Transaction
ID: b81377a92c...2afa
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.00225 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.37475 ERG
Tokens:
99,999.26
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.00225 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0005 ERG
Tokens:
0
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0015 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.37275 ERG
Tokens:
99,999.25
Transaction Details
Confirmations: 750,592
Total coins transferred: 0.378 ERG
Fees: 0.0015 ERG
Fees per byte: 0.000000186 ERG
Raw Transaction Data
{
"id": "b81377a92c4cdbff9aa55feee69b62ea56a367d9d1a58b43007cb5ba50f12afa",
"blockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"inclusionHeight": 1009141,
"timestamp": 1684751287043,
"index": 8,
"globalIndex": 5246218,
"numConfirmations": 750592,
"inputs": [
{
"boxId": "52c5e9b88aa78cfb66419897e631b32552343332efb5f617376790b6e2c2d9ee",
"value": 2250000,
"index": 0,
"spendingProof": null,
"outputBlockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"outputTransactionId": "6ba8a5a248aa4dacf1cd5667f46e72ec4c4ed2950966a26b317cc150140ecda4",
"outputIndex": 0,
"outputGlobalIndex": 29337521,
"outputCreatedAt": 1009139,
"outputSettledAt": 1009141,
"ergoTree": "1032040004020e20deaecf5b64bad6f5570bad0a610c4e484957cf4782308400bc90404c1d1410da0e20039208bc4eef9a03e8d78b8663a301bb5faddca78be19d7fe535b3c64cbefe420e208830612c52355f6f280d1297f19f67b078c9daa7d7b04b459c91cc644957c2800e208bc78f1c6aaec91e628e15cf668c16cc1e9bd8e4b9b7e16d6318b5f523a5e9bd0e204fd8b0d6d98242726f57b3dfa686126792b8e5056e1d51b6e90d6880cf2dcdc50e20892e6f47a10d5c90b87ad4863355cead00c3e2983217ee15533253cd9a6025c20e203a11955c4719e588bce6a7611d27bd1fdfdb57385caee266d8040c894f1c2e1d0e2009820fcb8871fb450c3e06b7cb5e27b0455087a366621a9dde7582a019111e3e040004000e203150f0f28939a532468870430736a92c123113dafba3fb02def757af7b87f18e0400040c02000402040204420201040404020442020204060402044202030408040204420204040a040204420205040c040204420206040e040204420400040204420400040004020402d808d601b2db6501fe730000d602e4e30102d6037e720204d604b2a4730100d605dc640be4c6720104640283080e73027303730473057306730773087309e4e3000ed606b2a5730a00d607db63087206d608db6308a7d196830401938cb2db63087201730b0001730ced927203730d907203730e97830701ed937202730f93cbc27204b4e4b2720573100073117312ed937202731393cbc27204b4e4b2720573140073157316ed937202731793cbc27204b4e4b272057318007319731aed937202731b93cbc27204b4e4b27205731c00731d731eed937202731f93cbc27204b4e4b2720573200073217322ed937202732393cbc27204b4e4b2720573240073257326ed937202732793cbc27204b4e4b272057328007329732a9683030193cbc27206b4e4b27205732b00732c732d93b27207732e00b27208732f00938cb27207733000018cb2720873310001",
"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(49,80,-16,-14,-119,57,-91,50,70,-120,112,67,7,54,-87,44,18,49,19,-38,-5,-93,-5,2,-34,-9,87,-81,123,-121,-15,-114)\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": "30fb30ef8f8cedda7ded3cb0943c2885b4c2d1e3f421a14ee5b09f21a688ce06",
"index": 0,
"amount": 1,
"name": "bPaideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2cbd1b0a99ffa349da735b75e2d77ec41f4c6a98193a8c79918036be9f8242a0",
"index": 1,
"amount": 999630150102,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107d0bcebe2876280fc8f8e280200000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1684670345000,5383520000,1,0,0,0,0]"
},
"R6": {
"serializedValue": "1d0504a094a5fe21c0e1c88324e0aeec882680fc8f8e280400000000040000000004141414140414141414",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[4561610000,4835580000,5109550000,5383520000],[0,0,0,0],[0,0,0,0],[10,10,10,10],[10,10,10,10]]"
},
"R8": {
"serializedValue": "1d0402a0cda385020002a0cda385020002a0cda385020002a0cda3850200",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[273970000,0],[273970000,0],[273970000,0],[273970000,0]]"
},
"R7": {
"serializedValue": "0c3c64640493c137bd53bb0f8c095f9419fea8ade518507c9f85d04d73f49f7d2d154d5217010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720006e43d6a84c9125898db8552ff5ca658e179d4e0e510bfe4a3e07688c0c634ebc010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720006b091e7c90e370bb3cde49ad9c91d27208edaba8d27402e54afe3c6a4ca80786010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720009b17ec003961d9188c3df1e2731b73c856385b4ded069815873cc884d0ab0b77010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c64029b17ec003961d9188c3df1e2731b73c856385b4ded069815873cc884d0ab0b77010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
}
},
{
"boxId": "42f8d8c6a79e150f5ff47def56668c686baf813ecbeb535f6de35807b0fee704",
"value": 1000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"outputTransactionId": "a0c34a3d396780f22278e12021f1d10b80e7a90835c68d1eec3ed26ce339a08b",
"outputIndex": 1,
"outputGlobalIndex": 29337517,
"outputCreatedAt": 1009139,
"outputSettledAt": 1009141,
"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: 0\n53: 8\n54: 8\n55: 8\n56: CBigInt(0)\n57: true\n58: 0\n59: 0\n60: 1\n61: 1\n62: 1\n63: 0\n64: Coll(49,80,-16,-14,-119,57,-91,50,70,-120,112,67,7,54,-87,44,18,49,19,-38,-5,-93,-5,2,-34,-9,87,-81,123,-121,-15,-114)\n65: 0\n66: 0\n67: 6\n68: 38\n69: 0\n70: 0\n71: 0\n72: 0\n73: 0\n74: 0\n75: 1\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 0\n82: CBigInt(0)\n83: 0\n84: 1\n85: 8\n86: 16\n87: 0\n88: 0\n89: 1\n90: 1\n91: 33\n92: 1\n93: 1\n94: 0\n95: 0\n96: 2\n97: 2",
"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 = getVar[Coll[Byte]](2.toByte).get\n val coll11 = box2.R5[Coll[Long]].get\n val i12 = coll11.size\n val coll13 = coll4(placeholder[Int](6)).get\n val coll14 = coll13.slice(placeholder[Int](7), coll13.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll15 = coll11.slice(placeholder[Int](10), i12).append(\n coll14.map(\n {(i15: Int) =>\n coll13.slice(\n placeholder[Int](11) + placeholder[Int](12) * i15 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i15 + placeholder[Int](16)\n )\n }\n ).slice(i12 - placeholder[Int](17), coll14.size).map({(coll15: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll16 = coll15.indices\n val coll17 = avlTree9.getMany(coll6, coll10).map({(opt17: Option[Coll[Byte]]) => if (opt17.isDefined) { coll16.map({(i19: Int) =>\n val i21 = i19 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(opt17.get.slice(i21, i21 + placeholder[Int](21)))\n }) } else { coll15.map({(l19: Long) => placeholder[Long](22) }) } })\n val coll18 = box2.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple19 = coll18(placeholder[Int](23))\n val avlTree20 = tuple19._1\n val coll21 = avlTree20.getMany(coll6, getVar[Coll[Byte]](3.toByte).get).map(\n {(opt21: Option[Coll[Byte]]) => byteArrayToLong(opt21.get.slice(placeholder[Int](24), placeholder[Int](25))) }\n )\n val coll22 = box2.R6[Coll[Coll[Long]]].get\n val l23 = coll22(placeholder[Int](26))(placeholder[Int](27))\n val l24 = coll22(placeholder[Int](28))(placeholder[Int](29))\n val coll25 = coll22(placeholder[Int](30))\n val b26 = if (l24 > placeholder[Long](31)) { coll25(placeholder[Int](32)).toByte } else { placeholder[Byte](33) }\n val l27 = coll22(placeholder[Int](34))(placeholder[Int](35))\n val coll28 = coll22(placeholder[Int](36))\n val b29 = if (l27 > placeholder[Long](37)) { coll28(placeholder[Int](38)).toByte } else { placeholder[Byte](39) }\n val b30 = b26 + b29\n val b31 = if (b30.toInt > placeholder[Int](40)) { max(placeholder[Byte](41) - b30, placeholder[Byte](42)) } else { placeholder[Byte](43) }\n val bi32 = placeholder[BigInt](44)\n val bi33 = placeholder[BigInt](45)\n val b34 = b30 + b31\n val avlTree35 = tuple19._2\n val coll36 = avlTree35.getMany(coll6, getVar[Coll[Byte]](5.toByte).get).map({(opt36: Option[Coll[Byte]]) => if (opt36.isDefined) {(\n val coll38 = opt36.get\n (byteArrayToLong(coll38.slice(placeholder[Int](46), placeholder[Int](47))), byteArrayToLong(coll38.slice(placeholder[Int](48), placeholder[Int](49))))\n )} else { (placeholder[Long](50), placeholder[Long](51)) } })\n val coll37 = box2.R8[Coll[Coll[Long]]].get\n val coll38 = coll37(placeholder[Int](52))\n val coll39 = coll5.map({(tuple39: (Coll[Byte], Coll[Byte])) => coll16.map({(i41: Int) =>\n val i43 = i41 * placeholder[Int](53) + placeholder[Int](54)\n byteArrayToLong(tuple39._2.slice(i43, i43 + placeholder[Int](55)))\n }) })\n val tuple40 = (coll38.map({(l40: Long) => placeholder[BigInt](56) }), placeholder[Boolean](57))\n val box41 = OUTPUTS(placeholder[Int](58))\n val coll42 = box41.R5[Coll[Long]].get\n val coll43 = box41.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple44 = coll43(placeholder[Int](59))\n val coll45 = box41.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](60))\n val bool47 = tuple44._2 == avlTree35\n val bool48 = coll43.slice(placeholder[Int](61), coll43.size) == coll18.slice(placeholder[Int](62), coll18.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](63))._1 == placeholder[Coll[Byte]](64), coll3(placeholder[Int](65))._1 == coll4(placeholder[Int](66)).get.slice(\n placeholder[Int](67), placeholder[Int](68)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll17(i49)\n if (coll51(placeholder[Int](69)) >= placeholder[Long](70)) {(\n val coll52 = coll38.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll21(i49).toBigInt * bi54 / l23.toBigInt * b31.toBigInt + if (b26.toInt > placeholder[Int](71)) { coll36(i49)._1.toBigInt * bi54 / l24.toBigInt * coll25(placeholder[Int](72)).toBigInt } else { bi32 } + if (b29.toInt > placeholder[Int](73)) { coll36(i49)._2.toBigInt * bi54 / l27.toBigInt * coll28(placeholder[Int](74)).toBigInt } else { bi33 } / b34.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll39(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple40 }._2\n })), coll11(placeholder[Int](75)).toBigInt + coll7.map({(i49: Int) =>\n val coll51 = coll17(i49)\n if (coll51(placeholder[Int](76)) >= placeholder[Long](77)) {(\n val coll52 = coll38.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll21(i49).toBigInt * bi54 / l23.toBigInt * b31.toBigInt + if (b26.toInt > placeholder[Int](78)) { coll36(i49)._1.toBigInt * bi54 / l24.toBigInt * coll25(placeholder[Int](79)).toBigInt } else { bi32 } + if (b29.toInt > placeholder[Int](80)) { coll36(i49)._2.toBigInt * bi54 / l27.toBigInt * coll28(placeholder[Int](81)).toBigInt } else { bi33 } / b34.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll39(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple40 }\n }).fold(placeholder[BigInt](82), {(tuple49: (BigInt, (Coll[BigInt], Boolean))) => tuple49._1 + tuple49._2._1(placeholder[Int](83)) }) == coll42(\n placeholder[Int](84)\n ).toBigInt, avlTree20.remove(coll6, getVar[Coll[Byte]](4.toByte).get).get.digest == tuple44._1.digest, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](85), placeholder[Int](86))) > placeholder[Long](87) }\n ), coll10\n ).get.digest == coll45(placeholder[Int](88)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](89)).get.slice(placeholder[Int](90), placeholder[Int](91)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box41.value == box2.value, box41.tokens == coll3, coll45(placeholder[Int](92)).digest == coll8(placeholder[Int](93)).digest, bool47, bool48, coll42(\n placeholder[Int](94)\n ) == coll11(placeholder[Int](95)), coll42.slice(placeholder[Int](96), coll42.size) == coll11.slice(placeholder[Int](97), i12), box41.R6[\n Coll[Coll[Long]]\n ].get == coll22, bool48, bool47, box41.R8[Coll[Coll[Long]]].get == coll37\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "3400ff2dedf79c34c3684c9a5352d58532c425bd8a8ec6892f0964bef341de56",
"value": 374750000,
"index": 2,
"spendingProof": null,
"outputBlockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"outputTransactionId": "6ba8a5a248aa4dacf1cd5667f46e72ec4c4ed2950966a26b317cc150140ecda4",
"outputIndex": 5,
"outputGlobalIndex": 29337526,
"outputCreatedAt": 1009139,
"outputSettledAt": 1009141,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(48,113,-22,97,57,-57,-89,109,-51,123,-51,-34,7,91,-126,11,-105,-114,54,-75,-61,-57,89,-13,21,-42,68,-44,102,84,67,5)\n3: false\n4: Coll(44,-67,27,10,-103,-1,-93,73,-38,115,91,117,-30,-41,126,-60,31,76,106,-104,25,58,-116,121,-111,-128,54,-66,-97,-126,66,-96)\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: 0\n15: 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)\n16: 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)\n17: 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)\n18: 0\n19: 1\n20: 9\n21: 2\n22: 1\n23: 2\n24: 1\n25: 33\n26: 0\n27: 0\n28: 3\n29: 1\n30: 9\n31: 0\n32: 0\n33: 1\n34: 1\n35: 9\n36: 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)\n37: 1\n38: 1\n39: 9\n40: 0\n41: 0\n42: 0\n43: 1\n44: 9\n45: 1\n46: 1\n47: 1\n48: 1\n49: 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 = box6.R5[Coll[Long]].get\n val coll8 = SELF.propositionBytes\n val box9 = OUTPUTS.filter({(box9: Box) => box9.propositionBytes == coll8 })(placeholder[Int](8))\n val avlTree10 = CONTEXT.dataInputs(placeholder[Int](9)).R4[AvlTree].get\n val coll11 = getVar[Coll[Byte]](0.toByte).get\n val coll12 = INPUTS.filter({(box12: Box) => box12.propositionBytes == coll8 })\n val l13 = coll12.fold(placeholder[Long](10), {(tuple13: (Long, Box)) => tuple13._1 + tuple13._2.value })\n val coll14 = box9.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 bool17 = coll14.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 != coll2 }).forall({(tuple17: (Coll[Byte], Long)) => tuple17._2 == func15(tuple17._1) })\n val bool18 = coll12.flatMap({(box18: Box) => box18.tokens }).forall({(tuple18: (Coll[Byte], Long)) =>\n val coll20 = tuple18._1\n (coll20 == coll2) || box9.tokens.exists({(tuple21: (Coll[Byte], Long)) => tuple21._1 == coll20 })\n })\n if (coll5(placeholder[Int](13)) > coll7(placeholder[Int](14))) {(\n val coll19 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](15), placeholder[Coll[Byte]](16), placeholder[Coll[Byte]](17), coll3), coll11)\n val l20 = byteArrayToLong(coll19(placeholder[Int](18)).get.slice(placeholder[Int](19), placeholder[Int](20))) * coll5(placeholder[Int](21)) + placeholder[Long](22)\n val tuple21 = OUTPUTS.filter({(box21: Box) => blake2b256(box21.propositionBytes) == coll19(placeholder[Int](23)).get.slice(placeholder[Int](24), placeholder[Int](25)) })(placeholder[Int](26)).tokens(placeholder[Int](27))\n allOf(Coll[Boolean](box9.value >= l13 - byteArrayToLong(coll19(placeholder[Int](28)).get.slice(placeholder[Int](29), placeholder[Int](30))), coll14.fold(placeholder[Long](31), {(tuple22: (Long, (Coll[Byte], Long))) =>\n val tuple24 = tuple22._2\n tuple22._1 + if (tuple24._1 == coll2) { tuple24._2 } else { placeholder[Long](32) }\n }) >= l16 - l20 - byteArrayToLong(coll19(placeholder[Int](33)).get.slice(placeholder[Int](34), placeholder[Int](35))), bool17, bool18, tuple21._1 == coll2, tuple21._2 >= l20))\n )} else {(\n val coll19 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](36), coll3), coll11)\n allOf(Coll[Boolean](box9.value >= l13 - byteArrayToLong(coll19(placeholder[Int](37)).get.slice(placeholder[Int](38), placeholder[Int](39))), coll14.fold(placeholder[Long](40), {(tuple20: (Long, (Coll[Byte], Long))) =>\n val tuple22 = tuple20._2\n tuple20._1 + if (tuple22._1 == coll2) { tuple22._2 } else { placeholder[Long](41) }\n }) >= l16 - byteArrayToLong(coll19(placeholder[Int](42)).get.slice(placeholder[Int](43), placeholder[Int](44))), bool17, bool18, coll5(placeholder[Int](45)) > coll7(placeholder[Int](46)), box4.tokens(placeholder[Int](47))._2 == box6.tokens(placeholder[Int](48))._2))\n )}\n )} else { placeholder[Boolean](49) })))\n}",
"address": "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",
"assets": [
{
"tokenId": "2cbd1b0a99ffa349da735b75e2d77ec41f4c6a98193a8c79918036be9f8242a0",
"index": 0,
"amount": 999992577,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "44230de89d5b333d36b2ed960fcbfbd4d5b8b47b0a0f7c529b2270235f0ee4e1",
"value": 1000000,
"index": 0,
"outputBlockId": "46a55d64366a87aee1573ea0f9eb8cc3e9bb1cbe375d75842a381c44d8b0f2f0",
"outputTransactionId": "f934d4cacd20406210afa579692ab450313bdc19f9789791627a5e0918d7a531",
"outputIndex": 2,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e203071ea6139c7a76dcd7bcdde075b820b978e36b5c3c759f315d644d4665443050100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfUtEnzZVfYMoFo8REtotZo5A93TgULLHjkvSC7oEAELzqkU61A5HrFVhvT96bTET9cNcZ925f4ewrLdEycp1SULEpRDKdEFZcTsTuUHhvHYggg2R2GWNZE2wTb7FG7Gp6jzNrNrhAZKhEHqr42WN5Aw6Xq9JtvigcVAgJKZ5E2d5FuYLfzKdK5cUzn2p",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "642e25ffa44ec9e804fb6b78ca6530dd504939f4c8e6b794c85c3935f164fd598407072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "961d012ca118f5a2e92073f7e073ff4883edf28a46425974652f6fd1ff11b2d9",
"transactionId": "b81377a92c4cdbff9aa55feee69b62ea56a367d9d1a58b43007cb5ba50f12afa",
"blockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"value": 2250000,
"index": 0,
"globalIndex": 29337527,
"creationHeight": 1009139,
"settlementHeight": 1009141,
"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(49,80,-16,-14,-119,57,-91,50,70,-120,112,67,7,54,-87,44,18,49,19,-38,-5,-93,-5,2,-34,-9,87,-81,123,-121,-15,-114)\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": "30fb30ef8f8cedda7ded3cb0943c2885b4c2d1e3f421a14ee5b09f21a688ce06",
"index": 0,
"amount": 1,
"name": "bPaideia Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2cbd1b0a99ffa349da735b75e2d77ec41f4c6a98193a8c79918036be9f8242a0",
"index": 1,
"amount": 999630150102,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107d0bcebe28762a0c9b3932a0200000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1684670345000,5657490000,1,0,0,0,0]"
},
"R6": {
"serializedValue": "1d0504a094a5fe21c0e1c88324e0aeec882680fc8f8e280400000000040000000004141414140414141414",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[4561610000,4835580000,5109550000,5383520000],[0,0,0,0],[0,0,0,0],[10,10,10,10],[10,10,10,10]]"
},
"R8": {
"serializedValue": "1d0402a0cda385020002a0cda385020002a0cda385020002a0cda3850200",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[273970000,0],[273970000,0],[273970000,0],[273970000,0]]"
},
"R7": {
"serializedValue": "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",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c6402b18beef4053229685bc3649b229874d0e2f369849cc32a7555474b75bbc1b314010720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "8ad03157c1e90184589c424b5b65ce99ce2f69c36b8bba7ad69e8bf5c53860a9",
"mainChain": true
},
{
"boxId": "3a76cc201e4ed5955f7b052be1f75bf0bb79b8d67f86fc5900c41195ff4e7bec",
"transactionId": "b81377a92c4cdbff9aa55feee69b62ea56a367d9d1a58b43007cb5ba50f12afa",
"blockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"value": 1000000,
"index": 1,
"globalIndex": 29337528,
"creationHeight": 1009139,
"settlementHeight": 1009141,
"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: 0\n53: 8\n54: 8\n55: 8\n56: CBigInt(0)\n57: true\n58: 0\n59: 0\n60: 1\n61: 1\n62: 1\n63: 0\n64: Coll(49,80,-16,-14,-119,57,-91,50,70,-120,112,67,7,54,-87,44,18,49,19,-38,-5,-93,-5,2,-34,-9,87,-81,123,-121,-15,-114)\n65: 0\n66: 0\n67: 6\n68: 38\n69: 0\n70: 0\n71: 0\n72: 0\n73: 0\n74: 0\n75: 1\n76: 0\n77: 0\n78: 0\n79: 0\n80: 0\n81: 0\n82: CBigInt(0)\n83: 0\n84: 1\n85: 8\n86: 16\n87: 0\n88: 0\n89: 1\n90: 1\n91: 33\n92: 1\n93: 1\n94: 0\n95: 0\n96: 2\n97: 2",
"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 = getVar[Coll[Byte]](2.toByte).get\n val coll11 = box2.R5[Coll[Long]].get\n val i12 = coll11.size\n val coll13 = coll4(placeholder[Int](6)).get\n val coll14 = coll13.slice(placeholder[Int](7), coll13.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll15 = coll11.slice(placeholder[Int](10), i12).append(\n coll14.map(\n {(i15: Int) =>\n coll13.slice(\n placeholder[Int](11) + placeholder[Int](12) * i15 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i15 + placeholder[Int](16)\n )\n }\n ).slice(i12 - placeholder[Int](17), coll14.size).map({(coll15: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll16 = coll15.indices\n val coll17 = avlTree9.getMany(coll6, coll10).map({(opt17: Option[Coll[Byte]]) => if (opt17.isDefined) { coll16.map({(i19: Int) =>\n val i21 = i19 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(opt17.get.slice(i21, i21 + placeholder[Int](21)))\n }) } else { coll15.map({(l19: Long) => placeholder[Long](22) }) } })\n val coll18 = box2.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple19 = coll18(placeholder[Int](23))\n val avlTree20 = tuple19._1\n val coll21 = avlTree20.getMany(coll6, getVar[Coll[Byte]](3.toByte).get).map(\n {(opt21: Option[Coll[Byte]]) => byteArrayToLong(opt21.get.slice(placeholder[Int](24), placeholder[Int](25))) }\n )\n val coll22 = box2.R6[Coll[Coll[Long]]].get\n val l23 = coll22(placeholder[Int](26))(placeholder[Int](27))\n val l24 = coll22(placeholder[Int](28))(placeholder[Int](29))\n val coll25 = coll22(placeholder[Int](30))\n val b26 = if (l24 > placeholder[Long](31)) { coll25(placeholder[Int](32)).toByte } else { placeholder[Byte](33) }\n val l27 = coll22(placeholder[Int](34))(placeholder[Int](35))\n val coll28 = coll22(placeholder[Int](36))\n val b29 = if (l27 > placeholder[Long](37)) { coll28(placeholder[Int](38)).toByte } else { placeholder[Byte](39) }\n val b30 = b26 + b29\n val b31 = if (b30.toInt > placeholder[Int](40)) { max(placeholder[Byte](41) - b30, placeholder[Byte](42)) } else { placeholder[Byte](43) }\n val bi32 = placeholder[BigInt](44)\n val bi33 = placeholder[BigInt](45)\n val b34 = b30 + b31\n val avlTree35 = tuple19._2\n val coll36 = avlTree35.getMany(coll6, getVar[Coll[Byte]](5.toByte).get).map({(opt36: Option[Coll[Byte]]) => if (opt36.isDefined) {(\n val coll38 = opt36.get\n (byteArrayToLong(coll38.slice(placeholder[Int](46), placeholder[Int](47))), byteArrayToLong(coll38.slice(placeholder[Int](48), placeholder[Int](49))))\n )} else { (placeholder[Long](50), placeholder[Long](51)) } })\n val coll37 = box2.R8[Coll[Coll[Long]]].get\n val coll38 = coll37(placeholder[Int](52))\n val coll39 = coll5.map({(tuple39: (Coll[Byte], Coll[Byte])) => coll16.map({(i41: Int) =>\n val i43 = i41 * placeholder[Int](53) + placeholder[Int](54)\n byteArrayToLong(tuple39._2.slice(i43, i43 + placeholder[Int](55)))\n }) })\n val tuple40 = (coll38.map({(l40: Long) => placeholder[BigInt](56) }), placeholder[Boolean](57))\n val box41 = OUTPUTS(placeholder[Int](58))\n val coll42 = box41.R5[Coll[Long]].get\n val coll43 = box41.R7[Coll[(AvlTree, AvlTree)]].get\n val tuple44 = coll43(placeholder[Int](59))\n val coll45 = box41.R4[Coll[AvlTree]].get\n val box46 = OUTPUTS(placeholder[Int](60))\n val bool47 = tuple44._2 == avlTree35\n val bool48 = coll43.slice(placeholder[Int](61), coll43.size) == coll18.slice(placeholder[Int](62), coll18.size)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](63))._1 == placeholder[Coll[Byte]](64), coll3(placeholder[Int](65))._1 == coll4(placeholder[Int](66)).get.slice(\n placeholder[Int](67), placeholder[Int](68)\n ), allOf(coll7.map({(i49: Int) =>\n val coll51 = coll17(i49)\n if (coll51(placeholder[Int](69)) >= placeholder[Long](70)) {(\n val coll52 = coll38.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll21(i49).toBigInt * bi54 / l23.toBigInt * b31.toBigInt + if (b26.toInt > placeholder[Int](71)) { coll36(i49)._1.toBigInt * bi54 / l24.toBigInt * coll25(placeholder[Int](72)).toBigInt } else { bi32 } + if (b29.toInt > placeholder[Int](73)) { coll36(i49)._2.toBigInt * bi54 / l27.toBigInt * coll28(placeholder[Int](74)).toBigInt } else { bi33 } / b34.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll39(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple40 }._2\n })), coll11(placeholder[Int](75)).toBigInt + coll7.map({(i49: Int) =>\n val coll51 = coll17(i49)\n if (coll51(placeholder[Int](76)) >= placeholder[Long](77)) {(\n val coll52 = coll38.map({(l52: Long) =>\n val bi54 = l52.toBigInt\n coll21(i49).toBigInt * bi54 / l23.toBigInt * b31.toBigInt + if (b26.toInt > placeholder[Int](78)) { coll36(i49)._1.toBigInt * bi54 / l24.toBigInt * coll25(placeholder[Int](79)).toBigInt } else { bi32 } + if (b29.toInt > placeholder[Int](80)) { coll36(i49)._2.toBigInt * bi54 / l27.toBigInt * coll28(placeholder[Int](81)).toBigInt } else { bi33 } / b34.toBigInt\n })\n (coll52, coll51.zip(coll52).map({(tuple53: (Long, BigInt)) => tuple53._1.toBigInt + tuple53._2 }) == coll39(i49).map({(l53: Long) => l53.toBigInt }))\n )} else { tuple40 }\n }).fold(placeholder[BigInt](82), {(tuple49: (BigInt, (Coll[BigInt], Boolean))) => tuple49._1 + tuple49._2._1(placeholder[Int](83)) }) == coll42(\n placeholder[Int](84)\n ).toBigInt, avlTree20.remove(coll6, getVar[Coll[Byte]](4.toByte).get).get.digest == tuple44._1.digest, avlTree9.update(\n coll5.filter(\n {(tuple49: (Coll[Byte], Coll[Byte])) => byteArrayToLong(tuple49._2.slice(placeholder[Int](85), placeholder[Int](86))) > placeholder[Long](87) }\n ), coll10\n ).get.digest == coll45(placeholder[Int](88)).digest, allOf(\n Coll[Boolean](\n blake2b256(box46.propositionBytes) == coll4(placeholder[Int](89)).get.slice(placeholder[Int](90), placeholder[Int](91)), box46.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n box41.value == box2.value, box41.tokens == coll3, coll45(placeholder[Int](92)).digest == coll8(placeholder[Int](93)).digest, bool47, bool48, coll42(\n placeholder[Int](94)\n ) == coll11(placeholder[Int](95)), coll42.slice(placeholder[Int](96), coll42.size) == coll11.slice(placeholder[Int](97), i12), box41.R6[\n Coll[Coll[Long]]\n ].get == coll22, bool48, bool47, box41.R8[Coll[Coll[Long]]].get == coll37\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "8eaf921b30df3274e6154e65c6d8b1d4a8330b76fd7e85acab7b279a738f099b",
"mainChain": true
},
{
"boxId": "9452fe9b448cdecaaec707e50d68ae89e0571c0433278a7febb8b9c912ae3a4d",
"transactionId": "b81377a92c4cdbff9aa55feee69b62ea56a367d9d1a58b43007cb5ba50f12afa",
"blockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"value": 500000,
"index": 2,
"globalIndex": 29337529,
"creationHeight": 1009139,
"settlementHeight": 1009141,
"ergoTree": "0008cd03553448c194fdd843c87d080f5e8ed983f5bb2807b13b45a9683bba8c7bfb5ae8",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(553448,8bebb3,...)))}",
"address": "9h7L7sUHZk43VQC3PHtSp5ujAWcZtYmWATBH746wi75C5XHi68b",
"assets": [
{
"tokenId": "2cbd1b0a99ffa349da735b75e2d77ec41f4c6a98193a8c79918036be9f8242a0",
"index": 0,
"amount": 100,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "e3cb89011738127f98fbe72ce0751d2dcd35f039b4a8a35c4952a6cfbe70067f",
"mainChain": true
},
{
"boxId": "1d2848a00934cf80482442893fcb28a41f7746a62e9a3f75273a9a76681e8f8a",
"transactionId": "b81377a92c4cdbff9aa55feee69b62ea56a367d9d1a58b43007cb5ba50f12afa",
"blockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"value": 1500000,
"index": 3,
"globalIndex": 29337530,
"creationHeight": 1009139,
"settlementHeight": 1009141,
"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": "42c6fbd88af185a99f187f3d00ccce925b5e305bf0ecacd3078c96b89bca14b6",
"mainChain": true
},
{
"boxId": "3f1628da68c8abf9046ebc307bae9488e98571c895f88e42bc845d3cf9399101",
"transactionId": "b81377a92c4cdbff9aa55feee69b62ea56a367d9d1a58b43007cb5ba50f12afa",
"blockId": "ac27a62b6b7c15efd7d0f945ffce9d60d4a5d736e9826719f016e2efdec0c0c7",
"value": 372750000,
"index": 4,
"globalIndex": 29337531,
"creationHeight": 1009139,
"settlementHeight": 1009141,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(48,113,-22,97,57,-57,-89,109,-51,123,-51,-34,7,91,-126,11,-105,-114,54,-75,-61,-57,89,-13,21,-42,68,-44,102,84,67,5)\n3: false\n4: Coll(44,-67,27,10,-103,-1,-93,73,-38,115,91,117,-30,-41,126,-60,31,76,106,-104,25,58,-116,121,-111,-128,54,-66,-97,-126,66,-96)\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: 0\n15: 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)\n16: 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)\n17: 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)\n18: 0\n19: 1\n20: 9\n21: 2\n22: 1\n23: 2\n24: 1\n25: 33\n26: 0\n27: 0\n28: 3\n29: 1\n30: 9\n31: 0\n32: 0\n33: 1\n34: 1\n35: 9\n36: 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)\n37: 1\n38: 1\n39: 9\n40: 0\n41: 0\n42: 0\n43: 1\n44: 9\n45: 1\n46: 1\n47: 1\n48: 1\n49: 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 = box6.R5[Coll[Long]].get\n val coll8 = SELF.propositionBytes\n val box9 = OUTPUTS.filter({(box9: Box) => box9.propositionBytes == coll8 })(placeholder[Int](8))\n val avlTree10 = CONTEXT.dataInputs(placeholder[Int](9)).R4[AvlTree].get\n val coll11 = getVar[Coll[Byte]](0.toByte).get\n val coll12 = INPUTS.filter({(box12: Box) => box12.propositionBytes == coll8 })\n val l13 = coll12.fold(placeholder[Long](10), {(tuple13: (Long, Box)) => tuple13._1 + tuple13._2.value })\n val coll14 = box9.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 bool17 = coll14.filter({(tuple17: (Coll[Byte], Long)) => tuple17._1 != coll2 }).forall({(tuple17: (Coll[Byte], Long)) => tuple17._2 == func15(tuple17._1) })\n val bool18 = coll12.flatMap({(box18: Box) => box18.tokens }).forall({(tuple18: (Coll[Byte], Long)) =>\n val coll20 = tuple18._1\n (coll20 == coll2) || box9.tokens.exists({(tuple21: (Coll[Byte], Long)) => tuple21._1 == coll20 })\n })\n if (coll5(placeholder[Int](13)) > coll7(placeholder[Int](14))) {(\n val coll19 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](15), placeholder[Coll[Byte]](16), placeholder[Coll[Byte]](17), coll3), coll11)\n val l20 = byteArrayToLong(coll19(placeholder[Int](18)).get.slice(placeholder[Int](19), placeholder[Int](20))) * coll5(placeholder[Int](21)) + placeholder[Long](22)\n val tuple21 = OUTPUTS.filter({(box21: Box) => blake2b256(box21.propositionBytes) == coll19(placeholder[Int](23)).get.slice(placeholder[Int](24), placeholder[Int](25)) })(placeholder[Int](26)).tokens(placeholder[Int](27))\n allOf(Coll[Boolean](box9.value >= l13 - byteArrayToLong(coll19(placeholder[Int](28)).get.slice(placeholder[Int](29), placeholder[Int](30))), coll14.fold(placeholder[Long](31), {(tuple22: (Long, (Coll[Byte], Long))) =>\n val tuple24 = tuple22._2\n tuple22._1 + if (tuple24._1 == coll2) { tuple24._2 } else { placeholder[Long](32) }\n }) >= l16 - l20 - byteArrayToLong(coll19(placeholder[Int](33)).get.slice(placeholder[Int](34), placeholder[Int](35))), bool17, bool18, tuple21._1 == coll2, tuple21._2 >= l20))\n )} else {(\n val coll19 = avlTree10.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](36), coll3), coll11)\n allOf(Coll[Boolean](box9.value >= l13 - byteArrayToLong(coll19(placeholder[Int](37)).get.slice(placeholder[Int](38), placeholder[Int](39))), coll14.fold(placeholder[Long](40), {(tuple20: (Long, (Coll[Byte], Long))) =>\n val tuple22 = tuple20._2\n tuple20._1 + if (tuple22._1 == coll2) { tuple22._2 } else { placeholder[Long](41) }\n }) >= l16 - byteArrayToLong(coll19(placeholder[Int](42)).get.slice(placeholder[Int](43), placeholder[Int](44))), bool17, bool18, coll5(placeholder[Int](45)) > coll7(placeholder[Int](46)), box4.tokens(placeholder[Int](47))._2 == box6.tokens(placeholder[Int](48))._2))\n )}\n )} else { placeholder[Boolean](49) })))\n}",
"address": "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",
"assets": [
{
"tokenId": "2cbd1b0a99ffa349da735b75e2d77ec41f4c6a98193a8c79918036be9f8242a0",
"index": 0,
"amount": 999992477,
"name": "bPaideia",
"decimals": 4,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "8ad03157c1e90184589c424b5b65ce99ce2f69c36b8bba7ad69e8bf5c53860a9",
"mainChain": true
}
],
"size": 8074,
"isUnconfirmed": false
}