Transaction
ID: d7964cd068...90ec
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
204.7 ERG
Tokens:
Loading assets...
Outputs (4)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
9,273.29
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
204.69 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 452,295
Total coins transferred: 204.7 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000194 ERG
Raw Transaction Data
{
"id": "d7964cd0685f6da3a985cc240780b25da73868d804ebf9a4884c19ecc03590ec",
"blockId": "be7098f3244f22b73f862a10afcfc0dd107358ecf41b7a6c007d035df89fc167",
"inclusionHeight": 1305142,
"timestamp": 1720636509863,
"index": 16,
"globalIndex": 7459590,
"numConfirmations": 452295,
"inputs": [
{
"boxId": "6ae41307dd54908ca0525fb860bbb692463e5de22d65f97e26736f1aa201eadb",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "5c2bd0f11253f0a862b5ab97728a8e4915b820082d5d13c20622c112845e0ca9",
"outputTransactionId": "098ff8b376c18562ffb53934a3459a731d8821b72034d4b8cbc950fea84d16a8",
"outputIndex": 0,
"outputGlobalIndex": 41353615,
"outputCreatedAt": 1305137,
"outputSettledAt": 1305139,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(-41,22,-109,-60,-102,-124,-5,-66,-51,73,8,-55,72,19,-76,101,20,-79,-117,103,-87,-103,82,-36,30,110,71,-111,85,109,-28,19)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(37,-73,72,107,26,120,100,122,-41,-43,10,40,126,94,-107,-117,78,69,42,75,-56,105,56,-55,66,24,-41,6,-68,55,127,-16)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(13,1,-14,-16,-77,37,75,74,23,49,-31,-74,26,-41,118,65,-2,84,-34,43,-42,-115,28,111,-63,-82,78,126,-99,-33,-78,18)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.tokens\n val tuple6 = coll5(placeholder[Int](2))\n val coll7 = tuple6._1\n val bool8 = coll4 == coll7\n val box9 = OUTPUTS(placeholder[Int](3))\n val coll10 = box9.R4[Coll[Long]].get\n val coll11 = SELF.R4[Coll[Long]].get\n val l12 = tuple6._2\n val coll13 = box9.tokens\n val tuple14 = coll13(placeholder[Int](4))\n val l15 = tuple14._2\n val l16 = CONTEXT.preHeader.timestamp\n val l17 = tuple3._2\n val coll18 = placeholder[Coll[Byte]](5)\n val tuple19 = coll13(placeholder[Int](6))\n val tuple20 = coll5(placeholder[Int](7))\n val l21 = coll11(placeholder[Int](8))\n val bool22 = allOf(\n Coll[Boolean](\n box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n placeholder[Int](9)\n ) == l21, coll13.size == placeholder[Int](10)\n )\n )\n if (bool8) {(\n val tuple23 = coll2(placeholder[Int](11))\n val l24 = tuple23._2\n val l25 = coll11(placeholder[Int](12))\n val coll26 = box1.R4[Coll[Long]].get\n val coll27 = box1.R5[Coll[Byte]].get\n val box28 = OUTPUTS(placeholder[Int](13))\n val tuple29 = box28.tokens(placeholder[Int](14))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n placeholder[Int](18)\n ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n Long\n ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n placeholder[Int](26)\n ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n 29\n ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n )\n )\n )\n )} else {(\n val box23 = INPUTS(placeholder[Int](32))\n val coll24 = box23.tokens\n val tuple25 = coll24(placeholder[Int](33))\n val coll26 = tuple25._1\n if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n val box27 = INPUTS(placeholder[Int](36))\n val coll28 = box27.R4[Coll[Long]].get\n val l29 = coll11(placeholder[Int](37))\n val l30 = coll10(placeholder[Int](38))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n placeholder[Int](43)\n ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n placeholder[Int](48)\n ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n )\n )\n )\n )} else {(\n val l27 = coll11(placeholder[Int](50))\n val l28 = coll10(placeholder[Int](51))\n if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n val coll33 = tuple31._2.tokens\n val l34 = tuple31._1\n if (coll33.size == placeholder[Int](54)) { l34 } else {(\n val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n val i36 = coll35.size\n if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n )}\n }) }\n val l30 = func29(INPUTS)\n val l31 = func29(OUTPUTS)\n val coll32 = box23.R4[Coll[Long]].get\n val l33 = coll32(placeholder[Int](59))\n val l34 = l16 - l33 / placeholder[Int](60).toLong\n val l35 = l27 - l28\n val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n l35 * placeholder[Long](72) / placeholder[Long](73)\n }\n }\n }\n }\n val box37 = INPUTS(placeholder[Int](74))\n val l38 = coll32(placeholder[Int](75))\n val l39 = coll11(placeholder[Int](76))\n val tuple40 = coll24(placeholder[Int](77))\n val l41 = tuple40._2 - l35\n val bool42 = l41 == placeholder[Long](78)\n val coll43 = tuple40._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n placeholder[Long](84)\n } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n placeholder[Long](88)\n } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n 90\n )) {(\n val box44 = OUTPUTS(placeholder[Int](91))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](92))\n val tuple47 = coll45(placeholder[Int](93))\n val coll48 = box44.R4[Coll[Long]].get\n allOf(\n Coll[Boolean](\n box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n Long\n ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n )\n )\n )} else { placeholder[Boolean](97) }\n )\n )\n )\n )} else { sigmaProp(placeholder[Boolean](98)) }\n )}\n )}\n}",
"address": "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",
"assets": [
{
"tokenId": "05cde13424a7972fbcd0b43fccbb5e501b1f75302175178fc86d8f243f3f3125",
"index": 0,
"amount": 1,
"name": "ergopad Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1028de73d018f0c9a374b71555c5b8f1390994f2f41633e7b9d68f77735782ee",
"index": 1,
"amount": 999997212,
"name": "ergopad Stake Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1105dac2a4c3d101be0dc82bc8d6ad8d936480f0b252",
"sigmaType": "Coll[SLong]",
"renderedValue": "[28122058925,863,2788,1720551060900,86400000]"
}
}
},
{
"boxId": "05d604eaedcdef879e36495c3af19d9347170abe04b2be9040f40fe39aa8eeb6",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "0d7715aea75a0f86f1c9dd6ab0013dc057d103c36253769c84c5b1600824c13d",
"outputTransactionId": "3111706972caff0f8695987d18b58a20b17810918a7464b7bc4a724d7b7ccbe2",
"outputIndex": 46,
"outputGlobalIndex": 41336179,
"outputCreatedAt": 1304436,
"outputSettledAt": 1304438,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n3: 1\n4: 0\n5: 0\n6: 1\n7: 1\n8: 0\n9: 0\n10: 1\n11: 1\n12: 1\n13: 3\n14: 0\n15: 1\n16: 2\n17: Coll(5,-51,-31,52,36,-89,-105,47,-68,-48,-76,63,-52,-69,94,80,27,31,117,48,33,117,23,-113,-56,109,-113,36,63,63,49,37)\n18: 1\n19: 1\n20: false\n21: true\n22: false",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val coll2 = box1.tokens(placeholder[Int](1))._1\n if (coll2 == placeholder[Coll[Byte]](2)) {(\n val box3 = OUTPUTS(INPUTS.indexOf(SELF, placeholder[Int](3)))\n val coll4 = box3.R4[Coll[Long]].get\n val coll5 = SELF.R4[Coll[Long]].get\n val coll6 = box3.tokens\n val tuple7 = coll6(placeholder[Int](4))\n val coll8 = SELF.tokens\n val tuple9 = coll8(placeholder[Int](5))\n val tuple10 = coll6(placeholder[Int](6))\n val tuple11 = coll8(placeholder[Int](7))\n val l12 = tuple11._2\n val coll13 = box1.R4[Coll[Long]].get\n sigmaProp(\n allOf(\n Coll[Boolean](\n box3.value == SELF.value, box3.propositionBytes == SELF.propositionBytes, coll4(placeholder[Int](8)) == coll5(placeholder[Int](9)) + placeholder[\n Long\n ](10), box3.R5[Coll[Byte]].get == SELF.R5[Coll[Byte]].get, coll4(placeholder[Int](11)) == coll5(\n placeholder[Int](12)\n ), tuple7._1 == tuple9._1, tuple7._2 == tuple9._2, tuple10._1 == tuple11._1, tuple10._2 == l12 + coll13(placeholder[Int](13)) * l12 / coll13(\n placeholder[Int](14)\n )\n )\n )\n )\n )} else {(\n val box3 = INPUTS(placeholder[Int](15))\n if (box3.id == SELF.id) {(\n val box4 = OUTPUTS(placeholder[Int](16))\n sigmaProp((coll2 == placeholder[Coll[Byte]](17)) && if (box4.propositionBytes == SELF.propositionBytes) {(\n val opt5 = box4.R5[Coll[Byte]]\n if (opt5.isDefined) { (opt5.get == SELF.R5[Coll[Byte]].get) && (OUTPUTS(placeholder[Int](18)).tokens(placeholder[Int](19))._1 == box3.R5[Coll[Byte]].get) } else { placeholder[Boolean](20) }\n )} else { placeholder[Boolean](21) })\n )} else { sigmaProp(placeholder[Boolean](22)) }\n )}\n}",
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"assets": [
{
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"index": 0,
"amount": 1,
"name": "ergopad Stake Token",
"decimals": 0,
"type": "EIP-004"
},
{
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"name": "ergopad",
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"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "1102be0dc4b7f6c5ec63",
"sigmaType": "Coll[SLong]",
"renderedValue": "[863,1715375885794]"
},
"R5": {
"serializedValue": "0e208318a708fc04aa002c8c419faba2e98d2bd6bfde3a62c213b974d77a284eb78b",
"sigmaType": "Coll[SByte]",
"renderedValue": "8318a708fc04aa002c8c419faba2e98d2bd6bfde3a62c213b974d77a284eb78b"
}
}
},
{
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"index": 2,
"spendingProof": "4a010ab6ea952d2c961939f9708120c9d35b83f2603865430daa0187a2d291fd51bed559c0d87f8f4beac1bed340a42b5d3eb1ebf1b38e90",
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"outputTransactionId": "098ff8b376c18562ffb53934a3459a731d8821b72034d4b8cbc950fea84d16a8",
"outputIndex": 3,
"outputGlobalIndex": 41353618,
"outputCreatedAt": 1305137,
"outputSettledAt": 1305139,
"ergoTree": "0008cd02b05453d7ea3278c7566df16e47de16d06570ef820aa8d8819d117319fe34e5ae",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b05453,7332dd,...)))}",
"address": "9fricWPLcPkXrfaoYnnKN5V8CA5f1CJ7mZs47aKutY7aeJ9aX5a",
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{
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"type": "EIP-004"
},
{
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},
{
"tokenId": "ef802b475c06189fdbf844153cdc1d449a5ba87cce13d11bb47b5a539f27f12b",
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},
{
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"amount": 1,
"name": "Defenders of Buchi",
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},
{
"tokenId": "bee120e2890bada8b4ddbaf79025b8fde23d757a8b1d1ed991ef1647d7290e1b",
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},
{
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"type": "EIP-004"
},
{
"tokenId": "f32ceb525c47789a9d2dc552048f5413450e75af30c7782ffec55acff8fe5bde",
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"amount": 1,
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"type": "EIP-004"
},
{
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"index": 64,
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"name": "Mecha Margo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "4ffdbf1bcc96c97fa0eb139d37469fa884d38cfc0f34681dd0b2da2b9a4e5016",
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"amount": 11018,
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"type": "EIP-004"
},
{
"tokenId": "843b5a2a0658550339c38f29827861fe459ce5206edaf17163113cccafc77af1",
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"amount": 5208333000000,
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"type": "EIP-004"
},
{
"tokenId": "b9b2f6ccc1ac3e04296af69a11c0d798add8ef563ef6f7c1bec9f65722e3a713",
"index": 67,
"amount": 1,
"name": "ergopad Stake Key",
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"type": "EIP-004"
},
{
"tokenId": "f2ceffbc5e3543d129cccee08a899a4dc779ec41963f00be4f1df27ee51263e1",
"index": 68,
"amount": 1,
"name": "Paideia Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8ec0c63c5c6e1d8e9d524f4b19f491263ab0aa24bacdf77806cc2557f612362e",
"index": 69,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "612d708dc2b6a2e7250e6956648f648422da97f52acf9788394d12faa411d189",
"index": 70,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "58f1d0af4141853c39cd3c49a03daf967762fcca5ed70490abe916b93aacd964",
"index": 71,
"amount": 1,
"name": "Expanding Duckpools.io",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0f131e833c86c01476d2b810c1ebad714ea22e79a0101fcdb6456489a66bf2f2",
"index": 72,
"amount": 9223372036854776000,
"name": "SPF_Ergo_Spectrum Finance_LP_YF",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ef0c8af3cb6398754f83d03fa7393b41f6bc48cc5ab8eff76b6f6f3507d2b55d",
"index": 73,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8f33fad3814015f29c8d26ec7bf6e8d69156bdf08a1f75c077ac284089526b29",
"index": 74,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "8e0d540d6918118d4ebfb72f547feeb6146a1f7f0e50bd2bfd3967f7cf25ea23",
"index": 75,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2e9e557d835a90e4eaf854dc89f1d18659eb76c428508b55a1d1cc36e001b858",
"index": 76,
"amount": 6440000000,
"name": "Test quacks",
"decimals": 6,
"type": "EIP-004"
},
{
"tokenId": "f0d5bdf474fcbd4249608e6dc6e9cf34a327b218f66445ea545b4c711b4676e3",
"index": 77,
"amount": 2468642,
"name": "COS",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fc4a2cc63328c549d4d67c16cd2baf519e67cbde85cb35a17cba220dbe6b2a8",
"index": 78,
"amount": 2,
"name": "Margo",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a7520547be19a3c1fb91216965fd30939bf1c5a0fe440a8032fcd6867d120700",
"index": 79,
"amount": 1,
"name": "EGIO Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "7d51a2a5b343a12079a45b51b5f0711601628604497038c60c40109a0ef89fff",
"index": 80,
"amount": 1,
"name": "T-Rekt #0478",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1c03f89247ebe5e52809baa5e3237792b6aafb8bc0c6334d7896b29fbfbd2758",
"index": 81,
"amount": 1,
"name": "Crux Finance Phase 1 Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "02f31739e2e4937bb9afb552943753d1e3e9cdd1a5e5661949cb0cef93f907ea",
"index": 82,
"amount": 6674,
"name": "Terahertz",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "8318a708fc04aa002c8c419faba2e98d2bd6bfde3a62c213b974d77a284eb78b",
"index": 83,
"amount": 1,
"name": "ergopad Stake Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "fbbaac7337d051c10fc3da0ccb864f4d32d40027551e1c3ea3ce361f39b91e40",
"index": 84,
"amount": 1,
"name": "kushti",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2ed02f39e28e43fd98b018729f1a8d2d6747c5f4c939c9bff1852559422f6520",
"index": 85,
"amount": 1,
"name": "Sigmanaut's Space Stars #317",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "d71693c49a84fbbecd4908c94813b46514b18b67a99952dc1e6e4791556de413",
"index": 86,
"amount": 3999999,
"name": "ergopad",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "17977d49132a287d8faa43ae40399716be241936c49075e901126921d3367279",
"index": 87,
"amount": 1,
"name": "Mage Champions #816",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "7d90339f2c42b1330397c922233fbe37c391c7b3faded343ad3f873edb903c87",
"index": 88,
"amount": 1,
"name": "Crux Finance Phase 1 Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2927241103fad6d9aecf073a8c9941368b86af951355082c767d36ff41e61290",
"index": 89,
"amount": 1,
"name": "Crux Finance Phase 1 Vesting Key",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a500898895f20a86122fb86ef82f6eb2467fed1c0b7243373af32eac0ad8bdda",
"index": 90,
"amount": 1,
"name": "Donald Duck 100x ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ab5fb32b61572b55a487328861c8a1bcc4a3779c940631b1b4beb202e39ad6b0",
"index": 91,
"amount": 1,
"name": "Addy",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "ebb40ecab7bb7d2a935024100806db04f44c62c33ae9756cf6fc4cb6b9aa2d12",
"index": 92,
"amount": 42138840,
"name": "🚬",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "cfd6c990172fe675c2b88ea0fe3a44d4910b5c823f54d10081b82df54581994b",
"transactionId": "d7964cd0685f6da3a985cc240780b25da73868d804ebf9a4884c19ecc03590ec",
"blockId": "be7098f3244f22b73f862a10afcfc0dd107358ecf41b7a6c007d035df89fc167",
"value": 1000000,
"index": 0,
"globalIndex": 41353674,
"creationHeight": 1305140,
"settlementHeight": 1305142,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 0\n4: 1\n5: Coll(-41,22,-109,-60,-102,-124,-5,-66,-51,73,8,-55,72,19,-76,101,20,-79,-117,103,-87,-103,82,-36,30,110,71,-111,85,109,-28,19)\n6: 0\n7: 0\n8: 4\n9: 4\n10: 2\n11: 1\n12: 1\n13: 2\n14: 0\n15: 0\n16: 0\n17: 1\n18: 2\n19: 2\n20: 1\n21: 3\n22: 3\n23: 1\n24: Coll(37,-73,72,107,26,120,100,122,-41,-43,10,40,126,94,-107,-117,78,69,42,75,-56,105,56,-55,66,24,-41,6,-68,55,127,-16)\n25: 0\n26: 1\n27: 1800000\n28: 1\n29: 1000\n30: 1\n31: 1\n32: 1\n33: 0\n34: Coll(13,1,-14,-16,-77,37,75,74,23,49,-31,-74,26,-41,118,65,-2,84,-34,43,-42,-115,28,111,-63,-82,78,126,-99,-33,-78,18)\n35: 3\n36: 2\n37: 1\n38: 3\n39: 0\n40: Coll(5,73,-22,51,116,-93,107,122,34,-88,3,118,106,-9,50,-26,23,-104,70,60,51,50,-59,-10,-40,108,-118,-71,25,94,-19,89)\n41: 1\n42: 1\n43: 2\n44: 0\n45: 1\n46: 1\n47: 2\n48: 2\n49: 3\n50: 0\n51: 0\n52: 3\n53: 0\n54: 0\n55: 1\n56: 0\n57: 0\n58: -999999999999\n59: 1\n60: 604800000\n61: 8\n62: 0\n63: 6\n64: 5\n65: 100\n66: 4\n67: 125\n68: 1000\n69: 2\n70: 20\n71: 100\n72: 25\n73: 100\n74: 2\n75: 0\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 1\n82: 2\n83: 2\n84: 1\n85: 0\n86: 3\n87: 3\n88: 1\n89: 0\n90: 0\n91: 2\n92: 0\n93: 1\n94: 1000\n95: 0\n96: 1\n97: true\n98: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val coll2 = box1.tokens\n val tuple3 = coll2(placeholder[Int](1))\n val coll4 = tuple3._1\n val coll5 = SELF.tokens\n val tuple6 = coll5(placeholder[Int](2))\n val coll7 = tuple6._1\n val bool8 = coll4 == coll7\n val box9 = OUTPUTS(placeholder[Int](3))\n val coll10 = box9.R4[Coll[Long]].get\n val coll11 = SELF.R4[Coll[Long]].get\n val l12 = tuple6._2\n val coll13 = box9.tokens\n val tuple14 = coll13(placeholder[Int](4))\n val l15 = tuple14._2\n val l16 = CONTEXT.preHeader.timestamp\n val l17 = tuple3._2\n val coll18 = placeholder[Coll[Byte]](5)\n val tuple19 = coll13(placeholder[Int](6))\n val tuple20 = coll5(placeholder[Int](7))\n val l21 = coll11(placeholder[Int](8))\n val bool22 = allOf(\n Coll[Boolean](\n box9.propositionBytes == SELF.propositionBytes, box9.value == SELF.value, tuple19._1 == tuple20._1, tuple19._2 == tuple20._2, tuple14._1 == coll7, coll10(\n placeholder[Int](9)\n ) == l21, coll13.size == placeholder[Int](10)\n )\n )\n if (bool8) {(\n val tuple23 = coll2(placeholder[Int](11))\n val l24 = tuple23._2\n val l25 = coll11(placeholder[Int](12))\n val coll26 = box1.R4[Coll[Long]].get\n val coll27 = box1.R5[Coll[Byte]].get\n val box28 = OUTPUTS(placeholder[Int](13))\n val tuple29 = box28.tokens(placeholder[Int](14))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, coll10(placeholder[Int](15)) == coll11(placeholder[Int](16)) + l24, coll10(placeholder[Int](17)) == l25, coll10(\n placeholder[Int](18)\n ) == coll11(placeholder[Int](19)) + placeholder[Long](20), coll10(placeholder[Int](21)) == coll11(placeholder[Int](22)), l15 == l12 - placeholder[\n Long\n ](23), blake2b256(box1.propositionBytes) == placeholder[Coll[Byte]](24), coll26(placeholder[Int](25)) == l25, coll26(\n placeholder[Int](26)\n ) >= l16 - placeholder[Long](27), coll27 == SELF.id, bool8, l17 == placeholder[Long](28), tuple23._1 == coll18, l24 >= placeholder[Long](\n 29\n ), box28.propositionBytes == INPUTS(placeholder[Int](30)).propositionBytes, tuple29._1 == coll27, tuple29._2 == placeholder[Long](31)\n )\n )\n )\n )} else {(\n val box23 = INPUTS(placeholder[Int](32))\n val coll24 = box23.tokens\n val tuple25 = coll24(placeholder[Int](33))\n val coll26 = tuple25._1\n if ((coll26 == placeholder[Coll[Byte]](34)) && (INPUTS.size >= placeholder[Int](35))) {(\n val box27 = INPUTS(placeholder[Int](36))\n val coll28 = box27.R4[Coll[Long]].get\n val l29 = coll11(placeholder[Int](37))\n val l30 = coll10(placeholder[Int](38))\n sigmaProp(\n allOf(\n Coll[Boolean](\n bool22, box27.tokens(placeholder[Int](39))._1 == placeholder[Coll[Byte]](40), coll28(placeholder[Int](41)) == l29 - placeholder[Long](42), coll28(\n placeholder[Int](43)\n ) == placeholder[Long](44), coll10(placeholder[Int](45)) == l29 + placeholder[Long](46), coll10(placeholder[Int](47)) == coll11(\n placeholder[Int](48)\n ), l30 == coll11(placeholder[Int](49)) + l21, l30 < l16, l15 == l12\n )\n )\n )\n )} else {(\n val l27 = coll11(placeholder[Int](50))\n val l28 = coll10(placeholder[Int](51))\n if ((l27 > l28) && (INPUTS.size >= placeholder[Int](52))) {(\n val func29 = {(coll29: Coll[Box]) => coll29.fold(placeholder[Long](53), {(tuple31: (Long, Box)) =>\n val coll33 = tuple31._2.tokens\n val l34 = tuple31._1\n if (coll33.size == placeholder[Int](54)) { l34 } else {(\n val coll35 = coll33.filter({(tuple35: (Coll[Byte], Long)) => tuple35._1 == coll18 })\n val i36 = coll35.size\n if (i36 == placeholder[Int](55)) { l34 + coll35(placeholder[Int](56))._2 } else { if (i36 == placeholder[Int](57)) { l34 } else { placeholder[Long](58) } }\n )}\n }) }\n val l30 = func29(INPUTS)\n val l31 = func29(OUTPUTS)\n val coll32 = box23.R4[Coll[Long]].get\n val l33 = coll32(placeholder[Int](59))\n val l34 = l16 - l33 / placeholder[Int](60).toLong\n val l35 = l27 - l28\n val l36 = if (l34 >= placeholder[Long](61)) { placeholder[Long](62) } else {\n if (l34 >= placeholder[Long](63)) { l35 * placeholder[Long](64) / placeholder[Long](65) } else {\n if (l34 >= placeholder[Long](66)) { l35 * placeholder[Long](67) / placeholder[Long](68) } else {\n if (l34 >= placeholder[Long](69)) { l35 * placeholder[Long](70) / placeholder[Long](71) } else {\n l35 * placeholder[Long](72) / placeholder[Long](73)\n }\n }\n }\n }\n val box37 = INPUTS(placeholder[Int](74))\n val l38 = coll32(placeholder[Int](75))\n val l39 = coll11(placeholder[Int](76))\n val tuple40 = coll24(placeholder[Int](77))\n val l41 = tuple40._2 - l35\n val bool42 = l41 == placeholder[Long](78)\n val coll43 = tuple40._1\n sigmaProp(\n allOf(\n Coll[Boolean](\n l30 > placeholder[Long](79), l31 > placeholder[Long](80), l30 - l31 == l36, bool22, box37.tokens.exists(\n {(tuple44: (Coll[Byte], Long)) => tuple44._1 == box23.R5[Coll[Byte]].get }\n ), l38 == l39, l28 == l27 - l35, coll10(placeholder[Int](81)) == l39, coll10(placeholder[Int](82)) == coll11(placeholder[Int](83)) - if (bool42) {\n placeholder[Long](84)\n } else { placeholder[Long](85) }, coll10(placeholder[Int](86)) == coll11(placeholder[Int](87)), l15 == l12 + if (bool42) {\n placeholder[Long](88)\n } else { placeholder[Long](89) }, box1.propositionBytes == box37.propositionBytes, coll4 == coll43, l17 == l35 - l36, if (l41 > placeholder[Long](\n 90\n )) {(\n val box44 = OUTPUTS(placeholder[Int](91))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](92))\n val tuple47 = coll45(placeholder[Int](93))\n val coll48 = box44.R4[Coll[Long]].get\n allOf(\n Coll[Boolean](\n box44.value == box23.value, tuple46._1 == coll26, tuple46._2 == tuple25._2, tuple47._1 == coll43, tuple47._2 == l41, l41 >= placeholder[\n Long\n ](94), coll48(placeholder[Int](95)) == l38, coll48(placeholder[Int](96)) == l33\n )\n )\n )} else { placeholder[Boolean](97) }\n )\n )\n )\n )} else { sigmaProp(placeholder[Boolean](98)) }\n )}\n )}\n}",
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"assets": [
{
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"index": 0,
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"name": "ergopad Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 1,
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"name": "ergopad Stake Token",
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"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "110598a9b3c2d101be0dc62bc8d6ad8d936480f0b252",
"sigmaType": "Coll[SLong]",
"renderedValue": "[28121131596,863,2787,1720551060900,86400000]"
}
},
"spentTransactionId": "4282414790249befd9e65bd87acca3d82959817e1285ab6b16f1ff92ca72eed2",
"mainChain": true
},
{
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"transactionId": "d7964cd0685f6da3a985cc240780b25da73868d804ebf9a4884c19ecc03590ec",
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"value": 10000000,
"index": 1,
"globalIndex": 41353675,
"creationHeight": 1305140,
"settlementHeight": 1305142,
"ergoTree": "0008cd02b05453d7ea3278c7566df16e47de16d06570ef820aa8d8819d117319fe34e5ae",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b05453,7332dd,...)))}",
"address": "9fricWPLcPkXrfaoYnnKN5V8CA5f1CJ7mZs47aKutY7aeJ9aX5a",
"assets": [
{
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"index": 0,
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"name": "ergopad",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {},
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"mainChain": true
},
{
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"transactionId": "d7964cd0685f6da3a985cc240780b25da73868d804ebf9a4884c19ecc03590ec",
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"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
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"spentTransactionId": "dbba938a51dc8f08c07f34777998c2d50e569c5204049aa52e0b399463f61ccc",
"mainChain": true
},
{
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"creationHeight": 1305140,
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b05453,7332dd,...)))}",
"address": "9fricWPLcPkXrfaoYnnKN5V8CA5f1CJ7mZs47aKutY7aeJ9aX5a",
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{
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{
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{
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},
{
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