Transaction
ID: ea11f8bf31...2157
Inputs (5)
Spent
Address:
Output transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
4.57 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.0001368 ERG
Tokens:
Loading assets...
Outputs (8)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.005 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.05 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00185 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.26 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2.26 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 198,445
Total coins transferred: 5.58 ERG
Fees: 0.00185 ERG
Fees per byte: 0.000000152 ERG
Raw Transaction Data
{
"id": "ea11f8bf312357c56b24ff229d4eb6118b43a0631c065e537b404552d9af2157",
"blockId": "5e1749e7b7ef27f70610c46a5510a2a9afc0ec0daedeb19419e1d257527632b0",
"inclusionHeight": 1570990,
"timestamp": 1752825705481,
"index": 2,
"globalIndex": 9226793,
"numConfirmations": 198445,
"inputs": [
{
"boxId": "a329cbff8201cd3125d0917405c10b596654309c95ef9ecd777ccf4e3bf934dd",
"value": 1000000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "b1001bdcbd07fb9116ce0fc3fcec95e613d472c76203722a360189516fe164b6",
"outputTransactionId": "ee7a6bf15e50e627f7963af059adf4c83dcc4bce6ce5ec13e430f9b1de6fa992",
"outputIndex": 0,
"outputGlobalIndex": 48947076,
"outputCreatedAt": 1570853,
"outputSettledAt": 1570855,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](\n -34.toByte, -82.toByte, -49.toByte, 91.toByte, 100.toByte, -70.toByte, -42.toByte, -11.toByte, 87.toByte, 11.toByte, -83.toByte, 10.toByte, 97.toByte, 12.toByte, 78.toByte, 72.toByte, 73.toByte, 87.toByte, -49.toByte, 71.toByte, -126.toByte, 48.toByte, -124.toByte, 0.toByte, -68.toByte, -112.toByte, 64.toByte, 76.toByte, 29.toByte, 20.toByte, 16.toByte, -38.toByte\n )\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val func3 = {(tuple3: (Coll[Box], Coll[Byte])) =>\n tuple3._1.filter({(box5: Box) => box5.tokens.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == tuple3._2 }) })\n }\n val box4 = func3((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)\n val opt5 = getVar[Coll[Byte]](1.toByte)\n val func6 = {(opt6: Option[Coll[Byte]]) => opt6.get.slice(1, 33) }\n val func7 = {(box7: Box) => box7.tokens(0) }\n val tuple8 = func7(SELF)\n val box9 = func3((OUTPUTS, tuple8._1))(0)\n val func10 = {(box10: Box) => box10.tokens(1) }\n val func11 = {(coll11: Coll[Byte]) =>\n val coll13 = func2(box4).getMany(Coll[Coll[Byte]](coll1, coll11), opt5.get)\n allOf(\n Coll[Boolean](\n {(tuple14: (Coll[Box], Coll[Byte])) => tuple14._1.filter({(box16: Box) => blake2b256(box16.propositionBytes) == tuple14._2 }) }(\n (INPUTS, func6(coll13(1)))\n ).size == 1, {(coll14: Coll[Byte]) =>\n allOf(Coll[Boolean](blake2b256(box9.propositionBytes) == coll14, func7(box9) == tuple8, func10(box9)._1 == func10(SELF)._1))\n }(func6(coll13(0)))\n )\n )\n }\n val b12 = getVar[Byte](0.toByte).get\n val i13 = INPUTS.indexOf(SELF, 0)\n val func14 = {(l14: Long) =>\n if (l14 < 128L) { 1 } else {\n if (l14 < 16384L) { 2 } else {\n if (l14 < 2097152L) { 3 } else {\n if (l14 < 268435456L) { 4 } else {\n if (l14 < 34359738368L) { 5 } else {\n if (l14 < 4398046511104L) { 6 } else { if (l14 < 562949953421312L) { 7 } else { if (l14 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b15: Byte) =>\n if (b15 == 0.toByte) {\n func11(\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 2.toByte) {\n func11(\n Coll[Byte](\n -117.toByte, -57.toByte, -113.toByte, 28.toByte, 106.toByte, -82.toByte, -55.toByte, 30.toByte, 98.toByte, -114.toByte, 21.toByte, -49.toByte, 102.toByte, -116.toByte, 22.toByte, -52.toByte, 30.toByte, -101.toByte, -40.toByte, -28.toByte, -71.toByte, -73.toByte, -31.toByte, 109.toByte, 99.toByte, 24.toByte, -75.toByte, -11.toByte, 35.toByte, -91.toByte, -23.toByte, -67.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 1.toByte) {\n func11(\n Coll[Byte](\n -120.toByte, 48.toByte, 97.toByte, 44.toByte, 82.toByte, 53.toByte, 95.toByte, 111.toByte, 40.toByte, 13.toByte, 18.toByte, -105.toByte, -15.toByte, -97.toByte, 103.toByte, -80.toByte, 120.toByte, -55.toByte, -38.toByte, -89.toByte, -41.toByte, -80.toByte, 75.toByte, 69.toByte, -100.toByte, -111.toByte, -52.toByte, 100.toByte, 73.toByte, 87.toByte, -62.toByte, -128.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 3.toByte) {\n func11(\n Coll[Byte](\n 79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 4.toByte) {\n func11(\n Coll[Byte](\n -119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 5.toByte) {\n func11(\n Coll[Byte](\n 58.toByte, 17.toByte, -107.toByte, 92.toByte, 71.toByte, 25.toByte, -27.toByte, -120.toByte, -68.toByte, -26.toByte, -89.toByte, 97.toByte, 29.toByte, 39.toByte, -67.toByte, 31.toByte, -33.toByte, -37.toByte, 87.toByte, 56.toByte, 92.toByte, -82.toByte, -30.toByte, 102.toByte, -40.toByte, 4.toByte, 12.toByte, -119.toByte, 79.toByte, 28.toByte, 46.toByte, 29.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 6.toByte) {\n func11(\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) => if (b15 == 7.toByte) { {(tuple17: (Coll[Byte], Box)) => if (i13 >= OUTPUTS.size) { false } else {(\n val box19 = OUTPUTS(i13)\n val l20 = box19.value\n val l21 = SELF.value\n val coll22 = box19.propositionBytes\n val coll23 = SELF.bytesWithoutRef\n val coll24 = SELF.propositionBytes\n val i25 = SELF.creationInfo._1\n val coll26 = box19.bytesWithoutRef\n val i27 = box19.creationInfo._1\n allOf(Coll[Boolean](l20 >= l21 - 2000000L, blake2b256(coll22) == func6(func2(tuple17._2).getMany(Coll[Coll[Byte]](tuple17._1), opt5.getOrElse(Coll[Byte]()))(0)), coll23.slice(func14(l21) + coll24.size + func14(i25.toLong), coll23.size) == coll26.slice(func14(l20) + coll22.size + func14(i27.toLong), coll26.size), anyOf(Coll[Boolean](i27 - i25 >= 504000, coll24 != coll22))))\n )} }((coll1, box4)) } else { false } }(b12)\n )\n )\n )\n}",
"address": "3bseGyoGRw4m55rWByCZiWWe6YhEPNpC9Ex3dE2KmPpbWES2LbKCEB5xeHk1fJyZ9BR4uNAps7B4NmkPTbjbSSrdH4CPFrkBXXAbdVDMed5WKnSqyqCdJmUsHfxdH2iREB5PEdGV7nFyxAsN8y5pLok3jejSxEhCDZCPk81PdLh8vSWG5DS3YaZ33ABnL4tQcLNq41LCt662xawB3QNqdKRuynVeNLpLUy69CZsRKx7XrWsBrrG57QgcVBryFbDs4sEGywZj9b2ZF32ZGTz13KHL5vNXirZQ9BjEbtTb95Y3iTmD49MRC3ZFDHuyvAJ9ndvWvAET7NMFwzHrrvArXyRRgPqVj83X8Yc6ftReNxhFa2WSFP8q6kGeXnYH1tFHhoMizDbgGA2mrwa4d8b5fvZNDzsouD9WeEhn5LFmev9dKAzGmtB2s9mDRdmLkixgBpkyCUBzmuV1Ym6Jqs8TR8wE8Pd1phBRZgZa7uK44CB23bMkuH5JqJBszMdKp7HnT95ScqP1NxYccbQkFVHAAanoq15jfFkHKeTf3vbqsUSJkckonegimEarT6BRTsbfHgw14pJBhW1Jb26BL7iLtzVs3wmb5PxRYWSKUgyFQfRxZdiiGvrQbXa2P7eXpzR2FDp3NHj2QMhEmziRsSb4T9VYb1FAt5PJBoe7Wb5tEg3Dj1gLw8UvR7XGmBpHEhS1hzL8xp39bZQy72RmocNFH8wJyryLLJgQQnxryVuxLkcQWMfA4kiXYzEXZHyXp5LgGU6XHyDf6d6kz6tpexuKksZ9nAQ5utJNiAzub8QXaHQgjuWjWERPToXR9EUukVg6yEuBFq7Z37XFHpLJcA339AokSKSDXdARDvBRPEfEpBTqqKoiJasGgZn7zwvVbZnCuryMhKZZGY5QRqMEjZPa86n5Y9oGcR3MMBLs1Mv9bEu3SGky7ZWMBodkLMZZEwJLgN5t7ZWGKfHnCYPsThTmNSvCBNxVc4Z3FiDHHcLAQi7A7TRtJppoQcg329cUHZKcf7eoHeEb7xoH94nVP8NfgQe2m1keFXoRwnuwJPh8kSVw77CzR8hZv24b3BmwvevVZD513cAk3oq5q18WgaBN7bQzE2S7UpVHnbhypQdpZ85PzR2eyP6inJ5fgKqjQkKTfSTYm3rYkTN8BdHQ7eHG3Ww7Zm1YTrphHY98KQCtth1pcPYGJTzbhdTQbjM1znY7eZjH7NWwmzzzJq8KxFL4MG4qcFDWrQ6Y7NVmvoduAniw3nGa2RmFGVVBpRvVH8pasg2Xg4DWMAFmoFGL5WBtqcvFMF4tSB9EpXDNwp7JaszNEk9YD1CcWMvj4y6zmStiHK856oG2KSvDgJsfCbJzfdhoZfczVjhV3JJrs3uar5joGzjNkjcKzq7UprEfMenRxz4xgwxVy57kWRBWqXKTGz6EMNhzXJcJCZtt2rNnZSRMzWBFVQe6Br5ABWvz4KHc8NgjE7zZb171dyCZeRj5evF5kgiJZWf3dwTS5tCmNHhqtrC4SjrUx819SjpFWbaf17FBniNTTcXDQyNZYAqtNcNkPjpcGC7Vc6MWLAQrkvgSpHS7rQhb7PwEovUnhSBuVxV5Mkb7XqW24f1tiXgSxjLfXxEzrY98YdvyswYwxT2eT5JU1Nefbqkqqi9DtPqkfLECbXkKBNrwYBAfVCswppfUgj9fcUyip96tdhavv9oi5vXS1EztdQt2jXL58XUXy8meS5wirzDtQZRrckrAbZZr2naQw6sVpuTgFzrsJ7kTmg2HjSyTyFcEMtNKt1kisSVWzb1eG7FqWkyn9i1kkmo8",
"assets": [
{
"tokenId": "9b7ea8b9abab7d2e60a5d92c6b1939af1a7c13985a942eed94e3dc5aaf37bc83",
"index": 0,
"amount": 1,
"name": "Sigmanauts Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00b6f6e34943cef98f5302c54cf13a81f7ab5cd6af2d7b14cf51d835e4e8288c",
"index": 1,
"amount": 19,
"name": "Sigmanaut",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107d08ffbcb8766242202020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1753365832680,18,17,1,1,0,0]"
},
"R6": {
"serializedValue": "1d0501240110011001320132",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[18],[8],[8],[25],[25]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e16090007200029687428dfe182ab80eeecd21c35cfc754f2aabbddcbe32fca5fd738d4ad8e0304072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402779d571a4ab72e22ed5a3e50a22248be2a2d8751bdb0f27087cdb515622b5c4f050720000f953cd7293a8b356623986c3ba210b0ca5d4348de6241d6203fb9436043460401072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "9ec55f1a884f5d680b1193c1af4d8b1950bc1976cbaadffa039b065e2041104e",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "b1001bdcbd07fb9116ce0fc3fcec95e613d472c76203722a360189516fe164b6",
"outputTransactionId": "ee7a6bf15e50e627f7963af059adf4c83dcc4bce6ce5ec13e430f9b1de6fa992",
"outputIndex": 1,
"outputGlobalIndex": 48947077,
"outputCreatedAt": 1570853,
"outputSettledAt": 1570855,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\n1: Coll(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[Coll[Byte]]](0.toByte).get\n val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(CONTEXT.dataInputs(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n ), Coll[Byte](\n 61.toByte, -86.toByte, 102.toByte, -128.toByte, -114.toByte, 105.toByte, -62.toByte, 90.toByte, -23.toByte, 50.toByte, -35.toByte, 102.toByte, 97.toByte, 28.toByte, 95.toByte, 11.toByte, 60.toByte, -70.toByte, -54.toByte, -47.toByte, 18.toByte, 82.toByte, 3.toByte, -24.toByte, 125.toByte, -115.toByte, -60.toByte, -111.toByte, -122.toByte, 28.toByte, 113.toByte, -26.toByte\n )\n ), coll1(0)\n )\n val coll3 = coll1(9)\n val func4 = {(tuple4: (Coll[Box], Coll[Byte])) =>\n tuple4._1.filter({(box6: Box) => box6.tokens.exists({(tuple8: (Coll[Byte], Long)) => tuple8._1 == tuple4._2 }) })\n }\n val coll5 = placeholder[Coll[Byte]](1)\n val box6 = func4((OUTPUTS, coll5))(0)\n val box7 = func4((INPUTS, coll5))(0)\n val func8 = {(box8: Box) => box8.R4[Coll[AvlTree]].get(0) }\n val avlTree9 = func8(box7)\n val box10 = func4((INPUTS, {(opt10: Option[Coll[Byte]]) => opt10.get.slice(6, 38) }(coll2(1))))(0)\n val coll11 = avlTree9.get(coll3, coll1(2)).get\n val coll12 = longToByteArray(\n max({(box12: Box) => box12.R5[Coll[Long]].get(0) }(box10), {(coll12: Coll[Byte]) => byteArrayToLong(coll12.slice(0, 8)) }(coll11))\n ).append(coll11.slice(8, coll11.size))\n val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n val avlTree14 = func13(box7)\n val opt15 = avlTree14.get(coll3, coll1(4))\n val bool16 = opt15.isDefined\n val opt17 = {(box17: Box) => box17.R6[AvlTree].get }(box10).get(coll3, coll1(1))\n val bool18 = opt17.isDefined\n val l19 = if (bool16) { byteArrayToLong(opt15.get.slice(0, 8)) } else { 0L }\n val l20 = if (bool18) { l19 } else { l19 + 1L }\n val l21 = if (bool16) { byteArrayToLong(opt15.get.slice(8, 16)) } else { 0L }\n val coll22 = coll1(8)\n val l23 = coll22.indices.slice(0, coll22.size / 8).map({(i23: Int) => byteArrayToLong(coll22.slice(i23 * 8, i23 + 1 * 8)) }).fold(\n 0L, {(tuple23: (Long, Long)) => tuple23._1 + tuple23._2 }\n )\n val l24 = if (bool18) {(\n val coll24 = opt17.get\n max(\n l21 - coll24.indices.slice(0, coll24.size / 8).map({(i25: Int) => byteArrayToLong(coll24.slice(i25 * 8, i25 + 1 * 8)) }).fold(\n 0L, {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }\n ) + l23, 0L\n )\n )} else { l21 + l23 }\n val coll25 = longToByteArray(l20).append(longToByteArray(l24))\n val coll26 = coll1(5)\n val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(0) }\n val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(1) }\n val func29 = {(box29: Box) => box29.R5[Coll[Long]].get(2) }\n val func30 = {(box30: Box) => box30.R5[Coll[Long]].get(3) }\n val func31 = {(box31: Box) => box31.R5[Coll[Long]].get(4) }\n val func32 = {(box32: Box) =>\n val coll34 = box32.R5[Coll[Long]].get\n coll34.slice(5, coll34.size)\n }\n val func33 = {(box33: Box) => box33.R6[Coll[Coll[Long]]].get }\n val func34 = {(box34: Box) => box34.R7[Coll[(AvlTree, AvlTree)]].get }\n val func35 = {(box35: Box) => box35.R8[Coll[Long]].get }\n sigmaProp(\n allOf(\n Coll[Boolean](\n {(tuple36: (Coll[Box], Coll[Byte])) => tuple36._1.filter({(box38: Box) => blake2b256(box38.propositionBytes) == tuple36._2 }) }(\n (OUTPUTS, {(opt36: Option[Coll[Byte]]) => opt36.get.slice(1, 33) }(coll2(0)))\n )(0).value >= SELF.value, {(tuple36: (Coll[Box], Coll[Byte])) =>\n tuple36._1.exists({(box38: Box) => box38.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == tuple36._2 }) })\n }((OUTPUTS, coll3)), allOf(\n Coll[Boolean](\n box6.value == box7.value, box6.tokens == box7.tokens, func8(box6).digest == avlTree9.update(\n Coll[(Coll[Byte], Coll[Byte])]((coll3, coll12)), coll1(3)\n ).get.digest, func13(box6).digest == if (bool16) { avlTree14.update(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get } else {\n avlTree14.insert(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get\n }.digest, func27(box6) == func27(box7), func28(box6) == func28(box7), func29(box6) == func29(box7), func30(box6) == func30(\n box7\n ) + l20 - l19, func31(box6) == func31(box7) + l24 - l21, func32(box6) == func32(box7), func33(box6) == func33(box7), func34(box6) == func34(\n box7\n ), func35(box6) == func35(box7)\n )\n ), coll1(6) == coll12, coll1(7) == coll25\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "192ac4c238aa92b6910e21b91df50946e45006a26ae733fba27fb9aa85200a2d",
"value": 5000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "b1001bdcbd07fb9116ce0fc3fcec95e613d472c76203722a360189516fe164b6",
"outputTransactionId": "ee7a6bf15e50e627f7963af059adf4c83dcc4bce6ce5ec13e430f9b1de6fa992",
"outputIndex": 2,
"outputGlobalIndex": 48947078,
"outputCreatedAt": 1570853,
"outputSettledAt": 1570855,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.tokens(0) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val preHeader3 = CONTEXT.preHeader\n val b4 = getVar[Byte](0.toByte).get\n val func5 = {(box5: Box) =>\n val coll7 = box5.R5[Coll[Long]].get\n coll7.slice(2, coll7.size)\n }\n val opt6 = getVar[(Int, Long)](10.toByte)\n val tuple7 = (-2, 0L)\n val tuple8 = tuple7\n val tuple9 = opt6.getOrElse(tuple8)\n val i10 = tuple9._1\n val l11 = tuple9._2\n val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n val coll17 = placeholder[Coll[Byte]](3)\n val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n }\n val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple22 = tuple20._2\n val l23 = tuple22._1\n val tuple24 = tuple22._2\n val l25 = tuple24._1\n val l26 = tuple24._2\n tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n val l29 = byteArrayToLong(coll27.slice(1, 9))\n if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n )} else { l26 } }).getOrElse(l26)\n }\n val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b22: Byte) =>\n if (b22 == 12.toByte) {\n {(coll24: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n } else { false }\n }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n val coll24 = func5(SELF)\n val coll25 = SELF.propositionBytes\n val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n val l27 = box26.value\n val l28 = func14(SELF)\n val coll29 = CONTEXT.dataInputs\n val coll30 = Coll[Byte]()\n val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n val tuple32 = (1L, (999L, 500L))\n val opt33 = opt6\n val tuple34 = tuple7\n val tuple35 = tuple8\n val tuple36 = tuple9\n val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n val l39 = l11\n l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n val tuple43 = tuple41._2\n tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll25 = coll24(4)\n val coll26 = coll24(3)\n val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n val coll29 = SELF.propositionBytes\n val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n val l31 = func21(SELF)\n val avlTree32 = func15(SELF)\n val opt33 = avlTree32.get(coll25, coll24(0))\n val bool34 = opt33.isDefined\n val coll35 = coll24(1)\n val coll36 = func5(SELF)\n val coll37 = func5(box30)\n allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n val coll38 = opt33.get\n val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n )} else { false } }(b4)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 1,
"name": "Sigmanauts Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 5000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10021e01",
"sigmaType": "Coll[SInt]",
"renderedValue": "[15,-1]"
},
"R5": {
"serializedValue": "1104b092a5f98766020002",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1753413362840,1,0,1]"
},
"R6": {
"serializedValue": "64e574533b601f9cb54ee3059893840a508b5d3e9f19a0ee51604e5c1c38a58faf01072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e305369676d616c6f6b202d2037306b204d657720666f72203268722773206f66204b757368746920534320726576696577",
"sigmaType": "Coll[SByte]",
"renderedValue": "5369676d616c6f6b202d2037306b204d657720666f72203268722773206f66204b757368746920534320726576696577"
}
}
},
{
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"value": 4574518543,
"index": 3,
"spendingProof": "698041d97851cfc998ae45db7b9c73143f107b5e9ec44cb98d1670bfdc5dfed1eec22c8ffeee9b2783fe4d2e1080cc9a19b21cf8f6a26498",
"outputBlockId": "fd988deaf831399ad919d2cfb7e93eab0fe7bc5d60f6a3429ed8fc07b0a89e60",
"outputTransactionId": "23d4ff907b32469f375305950010148310ad2cedac0be4b89bcb1fa0e5f9a132",
"outputIndex": 2,
"outputGlobalIndex": 48910300,
"outputCreatedAt": 1569511,
"outputSettledAt": 1569514,
"ergoTree": "0008cd026bc5d849581d171cd2b9b3b64887e3319bd4b52a63b72bb125cdde9050a4e0e4",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6bc5d8,4a53a1,...)))}",
"address": "9fLXRjthKecc7LsHyQAF9w2DfqVbsFxsHqUBpz2ouBPYRmaBxfT",
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{
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"decimals": 0,
"type": "EIP-004"
},
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"name": "SEGGS",
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"type": "EIP-004"
},
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},
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},
{
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},
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},
{
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"type": "EIP-004"
},
{
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},
{
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"type": "EIP-004"
},
{
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"type": "EIP-004"
},
{
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"type": "EIP-004"
},
{
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"decimals": 0,
"type": "EIP-004"
},
{
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"amount": 8,
"name": "catWITHbat",
"decimals": 0,
"type": "EIP-004"
},
{
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"amount": 1,
"name": "Mew Fun Lottery Ticket Test",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 15,
"amount": 1,
"name": "Mew Fun Lottery Ticket",
"decimals": 0,
"type": "EIP-004"
},
{
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"amount": 360,
"name": "ergopad",
"decimals": 2,
"type": "EIP-004"
},
{
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"name": "Cypher",
"decimals": 0,
"type": "EIP-004"
},
{
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"outputBlockId": "fd988deaf831399ad919d2cfb7e93eab0fe7bc5d60f6a3429ed8fc07b0a89e60",
"outputTransactionId": "23d4ff907b32469f375305950010148310ad2cedac0be4b89bcb1fa0e5f9a132",
"outputIndex": 3,
"outputGlobalIndex": 48910301,
"outputCreatedAt": 1569511,
"outputSettledAt": 1569514,
"ergoTree": "0008cd026bc5d849581d171cd2b9b3b64887e3319bd4b52a63b72bb125cdde9050a4e0e4",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(6bc5d8,4a53a1,...)))}",
"address": "9fLXRjthKecc7LsHyQAF9w2DfqVbsFxsHqUBpz2ouBPYRmaBxfT",
"assets": [
{
"tokenId": "ea67240163679fc39ebdfd7f52384bfc0ed00a3ed9417d281ae306397231728f",
"index": 0,
"amount": 1,
"name": "Mew Fun Lottery Ticket",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00b42b41cb438c41d0139aa8432eb5eeb70d5a02d3df891f880d5fe08670c365",
"index": 1,
"amount": 10000,
"name": "CRUX",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "03faf2cb329f2e90d6d23b58d91bbb6c046aa143261cc21f52fbe2824bfcbf04",
"index": 2,
"amount": 41,
"name": "SigUSD",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "d4f046685311cbf8cda51ea612476e37141f1f0d929703be810185b55d2a1d69",
"index": 3,
"amount": 1,
"name": "Mew Fun Lottery Ticket",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "7e0ffa300233666c35e3b92b2bb84b2995997af076e2a57134b0e6fae44129f5",
"index": 4,
"amount": 1,
"name": "Sigmanauts Membership",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "0e03bb9408154c47858ed547d874526978fbfe0e683125fbb696aa6fab86ae80",
"index": 5,
"amount": 1,
"name": "Test NFT 01",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "bdb6dbdf2ed60f09a8bfc7621a4c0945d709c59626fa0ef44b63a5603c70d6e4",
"index": 6,
"amount": 31253500,
"name": "Scam",
"decimals": 2,
"type": "EIP-004"
},
{
"tokenId": "b5160860c8584c4a4ab7e55f1500cbc744a77626c294a330ff5b5d8fd9f547b6",
"index": 7,
"amount": 1,
"name": "Mew Fun Lottery Ticket",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3a955a6120459f3a19202d952fd678c4747a4bded173e72ec806928cfc1cdba5",
"index": 8,
"amount": 1,
"name": "Mew Fun Lottery Ticket Test",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "53f02a91a6e79264a048e79ef506de8fdd48c86790b900c05c5893a6fe10d96b",
"value": 1000000000,
"index": 0,
"outputBlockId": "23c94deb8121036a5b3918c92061b1ce22f50cfe9eddae36e59c192166d72123",
"outputTransactionId": "6a0107ac5dfabf21418217f5f73dd2e1afbc586d66a76f751526c86e2ee020cc",
"outputIndex": 0,
"ergoTree": "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",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64c3304886c37ddc9c10620d2260693c33ba9a16a33cc50d80709639b115a4643206072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "529eba5418dfbb6454c55006f4a2ad948bb6609a59afa480a8e853144a1c3695",
"transactionId": "ea11f8bf312357c56b24ff229d4eb6118b43a0631c065e537b404552d9af2157",
"blockId": "5e1749e7b7ef27f70610c46a5510a2a9afc0ec0daedeb19419e1d257527632b0",
"value": 1000000000,
"index": 0,
"globalIndex": 48951213,
"creationHeight": 1570987,
"settlementHeight": 1570990,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)",
"ergoTreeScript": "{\n val coll1 = Coll[Byte](\n -34.toByte, -82.toByte, -49.toByte, 91.toByte, 100.toByte, -70.toByte, -42.toByte, -11.toByte, 87.toByte, 11.toByte, -83.toByte, 10.toByte, 97.toByte, 12.toByte, 78.toByte, 72.toByte, 73.toByte, 87.toByte, -49.toByte, 71.toByte, -126.toByte, 48.toByte, -124.toByte, 0.toByte, -68.toByte, -112.toByte, 64.toByte, 76.toByte, 29.toByte, 20.toByte, 16.toByte, -38.toByte\n )\n val func2 = {(box2: Box) => box2.R4[AvlTree].get }\n val func3 = {(tuple3: (Coll[Box], Coll[Byte])) =>\n tuple3._1.filter({(box5: Box) => box5.tokens.exists({(tuple7: (Coll[Byte], Long)) => tuple7._1 == tuple3._2 }) })\n }\n val box4 = func3((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)\n val opt5 = getVar[Coll[Byte]](1.toByte)\n val func6 = {(opt6: Option[Coll[Byte]]) => opt6.get.slice(1, 33) }\n val func7 = {(box7: Box) => box7.tokens(0) }\n val tuple8 = func7(SELF)\n val box9 = func3((OUTPUTS, tuple8._1))(0)\n val func10 = {(box10: Box) => box10.tokens(1) }\n val func11 = {(coll11: Coll[Byte]) =>\n val coll13 = func2(box4).getMany(Coll[Coll[Byte]](coll1, coll11), opt5.get)\n allOf(\n Coll[Boolean](\n {(tuple14: (Coll[Box], Coll[Byte])) => tuple14._1.filter({(box16: Box) => blake2b256(box16.propositionBytes) == tuple14._2 }) }(\n (INPUTS, func6(coll13(1)))\n ).size == 1, {(coll14: Coll[Byte]) =>\n allOf(Coll[Boolean](blake2b256(box9.propositionBytes) == coll14, func7(box9) == tuple8, func10(box9)._1 == func10(SELF)._1))\n }(func6(coll13(0)))\n )\n )\n }\n val b12 = getVar[Byte](0.toByte).get\n val i13 = INPUTS.indexOf(SELF, 0)\n val func14 = {(l14: Long) =>\n if (l14 < 128L) { 1 } else {\n if (l14 < 16384L) { 2 } else {\n if (l14 < 2097152L) { 3 } else {\n if (l14 < 268435456L) { 4 } else {\n if (l14 < 34359738368L) { 5 } else {\n if (l14 < 4398046511104L) { 6 } else { if (l14 < 562949953421312L) { 7 } else { if (l14 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b15: Byte) =>\n if (b15 == 0.toByte) {\n func11(\n Coll[Byte](\n 3.toByte, -110.toByte, 8.toByte, -68.toByte, 78.toByte, -17.toByte, -102.toByte, 3.toByte, -24.toByte, -41.toByte, -117.toByte, -122.toByte, 99.toByte, -93.toByte, 1.toByte, -69.toByte, 95.toByte, -83.toByte, -36.toByte, -89.toByte, -117.toByte, -31.toByte, -99.toByte, 127.toByte, -27.toByte, 53.toByte, -77.toByte, -58.toByte, 76.toByte, -66.toByte, -2.toByte, 66.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 2.toByte) {\n func11(\n Coll[Byte](\n -117.toByte, -57.toByte, -113.toByte, 28.toByte, 106.toByte, -82.toByte, -55.toByte, 30.toByte, 98.toByte, -114.toByte, 21.toByte, -49.toByte, 102.toByte, -116.toByte, 22.toByte, -52.toByte, 30.toByte, -101.toByte, -40.toByte, -28.toByte, -71.toByte, -73.toByte, -31.toByte, 109.toByte, 99.toByte, 24.toByte, -75.toByte, -11.toByte, 35.toByte, -91.toByte, -23.toByte, -67.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 1.toByte) {\n func11(\n Coll[Byte](\n -120.toByte, 48.toByte, 97.toByte, 44.toByte, 82.toByte, 53.toByte, 95.toByte, 111.toByte, 40.toByte, 13.toByte, 18.toByte, -105.toByte, -15.toByte, -97.toByte, 103.toByte, -80.toByte, 120.toByte, -55.toByte, -38.toByte, -89.toByte, -41.toByte, -80.toByte, 75.toByte, 69.toByte, -100.toByte, -111.toByte, -52.toByte, 100.toByte, 73.toByte, 87.toByte, -62.toByte, -128.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 3.toByte) {\n func11(\n Coll[Byte](\n 79.toByte, -40.toByte, -80.toByte, -42.toByte, -39.toByte, -126.toByte, 66.toByte, 114.toByte, 111.toByte, 87.toByte, -77.toByte, -33.toByte, -90.toByte, -122.toByte, 18.toByte, 103.toByte, -110.toByte, -72.toByte, -27.toByte, 5.toByte, 110.toByte, 29.toByte, 81.toByte, -74.toByte, -23.toByte, 13.toByte, 104.toByte, -128.toByte, -49.toByte, 45.toByte, -51.toByte, -59.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 4.toByte) {\n func11(\n Coll[Byte](\n -119.toByte, 46.toByte, 111.toByte, 71.toByte, -95.toByte, 13.toByte, 92.toByte, -112.toByte, -72.toByte, 122.toByte, -44.toByte, -122.toByte, 51.toByte, 85.toByte, -50.toByte, -83.toByte, 0.toByte, -61.toByte, -30.toByte, -104.toByte, 50.toByte, 23.toByte, -18.toByte, 21.toByte, 83.toByte, 50.toByte, 83.toByte, -51.toByte, -102.toByte, 96.toByte, 37.toByte, -62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 5.toByte) {\n func11(\n Coll[Byte](\n 58.toByte, 17.toByte, -107.toByte, 92.toByte, 71.toByte, 25.toByte, -27.toByte, -120.toByte, -68.toByte, -26.toByte, -89.toByte, 97.toByte, 29.toByte, 39.toByte, -67.toByte, 31.toByte, -33.toByte, -37.toByte, 87.toByte, 56.toByte, 92.toByte, -82.toByte, -30.toByte, 102.toByte, -40.toByte, 4.toByte, 12.toByte, -119.toByte, 79.toByte, 28.toByte, 46.toByte, 29.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) =>\n if (b15 == 6.toByte) {\n func11(\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n )\n )\n } else { false }\n }(b12), {(b15: Byte) => if (b15 == 7.toByte) { {(tuple17: (Coll[Byte], Box)) => if (i13 >= OUTPUTS.size) { false } else {(\n val box19 = OUTPUTS(i13)\n val l20 = box19.value\n val l21 = SELF.value\n val coll22 = box19.propositionBytes\n val coll23 = SELF.bytesWithoutRef\n val coll24 = SELF.propositionBytes\n val i25 = SELF.creationInfo._1\n val coll26 = box19.bytesWithoutRef\n val i27 = box19.creationInfo._1\n allOf(Coll[Boolean](l20 >= l21 - 2000000L, blake2b256(coll22) == func6(func2(tuple17._2).getMany(Coll[Coll[Byte]](tuple17._1), opt5.getOrElse(Coll[Byte]()))(0)), coll23.slice(func14(l21) + coll24.size + func14(i25.toLong), coll23.size) == coll26.slice(func14(l20) + coll22.size + func14(i27.toLong), coll26.size), anyOf(Coll[Boolean](i27 - i25 >= 504000, coll24 != coll22))))\n )} }((coll1, box4)) } else { false } }(b12)\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "9b7ea8b9abab7d2e60a5d92c6b1939af1a7c13985a942eed94e3dc5aaf37bc83",
"index": 0,
"amount": 1,
"name": "Sigmanauts Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00b6f6e34943cef98f5302c54cf13a81f7ab5cd6af2d7b14cf51d835e4e8288c",
"index": 1,
"amount": 19,
"name": "Sigmanaut",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107d08ffbcb8766242204040000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1753365832680,18,17,2,2,0,0]"
},
"R6": {
"serializedValue": "1d0501240110011001320132",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[18],[8],[8],[25],[25]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464014ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e16090007200029687428dfe182ab80eeecd21c35cfc754f2aabbddcbe32fca5fd738d4ad8e0304072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c640282b8aaa42a20189db872f2513ba4e253449f5dec9b6e689736e2c60d1f81ab0805072000699bd249866f9ad8a57c513ad202389d889430a05fe39e1e559980f0a3681a3302072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "14ae60fe493ff20576157242c831494a9215aff7ba64b45f597561fb65558c44",
"mainChain": true
},
{
"boxId": "48d374bef5b0cbd90cd2ffbdf552e3b7e282d6c456e286553c94c9b45fead1c5",
"transactionId": "ea11f8bf312357c56b24ff229d4eb6118b43a0631c065e537b404552d9af2157",
"blockId": "5e1749e7b7ef27f70610c46a5510a2a9afc0ec0daedeb19419e1d257527632b0",
"value": 1000000,
"index": 1,
"globalIndex": 48951214,
"creationHeight": 1570987,
"settlementHeight": 1570990,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\n1: Coll(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[Coll[Byte]]](0.toByte).get\n val coll2 = {(box2: Box) => box2.R4[AvlTree].get }(CONTEXT.dataInputs(0)).getMany(\n Coll[Coll[Byte]](\n Coll[Byte](\n 9.toByte, -126.toByte, 15.toByte, -53.toByte, -120.toByte, 113.toByte, -5.toByte, 69.toByte, 12.toByte, 62.toByte, 6.toByte, -73.toByte, -53.toByte, 94.toByte, 39.toByte, -80.toByte, 69.toByte, 80.toByte, -121.toByte, -93.toByte, 102.toByte, 98.toByte, 26.toByte, -99.toByte, -34.toByte, 117.toByte, -126.toByte, -96.toByte, 25.toByte, 17.toByte, 30.toByte, 62.toByte\n ), Coll[Byte](\n 61.toByte, -86.toByte, 102.toByte, -128.toByte, -114.toByte, 105.toByte, -62.toByte, 90.toByte, -23.toByte, 50.toByte, -35.toByte, 102.toByte, 97.toByte, 28.toByte, 95.toByte, 11.toByte, 60.toByte, -70.toByte, -54.toByte, -47.toByte, 18.toByte, 82.toByte, 3.toByte, -24.toByte, 125.toByte, -115.toByte, -60.toByte, -111.toByte, -122.toByte, 28.toByte, 113.toByte, -26.toByte\n )\n ), coll1(0)\n )\n val coll3 = coll1(9)\n val func4 = {(tuple4: (Coll[Box], Coll[Byte])) =>\n tuple4._1.filter({(box6: Box) => box6.tokens.exists({(tuple8: (Coll[Byte], Long)) => tuple8._1 == tuple4._2 }) })\n }\n val coll5 = placeholder[Coll[Byte]](1)\n val box6 = func4((OUTPUTS, coll5))(0)\n val box7 = func4((INPUTS, coll5))(0)\n val func8 = {(box8: Box) => box8.R4[Coll[AvlTree]].get(0) }\n val avlTree9 = func8(box7)\n val box10 = func4((INPUTS, {(opt10: Option[Coll[Byte]]) => opt10.get.slice(6, 38) }(coll2(1))))(0)\n val coll11 = avlTree9.get(coll3, coll1(2)).get\n val coll12 = longToByteArray(\n max({(box12: Box) => box12.R5[Coll[Long]].get(0) }(box10), {(coll12: Coll[Byte]) => byteArrayToLong(coll12.slice(0, 8)) }(coll11))\n ).append(coll11.slice(8, coll11.size))\n val func13 = {(box13: Box) => box13.R4[Coll[AvlTree]].get(1) }\n val avlTree14 = func13(box7)\n val opt15 = avlTree14.get(coll3, coll1(4))\n val bool16 = opt15.isDefined\n val opt17 = {(box17: Box) => box17.R6[AvlTree].get }(box10).get(coll3, coll1(1))\n val bool18 = opt17.isDefined\n val l19 = if (bool16) { byteArrayToLong(opt15.get.slice(0, 8)) } else { 0L }\n val l20 = if (bool18) { l19 } else { l19 + 1L }\n val l21 = if (bool16) { byteArrayToLong(opt15.get.slice(8, 16)) } else { 0L }\n val coll22 = coll1(8)\n val l23 = coll22.indices.slice(0, coll22.size / 8).map({(i23: Int) => byteArrayToLong(coll22.slice(i23 * 8, i23 + 1 * 8)) }).fold(\n 0L, {(tuple23: (Long, Long)) => tuple23._1 + tuple23._2 }\n )\n val l24 = if (bool18) {(\n val coll24 = opt17.get\n max(\n l21 - coll24.indices.slice(0, coll24.size / 8).map({(i25: Int) => byteArrayToLong(coll24.slice(i25 * 8, i25 + 1 * 8)) }).fold(\n 0L, {(tuple25: (Long, Long)) => tuple25._1 + tuple25._2 }\n ) + l23, 0L\n )\n )} else { l21 + l23 }\n val coll25 = longToByteArray(l20).append(longToByteArray(l24))\n val coll26 = coll1(5)\n val func27 = {(box27: Box) => box27.R5[Coll[Long]].get(0) }\n val func28 = {(box28: Box) => box28.R5[Coll[Long]].get(1) }\n val func29 = {(box29: Box) => box29.R5[Coll[Long]].get(2) }\n val func30 = {(box30: Box) => box30.R5[Coll[Long]].get(3) }\n val func31 = {(box31: Box) => box31.R5[Coll[Long]].get(4) }\n val func32 = {(box32: Box) =>\n val coll34 = box32.R5[Coll[Long]].get\n coll34.slice(5, coll34.size)\n }\n val func33 = {(box33: Box) => box33.R6[Coll[Coll[Long]]].get }\n val func34 = {(box34: Box) => box34.R7[Coll[(AvlTree, AvlTree)]].get }\n val func35 = {(box35: Box) => box35.R8[Coll[Long]].get }\n sigmaProp(\n allOf(\n Coll[Boolean](\n {(tuple36: (Coll[Box], Coll[Byte])) => tuple36._1.filter({(box38: Box) => blake2b256(box38.propositionBytes) == tuple36._2 }) }(\n (OUTPUTS, {(opt36: Option[Coll[Byte]]) => opt36.get.slice(1, 33) }(coll2(0)))\n )(0).value >= SELF.value, {(tuple36: (Coll[Box], Coll[Byte])) =>\n tuple36._1.exists({(box38: Box) => box38.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == tuple36._2 }) })\n }((OUTPUTS, coll3)), allOf(\n Coll[Boolean](\n box6.value == box7.value, box6.tokens == box7.tokens, func8(box6).digest == avlTree9.update(\n Coll[(Coll[Byte], Coll[Byte])]((coll3, coll12)), coll1(3)\n ).get.digest, func13(box6).digest == if (bool16) { avlTree14.update(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get } else {\n avlTree14.insert(Coll[(Coll[Byte], Coll[Byte])]((coll3, coll25)), coll26).get\n }.digest, func27(box6) == func27(box7), func28(box6) == func28(box7), func29(box6) == func29(box7), func30(box6) == func30(\n box7\n ) + l20 - l19, func31(box6) == func31(box7) + l24 - l21, func32(box6) == func32(box7), func33(box6) == func33(box7), func34(box6) == func34(\n box7\n ), func35(box6) == func35(box7)\n )\n ), coll1(6) == coll12, coll1(7) == coll25\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "14ae60fe493ff20576157242c831494a9215aff7ba64b45f597561fb65558c44",
"mainChain": true
},
{
"boxId": "87801d816505c59ae3190c246616bab3ceda16d0fe33344b3a5c4e5e9fa5ac5f",
"transactionId": "ea11f8bf312357c56b24ff229d4eb6118b43a0631c065e537b404552d9af2157",
"blockId": "5e1749e7b7ef27f70610c46a5510a2a9afc0ec0daedeb19419e1d257527632b0",
"value": 5000000,
"index": 2,
"globalIndex": 48951215,
"creationHeight": 1570987,
"settlementHeight": 1570990,
"ergoTree": "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",
"ergoTreeConstants": "0: Coll(48,-116,21,-33,-8,-92,-81,-69,-46,-102,-104,-5,-53,46,28,-114,-1,101,42,-60,70,-120,67,17,-32,76,-120,-14,76,67,-54,113)\n1: Coll(27,75,-117,120,-97,-35,74,52,-59,-15,-49,115,-76,-39,-102,92,-84,-72,-52,-70,117,38,95,110,-33,73,80,-119,59,22,47,7)\n2: Coll(31,-42,-32,50,-24,71,108,74,-91,76,24,-63,-93,8,-36,-24,57,64,-24,-12,-94,-113,87,100,64,81,62,-41,50,106,-44,-119)\n3: Coll(-101,126,-88,-71,-85,-85,125,46,96,-91,-39,44,107,25,57,-81,26,124,19,-104,90,-108,46,-19,-108,-29,-36,90,-81,55,-68,-125)",
"ergoTreeScript": "{\n val func1 = {(box1: Box) => box1.tokens(0) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.exists({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val preHeader3 = CONTEXT.preHeader\n val b4 = getVar[Byte](0.toByte).get\n val func5 = {(box5: Box) =>\n val coll7 = box5.R5[Coll[Long]].get\n coll7.slice(2, coll7.size)\n }\n val opt6 = getVar[(Int, Long)](10.toByte)\n val tuple7 = (-2, 0L)\n val tuple8 = tuple7\n val tuple9 = opt6.getOrElse(tuple8)\n val i10 = tuple9._1\n val l11 = tuple9._2\n val func12 = {(tuple12: (Coll[Box], Coll[Byte])) => tuple12._1.filter({(box14: Box) => blake2b256(box14.propositionBytes) == tuple12._2 }) }\n val func13 = {(box13: Box) => box13.R4[Coll[Int]].get(0) }\n val func14 = {(box14: Box) => box14.R5[Coll[Long]].get(1) }\n val func15 = {(box15: Box) => box15.R6[AvlTree].get }\n val func16 = {(box16: Box) => box16.R4[Coll[Int]].get(1) }\n val coll17 = placeholder[Coll[Byte]](3)\n val func18 = {(tuple18: (Coll[Box], Coll[Byte])) =>\n tuple18._1.filter({(box20: Box) => box20.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == tuple18._2 }) })\n }\n val func19 = {(box19: Box) => box19.R4[AvlTree].get }\n val func20 = {(tuple20: (Option[Coll[Byte]], (Long, (Long, Long)))) =>\n val tuple22 = tuple20._2\n val l23 = tuple22._1\n val tuple24 = tuple22._2\n val l25 = tuple24._1\n val l26 = tuple24._2\n tuple20._1.map({(coll27: Coll[Byte]) => if (coll27.size == 9) {(\n val l29 = byteArrayToLong(coll27.slice(1, 9))\n if (l29 < l23) { l23 } else { if (l29 > l25) { l25 } else { l29 } }\n )} else { l26 } }).getOrElse(l26)\n }\n val func21 = {(box21: Box) => box21.R5[Coll[Long]].get(0) }\n sigmaProp(\n anyOf(\n Coll[Boolean](\n {(b22: Byte) =>\n if (b22 == 12.toByte) {\n {(coll24: Coll[Coll[Byte]]) =>\n allOf(\n Coll[Boolean](\n preHeader3.height - SELF.creationInfo._1 > 788400, coll24.forall({(coll26: Coll[Byte]) => !func2((OUTPUTS, coll26)) }), INPUTS.size == 1\n )\n )\n }(Coll[Coll[Byte]](func1(SELF)._1))\n } else { false }\n }(b4), {(b22: Byte) => if (b22 == 13.toByte) {(\n val coll24 = func5(SELF)\n val coll25 = SELF.propositionBytes\n val box26 = func12((OUTPUTS, blake2b256(coll25)))(0)\n val l27 = box26.value\n val l28 = func14(SELF)\n val coll29 = CONTEXT.dataInputs\n val coll30 = Coll[Byte]()\n val coll31 = func19(func18((coll29, placeholder[Coll[Byte]](0)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-10.toByte, -1.toByte, -117.toByte, 114.toByte, 16.toByte, 1.toByte, 85.toByte, 69.toByte, -44.toByte, -77.toByte, -84.toByte, 95.toByte, -58.toByte, 12.toByte, -112.toByte, -128.toByte, -110.toByte, -48.toByte, 53.toByte, -95.toByte, -95.toByte, 97.toByte, 85.toByte, -64.toByte, 41.toByte, -24.toByte, -43.toByte, 17.toByte, 98.toByte, 124.toByte, 122.toByte, 44.toByte), Coll[Byte](-81.toByte, 120.toByte, 91.toByte, 10.toByte, -35.toByte, -128.toByte, 92.toByte, 92.toByte, 49.toByte, -15.toByte, -52.toByte, 58.toByte, 62.toByte, -106.toByte, -56.toByte, -112.toByte, 8.toByte, -3.toByte, 113.toByte, 39.toByte, 50.toByte, 1.toByte, 7.toByte, -93.toByte, 120.toByte, 75.toByte, 127.toByte, 73.toByte, -23.toByte, 86.toByte, 72.toByte, 66.toByte)), getVar[Coll[Byte]](1.toByte).getOrElse(coll30))\n val tuple32 = (1L, (999L, 500L))\n val opt33 = opt6\n val tuple34 = tuple7\n val tuple35 = tuple8\n val tuple36 = tuple9\n val coll37 = func19(func18((coll29, placeholder[Coll[Byte]](1)))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-11.toByte, -111.toByte, -114.toByte, -76.toByte, -80.toByte, 40.toByte, 60.toByte, 102.toByte, -101.toByte, -35.toByte, -118.toByte, 25.toByte, 86.toByte, 64.toByte, 118.toByte, 108.toByte, 25.toByte, -28.toByte, 10.toByte, 105.toByte, 58.toByte, 102.toByte, -105.toByte, -73.toByte, 117.toByte, -80.toByte, -114.toByte, 9.toByte, 5.toByte, 37.toByte, 35.toByte, -44.toByte), Coll[Byte](118.toByte, 124.toByte, -86.toByte, -128.toByte, -71.toByte, -114.toByte, 73.toByte, 106.toByte, -40.toByte, -87.toByte, -10.toByte, -119.toByte, -60.toByte, 65.toByte, 10.toByte, -28.toByte, 83.toByte, 50.toByte, 127.toByte, 15.toByte, -107.toByte, -23.toByte, 80.toByte, -124.toByte, -64.toByte, -82.toByte, 32.toByte, 99.toByte, 80.toByte, 121.toByte, 59.toByte, 119.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll30))\n val box38 = func12((OUTPUTS, {(opt38: Option[Coll[Byte]]) => opt38.get.slice(1, 33) }(coll37(1))))(0)\n allOf(Coll[Boolean]((coll24.indices.forall({(i39: Int) => if (i39 == i10) { coll24(i39) == l11 } else { coll24(i39) <= l11 } }) && (coll24.size > i10)) && (i10 >= 0), allOf(Coll[Boolean](box26.propositionBytes == coll25, l27 >= SELF.value - 3000000L, l27 >= 2000000L, func1(box26) == func1(SELF), func13(box26) == func13(SELF), func14(box26) == l28, func5(box26) == coll24, func15(box26) == func15(SELF), func16(box26) == if ((l28 >= {(box39: Box) => box39.R5[Coll[Long]].get(1) }(func18((coll29, coll17))(0)) * func20((coll31(0), tuple32)) / 1000L) && \n val l39 = l11\n l39 >= l28 * func20((coll31(1), tuple32)) / 1000L\n ) { i10 } else { -2 })), preHeader3.timestamp > func21(SELF), allOf(Coll[Boolean](box38.value >= 1000000L, {(tuple39: (Coll[Box], Coll[Byte])) => tuple39._1.flatMap({(box41: Box) => box41.tokens }).fold(0L, {(tuple41: (Long, (Coll[Byte], Long))) =>\n val tuple43 = tuple41._2\n tuple41._1 + if (tuple43._1 == tuple39._2) { tuple43._2 } else { 0L }\n }) }((Coll[Box](box38), placeholder[Coll[Byte]](2))) >= min(SELF.tokens(1)._2, byteArrayToLong(coll37(0).get.slice(1, 9))))), func16(SELF) == -1))\n )} else { false } }(b4), {(b22: Byte) => if (b22 == 6.toByte) {(\n val coll24 = getVar[Coll[Coll[Byte]]](1.toByte).get\n val coll25 = coll24(4)\n val coll26 = coll24(3)\n val coll27 = coll26.indices.slice(0, coll26.size / 8).map({(i27: Int) => byteArrayToLong(coll26.slice(i27 * 8, i27 + 1 * 8)) })\n val l28 = coll27.fold(0L, {(tuple28: (Long, Long)) => tuple28._1 + tuple28._2 })\n val coll29 = SELF.propositionBytes\n val box30 = func12((OUTPUTS, blake2b256(coll29)))(0)\n val l31 = func21(SELF)\n val avlTree32 = func15(SELF)\n val opt33 = avlTree32.get(coll25, coll24(0))\n val bool34 = opt33.isDefined\n val coll35 = coll24(1)\n val coll36 = func5(SELF)\n val coll37 = func5(box30)\n allOf(Coll[Boolean](byteArrayToLong({(box38: Box) => box38.R4[Coll[AvlTree]].get(0) }(func18((INPUTS, coll17))(0)).get(coll25, coll24(2)).get.slice(8, 16)) >= l28, box30.propositionBytes == coll29, box30.value >= SELF.value, box30.tokens == SELF.tokens, func13(box30) == func13(SELF), func16(box30) == func16(SELF), func21(box30) == l31, func15(box30).digest == if (bool34) { avlTree32.update(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get } else { avlTree32.insert(Coll[(Coll[Byte], Coll[Byte])]((coll25, coll26)), coll35).get }.digest, preHeader3.timestamp < l31, if (bool34) {(\n val coll38 = opt33.get\n val coll39 = coll38.indices.slice(0, coll38.size / 8).map({(i39: Int) => byteArrayToLong(coll38.slice(i39 * 8, i39 + 1 * 8)) })\n allOf(Coll[Boolean](func14(box30) == func14(SELF) - coll39.fold(0L, {(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 }) + l28, coll37 == coll36.zip(coll39.zip(coll27).map({(tuple40: (Long, Long)) => tuple40._2 - tuple40._1 })).map({(tuple40: (Long, Long)) => tuple40._1 + tuple40._2 })))\n )} else { allOf(Coll[Boolean](func14(box30) == func14(SELF) + l28, coll37 == coll36.zip(coll27).map({(tuple38: (Long, Long)) => tuple38._1 + tuple38._2 }))) }, func2((INPUTS, coll25)), coll37 != coll36))\n )} else { false } }(b4)\n )\n )\n )\n}",
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"assets": [
{
"tokenId": "38e5ce513bf85098e8f476a24287fccbf273c9f19d522ee07990e2df721e3bbc",
"index": 0,
"amount": 1,
"name": "Sigmanauts Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 5000000,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "10021e01",
"sigmaType": "Coll[SInt]",
"renderedValue": "[15,-1]"
},
"R5": {
"serializedValue": "1104b092a5f98766040004",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1753413362840,2,0,2]"
},
"R6": {
"serializedValue": "6436e84bd791287472958bd7e7d83ac31e8db081731e3b346e1bb68939eaee049a02072000",
"sigmaType": null,
"renderedValue": null
},
"R7": {
"serializedValue": "0e305369676d616c6f6b202d2037306b204d657720666f72203268722773206f66204b757368746920534320726576696577",
"sigmaType": "Coll[SByte]",
"renderedValue": "5369676d616c6f6b202d2037306b204d657720666f72203268722773206f66204b757368746920534320726576696577"
}
},
"spentTransactionId": "14ae60fe493ff20576157242c831494a9215aff7ba64b45f597561fb65558c44",
"mainChain": true
},
{
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