Transaction
ID: 765100bb23...961d
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
1.15 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
1.04 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.15 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00015 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00485 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
1.04 ERG
Tokens:
Loading assets...
Transaction Details
Confirmations: 260,083
Total coins transferred: 2.2 ERG
Fees: 0.00485 ERG
Fees per byte: 0.000000207 ERG
Raw Transaction Data
{
"id": "765100bb23c733aefb95ef209e842158be3ebbbe4dbc7461ea2d0ac8f085961d",
"blockId": "fdb1f876dd4d56a0b45c50952a0c8ab6321f65e7aab22019abdc8595729622f0",
"inclusionHeight": 1498351,
"timestamp": 1744027737267,
"index": 2,
"globalIndex": 8806865,
"numConfirmations": 260083,
"inputs": [
{
"boxId": "2ad4614cb44871fc9f4639a10702bd519842e846a158a0b3786c073c540a58be",
"value": 1153378059,
"index": 0,
"spendingProof": null,
"outputBlockId": "fdb1f876dd4d56a0b45c50952a0c8ab6321f65e7aab22019abdc8595729622f0",
"outputTransactionId": "0af0555d3733849c213f8b880375909a5aa00dc87fcf50ae0a788721ba42f433",
"outputIndex": 0,
"outputGlobalIndex": 47225607,
"outputCreatedAt": 1498349,
"outputSettledAt": 1498351,
"ergoTree": "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",
"ergoTreeConstants": "0: 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)",
"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": "233536261ad8920b85644d30fff8e68c470470138950317ad520b300e8c1e573",
"index": 0,
"amount": 1,
"name": "Paideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 692622596048,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "110780d8f79dc565d2e9eeb7a8285c0000ccf541acc21e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1744459200000,692622056041,46,0,0,540006,250006]"
},
"R6": {
"serializedValue": "1d0501d2e9eeb7a8280100010001140114",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[692622056041],[0],[0],[10],[10]]"
},
"R8": {
"serializedValue": "1102ccf541acc21e",
"sigmaType": "Coll[SLong]",
"renderedValue": "[540006,250006]"
},
"R7": {
"serializedValue": "0c3c6464013c69d7c6f0038e7ea6bb29471afeb3e38b81ba39e15e3eacf6281d15dd2337a1070720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c64023c69d7c6f0038e7ea6bb29471afeb3e38b81ba39e15e3eacf6281d15dd2337a1070720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "899d22f246aaedab58f2edba03329d6c453b74b32d457ef0c05e6a098f9fecc4",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "5fe88c2bb68af9943215a3b5ef49a74cdd3b78ee3fa5153c92a1cd167d19245a",
"outputTransactionId": "e041067f11fad4f3116235558e07f03a347d8b1ef7f2403510d31d7226384783",
"outputIndex": 1,
"outputGlobalIndex": 47152078,
"outputCreatedAt": 1494752,
"outputSettledAt": 1494754,
"ergoTree": "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",
"ergoTreeConstants": "0: 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)\n1: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll2 = coll1.map({(tuple2: (Coll[Byte], Coll[Byte])) => tuple2._1 })\n val coll3 = coll2.indices\n val func4 = {(box4: Box) => box4.R4[Coll[AvlTree]].get(0) }\n val func5 = {(tuple5: (Coll[Box], Coll[Byte])) =>\n tuple5._1.filter({(box7: Box) => box7.tokens.exists({(tuple9: (Coll[Byte], Long)) => tuple9._1 == tuple5._2 }) })\n }\n val coll6 = placeholder[Coll[Byte]](1)\n val box7 = func5((INPUTS, coll6))(0)\n val avlTree8 = func4(box7)\n val coll9 = avlTree8.getMany(coll2, getVar[Coll[Byte]](2.toByte).get)\n val func10 = {(coll10: Coll[Byte]) => byteArrayToLong(coll10.slice(8, 16)) }\n val func11 = {(coll11: Coll[Byte]) => coll11.slice(0, coll11.size - 16 / 8).indices.map({(i13: Int) =>\n val i15 = i13 * 8\n byteArrayToLong(coll11.slice(i15 + 16, i15 + 8 + 16))\n }) }\n val func12 = {(box12: Box) =>\n val coll14 = box12.R5[Coll[Long]].get\n coll14.slice(5, coll14.size)\n }\n val coll13 = func12(box7)\n val coll14 = coll9.map({(opt14: Option[Coll[Byte]]) => if (opt14.isDefined) {(\n val coll16 = opt14.get\n Coll[Long](func10(coll16)).append(func11(coll16))\n )} else { coll13.map({(l16: Long) => -1L }) } })\n val func15 = {(box15: Box) => box15.R7[Coll[(AvlTree, AvlTree)]].get }\n val coll16 = func15(box7)\n val tuple17 = coll16(0)\n val avlTree18 = tuple17._1\n val coll19 = avlTree18.getMany(coll2, getVar[Coll[Byte]](3.toByte).get).map({(opt19: Option[Coll[Byte]]) => func10(opt19.get) })\n val func20 = {(box20: Box) => box20.R6[Coll[Coll[Long]]].get(0) }\n val l21 = {(box21: Box) => box21.R6[Coll[Coll[Long]]].get(1) }(box7)(0)\n val b22 = if (l21 > 0L) { {(box22: Box) => box22.R6[Coll[Coll[Long]]].get(3) }(box7)(0).toByte } else { 0.toByte }\n val l23 = {(box23: Box) => box23.R6[Coll[Coll[Long]]].get(2) }(box7)(0)\n val b24 = if (l23 > 0L) { {(box24: Box) => box24.R6[Coll[Coll[Long]]].get(4) }(box7)(0).toByte } else { 0.toByte }\n val b25 = b22 + b24\n val b26 = if (b25.toInt > 0) { max(100.toByte - b25, 0.toByte) } else { 100.toByte }\n val bi27 = 0.toBigInt\n val bi28 = 0.toBigInt\n val b29 = b25 + b26\n val avlTree30 = tuple17._2\n val coll31 = avlTree30.getMany(coll2, getVar[Coll[Byte]](5.toByte).get).map({(opt31: Option[Coll[Byte]]) => if (opt31.isDefined) {(\n val coll33 = opt31.get\n (byteArrayToLong(coll33.slice(0, 8)), byteArrayToLong(coll33.slice(8, 16)))\n )} else { (0L, 0L) } })\n val func32 = {(box32: Box) => box32.R8[Coll[Long]].get }\n val coll33 = func32(box7)\n val coll34 = coll1.map({(tuple34: (Coll[Byte], Coll[Byte])) =>\n val coll36 = tuple34._2\n Coll[Long](func10(coll36)).append(func11(coll36))\n })\n val func35 = {(coll35: Coll[Byte]) => byteArrayToLong(coll35.slice(0, 8)) }\n val coll36 = coll9.map({(opt36: Option[Coll[Byte]]) => if (opt36.isDefined) { func35(opt36.get) } else { -1L } })\n val coll37 = coll1.map({(tuple37: (Coll[Byte], Coll[Byte])) => func35(tuple37._2) })\n val tuple38 = (func32(box7).map({(l38: Long) => 0.toBigInt }), true)\n val func39 = {(box39: Box) => box39.R5[Coll[Long]].get(1) }\n val coll40 = coll33.indices.map({(i40: Int) => coll3.map({(i42: Int) =>\n val coll44 = coll14(i42)\n if (coll44(0) >= 0L) {(\n val coll45 = func32(box7).map({(l45: Long) =>\n val bi47 = l45.toBigInt\n coll19(i42).toBigInt * bi47 / func20(box7)(0).toBigInt * b26.toBigInt + if (b22.toInt > 0) { coll31(i42)._1.toBigInt * bi47 / l21.toBigInt * b22.toBigInt } else { bi27 } + if (b24.toInt > 0) { coll31(i42)._2.toBigInt * bi47 / l23.toBigInt * b24.toBigInt } else { bi28 } / b29.toBigInt\n })\n (coll45, (coll44.zip(coll45).map({(tuple46: (Long, BigInt)) => tuple46._1.toBigInt + tuple46._2 }) == coll34(i42).map({(l46: Long) => l46.toBigInt })) && (coll36(i42) == coll37(i42)))\n )} else { tuple38 }\n }).fold(0.toBigInt, {(tuple42: (BigInt, (Coll[BigInt], Boolean))) => tuple42._1 + tuple42._2._1(i40) }) })\n val box41 = func5((OUTPUTS, coll6))(0)\n val coll42 = func15(box41)\n val tuple43 = coll42(0)\n val coll44 = tuple43._1.digest\n val coll45 = {(opt45: Option[Coll[Byte]]) => opt45.get.slice(1, 33) }(\n {(box45: Box) => box45.R4[AvlTree].get }(func5((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n val box46 = {(tuple46: (Coll[Box], Coll[Byte])) => tuple46._1.filter({(box48: Box) => blake2b256(box48.propositionBytes) == tuple46._2 }) }(\n (OUTPUTS, coll45)\n )(0)\n val func47 = {(box47: Box) => box47.R4[Coll[AvlTree]].get(1) }\n val func48 = {(box48: Box) => box48.R5[Coll[Long]].get(0) }\n val func49 = {(box49: Box) => box49.R5[Coll[Long]].get(2) }\n val func50 = {(box50: Box) => box50.R5[Coll[Long]].get(3) }\n val func51 = {(box51: Box) => box51.R5[Coll[Long]].get(4) }\n val func52 = {(box52: Box) => box52.R6[Coll[Coll[Long]]].get }\n sigmaProp(allOf(Coll[Boolean](allOf(coll3.map({(i53: Int) =>\n val coll55 = coll14(i53)\n if (coll55(0) >= 0L) {(\n val coll56 = coll33.map({(l56: Long) =>\n val bi58 = l56.toBigInt\n coll19(i53).toBigInt * bi58 / func20(box7)(0).toBigInt * b26.toBigInt + if (b22.toInt > 0) { coll31(i53)._1.toBigInt * bi58 / l21.toBigInt * b22.toBigInt } else { bi27 } + if (b24.toInt > 0) { coll31(i53)._2.toBigInt * bi58 / l23.toBigInt * b24.toBigInt } else { bi28 } / b29.toBigInt\n })\n (coll56, (coll55.zip(coll56).map({(tuple57: (Long, BigInt)) => tuple57._1.toBigInt + tuple57._2 }) == coll34(i53).map({(l57: Long) => l57.toBigInt })) && (coll36(i53) == coll37(i53)))\n )} else { tuple38 }._2\n })), func39(box7).toBigInt + coll40(0) == func39(box41).toBigInt, avlTree18.remove(coll2, getVar[Coll[Byte]](4.toByte).get).get.digest == coll44, avlTree8.update(coll1.filter({(tuple53: (Coll[Byte], Coll[Byte])) => func10(tuple53._2) > 0L }), getVar[Coll[Byte]](6.toByte).get).get.digest == func4(box41).digest, allOf(Coll[Boolean](blake2b256(box46.propositionBytes) == coll45, box46.value >= SELF.value)), allOf(Coll[Boolean](box41.value == box7.value, box41.tokens == box7.tokens, func47(box41).digest == func47(box7).digest, tuple43._2 == avlTree30, coll42.slice(1, coll42.size) == coll16.slice(1, coll16.size), func48(box41) == func48(box7), func49(box41) == func49(box7), func50(box41) == func50(box7), func51(box41) == func51(box7), func52(box41) == func52(box7), func32(box41) == coll33)), (coll1.size >= 10) || (coll44 == Coll[Byte](78.toByte, -58.toByte, 31.toByte, 72.toByte, 91.toByte, -104.toByte, -21.toByte, -121.toByte, 21.toByte, 63.toByte, 124.toByte, 87.toByte, -37.toByte, 79.toByte, 94.toByte, -51.toByte, 117.toByte, 85.toByte, 111.toByte, -35.toByte, -68.toByte, 64.toByte, 59.toByte, 65.toByte, -84.toByte, -8.toByte, 68.toByte, 31.toByte, -34.toByte, -114.toByte, 22.toByte, 9.toByte, 0.toByte)), coll13.indices.forall({(i53: Int) => func12(box41)(i53).toBigInt == coll13(i53).toBigInt - coll40(i53) }))))\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "fa37d43f32c26f0db42a886ff0f8403e53c12c0e3d6284638087d03a6bb490bc",
"value": 1041750000,
"index": 2,
"spendingProof": null,
"outputBlockId": "fdb1f876dd4d56a0b45c50952a0c8ab6321f65e7aab22019abdc8595729622f0",
"outputTransactionId": "0af0555d3733849c213f8b880375909a5aa00dc87fcf50ae0a788721ba42f433",
"outputIndex": 5,
"outputGlobalIndex": 47225612,
"outputCreatedAt": 1498349,
"outputSettledAt": 1498351,
"ergoTree": "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",
"ergoTreeConstants": "0: 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)\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(0,6,83,-85,14,127,-72,-101,-6,34,29,117,-67,37,-82,-40,-71,-114,11,-84,102,-95,58,-94,41,-54,-11,-123,81,40,-45,58,35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-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), Coll[Byte](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), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.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), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "guXrqVUozVvKJDd35QAC9e9D5okdcBLu4mrbTPU1my2vNZbTGemsYHeE2MWcL7W9dSvAqXikSgwus2rM6BjC1jvEBMoewT3siatBE2qZZp7NUjGytM3wr62C6NhvQMoewg2Kb9AERUuWca6BZb6WS2CiJE55K2QMn5ZTKxPq75uRLkQkaas31rYNjRvRuSVdCw3uoLHhUmpzLzVmaunHZMdJF7YaHZHb6A7ypBj8LDkQtbsS5yXE9YjhJZda4xdFXSNLQqtxTpCj8iMkSM3vemo4C2mdPuufGo8cWBtcVhe44aZeYE78KisySXFwtb6D5hBoNoUJBmEb37YL9kuCgZTinht3dUzVW24e3h82dqammfPYwEWJtpVimX3AFLcLJGvX4XhvCLKECZDaAUArCjruRtBw6eCrMWMhBYXBgvDFAmprzyn1U1SGgxWrFVyVShmfzC8qBKySaT17UCNf9hHt43NQYRDo8JQSYykqtzS4AqSV6ZDjTMRHnQQCCGafMT78iV3xPGrL9Fmpc5V5waH5rE7sbvQaqivXmVitTtCkQZJKaz8hrMUARkbJvza7NtuQfLgoUGZh6DyFGJ5VbTiVqhUadjX2EtNHRZnVFj2r9AXi3xYJdjzuQfUod3KZQ9dwEs1BcP5E8kUe2wF8o2Hrfi1LVAtXhnu4acNeyW8bMmVQH4RxfpgbLoe7YiqR7XHCHm3UMbQ8nSgGrwTpjTtFb4GTAgGXAjbsJpfSm5HyRr9omuKRZoy1v35KPnHHMWSa1794rh9NW4Yt8rdZijzvzaMypVTNNgcY22RpzwWRhP3CqHEtA2aqVUxrvVDGZgmLjGjGRucCyTsMNFJYHXpKvgq1su4rgeYk8ucxJPpCYCFdA4wA2rdt7DNSGEbykcd9wUvyqx1pAGc7BAkwLwmVJia1xWY685VwGzrA9AwHGBqsmRff9BmhoLKnsc6QLseGpyoNAa3iqfqzK3v86awDkBYEzc19MLdxyjokXxSi7bbAShqfMUEY4cF36BWDFmNG8SQszXFWZU2rz6WAxjQz2PGQuVLN4A6i6fQv7jUdiWzKH3H1cdNMdpoXYrHDriChAXY9r1XMpe8ySUPNHvVKr76K37C1RdNfYVPq4vmYacQNMfdJx4HQJppygNZUZAQB1rQqCVt2ASEoacrrhGVBa1ZHDJ3h6KYM16TE6KTWaQU2wCbgxobHeyvCLB8NhSWYU3QKQuNb8YQcm2mcoQycRWqcfrQhnwoovWM8veeFjT9aUTnAX5RKNpRi9qxgM8AxtAoHzMgSujeyKddVKKutZ3ZNQ21eBu3kfSm5AeiPUZnDFsoZAVZydhThofFvkgWiMHaDqgRz9sPw4pQuuix5Q4VaqM1C3vBuMxh8UHgBBbrvYFfaRo3vyrCXFA52bUqwKW9R4dYMQ3oQxdEr53UtbvVjmSNbsd7nYWNn3itfS7nvsYCWhFXfP4djkXMspsy8V23bYtM4Awrtc5HsTr1PAGi2RFnmqHnjvMFnwbFygrEhXtmWmzfwAE2jAmsqpAGMZxD54Ra9c6dTtxp436XDErDgYaerW1GqyMPikWBeLGwxn8bNzKKz7EmhbRzzzHcQwDXJDVnWNZBzVfNDsdbnLUB5KL2JtHqq2NaD8VjFV6UfVi5UkpR9n3vnhjLeqPdA4aaZTHchmQa1sJ4JZCg1MA9jfq7vaYigo6CS1nQM2Rw7HzXzxY28S1SF6E1zxJHkGhwvPCFt3Hrvgb2sMgSEs28dV5xSuVhgqEUk1kvn6iYcpiZDioFxLUxK8Ap72typxEGwSWMKCjfJ2TjFwv8A8wCsAwAP7GSgjQjXnaXZu7RPR73yDrsJZkJ751uXQ3huU75HJk47mUTm1uZBYGHh1vBkQksQZ68HZo1pUphvnKTSXSyCL5qZdybpDVmGGPWTeqivQjSkSaLFAjmSqZYmJQNjgmqm8a5MYg6Rg1QKJ5Q6P1931KpxUjPqvEU8rASthoBeKLXgkPLfXK3GDZf2rBstPavJNuhuKeS5ptoNLMFYHQnpUS8ywTa96iQogy99W6nsM73qEdzjpARhr4Vf5cqDFPuADw1yC4WbCixDJHkP3LC22hzttfJnPfnvm4szVvPs3AcpTk1sLUAunmFbKQ766xQWiWfuXLcCxZH7iqne6WphY5bjF9zpmGD199cP7wUyyNsXaJnNzp6bku6Q2ojB3R4YqDiSfa5hNw5tt4WfNYkj3vjyxPK2of944dZnoecYuQ3GfiTyoNggRuv6ushr349cFaayUbZ1ri9JyjaUUNFBseNNgGNGDxb2Nr7SddnG9PWyvnG9bFt7ddjbhrxSsXYW1jiHXW3WSDy2bkB7GbZ443Yqe7kUPUhzfPPwiPEif3cf6qYdMvR6bJp8t4jzicd3oikUnbwbW5kYN4s75KdWcBEGaCWjakMHmRFKijLmvQBT2cDEi83BWTkdjFkwdg2L3ax7Pgk15qxFQmQA5W4nvLBBcUL3b3iQNxDtdDcQmKQnnrTs4ApE4mEBVsF3nxXdUTcC5Vib1MoY1kxPV34AtPB36zKHj7zAyoqmMtF35rvB1FtRBPekNnsjzdB1S3atuUTWbYWbzcdMqBxGh6nnmQFRw4zpekXyyoBmcmvCp4szqKKdoDirgDkFGEdq87sxfRfaWze5VSQTtnadQ5ndyXMX3AcxvneHVFf85y33Kw5gi9jkvFJV2rauEfVjNr8PJxcEuQPD9ftwFe1upjbkL5NywpYrAo97DtCR6mMi9bWJWRam6W4GsEnLTsuV1YUKMJeDpVSmEjBgp22onmoWituc4TiZucyDJQNsTWsXT9EjsP7MKmH5hP69vypj7WxfGgjdgjziD9cTaiNHkpkQKnBB8KhGEhaX7dHMCXU7Cg4Fs7ZDgacSnLD4An9nm82LFkftNJ9y6HwnDpPxvm9fL2f12uVjtabRMRcxxSSfNsenvcHDRPYWNhAE8DdtX1VNfjdvqE9sCJPxqfwYNUTbxmKbpmgvtAn1TSMFVU63cLGn5o54S3fFmCbs7gq77ZYy9G7aB49BHNUDTWTxiaWw4UpEHhrRot3og84BV7r7XBEekRCf7dTy2DkRzyVkFaYfZ7Zzcf38QJ8CWbNRUws5UmYWEu8vWvmgmNbweKHiVAmQdwYbiDoL7DRcTt1gTy2J3q5YCorPauYhbdJfWizrHNxtiqhgj31FgPNBmrksBSgciHwsiaMJq51beLGd249XUZDWRTYnJp1ghRtYTMQ1",
"assets": [
{
"tokenId": "879c71d7d9ad213024962824e7f6f225b282dfb818326b46e80e155a11a90544",
"index": 0,
"amount": 1969177582139,
"name": "ERG_Paideia_LP",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 1,
"amount": 337913523622,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
},
{
"tokenId": "4fdf8ed79f9a85eade4bd580b12d557c3894362a057da33d28b290ad3446a53e",
"index": 2,
"amount": 63810161,
"name": "Paideia_Sigusd_LP",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "0cca9016769f0abbd704bc14e422ba3dd4ec10e00ecd120f36846bb859a16ca0",
"value": 1000000000,
"index": 0,
"outputBlockId": "4c8dc2ed20f330c612719316b3494a4d66de5f0668ecbc6283a0e3bde4207893",
"outputTransactionId": "66b181ec5489107a9bf3c7b13563acee0d31cd0e79d9b837e2a489467dde6f9a",
"outputIndex": 0,
"ergoTree": "10010e20000653ab0e7fb89bfa221d75bd25aed8b98e0bac66a13aa229caf5855128d33ad808d601d901013c0c630eb58c720101d9010363aedb63087203d901054d0e938c7205018c720102d602d9010263e4c672020464d60383200202a90255028e0241028602cb02d502aa0257022302a8025202d402c102dc0265027d029e02810243028202ff0288028d025a028a02ec0252021502310230021dd604e3010ed605d9010532b4e4720504020442d606e4e30002d607dc0c1aa402a70400d608d9010805958f72080580020402958f7208058080020404958f720805808080020406958f72080580808080020408958f720805808080808002040a958f72080580808080808002040c958f7208058080808080808002040e958f72080580808080808080800204100412d197830201dad9010902959372090208d802d60bb2da7201018602a5dad9010b638cb2db6308720b0400000101a7040000d60cdc640bda720201720b0283020e7203cbb3831c020269026d022e0270026102690264026502690261022e0263026f026e027402720261026302740273022e0261026302740269026f026e022ec2b2da7201018602a47300040000e472049683040193db6308a7db6308720b90c1a7c1720b93cbc2720bda720501b2720c040000e6b2720c0402000100017206ed9372060207dad901093c0e6395927207b1a50100d809d60bb2a5720700d60cc1720bd60dc1a7d60ec2720bd60fc4a7d610c2a7d6118cc7a701d612c4720bd6138cc7720b019683040192720c99720d058092f40193cb720eda720501b2dc640bda7202018c7209020283010e8c720901e5720483000204000093b4720f9a9ada720801720db17210da7208017e721105b1720fb472129a9ada720801720cb1720eda7208017e721305b17212978302019299721372110480c33d947210720e0186027203a7",
"address": "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",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64a1db138991f9e426fe847dbae52abd772f8681deb022a8a3d0cad0ef86436f7107072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "0a0712ac4441e3edbff97e4aba23b73d7ec28d6e49e1ee05193dd6e49f35b341",
"transactionId": "765100bb23c733aefb95ef209e842158be3ebbbe4dbc7461ea2d0ac8f085961d",
"blockId": "fdb1f876dd4d56a0b45c50952a0c8ab6321f65e7aab22019abdc8595729622f0",
"value": 1153378059,
"index": 0,
"globalIndex": 47225613,
"creationHeight": 1498349,
"settlementHeight": 1498351,
"ergoTree": "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",
"ergoTreeConstants": "0: 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)",
"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}",
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"ergoTreeConstants": "0: 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)\n1: Coll(35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val coll1 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll2 = coll1.map({(tuple2: (Coll[Byte], Coll[Byte])) => tuple2._1 })\n val coll3 = coll2.indices\n val func4 = {(box4: Box) => box4.R4[Coll[AvlTree]].get(0) }\n val func5 = {(tuple5: (Coll[Box], Coll[Byte])) =>\n tuple5._1.filter({(box7: Box) => box7.tokens.exists({(tuple9: (Coll[Byte], Long)) => tuple9._1 == tuple5._2 }) })\n }\n val coll6 = placeholder[Coll[Byte]](1)\n val box7 = func5((INPUTS, coll6))(0)\n val avlTree8 = func4(box7)\n val coll9 = avlTree8.getMany(coll2, getVar[Coll[Byte]](2.toByte).get)\n val func10 = {(coll10: Coll[Byte]) => byteArrayToLong(coll10.slice(8, 16)) }\n val func11 = {(coll11: Coll[Byte]) => coll11.slice(0, coll11.size - 16 / 8).indices.map({(i13: Int) =>\n val i15 = i13 * 8\n byteArrayToLong(coll11.slice(i15 + 16, i15 + 8 + 16))\n }) }\n val func12 = {(box12: Box) =>\n val coll14 = box12.R5[Coll[Long]].get\n coll14.slice(5, coll14.size)\n }\n val coll13 = func12(box7)\n val coll14 = coll9.map({(opt14: Option[Coll[Byte]]) => if (opt14.isDefined) {(\n val coll16 = opt14.get\n Coll[Long](func10(coll16)).append(func11(coll16))\n )} else { coll13.map({(l16: Long) => -1L }) } })\n val func15 = {(box15: Box) => box15.R7[Coll[(AvlTree, AvlTree)]].get }\n val coll16 = func15(box7)\n val tuple17 = coll16(0)\n val avlTree18 = tuple17._1\n val coll19 = avlTree18.getMany(coll2, getVar[Coll[Byte]](3.toByte).get).map({(opt19: Option[Coll[Byte]]) => func10(opt19.get) })\n val func20 = {(box20: Box) => box20.R6[Coll[Coll[Long]]].get(0) }\n val l21 = {(box21: Box) => box21.R6[Coll[Coll[Long]]].get(1) }(box7)(0)\n val b22 = if (l21 > 0L) { {(box22: Box) => box22.R6[Coll[Coll[Long]]].get(3) }(box7)(0).toByte } else { 0.toByte }\n val l23 = {(box23: Box) => box23.R6[Coll[Coll[Long]]].get(2) }(box7)(0)\n val b24 = if (l23 > 0L) { {(box24: Box) => box24.R6[Coll[Coll[Long]]].get(4) }(box7)(0).toByte } else { 0.toByte }\n val b25 = b22 + b24\n val b26 = if (b25.toInt > 0) { max(100.toByte - b25, 0.toByte) } else { 100.toByte }\n val bi27 = 0.toBigInt\n val bi28 = 0.toBigInt\n val b29 = b25 + b26\n val avlTree30 = tuple17._2\n val coll31 = avlTree30.getMany(coll2, getVar[Coll[Byte]](5.toByte).get).map({(opt31: Option[Coll[Byte]]) => if (opt31.isDefined) {(\n val coll33 = opt31.get\n (byteArrayToLong(coll33.slice(0, 8)), byteArrayToLong(coll33.slice(8, 16)))\n )} else { (0L, 0L) } })\n val func32 = {(box32: Box) => box32.R8[Coll[Long]].get }\n val coll33 = func32(box7)\n val coll34 = coll1.map({(tuple34: (Coll[Byte], Coll[Byte])) =>\n val coll36 = tuple34._2\n Coll[Long](func10(coll36)).append(func11(coll36))\n })\n val func35 = {(coll35: Coll[Byte]) => byteArrayToLong(coll35.slice(0, 8)) }\n val coll36 = coll9.map({(opt36: Option[Coll[Byte]]) => if (opt36.isDefined) { func35(opt36.get) } else { -1L } })\n val coll37 = coll1.map({(tuple37: (Coll[Byte], Coll[Byte])) => func35(tuple37._2) })\n val tuple38 = (func32(box7).map({(l38: Long) => 0.toBigInt }), true)\n val func39 = {(box39: Box) => box39.R5[Coll[Long]].get(1) }\n val coll40 = coll33.indices.map({(i40: Int) => coll3.map({(i42: Int) =>\n val coll44 = coll14(i42)\n if (coll44(0) >= 0L) {(\n val coll45 = func32(box7).map({(l45: Long) =>\n val bi47 = l45.toBigInt\n coll19(i42).toBigInt * bi47 / func20(box7)(0).toBigInt * b26.toBigInt + if (b22.toInt > 0) { coll31(i42)._1.toBigInt * bi47 / l21.toBigInt * b22.toBigInt } else { bi27 } + if (b24.toInt > 0) { coll31(i42)._2.toBigInt * bi47 / l23.toBigInt * b24.toBigInt } else { bi28 } / b29.toBigInt\n })\n (coll45, (coll44.zip(coll45).map({(tuple46: (Long, BigInt)) => tuple46._1.toBigInt + tuple46._2 }) == coll34(i42).map({(l46: Long) => l46.toBigInt })) && (coll36(i42) == coll37(i42)))\n )} else { tuple38 }\n }).fold(0.toBigInt, {(tuple42: (BigInt, (Coll[BigInt], Boolean))) => tuple42._1 + tuple42._2._1(i40) }) })\n val box41 = func5((OUTPUTS, coll6))(0)\n val coll42 = func15(box41)\n val tuple43 = coll42(0)\n val coll44 = tuple43._1.digest\n val coll45 = {(opt45: Option[Coll[Byte]]) => opt45.get.slice(1, 33) }(\n {(box45: Box) => box45.R4[AvlTree].get }(func5((CONTEXT.dataInputs, placeholder[Coll[Byte]](0)))(0)).getMany(\n Coll[Coll[Byte]](\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 ), getVar[Coll[Byte]](0.toByte).get\n )(0)\n )\n val box46 = {(tuple46: (Coll[Box], Coll[Byte])) => tuple46._1.filter({(box48: Box) => blake2b256(box48.propositionBytes) == tuple46._2 }) }(\n (OUTPUTS, coll45)\n )(0)\n val func47 = {(box47: Box) => box47.R4[Coll[AvlTree]].get(1) }\n val func48 = {(box48: Box) => box48.R5[Coll[Long]].get(0) }\n val func49 = {(box49: Box) => box49.R5[Coll[Long]].get(2) }\n val func50 = {(box50: Box) => box50.R5[Coll[Long]].get(3) }\n val func51 = {(box51: Box) => box51.R5[Coll[Long]].get(4) }\n val func52 = {(box52: Box) => box52.R6[Coll[Coll[Long]]].get }\n sigmaProp(allOf(Coll[Boolean](allOf(coll3.map({(i53: Int) =>\n val coll55 = coll14(i53)\n if (coll55(0) >= 0L) {(\n val coll56 = coll33.map({(l56: Long) =>\n val bi58 = l56.toBigInt\n coll19(i53).toBigInt * bi58 / func20(box7)(0).toBigInt * b26.toBigInt + if (b22.toInt > 0) { coll31(i53)._1.toBigInt * bi58 / l21.toBigInt * b22.toBigInt } else { bi27 } + if (b24.toInt > 0) { coll31(i53)._2.toBigInt * bi58 / l23.toBigInt * b24.toBigInt } else { bi28 } / b29.toBigInt\n })\n (coll56, (coll55.zip(coll56).map({(tuple57: (Long, BigInt)) => tuple57._1.toBigInt + tuple57._2 }) == coll34(i53).map({(l57: Long) => l57.toBigInt })) && (coll36(i53) == coll37(i53)))\n )} else { tuple38 }._2\n })), func39(box7).toBigInt + coll40(0) == func39(box41).toBigInt, avlTree18.remove(coll2, getVar[Coll[Byte]](4.toByte).get).get.digest == coll44, avlTree8.update(coll1.filter({(tuple53: (Coll[Byte], Coll[Byte])) => func10(tuple53._2) > 0L }), getVar[Coll[Byte]](6.toByte).get).get.digest == func4(box41).digest, allOf(Coll[Boolean](blake2b256(box46.propositionBytes) == coll45, box46.value >= SELF.value)), allOf(Coll[Boolean](box41.value == box7.value, box41.tokens == box7.tokens, func47(box41).digest == func47(box7).digest, tuple43._2 == avlTree30, coll42.slice(1, coll42.size) == coll16.slice(1, coll16.size), func48(box41) == func48(box7), func49(box41) == func49(box7), func50(box41) == func50(box7), func51(box41) == func51(box7), func52(box41) == func52(box7), func32(box41) == coll33)), (coll1.size >= 10) || (coll44 == Coll[Byte](78.toByte, -58.toByte, 31.toByte, 72.toByte, 91.toByte, -104.toByte, -21.toByte, -121.toByte, 21.toByte, 63.toByte, 124.toByte, 87.toByte, -37.toByte, 79.toByte, 94.toByte, -51.toByte, 117.toByte, 85.toByte, 111.toByte, -35.toByte, -68.toByte, 64.toByte, 59.toByte, 65.toByte, -84.toByte, -8.toByte, 68.toByte, 31.toByte, -34.toByte, -114.toByte, 22.toByte, 9.toByte, 0.toByte)), coll13.indices.forall({(i53: Int) => func12(box41)(i53).toBigInt == coll13(i53).toBigInt - coll40(i53) }))))\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "322f3fedb10fa762fca3396d6ae25eaa1e8a9532f3f8a16039b582e6cab85ce9",
"mainChain": true
},
{
"boxId": "c2bf94534db3c88412c8564e6d107057cfb19131e652e4a2dacbfad84da972b4",
"transactionId": "765100bb23c733aefb95ef209e842158be3ebbbe4dbc7461ea2d0ac8f085961d",
"blockId": "fdb1f876dd4d56a0b45c50952a0c8ab6321f65e7aab22019abdc8595729622f0",
"value": 150000,
"index": 2,
"globalIndex": 47225615,
"creationHeight": 1498349,
"settlementHeight": 1498351,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [
{
"tokenId": "1fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad489",
"index": 0,
"amount": 100,
"name": "Paideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "f566c7a93032eace962bf730c86028bc36b32f3f535811b4a15e42e134554de8",
"mainChain": true
},
{
"boxId": "c0e8324514fbe9990e2b5da1c1533d3cbd6a3548602f09c9658ea96476a7826c",
"transactionId": "765100bb23c733aefb95ef209e842158be3ebbbe4dbc7461ea2d0ac8f085961d",
"blockId": "fdb1f876dd4d56a0b45c50952a0c8ab6321f65e7aab22019abdc8595729622f0",
"value": 4850000,
"index": 3,
"globalIndex": 47225616,
"creationHeight": 1498349,
"settlementHeight": 1498351,
"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",
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"spentTransactionId": "aa6acfec82f21097ae28a506d2ded2deb4512a0184f6fa8939051486de6d7ea0",
"mainChain": true
},
{
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"value": 1036750000,
"index": 4,
"globalIndex": 47225617,
"creationHeight": 1498349,
"settlementHeight": 1498351,
"ergoTree": "10040e201b4b8b789fdd4a34c5f1cf73b4d99a5cacb8ccba75265f6edf4950893b162f070e201b4b8b789fdd4a34c5f1cf73b4d99a5cacb8ccba75265f6edf4950893b162f070e201fd6e032e8476c4aa54c18c1a308dce83940e8f4a28f576440513ed7326ad4890e40000653ab0e7fb89bfa221d75bd25aed8b98e0bac66a13aa229caf5855128d33a233536261ad8920b85644d30fff8e68c470470138950317ad520b300e8c1e573d811d601d901013c0c630eb58c720101d901036393cbc272038c720102d602d901023c0c630eb58c720201d9010463aedb63087204d901064d0e938c7206018c720202d603830002d604e3010ed605d901050c63b072050500d9010741639a8c720701c18c720702d6067303d607b472060440048001d6087300d609d9010963e4c672090464d60a7302d60bd9010b3c0c630eb0dc0c0f8c720b0101d9010d63db6308720d0500d9010d414d0ed801d60f8c720d029a8c720d0195938c720f018c720b028c720f020500d60cd9010c32b4e4720c04020442d60d832002025b02cf02f102020225024302660278020c02d50219021202570205020a026e02d3023a02c502d1022e02ef020e02300241023902ed025d0298021f024b02fad60ee4e30002d60fd9010f63b2db6308720f040200d610dc0c1aa402a70400d611d9011105958f72110580020402958f7211058080020404958f721105808080020406958f72110580808080020408958f721105808080808002040a958f72110580808080808002040c958f7211058080808080808002040e958f72110580808080808080800204100412d197830401dad901120295ec93721202039372120204d812d614cbc2a7d615b2da7201018602a57214040000d616db6501fed617b2da720201860272167301040000d618e572047203d619da7201018602a47214d61ada7205017219d61bb2da7202018602a57207040000d61cdc640bda720901b2da7202018602721672080400000283040e8320020289022e026f024702a1020d025c029002b8027a02d402860233025502ce02ad020002c302e202980232021702ee021502530232025302cd029a0260022502c2832002024f02d802b002d602d9028202420272026f025702b302df02a6028602120267029202b802e50205026e021d025102b602e9020d0268028002cf022d02cd02c583200202b002b9020702ab02af02ad028d02ff02ce022f029f021d02fa0215023502c0022202dd02a00253026602f402fb02d2027f0258021d0213022f024b022302f683200202b802c3022c020b029e024202cc028602d0023002b20261028e025a020602c002d202eb022b02a00264021f02090206028502b9028502ed02ab02100295026fe5e3020e7203d61ddad9011d32b4e4721d040c044c01b2721c040600d61e7cb4e4b2721c04040004020412d61fda720b0186027219720ad6208301637215d621da720b0186027220720ad622da720b0186027219721dd623da720b0186027220721dd624afb5db63087215d901244d0ed801d6268c722401ed947226720a947226721dd901244d0e928c722402da720b01860272198c722401d625afdc0c0f721901d9012563db63087225d901254d0ed801d6278c722501ec937227720aaedb63087215d901284d0e938c722801722797830201dad9012602959372260203d803d628dc640bda72090172170283040e8320020222025e023f02c502d1028902f5024702d902c6022602be02bd02c602710239028b026c0200027c0278023d02c4027f0290023f022402bf027f02340284027983200202bc024a025a02b902e4025a02b7024b027902fa02ec02bf02670249026c02c202bf028c022b020e025502db02e802ac02cf02c3029d021402890211027402908320020276027c02aa028002b9028e0249026a02d802a902f6028902c40241020a02e402530232027f020f029502e90250028402c002ae0220026302500279023b0277720d7218d6299a9c7cb4e4b2722804000004020412dad9012963b2e4c67229051104040001721b0502d62a93720a721d9683070192c1721599721a7cb4e4b272280406000402041292722199721f9a9a72297cb4e4b272280402000402041295722a721e050095722a0101927223997222721e7224722592da720b018602830163b2b5a5d9012b6393cbc2722bb4e4b2722804040004020442040000720a722993cbc2b2a4040200da720c01b2721c040200010001720edad9012602959372260204d801d628dc640bda72090172170283020e83200202ec02f202d0024b02ae024802a0020a028a026e024902c002560272026302c902f502d2023f022602c80223025802a1027602ab02d102f0022102d802b10230720d72189683070192c1721599721a7cb4e4b272280402000402041292722199721f7cb4e4b27228040000040204129593720a721d010192722372227224722593cbc2b2a4040200da720c01b2721c040000938cda720f01721b028cda720f01b2da7202018602a4720704000002010001720e010001720edad9011202959372120209e6b2dc640bda720901b2da7202018602db6501fe72080400000283010ecbb3831c020269026d022e0270026102690264026502690261022e0263026f026e027402720261026302740273022e0261026302740269026f026e022ec2b2da7202018602a4b4720604000440040000e47204040000010001720edad901120295937212020ad804d614cbc2a7d615da7201018602a47214d616da7201018602a57214d617da72050172159683050192b17215040a93b172160402afdb6308b27216040000d901184d0e93da720b01860272158c7218018c72180290997217da7205017216058092f401927217058092f401010001720edad9011202959372120207dad901143c0e6395927210b1a50100d809d616b2a5721000d617c17216d618c1a7d619c27216d61ac4a7d61bc2a7d61c8cc7a701d61dc47216d61e8cc772160196830401927217997218058092f40193cb7219da720c01b2dc640bda7209018c7214020283010e8c721401e57204720304000093b4721a9a9ada7211017218b1721bda7211017e721c05b1721ab4721d9a9ada7211017217b17219da7211017e721e05b1721d978302019299721e721c0480c33d94721b721901860283200202c702c5023702e602c602350293020e02cb024a02ce029502a50249022602b302ab02770269028d029f0249022202f002b102c5028e02a8027102560248023bb2da7202018602db6501fe7208040000010001720e",
"ergoTreeConstants": "0: 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)\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(0,6,83,-85,14,127,-72,-101,-6,34,29,117,-67,37,-82,-40,-71,-114,11,-84,102,-95,58,-94,41,-54,-11,-123,81,40,-45,58,35,53,54,38,26,-40,-110,11,-123,100,77,48,-1,-8,-26,-116,71,4,112,19,-119,80,49,122,-43,32,-77,0,-24,-63,-27,115)",
"ergoTreeScript": "{\n val func1 = {(tuple1: (Coll[Box], Coll[Byte])) => tuple1._1.filter({(box3: Box) => blake2b256(box3.propositionBytes) == tuple1._2 }) }\n val func2 = {(tuple2: (Coll[Box], Coll[Byte])) =>\n tuple2._1.filter({(box4: Box) => box4.tokens.exists({(tuple6: (Coll[Byte], Long)) => tuple6._1 == tuple2._2 }) })\n }\n val coll3 = Coll[Byte]()\n val opt4 = getVar[Coll[Byte]](1.toByte)\n val func5 = {(coll5: Coll[Box]) => coll5.fold(0L, {(tuple7: (Long, Box)) => tuple7._1 + tuple7._2.value }) }\n val coll6 = placeholder[Coll[Byte]](3)\n val coll7 = coll6.slice(32, 64)\n val coll8 = placeholder[Coll[Byte]](0)\n val func9 = {(box9: Box) => box9.R4[AvlTree].get }\n val coll10 = placeholder[Coll[Byte]](2)\n val func11 = {(tuple11: (Coll[Box], Coll[Byte])) => tuple11._1.flatMap({(box13: Box) => box13.tokens }).fold(0L, {(tuple13: (Long, (Coll[Byte], Long))) =>\n val tuple15 = tuple13._2\n tuple13._1 + if (tuple15._1 == tuple11._2) { tuple15._2 } else { 0L }\n }) }\n val func12 = {(opt12: Option[Coll[Byte]]) => opt12.get.slice(1, 33) }\n val coll13 = Coll[Byte](\n 91.toByte, -49.toByte, -15.toByte, 2.toByte, 37.toByte, 67.toByte, 102.toByte, 120.toByte, 12.toByte, -43.toByte, 25.toByte, 18.toByte, 87.toByte, 5.toByte, 10.toByte, 110.toByte, -45.toByte, 58.toByte, -59.toByte, -47.toByte, 46.toByte, -17.toByte, 14.toByte, 48.toByte, 65.toByte, 57.toByte, -19.toByte, 93.toByte, -104.toByte, 31.toByte, 75.toByte, -6.toByte\n )\n val b14 = getVar[Byte](0.toByte).get\n val func15 = {(box15: Box) => box15.tokens(1) }\n val i16 = INPUTS.indexOf(SELF, 0)\n val func17 = {(l17: Long) =>\n if (l17 < 128L) { 1 } else {\n if (l17 < 16384L) { 2 } else {\n if (l17 < 2097152L) { 3 } else {\n if (l17 < 268435456L) { 4 } else {\n if (l17 < 34359738368L) { 5 } else {\n if (l17 < 4398046511104L) { 6 } else { if (l17 < 562949953421312L) { 7 } else { if (l17 < 72057594037927936L) { 8 } else { 9 } } }\n }\n }\n }\n }\n }\n }\n sigmaProp(anyOf(Coll[Boolean]({(b18: Byte) => if ((b18 == 3.toByte) || (b18 == 4.toByte)) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val box21 = func1((OUTPUTS, coll20))(0)\n val coll22 = CONTEXT.dataInputs\n val box23 = func2((coll22, placeholder[Coll[Byte]](1)))(0)\n val coll24 = opt4.getOrElse(coll3)\n val coll25 = func1((INPUTS, coll20))\n val l26 = func5(coll25)\n val box27 = func2((OUTPUTS, coll7))(0)\n val coll28 = func9(func2((coll22, coll8))(0)).getMany(Coll[Coll[Byte]](Coll[Byte](-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), Coll[Byte](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), Coll[Byte](-80.toByte, -71.toByte, 7.toByte, -85.toByte, -81.toByte, -83.toByte, -115.toByte, -1.toByte, -50.toByte, 47.toByte, -97.toByte, 29.toByte, -6.toByte, 21.toByte, 53.toByte, -64.toByte, 34.toByte, -35.toByte, -96.toByte, 83.toByte, 102.toByte, -12.toByte, -5.toByte, -46.toByte, 127.toByte, 88.toByte, 29.toByte, 19.toByte, 47.toByte, 75.toByte, 35.toByte, -10.toByte), Coll[Byte](-72.toByte, -61.toByte, 44.toByte, 11.toByte, -98.toByte, 66.toByte, -52.toByte, -122.toByte, -48.toByte, 48.toByte, -78.toByte, 97.toByte, -114.toByte, 90.toByte, 6.toByte, -64.toByte, -46.toByte, -21.toByte, 43.toByte, -96.toByte, 100.toByte, 31.toByte, 9.toByte, 6.toByte, -123.toByte, -71.toByte, -123.toByte, -19.toByte, -85.toByte, 16.toByte, -107.toByte, 111.toByte)), getVar[Coll[Byte]](2.toByte).getOrElse(coll3))\n val coll29 = {(opt29: Option[Coll[Byte]]) => opt29.get.slice(6, 38) }(coll28(3))\n val l30 = byteArrayToLong(coll28(2).get.slice(1, 9))\n val l31 = func11((coll25, coll10))\n val coll32 = Coll[Box](box21)\n val l33 = func11((coll32, coll10))\n val l34 = func11((coll25, coll29))\n val l35 = func11((coll32, coll29))\n val bool36 = box21.tokens.filter({(tuple36: (Coll[Byte], Long)) =>\n val coll38 = tuple36._1\n (coll38 != coll10) && (coll38 != coll29)\n }).forall({(tuple36: (Coll[Byte], Long)) => tuple36._2 >= func11((coll25, tuple36._1)) })\n val bool37 = coll25.flatMap({(box37: Box) => box37.tokens }).forall({(tuple37: (Coll[Byte], Long)) =>\n val coll39 = tuple37._1\n (coll39 == coll10) || box21.tokens.exists({(tuple40: (Coll[Byte], Long)) => tuple40._1 == coll39 })\n })\n anyOf(Coll[Boolean]({(b38: Byte) => if (b38 == 3.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](34.toByte, 94.toByte, 63.toByte, -59.toByte, -47.toByte, -119.toByte, -11.toByte, 71.toByte, -39.toByte, -58.toByte, 38.toByte, -66.toByte, -67.toByte, -58.toByte, 113.toByte, 57.toByte, -117.toByte, 108.toByte, 0.toByte, 124.toByte, 120.toByte, 61.toByte, -60.toByte, 127.toByte, -112.toByte, 63.toByte, 36.toByte, -65.toByte, 127.toByte, 52.toByte, -124.toByte, 121.toByte), Coll[Byte](-68.toByte, 74.toByte, 90.toByte, -71.toByte, -28.toByte, 90.toByte, -73.toByte, 75.toByte, 121.toByte, -6.toByte, -20.toByte, -65.toByte, 103.toByte, 73.toByte, 108.toByte, -62.toByte, -65.toByte, -116.toByte, 43.toByte, 14.toByte, 85.toByte, -37.toByte, -24.toByte, -84.toByte, -49.toByte, -61.toByte, -99.toByte, 20.toByte, -119.toByte, 17.toByte, 116.toByte, -112.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), coll13), coll24)\n val l41 = byteArrayToLong(coll40(0).get.slice(1, 9)) * {(box41: Box) => box41.R5[Coll[Long]].get(2) }(box27) + 1L\n val bool42 = coll10 == coll29\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(3).get.slice(1, 9)), l33 >= l31 - l41 + byteArrayToLong(coll40(1).get.slice(1, 9)) + if (bool42) { l30 } else { 0L }, if (bool42) { true } else { l35 >= l34 - l30 }, bool36, bool37, func11((Coll[Box](OUTPUTS.filter({(box43: Box) => blake2b256(box43.propositionBytes) == coll40(2).get.slice(1, 33) })(0)), coll10)) >= l41, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(1))))\n )} else { false } }(b14), {(b38: Byte) => if (b38 == 4.toByte) {(\n val coll40 = func9(box23).getMany(Coll[Coll[Byte]](Coll[Byte](-20.toByte, -14.toByte, -48.toByte, 75.toByte, -82.toByte, 72.toByte, -96.toByte, 10.toByte, -118.toByte, 110.toByte, 73.toByte, -64.toByte, 86.toByte, 114.toByte, 99.toByte, -55.toByte, -11.toByte, -46.toByte, 63.toByte, 38.toByte, -56.toByte, 35.toByte, 88.toByte, -95.toByte, 118.toByte, -85.toByte, -47.toByte, -16.toByte, 33.toByte, -40.toByte, -79.toByte, 48.toByte), coll13), coll24)\n allOf(Coll[Boolean](box21.value >= l26 - byteArrayToLong(coll40(1).get.slice(1, 9)), l33 >= l31 - byteArrayToLong(coll40(0).get.slice(1, 9)), if (coll10 == coll29) { true } else { l35 >= l34 }, bool36, bool37, blake2b256(INPUTS(1).propositionBytes) == func12(coll28(0)), func15(box27)._2 == func15(func2((INPUTS, coll7))(0))._2))\n )} else { false } }(b14)))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 9.toByte) { func9(func2((CONTEXT.dataInputs, coll8))(0)).getMany(Coll[Coll[Byte]](blake2b256(Coll[Byte](105.toByte, 109.toByte, 46.toByte, 112.toByte, 97.toByte, 105.toByte, 100.toByte, 101.toByte, 105.toByte, 97.toByte, 46.toByte, 99.toByte, 111.toByte, 110.toByte, 116.toByte, 114.toByte, 97.toByte, 99.toByte, 116.toByte, 115.toByte, 46.toByte, 97.toByte, 99.toByte, 116.toByte, 105.toByte, 111.toByte, 110.toByte, 46.toByte).append(func2((INPUTS, coll6.slice(0, 32)))(0).propositionBytes))), opt4.get)(0).isDefined } else { false } }(b14), {(b18: Byte) => if (b18 == 10.toByte) {(\n val coll20 = blake2b256(SELF.propositionBytes)\n val coll21 = func1((INPUTS, coll20))\n val coll22 = func1((OUTPUTS, coll20))\n val l23 = func5(coll21)\n allOf(Coll[Boolean](coll21.size >= 5, coll22.size == 1, coll22(0).tokens.forall({(tuple24: (Coll[Byte], Long)) => func11((coll21, tuple24._1)) == tuple24._2 }), l23 - func5(coll22) <= 2000000L, l23 >= 2000000L))\n )} else { false } }(b14), {(b18: Byte) => if (b18 == 7.toByte) { {(tuple20: (Coll[Byte], Box)) => if (i16 >= OUTPUTS.size) { false } else {(\n val box22 = OUTPUTS(i16)\n val l23 = box22.value\n val l24 = SELF.value\n val coll25 = box22.propositionBytes\n val coll26 = SELF.bytesWithoutRef\n val coll27 = SELF.propositionBytes\n val i28 = SELF.creationInfo._1\n val coll29 = box22.bytesWithoutRef\n val i30 = box22.creationInfo._1\n allOf(Coll[Boolean](l23 >= l24 - 2000000L, blake2b256(coll25) == func12(func9(tuple20._2).getMany(Coll[Coll[Byte]](tuple20._1), opt4.getOrElse(coll3))(0)), coll26.slice(func17(l24) + coll27.size + func17(i28.toLong), coll26.size) == coll29.slice(func17(l23) + coll25.size + func17(i30.toLong), coll29.size), anyOf(Coll[Boolean](i30 - i28 >= 504000, coll27 != coll25))))\n )} }((Coll[Byte](-57.toByte, -59.toByte, 55.toByte, -26.toByte, -58.toByte, 53.toByte, -109.toByte, 14.toByte, -53.toByte, 74.toByte, -50.toByte, -107.toByte, -91.toByte, 73.toByte, 38.toByte, -77.toByte, -85.toByte, 119.toByte, 105.toByte, -115.toByte, -97.toByte, 73.toByte, 34.toByte, -16.toByte, -79.toByte, -59.toByte, -114.toByte, -88.toByte, 113.toByte, 86.toByte, 72.toByte, 59.toByte), func2((CONTEXT.dataInputs, coll8))(0))) } else { false } }(b14))))\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 1969177582139,
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},
{
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},
{
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}
],
"additionalRegisters": {},
"spentTransactionId": "3e9f1008afc60bd6be73e7233e578378b871f40b605c90a67d1f2a2355f99e55",
"mainChain": true
}
],
"size": 23449,
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}