d79249d7a03c535d17efaee83e216e80a44c4b",
"index": 0,
"amount": 907000,
"name": "RSN",
"decimals": 3,
"type": "EIP-004"
},
{
"tokenId": "bde52d7f7ceba350cae6092bbf44207c38a1d6e4414f83463dfed0b13ef26062",
"index": 1,
"amount": 1,
"name": "$COMET Oniric 3D Collection 2590",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a248b7e5e6dfcd30f24bf8cf5d07ff2e90cc1d1bcfccf8e4c0ceaca1be8a45dc",
"index": 2,
"amount": 1,
"name": "CyberDog #4",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f57460c0089503e9f349ab48e02a4beee9caf9d944335746b429dd46f471970f",
"index": 3,
"amount": 1,
"name": "ERGO SUMMIT 2022 EGG",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "7d01c7f5e6318f1cde5897d42ead9d3e3f53f5bff241823e5232c76c2654ccc4",
"index": 4,
"amount": 1,
"name": "Gnomekin #2965 ERGnomes Halloween '21 Special",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ff79afe6abd7d58371cdf14750621357229f37332df0aaac8a8bb50904cb021b",
"index": 5,
"amount": 1,
"name": "CyberBear #2",
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"type": "EIP-004"
},
{
"tokenId": "c3a9f99fd5f056ad146245713c15c9a5465dbfe8315f38fd7b50aa286452cfa2",
"index": 6,
"amount": 1,
"name": "Capitals of asia - Singapore",
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{
"tokenId": "ea6458da6ad10e1b81a458728f7f124c1da30a100dc9ff41d35e6a0b98b6e9aa",
"index": 7,
"amount": 1,
"name": "Puppy Dog",
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},
{
"tokenId": "411c4a6f0c1e1ebeec12e5bc9be984caba0024dfaa7a3441125dbdd67684e8be",
"index": 8,
"amount": 1,
"name": "Ergo Champions #1371",
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"type": "EIP-004"
},
{
"tokenId": "a3afb2f9a331c2c9950d705bab920e1aca90dbb9962ed51d8d98aa8b95ed6700",
"index": 9,
"amount": 1,
"name": "Cybercitizen #1696",
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"type": "EIP-004"
},
{
"tokenId": "c361b09b7733ef2c75cc39bc92f37fb977ebc569882885cae71526e9afcc2134",
"index": 10,
"amount": 1,
"name": "Mini Champs #460",
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"type": "EIP-004"
},
{
"tokenId": "70c8008df23f7fe902f2ee554402e22ee111793502ce99c39b5360bdf9382175",
"index": 11,
"amount": 1,
"name": "CyberBull #1",
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"type": "EIP-004"
},
{
"tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
"index": 12,
"amount": 189,
"name": "SigUSD",
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"type": "EIP-004"
},
{
"tokenId": "e023c5f382b6e96fbd878f6811aac73345489032157ad5affb84aefd4956c297",
"index": 13,
"amount": 120076,
"name": "rsADA",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {}
},
{
"boxId": "5d61f9e1da09793bd8d1e28aee95083b0e892711ea71f0f9daf9439587ebb074",
"value": 1000000,
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"outputBlockId": "51595f5e6957a99980109ba49ba556e2028a093724c34e68541bfa1c44b14852",
"outputTransactionId": "87c8cf3dd608118901397ac2ffe2403606c20faef387033d750803c488b1fd3a",
"outputIndex": 0,
"outputGlobalIndex": 36103148,
"outputCreatedAt": 1178001,
"outputSettledAt": 1178003,
"ergoTree": "0008cd03a7abc629961e781e824b8d0cff264a92197e7701a3907f987bb80540a9e9d49f",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(a7abc6,fb6941,...)))}",
"address": "9hjed2L2mpQod5s2XMmugypqzTLA69bkCkkA2Fb2jefwxXWavzT",
"assets": [
{
"tokenId": "1734c44b1c8f999bc922434eb6ba4794187c16da35eefc9c690c88e81e0db2d6",
"index": 0,
"amount": 1500,
"name": "Call_A_SigUSD_ERG_462400000_2024-04-12_per_100",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "08cd03a7abc629961e781e824b8d0cff264a92197e7701a3907f987bb80540a9e9d49f",
"sigmaType": "SSigmaProp",
"renderedValue": "03a7abc629961e781e824b8d0cff264a92197e7701a3907f987bb80540a9e9d49f"
},
"R5": {
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}
],
"dataInputs": [],
"outputs": [
{
"boxId": "c1760bfea75a3660606496b8dd807ce824e911bf6182509cea28ddf0a985234b",
"transactionId": "f2ae7f6ceb68fb40c75a66dad357a8e7fc8de44803e36278a63eb7f5599fa4ec",
"blockId": "b70d667774dce4302d6127f07afcd6761952f916ab31ff3f5eb62f8eaac02e5b",
"value": 2100000,
"index": 0,
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"ergoTreeConstants": "0: 3\n1: 3\n2: 0\n3: 6\n4: 0\n5: 0\n6: 0\n7: 1\n8: 0\n9: 2\n10: 0\n11: 0\n12: CBigInt(1000)\n13: CBigInt(1000000)\n14: 2\n15: 0\n16: 0\n17: 4\n18: 100\n19: 0\n20: 0\n21: 0\n22: 100\n23: 500\n24: 1000\n25: 2000\n26: 4000\n27: 9000\n28: 13000\n29: 20000\n30: 30000\n31: 40000\n32: 50000\n33: 70000\n34: 110000\n35: 140000\n36: 170000\n37: 210000\n38: 250000\n39: 300000\n40: 500000\n41: 1000000\n42: 10000000\n43: 1\n44: 0\n45: 1\n46: 0\n47: 0\n48: 1\n49: CBigInt(1)\n50: CBigInt(0)\n51: 4\n52: 0\n53: 1775840000\n54: CBigInt(0)\n55: 1\n56: CBigInt(177584)\n57: CBigInt(1)\n58: 1\n59: 0\n60: 2\n61: 177584000\n62: 10000\n63: CBigInt(100)\n64: 0\n65: Coll(1,29,51,100,-34,7,-27,-94,111,12,78,-17,8,82,-51,-37,56,112,57,-87,33,-73,21,78,-13,-54,-78,44,110,-38,-120,127)\n66: 30\n67: 1000000\n68: 0\n69: false\n70: 2\n71: 2\n72: 3\n73: 3\n74: 4\n75: false\n76: 0\n77: 2\n78: false",
"ergoTreeScript": "{\n val prop1 = SELF.R4[SigmaProp].get\n val l2 = CONTEXT.preHeader.timestamp\n val box3 = SELF.R5[Box].get\n val coll4 = box3.R8[Coll[Long]].get\n val l5 = coll4(placeholder[Int](0))\n val coll6 = SELF.R6[Coll[Long]].get\n val l7 = l5 - coll6(placeholder[Int](1))\n val box8 = OUTPUTS(placeholder[Int](2))\n val coll9 = box8.propositionBytes\n val l10 = coll4(placeholder[Int](3))\n val coll11 = box3.id\n val tuple12 = (Coll[Byte](), placeholder[Long](4))\n val tuple13 = SELF.tokens.getOrElse(placeholder[Int](5), tuple12)\n val tuple14 = box8.tokens.getOrElse(placeholder[Int](6), tuple12)\n val l15 = tuple14._2\n val coll16 = SELF.R7[Coll[Byte]].get\n val l17 = SELF.value\n val tuple18 = OUTPUTS(placeholder[Int](7)).tokens.getOrElse(placeholder[Int](8), tuple12)\n val l19 = tuple13._2\n val coll20 = prop1.propBytes\n val l21 = coll4(placeholder[Int](9))\n val bool22 = coll4(placeholder[Int](10)) == placeholder[Long](11)\n val bi23 = placeholder[BigInt](12)\n val bi24 = placeholder[BigInt](13)\n prop1 || sigmaProp(if (((l2 <= l7) && (INPUTS.size == placeholder[Int](14))) && (CONTEXT.dataInputs.size > placeholder[Int](15))) {(\n val box25 = CONTEXT.dataInputs(placeholder[Int](16))\n val l26 = l19 - l15\n val l27 = box25.R4[Long].get\n val l28 = coll4(placeholder[Int](17)) * placeholder[Long](18)\n val l29 = if (bool22) { max(placeholder[Long](19), l27 - l28 * l21) } else { max(placeholder[Long](20), l28 - l27 * l21) }\n val coll30 = Coll[Long](placeholder[Long](21), placeholder[Long](22), placeholder[Long](23), placeholder[Long](24), placeholder[Long](25), placeholder[Long](26), placeholder[Long](27), placeholder[Long](28), placeholder[Long](29), placeholder[Long](30), placeholder[Long](31), placeholder[Long](32), placeholder[Long](33), placeholder[Long](34), placeholder[Long](35), placeholder[Long](36), placeholder[Long](37), placeholder[Long](38), placeholder[Long](39), placeholder[Long](40), placeholder[Long](41), placeholder[Long](42))\n val coll31 = coll30.map({(l31: Long) => l31 * l31 }).zip(coll30)\n val func32 = {(l32: Long) =>\n val i34 = coll31.map({(tuple34: (Long, Long)) => if (tuple34._1 >= l32) { placeholder[Long](43) } else { placeholder[Long](44) } }).indexOf(placeholder[Long](45), placeholder[Int](46))\n val tuple35 = coll31(i34)\n if (i34.toLong > placeholder[Long](47)) {(\n val tuple36 = coll31(i34 - placeholder[Int](48))\n val l37 = tuple36._2\n val l38 = tuple36._1\n max(placeholder[BigInt](49), l37.toBigInt + tuple35._2 - l37.toBigInt * l32 - l38.toBigInt / tuple35._1 - l38.toBigInt)\n )} else { placeholder[BigInt](50) }\n }\n val bi33 = func32(l5 - l2)\n val bi34 = placeholder[Long](51) * coll6(placeholder[Int](52)).toBigInt * l21.toBigInt * l28.toBigInt * bi33 / placeholder[Int](53).toBigInt\n val bi35 = max(placeholder[BigInt](54), bi34 - bi34 * coll6(placeholder[Int](55)).toBigInt * func32(max(l27 - l28, l28 - l27)) * placeholder[BigInt](56) / bi23 * func32(l28) * max(placeholder[BigInt](57), bi33))\n val bi36 = if (coll4(placeholder[Int](58)) == placeholder[Long](59)) { l29.toBigInt + bi35 } else { l29.toBigInt + bi35 + bi35 * coll6(placeholder[Int](60)).toBigInt * bi33 / placeholder[Int](61).toBigInt }\n val bi37 = max(bi24, bi36 - bi36 % placeholder[Long](62).toBigInt)\n val bi38 = l26.toBigInt * if (bool22) { min(l27 * l21.toBigInt, bi37) } else { min(l28 * l21.toBigInt, bi37) } / placeholder[BigInt](63)\n (((((((((box25.tokens(placeholder[Int](64))._1 == placeholder[Coll[Byte]](65)) && (HEIGHT <= box25.R5[Int].get + placeholder[Int](66))) && if (coll9 == SELF.propositionBytes) { ((((((coll11 == tuple13._1) && (box8.value >= l10 + placeholder[Long](67))) && ((tuple14._1 == coll11) || (l15 == placeholder[Long](68)))) && (box8.R4[SigmaProp].get == prop1)) && (box8.R5[Box].get == box3)) && (box8.R6[Coll[Long]].get == coll6)) && (box8.R7[Coll[Byte]].get == coll16) } else { placeholder[Boolean](69) }) && (box8.value == l17)) && (tuple18._1 == coll11)) && (tuple18._2 == l26)) && (OUTPUTS(placeholder[Int](70)).propositionBytes == coll20)) && (OUTPUTS(placeholder[Int](71)).value.toBigInt >= max(bi24, bi38))) && (OUTPUTS(placeholder[Int](72)).propositionBytes == coll16)) && (OUTPUTS(placeholder[Int](73)).value.toBigInt >= max(bi24, bi38 * coll6(placeholder[Int](74)).toBigInt / bi23))\n )} else { placeholder[Boolean](75) } || if ((l2 > l7) || (l19 == placeholder[Long](76))) { (((coll9 == coll20) && (box8.value >= l17 - l10)) && (tuple14 == tuple13)) && (OUTPUTS.size == placeholder[Int](77)) } else { placeholder[Boolean](78) })\n}",
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"name": "Call_A_SigUSD_ERG_462400000_2024-04-12_per_100",
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"sigmaType": "SSigmaProp",
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"renderedValue": null
},
"R6": {
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"sigmaType": "Coll[SLong]",
"renderedValue": "[580,50,100,14400000,2]"
},
"R7": {
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"sigmaType": "Coll[SByte]",
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{
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"ergoTree": "0008cd03a7abc629961e781e824b8d0cff264a92197e7701a3907f987bb80540a9e9d49f",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(a7abc6,fb6941,...)))}",
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