Transaction
ID: e21283b350...d169
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.004 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.05 ERG
Tokens:
100,000,000
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.004 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.049 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Transaction Details
Confirmations: 252,561
Total coins transferred: 0.054 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000402 ERG
Raw Transaction Data
{
"id": "e21283b3500024d9c78fbb85ff25defb336bea54530c5e4e930aaf83e724d169",
"blockId": "c724eb2e01d9967833be482ffca1fd9e4ff67e615959404015ef892d1c4b71b2",
"inclusionHeight": 1509285,
"timestamp": 1745350831003,
"index": 2,
"globalIndex": 8877798,
"numConfirmations": 252561,
"inputs": [
{
"boxId": "7bd13a421902c1202c2f78617e2065429cd2d2f65cce2749122fbe145312e30d",
"value": 4000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "b3bcbb29195ed7747f0fa37417175645769d95ede131ac5c7a25afe5a0a4dbfd",
"outputTransactionId": "6fd4942786987a674a093b1818a137713db4567b042efb4a502a041ca83ed223",
"outputIndex": 2,
"outputGlobalIndex": 47515428,
"outputCreatedAt": 1509228,
"outputSettledAt": 1509230,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-97,66,-89,69,125,72,-13,68,-107,-40,-64,-64,-86,123,90,-55,-101,71,-114,22,56,-28,121,70,7,127,5,71,110,35,-88,-123)\n2: 0\n3: 4000000\n4: 0\n5: 0\n6: Coll(82,-51,-84,78,-82,-22,-34,92,82,5,107,26,94,108,-53,93,92,4,-8,25,-120,-79,90,-6,39,-71,61,-45,-75,109,76,-7)\n7: 1\n8: 1\n9: 0\n10: 1\n11: 1\n12: 2\n13: 3\n14: 2\n15: 1\n16: 0\n17: Coll(48,46,-109,-24,-93,121,-5,123,-41,80,86,121,71,-48,-93,-106,-14,-79,56,-75,23,-127,-25,67,69,126,-30,6,-27,-72,-20,-64)\n18: 2\n19: 1\n20: 1\n21: false\n22: 1\n23: 0\n24: 0\n25: 2\n26: 0\n27: 0\n28: 2\n29: 1000\n30: 1\n31: 0\n32: 1000000\n33: 0\n34: 0\n35: 0\n36: 1\n37: 1\n38: 1\n39: 1\n40: 2\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 0\n48: 0\n49: 0\n50: 1\n51: 1\n52: 1\n53: 2\n54: 2\n55: 2\n56: 1\n57: 2\n58: 1\n59: 2\n60: 2\n61: 0\n62: 2\n63: 1\n64: 1\n65: 1\n66: 1\n67: 1\n68: 1\n69: 0\n70: 1\n71: 0\n72: 1\n73: 1\n74: 0\n75: 1\n76: 1\n77: 1\n78: 0\n79: 0\n80: 1\n81: 1\n82: 1\n83: 0",
"ergoTreeScript": "{\n val coll1 = CONTEXT.dataInputs\n val box2 = coll1(placeholder[Int](0))\n val coll3 = box2.tokens\n val coll4 = placeholder[Coll[Byte]](1)\n val coll5 = SELF.propositionBytes\n val box6 = OUTPUTS(placeholder[Int](2))\n val coll7 = box6.tokens\n val coll8 = SELF.tokens\n val bool9 = SELF.value >= placeholder[Long](3)\n val box10 = INPUTS(placeholder[Int](4))\n val tuple11 = coll3(placeholder[Int](5))\n val bool12 = allOf(Coll[Boolean](box2.propositionBytes == coll5, tuple11._1 == placeholder[Coll[Byte]](6), tuple11._2 == placeholder[Long](7)))\n val tuple13 = (Coll[Byte](placeholder[Byte](8)), placeholder[Long](9))\n val tuple14 = coll8.getOrElse(placeholder[Int](10), tuple13)\n val tuple15 = coll7.getOrElse(placeholder[Int](11), tuple13)\n val l16 = tuple15._2\n if (if ((coll3.size == placeholder[Int](12)) && (coll1.size == placeholder[Int](13))) {(\n val coll17 = coll1(placeholder[Int](14)).tokens\n allOf(\n Coll[Boolean](\n coll17(placeholder[Int](15))._1 == box2.R4[Coll[Byte]].get, coll17(placeholder[Int](16))._1 == placeholder[Coll[Byte]](17), box2.R6[\n Long\n ].get == placeholder[Long](18), coll3(placeholder[Int](19))._2 == placeholder[Long](20)\n )\n )\n )} else { placeholder[Boolean](21) }) {(\n val coll17 = INPUTS.filter({(box17: Box) => box17.propositionBytes != coll5 })\n val coll18 = box2.R5[Coll[Byte]].get\n val coll19 = OUTPUTS(placeholder[Int](22)).tokens\n val l20 = coll17.flatMap({(box20: Box) => box20.tokens.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }) }).fold(\n placeholder[Long](23), {(tuple20: (Long, (Coll[Byte], Long))) => tuple20._1 + tuple20._2._2 }\n ) - coll19.filter({(tuple20: (Coll[Byte], Long)) => tuple20._1 == coll18 }).fold(\n placeholder[Long](24), {(tuple20: (Long, (Coll[Byte], Long))) => tuple20._1 + tuple20._2._2 }\n )\n val box21 = coll1(placeholder[Int](25))\n val coll22 = box21.R7[Coll[Byte]].get\n val l23 = coll19.filter({(tuple23: (Coll[Byte], Long)) => tuple23._1 == coll22 }).fold(\n placeholder[Long](26), {(tuple23: (Long, (Coll[Byte], Long))) => tuple23._1 + tuple23._2._2 }\n ) - coll17.flatMap({(box23: Box) => box23.tokens.filter({(tuple25: (Coll[Byte], Long)) => tuple25._1 == coll22 }) }).fold(\n placeholder[Long](27), {(tuple23: (Long, (Coll[Byte], Long))) => tuple23._1 + tuple23._2._2 }\n )\n sigmaProp(\n allOf(\n Coll[Boolean](\n box2.R4[Coll[Byte]].get == coll4, allOf(\n Coll[Boolean](\n l20 + l20 * box21.R4[Coll[Long]].get(placeholder[Int](28)) * placeholder[Long](29) - coll1(placeholder[Int](30)).R8[Coll[Long]].get(\n placeholder[Int](31)\n ) / placeholder[Long](32) == l23, INPUTS.filter({(box24: Box) => box24.propositionBytes == coll5 }).flatMap(\n {(box24: Box) => box24.tokens.filter({(tuple26: (Coll[Byte], Long)) => tuple26._1 == coll22 }) }\n ).fold(placeholder[Long](33), {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 + tuple24._2._2 }) - coll7.filter(\n {(tuple24: (Coll[Byte], Long)) => tuple24._1 == coll22 }\n ).fold(placeholder[Long](34), {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 + tuple24._2._2 }) == l23\n )\n ), box6.propositionBytes == coll5\n )\n )\n )\n )} else {\n if (allOf(\n Coll[Boolean](\n (SELF.id == box10.id) && (coll5 == OUTPUTS(placeholder[Int](35)).propositionBytes), tuple14._2 < l16, l16 != placeholder[Long](\n 36\n ), tuple14._1 == tuple15._1\n )\n )) {(\n val coll17 = INPUTS.slice(placeholder[Int](37), INPUTS.size + placeholder[Int](38))\n val coll18 = box2.R5[Coll[Byte]].get\n val box19 = OUTPUTS(placeholder[Int](39))\n val coll20 = box19.tokens\n val coll21 = coll1(placeholder[Int](40)).R7[Coll[Byte]].get\n sigmaProp(\n allOf(\n Coll[Boolean](\n box2.R6[Long].get == placeholder[Long](41), allOf(\n Coll[Boolean](\n coll17.flatMap({(box22: Box) => box22.tokens.filter({(tuple24: (Coll[Byte], Long)) => tuple24._1 == coll18 }) }).fold(\n placeholder[Long](42), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll20.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }).fold(\n placeholder[Long](43), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) == coll20.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 }).fold(\n placeholder[Long](44), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll17.flatMap({(box22: Box) => box22.tokens.filter({(tuple24: (Coll[Byte], Long)) => tuple24._1 == coll21 }) }).fold(\n placeholder[Long](45), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ), coll7.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }).fold(\n placeholder[Long](46), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll8.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }).fold(\n placeholder[Long](47), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) == coll8.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 }).fold(\n placeholder[Long](48), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll7.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 }).fold(\n placeholder[Long](49), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n )\n )\n ), coll17.forall({(box22: Box) => box22.propositionBytes == box19.propositionBytes }), bool9\n )\n )\n )\n )} else {(\n val opt17 = box2.R4[Coll[Byte]]\n val opt18 = box2.R5[Coll[Byte]]\n if (box2.R6[Long].get == placeholder[Long](50)) {(\n val box19 = OUTPUTS(placeholder[Int](51))\n val coll20 = opt18.get\n val coll21 = box19.tokens\n val tuple22 = coll21(placeholder[Int](52))\n val tuple23 = coll7(placeholder[Int](53))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box19.propositionBytes == coll5, allOf(\n Coll[Boolean](opt17.get == box19.R4[Coll[Byte]].get, coll20 == box19.R5[Coll[Byte]].get, box19.R6[Long].get == placeholder[Long](54))\n ), allOf(\n Coll[Boolean](\n allOf(Coll[Boolean](coll21.size == placeholder[Int](55), tuple22._1 == coll20, tuple22._2 == placeholder[Long](56))), allOf(\n Coll[Boolean](tuple23._1 == box10.R7[Coll[Byte]].get, tuple23._2 == coll8(placeholder[Int](57))._2)\n )\n )\n ), box10.tokens(placeholder[Int](58))._1 == coll4, bool12, bool9\n )\n )\n )\n )} else {(\n val tuple19 = coll7(placeholder[Int](59))\n val l20 = tuple19._2\n val box21 = coll1(placeholder[Int](60))\n val l22 = box21.R4[Coll[Long]].get(placeholder[Int](61))\n val bool23 = l20 == l22\n val coll24 = box21.R7[Coll[Byte]].get\n val bool25 = tuple19._1 == coll24\n val l26 = l20 - coll8.getOrElse(placeholder[Int](62), tuple13)._2\n val coll27 = opt18.get\n val coll28 = opt17.get\n sigmaProp(allOf(Coll[Boolean](allOf(Coll[Boolean](if (bool23) {(\n val tuple29 = coll7(placeholder[Int](63))\n allOf(Coll[Boolean](tuple29._2 == placeholder[Long](64), tuple29._1 == coll8(placeholder[Int](65))._1, bool25))\n )} else {(\n val tuple29 = coll8(placeholder[Int](66))\n val tuple30 = coll7(placeholder[Int](67))\n allOf(Coll[Boolean](tuple29._2 - tuple30._2 == l26, tuple30._1 == tuple29._1, bool25))\n )}, OUTPUTS(placeholder[Int](68)).tokens.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll27 }).fold(placeholder[Long](69), {(tuple29: (Long, (Coll[Byte], Long))) => tuple29._1 + tuple29._2._2 }) - INPUTS(placeholder[Int](70)).tokens.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll27 }).fold(placeholder[Long](71), {(tuple29: (Long, (Coll[Byte], Long))) => tuple29._1 + tuple29._2._2 }) == l26)), allOf(Coll[Boolean](bool25, box21.tokens(placeholder[Int](72))._1 == coll28)), allOf(Coll[Boolean](coll28 == box6.R4[Coll[Byte]].get, coll27 == box6.R5[Coll[Byte]].get)), if (bool23) { allOf(Coll[Boolean](box6.R6[Long].get == placeholder[Long](73), coll7(placeholder[Int](74))._2 == placeholder[Long](75), coll7(placeholder[Int](76))._2 == placeholder[Long](77), bool23)) } else { allOf(Coll[Boolean](box6.R6[Long].get == placeholder[Long](78), coll7(placeholder[Int](79))._2 == placeholder[Long](80), coll7(placeholder[Int](81))._2 != placeholder[Long](82))) }, box6.propositionBytes == coll5, bool12, bool9, coll7.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll24 }).fold(placeholder[Long](83), {(tuple29: (Long, (Coll[Byte], Long))) => tuple29._1 + tuple29._2._2 }) <= l22)))\n )}\n )}\n }\n}",
"address": "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",
"assets": [
{
"tokenId": "52cdac4eaeeade5c52056b1a5e6ccb5d5c04f81988b15afa27b93dd3b56d4cf9",
"index": 0,
"amount": 1,
"name": "Exle: SLT CrowdFund Token V1.3",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"index": 1,
"amount": 9223372036854776000,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209f42a7457d48f34495d8c0c0aa7b5ac99b478e1638e47946077f05476e23a885",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f42a7457d48f34495d8c0c0aa7b5ac99b478e1638e47946077f05476e23a885"
},
"R5": {
"serializedValue": "0e209d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871"
},
"R6": {
"serializedValue": "0500",
"sigmaType": "SLong",
"renderedValue": "0"
}
}
},
{
"boxId": "b334f7c6c947d5220940e68969d0b2f25aeb13730da7cc45b12cdeeb84dffffc",
"value": 50000000,
"index": 1,
"spendingProof": "5831809ccd59d42731bda192cce3dadfb53d05152b5020fd38b3f011f5b1447f7eff93690bf147e782e8954b040ba26bdf5e01c640dfc2d8",
"outputBlockId": "f52a0d41052c34722bcbdd6dda202bed1a0e3b0579862910ae47fc7bf697fe3d",
"outputTransactionId": "63bfcbcb9fd24c7e5f174a0a6f5cb2b2d8ef16f762af60b649f01a90acea2f4f",
"outputIndex": 0,
"outputGlobalIndex": 47515210,
"outputCreatedAt": 1509225,
"outputSettledAt": 1509227,
"ergoTree": "0008cd02eb083423041003740c9e791b2fea5ecf6e273669630a25b7ecabf9145395e447",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(eb0834,848edd,...)))}",
"address": "9gJa6Mict6TVu9yipUX5aRUW87Yv8J62bbPEtkTje28sh5i3Lz8",
"assets": [
{
"tokenId": "f60bff91f7ae3f3a5f0c2d35b46ef8991f213a61d7f7e453d344fa52a42d9f9a",
"index": 0,
"amount": 10000000000,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "7bd13a421902c1202c2f78617e2065429cd2d2f65cce2749122fbe145312e30d",
"value": 4000000,
"index": 0,
"outputBlockId": "b3bcbb29195ed7747f0fa37417175645769d95ede131ac5c7a25afe5a0a4dbfd",
"outputTransactionId": "6fd4942786987a674a093b1818a137713db4567b042efb4a502a041ca83ed223",
"outputIndex": 2,
"ergoTree": "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",
"address": "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",
"assets": [
{
"tokenId": "52cdac4eaeeade5c52056b1a5e6ccb5d5c04f81988b15afa27b93dd3b56d4cf9",
"index": 0,
"amount": 1,
"name": "Exle: SLT CrowdFund Token V1.3",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"index": 1,
"amount": 9223372036854776000,
"name": null,
"decimals": null,
"type": null
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209f42a7457d48f34495d8c0c0aa7b5ac99b478e1638e47946077f05476e23a885",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f42a7457d48f34495d8c0c0aa7b5ac99b478e1638e47946077f05476e23a885"
},
"R5": {
"serializedValue": "0e209d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871"
},
"R6": {
"serializedValue": "0500",
"sigmaType": "SLong",
"renderedValue": "0"
}
}
},
{
"boxId": "a981ee0062d20e75c1ce844db0eeadf094bb34f877eec85b8539a893c7b321e3",
"value": 1000000,
"index": 1,
"outputBlockId": "b3bcbb29195ed7747f0fa37417175645769d95ede131ac5c7a25afe5a0a4dbfd",
"outputTransactionId": "6fd4942786987a674a093b1818a137713db4567b042efb4a502a041ca83ed223",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R5": {
"serializedValue": "1a022015133f2f355f4b8564dc88536968363e23377ac95d883f86a522d395f1d9ff37202f918f613dfd33193cbf8cd59f8174ea7cb993fd6b29f02b71f3e58d1f700efd",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[15133f2f355f4b8564dc88536968363e23377ac95d883f86a522d395f1d9ff37,2f918f613dfd33193cbf8cd59f8174ea7cb993fd6b29f02b71f3e58d1f700efd]"
},
"R6": {
"serializedValue": "0e6645786c6520534c54205365727669636520426f783a2041206c656e64696e672070726f746f636f6c20746861742070726f7669646520686973746f726963616c2077726974696e6773206f66204c6f616e7320696e207465726d73206f6620546f6b656e732e",
"sigmaType": "Coll[SByte]",
"renderedValue": "45786c6520534c54205365727669636520426f783a2041206c656e64696e672070726f746f636f6c20746861742070726f7669646520686973746f726963616c2077726974696e6773206f66204c6f616e7320696e207465726d73206f6620546f6b656e732e"
},
"R8": {
"serializedValue": "110290038084af5f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[200,100000000]"
},
"R7": {
"serializedValue": "0e240008cd024f716db88462f0c69b98d20cc281c0e51d6d1aa9ab79aa266e68b2eada18a18c",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd024f716db88462f0c69b98d20cc281c0e51d6d1aa9ab79aa266e68b2eada18a18c"
},
"R4": {
"serializedValue": "110290887802",
"sigmaType": "Coll[SLong]",
"renderedValue": "[983560,1]"
}
}
},
{
"boxId": "b6a67313971cddbc2367b5e2104282fa76f603975a5eff18ba6bc3e9c9829401",
"value": 1474560,
"index": 2,
"outputBlockId": "b3bcbb29195ed7747f0fa37417175645769d95ede131ac5c7a25afe5a0a4dbfd",
"outputTransactionId": "6fd4942786987a674a093b1818a137713db4567b042efb4a502a041ca83ed223",
"outputIndex": 1,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "1105a09c01baf3c30128c0d1028084af5f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000,1604829,20,21600,100000000]"
},
"R5": {
"serializedValue": "1a0203466f6f03426172",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[466f6f,426172]"
},
"R6": {
"serializedValue": "0e240008cd0233e9a9935c8bbb8ae09b2c944c1d060492a8832252665e043b0732bdf593bf2c",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd0233e9a9935c8bbb8ae09b2c944c1d060492a8832252665e043b0732bdf593bf2c"
},
"R7": {
"serializedValue": "0e20f60bff91f7ae3f3a5f0c2d35b46ef8991f213a61d7f7e453d344fa52a42d9f9a",
"sigmaType": "Coll[SByte]",
"renderedValue": "f60bff91f7ae3f3a5f0c2d35b46ef8991f213a61d7f7e453d344fa52a42d9f9a"
}
}
}
],
"outputs": [
{
"boxId": "d17c4d5427e1d5853afe8b4700b397f35a4da2bb86f61a6ab7785c37770f6c3f",
"transactionId": "e21283b3500024d9c78fbb85ff25defb336bea54530c5e4e930aaf83e724d169",
"blockId": "c724eb2e01d9967833be482ffca1fd9e4ff67e615959404015ef892d1c4b71b2",
"value": 4000000,
"index": 0,
"globalIndex": 47516463,
"creationHeight": 1509282,
"settlementHeight": 1509285,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-97,66,-89,69,125,72,-13,68,-107,-40,-64,-64,-86,123,90,-55,-101,71,-114,22,56,-28,121,70,7,127,5,71,110,35,-88,-123)\n2: 0\n3: 4000000\n4: 0\n5: 0\n6: Coll(82,-51,-84,78,-82,-22,-34,92,82,5,107,26,94,108,-53,93,92,4,-8,25,-120,-79,90,-6,39,-71,61,-45,-75,109,76,-7)\n7: 1\n8: 1\n9: 0\n10: 1\n11: 1\n12: 2\n13: 3\n14: 2\n15: 1\n16: 0\n17: Coll(48,46,-109,-24,-93,121,-5,123,-41,80,86,121,71,-48,-93,-106,-14,-79,56,-75,23,-127,-25,67,69,126,-30,6,-27,-72,-20,-64)\n18: 2\n19: 1\n20: 1\n21: false\n22: 1\n23: 0\n24: 0\n25: 2\n26: 0\n27: 0\n28: 2\n29: 1000\n30: 1\n31: 0\n32: 1000000\n33: 0\n34: 0\n35: 0\n36: 1\n37: 1\n38: 1\n39: 1\n40: 2\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 0\n48: 0\n49: 0\n50: 1\n51: 1\n52: 1\n53: 2\n54: 2\n55: 2\n56: 1\n57: 2\n58: 1\n59: 2\n60: 2\n61: 0\n62: 2\n63: 1\n64: 1\n65: 1\n66: 1\n67: 1\n68: 1\n69: 0\n70: 1\n71: 0\n72: 1\n73: 1\n74: 0\n75: 1\n76: 1\n77: 1\n78: 0\n79: 0\n80: 1\n81: 1\n82: 1\n83: 0",
"ergoTreeScript": "{\n val coll1 = CONTEXT.dataInputs\n val box2 = coll1(placeholder[Int](0))\n val coll3 = box2.tokens\n val coll4 = placeholder[Coll[Byte]](1)\n val coll5 = SELF.propositionBytes\n val box6 = OUTPUTS(placeholder[Int](2))\n val coll7 = box6.tokens\n val coll8 = SELF.tokens\n val bool9 = SELF.value >= placeholder[Long](3)\n val box10 = INPUTS(placeholder[Int](4))\n val tuple11 = coll3(placeholder[Int](5))\n val bool12 = allOf(Coll[Boolean](box2.propositionBytes == coll5, tuple11._1 == placeholder[Coll[Byte]](6), tuple11._2 == placeholder[Long](7)))\n val tuple13 = (Coll[Byte](placeholder[Byte](8)), placeholder[Long](9))\n val tuple14 = coll8.getOrElse(placeholder[Int](10), tuple13)\n val tuple15 = coll7.getOrElse(placeholder[Int](11), tuple13)\n val l16 = tuple15._2\n if (if ((coll3.size == placeholder[Int](12)) && (coll1.size == placeholder[Int](13))) {(\n val coll17 = coll1(placeholder[Int](14)).tokens\n allOf(\n Coll[Boolean](\n coll17(placeholder[Int](15))._1 == box2.R4[Coll[Byte]].get, coll17(placeholder[Int](16))._1 == placeholder[Coll[Byte]](17), box2.R6[\n Long\n ].get == placeholder[Long](18), coll3(placeholder[Int](19))._2 == placeholder[Long](20)\n )\n )\n )} else { placeholder[Boolean](21) }) {(\n val coll17 = INPUTS.filter({(box17: Box) => box17.propositionBytes != coll5 })\n val coll18 = box2.R5[Coll[Byte]].get\n val coll19 = OUTPUTS(placeholder[Int](22)).tokens\n val l20 = coll17.flatMap({(box20: Box) => box20.tokens.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }) }).fold(\n placeholder[Long](23), {(tuple20: (Long, (Coll[Byte], Long))) => tuple20._1 + tuple20._2._2 }\n ) - coll19.filter({(tuple20: (Coll[Byte], Long)) => tuple20._1 == coll18 }).fold(\n placeholder[Long](24), {(tuple20: (Long, (Coll[Byte], Long))) => tuple20._1 + tuple20._2._2 }\n )\n val box21 = coll1(placeholder[Int](25))\n val coll22 = box21.R7[Coll[Byte]].get\n val l23 = coll19.filter({(tuple23: (Coll[Byte], Long)) => tuple23._1 == coll22 }).fold(\n placeholder[Long](26), {(tuple23: (Long, (Coll[Byte], Long))) => tuple23._1 + tuple23._2._2 }\n ) - coll17.flatMap({(box23: Box) => box23.tokens.filter({(tuple25: (Coll[Byte], Long)) => tuple25._1 == coll22 }) }).fold(\n placeholder[Long](27), {(tuple23: (Long, (Coll[Byte], Long))) => tuple23._1 + tuple23._2._2 }\n )\n sigmaProp(\n allOf(\n Coll[Boolean](\n box2.R4[Coll[Byte]].get == coll4, allOf(\n Coll[Boolean](\n l20 + l20 * box21.R4[Coll[Long]].get(placeholder[Int](28)) * placeholder[Long](29) - coll1(placeholder[Int](30)).R8[Coll[Long]].get(\n placeholder[Int](31)\n ) / placeholder[Long](32) == l23, INPUTS.filter({(box24: Box) => box24.propositionBytes == coll5 }).flatMap(\n {(box24: Box) => box24.tokens.filter({(tuple26: (Coll[Byte], Long)) => tuple26._1 == coll22 }) }\n ).fold(placeholder[Long](33), {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 + tuple24._2._2 }) - coll7.filter(\n {(tuple24: (Coll[Byte], Long)) => tuple24._1 == coll22 }\n ).fold(placeholder[Long](34), {(tuple24: (Long, (Coll[Byte], Long))) => tuple24._1 + tuple24._2._2 }) == l23\n )\n ), box6.propositionBytes == coll5\n )\n )\n )\n )} else {\n if (allOf(\n Coll[Boolean](\n (SELF.id == box10.id) && (coll5 == OUTPUTS(placeholder[Int](35)).propositionBytes), tuple14._2 < l16, l16 != placeholder[Long](\n 36\n ), tuple14._1 == tuple15._1\n )\n )) {(\n val coll17 = INPUTS.slice(placeholder[Int](37), INPUTS.size + placeholder[Int](38))\n val coll18 = box2.R5[Coll[Byte]].get\n val box19 = OUTPUTS(placeholder[Int](39))\n val coll20 = box19.tokens\n val coll21 = coll1(placeholder[Int](40)).R7[Coll[Byte]].get\n sigmaProp(\n allOf(\n Coll[Boolean](\n box2.R6[Long].get == placeholder[Long](41), allOf(\n Coll[Boolean](\n coll17.flatMap({(box22: Box) => box22.tokens.filter({(tuple24: (Coll[Byte], Long)) => tuple24._1 == coll18 }) }).fold(\n placeholder[Long](42), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll20.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }).fold(\n placeholder[Long](43), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) == coll20.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 }).fold(\n placeholder[Long](44), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll17.flatMap({(box22: Box) => box22.tokens.filter({(tuple24: (Coll[Byte], Long)) => tuple24._1 == coll21 }) }).fold(\n placeholder[Long](45), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ), coll7.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }).fold(\n placeholder[Long](46), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll8.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll18 }).fold(\n placeholder[Long](47), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) == coll8.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 }).fold(\n placeholder[Long](48), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n ) - coll7.filter({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 }).fold(\n placeholder[Long](49), {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 + tuple22._2._2 }\n )\n )\n ), coll17.forall({(box22: Box) => box22.propositionBytes == box19.propositionBytes }), bool9\n )\n )\n )\n )} else {(\n val opt17 = box2.R4[Coll[Byte]]\n val opt18 = box2.R5[Coll[Byte]]\n if (box2.R6[Long].get == placeholder[Long](50)) {(\n val box19 = OUTPUTS(placeholder[Int](51))\n val coll20 = opt18.get\n val coll21 = box19.tokens\n val tuple22 = coll21(placeholder[Int](52))\n val tuple23 = coll7(placeholder[Int](53))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box19.propositionBytes == coll5, allOf(\n Coll[Boolean](opt17.get == box19.R4[Coll[Byte]].get, coll20 == box19.R5[Coll[Byte]].get, box19.R6[Long].get == placeholder[Long](54))\n ), allOf(\n Coll[Boolean](\n allOf(Coll[Boolean](coll21.size == placeholder[Int](55), tuple22._1 == coll20, tuple22._2 == placeholder[Long](56))), allOf(\n Coll[Boolean](tuple23._1 == box10.R7[Coll[Byte]].get, tuple23._2 == coll8(placeholder[Int](57))._2)\n )\n )\n ), box10.tokens(placeholder[Int](58))._1 == coll4, bool12, bool9\n )\n )\n )\n )} else {(\n val tuple19 = coll7(placeholder[Int](59))\n val l20 = tuple19._2\n val box21 = coll1(placeholder[Int](60))\n val l22 = box21.R4[Coll[Long]].get(placeholder[Int](61))\n val bool23 = l20 == l22\n val coll24 = box21.R7[Coll[Byte]].get\n val bool25 = tuple19._1 == coll24\n val l26 = l20 - coll8.getOrElse(placeholder[Int](62), tuple13)._2\n val coll27 = opt18.get\n val coll28 = opt17.get\n sigmaProp(allOf(Coll[Boolean](allOf(Coll[Boolean](if (bool23) {(\n val tuple29 = coll7(placeholder[Int](63))\n allOf(Coll[Boolean](tuple29._2 == placeholder[Long](64), tuple29._1 == coll8(placeholder[Int](65))._1, bool25))\n )} else {(\n val tuple29 = coll8(placeholder[Int](66))\n val tuple30 = coll7(placeholder[Int](67))\n allOf(Coll[Boolean](tuple29._2 - tuple30._2 == l26, tuple30._1 == tuple29._1, bool25))\n )}, OUTPUTS(placeholder[Int](68)).tokens.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll27 }).fold(placeholder[Long](69), {(tuple29: (Long, (Coll[Byte], Long))) => tuple29._1 + tuple29._2._2 }) - INPUTS(placeholder[Int](70)).tokens.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll27 }).fold(placeholder[Long](71), {(tuple29: (Long, (Coll[Byte], Long))) => tuple29._1 + tuple29._2._2 }) == l26)), allOf(Coll[Boolean](bool25, box21.tokens(placeholder[Int](72))._1 == coll28)), allOf(Coll[Boolean](coll28 == box6.R4[Coll[Byte]].get, coll27 == box6.R5[Coll[Byte]].get)), if (bool23) { allOf(Coll[Boolean](box6.R6[Long].get == placeholder[Long](73), coll7(placeholder[Int](74))._2 == placeholder[Long](75), coll7(placeholder[Int](76))._2 == placeholder[Long](77), bool23)) } else { allOf(Coll[Boolean](box6.R6[Long].get == placeholder[Long](78), coll7(placeholder[Int](79))._2 == placeholder[Long](80), coll7(placeholder[Int](81))._2 != placeholder[Long](82))) }, box6.propositionBytes == coll5, bool12, bool9, coll7.filter({(tuple29: (Coll[Byte], Long)) => tuple29._1 == coll24 }).fold(placeholder[Long](83), {(tuple29: (Long, (Coll[Byte], Long))) => tuple29._1 + tuple29._2._2 }) <= l22)))\n )}\n )}\n }\n}",
"address": "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",
"assets": [
{
"tokenId": "52cdac4eaeeade5c52056b1a5e6ccb5d5c04f81988b15afa27b93dd3b56d4cf9",
"index": 0,
"amount": 1,
"name": "Exle: SLT CrowdFund Token V1.3",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"index": 1,
"amount": 1,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "f60bff91f7ae3f3a5f0c2d35b46ef8991f213a61d7f7e453d344fa52a42d9f9a",
"index": 2,
"amount": 10000,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209f42a7457d48f34495d8c0c0aa7b5ac99b478e1638e47946077f05476e23a885",
"sigmaType": "Coll[SByte]",
"renderedValue": "9f42a7457d48f34495d8c0c0aa7b5ac99b478e1638e47946077f05476e23a885"
},
"R5": {
"serializedValue": "0e209d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"sigmaType": "Coll[SByte]",
"renderedValue": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871"
},
"R6": {
"serializedValue": "0502",
"sigmaType": "SLong",
"renderedValue": "1"
}
},
"spentTransactionId": "ff29807c019eb6ff8c142edd970493bec1e236a886a0ea198377fa6e75f37e92",
"mainChain": true
},
{
"boxId": "63bf3af8795c1c59d69883709d0bbe9c477d68f99c28e006f658135ba5cadf69",
"transactionId": "e21283b3500024d9c78fbb85ff25defb336bea54530c5e4e930aaf83e724d169",
"blockId": "c724eb2e01d9967833be482ffca1fd9e4ff67e615959404015ef892d1c4b71b2",
"value": 49000000,
"index": 1,
"globalIndex": 47516464,
"creationHeight": 1509282,
"settlementHeight": 1509285,
"ergoTree": "0008cd02eb083423041003740c9e791b2fea5ecf6e273669630a25b7ecabf9145395e447",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(eb0834,848edd,...)))}",
"address": "9gJa6Mict6TVu9yipUX5aRUW87Yv8J62bbPEtkTje28sh5i3Lz8",
"assets": [
{
"tokenId": "9d5a69629b999312d1971ba10d185c914eea72505a0206f16ea52aa3a9f8f871",
"index": 0,
"amount": 10000,
"name": null,
"decimals": null,
"type": null
},
{
"tokenId": "f60bff91f7ae3f3a5f0c2d35b46ef8991f213a61d7f7e453d344fa52a42d9f9a",
"index": 1,
"amount": 9999990000,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "02b81fd796de744bed93570d71b811ee2c86c2f6856bc92e3da454cbf4c01b41",
"mainChain": true
},
{
"boxId": "73d8558923f5c546132b8da4c1d7d2d6402736cf2a1afe4618114d4f39224cfb",
"transactionId": "e21283b3500024d9c78fbb85ff25defb336bea54530c5e4e930aaf83e724d169",
"blockId": "c724eb2e01d9967833be482ffca1fd9e4ff67e615959404015ef892d1c4b71b2",
"value": 1000000,
"index": 2,
"globalIndex": 47516465,
"creationHeight": 1509282,
"settlementHeight": 1509285,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"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)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "7f46b67c3e02c0d1dc14a8295db8817af3b4a01fadaab9855cbdca4b466207e4",
"mainChain": true
}
],
"size": 2488,
"isUnconfirmed": false
}