Transaction
ID: 3fd742d818...15fe
Inputs (4)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Spent
Address:
Output transaction:
Settlement height:
Value:
3.72 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
4.27 ERG
Outputs (14)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.473 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.42 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
4.83 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.235 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.136 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.574 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.011 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.332 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.937 ERG
Tokens:
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.019 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.007 ERG
Transaction Details
Confirmations: 1,079,617
Total coins transferred: 8 ERG
Fees: 0.019 ERG
Fees per byte: 0.000003961 ERG
Raw Transaction Data
{
"id": "3fd742d8185d6abb6f3cf902dab3a858951387f1d05be2a1a2cd789678d515fe",
"blockId": "f20d8e5f95bee9d53cb51ddc10f5b245f5947f47702e93d600a731ee57d13ae8",
"inclusionHeight": 688963,
"timestamp": 1645229281680,
"index": 10,
"globalIndex": 2671166,
"numConfirmations": 1079617,
"inputs": [
{
"boxId": "83382aeebcbc85c7be486d63e484a3fdb78d84878d7261e317c728ec98ab99ec",
"value": 10000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "63b4208c0ee2545867034bc978e1d760e17cd9f5f47db3d20f5363c837cd5f29",
"outputTransactionId": "09fdd8652d29ceb37a8a7b48cb2c540187cf386208217683307a278d8487cd60",
"outputIndex": 0,
"outputGlobalIndex": 13371790,
"outputCreatedAt": 688754,
"outputSettledAt": 688757,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 1\n4: false\n5: false\n6: 0\n7: -1\n8: false\n9: 1\n10: false\n11: 0\n12: 1\n13: 0\n14: 1\n15: 1\n16: 2\n17: 2\n18: 0\n19: 0\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: false\n26: false\n27: true",
"ergoTreeScript": "{\n val opt1 = SELF.R7[Coll[Long]]\n val opt2 = SELF.R8[Coll[(Coll[Byte], Coll[Byte])]]\n val bool3 = allOf(\n Coll[Boolean](\n SELF.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, SELF.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, SELF.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, opt1.isDefined, opt2.isDefined, INPUTS(placeholder[Int](0)) == SELF\n )\n )\n val box4 = INPUTS(placeholder[Int](1))\n val opt5 = box4.R5[Coll[(Coll[Byte], Coll[Byte])]]\n val opt6 = box4.R4[Coll[(Coll[Byte], Coll[Long])]]\n val box7 = OUTPUTS(placeholder[Int](2))\n val opt8 = box7.R7[Coll[Long]]\n val coll9 = box7.tokens\n if (bool3) {\n sigmaProp(\n if (if (if (if (bool3) { opt2.get.exists({(tuple10: (Coll[Byte], Coll[Byte])) => tuple10._1 == INPUTS(placeholder[Int](3)).propositionBytes }) } else {\n placeholder[Boolean](4)\n }) {\n allOf(\n Coll[Boolean](\n box4.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box4.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box4.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box4.R7[Coll[Long]].isDefined, box4.R8[Coll[(Coll[Byte], Coll[Byte])]].isDefined\n )\n )\n } else { placeholder[Boolean](5) }) {\n opt5.get.forall(\n {(tuple10: (Coll[Byte], Coll[Byte])) =>\n opt6.get.map({(tuple12: (Coll[Byte], Coll[Long])) => tuple12._1 }).indexOf(tuple10._1, placeholder[Int](6)) != placeholder[Int](7)\n }\n )\n } else { placeholder[Boolean](8) } && if (if (box7.propositionBytes == SELF.propositionBytes) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box7.R7[Coll[Long]].isDefined, box7.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].isDefined, box7.value == SELF.value, box7.tokens.size == placeholder[Int](9)\n )\n )\n } else { placeholder[Boolean](10) }) {(\n val coll10 = opt8.get\n val coll11 = opt1.get\n val l12 = coll11(placeholder[Int](11))\n val l13 = coll10(placeholder[Int](12))\n (\n ((coll10(placeholder[Int](13)) == l12 + placeholder[Long](14)) && ((l13 <= HEIGHT.toLong) && (l13 > coll11(placeholder[Int](15))))) && (\n coll10(placeholder[Int](16)) == coll11(placeholder[Int](17))\n )\n ) && if (l12 != placeholder[Long](18)) { SELF.tokens(placeholder[Int](19))._1 == coll9(placeholder[Int](20))._1 } else {(\n val coll14 = SELF.tokens\n if (coll14.size > placeholder[Int](21)) { coll14(placeholder[Int](22))._1 == coll9(placeholder[Int](23))._1 } else {\n coll9(placeholder[Int](24))._1 == SELF.id\n }\n )}\n )} else { placeholder[Boolean](25) }) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].get == opt6.get, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].get == opt5.get, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].get == box4.R6[Coll[(Coll[Byte], Int)]].get, opt8.get == box4.R7[Coll[Long]].get, box7.R8[Coll[(Coll[Byte], Coll[Byte])]].get == box4.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].get\n )\n )\n } else { placeholder[Boolean](26) }\n )\n } else { sigmaProp(placeholder[Boolean](27)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c0",
"index": 0,
"amount": 1,
"name": "GetBlok.io SmartPool Display Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
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"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[0008cd021539c4f42656ddd159ed027af4fcf552407e87dd3422a8b4651e34eca6a3b2a3,39656751684b6f567270484b5969796f313442575a383344443636775a69614b47766e506852664b48695a3257594842416937],[0008cd039c90146571b5c3154126aabcc0a985119c1bfeaadde1165a68bf7ac448bdc771,3968656b737476524452516159535a754a64566f437a4a6876563862576d4d64325641574c784c424631586542366571624a62],[0008cd03aae36e07b8efe060278ba32ae04fc20807b38c9aa2f94eecb4ee2b539e9522f3,39686d346f694a6b50686347504e6465783444776d447670483536577867325a3153474d3878446d343270314c326765475334],[0008cd036eb9145a5e84519b9e0b1d2415f5ea7416d7d88709ecaf1af9b0f7c13d7fab55,39684a5a7868377042485a5968525a4e474b396b615531377343555331376d416f717763664b445472786e384454696a655250],[0008cd02b6f3816cfb73df221653dfc5bb3005db63496ced1d64c278e63ca9858730d204,396675646b7544755a546b676a5a567348553859314e713155745048476a44327344367a46417279356f33476f4a63345a3145],[0008cd02453463956472c0abc816127e218e994a6bd4774f8b37b4b8d476678a93ce3c8f,39663359466a4d666953716e3375624e345775593172676343546f4a653536524c775a4831424e314d727447687864386a7a54],[0008cd0286a41210a7d78845a1a5efe7ff4e32578c62f8da339db6290f2afdd971cb94a4,3966594d6a6561564a67694d684c47435850704145775a6b4a6a4543456b6f5844346562437355625554425156475231636243],[0008cd029067df40ef162b5b0f0b3a4989cbd4c850eb87c8e84129bd941fa6fe1aa0fe7c,39666366416232626948745336755152464567383370595354554e6a706b7a657a364b377636736132516466436e3743357552],[0008cd0286d6c2ebaaf6bad31394335ae851f43b0ea79a5d0494bedc076f6edd41c6852f,396659536f3153754437705455774e417376595245627a5173665477384654446a53754b663151327a39625a447453765a7664],[0008cd032d034db8f09f2f53e1286ba872f64aa75ff20244b277874aae03abd14b7da3fb,39676f6456383451754263526f3139697739594e57344839646d6b41687665584669537048356847544b636e56373635343433]]"
},
"R6": {
"serializedValue": "0c4c0e03240008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed37202706240008cd0287352ce40ff53154c5b3751a661908d3ca99edbb198e7ebb63d1d00e580f2efd06240008cd026dd353119c75189796b3fb01c60289399f5fa2e7e115f4d8e3ffcc0a4ba5326906",
"sigmaType": "Coll[(Coll[SByte], SInt)]",
"renderedValue": "[[0008cd026d9d81d27185efa93c148f700839183a882aae3a4de1f984faff69eeed372027,3],[0008cd0287352ce40ff53154c5b3751a661908d3ca99edbb198e7ebb63d1d00e580f2efd,3],[0008cd026dd353119c75189796b3fb01c60289399f5fa2e7e115f4d8e3ffcc0a4ba53269,3]]"
},
"R8": {
"serializedValue": "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",
"sigmaType": "Coll[(Coll[SByte], Coll[SByte])]",
"renderedValue": "[[100804000401040004000e204f5c05967a2a68d5fe0cdd7a688289f5b1a8aef7d24cab71c20ab8896068e0a80100010108cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7ea02d1afe4c6a7040c3c0e11d901013c0e11d801d603dc0c1aada5d9010363c27203028c7201017300959472037301d802d604b2a5720300d605db630872049591b172057302d801d606b27205730300ed938c7206017304938c720602c17204730573067307,566f746520546f6b656e204469737472696275746f72],[0008cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7,3967556962486f616569774b5a53707967685a4536594d455a564a753977734b7a465332335778525671366e7a547663476f55]]"
},
"R7": {
"serializedValue": "1104a603e48954aaf9500a",
"sigmaType": "Coll[SLong]",
"renderedValue": "[211,688754,663125,5]"
},
"R4": {
"serializedValue": "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",
"sigmaType": "Coll[(Coll[SByte], Coll[SLong])]",
"renderedValue": "[[0008cd021539c4f42656ddd159ed027af4fcf552407e87dd3422a8b4651e34eca6a3b2a3,[8414,100000000,0,0]],[0008cd039c90146571b5c3154126aabcc0a985119c1bfeaadde1165a68bf7ac448bdc771,[35350,10000000000,4099000000,0]],[0008cd03aae36e07b8efe060278ba32ae04fc20807b38c9aa2f94eecb4ee2b539e9522f3,[46269,100000000,0,0]],[0008cd036eb9145a5e84519b9e0b1d2415f5ea7416d7d88709ecaf1af9b0f7c13d7fab55,[32198,100000000,0,0]],[0008cd02b6f3816cfb73df221653dfc5bb3005db63496ced1d64c278e63ca9858730d204,[16898,100000000,0,0]],[0008cd02453463956472c0abc816127e218e994a6bd4774f8b37b4b8d476678a93ce3c8f,[9596,1000000000,125000000,0]],[0008cd0286a41210a7d78845a1a5efe7ff4e32578c62f8da339db6290f2afdd971cb94a4,[0,100000000,42000000,4]],[0008cd029067df40ef162b5b0f0b3a4989cbd4c850eb87c8e84129bd941fa6fe1aa0fe7c,[30992,100000000,0,0]],[0008cd0286d6c2ebaaf6bad31394335ae851f43b0ea79a5d0494bedc076f6edd41c6852f,[70330,100000000,0,0]],[0008cd032d034db8f09f2f53e1286ba872f64aa75ff20244b277874aae03abd14b7da3fb,[26773,100000000,0,0]]]"
}
}
},
{
"boxId": "51ee148b7dfec89ed5435a2fc592cca76811eeff364ed0602a77423a92f15179",
"value": 10000000,
"index": 1,
"spendingProof": "9a01bef2d5e972a7913e2ee2effa861530f3c13f3db641f89a92fe876778693f129b1412e3acb534536430bad168eeef22f392151ac5968d",
"outputBlockId": "9a119d83c629590d00b1bb49bba19b2249398a7a3ff9b980f98df81360d10fce",
"outputTransactionId": "661d03485d842512c0f0f14423c74aa240225416981e4601144b5d64c215f187",
"outputIndex": 19,
"outputGlobalIndex": 13381573,
"outputCreatedAt": 688959,
"outputSettledAt": 688962,
"ergoTree": "100804000401040004000e204f5c05967a2a68d5fe0cdd7a688289f5b1a8aef7d24cab71c20ab8896068e0a80100010108cd0302122c332fd4e3c901f045ac18f559dcecf8dc61f6f94fbb34d0c7c3aac71fb7ea02d1afe4c6a7040c3c0e11d901013c0e11d801d603dc0c1aada5d9010363c27203028c7201017300959472037301d802d604b2a5720300d605db630872049591b172057302d801d606b27205730300ed938c7206017304938c720602c17204730573067307",
"ergoTreeConstants": "0: 0\n1: -1\n2: 0\n3: 0\n4: Coll(79,92,5,-106,122,42,104,-43,-2,12,-35,122,104,-126,-119,-11,-79,-88,-82,-9,-46,76,-85,113,-62,10,-72,-119,96,104,-32,-88)\n5: false\n6: true\n7: SigmaProp(ProveDlog(ECPoint(2122c3,fecf3d,...)))",
"ergoTreeScript": "{sigmaProp(SELF.R4[Coll[(Coll[Byte], Coll[Long])]].get.forall({(tuple1: (Coll[Byte], Coll[Long])) =>\n val i3 = OUTPUTS.map({(box3: Box) => box3.propositionBytes }).indexOf(tuple1._1, placeholder[Int](0))\n if (i3 != placeholder[Int](1)) {(\n val box4 = OUTPUTS(i3)\n val coll5 = box4.tokens\n if (coll5.size > placeholder[Int](2)) {(\n val tuple6 = coll5(placeholder[Int](3))\n (tuple6._1 == placeholder[Coll[Byte]](4)) && (tuple6._2 == box4.value)\n )} else { placeholder[Boolean](5) }\n )} else { placeholder[Boolean](6) }\n })) && placeholder[SigmaProp](7)}",
"address": "5myzaZfXxd9b8H7695FKNa6UMYgM43KQCV9KPLC8QffhVSmbjMQcapFWUjcnTUpr2LhaqTN6sHU6JqQpaUtqB47q93brG1TY5166XvJDAotEV96EnH1P5whp7K2YHgx12TdRvhnc9aJjGEQAfBXG8fL9FHrx5VH4QoXmRbYt8V8LtQ37iMwDTVGHVKpLpU2JpQT25jQXAWcgdeVjKtJX7q3mUkEck3QXdQQHub688azmn4oLoq76auhr22gtV5J4VwL",
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{
"tokenId": "4f5c05967a2a68d5fe0cdd7a688289f5b1a8aef7d24cab71c20ab8896068e0a8",
"index": 0,
"amount": 7982000000,
"name": "GetBlok.io Soft-Fork Governance Token",
"decimals": 9,
"type": "EIP-004"
}
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{
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"value": 3716000000,
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"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "34323ff0647cc1d800812110a33ccb2601bba164829be66646c271b870f681d4",
"value": 4266000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "63b4208c0ee2545867034bc978e1d760e17cd9f5f47db3d20f5363c837cd5f29",
"outputTransactionId": "09fdd8652d29ceb37a8a7b48cb2c540187cf386208217683307a278d8487cd60",
"outputIndex": 11,
"outputGlobalIndex": 13371801,
"outputCreatedAt": 688754,
"outputSettledAt": 688757,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(-58,-73,95,96,127,-16,-115,118,-82,26,-53,120,86,78,91,-110,-116,-51,-106,-72,-76,-37,-54,-47,97,-42,32,109,-73,-26,8,-64)\n2: 1\n3: 0\n4: true\n5: 1\n6: true\n7: false\n8: 1\n9: 0\n10: 2\n11: 1\n12: 0\n13: 2\n14: 1000\n15: 1000000\n16: 2\n17: 1\n18: 0\n19: 2\n20: 0\n21: 1000000\n22: 0\n23: 0\n24: 1000000\n25: 0\n26: 1\n27: 0\n28: 2\n29: -1\n30: 2\n31: -1\n32: 0\n33: false\n34: -1\n35: -1\n36: 0\n37: false\n38: -1\n39: 0\n40: 0\n41: -1\n42: false\n43: true\n44: 0\n45: true\n46: 0\n47: 0\n48: 0\n49: 0\n50: 0\n51: false\n52: Coll(16,28,4,0,4,2,4,0,4,2,1,0,1,0,4,0,4,1,1,0,4,2,1,0,4,0,4,2,4,0,5,2,4,2,4,4,4,4,5,0,4,0,4,0,4,0,4,0,4,0,4,0,1,0,1,0,1,1,-40,9,-42,1,-58,-89,7,17,-42,2,-58,-89,8,12,60,14,14,-42,3,-106,-125,6,1,-26,-58,-89,4,12,60,14,17,-26,-58,-89,5,12,60,14,14,-26,-58,-89)\n53: true",
"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "de82b78cfe81ba72679a0e66f5904c678fa3e796b39f61d5e83ddb66139beafa",
"transactionId": "3fd742d8185d6abb6f3cf902dab3a858951387f1d05be2a1a2cd789678d515fe",
"blockId": "f20d8e5f95bee9d53cb51ddc10f5b245f5947f47702e93d600a731ee57d13ae8",
"value": 10000000,
"index": 0,
"globalIndex": 13381791,
"creationHeight": 688959,
"settlementHeight": 688963,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: 1\n4: false\n5: false\n6: 0\n7: -1\n8: false\n9: 1\n10: false\n11: 0\n12: 1\n13: 0\n14: 1\n15: 1\n16: 2\n17: 2\n18: 0\n19: 0\n20: 0\n21: 0\n22: 0\n23: 0\n24: 0\n25: false\n26: false\n27: true",
"ergoTreeScript": "{\n val opt1 = SELF.R7[Coll[Long]]\n val opt2 = SELF.R8[Coll[(Coll[Byte], Coll[Byte])]]\n val bool3 = allOf(\n Coll[Boolean](\n SELF.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, SELF.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, SELF.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, opt1.isDefined, opt2.isDefined, INPUTS(placeholder[Int](0)) == SELF\n )\n )\n val box4 = INPUTS(placeholder[Int](1))\n val opt5 = box4.R5[Coll[(Coll[Byte], Coll[Byte])]]\n val opt6 = box4.R4[Coll[(Coll[Byte], Coll[Long])]]\n val box7 = OUTPUTS(placeholder[Int](2))\n val opt8 = box7.R7[Coll[Long]]\n val coll9 = box7.tokens\n if (bool3) {\n sigmaProp(\n if (if (if (if (bool3) { opt2.get.exists({(tuple10: (Coll[Byte], Coll[Byte])) => tuple10._1 == INPUTS(placeholder[Int](3)).propositionBytes }) } else {\n placeholder[Boolean](4)\n }) {\n allOf(\n Coll[Boolean](\n box4.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box4.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box4.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box4.R7[Coll[Long]].isDefined, box4.R8[Coll[(Coll[Byte], Coll[Byte])]].isDefined\n )\n )\n } else { placeholder[Boolean](5) }) {\n opt5.get.forall(\n {(tuple10: (Coll[Byte], Coll[Byte])) =>\n opt6.get.map({(tuple12: (Coll[Byte], Coll[Long])) => tuple12._1 }).indexOf(tuple10._1, placeholder[Int](6)) != placeholder[Int](7)\n }\n )\n } else { placeholder[Boolean](8) } && if (if (box7.propositionBytes == SELF.propositionBytes) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].isDefined, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].isDefined, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].isDefined, box7.R7[Coll[Long]].isDefined, box7.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].isDefined, box7.value == SELF.value, box7.tokens.size == placeholder[Int](9)\n )\n )\n } else { placeholder[Boolean](10) }) {(\n val coll10 = opt8.get\n val coll11 = opt1.get\n val l12 = coll11(placeholder[Int](11))\n val l13 = coll10(placeholder[Int](12))\n (\n ((coll10(placeholder[Int](13)) == l12 + placeholder[Long](14)) && ((l13 <= HEIGHT.toLong) && (l13 > coll11(placeholder[Int](15))))) && (\n coll10(placeholder[Int](16)) == coll11(placeholder[Int](17))\n )\n ) && if (l12 != placeholder[Long](18)) { SELF.tokens(placeholder[Int](19))._1 == coll9(placeholder[Int](20))._1 } else {(\n val coll14 = SELF.tokens\n if (coll14.size > placeholder[Int](21)) { coll14(placeholder[Int](22))._1 == coll9(placeholder[Int](23))._1 } else {\n coll9(placeholder[Int](24))._1 == SELF.id\n }\n )}\n )} else { placeholder[Boolean](25) }) {\n allOf(\n Coll[Boolean](\n box7.R4[Coll[(Coll[Byte], Coll[Long])]].get == opt6.get, box7.R5[Coll[(Coll[Byte], Coll[Byte])]].get == opt5.get, box7.R6[\n Coll[(Coll[Byte], Int)]\n ].get == box4.R6[Coll[(Coll[Byte], Int)]].get, opt8.get == box4.R7[Coll[Long]].get, box7.R8[Coll[(Coll[Byte], Coll[Byte])]].get == box4.R8[\n Coll[(Coll[Byte], Coll[Byte])]\n ].get\n )\n )\n } else { placeholder[Boolean](26) }\n )\n } else { sigmaProp(placeholder[Boolean](27)) }\n}",
"address": "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",
"assets": [
{
"tokenId": "c6b75f607ff08d76ae1acb78564e5b928ccd96b8b4dbcad161d6206db7e608c0",
"index": 0,
"amount": 1,
"name": "GetBlok.io SmartPool Display Token",
"decimals": 0,
"type": "EIP-004"
}
],
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"ergoTreeScript": "{\n val coll1 = SELF.propositionBytes\n val coll2 = INPUTS.filter({(box2: Box) => box2.propositionBytes == coll1 })\n val i3 = coll2.size\n val box4 = INPUTS(placeholder[Int](0))\n val coll5 = placeholder[Coll[Byte]](1)\n if (!if ((i3 > placeholder[Int](2)) && (coll2(placeholder[Int](3)).id == SELF.id)) { placeholder[Boolean](4) } else {\n if (i3 == placeholder[Int](5)) { placeholder[Boolean](6) } else { placeholder[Boolean](7) }\n }) { sigmaProp({(bool6: Boolean) => if (bool6) {(\n val coll8 = INPUTS(placeholder[Int](8)).R4[Coll[(Coll[Byte], Coll[Long])]].get\n val coll9 = box4.R4[Coll[(Coll[Byte], Coll[Long])]].get\n val l10 = coll2.fold(placeholder[Long](9), {(tuple10: (Long, Box)) => tuple10._1 + tuple10._2.value }) - coll9.filter({(tuple10: (Coll[Byte], Coll[Long])) =>\n val coll12 = tuple10._2\n coll12(placeholder[Int](10)) < coll12(placeholder[Int](11))\n }).fold(placeholder[Long](12), {(tuple10: (Long, (Coll[Byte], Coll[Long]))) => tuple10._1 + tuple10._2._2(placeholder[Int](13)) })\n val coll11 = box4.R6[Coll[(Coll[Byte], Int)]].get.map({(tuple11: (Coll[Byte], Int)) =>\n val l13 = tuple11._2.toLong * l10 / placeholder[Long](14)\n (tuple11._1, l13 - l13 % placeholder[Long](15))\n })\n val coll12 = OUTPUTS.map({(box12: Box) => box12.propositionBytes })\n val coll13 = OUTPUTS.map({(box13: Box) => box13.value })\n val l14 = coll8.filter({(tuple14: (Coll[Byte], Coll[Long])) =>\n val coll16 = tuple14._2\n coll16(placeholder[Int](16)) < coll16(placeholder[Int](17))\n }).fold(placeholder[Long](18), {(tuple14: (Long, (Coll[Byte], Coll[Long]))) => tuple14._1 + tuple14._2._2(placeholder[Int](19)) })\n ((coll8.forall({(tuple15: (Coll[Byte], Coll[Long])) =>\n val coll17 = tuple15._1\n val i18 = coll9.map({(tuple18: (Coll[Byte], Coll[Long])) => tuple18._1 }).indexOf(coll17, placeholder[Int](20))\n val coll19 = tuple15._2\n val l20 = {(l20: Long) =>\n val l22 = coll11.fold(l10, {(tuple22: (Long, (Coll[Byte], Long))) => tuple22._1 - tuple22._2._2 }) - placeholder[Long](21) * coll8.size.toLong * l20 / coll8.fold(placeholder[Long](22), {(tuple22: (Long, (Coll[Byte], Coll[Long]))) => tuple22._1 + tuple22._2._2(placeholder[Int](23)) })\n l22 - l22 % placeholder[Long](24)\n }(coll19(placeholder[Int](25)))\n val l21 = coll19(placeholder[Int](26))\n val i22 = coll12.indexOf(coll17, placeholder[Int](27))\n val l23 = coll19(placeholder[Int](28))\n if (i18 != placeholder[Int](29)) {(\n val l24 = coll9.map({(tuple24: (Coll[Byte], Coll[Long])) => tuple24._2 })(i18)(placeholder[Int](30)) + l20\n if (l24 >= l21) { if (i22 != placeholder[Int](31)) { (coll13(i22) == l24) && (l23 == placeholder[Long](32)) } else { placeholder[Boolean](33) } } else { (i22 == placeholder[Int](34)) && (l23 == l24) }\n )} else { if (l20 >= l21) { if (i22 != placeholder[Int](35)) { (coll13(i22) == l20) && (l23 == placeholder[Long](36)) } else { placeholder[Boolean](37) } } else { (i22 == placeholder[Int](38)) && (l23 == l20) } }\n }) && coll11.forall({(tuple15: (Coll[Byte], Long)) =>\n val l17 = tuple15._2\n if (l17 > placeholder[Long](39)) {(\n val i18 = coll12.indexOf(tuple15._1, placeholder[Int](40))\n if (i18 != placeholder[Int](41)) { OUTPUTS(i18).value == l17 } else { placeholder[Boolean](42) }\n )} else { placeholder[Boolean](43) }\n })) && if (l14 > placeholder[Long](44)) { OUTPUTS.exists({(box15: Box) => (box15.value == l14) && (box15.propositionBytes == coll1) }) } else { placeholder[Boolean](45) }) && if (box4.R7[Coll[Long]].get(placeholder[Int](46)) != placeholder[Long](47)) { box4.tokens(placeholder[Int](48))._1 == coll5 } else {(\n val coll15 = box4.tokens\n if (coll15.size > placeholder[Int](49)) { coll15(placeholder[Int](50))._1 == coll5 } else { box4.id == coll5 }\n )}\n )} else { placeholder[Boolean](51) } }(box4.propositionBytes == placeholder[Coll[Byte]](52))) } else { sigmaProp(placeholder[Boolean](53)) }\n}",
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"mainChain": true
},
{
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"ergoTree": "0008cd0287352ce40ff53154c5b3751a661908d3ca99edbb198e7ebb63d1d00e580f2efd",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(87352c,619230,...)))}",
"address": "9fYcDQQ1pduG13GcmrLfLj2Khfge6DeTARVGhy58aXEqmhuft2C",
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"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(b6f381,3477d9,...)))}",
"address": "9fudkuDuZTkgjZVsHU8Y1Nq1UtPHGjD2sD6zFAry5o3GoJc4Z1E",
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"ergoTreeConstants": "",
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"ergoTreeConstants": "",
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