Transaction
ID: ddfd0982d5...a835
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.49 ERG
Tokens:
9,997.00
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 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:
0.485 ERG
Tokens:
9,996.99
Transaction Details
Confirmations: 570,614
Total coins transferred: 0.492 ERG
Fees: 0.00485 ERG
Fees per byte: 0.000000565 ERG
Raw Transaction Data
{
"id": "ddfd0982d5740806ba429c8a708f5e99b2a2aecaf1145a79d61e20fb7008a835",
"blockId": "589f24ecf8a4a97b838ba1531b09ea8931a9ea7a8ed7b7d0612e358a6de0148d",
"inclusionHeight": 1185843,
"timestamp": 1706204375659,
"index": 1,
"globalIndex": 6524539,
"numConfirmations": 570614,
"inputs": [
{
"boxId": "797cecdf5b2b75f6771f11b7a26a1a944832152d643fea8124d014c543a1abd8",
"value": 1000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "f0f2067b54e4274c1b18fd5e12e83f0d542d53d5eff4b21931b10765d133cbd9",
"outputTransactionId": "ad60521f2b5e2f75b3783c94f72b2ae85689b6f4b2aa2a1de1f19a395d287e67",
"outputIndex": 0,
"outputGlobalIndex": 36395277,
"outputCreatedAt": 1185839,
"outputSettledAt": 1185841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: Coll(-34,-82,-49,91,100,-70,-42,-11,87,11,-83,10,97,12,78,72,73,87,-49,71,-126,48,-124,0,-68,-112,64,76,29,20,16,-38)\n3: Coll(3,-110,8,-68,78,-17,-102,3,-24,-41,-117,-122,99,-93,1,-69,95,-83,-36,-89,-117,-31,-99,127,-27,53,-77,-58,76,-66,-2,66)\n4: Coll(-120,48,97,44,82,53,95,111,40,13,18,-105,-15,-97,103,-80,120,-55,-38,-89,-41,-80,75,69,-100,-111,-52,100,73,87,-62,-128)\n5: Coll(-117,-57,-113,28,106,-82,-55,30,98,-114,21,-49,102,-116,22,-52,30,-101,-40,-28,-71,-73,-31,109,99,24,-75,-11,35,-91,-23,-67)\n6: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n7: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n8: Coll(58,17,-107,92,71,25,-27,-120,-68,-26,-89,97,29,39,-67,31,-33,-37,87,56,92,-82,-30,102,-40,4,12,-119,79,28,46,29)\n9: Coll(9,-126,15,-53,-120,113,-5,69,12,62,6,-73,-53,94,39,-80,69,80,-121,-93,102,98,26,-99,-34,117,-126,-96,25,17,30,62)\n10: 0\n11: 0\n12: Coll(-81,24,111,-17,71,1,117,-104,-101,-100,-110,29,15,-116,-47,-122,41,-26,46,-107,57,-112,-127,101,-62,-17,-124,28,-126,66,-23,-75)\n13: 0\n14: 6\n15: 0\n16: 1\n17: 1\n18: 33\n19: 1\n20: 2\n21: 1\n22: 33\n23: 2\n24: 3\n25: 1\n26: 33\n27: 3\n28: 4\n29: 1\n30: 33\n31: 4\n32: 5\n33: 1\n34: 33\n35: 5\n36: 6\n37: 1\n38: 33\n39: 6\n40: 7\n41: 1\n42: 33\n43: 0\n44: 1\n45: 33\n46: 0\n47: 0\n48: 1\n49: 1",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val b2 = getVar[Byte](1.toByte).get\n val i3 = b2.toInt\n val box4 = INPUTS(placeholder[Int](1))\n val coll5 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4), placeholder[Coll[Byte]](5), placeholder[Coll[Byte]](6), placeholder[\n Coll[Byte]\n ](7), placeholder[Coll[Byte]](8), placeholder[Coll[Byte]](9)\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val box6 = OUTPUTS(placeholder[Int](10))\n val coll7 = box6.tokens\n val coll8 = SELF.tokens\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), (i3 >= placeholder[Int](13)) && (i3 <= placeholder[Int](14)), anyOf(\n Coll[Boolean](\n (b2 == placeholder[Byte](15)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](16)).get.slice(placeholder[Int](17), placeholder[Int](18))\n ), (b2 == placeholder[Byte](19)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](20)).get.slice(placeholder[Int](21), placeholder[Int](22))\n ), (b2 == placeholder[Byte](23)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](24)).get.slice(placeholder[Int](25), placeholder[Int](26))\n ), (b2 == placeholder[Byte](27)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](28)).get.slice(placeholder[Int](29), placeholder[Int](30))\n ), (b2 == placeholder[Byte](31)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](32)).get.slice(placeholder[Int](33), placeholder[Int](34))\n ), (b2 == placeholder[Byte](35)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))\n ), (b2 == placeholder[Byte](39)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))\n )\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box6.propositionBytes) == coll5(placeholder[Int](43)).get.slice(placeholder[Int](44), placeholder[Int](45)), coll7(\n placeholder[Int](46)\n ) == coll8(placeholder[Int](47)), coll7(placeholder[Int](48))._1 == coll8(placeholder[Int](49))._1\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "bc57367811c3158252b29476525930d3deebb03a178e85ae90dd7d8aca938674",
"index": 0,
"amount": 1,
"name": "MyFirstDAO Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00de06c61282578684b377ffd6314c38ce596f2c054107fe2314810677859269",
"index": 1,
"amount": 1101000000001,
"name": "MyFirstDAOToken",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107ee99f5a2a26380acf1f6a93a02000080dac40900",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1705407063671,1002060000000,1,0,0,10000000,0]"
},
"R6": {
"serializedValue": "1d050280d2aceda93a80acf1f6a93a020000020000023232023232",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[1002050000000,1002060000000],[0,0],[0,0],[25,25],[25,25]]"
},
"R8": {
"serializedValue": "110280dac40900",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000,0]"
},
"R7": {
"serializedValue": "0c3c64640231c23729d66619d7f8b57ed9aeb017a2271ffb600ade9977c82948b8758cf403010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e16090007200069f6d2885a79da10cee13acca4bb61a2c273e7eb8bbcac77c93be4c97015806d010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c640269f6d2885a79da10cee13acca4bb61a2c273e7eb8bbcac77c93be4c97015806d010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "a1e2bea78c0ea61b5cf79272dc10e87c1342d491c18f68f94bef4b87a90a0412",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "f0f2067b54e4274c1b18fd5e12e83f0d542d53d5eff4b21931b10765d133cbd9",
"outputTransactionId": "1af7231929c518c82bd93d308868ba57cb94b78f53a34e7abce0385ced023433",
"outputIndex": 1,
"outputGlobalIndex": 36395273,
"outputCreatedAt": 1185839,
"outputSettledAt": 1185841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-17,-60,-10,3,-34,-90,4,18,-122,-88,-97,91,-43,22,-84,-106,-22,91,37,-38,79,8,-41,108,105,39,-32,29,97,-78,42,-33)\n3: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n4: Coll(73,50,-62,-121,84,-14,-28,-6,-72,-24,90,-8,-18,61,-21,91,-66,73,36,-73,88,84,102,-46,13,-18,-44,-55,-98,65,-111,-94)\n5: 0\n6: 2\n7: 0\n8: 6\n9: 37\n10: 5\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 1\n17: 4\n18: 0\n19: 8\n20: 8\n21: 8\n22: -1\n23: 0\n24: 8\n25: 16\n26: 0\n27: 0\n28: 1\n29: 0\n30: 3\n31: 0\n32: 0\n33: 0\n34: 2\n35: 0\n36: 4\n37: 0\n38: 0\n39: 0\n40: 0\n41: 100\n42: 0\n43: 100\n44: CBigInt(0)\n45: CBigInt(0)\n46: 0\n47: 8\n48: 8\n49: 16\n50: 0\n51: 0\n52: 8\n53: 8\n54: 8\n55: CBigInt(0)\n56: true\n57: 0\n58: 0\n59: 0\n60: 0\n61: 0\n62: 0\n63: CBigInt(0)\n64: 0\n65: 0\n66: 1\n67: 1\n68: 1\n69: 0\n70: Coll(-81,24,111,-17,71,1,117,-104,-101,-100,-110,29,15,-116,-47,-122,41,-26,46,-107,57,-112,-127,101,-62,-17,-124,28,-126,66,-23,-75)\n71: 0\n72: 0\n73: 6\n74: 38\n75: 0\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 1\n82: 0\n83: 1\n84: 8\n85: 16\n86: 0\n87: 0\n88: 1\n89: 1\n90: 33\n91: 1\n92: 1\n93: 0\n94: 0\n95: 2\n96: 5\n97: 2\n98: 5\n99: 10\n100: 78\n101: -58\n102: 31\n103: 72\n104: 91\n105: -104\n106: -21\n107: -121\n108: 21\n109: 63\n110: 124\n111: 87\n112: -37\n113: 79\n114: 94\n115: -51\n116: 117\n117: 85\n118: 111\n119: -35\n120: -68\n121: 64\n122: 59\n123: 65\n124: -84\n125: -8\n126: 68\n127: 31\n128: -34\n129: -114\n130: 22\n131: 9\n132: 0\n133: 5",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box2.tokens\n val coll4 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4)), getVar[Coll[Byte]](0.toByte).get\n )\n val coll5 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll6 = coll5.map({(tuple6: (Coll[Byte], Coll[Byte])) => tuple6._1 })\n val coll7 = coll6.indices\n val coll8 = box2.R4[Coll[AvlTree]].get\n val avlTree9 = coll8(placeholder[Int](5))\n val coll10 = box2.R5[Coll[Long]].get\n val i11 = coll10.size\n val coll12 = coll4(placeholder[Int](6)).get\n val coll13 = coll12.slice(placeholder[Int](7), coll12.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll14 = coll10.slice(placeholder[Int](10), i11).append(\n coll13.map(\n {(i14: Int) =>\n coll12.slice(\n placeholder[Int](11) + placeholder[Int](12) * i14 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i14 + placeholder[Int](16)\n )\n }\n ).slice(i11 - placeholder[Int](17), coll13.size).map({(coll14: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll15 = coll14.indices\n val coll16 = avlTree9.getMany(coll6, getVar[Coll[Byte]](2.toByte).get).map({(opt16: Option[Coll[Byte]]) => if (opt16.isDefined) { coll15.map({(i18: Int) =>\n val i20 = i18 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(opt16.get.slice(i20, i20 + placeholder[Int](21)))\n }) } else { coll14.map({(l18: Long) => placeholder[Long](22) }) } })\n val coll17 = box2.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple18 = coll17(placeholder[Int](23))\n val avlTree19 = tuple18._1\n val coll20 = avlTree19.getMany(coll6, getVar[Coll[Byte]](3.toByte).get).map(\n {(opt20: Option[Coll[Byte]]) => byteArrayToLong(opt20.get.slice(placeholder[Int](24), placeholder[Int](25))) }\n )\n val coll21 = box2.R6[Coll[Coll[Long]]].get\n val l22 = coll21(placeholder[Int](26))(placeholder[Int](27))\n val l23 = coll21(placeholder[Int](28))(placeholder[Int](29))\n val coll24 = coll21(placeholder[Int](30))\n val b25 = if (l23 > placeholder[Long](31)) { coll24(placeholder[Int](32)).toByte } else { placeholder[Byte](33) }\n val l26 = coll21(placeholder[Int](34))(placeholder[Int](35))\n val coll27 = coll21(placeholder[Int](36))\n val b28 = if (l26 > placeholder[Long](37)) { coll27(placeholder[Int](38)).toByte } else { placeholder[Byte](39) }\n val b29 = b25 + b28\n val b30 = if (b29.toInt > placeholder[Int](40)) { max(placeholder[Byte](41) - b29, placeholder[Byte](42)) } else { placeholder[Byte](43) }\n val bi31 = placeholder[BigInt](44)\n val bi32 = placeholder[BigInt](45)\n val b33 = b29 + b30\n val avlTree34 = tuple18._2\n val coll35 = avlTree34.getMany(coll6, getVar[Coll[Byte]](5.toByte).get).map({(opt35: Option[Coll[Byte]]) => if (opt35.isDefined) {(\n val coll37 = opt35.get\n (byteArrayToLong(coll37.slice(placeholder[Int](46), placeholder[Int](47))), byteArrayToLong(coll37.slice(placeholder[Int](48), placeholder[Int](49))))\n )} else { (placeholder[Long](50), placeholder[Long](51)) } })\n val coll36 = box2.R8[Coll[Long]].get\n val coll37 = coll5.map({(tuple37: (Coll[Byte], Coll[Byte])) => coll15.map({(i39: Int) =>\n val i41 = i39 * placeholder[Int](52) + placeholder[Int](53)\n byteArrayToLong(tuple37._2.slice(i41, i41 + placeholder[Int](54)))\n }) })\n val tuple38 = (coll36.map({(l38: Long) => placeholder[BigInt](55) }), placeholder[Boolean](56))\n val coll39 = coll36.indices.map({(i39: Int) => coll7.map({(i41: Int) =>\n val coll43 = coll16(i41)\n if (coll43(placeholder[Int](57)) >= placeholder[Long](58)) {(\n val coll44 = coll36.map({(l44: Long) =>\n val bi46 = l44.toBigInt\n coll20(i41).toBigInt * bi46 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](59)) { coll35(i41)._1.toBigInt * bi46 / l23.toBigInt * coll24(placeholder[Int](60)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](61)) { coll35(i41)._2.toBigInt * bi46 / l26.toBigInt * coll27(placeholder[Int](62)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll44, coll43.zip(coll44).map({(tuple45: (Long, BigInt)) => tuple45._1.toBigInt + tuple45._2 }) == coll37(i41).map({(l45: Long) => l45.toBigInt }))\n )} else { tuple38 }\n }).fold(placeholder[BigInt](63), {(tuple41: (BigInt, (Coll[BigInt], Boolean))) => tuple41._1 + tuple41._2._1(i39) }) })\n val box40 = OUTPUTS(placeholder[Int](64))\n val coll41 = box40.R5[Coll[Long]].get\n val coll42 = box40.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple43 = coll42(placeholder[Int](65))\n val coll44 = tuple43._1.digest\n val coll45 = box40.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](66))\n val bool47 = tuple43._2 == avlTree34\n val bool48 = coll42.slice(placeholder[Int](67), coll42.size) == coll17.slice(placeholder[Int](68), coll17.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](69))._1 == placeholder[Coll[Byte]](70), coll3(placeholder[Int](71))._1 == coll4(placeholder[Int](72)).get.slice(\n placeholder[Int](73), placeholder[Int](74)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](75)) >= placeholder[Long](76)) {(\n val coll52 = coll36.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](77)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](78)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](79)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](80)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll37(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple38 }._2\n })), coll10(placeholder[Int](81)).toBigInt + coll39(placeholder[Int](82)) == coll41(placeholder[Int](83)).toBigInt, avlTree19.remove(\n coll6, getVar[Coll[Byte]](4.toByte).get\n ).get.digest == coll44, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](84), placeholder[Int](85))) > placeholder[Long](86) }\n ), getVar[Coll[Byte]](6.toByte).get\n ).get.digest == coll45(placeholder[Int](87)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](88)).get.slice(placeholder[Int](89), placeholder[Int](90)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box40.value == box2.value, box40.tokens == coll3, coll45(placeholder[Int](91)).digest == coll8(placeholder[Int](92)).digest, bool47, bool48, coll41(\n placeholder[Int](93)\n ) == coll10(placeholder[Int](94)), coll41.slice(placeholder[Int](95), placeholder[Int](96)) == coll10.slice(\n placeholder[Int](97), placeholder[Int](98)\n ), box40.R6[Coll[Coll[Long]]].get == coll21, bool48, bool47, box40.R8[Coll[Long]].get == coll36\n )\n ), (coll5.size >= placeholder[Int](99)) || (\n coll44 == Coll[Byte](\n placeholder[Byte](100), placeholder[Byte](101), placeholder[Byte](102), placeholder[Byte](103), placeholder[Byte](104), placeholder[Byte](\n 105\n ), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108), placeholder[Byte](109), placeholder[Byte](110), placeholder[Byte](\n 111\n ), placeholder[Byte](112), placeholder[Byte](113), placeholder[Byte](114), placeholder[Byte](115), placeholder[Byte](116), placeholder[Byte](\n 117\n ), placeholder[Byte](118), placeholder[Byte](119), placeholder[Byte](120), placeholder[Byte](121), placeholder[Byte](122), placeholder[Byte](\n 123\n ), placeholder[Byte](124), placeholder[Byte](125), placeholder[Byte](126), placeholder[Byte](127), placeholder[Byte](128), placeholder[Byte](\n 129\n ), placeholder[Byte](130), placeholder[Byte](131), placeholder[Byte](132)\n )\n ), coll15.forall({(i49: Int) => coll41.slice(placeholder[Int](133), coll41.size)(i49).toBigInt == coll14(i49).toBigInt - coll39(i49) })\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "f91f70faee94169c3eaccd148527ccd68362d4a006afe1a5816f28fc302c320f",
"value": 490000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "f0f2067b54e4274c1b18fd5e12e83f0d542d53d5eff4b21931b10765d133cbd9",
"outputTransactionId": "ad60521f2b5e2f75b3783c94f72b2ae85689b6f4b2aa2a1de1f19a395d287e67",
"outputIndex": 5,
"outputGlobalIndex": 36395282,
"outputCreatedAt": 1185839,
"outputSettledAt": 1185841,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(70,47,-51,40,84,79,105,33,97,72,49,118,-95,49,53,51,38,-4,105,80,-75,64,-64,-125,107,-100,93,-25,52,-91,-35,-37)\n3: false\n4: Coll(0,64,-82,101,12,78,-41,123,-51,32,57,20,-109,-85,-24,76,26,-101,-75,-114,-24,-114,-121,-15,86,112,-56,1,-30,-4,89,-125)\n5: Coll(91,-49,-15,2,37,67,102,120,12,-43,25,18,87,5,10,110,-45,58,-59,-47,46,-17,14,48,65,57,-19,93,-104,31,75,-6)\n6: 0\n7: 0\n8: 0\n9: 1\n10: 0\n11: 0\n12: 0\n13: 0\n14: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n15: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n16: 0\n17: 0\n18: Coll(34,94,63,-59,-47,-119,-11,71,-39,-58,38,-66,-67,-58,113,57,-117,108,0,124,120,61,-60,127,-112,63,36,-65,127,52,-124,121)\n19: Coll(-68,74,90,-71,-28,90,-73,75,121,-6,-20,-65,103,73,108,-62,-65,-116,43,14,85,-37,-24,-84,-49,-61,-99,20,-119,17,116,-112)\n20: Coll(118,124,-86,-128,-71,-114,73,106,-40,-87,-10,-119,-60,65,10,-28,83,50,127,15,-107,-23,80,-124,-64,-82,32,99,80,121,59,119)\n21: 0\n22: 1\n23: 9\n24: 2\n25: 1\n26: 2\n27: 1\n28: 33\n29: 0\n30: 0\n31: 3\n32: 1\n33: 9\n34: 0\n35: 0\n36: 1\n37: 1\n38: 9\n39: 1\n40: 1\n41: 1\n42: 33\n43: Coll(-20,-14,-48,75,-82,72,-96,10,-118,110,73,-64,86,114,99,-55,-11,-46,63,38,-56,35,88,-95,118,-85,-47,-16,33,-40,-79,48)\n44: 1\n45: 1\n46: 9\n47: 0\n48: 0\n49: 0\n50: 1\n51: 9\n52: 1\n53: 0\n54: 1\n55: 33\n56: 1\n57: 1\n58: false",
"ergoTreeScript": "{\n val bool1 = INPUTS.exists({(box1: Box) =>\n val coll3 = box1.tokens\n if (coll3.size > placeholder[Int](0)) { coll3(placeholder[Int](1))._1 == placeholder[Coll[Byte]](2) } else { placeholder[Boolean](3) }\n })\n val coll2 = placeholder[Coll[Byte]](4)\n val coll3 = placeholder[Coll[Byte]](5)\n sigmaProp(anyOf(Coll[Boolean](bool1, if (!bool1) {(\n val box4 = OUTPUTS(placeholder[Int](6))\n val coll5 = box4.R5[Coll[Long]].get\n val box6 = INPUTS(placeholder[Int](7))\n val coll7 = SELF.propositionBytes\n val box8 = OUTPUTS.filter({(box8: Box) => box8.propositionBytes == coll7 })(placeholder[Int](8))\n val coll9 = CONTEXT.dataInputs\n val avlTree10 = coll9(placeholder[Int](9)).R4[AvlTree].get\n val coll11 = getVar[Coll[Byte]](0.toByte).get\n val coll12 = INPUTS.filter({(box12: Box) => box12.propositionBytes == coll7 })\n val l13 = coll12.fold(placeholder[Long](10), {(tuple13: (Long, Box)) => tuple13._1 + tuple13._2.value })\n val coll14 = box8.tokens\n val func15 = {(coll15: Coll[Byte]) => coll12.flatMap({(box17: Box) => box17.tokens }).fold(placeholder[Long](11), {(tuple17: (Long, (Coll[Byte], Long))) =>\n val tuple19 = tuple17._2\n tuple17._1 + if (tuple19._1 == coll15) { tuple19._2 } else { placeholder[Long](12) }\n }) }\n val l16 = func15(coll2)\n val coll17 = coll9(placeholder[Int](13)).R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](14), placeholder[Coll[Byte]](15)), getVar[Coll[Byte]](1.toByte).get)\n val bool18 = coll14.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 != coll2 }).forall({(tuple18: (Coll[Byte], Long)) => tuple18._2 == func15(tuple18._1) })\n val bool19 = coll12.flatMap({(box19: Box) => box19.tokens }).forall({(tuple19: (Coll[Byte], Long)) =>\n val coll21 = tuple19._1\n (coll21 == coll2) || box8.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 })\n })\n if (coll5(placeholder[Int](16)) > box6.R5[Coll[Long]].get(placeholder[Int](17))) {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](18), placeholder[Coll[Byte]](19), placeholder[Coll[Byte]](20), coll3), coll11)\n val l21 = byteArrayToLong(coll20(placeholder[Int](21)).get.slice(placeholder[Int](22), placeholder[Int](23))) * coll5(placeholder[Int](24)) + placeholder[Long](25)\n val tuple22 = OUTPUTS.filter({(box22: Box) => blake2b256(box22.propositionBytes) == coll20(placeholder[Int](26)).get.slice(placeholder[Int](27), placeholder[Int](28)) })(placeholder[Int](29)).tokens(placeholder[Int](30))\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](31)).get.slice(placeholder[Int](32), placeholder[Int](33))), coll14.fold(placeholder[Long](34), {(tuple23: (Long, (Coll[Byte], Long))) =>\n val tuple25 = tuple23._2\n tuple23._1 + if (tuple25._1 == coll2) { tuple25._2 } else { placeholder[Long](35) }\n }) >= l16 - l21 - byteArrayToLong(coll20(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))), bool18, bool19, tuple22._1 == coll2, tuple22._2 >= l21, blake2b256(INPUTS(placeholder[Int](39)).propositionBytes) == coll17(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))))\n )} else {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](43), coll3), coll11)\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](44)).get.slice(placeholder[Int](45), placeholder[Int](46))), coll14.fold(placeholder[Long](47), {(tuple21: (Long, (Coll[Byte], Long))) =>\n val tuple23 = tuple21._2\n tuple21._1 + if (tuple23._1 == coll2) { tuple23._2 } else { placeholder[Long](48) }\n }) >= l16 - byteArrayToLong(coll20(placeholder[Int](49)).get.slice(placeholder[Int](50), placeholder[Int](51))), bool18, bool19, blake2b256(INPUTS(placeholder[Int](52)).propositionBytes) == coll17(placeholder[Int](53)).get.slice(placeholder[Int](54), placeholder[Int](55)), box4.tokens(placeholder[Int](56))._2 == box6.tokens(placeholder[Int](57))._2))\n )}\n )} else { placeholder[Boolean](58) })))\n}",
"address": "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",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 99969993,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "64b78de44a7ec90beb0cce21a7ff84ee7e06ec3e33051191e6937547c7a1cb69",
"value": 1000000,
"index": 0,
"outputBlockId": "43f92561a92903c0e0c74471175f63633c82e47d173fdf04a16de8a150c233f6",
"outputTransactionId": "11dcfb2ba71d17f645e4069999103d854a3bc306da850712184559fd0c8d6ead",
"outputIndex": 0,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e20462fcd28544f692161483176a131353326fc6950b540c0836b9c5de734a5dddb0100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfc8iwVgt5EsbRdPHBjuffeoMRFU7cR6YU4M1H9dcq14BX6g9q1pMHmvLZxkxc5LAioog27rMaELFkCyG79nS1ppciYBGHGg6sfBoFEbPEHJ8cZ5YsEVXWGHU5CmrTJJae674GzEsbXQbdrZX2AvcnUg1EKFo59SSbqvfzhnvE1eN95yU6X9nmigA39ux",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64c35ecd0a7e76bd8055fc2dc86c53a9c49156b82abd7f7a9fc9b761697d3fe37206072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "4aeec5fc302bbbb1d339687206759a8ab91321fa25ac3454cb95d43f86aa56d3",
"value": 1000000,
"index": 1,
"outputBlockId": "94bc65df5765da1afa3183b16efc7b2e5582ddcdebbe94ea4e071f1826de3ede",
"outputTransactionId": "96c6b65e9366e961a6fbe83662de22f7d978a5d8e0070aced3b60b2573acbef2",
"outputIndex": 0,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e20008a3b597bd494557adf7d0d0a3b6ba32f935cf52f83f46a6b1233333a487a510100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfCuknDpV3PzizoM2efhYNFH3o7uHxSjqDTXCRdcV2F4vMAbtG8fxGWK9ZxWniTZ6GFE5mT7DEpU6W6piUfh32UkeqxrkxS1Gb6KitQDAbSnrTwCceBFbSkmGRLmPxi26PrzREXVVz4UnXjm1xmFrng6vu6NtPvPfEzz1a4asj856HV8Pq1mMx3UgNfeA",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64270150e06772c90f006c9252ef6c18ac683dcb1a7fc085880e394417e685af4708072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "b2bc7e962fba8829d3f95a487c6c3758603b3796b86b9e158e2c258cec3483e5",
"transactionId": "ddfd0982d5740806ba429c8a708f5e99b2a2aecaf1145a79d61e20fb7008a835",
"blockId": "589f24ecf8a4a97b838ba1531b09ea8931a9ea7a8ed7b7d0612e358a6de0148d",
"value": 1000000,
"index": 0,
"globalIndex": 36395398,
"creationHeight": 1185839,
"settlementHeight": 1185843,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: Coll(-34,-82,-49,91,100,-70,-42,-11,87,11,-83,10,97,12,78,72,73,87,-49,71,-126,48,-124,0,-68,-112,64,76,29,20,16,-38)\n3: Coll(3,-110,8,-68,78,-17,-102,3,-24,-41,-117,-122,99,-93,1,-69,95,-83,-36,-89,-117,-31,-99,127,-27,53,-77,-58,76,-66,-2,66)\n4: Coll(-120,48,97,44,82,53,95,111,40,13,18,-105,-15,-97,103,-80,120,-55,-38,-89,-41,-80,75,69,-100,-111,-52,100,73,87,-62,-128)\n5: Coll(-117,-57,-113,28,106,-82,-55,30,98,-114,21,-49,102,-116,22,-52,30,-101,-40,-28,-71,-73,-31,109,99,24,-75,-11,35,-91,-23,-67)\n6: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n7: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n8: Coll(58,17,-107,92,71,25,-27,-120,-68,-26,-89,97,29,39,-67,31,-33,-37,87,56,92,-82,-30,102,-40,4,12,-119,79,28,46,29)\n9: Coll(9,-126,15,-53,-120,113,-5,69,12,62,6,-73,-53,94,39,-80,69,80,-121,-93,102,98,26,-99,-34,117,-126,-96,25,17,30,62)\n10: 0\n11: 0\n12: Coll(-81,24,111,-17,71,1,117,-104,-101,-100,-110,29,15,-116,-47,-122,41,-26,46,-107,57,-112,-127,101,-62,-17,-124,28,-126,66,-23,-75)\n13: 0\n14: 6\n15: 0\n16: 1\n17: 1\n18: 33\n19: 1\n20: 2\n21: 1\n22: 33\n23: 2\n24: 3\n25: 1\n26: 33\n27: 3\n28: 4\n29: 1\n30: 33\n31: 4\n32: 5\n33: 1\n34: 33\n35: 5\n36: 6\n37: 1\n38: 33\n39: 6\n40: 7\n41: 1\n42: 33\n43: 0\n44: 1\n45: 33\n46: 0\n47: 0\n48: 1\n49: 1",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val b2 = getVar[Byte](1.toByte).get\n val i3 = b2.toInt\n val box4 = INPUTS(placeholder[Int](1))\n val coll5 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4), placeholder[Coll[Byte]](5), placeholder[Coll[Byte]](6), placeholder[\n Coll[Byte]\n ](7), placeholder[Coll[Byte]](8), placeholder[Coll[Byte]](9)\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val box6 = OUTPUTS(placeholder[Int](10))\n val coll7 = box6.tokens\n val coll8 = SELF.tokens\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](11))._1 == placeholder[Coll[Byte]](12), (i3 >= placeholder[Int](13)) && (i3 <= placeholder[Int](14)), anyOf(\n Coll[Boolean](\n (b2 == placeholder[Byte](15)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](16)).get.slice(placeholder[Int](17), placeholder[Int](18))\n ), (b2 == placeholder[Byte](19)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](20)).get.slice(placeholder[Int](21), placeholder[Int](22))\n ), (b2 == placeholder[Byte](23)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](24)).get.slice(placeholder[Int](25), placeholder[Int](26))\n ), (b2 == placeholder[Byte](27)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](28)).get.slice(placeholder[Int](29), placeholder[Int](30))\n ), (b2 == placeholder[Byte](31)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](32)).get.slice(placeholder[Int](33), placeholder[Int](34))\n ), (b2 == placeholder[Byte](35)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))\n ), (b2 == placeholder[Byte](39)) && (\n blake2b256(box4.propositionBytes) == coll5(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))\n )\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box6.propositionBytes) == coll5(placeholder[Int](43)).get.slice(placeholder[Int](44), placeholder[Int](45)), coll7(\n placeholder[Int](46)\n ) == coll8(placeholder[Int](47)), coll7(placeholder[Int](48))._1 == coll8(placeholder[Int](49))._1\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "bc57367811c3158252b29476525930d3deebb03a178e85ae90dd7d8aca938674",
"index": 0,
"amount": 1,
"name": "MyFirstDAO Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "00de06c61282578684b377ffd6314c38ce596f2c054107fe2314810677859269",
"index": 1,
"amount": 1101000000001,
"name": "MyFirstDAOToken",
"decimals": 6,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107ee99f5a2a2638086b680aa3a0200000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1705407063671,1002070000000,1,0,0,0,0]"
},
"R6": {
"serializedValue": "1d050280d2aceda93a80acf1f6a93a020000020000023232023232",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[1002050000000,1002060000000],[0,0],[0,0],[25,25],[25,25]]"
},
"R8": {
"serializedValue": "110280dac40900",
"sigmaType": "Coll[SLong]",
"renderedValue": "[10000000,0]"
},
"R7": {
"serializedValue": "0c3c6464024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e16090007200069f6d2885a79da10cee13acca4bb61a2c273e7eb8bbcac77c93be4c97015806d010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c640209e7856307f2be6c9e5046536d41c6aaacfcd0684d8249c4f62f6776c74f8db3010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "bc9f3fe1fa743371c6c6d49f540d68d3a24b37ce919683ceed815e2fd3405b1b",
"mainChain": true
},
{
"boxId": "fb8f4afc0661bafabf0e3c4b73664e1a332aa90b27f3e10983a7d299cdb37a5f",
"transactionId": "ddfd0982d5740806ba429c8a708f5e99b2a2aecaf1145a79d61e20fb7008a835",
"blockId": "589f24ecf8a4a97b838ba1531b09ea8931a9ea7a8ed7b7d0612e358a6de0148d",
"value": 1000000,
"index": 1,
"globalIndex": 36395399,
"creationHeight": 1185839,
"settlementHeight": 1185843,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(-17,-60,-10,3,-34,-90,4,18,-122,-88,-97,91,-43,22,-84,-106,-22,91,37,-38,79,8,-41,108,105,39,-32,29,97,-78,42,-33)\n3: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n4: Coll(73,50,-62,-121,84,-14,-28,-6,-72,-24,90,-8,-18,61,-21,91,-66,73,36,-73,88,84,102,-46,13,-18,-44,-55,-98,65,-111,-94)\n5: 0\n6: 2\n7: 0\n8: 6\n9: 37\n10: 5\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 1\n17: 4\n18: 0\n19: 8\n20: 8\n21: 8\n22: -1\n23: 0\n24: 8\n25: 16\n26: 0\n27: 0\n28: 1\n29: 0\n30: 3\n31: 0\n32: 0\n33: 0\n34: 2\n35: 0\n36: 4\n37: 0\n38: 0\n39: 0\n40: 0\n41: 100\n42: 0\n43: 100\n44: CBigInt(0)\n45: CBigInt(0)\n46: 0\n47: 8\n48: 8\n49: 16\n50: 0\n51: 0\n52: 8\n53: 8\n54: 8\n55: CBigInt(0)\n56: true\n57: 0\n58: 0\n59: 0\n60: 0\n61: 0\n62: 0\n63: CBigInt(0)\n64: 0\n65: 0\n66: 1\n67: 1\n68: 1\n69: 0\n70: Coll(-81,24,111,-17,71,1,117,-104,-101,-100,-110,29,15,-116,-47,-122,41,-26,46,-107,57,-112,-127,101,-62,-17,-124,28,-126,66,-23,-75)\n71: 0\n72: 0\n73: 6\n74: 38\n75: 0\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 1\n82: 0\n83: 1\n84: 8\n85: 16\n86: 0\n87: 0\n88: 1\n89: 1\n90: 33\n91: 1\n92: 1\n93: 0\n94: 0\n95: 2\n96: 5\n97: 2\n98: 5\n99: 10\n100: 78\n101: -58\n102: 31\n103: 72\n104: 91\n105: -104\n106: -21\n107: -121\n108: 21\n109: 63\n110: 124\n111: 87\n112: -37\n113: 79\n114: 94\n115: -51\n116: 117\n117: 85\n118: 111\n119: -35\n120: -68\n121: 64\n122: 59\n123: 65\n124: -84\n125: -8\n126: 68\n127: 31\n128: -34\n129: -114\n130: 22\n131: 9\n132: 0\n133: 5",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box2.tokens\n val coll4 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4)), getVar[Coll[Byte]](0.toByte).get\n )\n val coll5 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll6 = coll5.map({(tuple6: (Coll[Byte], Coll[Byte])) => tuple6._1 })\n val coll7 = coll6.indices\n val coll8 = box2.R4[Coll[AvlTree]].get\n val avlTree9 = coll8(placeholder[Int](5))\n val coll10 = box2.R5[Coll[Long]].get\n val i11 = coll10.size\n val coll12 = coll4(placeholder[Int](6)).get\n val coll13 = coll12.slice(placeholder[Int](7), coll12.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll14 = coll10.slice(placeholder[Int](10), i11).append(\n coll13.map(\n {(i14: Int) =>\n coll12.slice(\n placeholder[Int](11) + placeholder[Int](12) * i14 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i14 + placeholder[Int](16)\n )\n }\n ).slice(i11 - placeholder[Int](17), coll13.size).map({(coll14: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll15 = coll14.indices\n val coll16 = avlTree9.getMany(coll6, getVar[Coll[Byte]](2.toByte).get).map({(opt16: Option[Coll[Byte]]) => if (opt16.isDefined) { coll15.map({(i18: Int) =>\n val i20 = i18 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(opt16.get.slice(i20, i20 + placeholder[Int](21)))\n }) } else { coll14.map({(l18: Long) => placeholder[Long](22) }) } })\n val coll17 = box2.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple18 = coll17(placeholder[Int](23))\n val avlTree19 = tuple18._1\n val coll20 = avlTree19.getMany(coll6, getVar[Coll[Byte]](3.toByte).get).map(\n {(opt20: Option[Coll[Byte]]) => byteArrayToLong(opt20.get.slice(placeholder[Int](24), placeholder[Int](25))) }\n )\n val coll21 = box2.R6[Coll[Coll[Long]]].get\n val l22 = coll21(placeholder[Int](26))(placeholder[Int](27))\n val l23 = coll21(placeholder[Int](28))(placeholder[Int](29))\n val coll24 = coll21(placeholder[Int](30))\n val b25 = if (l23 > placeholder[Long](31)) { coll24(placeholder[Int](32)).toByte } else { placeholder[Byte](33) }\n val l26 = coll21(placeholder[Int](34))(placeholder[Int](35))\n val coll27 = coll21(placeholder[Int](36))\n val b28 = if (l26 > placeholder[Long](37)) { coll27(placeholder[Int](38)).toByte } else { placeholder[Byte](39) }\n val b29 = b25 + b28\n val b30 = if (b29.toInt > placeholder[Int](40)) { max(placeholder[Byte](41) - b29, placeholder[Byte](42)) } else { placeholder[Byte](43) }\n val bi31 = placeholder[BigInt](44)\n val bi32 = placeholder[BigInt](45)\n val b33 = b29 + b30\n val avlTree34 = tuple18._2\n val coll35 = avlTree34.getMany(coll6, getVar[Coll[Byte]](5.toByte).get).map({(opt35: Option[Coll[Byte]]) => if (opt35.isDefined) {(\n val coll37 = opt35.get\n (byteArrayToLong(coll37.slice(placeholder[Int](46), placeholder[Int](47))), byteArrayToLong(coll37.slice(placeholder[Int](48), placeholder[Int](49))))\n )} else { (placeholder[Long](50), placeholder[Long](51)) } })\n val coll36 = box2.R8[Coll[Long]].get\n val coll37 = coll5.map({(tuple37: (Coll[Byte], Coll[Byte])) => coll15.map({(i39: Int) =>\n val i41 = i39 * placeholder[Int](52) + placeholder[Int](53)\n byteArrayToLong(tuple37._2.slice(i41, i41 + placeholder[Int](54)))\n }) })\n val tuple38 = (coll36.map({(l38: Long) => placeholder[BigInt](55) }), placeholder[Boolean](56))\n val coll39 = coll36.indices.map({(i39: Int) => coll7.map({(i41: Int) =>\n val coll43 = coll16(i41)\n if (coll43(placeholder[Int](57)) >= placeholder[Long](58)) {(\n val coll44 = coll36.map({(l44: Long) =>\n val bi46 = l44.toBigInt\n coll20(i41).toBigInt * bi46 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](59)) { coll35(i41)._1.toBigInt * bi46 / l23.toBigInt * coll24(placeholder[Int](60)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](61)) { coll35(i41)._2.toBigInt * bi46 / l26.toBigInt * coll27(placeholder[Int](62)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll44, coll43.zip(coll44).map({(tuple45: (Long, BigInt)) => tuple45._1.toBigInt + tuple45._2 }) == coll37(i41).map({(l45: Long) => l45.toBigInt }))\n )} else { tuple38 }\n }).fold(placeholder[BigInt](63), {(tuple41: (BigInt, (Coll[BigInt], Boolean))) => tuple41._1 + tuple41._2._1(i39) }) })\n val box40 = OUTPUTS(placeholder[Int](64))\n val coll41 = box40.R5[Coll[Long]].get\n val coll42 = box40.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple43 = coll42(placeholder[Int](65))\n val coll44 = tuple43._1.digest\n val coll45 = box40.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](66))\n val bool47 = tuple43._2 == avlTree34\n val bool48 = coll42.slice(placeholder[Int](67), coll42.size) == coll17.slice(placeholder[Int](68), coll17.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](69))._1 == placeholder[Coll[Byte]](70), coll3(placeholder[Int](71))._1 == coll4(placeholder[Int](72)).get.slice(\n placeholder[Int](73), placeholder[Int](74)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll16(i49)\n if (coll51(placeholder[Int](75)) >= placeholder[Long](76)) {(\n val coll52 = coll36.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll20(i49).toBigInt * bi54 / l22.toBigInt * b30.toBigInt + if (b25.toInt > placeholder[Int](77)) { coll35(i49)._1.toBigInt * bi54 / l23.toBigInt * coll24(placeholder[Int](78)).toBigInt } else { bi31 } + if (b28.toInt > placeholder[Int](79)) { coll35(i49)._2.toBigInt * bi54 / l26.toBigInt * coll27(placeholder[Int](80)).toBigInt } else { bi32 } / b33.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll37(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple38 }._2\n })), coll10(placeholder[Int](81)).toBigInt + coll39(placeholder[Int](82)) == coll41(placeholder[Int](83)).toBigInt, avlTree19.remove(\n coll6, getVar[Coll[Byte]](4.toByte).get\n ).get.digest == coll44, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](84), placeholder[Int](85))) > placeholder[Long](86) }\n ), getVar[Coll[Byte]](6.toByte).get\n ).get.digest == coll45(placeholder[Int](87)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](88)).get.slice(placeholder[Int](89), placeholder[Int](90)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box40.value == box2.value, box40.tokens == coll3, coll45(placeholder[Int](91)).digest == coll8(placeholder[Int](92)).digest, bool47, bool48, coll41(\n placeholder[Int](93)\n ) == coll10(placeholder[Int](94)), coll41.slice(placeholder[Int](95), placeholder[Int](96)) == coll10.slice(\n placeholder[Int](97), placeholder[Int](98)\n ), box40.R6[Coll[Coll[Long]]].get == coll21, bool48, bool47, box40.R8[Coll[Long]].get == coll36\n )\n ), (coll5.size >= placeholder[Int](99)) || (\n coll44 == Coll[Byte](\n placeholder[Byte](100), placeholder[Byte](101), placeholder[Byte](102), placeholder[Byte](103), placeholder[Byte](104), placeholder[Byte](\n 105\n ), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108), placeholder[Byte](109), placeholder[Byte](110), placeholder[Byte](\n 111\n ), placeholder[Byte](112), placeholder[Byte](113), placeholder[Byte](114), placeholder[Byte](115), placeholder[Byte](116), placeholder[Byte](\n 117\n ), placeholder[Byte](118), placeholder[Byte](119), placeholder[Byte](120), placeholder[Byte](121), placeholder[Byte](122), placeholder[Byte](\n 123\n ), placeholder[Byte](124), placeholder[Byte](125), placeholder[Byte](126), placeholder[Byte](127), placeholder[Byte](128), placeholder[Byte](\n 129\n ), placeholder[Byte](130), placeholder[Byte](131), placeholder[Byte](132)\n )\n ), coll15.forall({(i49: Int) => coll41.slice(placeholder[Int](133), coll41.size)(i49).toBigInt == coll14(i49).toBigInt - coll39(i49) })\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "e67895b557ead8a700866259daa27b553debe2a94b37d281c5c06d44ea11b9ce",
"mainChain": true
},
{
"boxId": "816fe0e24c7f4dd7fdca2197af09556e61fc400305f2424da64f5f8e15a03acb",
"transactionId": "ddfd0982d5740806ba429c8a708f5e99b2a2aecaf1145a79d61e20fb7008a835",
"blockId": "589f24ecf8a4a97b838ba1531b09ea8931a9ea7a8ed7b7d0612e358a6de0148d",
"value": 150000,
"index": 2,
"globalIndex": 36395400,
"creationHeight": 1185839,
"settlementHeight": 1185843,
"ergoTree": "0008cd023812ba777e72f8e606cda4d4faa2288d439a16cd7c462dc12d3e10a317b019e7",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(3812ba,bc1fbe,...)))}",
"address": "9ewkq1bvnTdmEc7zwmVBxN8rKri8cYNQbgJtMLUxLsFu5AcDCWE",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 100,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "5cf1f986458d1836cd79b78822d502fef1a715f5b9f77553356312715d7ed3fc",
"mainChain": true
},
{
"boxId": "588014408bf48ec4c9c4a8537e7767d4c06a6a00eca1306f2316767b552e120a",
"transactionId": "ddfd0982d5740806ba429c8a708f5e99b2a2aecaf1145a79d61e20fb7008a835",
"blockId": "589f24ecf8a4a97b838ba1531b09ea8931a9ea7a8ed7b7d0612e358a6de0148d",
"value": 4850000,
"index": 3,
"globalIndex": 36395401,
"creationHeight": 1185839,
"settlementHeight": 1185843,
"ergoTree": "1005040004000e36100204a00b08cd0279be667ef9dcbbac55a06295ce870b07029bfcdb2dce28d959f2815b16f81798ea02d192a39a8cc7a701730073011001020402d19683030193a38cc7b2a57300000193c2b2a57301007473027303830108cdeeac93b1a57304",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(16,2,4,-96,11,8,-51,2,121,-66,102,126,-7,-36,-69,-84,85,-96,98,-107,-50,-121,11,7,2,-101,-4,-37,45,-50,40,-39,89,-14,-127,91,22,-8,23,-104,-22,2,-47,-110,-93,-102,-116,-57,-89,1,115,0,115,1)\n3: Coll(1)\n4: 1",
"ergoTreeScript": "{sigmaProp(\n allOf(\n Coll[Boolean](\n HEIGHT == OUTPUTS(placeholder[Int](0)).creationInfo._1, OUTPUTS(placeholder[Int](1)).propositionBytes == substConstants(\n placeholder[Coll[Byte]](2), placeholder[Coll[Int]](3), Coll[SigmaProp](proveDlog(decodePoint(minerPubKey)))\n ), OUTPUTS.size == placeholder[Int](4)\n )\n )\n)}",
"address": "2iHkR7CWvD1R4j1yZg5bkeDRQavjAaVPeTDFGGLZduHyfWMuYpmhHocX8GJoaieTx78FntzJbCBVL6rf96ocJoZdmWBL2fci7NqWgAirppPQmZ7fN9V6z13Ay6brPriBKYqLp1bT2Fk4FkFLCfdPpe",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "512d06316809911ab09d096fcd2df7ebfa1438cc35e29e2fdedfcbb1aafad213",
"mainChain": true
},
{
"boxId": "bfa1ad27dd163f165d766224027959d3663b05b24022e27edf57eb1927886a2c",
"transactionId": "ddfd0982d5740806ba429c8a708f5e99b2a2aecaf1145a79d61e20fb7008a835",
"blockId": "589f24ecf8a4a97b838ba1531b09ea8931a9ea7a8ed7b7d0612e358a6de0148d",
"value": 485000000,
"index": 4,
"globalIndex": 36395402,
"creationHeight": 1185839,
"settlementHeight": 1185843,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(70,47,-51,40,84,79,105,33,97,72,49,118,-95,49,53,51,38,-4,105,80,-75,64,-64,-125,107,-100,93,-25,52,-91,-35,-37)\n3: false\n4: Coll(0,64,-82,101,12,78,-41,123,-51,32,57,20,-109,-85,-24,76,26,-101,-75,-114,-24,-114,-121,-15,86,112,-56,1,-30,-4,89,-125)\n5: Coll(91,-49,-15,2,37,67,102,120,12,-43,25,18,87,5,10,110,-45,58,-59,-47,46,-17,14,48,65,57,-19,93,-104,31,75,-6)\n6: 0\n7: 0\n8: 0\n9: 1\n10: 0\n11: 0\n12: 0\n13: 0\n14: Coll(-119,46,111,71,-95,13,92,-112,-72,122,-44,-122,51,85,-50,-83,0,-61,-30,-104,50,23,-18,21,83,50,83,-51,-102,96,37,-62)\n15: Coll(79,-40,-80,-42,-39,-126,66,114,111,87,-77,-33,-90,-122,18,103,-110,-72,-27,5,110,29,81,-74,-23,13,104,-128,-49,45,-51,-59)\n16: 0\n17: 0\n18: Coll(34,94,63,-59,-47,-119,-11,71,-39,-58,38,-66,-67,-58,113,57,-117,108,0,124,120,61,-60,127,-112,63,36,-65,127,52,-124,121)\n19: Coll(-68,74,90,-71,-28,90,-73,75,121,-6,-20,-65,103,73,108,-62,-65,-116,43,14,85,-37,-24,-84,-49,-61,-99,20,-119,17,116,-112)\n20: Coll(118,124,-86,-128,-71,-114,73,106,-40,-87,-10,-119,-60,65,10,-28,83,50,127,15,-107,-23,80,-124,-64,-82,32,99,80,121,59,119)\n21: 0\n22: 1\n23: 9\n24: 2\n25: 1\n26: 2\n27: 1\n28: 33\n29: 0\n30: 0\n31: 3\n32: 1\n33: 9\n34: 0\n35: 0\n36: 1\n37: 1\n38: 9\n39: 1\n40: 1\n41: 1\n42: 33\n43: Coll(-20,-14,-48,75,-82,72,-96,10,-118,110,73,-64,86,114,99,-55,-11,-46,63,38,-56,35,88,-95,118,-85,-47,-16,33,-40,-79,48)\n44: 1\n45: 1\n46: 9\n47: 0\n48: 0\n49: 0\n50: 1\n51: 9\n52: 1\n53: 0\n54: 1\n55: 33\n56: 1\n57: 1\n58: false",
"ergoTreeScript": "{\n val bool1 = INPUTS.exists({(box1: Box) =>\n val coll3 = box1.tokens\n if (coll3.size > placeholder[Int](0)) { coll3(placeholder[Int](1))._1 == placeholder[Coll[Byte]](2) } else { placeholder[Boolean](3) }\n })\n val coll2 = placeholder[Coll[Byte]](4)\n val coll3 = placeholder[Coll[Byte]](5)\n sigmaProp(anyOf(Coll[Boolean](bool1, if (!bool1) {(\n val box4 = OUTPUTS(placeholder[Int](6))\n val coll5 = box4.R5[Coll[Long]].get\n val box6 = INPUTS(placeholder[Int](7))\n val coll7 = SELF.propositionBytes\n val box8 = OUTPUTS.filter({(box8: Box) => box8.propositionBytes == coll7 })(placeholder[Int](8))\n val coll9 = CONTEXT.dataInputs\n val avlTree10 = coll9(placeholder[Int](9)).R4[AvlTree].get\n val coll11 = getVar[Coll[Byte]](0.toByte).get\n val coll12 = INPUTS.filter({(box12: Box) => box12.propositionBytes == coll7 })\n val l13 = coll12.fold(placeholder[Long](10), {(tuple13: (Long, Box)) => tuple13._1 + tuple13._2.value })\n val coll14 = box8.tokens\n val func15 = {(coll15: Coll[Byte]) => coll12.flatMap({(box17: Box) => box17.tokens }).fold(placeholder[Long](11), {(tuple17: (Long, (Coll[Byte], Long))) =>\n val tuple19 = tuple17._2\n tuple17._1 + if (tuple19._1 == coll15) { tuple19._2 } else { placeholder[Long](12) }\n }) }\n val l16 = func15(coll2)\n val coll17 = coll9(placeholder[Int](13)).R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](14), placeholder[Coll[Byte]](15)), getVar[Coll[Byte]](1.toByte).get)\n val bool18 = coll14.filter({(tuple18: (Coll[Byte], Long)) => tuple18._1 != coll2 }).forall({(tuple18: (Coll[Byte], Long)) => tuple18._2 == func15(tuple18._1) })\n val bool19 = coll12.flatMap({(box19: Box) => box19.tokens }).forall({(tuple19: (Coll[Byte], Long)) =>\n val coll21 = tuple19._1\n (coll21 == coll2) || box8.tokens.exists({(tuple22: (Coll[Byte], Long)) => tuple22._1 == coll21 })\n })\n if (coll5(placeholder[Int](16)) > box6.R5[Coll[Long]].get(placeholder[Int](17))) {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](18), placeholder[Coll[Byte]](19), placeholder[Coll[Byte]](20), coll3), coll11)\n val l21 = byteArrayToLong(coll20(placeholder[Int](21)).get.slice(placeholder[Int](22), placeholder[Int](23))) * coll5(placeholder[Int](24)) + placeholder[Long](25)\n val tuple22 = OUTPUTS.filter({(box22: Box) => blake2b256(box22.propositionBytes) == coll20(placeholder[Int](26)).get.slice(placeholder[Int](27), placeholder[Int](28)) })(placeholder[Int](29)).tokens(placeholder[Int](30))\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](31)).get.slice(placeholder[Int](32), placeholder[Int](33))), coll14.fold(placeholder[Long](34), {(tuple23: (Long, (Coll[Byte], Long))) =>\n val tuple25 = tuple23._2\n tuple23._1 + if (tuple25._1 == coll2) { tuple25._2 } else { placeholder[Long](35) }\n }) >= l16 - l21 - byteArrayToLong(coll20(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38))), bool18, bool19, tuple22._1 == coll2, tuple22._2 >= l21, blake2b256(INPUTS(placeholder[Int](39)).propositionBytes) == coll17(placeholder[Int](40)).get.slice(placeholder[Int](41), placeholder[Int](42))))\n )} else {(\n val coll20 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](43), coll3), coll11)\n allOf(Coll[Boolean](box8.value >= l13 - byteArrayToLong(coll20(placeholder[Int](44)).get.slice(placeholder[Int](45), placeholder[Int](46))), coll14.fold(placeholder[Long](47), {(tuple21: (Long, (Coll[Byte], Long))) =>\n val tuple23 = tuple21._2\n tuple21._1 + if (tuple23._1 == coll2) { tuple23._2 } else { placeholder[Long](48) }\n }) >= l16 - byteArrayToLong(coll20(placeholder[Int](49)).get.slice(placeholder[Int](50), placeholder[Int](51))), bool18, bool19, blake2b256(INPUTS(placeholder[Int](52)).propositionBytes) == coll17(placeholder[Int](53)).get.slice(placeholder[Int](54), placeholder[Int](55)), box4.tokens(placeholder[Int](56))._2 == box6.tokens(placeholder[Int](57))._2))\n )}\n )} else { placeholder[Boolean](58) })))\n}",
"address": "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",
"assets": [
{
"tokenId": "0040ae650c4ed77bcd20391493abe84c1a9bb58ee88e87f15670c801e2fc5983",
"index": 0,
"amount": 99969893,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "bc9f3fe1fa743371c6c6d49f540d68d3a24b37ce919683ceed815e2fd3405b1b",
"mainChain": true
}
],
"size": 8589,
"isUnconfirmed": false
}