Transaction
ID: 8eec95840c...8679
Inputs (6)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.007 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.002 ERG
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Outputs (12)
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Unspent
Address:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Unspent
Unspent
Unspent
Unspent
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.002 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Transaction Details
Confirmations: 539,947
Total coins transferred: 0.013 ERG
Fees: 0.001 ERG
Fees per byte: 0.000000024 ERG
Raw Transaction Data
{
"id": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"inclusionHeight": 1221279,
"timestamp": 1710494537855,
"index": 4,
"globalIndex": 6822083,
"numConfirmations": 539947,
"inputs": [
{
"boxId": "53aecf2c9f33e256b63f03b30884fa0eb4885aa1ec31186ca8ef1e97166698b0",
"value": 7000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "d0e8d9f498d3ea07f857730236607731ed642d0fdabe9f065424652eb708a14b",
"outputTransactionId": "0426f10ff8818f1f7838f1ab61b6991a579c5d777a7ef0e2c65c545845cee7b7",
"outputIndex": 0,
"outputGlobalIndex": 37943166,
"outputCreatedAt": 1220722,
"outputSettledAt": 1220724,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n3: 0\n4: 1\n5: Coll(91,-28,71,-57,19,-110,-60,48,-80,18,96,72,38,-97,-102,120,-118,-13,85,39,117,95,-84,-23,-46,41,-3,-122,83,14,52,-11)\n6: Coll(-123,-126,49,25,-14,96,-57,-69,-17,91,10,69,78,-79,-26,67,-22,98,-63,27,-91,75,108,40,114,-14,68,-44,66,-3,57,127)\n7: 0\n8: Coll(37,-75,-102,116,0,-35,-76,-39,37,58,20,83,113,-73,-52,-114,-40,97,99,-40,-2,-87,44,-43,112,-116,-122,18,-13,-42,-109,-81)\n9: 0\n10: 5\n11: Coll(61,-86,102,-128,-114,105,-62,90,-23,50,-35,102,97,28,95,11,60,-70,-54,-47,18,82,3,-24,125,-115,-60,-111,-122,28,113,-26)\n12: Coll(32,80,114,111,112,111,115,97,108)\n13: 9223372036854775807\n14: Coll(-70,-86,-101,22,76,-76,-72,13,115,94,16,66,78,38,-92,113,-71,98,28,2,-17,-54,23,70,19,90,-61,-10,-37,16,20,16)\n15: Coll(32,65,99,116,105,111,110)\n16: 9223372036854775807\n17: 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)\n18: Coll(32,83,116,97,107,101,32,83,116,97,116,101)\n19: 1\n20: -1\n21: 0\n22: 1\n23: 1\n24: 33\n25: 48\n26: 0\n27: 1\n28: 33\n29: 10\n30: 0\n31: 0\n32: 0\n33: 0\n34: 32\n35: 2000000\n36: 1\n37: Coll(-46,74,-49,66,15,5,-112,35,-23,116,33,0,-123,30,-74,-83,-115,-104,118,19,-110,-75,-39,118,20,59,96,8,-109,23,106,7)\n38: 0\n39: 1\n40: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val avlTree2 = box1.R4[AvlTree].get\n val coll3 = getVar[Coll[Byte]](1.toByte).get\n val avlTree4 = SELF.R4[AvlTree].get\n sigmaProp(allOf(Coll[Boolean](box1.tokens(placeholder[Int](1))._1 == placeholder[Coll[Byte]](2), if (getVar[Byte](0.toByte).get == placeholder[Byte](3)) {(\n val box5 = OUTPUTS(placeholder[Int](4))\n val coll6 = avlTree2.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](5), placeholder[Coll[Byte]](6)), coll3)\n val tuple7 = box5.tokens(placeholder[Int](7))\n val coll8 = SELF.id\n val coll9 = getVar[Coll[Byte]](3.toByte).get\n val coll10 = avlTree4.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](8)), getVar[Coll[Byte]](2.toByte).get)(placeholder[Int](9)).get\n val coll11 = coll10.slice(placeholder[Int](10), coll10.size)\n val tuple12 = if (coll9 == placeholder[Coll[Byte]](11)) { (coll11.append(placeholder[Coll[Byte]](12)), placeholder[Long](13)) } else { if (coll9 == placeholder[Coll[Byte]](14)) { (coll11.append(placeholder[Coll[Byte]](15)), placeholder[Long](16)) } else { if (coll9 == placeholder[Coll[Byte]](17)) { (coll11.append(placeholder[Coll[Byte]](18)), placeholder[Long](19)) } else { (coll11, placeholder[Long](20)) } } }\n val coll13 = box5.R4[Coll[Byte]].get\n val box14 = OUTPUTS(placeholder[Int](21))\n allOf(Coll[Boolean](allOf(Coll[Boolean](blake2b256(box5.propositionBytes) == coll6(placeholder[Int](22)).get.slice(placeholder[Int](23), placeholder[Int](24)), tuple7._1 == coll8, tuple7._2 == tuple12._2, coll13 == tuple12._1, box5.R5[Coll[Byte]].get == coll13, box5.R6[Coll[Byte]].get == Coll[Byte](placeholder[Byte](25)))), allOf(Coll[Boolean](blake2b256(box14.propositionBytes) == coll6(placeholder[Int](26)).get.slice(placeholder[Int](27), placeholder[Int](28)), box14.tokens == SELF.tokens, box14.R4[AvlTree].get.digest == avlTree4.insert(Coll[(Coll[Byte], Coll[Byte])]((coll9, Coll[Byte](placeholder[Byte](29), placeholder[Byte](30), placeholder[Byte](31), placeholder[Byte](32), placeholder[Byte](33), placeholder[Byte](34)).append(coll8))), getVar[Coll[Byte]](4.toByte).get).get.digest, box14.value >= SELF.value - placeholder[Long](35), box14.R5[Coll[Byte]].get == SELF.R5[Coll[Byte]].get))))\n )} else { blake2b256(INPUTS(placeholder[Int](36)).propositionBytes) == avlTree2.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](37)), coll3)(placeholder[Int](38)).get.slice(placeholder[Int](39), placeholder[Int](40)) })))\n}",
"address": "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",
"assets": [
{
"tokenId": "00c3fd71f6ef5a03d125d11bd5fa5b738ef12dd3104491c243698a4486f139a6",
"index": 0,
"amount": 1,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3503ba6ce5d8bc1332229284c95fff15cf3c1d0b463fdfd6f3c9b57b7af09fe3",
"index": 1,
"amount": 1,
"name": "Good Things DAO Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "64ddade122fb76c989608f53c7cb254fd79e4db6aabe32e3f4d367ffca7c2ed89806072000",
"sigmaType": null,
"renderedValue": null
},
"R5": {
"serializedValue": "0e209a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be",
"sigmaType": "Coll[SByte]",
"renderedValue": "9a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be"
}
}
},
{
"boxId": "0827daf418a2f00a0f1d474590d10165f0d64b869987a6edffe395281c1c5278",
"value": 2000000,
"index": 1,
"spendingProof": null,
"outputBlockId": "b7ada164193065c8466e0b36f04ab0939843338fbe781d625b5a02cd92981a65",
"outputTransactionId": "30a83d689de3a813f72fd991fedac9c0bdcf30a39763bddc952605753373501d",
"outputIndex": 10,
"outputGlobalIndex": 35918414,
"outputCreatedAt": 1173637,
"outputSettledAt": 1173639,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n2: Coll(-121,90,-57,120,55,-56,-44,115,10,-122,-18,34,-128,67,79,98,-112,-83,-101,-32,-76,73,-76,58,-71,44,-77,-34,-101,7,99,55)\n3: Coll(-65,23,-80,-4,-80,121,-100,-67,-107,-64,90,96,11,10,108,-1,-30,83,-64,29,120,-33,-124,107,56,-2,-99,-67,66,109,-90,31)\n4: Coll(30,33,26,-16,124,56,-30,-114,7,75,117,127,39,113,51,117,125,83,-120,111,-78,3,1,-61,-102,52,-45,11,-17,-69,28,-62)\n5: Coll(-67,87,21,19,-28,-29,-27,-80,-50,-3,122,27,97,-24,6,66,71,-91,-97,-56,120,79,108,-16,-69,-45,-95,-91,-124,55,100,79)\n6: Coll(-113,-112,-104,30,7,17,115,-5,27,-72,-40,-105,65,114,10,72,56,-18,102,20,99,90,41,49,87,95,70,-52,27,-94,59,97)\n7: Coll(4,-49,53,5,11,-94,79,13,121,120,-24,-15,104,110,65,-71,-111,-29,88,-20,-69,-38,-80,-48,-1,9,-79,-112,122,68,-120,91)\n8: Coll(-57,71,-35,-2,-114,-81,-32,27,-46,123,39,78,-122,-93,87,-16,-90,-50,102,61,20,25,-30,-14,91,-116,-85,-47,-31,29,-59,102)\n9: Coll(-86,14,126,94,59,100,68,84,-53,73,-18,18,83,-113,-64,-77,-121,44,28,-101,46,49,117,-59,123,-27,8,-30,-51,96,-119,-104)\n10: Coll(14,-44,-42,101,21,102,-43,117,-22,-84,-79,72,0,102,4,113,-77,21,-15,-69,124,-109,-21,13,-21,99,-3,-50,-41,-70,-104,79)\n11: Coll(99,-6,-127,-116,-67,-17,-10,111,109,-124,60,-81,100,101,-5,89,-78,78,3,104,41,-84,59,-71,-78,103,79,-17,42,-11,75,85)\n12: Coll(-4,98,-59,-31,-2,4,-93,-38,-100,28,89,-85,38,85,62,-8,-117,-65,-78,-44,13,-65,-5,-6,22,69,-73,-1,-49,58,-37,30)\n13: Coll(54,81,-127,41,-82,100,93,107,77,-3,-48,44,40,-69,28,90,111,-87,-96,7,-46,62,-62,19,-31,-77,-19,45,13,32,71,82)\n14: Coll(-85,111,-85,11,63,-33,-97,-118,-123,28,-34,80,23,113,62,41,-59,-9,-91,-44,-113,-61,-91,45,26,41,-28,58,-128,7,77,-22)\n15: Coll(103,-36,20,-108,67,49,53,36,52,-105,-117,4,14,3,-47,-56,-104,85,111,85,23,-86,-54,69,17,-54,-75,66,31,-109,-84,-4)\n16: Coll(-92,49,28,114,107,53,-79,-114,-14,43,-125,78,-32,-1,87,-1,55,13,-125,-52,-108,-56,-97,-64,109,-39,125,0,-110,21,-104,113)\n17: Coll(12,-47,45,108,-50,127,-17,93,-86,-112,-76,94,122,11,63,-21,123,-120,-100,-116,-76,-37,-28,88,-8,27,-111,-53,45,-64,-83,-9)\n18: Coll(102,3,28,-67,115,53,-112,117,59,42,-8,-85,-126,-116,-20,-71,93,123,108,-12,-38,101,2,-77,31,-66,-45,13,-97,105,-25,69)\n19: Coll(-61,3,-35,-14,-100,4,3,72,-66,92,49,-127,-66,23,106,-73,94,119,33,-31,83,-50,-1,-125,106,-107,15,-39,5,-99,-125,-51)\n20: Coll(82,-115,-55,-29,10,-98,122,-105,-122,-18,-93,9,63,-35,-50,60,62,-126,-56,127,-28,19,110,5,-102,-76,-93,-70,-95,-92,-11,73)\n21: Coll(-104,-16,-56,-32,-28,6,-38,-87,123,112,89,-128,-108,-71,-26,98,106,-54,-38,-60,25,-38,102,123,77,113,-13,48,100,-8,-43,-35)\n22: Coll(73,118,0,-124,-9,-43,90,-71,4,112,-21,-12,-44,-70,-81,5,125,-117,66,-40,-52,45,-85,97,-98,-38,-94,-103,-118,16,71,-99)\n23: Coll(-77,-96,-29,91,74,2,-34,-95,126,-55,58,42,-124,-57,-35,-128,23,53,53,-64,17,-38,66,-34,91,27,3,-62,106,88,-35,69)\n24: Coll(-18,-85,59,86,-82,63,-53,10,-46,-1,-57,84,-121,72,-50,-29,-50,100,29,-94,-103,-117,74,120,-31,85,-98,-57,50,14,64,69)\n25: Coll(1,54,-18,76,64,-60,-36,95,-70,58,4,-122,-27,7,75,43,-104,17,-114,72,-102,-20,29,10,60,67,37,-10,25,115,-19,-56)\n26: Coll(19,37,111,124,19,57,-63,75,-110,-125,1,-30,90,-27,64,113,-83,73,122,25,47,124,-8,25,62,38,97,-69,14,-83,125,-83)\n27: Coll(110,-98,-11,-34,103,65,69,-105,-39,51,99,-101,20,-36,42,-66,6,36,22,58,-59,110,-74,-93,-80,-79,79,83,-20,-64,80,-88)\n28: 1\n29: 0\n30: Coll(61,-86,102,-128,-114,105,-62,90,-23,50,-35,102,97,28,95,11,60,-70,-54,-47,18,82,3,-24,125,-115,-60,-111,-122,28,113,-26)\n31: Coll(-70,-86,-101,22,76,-76,-72,13,115,94,16,66,78,38,-92,113,-71,98,28,2,-17,-54,23,70,19,90,-61,-10,-37,16,20,16)\n32: Coll(-54,11,-75,-24,-54,-41,24,34,92,-113,45,2,97,-96,-48,-107,-14,93,94,-121,70,10,-122,51,-12,0,-36,60,-55,7,-111,47)\n33: 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)\n34: Coll(65,-13,-104,-128,101,82,-124,94,82,0,-112,50,16,95,89,-27,-53,44,-79,65,-34,99,-52,115,123,109,-103,87,83,-61,110,-127)\n35: 1\n36: 6\n37: 38\n38: 1\n39: 3\n40: 0\n41: 5\n42: 2\n43: 6\n44: 38\n45: 0\n46: 6\n47: 38\n48: 2\n49: 7\n50: 3\n51: 9\n52: 4\n53: 11\n54: 5\n55: 15\n56: 7\n57: 17\n58: 8\n59: 19\n60: 9\n61: 13\n62: 6\n63: 21\n64: 10\n65: 25\n66: 12\n67: 23\n68: 11\n69: 0\n70: 1\n71: 2\n72: 1\n73: 0\n74: Coll(105,109,46,112,97,105,100,101,105,97,46,99,111,110,116,114,97,99,116,115,46,97,99,116,105,111,110,46)\n75: 2\n76: 78\n77: -58\n78: 31\n79: 72\n80: 91\n81: -104\n82: -21\n83: -121\n84: 21\n85: 63\n86: 124\n87: 87\n88: -37\n89: 79\n90: 94\n91: -51\n92: 117\n93: 85\n94: 111\n95: -35\n96: -68\n97: 64\n98: 59\n99: 65\n100: -84\n101: -8\n102: 68\n103: 31\n104: -34\n105: -114\n106: 22\n107: 9\n108: 0\n109: 0\n110: 3\n111: 4\n112: 5\n113: 6\n114: 7\n115: 8\n116: 9\n117: 10\n118: 0\n119: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n120: 2\n121: 1\n122: 6\n123: 7\n124: 32\n125: 4\n126: 1\n127: 6\n128: 2\n129: 32\n130: 6\n131: 1\n132: 6\n133: 33\n134: 35\n135: 32\n136: 8\n137: 1\n138: 6\n139: 7\n140: 9\n141: 32\n142: 10\n143: 1\n144: 6\n145: 11\n146: 32\n147: 12\n148: 1\n149: 6\n150: 31\n151: 32\n152: 16\n153: 1\n154: 6\n155: 70\n156: 32\n157: 18\n158: 1\n159: 6\n160: 24\n161: 32\n162: 20\n163: 1\n164: 6\n165: 135\n166: 32\n167: 14\n168: 1\n169: 6\n170: 28\n171: 32\n172: 22\n173: 1\n174: 6\n175: 12\n176: 32\n177: 26\n178: 1\n179: 6\n180: 27\n181: 32\n182: 24\n183: 1\n184: 6\n185: 63\n186: 32\n187: 0\n188: 1\n189: 33\n190: 1000000\n191: 0\n192: 0\n193: 9223372036854775807\n194: 9223372036854775807\n195: 3\n196: 1\n197: 33\n198: 1000000\n199: 1\n200: 1\n201: Coll(-57,-59,55,-26,-58,53,-109,14,-53,74,-50,-107,-91,73,38,-77,-85,119,105,-115,-97,73,34,-16,-79,-59,-114,-88,113,86,72,59)\n202: Coll(-87,85,-114,65,-122,-53,-43,-86,87,35,-88,82,-44,-63,-36,101,125,-98,-127,67,-126,-1,-120,-115,90,-118,-20,82,21,49,48,29)\n203: 0\n204: 1\n205: Coll(105,109,46,112,97,105,100,101,105,97,46,99,111,110,116,114,97,99,116,115,46,112,114,111,112,111,115,97,108,46)\n206: 2\n207: 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)\n208: 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)\n209: 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)\n210: 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)\n211: 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)\n212: 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)\n213: 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)\n214: 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)\n215: 1\n216: 33\n217: 1000000\n218: 0\n219: 3\n220: 6\n221: 38\n222: 1\n223: 1\n224: 2\n225: 4\n226: 1\n227: 9\n228: 1\n229: 0\n230: 0\n231: 0\n232: 1000000\n233: 1\n234: 33\n235: 1000000\n236: 1\n237: 33\n238: 1000000\n239: 1\n240: 33\n241: 1000000\n242: 1\n243: 33\n244: 1000000\n245: 1\n246: 33\n247: 1000000\n248: 1\n249: 33\n250: 1000000\n251: 1\n252: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val coll2 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](1), placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4), placeholder[Coll[Byte]](5), placeholder[\n Coll[Byte]\n ](6), placeholder[Coll[Byte]](7), placeholder[Coll[Byte]](8), placeholder[Coll[Byte]](9), placeholder[Coll[Byte]](10), placeholder[Coll[Byte]](\n 11\n ), placeholder[Coll[Byte]](12), placeholder[Coll[Byte]](13), placeholder[Coll[Byte]](14), placeholder[Coll[Byte]](15), placeholder[Coll[Byte]](\n 16\n ), placeholder[Coll[Byte]](17), placeholder[Coll[Byte]](18), placeholder[Coll[Byte]](19), placeholder[Coll[Byte]](20), placeholder[Coll[Byte]](\n 21\n ), placeholder[Coll[Byte]](22), placeholder[Coll[Byte]](23), placeholder[Coll[Byte]](24), placeholder[Coll[Byte]](25), placeholder[Coll[Byte]](\n 26\n ), placeholder[Coll[Byte]](27)\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val coll3 = coll2(placeholder[Int](28)).get\n val box4 = INPUTS(placeholder[Int](29))\n val avlTree5 = box4.R4[AvlTree].get\n val coll6 = avlTree5.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](30), placeholder[Coll[Byte]](31), placeholder[Coll[Byte]](32), placeholder[Coll[Byte]](33), placeholder[Coll[Byte]](34)\n ), getVar[Coll[Byte]](1.toByte).get\n )\n val coll7 = coll6(placeholder[Int](35)).get.slice(placeholder[Int](36), placeholder[Int](37))\n val coll8 = Coll[Coll[Byte]](coll7)\n val coll9 = getVar[Coll[Coll[Byte]]](3.toByte).get\n val coll10 = coll9(placeholder[Int](38))\n val coll11 = coll2(placeholder[Int](39)).get\n val coll12 = coll9(placeholder[Int](40))\n val coll13 = coll2(placeholder[Int](41)).get\n val coll14 = coll6(placeholder[Int](42)).get.slice(placeholder[Int](43), placeholder[Int](44))\n val coll15 = coll6(placeholder[Int](45)).get.slice(placeholder[Int](46), placeholder[Int](47))\n val coll16 = Coll[Coll[Byte]](coll14, coll15)\n val coll17 = coll9(placeholder[Int](48))\n val coll18 = coll2(placeholder[Int](49)).get\n val coll19 = coll9(placeholder[Int](50))\n val coll20 = coll2(placeholder[Int](51)).get\n val coll21 = Coll[Coll[Byte]](coll14)\n val coll22 = coll9(placeholder[Int](52))\n val coll23 = coll2(placeholder[Int](53)).get\n val coll24 = coll9(placeholder[Int](54))\n val coll25 = coll2(placeholder[Int](55)).get\n val coll26 = coll9(placeholder[Int](56))\n val coll27 = coll2(placeholder[Int](57)).get\n val coll28 = coll9(placeholder[Int](58))\n val coll29 = coll2(placeholder[Int](59)).get\n val coll30 = coll9(placeholder[Int](60))\n val coll31 = coll2(placeholder[Int](61)).get\n val coll32 = coll9(placeholder[Int](62))\n val coll33 = coll2(placeholder[Int](63)).get\n val coll34 = coll9(placeholder[Int](64))\n val coll35 = coll2(placeholder[Int](65)).get\n val coll36 = coll9(placeholder[Int](66))\n val coll37 = coll2(placeholder[Int](67)).get\n val coll38 = coll9(placeholder[Int](68))\n val box39 = OUTPUTS(placeholder[Int](69))\n val coll40 = box39.tokens\n val coll41 = box4.tokens\n val tuple42 = coll40(placeholder[Int](70))\n val tuple43 = coll40(placeholder[Int](71))\n val box44 = OUTPUTS(placeholder[Int](72))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](73))\n val coll47 = placeholder[Coll[Byte]](74)\n val coll48 = getVar[Coll[Coll[Byte]]](4.toByte).get\n val box49 = OUTPUTS(placeholder[Int](75))\n val coll50 = box49.tokens\n val coll51 = Coll[Byte](\n placeholder[Byte](76), placeholder[Byte](77), placeholder[Byte](78), placeholder[Byte](79), placeholder[Byte](80), placeholder[Byte](81), placeholder[Byte](\n 82\n ), placeholder[Byte](83), placeholder[Byte](84), placeholder[Byte](85), placeholder[Byte](86), placeholder[Byte](87), placeholder[Byte](88), placeholder[\n Byte\n ](89), placeholder[Byte](90), placeholder[Byte](91), placeholder[Byte](92), placeholder[Byte](93), placeholder[Byte](94), placeholder[Byte](\n 95\n ), placeholder[Byte](96), placeholder[Byte](97), placeholder[Byte](98), placeholder[Byte](99), placeholder[Byte](100), placeholder[Byte](101), placeholder[\n Byte\n ](102), placeholder[Byte](103), placeholder[Byte](104), placeholder[Byte](105), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108)\n )\n val coll52 = box49.R5[Coll[Long]].get\n val l53 = coll52(placeholder[Int](109))\n val l54 = CONTEXT.preHeader.timestamp\n val box55 = OUTPUTS(placeholder[Int](110))\n val box56 = OUTPUTS(placeholder[Int](111))\n val box57 = OUTPUTS(placeholder[Int](112))\n val box58 = OUTPUTS(placeholder[Int](113))\n val box59 = OUTPUTS(placeholder[Int](114))\n val box60 = OUTPUTS(placeholder[Int](115))\n val box61 = OUTPUTS(placeholder[Int](116))\n val box62 = OUTPUTS(placeholder[Int](117))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](118))._1 == placeholder[Coll[Byte]](119), allOf(\n Coll[Boolean](\n coll2(placeholder[Int](120)).get.patch(\n placeholder[Int](121), blake2b256(\n substConstants(coll3.slice(placeholder[Int](122), coll3.size), Coll[Int](placeholder[Int](123)), coll8)\n ), placeholder[Int](124)\n ) == coll10, coll2(placeholder[Int](125)).get.patch(\n placeholder[Int](126), blake2b256(\n substConstants(coll11.slice(placeholder[Int](127), coll11.size), Coll[Int](placeholder[Int](128)), coll8)\n ), placeholder[Int](129)\n ) == coll12, coll2(placeholder[Int](130)).get.patch(\n placeholder[Int](131), blake2b256(\n substConstants(coll13.slice(placeholder[Int](132), coll13.size), Coll[Int](placeholder[Int](133), placeholder[Int](134)), coll16)\n ), placeholder[Int](135)\n ) == coll17, coll2(placeholder[Int](136)).get.patch(\n placeholder[Int](137), blake2b256(\n substConstants(coll18.slice(placeholder[Int](138), coll18.size), Coll[Int](placeholder[Int](139), placeholder[Int](140)), coll16)\n ), placeholder[Int](141)\n ) == coll19, coll2(placeholder[Int](142)).get.patch(\n placeholder[Int](143), blake2b256(\n substConstants(coll20.slice(placeholder[Int](144), coll20.size), Coll[Int](placeholder[Int](145)), coll21)\n ), placeholder[Int](146)\n ) == coll22, coll2(placeholder[Int](147)).get.patch(\n placeholder[Int](148), blake2b256(\n substConstants(coll23.slice(placeholder[Int](149), coll23.size), Coll[Int](placeholder[Int](150)), coll21)\n ), placeholder[Int](151)\n ) == coll24, coll2(placeholder[Int](152)).get.patch(\n placeholder[Int](153), blake2b256(\n substConstants(coll25.slice(placeholder[Int](154), coll25.size), Coll[Int](placeholder[Int](155)), coll21)\n ), placeholder[Int](156)\n ) == coll26, coll2(placeholder[Int](157)).get.patch(\n placeholder[Int](158), blake2b256(\n substConstants(coll27.slice(placeholder[Int](159), coll27.size), Coll[Int](placeholder[Int](160)), coll21)\n ), placeholder[Int](161)\n ) == coll28, coll2(placeholder[Int](162)).get.patch(\n placeholder[Int](163), blake2b256(\n substConstants(coll29.slice(placeholder[Int](164), coll29.size), Coll[Int](placeholder[Int](165)), coll21)\n ), placeholder[Int](166)\n ) == coll30, coll2(placeholder[Int](167)).get.patch(\n placeholder[Int](168), blake2b256(\n substConstants(coll31.slice(placeholder[Int](169), coll31.size), Coll[Int](placeholder[Int](170)), coll21)\n ), placeholder[Int](171)\n ) == coll32, coll2(placeholder[Int](172)).get.patch(\n placeholder[Int](173), blake2b256(\n substConstants(coll33.slice(placeholder[Int](174), coll33.size), Coll[Int](placeholder[Int](175)), coll21)\n ), placeholder[Int](176)\n ) == coll34, coll2(placeholder[Int](177)).get.patch(\n placeholder[Int](178), blake2b256(\n substConstants(coll35.slice(placeholder[Int](179), coll35.size), Coll[Int](placeholder[Int](180)), coll21)\n ), placeholder[Int](181)\n ) == coll36, coll2(placeholder[Int](182)).get.patch(\n placeholder[Int](183), blake2b256(\n substConstants(coll37.slice(placeholder[Int](184), coll37.size), Coll[Int](placeholder[Int](185)), coll21)\n ), placeholder[Int](186)\n ) == coll38\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box39.propositionBytes) == coll2(placeholder[Int](187)).get.slice(\n placeholder[Int](188), placeholder[Int](189)\n ), box39.value >= placeholder[Long](190), coll40(placeholder[Int](191)) == coll41(\n placeholder[Int](192)\n ), tuple42._1 == coll15, tuple42._2 == placeholder[Long](193), tuple43._1 == coll7, tuple43._2 == placeholder[Long](\n 194\n ), coll40.size == placeholder[Int](195), box39.R4[Coll[Byte]].get == coll14\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box44.propositionBytes) == coll10.slice(placeholder[Int](196), placeholder[Int](197)), box44.value >= placeholder[Long](\n 198\n ), tuple46._1 == coll14, tuple46._2 == placeholder[Long](199), coll45.size == placeholder[Int](200), box44.R4[\n AvlTree\n ].get.digest == avlTree5.insert(\n Coll[(Coll[Byte], Coll[Byte])](\n (placeholder[Coll[Byte]](201), coll12), (placeholder[Coll[Byte]](202), coll10), (\n blake2b256(coll47.append(coll48(placeholder[Int](203)))), coll17\n ), (blake2b256(coll47.append(coll48(placeholder[Int](204)))), coll19), (\n blake2b256(placeholder[Coll[Byte]](205).append(coll48(placeholder[Int](206)))), coll22\n ), (placeholder[Coll[Byte]](207), coll24), (placeholder[Coll[Byte]](208), coll32), (placeholder[Coll[Byte]](209), coll26), (\n placeholder[Coll[Byte]](210), coll28\n ), (placeholder[Coll[Byte]](211), coll30), (placeholder[Coll[Byte]](212), coll34), (placeholder[Coll[Byte]](213), coll38), (\n placeholder[Coll[Byte]](214), coll36\n )\n ), getVar[Coll[Byte]](2.toByte).get\n ).get.digest\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box49.propositionBytes) == coll34.slice(placeholder[Int](215), placeholder[Int](216)), box49.value >= placeholder[Long](217), coll50(\n placeholder[Int](218)\n )._1 == coll6(placeholder[Int](219)).get.slice(placeholder[Int](220), placeholder[Int](221)), coll50(placeholder[Int](222)) == coll41(\n placeholder[Int](223)\n ), coll50.size == placeholder[Int](224), box49.R4[Coll[AvlTree]].get.forall(\n {(avlTree63: AvlTree) => avlTree63.digest == coll51 }\n ), l53 > l54, l53 < l54 + byteArrayToLong(coll6(placeholder[Int](225)).get.slice(placeholder[Int](226), placeholder[Int](227))), coll52.slice(\n placeholder[Int](228), coll52.size\n ).forall({(l63: Long) => l63 == placeholder[Long](229) }), box49.R6[Coll[Coll[Long]]].get.flatMap({(coll63: Coll[Long]) => coll63 }).forall(\n {(l63: Long) => l63 == placeholder[Long](230) }\n ), box49.R7[Coll[(AvlTree, AvlTree)]].get.forall(\n {(tuple63: (AvlTree, AvlTree)) => (tuple63._1.digest == coll51) && (tuple63._2.digest == coll51) }\n ), box49.R8[Coll[Long]].get.forall({(l63: Long) => l63 == placeholder[Long](231) })\n )\n ), allOf(\n Coll[Boolean](\n box55.value >= placeholder[Long](232), blake2b256(box55.propositionBytes) == coll24.slice(\n placeholder[Int](233), placeholder[Int](234)\n ), box56.value >= placeholder[Long](235), blake2b256(box56.propositionBytes) == coll32.slice(\n placeholder[Int](236), placeholder[Int](237)\n ), box57.value >= placeholder[Long](238), blake2b256(box57.propositionBytes) == coll36.slice(\n placeholder[Int](239), placeholder[Int](240)\n ), box58.value >= placeholder[Long](241), blake2b256(box58.propositionBytes) == coll26.slice(\n placeholder[Int](242), placeholder[Int](243)\n ), box59.value >= placeholder[Long](244), blake2b256(box59.propositionBytes) == coll30.slice(\n placeholder[Int](245), placeholder[Int](246)\n ), box60.value >= placeholder[Long](247), blake2b256(box60.propositionBytes) == coll38.slice(\n placeholder[Int](248), placeholder[Int](249)\n ), box61.value >= placeholder[Long](250), blake2b256(box61.propositionBytes) == coll28.slice(placeholder[Int](251), placeholder[Int](252))\n )\n ), allOf(Coll[Boolean](box62.value >= SELF.value, box62.propositionBytes == SELF.propositionBytes))\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {}
},
{
"boxId": "722919222af0efe5e92b267f6520c21dc35f13a13197d551addd1928a89ec5ca",
"value": 1000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "7b6fa731e5cd806b4696906be74efbd8da58a474f1a6364393016f6c8ee9f445",
"outputTransactionId": "ba3baea583dab06a9a6fc9a915db88db274388bb00cdfe0babecfe0b54b20144",
"outputIndex": 1,
"outputGlobalIndex": 37942806,
"outputCreatedAt": 1220714,
"outputSettledAt": 1220716,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(91,-28,71,-57,19,-110,-60,48,-80,18,96,72,38,-97,-102,120,-118,-13,85,39,117,95,-84,-23,-46,41,-3,-122,83,14,52,-11)\n3: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n4: 0\n5: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n6: 0\n7: 1\n8: 33\n9: 0\n10: 0\n11: 6\n12: 38\n13: 0\n14: 1\n15: 1\n16: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box1.R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3)), getVar[Coll[Byte]](0.toByte).get)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), blake2b256(box2.propositionBytes) == coll3(placeholder[Int](6)).get.slice(\n placeholder[Int](7), placeholder[Int](8)\n ), SELF.tokens(placeholder[Int](9))._1 == box2.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](getVar[Coll[Byte]](2.toByte).get), getVar[Coll[Byte]](1.toByte).get\n )(placeholder[Int](10)).get.slice(placeholder[Int](11), placeholder[Int](12)), blake2b256(OUTPUTS(placeholder[Int](13)).propositionBytes) == coll3(\n placeholder[Int](14)\n ).get.slice(placeholder[Int](15), placeholder[Int](16))\n )\n )\n )\n}",
"address": "3EFHCKeRPVHgyayoQ4uZbb7hxTkzDNWdHxcNDEodajfiCiX3bKNBWy3VooVSsrhPG8rM7DHyLtq2eEufJNxnVKbibiYSxAyBorZtkVsmKdX9BCcdLno8X2E2GfK4TTkM5xW5Nw2GkNLCxP3HMzn1YZo5PfbbMKC8TnhkFjP3iSK9ETUZcoDaDfpjBBQci5v9MKfbinskuV3PuJjk8aEUUup8RBoWcfbbtPmFuWZeoBELh1nFyepjUrvd4ERhuL4KM79GdLmjPynKcK2YzJJjUeokGbV9dzmZCPVQcAoU8LKCQE7MrwJiwRe34pi16zQgHwCp2B4JBvZo4xf8wNYxV5iHBHgoPYTN7SmQAJNLSzUQDY8TJiqbRgAoJJ",
"assets": [
{
"tokenId": "2e1393aa54df7d36eaf52c0d0233b5a0c918e7835d90061a75e4e9f57e48f191",
"index": 0,
"amount": 9223372036854776000,
"name": "Good Things DAO Proposal",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e18476f6f64205468696e67732044414f2050726f706f73616c",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f2050726f706f73616c"
},
"R5": {
"serializedValue": "0e18476f6f64205468696e67732044414f2050726f706f73616c",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f2050726f706f73616c"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
}
}
},
{
"boxId": "e1ecd4b91d399855ce99dd2b558be5f487c7d3aab559bc37d01e7ebf07a8b82a",
"value": 1000000,
"index": 3,
"spendingProof": null,
"outputBlockId": "cd8e1868ae6fb8a91f8ae66832ba86c51ecd0e9b87ebbb1dd8f4f6f4742579a2",
"outputTransactionId": "1ca79052607b9fb669bcb854b9a66c7db489d20520a9818d87b4628ce55529e3",
"outputIndex": 1,
"outputGlobalIndex": 37943080,
"outputCreatedAt": 1220718,
"outputSettledAt": 1220720,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(91,-28,71,-57,19,-110,-60,48,-80,18,96,72,38,-97,-102,120,-118,-13,85,39,117,95,-84,-23,-46,41,-3,-122,83,14,52,-11)\n3: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n4: 0\n5: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n6: 0\n7: 1\n8: 33\n9: 0\n10: 0\n11: 6\n12: 38\n13: 0\n14: 1\n15: 1\n16: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box1.R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3)), getVar[Coll[Byte]](0.toByte).get)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), blake2b256(box2.propositionBytes) == coll3(placeholder[Int](6)).get.slice(\n placeholder[Int](7), placeholder[Int](8)\n ), SELF.tokens(placeholder[Int](9))._1 == box2.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](getVar[Coll[Byte]](2.toByte).get), getVar[Coll[Byte]](1.toByte).get\n )(placeholder[Int](10)).get.slice(placeholder[Int](11), placeholder[Int](12)), blake2b256(OUTPUTS(placeholder[Int](13)).propositionBytes) == coll3(\n placeholder[Int](14)\n ).get.slice(placeholder[Int](15), placeholder[Int](16))\n )\n )\n )\n}",
"address": "3EFHCKeRPVHgyayoQ4uZbb7hxTkzDNWdHxcNDEodajfiCiX3bKNBWy3VooVSsrhPG8rM7DHyLtq2eEufJNxnVKbibiYSxAyBorZtkVsmKdX9BCcdLno8X2E2GfK4TTkM5xW5Nw2GkNLCxP3HMzn1YZo5PfbbMKC8TnhkFjP3iSK9ETUZcoDaDfpjBBQci5v9MKfbinskuV3PuJjk8aEUUup8RBoWcfbbtPmFuWZeoBELh1nFyepjUrvd4ERhuL4KM79GdLmjPynKcK2YzJJjUeokGbV9dzmZCPVQcAoU8LKCQE7MrwJiwRe34pi16zQgHwCp2B4JBvZo4xf8wNYxV5iHBHgoPYTN7SmQAJNLSzUQDY8TJiqbRgAoJJ",
"assets": [
{
"tokenId": "f8a824657dd6fb845dac80450a3320bd010d4070ec700a1abffbd83f5b8be40d",
"index": 0,
"amount": 9223372036854776000,
"name": "Good Things DAO Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e16476f6f64205468696e67732044414f20416374696f6e",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f20416374696f6e"
},
"R5": {
"serializedValue": "0e16476f6f64205468696e67732044414f20416374696f6e",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f20416374696f6e"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
}
}
},
{
"boxId": "a6fc984d293dd15efc90f0fa99eedec8312199b7c193c80988251f4626ac002d",
"value": 1000000,
"index": 4,
"spendingProof": null,
"outputBlockId": "24b56162627954470b80e1c6179e70d5f423b51fe4443e8172726f4c682c3893",
"outputTransactionId": "4c350364cbb1bf29d640f9f1d3d585eedc92582d636528e24a6e3252272e94e7",
"outputIndex": 3,
"outputGlobalIndex": 37942636,
"outputCreatedAt": 1220711,
"outputSettledAt": 1220713,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(91,-28,71,-57,19,-110,-60,48,-80,18,96,72,38,-97,-102,120,-118,-13,85,39,117,95,-84,-23,-46,41,-3,-122,83,14,52,-11)\n3: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n4: 0\n5: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n6: 0\n7: 1\n8: 33\n9: 0\n10: 0\n11: 6\n12: 38\n13: 0\n14: 1\n15: 1\n16: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box1.R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3)), getVar[Coll[Byte]](0.toByte).get)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), blake2b256(box2.propositionBytes) == coll3(placeholder[Int](6)).get.slice(\n placeholder[Int](7), placeholder[Int](8)\n ), SELF.tokens(placeholder[Int](9))._1 == box2.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](getVar[Coll[Byte]](2.toByte).get), getVar[Coll[Byte]](1.toByte).get\n )(placeholder[Int](10)).get.slice(placeholder[Int](11), placeholder[Int](12)), blake2b256(OUTPUTS(placeholder[Int](13)).propositionBytes) == coll3(\n placeholder[Int](14)\n ).get.slice(placeholder[Int](15), placeholder[Int](16))\n )\n )\n )\n}",
"address": "3EFHCKeRPVHgyayoQ4uZbb7hxTkzDNWdHxcNDEodajfiCiX3bKNBWy3VooVSsrhPG8rM7DHyLtq2eEufJNxnVKbibiYSxAyBorZtkVsmKdX9BCcdLno8X2E2GfK4TTkM5xW5Nw2GkNLCxP3HMzn1YZo5PfbbMKC8TnhkFjP3iSK9ETUZcoDaDfpjBBQci5v9MKfbinskuV3PuJjk8aEUUup8RBoWcfbbtPmFuWZeoBELh1nFyepjUrvd4ERhuL4KM79GdLmjPynKcK2YzJJjUeokGbV9dzmZCPVQcAoU8LKCQE7MrwJiwRe34pi16zQgHwCp2B4JBvZo4xf8wNYxV5iHBHgoPYTN7SmQAJNLSzUQDY8TJiqbRgAoJJ",
"assets": [
{
"tokenId": "9a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be",
"index": 0,
"amount": 1,
"name": "Good Things DAO DAO Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e17476f6f64205468696e67732044414f2044414f204b6579",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f2044414f204b6579"
},
"R5": {
"serializedValue": "0e17476f6f64205468696e67732044414f2044414f204b6579",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f2044414f204b6579"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
}
}
},
{
"boxId": "e16a510b1b033d71a93f8db8293e0bca4dcda5bc8ca297daffbd29036d8eabe6",
"value": 1000000,
"index": 5,
"spendingProof": null,
"outputBlockId": "d0e8d9f498d3ea07f857730236607731ed642d0fdabe9f065424652eb708a14b",
"outputTransactionId": "0426f10ff8818f1f7838f1ab61b6991a579c5d777a7ef0e2c65c545845cee7b7",
"outputIndex": 1,
"outputGlobalIndex": 37943167,
"outputCreatedAt": 1220722,
"outputSettledAt": 1220724,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: Coll(91,-28,71,-57,19,-110,-60,48,-80,18,96,72,38,-97,-102,120,-118,-13,85,39,117,95,-84,-23,-46,41,-3,-122,83,14,52,-11)\n3: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n4: 0\n5: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n6: 0\n7: 1\n8: 33\n9: 0\n10: 0\n11: 6\n12: 38\n13: 0\n14: 1\n15: 1\n16: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val box2 = INPUTS(placeholder[Int](1))\n val coll3 = box1.R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3)), getVar[Coll[Byte]](0.toByte).get)\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](4))._1 == placeholder[Coll[Byte]](5), blake2b256(box2.propositionBytes) == coll3(placeholder[Int](6)).get.slice(\n placeholder[Int](7), placeholder[Int](8)\n ), SELF.tokens(placeholder[Int](9))._1 == box2.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](getVar[Coll[Byte]](2.toByte).get), getVar[Coll[Byte]](1.toByte).get\n )(placeholder[Int](10)).get.slice(placeholder[Int](11), placeholder[Int](12)), blake2b256(OUTPUTS(placeholder[Int](13)).propositionBytes) == coll3(\n placeholder[Int](14)\n ).get.slice(placeholder[Int](15), placeholder[Int](16))\n )\n )\n )\n}",
"address": "3EFHCKeRPVHgyayoQ4uZbb7hxTkzDNWdHxcNDEodajfiCiX3bKNBWy3VooVSsrhPG8rM7DHyLtq2eEufJNxnVKbibiYSxAyBorZtkVsmKdX9BCcdLno8X2E2GfK4TTkM5xW5Nw2GkNLCxP3HMzn1YZo5PfbbMKC8TnhkFjP3iSK9ETUZcoDaDfpjBBQci5v9MKfbinskuV3PuJjk8aEUUup8RBoWcfbbtPmFuWZeoBELh1nFyepjUrvd4ERhuL4KM79GdLmjPynKcK2YzJJjUeokGbV9dzmZCPVQcAoU8LKCQE7MrwJiwRe34pi16zQgHwCp2B4JBvZo4xf8wNYxV5iHBHgoPYTN7SmQAJNLSzUQDY8TJiqbRgAoJJ",
"assets": [
{
"tokenId": "833c861d4ad85e085b22c398045b77bc8dc53193429ca0383a949ac8e21f246b",
"index": 0,
"amount": 1,
"name": "Good Things DAO Stake State",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e1b476f6f64205468696e67732044414f205374616b65205374617465",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f205374616b65205374617465"
},
"R5": {
"serializedValue": "0e1b476f6f64205468696e67732044414f205374616b65205374617465",
"sigmaType": "Coll[SByte]",
"renderedValue": "476f6f64205468696e67732044414f205374616b65205374617465"
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
}
}
}
],
"dataInputs": [
{
"boxId": "4aeec5fc302bbbb1d339687206759a8ab91321fa25ac3454cb95d43f86aa56d3",
"value": 1000000,
"index": 0,
"outputBlockId": "94bc65df5765da1afa3183b16efc7b2e5582ddcdebbe94ea4e071f1826de3ede",
"outputTransactionId": "96c6b65e9366e961a6fbe83662de22f7d978a5d8e0070aced3b60b2573acbef2",
"outputIndex": 0,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e20008a3b597bd494557adf7d0d0a3b6ba32f935cf52f83f46a6b1233333a487a510100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbfCuknDpV3PzizoM2efhYNFH3o7uHxSjqDTXCRdcV2F4vMAbtG8fxGWK9ZxWniTZ6GFE5mT7DEpU6W6piUfh32UkeqxrkxS1Gb6KitQDAbSnrTwCceBFbSkmGRLmPxi26PrzREXVVz4UnXjm1xmFrng6vu6NtPvPfEzz1a4asj856HV8Pq1mMx3UgNfeA",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "64270150e06772c90f006c9252ef6c18ac683dcb1a7fc085880e394417e685af4708072000",
"sigmaType": null,
"renderedValue": null
}
}
}
],
"outputs": [
{
"boxId": "acd951171fe59d0356b173aaa3ce002b4eaeb44534103beed580ed2ed046364b",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 0,
"globalIndex": 37964196,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 1\n2: 0\n3: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n4: Coll(-11,-111,-114,-76,-80,40,60,102,-101,-35,-118,25,86,64,118,108,25,-28,10,105,58,102,-105,-73,117,-80,-114,9,5,37,35,-44)\n5: 1\n6: 1\n7: 2\n8: 2\n9: 1\n10: 1\n11: 1\n12: 0\n13: 9223372036854775807\n14: 0\n15: 1\n16: Coll(-16,54,125,-33,52,53,-104,31,74,-91,87,27,-111,-35,70,-2,-127,54,103,-14,-120,-115,79,-58,-111,-106,-113,-34,21,-121,-101,-105)\n17: Coll(105,109,46,112,97,105,100,101,105,97,46,99,111,110,116,114,97,99,116,115,46,112,114,111,112,111,115,97,108,46)\n18: Coll(105,109,46,112,97,105,100,101,105,97,46,99,111,110,116,114,97,99,116,115,46,97,99,116,105,111,110,46)\n19: 2\n20: 2\n21: 0\n22: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n23: 0\n24: 0\n25: 1\n26: 33\n27: 0\n28: 0\n29: 1\n30: 3\n31: 0\n32: 1\n33: 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)\n34: 1\n35: 1\n36: 9\n37: 1\n38: 1\n39: 33\n40: 0\n41: 0\n42: 1\n43: 9\n44: 1\n45: 0\n46: 0\n47: 1\n48: 0\n49: 1\n50: 0\n51: 2\n52: 1\n53: 33",
"ergoTreeScript": "{\n val coll1 = CONTEXT.dataInputs\n val box2 = coll1(placeholder[Int](0))\n val box3 = coll1(placeholder[Int](1))\n val coll4 = SELF.R4[Coll[Byte]].get\n val box5 = OUTPUTS(placeholder[Int](2))\n val coll6 = box2.R4[AvlTree].get.getMany(Coll[Coll[Byte]](placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4)), getVar[Coll[Byte]](0.toByte).get)\n val coll7 = box5.tokens\n val coll8 = SELF.tokens\n val tuple9 = coll7(placeholder[Int](5))\n val tuple10 = coll8(placeholder[Int](6))\n val coll11 = tuple10._1\n val l12 = tuple10._2\n val tuple13 = coll7(placeholder[Int](7))\n val tuple14 = coll8(placeholder[Int](8))\n val coll15 = tuple14._1\n val coll16 = INPUTS(placeholder[Int](9)).R5[Coll[Box]].get\n val coll17 = coll16.slice(placeholder[Int](10), coll16.size)\n val i18 = coll17.size\n val box19 = OUTPUTS(placeholder[Int](11))\n val box20 = coll16(placeholder[Int](12))\n val l21 = placeholder[Long](13) - l12\n val coll22 = box19.tokens\n val tuple23 = coll22(placeholder[Int](14))\n val tuple24 = coll22(placeholder[Int](15))\n val coll25 = box19.propositionBytes\n val coll26 = box20.propositionBytes\n val coll27 = box3.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](placeholder[Coll[Byte]](16), blake2b256(placeholder[Coll[Byte]](17).append(coll26))).append(\n coll17.map({(box27: Box) => blake2b256(placeholder[Coll[Byte]](18).append(box27.propositionBytes)) })\n ), getVar[Coll[Byte]](1.toByte).get\n )\n val coll28 = box19.R5[Coll[Long]].get\n val coll29 = OUTPUTS.slice(placeholder[Int](19), i18 + placeholder[Int](20))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box2.tokens(placeholder[Int](21))._1 == placeholder[Coll[Byte]](22), box3.tokens(placeholder[Int](23))._1 == coll4, allOf(\n Coll[Boolean](\n blake2b256(box5.propositionBytes) == coll6(placeholder[Int](24)).get.slice(\n placeholder[Int](25), placeholder[Int](26)\n ), box5.value >= SELF.value, coll7(placeholder[Int](27)) == coll8(placeholder[Int](28)), tuple9._1 == coll11, tuple9._2 == l12 - placeholder[Long](\n 29\n ), tuple13._1 == coll15, tuple13._2 == tuple14._2 - i18.toLong, coll7.size == placeholder[Int](30), box5.R4[Coll[Byte]].get == coll4\n )\n ), allOf(\n Coll[Boolean](\n box19.value >= box20.value, box19.R4[Coll[Int]].get(placeholder[Int](31)).toLong == l21, tuple23._1 == coll11, tuple23._2 == placeholder[Long](\n 32\n ), tuple24._1 == placeholder[Coll[Byte]](33), tuple24._2 == byteArrayToLong(\n coll6(placeholder[Int](34)).get.slice(placeholder[Int](35), placeholder[Int](36))\n ), coll25 == coll26, blake2b256(coll25) == coll27(placeholder[Int](37)).get.slice(placeholder[Int](38), placeholder[Int](39)), coll28(\n placeholder[Int](40)\n ) >= CONTEXT.preHeader.timestamp + byteArrayToLong(\n coll27(placeholder[Int](41)).get.slice(placeholder[Int](42), placeholder[Int](43))\n ), coll28.slice(placeholder[Int](44), coll28.size).forall({(l30: Long) => l30 == placeholder[Long](45) })\n )\n ), coll29.indices.forall({(i30: Int) =>\n val box32 = coll29(i30)\n val tuple33 = box32.tokens(placeholder[Int](46))\n val coll34 = box32.R4[Coll[Long]].get\n allOf(Coll[Boolean](box32.value >= coll17(i30).value, tuple33._1 == coll15, tuple33._2 == placeholder[Long](47), coll34(placeholder[Int](48)) == l21, coll34(placeholder[Int](49)) >= placeholder[Long](50), blake2b256(box32.propositionBytes) == coll27.slice(placeholder[Int](51), coll27.size).map({(opt35: Option[Coll[Byte]]) => opt35.get.slice(placeholder[Int](52), placeholder[Int](53)) })(i30)))\n })\n )\n )\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "00c3fd71f6ef5a03d125d11bd5fa5b738ef12dd3104491c243698a4486f139a6",
"index": 0,
"amount": 1,
"name": "Paideia DAO",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "2e1393aa54df7d36eaf52c0d0233b5a0c918e7835d90061a75e4e9f57e48f191",
"index": 1,
"amount": 9223372036854776000,
"name": "Good Things DAO Proposal",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "f8a824657dd6fb845dac80450a3320bd010d4070ec700a1abffbd83f5b8be40d",
"index": 2,
"amount": 9223372036854776000,
"name": "Good Things DAO Action",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0e209a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be",
"sigmaType": "Coll[SByte]",
"renderedValue": "9a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be"
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "575369f6e924abd299cbd5347d5c82208deb6bcdc81e4f7d14a32672f7c76b2d",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 1,
"globalIndex": 37964197,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "100904000e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020442040004000e20f8a824657dd6fb845dac80450a3320bd010d4070ec700a1abffbd83f5b8be40d0100d801d601b2a5730000d19683040193db6308a7db6308720190c1a7c1720193cbc27201b4e4b2dc640be4c6720104640283010e7301e4e3000e73020073037304aea4d9010263d801d604db630872029591b172047305938cb272047306000173077308",
"ergoTreeConstants": "0: 0\n1: Coll(-87,85,-114,65,-122,-53,-43,-86,87,35,-88,82,-44,-63,-36,101,125,-98,-127,67,-126,-1,-120,-115,90,-118,-20,82,21,49,48,29)\n2: 0\n3: 1\n4: 33\n5: 0\n6: 0\n7: Coll(-8,-88,36,101,125,-42,-5,-124,93,-84,-128,69,10,51,32,-67,1,13,64,112,-20,112,10,26,-65,-5,-40,63,91,-117,-28,13)\n8: false",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n sigmaProp(\n allOf(\n Coll[Boolean](\n SELF.tokens == box1.tokens, SELF.value <= box1.value, blake2b256(box1.propositionBytes) == box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](placeholder[Coll[Byte]](1)), getVar[Coll[Byte]](0.toByte).get\n )(placeholder[Int](2)).get.slice(placeholder[Int](3), placeholder[Int](4)), INPUTS.exists({(box2: Box) =>\n val coll4 = box2.tokens\n if (coll4.size > placeholder[Int](5)) { coll4(placeholder[Int](6))._1 == placeholder[Coll[Byte]](7) } else { placeholder[Boolean](8) }\n })\n )\n )\n )\n}",
"address": "FDdVv3XcPnh67Hm9GfPJpFCLuVeaYKY9MGf67RZfgNcGhsxDZPTz5JVn86hKGoSf3aCbgdeLQEhdydnKCFnCTKQESRtkR5KYByefEG5cafv8MLgTtrA6DoXs92Pg4RD1boqiHurboqCFevHpe82AQjgSnxyajDRUwMewhbZ2qz47k6AocinmvYehcNw48KJvmNbxSnVTh7DViFAj9V5Jqgc8TZ8GZRcNCQtBWviUChhc9Ht5APxGXg7kriw3yWJh",
"assets": [
{
"tokenId": "9a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be",
"index": 0,
"amount": 1,
"name": "Good Things DAO DAO Key",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "6407bf19ca678f00fba158fd99928e17de59c85bbc71ed19509de67ad1e7f63a0406072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "76772446b3e9f3c7ac156b245370f3e883cf15a696b8b18f65a444dee0b82eb0",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 2,
"globalIndex": 37964198,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"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(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)\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": "833c861d4ad85e085b22c398045b77bc8dc53193429ca0383a949ac8e21f246b",
"index": 0,
"amount": 1,
"name": "Good Things DAO Stake State",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "3503ba6ce5d8bc1332229284c95fff15cf3c1d0b463fdfd6f3c9b57b7af09fe3",
"index": 1,
"amount": 1,
"name": "Good Things DAO Token",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "1107cca489cece63000000000000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[1711357896998,0,0,0,0,0,0]"
},
"R6": {
"serializedValue": "1d05020000020000020000020000020000",
"sigmaType": "Coll[Coll[SLong]]",
"renderedValue": "[[0,0],[0,0],[0,0],[0,0],[0,0]]"
},
"R8": {
"serializedValue": "11020000",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0]"
},
"R7": {
"serializedValue": "0c3c6464024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
},
"R4": {
"serializedValue": "0c64024ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e1609000720004ec61f485b98eb87153f7c57db4f5ecd75556fddbc403b41acf8441fde8e160900072000",
"sigmaType": null,
"renderedValue": null
}
},
"spentTransactionId": "27cd50df1cb2c5147eee3f6509b04c768a7d18df6f63b1e73aaf0e727aaa9b7d",
"mainChain": true
},
{
"boxId": "8b9bf1ca77b24a1170375f4b8c9a553deb7282a4e15a0a53f5433a53f57ba7ff",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 3,
"globalIndex": 37964199,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "1042040004000e208830612c52355f6f280d1297f19f67b078c9daa7d7b04b459c91cc644957c2800e20efc4f603dea6041286a89f5bd516ac96ea5b25da4f08d76c6927e01d61b22adf0e204932c28754f2e4fab8e85af8ee3deb5bbe4924b7585466d20deed4c99e4191a2040004040400040c044a040c044a040a040c044a0402040a040805000410041004100400040004100410041004000400040204000e209a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be04000402040c044c040404000402040204020402040204000402050004020402040404050404050004000402044204020402040a04000400040404040406040604080408d81cd601b2db6501fe730000d602b2a4730100d603db63087202d604dc640be4c6720104640283030e730273037304e4e3000ed605e4e3010c3c0e0ed606b27205730500d6078c720601d608e4c672020511d609b17208d60ae4b27204730600d60bdb0c0eb4720a73079d99b1720a73087309d60cad720bd9010c04b4720a9a9a730a9c730b720c730c9a730d9c730e9a720c730fd60db3b4720873107209adb4720c9972097311b1720bd9010d0e7312d60edb0c0e720dd60fad720ed9010f04d801d6119a9c720f731373147cb48c72060272119a72117315d610b2720f731600d611e4c67202040c64d612b27211731700d613e4e3020ed614ad720ed9011404d801d6169a9c7214731873197cb4e4dc640a7212027207721372169a7216731ad615b27214731b00d6169972107215d617b2a5731c00d618db63087217d619e4c672170511d61ae4c67217040c64d61bdc0c1d721401720fd61cb2a5731d00d196830c01938cb2db63087201731e0001731f938cb2720373200001b4e4b2720473210073227323938cb2db6308b2a5732400732500017207ed937216998cb27218732600028cb272037327000293721699b27219732800b2720873290093b17205732a93db6401e4dc640d72120272057213db6401b2721a732b00afb4721b732cb1721bd9011d59d801d61f8c721d02ed928c721d01721f92721f732d9399b27214732e00b2720f732f0099c17202c17217afb472037330b17203d9011d4d0ed802d61f8c721d01d6209adc0c1a720c02721f7331733293998c721d02b072187333d90121414d0ed802d6238c722102d6248c72210195938c722301721f9a72248c722302722499b27214722000b2720f7220009683020193cbc2721cb4e4b272047334007335733692c1721cc1a79683090193b2721a733700b2721173380093b472197339b17219720d93b27219733a00b27208733b0093b27219733c00b27208733d0093b27219733e00b27208733f0093b27219734000b2720873410093e4c67217061de4c67202061d93e4c67217070c3c6464e4c67202070c3c646493e4c672170811e4c6720208119272107215",
"ergoTreeConstants": "0: 0\n1: 0\n2: 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)\n3: 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)\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: 6\n11: 37\n12: 5\n13: 6\n14: 37\n15: 1\n16: 5\n17: 4\n18: 0\n19: 8\n20: 8\n21: 8\n22: 0\n23: 0\n24: 8\n25: 8\n26: 8\n27: 0\n28: 0\n29: 1\n30: 0\n31: Coll(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)\n32: 0\n33: 1\n34: 6\n35: 38\n36: 2\n37: 0\n38: 1\n39: 1\n40: 1\n41: 1\n42: 1\n43: 0\n44: 1\n45: 0\n46: 1\n47: 1\n48: 2\n49: -3\n50: 2\n51: 0\n52: 0\n53: 1\n54: 33\n55: 1\n56: 1\n57: 5\n58: 0\n59: 0\n60: 2\n61: 2\n62: 3\n63: 3\n64: 4\n65: 4",
"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 tuple6 = coll5(placeholder[Int](5))\n val coll7 = tuple6._1\n val coll8 = box2.R5[Coll[Long]].get\n val i9 = coll8.size\n val coll10 = coll4(placeholder[Int](6)).get\n val coll11 = coll10.slice(placeholder[Int](7), coll10.size - placeholder[Int](8) / placeholder[Int](9)).indices\n val coll12 = coll11.map(\n {(i12: Int) =>\n coll10.slice(\n placeholder[Int](10) + placeholder[Int](11) * i12 + placeholder[Int](12), placeholder[Int](13) + placeholder[Int](14) * i12 + placeholder[Int](15)\n )\n }\n )\n val coll13 = coll8.slice(placeholder[Int](16), i9).append(\n coll12.slice(i9 - placeholder[Int](17), coll11.size).map({(coll13: Coll[Byte]) => placeholder[Long](18) })\n )\n val coll14 = coll13.indices\n val coll15 = coll14.map({(i15: Int) =>\n val i17 = i15 * placeholder[Int](19) + placeholder[Int](20)\n byteArrayToLong(tuple6._2.slice(i17, i17 + placeholder[Int](21)))\n })\n val l16 = coll15(placeholder[Int](22))\n val coll17 = box2.R4[Coll[AvlTree]].get\n val avlTree18 = coll17(placeholder[Int](23))\n val coll19 = getVar[Coll[Byte]](2.toByte).get\n val coll20 = coll14.map({(i20: Int) =>\n val i22 = i20 * placeholder[Int](24) + placeholder[Int](25)\n byteArrayToLong(avlTree18.get(coll7, coll19).get.slice(i22, i22 + placeholder[Int](26)))\n })\n val l21 = coll20(placeholder[Int](27))\n val l22 = l16 - l21\n val box23 = OUTPUTS(placeholder[Int](28))\n val coll24 = box23.tokens\n val coll25 = box23.R5[Coll[Long]].get\n val coll26 = box23.R4[Coll[AvlTree]].get\n val coll27 = coll20.zip(coll15)\n val box28 = OUTPUTS(placeholder[Int](29))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](30))._1 == placeholder[Coll[Byte]](31), coll3(placeholder[Int](32))._1 == coll4(placeholder[Int](33)).get.slice(\n placeholder[Int](34), placeholder[Int](35)\n ), OUTPUTS(placeholder[Int](36)).tokens(placeholder[Int](37))._1 == coll7, (\n l22 == coll24(placeholder[Int](38))._2 - coll3(placeholder[Int](39))._2\n ) && (l22 == coll25(placeholder[Int](40)) - coll8(placeholder[Int](41))), coll5.size == placeholder[Int](42), avlTree18.update(\n coll5, coll19\n ).get.digest == coll26(placeholder[Int](43)).digest, coll27.slice(placeholder[Int](44), coll27.size).forall({(tuple29: (Long, Long)) =>\n val l31 = tuple29._2\n (tuple29._1 >= l31) && (l31 >= placeholder[Long](45))\n }), coll20(placeholder[Int](46)) - coll15(placeholder[Int](47)) == box2.value - box23.value, coll3.slice(placeholder[Int](48), coll3.size).forall(\n {(tuple29: (Coll[Byte], Long)) =>\n val coll31 = tuple29._1\n val i32 = coll12.indexOf(coll31, placeholder[Int](49)) + placeholder[Int](50)\n tuple29._2 - coll24.fold(placeholder[Long](51), {(tuple33: (Long, (Coll[Byte], Long))) =>\n val tuple35 = tuple33._2\n val l36 = tuple33._1\n if (tuple35._1 == coll31) { l36 + tuple35._2 } else { l36 }\n }) == coll20(i32) - coll15(i32)\n }\n ), allOf(\n Coll[Boolean](\n blake2b256(box28.propositionBytes) == coll4(placeholder[Int](52)).get.slice(placeholder[Int](53), placeholder[Int](54)), box28.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n coll26(placeholder[Int](55)) == coll17(placeholder[Int](56)), coll25.slice(placeholder[Int](57), coll25.size) == coll13, coll25(\n placeholder[Int](58)\n ) == coll8(placeholder[Int](59)), coll25(placeholder[Int](60)) == coll8(placeholder[Int](61)), coll25(placeholder[Int](62)) == coll8(\n placeholder[Int](63)\n ), coll25(placeholder[Int](64)) == coll8(placeholder[Int](65)), box23.R6[Coll[Coll[Long]]].get == box2.R6[Coll[Coll[Long]]].get, box23.R7[\n Coll[(AvlTree, AvlTree)]\n ].get == box2.R7[Coll[(AvlTree, AvlTree)]].get, box23.R8[Coll[Long]].get == box2.R8[Coll[Long]].get\n )\n ), l16 >= l21\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "2bb5fb9e8c2a5cd15b65ec238177b15776554c999ca26cb1ef776f058178e10b",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 4,
"globalIndex": 37964200,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 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)\n3: 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)\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: 0\n9: 2\n10: 0\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 5\n17: 6\n18: 37\n19: 1\n20: 4\n21: 0\n22: 8\n23: 8\n24: 8\n25: 0\n26: 1\n27: 0\n28: Coll(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)\n29: 0\n30: 1\n31: 6\n32: 38\n33: 2\n34: 2\n35: 1\n36: 1\n37: 0\n38: 0\n39: 3\n40: 3\n41: 0\n42: 0\n43: 1\n44: 1\n45: 1\n46: 1\n47: 1\n48: 1\n49: 0\n50: 0\n51: 1\n52: 0\n53: 0\n54: 1\n55: 33\n56: 2\n57: 1\n58: 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 box5 = OUTPUTS(placeholder[Int](5))\n val coll6 = box5.tokens\n val coll7 = box5.R4[Coll[AvlTree]].get\n val coll8 = box2.R4[Coll[AvlTree]].get\n val coll9 = box5.R5[Coll[Long]].get\n val coll10 = box2.R5[Coll[Long]].get\n val i11 = coll10.size\n val coll12 = box2.id\n val coll13 = OUTPUTS(placeholder[Int](6)).tokens(placeholder[Int](7))._1\n val coll14 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val tuple15 = coll14(placeholder[Int](8))\n val coll16 = coll4(placeholder[Int](9)).get\n val coll17 = coll16.slice(placeholder[Int](10), coll16.size - placeholder[Int](11) / placeholder[Int](12)).indices\n val coll18 = coll10.slice(placeholder[Int](13), i11).append(\n coll17.map(\n {(i18: Int) =>\n coll16.slice(\n placeholder[Int](14) + placeholder[Int](15) * i18 + placeholder[Int](16), placeholder[Int](17) + placeholder[Int](18) * i18 + placeholder[Int](19)\n )\n }\n ).slice(i11 - placeholder[Int](20), coll17.size).map({(coll18: Coll[Byte]) => placeholder[Long](21) })\n ).indices\n val coll19 = coll18.map({(i19: Int) =>\n val i21 = i19 * placeholder[Int](22) + placeholder[Int](23)\n byteArrayToLong(tuple15._2.slice(i21, i21 + placeholder[Int](24)))\n })\n val l20 = coll19(placeholder[Int](25))\n val box21 = OUTPUTS(placeholder[Int](26))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](27))._1 == placeholder[Coll[Byte]](28), allOf(\n Coll[Boolean](\n coll3(placeholder[Int](29))._1 == coll4(placeholder[Int](30)).get.slice(\n placeholder[Int](31), placeholder[Int](32)\n ), box5.value >= box2.value, coll6.slice(placeholder[Int](33), coll6.size) == coll3.slice(placeholder[Int](34), coll3.size), coll7(\n placeholder[Int](35)\n ) == coll8(placeholder[Int](36)), coll9(placeholder[Int](37)) == coll10(placeholder[Int](38)), coll9.slice(\n placeholder[Int](39), coll9.size\n ) == coll10.slice(placeholder[Int](40), i11), box5.R6[Coll[Coll[Long]]].get == box2.R6[Coll[Coll[Long]]].get, box5.R7[\n Coll[(AvlTree, AvlTree)]\n ].get == box2.R7[Coll[(AvlTree, AvlTree)]].get, box5.R8[Coll[Long]].get == box2.R8[Coll[Long]].get\n )\n ), (coll12 == coll13) && (coll12 == tuple15._1), OUTPUTS.flatMap({(box22: Box) => box22.tokens }).fold(\n placeholder[Long](41), {(tuple22: (Long, (Coll[Byte], Long))) =>\n val tuple24 = tuple22._2\n tuple22._1 + if (tuple24._1 == coll13) { tuple24._2 } else { placeholder[Long](42) }\n }\n ) == placeholder[Long](43), (l20 == coll6(placeholder[Int](44))._2 - coll3(placeholder[Int](45))._2) && (\n l20 == coll9(placeholder[Int](46)) - coll10(placeholder[Int](47))\n ), coll14.size == placeholder[Int](48), coll8(placeholder[Int](49)).insert(coll14, getVar[Coll[Byte]](2.toByte).get).get.digest == coll7(\n placeholder[Int](50)\n ).digest, coll19.slice(placeholder[Int](51), coll18.size).forall({(l22: Long) => l22 == placeholder[Long](52) }), allOf(\n Coll[Boolean](\n blake2b256(box21.propositionBytes) == coll4(placeholder[Int](53)).get.slice(placeholder[Int](54), placeholder[Int](55)), box21.value >= SELF.value\n )\n ), coll10(placeholder[Int](56)) + placeholder[Long](57) == coll9(placeholder[Int](58))\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "27cd50df1cb2c5147eee3f6509b04c768a7d18df6f63b1e73aaf0e727aaa9b7d",
"mainChain": true
},
{
"boxId": "134ab5996c0e2728ab47d0b6eabd68c55f0ced545a0377941faf197e9fa6db29",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 5,
"globalIndex": 37964201,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "1039040004000e20efc4f603dea6041286a89f5bd516ac96ea5b25da4f08d76c6927e01d61b22adf0e208bc78f1c6aaec91e628e15cf668c16cc1e9bd8e4b9b7e16d6318b5f523a5e9bd0e204932c28754f2e4fab8e85af8ee3deb5bbe4924b7585466d20deed4c99e4191a20400040004040400040c044a040c044a040a040c044a04020400040a040805000410041004100400040204000e209a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be04000400040c044c0402040204000400040604060404040004020402040204020402040405000405040404020400040204020442040405020404d815d601b2db6501fe730000d602b2a4730100d603db63087202d604dc640be4c6720104640283030e730273037304e4e3000ed605b2a5730500d606e4c67205040c64d607e4c67202040c64d608e4c672050511d609e4c672020511d60ab17209d60be4e3010c3c0e0ed60cad720bd9010c3c0e0e8c720c01d60db2720c730600d60ee4b27204730700d60fdb0c0eb4720e73089d99b1720e7309730ad610ad720fd9011004b4720e9a9a730b9c730c7210730d9a730e9c730f9a72107310d611b27207731100d612addb0c0eb3b472097312720aadb4721099720a7313b1720fd901120e7314d9011204d801d6149a9c7212731573167cb4e4dc640a721102720de4e3020e72149a72147317d613b27212731800d614db63087205d615b2a5731900d196830a01938cb2db63087201731a0001731b96830701938cb27203731c0001b4e4b27204731d00731e731f93b27206732000b2720773210093b27208732200b2720973230093b472087324b17208b472097325720a93e4c67205061de4c67202061d93e4c67205070c3c6464e4c67202070c3c646493e4c672050811e4c672020811938cb2db6308b2a473260073270001720d96830201937213998cb27203732800028cb272147329000293721399b27209732a00b27208732b0093b27212732c0099c17202c17205afb47203732db17203d901164d0ed801d6188c72160193998c721602b07214732ed90119414d0ed802d61b8c721902d61c8c72190195938c721b0172189a721c8c721b02721cb272129adc0c1a7210027218732f73300093b1720b733193db6401e4dc640e721102720ce4e3030edb6401b272067332009683020193cbc27215b4e4b272047333007334733592c17215c1a79399b272097336007337b27208733800",
"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(-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)\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: 0\n7: 2\n8: 0\n9: 6\n10: 37\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 1\n17: 0\n18: 5\n19: 4\n20: 0\n21: 8\n22: 8\n23: 8\n24: 0\n25: 1\n26: 0\n27: Coll(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)\n28: 0\n29: 0\n30: 6\n31: 38\n32: 1\n33: 1\n34: 0\n35: 0\n36: 3\n37: 3\n38: 2\n39: 0\n40: 1\n41: 1\n42: 1\n43: 1\n44: 1\n45: 2\n46: 0\n47: -3\n48: 2\n49: 1\n50: 0\n51: 1\n52: 1\n53: 33\n54: 2\n55: 1\n56: 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 box5 = OUTPUTS(placeholder[Int](5))\n val coll6 = box5.R4[Coll[AvlTree]].get\n val coll7 = box2.R4[Coll[AvlTree]].get\n val coll8 = box5.R5[Coll[Long]].get\n val coll9 = box2.R5[Coll[Long]].get\n val i10 = coll9.size\n val coll11 = getVar[Coll[(Coll[Byte], Coll[Byte])]](1.toByte).get\n val coll12 = coll11.map({(tuple12: (Coll[Byte], Coll[Byte])) => tuple12._1 })\n val coll13 = coll12(placeholder[Int](6))\n val coll14 = coll4(placeholder[Int](7)).get\n val coll15 = coll14.slice(placeholder[Int](8), coll14.size - placeholder[Int](9) / placeholder[Int](10)).indices\n val coll16 = coll15.map(\n {(i16: Int) =>\n coll14.slice(\n placeholder[Int](11) + placeholder[Int](12) * i16 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i16 + placeholder[Int](16)\n )\n }\n )\n val avlTree17 = coll7(placeholder[Int](17))\n val coll18 = coll9.slice(placeholder[Int](18), i10).append(\n coll16.slice(i10 - placeholder[Int](19), coll15.size).map({(coll18: Coll[Byte]) => placeholder[Long](20) })\n ).indices.map({(i18: Int) =>\n val i20 = i18 * placeholder[Int](21) + placeholder[Int](22)\n byteArrayToLong(avlTree17.get(coll13, getVar[Coll[Byte]](2.toByte).get).get.slice(i20, i20 + placeholder[Int](23)))\n })\n val l19 = coll18(placeholder[Int](24))\n val coll20 = box5.tokens\n val box21 = OUTPUTS(placeholder[Int](25))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](26))._1 == placeholder[Coll[Byte]](27), allOf(\n Coll[Boolean](\n coll3(placeholder[Int](28))._1 == coll4(placeholder[Int](29)).get.slice(placeholder[Int](30), placeholder[Int](31)), coll6(\n placeholder[Int](32)\n ) == coll7(placeholder[Int](33)), coll8(placeholder[Int](34)) == coll9(placeholder[Int](35)), coll8.slice(\n placeholder[Int](36), coll8.size\n ) == coll9.slice(placeholder[Int](37), i10), box5.R6[Coll[Coll[Long]]].get == box2.R6[Coll[Coll[Long]]].get, box5.R7[\n Coll[(AvlTree, AvlTree)]\n ].get == box2.R7[Coll[(AvlTree, AvlTree)]].get, box5.R8[Coll[Long]].get == box2.R8[Coll[Long]].get\n )\n ), INPUTS(placeholder[Int](38)).tokens(placeholder[Int](39))._1 == coll13, allOf(\n Coll[Boolean](\n l19 == coll3(placeholder[Int](40))._2 - coll20(placeholder[Int](41))._2, l19 == coll9(placeholder[Int](42)) - coll8(placeholder[Int](43))\n )\n ), coll18(placeholder[Int](44)) == box2.value - box5.value, coll3.slice(placeholder[Int](45), coll3.size).forall({(tuple22: (Coll[Byte], Long)) =>\n val coll24 = tuple22._1\n tuple22._2 - coll20.fold(placeholder[Long](46), {(tuple25: (Long, (Coll[Byte], Long))) =>\n val tuple27 = tuple25._2\n val l28 = tuple25._1\n if (tuple27._1 == coll24) { l28 + tuple27._2 } else { l28 }\n }) == coll18(coll16.indexOf(coll24, placeholder[Int](47)) + placeholder[Int](48))\n }), coll11.size == placeholder[Int](49), avlTree17.remove(coll12, getVar[Coll[Byte]](3.toByte).get).get.digest == coll6(\n placeholder[Int](50)\n ).digest, allOf(\n Coll[Boolean](\n blake2b256(box21.propositionBytes) == coll4(placeholder[Int](51)).get.slice(placeholder[Int](52), placeholder[Int](53)), box21.value >= SELF.value\n )\n ), coll9(placeholder[Int](54)) - placeholder[Long](55) == coll8(placeholder[Int](56))\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "716aade0f0089addb615fed405a3a0dc5b8b47e3308d8c3acc346d5e28f722f4",
"mainChain": true
},
{
"boxId": "7a317248c4c30b779235b43db833eab95b05db74b3e1fe607c3d577bb2ca0773",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 6,
"globalIndex": 37964202,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"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(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)\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": null,
"mainChain": true
},
{
"boxId": "6f71de517531d56595733420c8b2154419657ff6e029b5bad901cb7423f6ed00",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 7,
"globalIndex": 37964203,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\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(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)\n4: Coll(-80,-71,7,-85,-81,-83,-115,-1,-50,47,-97,29,-6,21,53,-64,34,-35,-96,83,102,-12,-5,-46,127,88,29,19,47,75,35,-10)\n5: Coll(-101,22,-79,-128,-127,39,77,-62,47,24,-24,89,25,-106,-94,102,-45,-71,33,-73,113,-127,12,-54,12,-72,-25,18,74,-40,8,-66)\n6: Coll(65,-13,-104,-128,101,82,-124,94,82,0,-112,50,16,95,89,-27,-53,44,-79,65,-34,99,-52,115,123,109,-103,87,83,-61,110,-127)\n7: 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)\n8: Coll(40,-58,-124,89,62,17,78,122,82,44,-90,-26,-112,-104,119,-83,10,121,-82,-103,-37,109,108,-44,56,25,-93,77,80,91,55,-24)\n9: Coll(59,8,57,-57,-9,126,-4,-122,-37,-96,-92,95,-86,-51,100,-90,56,-74,-114,10,-62,106,-88,10,21,-116,-114,-66,87,-82,21,-125)\n10: 0\n11: 0\n12: 1\n13: 0\n14: 78\n15: -58\n16: 31\n17: 72\n18: 91\n19: -104\n20: -21\n21: -121\n22: 21\n23: 63\n24: 124\n25: 87\n26: -37\n27: 79\n28: 94\n29: -51\n30: 117\n31: 85\n32: 111\n33: -35\n34: -68\n35: 64\n36: 59\n37: 65\n38: -84\n39: -8\n40: 68\n41: 31\n42: -34\n43: -114\n44: 22\n45: 9\n46: 0\n47: 0\n48: 1\n49: 1\n50: 2\n51: 3\n52: 6\n53: 0\n54: 100\n55: 1\n56: 0\n57: 4\n58: 7\n59: 1\n60: 5\n61: 0\n62: 6\n63: 37\n64: 5\n65: 6\n66: 37\n67: 5\n68: 6\n69: 37\n70: 1\n71: 3\n72: 0\n73: 0\n74: 3\n75: 1\n76: 9\n77: 1\n78: 5\n79: 0\n80: 1\n81: 1\n82: 33\n83: 0\n84: 0\n85: 6\n86: 38\n87: 1\n88: 2\n89: 2\n90: 3\n91: 0\n92: 4\n93: 0\n94: 0\n95: 1\n96: 3\n97: 4\n98: 1\n99: 0\n100: 100\n101: 1\n102: 0\n103: 1\n104: 0\n105: 2\n106: 1\n107: 9\n108: 1\n109: 1\n110: 0\n111: 0\n112: 1\n113: 0\n114: 1\n115: 1\n116: 0\n117: 2\n118: 1\n119: 0\n120: 3\n121: 1\n122: 0\n123: 4\n124: 1\n125: 0\n126: 0\n127: 1\n128: 1\n129: 1\n130: 0\n131: 4\n132: 1\n133: 9\n134: 0\n135: Coll(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)",
"ergoTreeScript": "{\n val box1 = OUTPUTS(placeholder[Int](0))\n val box2 = CONTEXT.dataInputs(placeholder[Int](1))\n val coll3 = box2.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 box4 = INPUTS(placeholder[Int](10))\n val coll5 = box4.tokens\n val box6 = OUTPUTS(placeholder[Int](11))\n val coll7 = box6.R5[Coll[Long]].get\n val coll8 = box4.R5[Coll[Long]].get\n val l9 = coll8(placeholder[Int](12))\n val coll10 = box6.R4[Coll[AvlTree]].get\n val coll11 = box4.R4[Coll[AvlTree]].get\n val coll12 = coll11(placeholder[Int](13)).digest\n val coll13 = Coll[Int](\n placeholder[Int](14), placeholder[Int](15), placeholder[Int](16), placeholder[Int](17), placeholder[Int](18), placeholder[Int](19), placeholder[Int](\n 20\n ), placeholder[Int](21), placeholder[Int](22), placeholder[Int](23), placeholder[Int](24), placeholder[Int](25), placeholder[Int](26), placeholder[Int](\n 27\n ), placeholder[Int](28), placeholder[Int](29), placeholder[Int](30), placeholder[Int](31), placeholder[Int](32), placeholder[Int](33), placeholder[Int](\n 34\n ), placeholder[Int](35), placeholder[Int](36), placeholder[Int](37), placeholder[Int](38), placeholder[Int](39), placeholder[Int](40), placeholder[Int](\n 41\n ), placeholder[Int](42), placeholder[Int](43), placeholder[Int](44), placeholder[Int](45), placeholder[Int](46)\n ).map({(i13: Int) => i13.toByte })\n val coll14 = box6.R6[Coll[Coll[Long]]].get\n val coll15 = coll14(placeholder[Int](47))\n val i16 = coll15.size\n val i17 = i16 - placeholder[Int](48)\n val coll18 = coll14(placeholder[Int](49))\n val coll19 = coll14(placeholder[Int](50))\n val coll20 = coll14(placeholder[Int](51))\n val opt21 = coll3(placeholder[Int](52))\n val b22 = max(placeholder[Byte](53), min(placeholder[Byte](54), if (opt21.isDefined) { opt21.get(placeholder[Int](55)) } else { placeholder[Byte](56) }))\n val coll23 = coll14(placeholder[Int](57))\n val i24 = coll23.size\n val opt25 = coll3(placeholder[Int](58))\n val coll26 = box6.R7[Coll[(AvlTree, AvlTree)]].get\n val i27 = coll26.size\n val tuple28 = coll26(i27 - placeholder[Int](59))\n val coll29 = box6.R8[Coll[Long]].get\n val i30 = coll8.size\n val coll31 = coll3(placeholder[Int](60)).get\n val coll32 = coll31.slice(placeholder[Int](61), coll31.size - placeholder[Int](62) / placeholder[Int](63)).indices\n val coll33 = coll8.slice(placeholder[Int](64), i30).append(\n coll32.map(\n {(i33: Int) =>\n coll31.slice(\n placeholder[Int](65) + placeholder[Int](66) * i33 + placeholder[Int](67), placeholder[Int](68) + placeholder[Int](69) * i33 + placeholder[Int](70)\n )\n }\n ).slice(i30 - placeholder[Int](71), coll32.size).map({(coll33: Coll[Byte]) => placeholder[Long](72) })\n )\n val l34 = coll33(placeholder[Int](73))\n val coll35 = box4.R7[Coll[(AvlTree, AvlTree)]].get\n val i36 = byteArrayToLong(coll3(placeholder[Int](74)).get.slice(placeholder[Int](75), placeholder[Int](76))).toInt\n val i37 = i36 - placeholder[Int](77)\n val coll38 = box4.R6[Coll[Coll[Long]]].get\n val coll39 = coll7.slice(placeholder[Int](78), coll7.size)\n val l40 = coll8(placeholder[Int](79))\n sigmaProp(\n allOf(\n Coll[Boolean](\n allOf(\n Coll[Boolean](\n blake2b256(box1.propositionBytes) == coll3(placeholder[Int](80)).get.slice(placeholder[Int](81), placeholder[Int](82)), box1.value >= SELF.value\n )\n ), allOf(\n Coll[Boolean](\n coll5(placeholder[Int](83))._1 == coll3(placeholder[Int](84)).get.slice(placeholder[Int](85), placeholder[Int](86)), box6.tokens == coll5, coll7(\n placeholder[Int](87)\n ) == l9, coll7(placeholder[Int](88)) == coll8(placeholder[Int](89)), coll7(placeholder[Int](90)) == placeholder[Long](91), coll7(\n placeholder[Int](92)\n ) == placeholder[Long](93), coll10(placeholder[Int](94)).digest == coll12, coll10(placeholder[Int](95)).digest == coll13\n )\n ), allOf(\n Coll[Boolean](\n coll15(i17) == l9, coll18(i17) == coll8(placeholder[Int](96)), coll19(i17) == coll8(placeholder[Int](97)), coll20(i17) == b22.toLong, coll23(\n i24 - placeholder[Int](98)\n ) == max(\n placeholder[Byte](99), min(\n placeholder[Byte](100) - b22, if (opt25.isDefined) { opt25.get(placeholder[Int](101)) } else { placeholder[Byte](102) }\n )\n ).toLong, tuple28._1.digest == coll12, tuple28._2.digest == coll11(placeholder[Int](103)).digest, coll29(placeholder[Int](104)) == min(\n byteArrayToLong(coll3(placeholder[Int](105)).get.slice(placeholder[Int](106), placeholder[Int](107))), coll5(\n placeholder[Int](108)\n )._2 - l9 - l34 - placeholder[Long](109)\n ) + l34\n )\n ), allOf(\n Coll[Boolean](\n coll35(placeholder[Int](110))._1.digest == coll13, coll26.slice(placeholder[Int](111), i37) == coll35.slice(\n placeholder[Int](112), i36\n ), coll18.slice(placeholder[Int](113), i37) == coll38(placeholder[Int](114)).slice(placeholder[Int](115), i36), coll19.slice(\n placeholder[Int](116), i37\n ) == coll38(placeholder[Int](117)).slice(placeholder[Int](118), i36), coll20.slice(placeholder[Int](119), i37) == coll38(\n placeholder[Int](120)\n ).slice(placeholder[Int](121), i36), coll23.slice(placeholder[Int](122), i37) == coll38(placeholder[Int](123)).slice(\n placeholder[Int](124), i36\n ), coll15.slice(placeholder[Int](125), i37) == coll38(placeholder[Int](126)).slice(placeholder[Int](127), i36)\n )\n ), coll29.slice(placeholder[Int](128), coll33.size).indices.forall({(i41: Int) =>\n val i43 = i41 + placeholder[Int](129)\n coll29(i43) == coll33(i43)\n }), allOf(Coll[Boolean](i27 == i36, i16 == i36, coll20.size == i36, i24 == i36, coll18.size == i36, coll19.size == i36)), coll39.indices.forall(\n {(i41: Int) => coll39(i41) == coll29(i41) }\n ), coll7(placeholder[Int](130)) == l40 + byteArrayToLong(\n coll3(placeholder[Int](131)).get.slice(placeholder[Int](132), placeholder[Int](133))\n ), l40 <= CONTEXT.preHeader.timestamp, box2.tokens(placeholder[Int](134))._1 == placeholder[Coll[Byte]](135)\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "d563cbe7e9f2dde2be95391943013089a1087dca2aa0e9333c5c23f5b64afc6f",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 8,
"globalIndex": 37964204,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "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",
"ergoTreeConstants": "0: 2\n1: 0\n2: 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)\n3: 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)\n4: Coll(61,-86,102,-128,-114,105,-62,90,-23,50,-35,102,97,28,95,11,60,-70,-54,-47,18,82,3,-24,125,-115,-60,-111,-122,28,113,-26)\n5: 1\n6: 3\n7: 0\n8: 0\n9: 0\n10: 0\n11: 0\n12: 0\n13: 8\n14: 8\n15: 1\n16: 0\n17: 8\n18: 0\n19: 1\n20: 8\n21: 16\n22: 0\n23: 0\n24: 8\n25: 8\n26: 1\n27: 8\n28: 0\n29: 0\n30: 8\n31: 8\n32: 1\n33: 8\n34: 0\n35: 0\n36: 2\n37: 6\n38: 38\n39: 0\n40: 1\n41: 33\n42: 3\n43: 0\n44: 0\n45: 1\n46: 0\n47: 0\n48: 1\n49: 1\n50: 2\n51: 2\n52: 3\n53: 3\n54: 4\n55: 4\n56: 5\n57: 5\n58: 0\n59: 1\n60: 6\n61: 38\n62: 0\n63: Coll(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)",
"ergoTreeScript": "{\n val box1 = INPUTS(placeholder[Int](0))\n val box2 = CONTEXT.dataInputs(placeholder[Int](1))\n val coll3 = box2.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 box4 = OUTPUTS(placeholder[Int](5))\n val box5 = INPUTS(placeholder[Int](6))\n val coll6 = box5.tokens(placeholder[Int](7))._1\n val box7 = OUTPUTS(placeholder[Int](8))\n val box8 = INPUTS(placeholder[Int](9))\n val coll9 = box8.tokens\n val coll10 = box7.R4[Coll[AvlTree]].get\n val coll11 = box8.R4[Coll[AvlTree]].get\n val avlTree12 = coll11(placeholder[Int](10))\n val coll13 = avlTree12.get(coll6, getVar[Coll[Byte]](2.toByte).get).get\n val coll14 = longToByteArray(\n max(box1.R5[Coll[Long]].get(placeholder[Int](11)), byteArrayToLong(coll13.slice(placeholder[Int](12), placeholder[Int](13))))\n ).append(coll13.slice(placeholder[Int](14), coll13.size))\n val avlTree15 = coll11(placeholder[Int](15))\n val opt16 = avlTree15.get(coll6, getVar[Coll[Byte]](4.toByte).get)\n val bool17 = opt16.isDefined\n val opt18 = box1.R6[AvlTree].get.get(coll6, getVar[Coll[Byte]](1.toByte).get)\n val bool19 = opt18.isDefined\n val l20 = if (bool17) { byteArrayToLong(opt16.get.slice(placeholder[Int](16), placeholder[Int](17))) } else { placeholder[Long](18) }\n val l21 = if (bool19) { l20 } else { l20 + placeholder[Long](19) }\n val l22 = if (bool17) { byteArrayToLong(opt16.get.slice(placeholder[Int](20), placeholder[Int](21))) } else { placeholder[Long](22) }\n val coll23 = box5.R5[Coll[Byte]].get\n val l24 = coll23.indices.slice(placeholder[Int](23), coll23.size / placeholder[Int](24)).map(\n {(i24: Int) => byteArrayToLong(coll23.slice(i24 * placeholder[Int](25), i24 + placeholder[Int](26) * placeholder[Int](27))) }\n ).fold(placeholder[Long](28), {(tuple24: (Long, Long)) => tuple24._1 + tuple24._2 })\n val l25 = if (bool19) {(\n val coll25 = opt18.get\n l22 - coll25.indices.slice(placeholder[Int](29), coll25.size / placeholder[Int](30)).map(\n {(i26: Int) => byteArrayToLong(coll25.slice(i26 * placeholder[Int](31), i26 + placeholder[Int](32) * placeholder[Int](33))) }\n ).fold(placeholder[Long](34), {(tuple26: (Long, Long)) => tuple26._1 + tuple26._2 }) + l24\n )} else { l22 + l24 }\n val coll26 = longToByteArray(l21).append(longToByteArray(l25))\n val coll27 = getVar[Coll[Byte]](5.toByte).get\n val coll28 = box7.R5[Coll[Long]].get\n val coll29 = box8.R5[Coll[Long]].get\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](35))._1 == coll3(placeholder[Int](36)).get.slice(placeholder[Int](37), placeholder[Int](38)), allOf(\n Coll[Boolean](\n blake2b256(box4.propositionBytes) == coll3(placeholder[Int](39)).get.slice(placeholder[Int](40), placeholder[Int](41)), box4.value >= SELF.value\n )\n ), OUTPUTS(placeholder[Int](42)).tokens(placeholder[Int](43))._1 == coll6, allOf(\n Coll[Boolean](\n box7.value == box8.value, box7.tokens == coll9, coll10(placeholder[Int](44)).digest == avlTree12.update(\n Coll[(Coll[Byte], Coll[Byte])]((coll6, coll14)), getVar[Coll[Byte]](3.toByte).get\n ).get.digest, coll10(placeholder[Int](45)).digest == if (bool17) {\n avlTree15.update(Coll[(Coll[Byte], Coll[Byte])]((coll6, coll26)), coll27).get\n } else { avlTree15.insert(Coll[(Coll[Byte], Coll[Byte])]((coll6, coll26)), coll27).get }.digest, coll28(placeholder[Int](46)) == coll29(\n placeholder[Int](47)\n ), coll28(placeholder[Int](48)) == coll29(placeholder[Int](49)), coll28(placeholder[Int](50)) == coll29(placeholder[Int](51)), coll28(\n placeholder[Int](52)\n ) == coll29(placeholder[Int](53)) + l21 - l20, coll28(placeholder[Int](54)) == coll29(placeholder[Int](55)) + l25 - l22, coll28.slice(\n placeholder[Int](56), coll28.size\n ) == coll29.slice(placeholder[Int](57), coll29.size), box7.R6[Coll[Coll[Long]]].get == box8.R6[Coll[Coll[Long]]].get, box7.R7[\n Coll[(AvlTree, AvlTree)]\n ].get == box8.R7[Coll[(AvlTree, AvlTree)]].get, box7.R8[Coll[Long]].get == box8.R8[Coll[Long]].get\n )\n ), coll9(placeholder[Int](58))._1 == coll3(placeholder[Int](59)).get.slice(placeholder[Int](60), placeholder[Int](61)), box2.tokens(\n placeholder[Int](62)\n )._1 == placeholder[Coll[Byte]](63), getVar[Coll[Byte]](6.toByte).get == coll14, getVar[Coll[Byte]](7.toByte).get == coll26\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "4c458c42624758569211ae1d5571bed73420cb698773f7b661eb8b214c0661b9",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 9,
"globalIndex": 37964205,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "1034040004000e20efc4f603dea6041286a89f5bd516ac96ea5b25da4f08d76c6927e01d61b22adf0e203a11955c4719e588bce6a7611d27bd1fdfdb57385caee266d8040c894f1c2e1d0e204932c28754f2e4fab8e85af8ee3deb5bbe4924b7585466d20deed4c99e4191a20400040a04040400040c044a040c044a040a040c044a0402040a0408050004020402040204000e209a59db1cb3f841638a0fe27af9e1aafca052bb5848dfb13b31b414cd42f6b6be04000400040c044c0400040a0400040a0500040204020500040004000404040404010404040005000405040004040500040204020442d813d601b2db6501fe730000d602b2a4730100d603db63087202d604dc640be4c6720104640283030e730273037304e4e3000ed605b2a5730500d606e4c672050511d607e4c672020511d60899c17205c17202d609b472067306b17206d60ab17207d60be4b27204730700d60cdb0c0eb4720b73089d99b1720b7309730ad60dad720cd9010d04b4720b9a9a730b9c730c720d730d9a730e9c730f9a720d7310d60eb3b472077311720aadb4720d99720a7312b1720cd9010e0e7313d60fdb63087205d610998cb2720f731400028cb2720373150002d611b17203d612b1720fd613b2a5731600d196830801938cb2db6308720173170001731896830601938cb2720373190001b4e4b27204731a00731b731c93e4c67205040c64e4c67202040c6493b47206731d731eb47207731f732093e4c67205061de4c67202061d93e4c67205070c3c6464e4c67202070c3c646493e4c672050811e4c672020811ed92720873219399b27209732200b2720e7323007208ed92721073249399b27209732500b2720e7326007210afdc0c1db472037327721101b4720f73287211d901143c4d0e4d0ed806d6168c721401d6178c721601d6188c721402d619dc0c1a720d0272177329d61a998c7218028c721602d61b9a7219732a968304019372178c721801927219732b93721a99b27209721b00b2720e721b0092721a732cafb4720f72117212d901144d0ed802d616dc0c1a720d028c721401732dd6178c72140296830301927216732e937217b272099a7216732f00927217733092721272119683020193cbc27213b4e4b272047331007332733392c17213c1a7",
"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(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)\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: 5\n7: 2\n8: 0\n9: 6\n10: 37\n11: 6\n12: 37\n13: 5\n14: 6\n15: 37\n16: 1\n17: 5\n18: 4\n19: 0\n20: 1\n21: 1\n22: 1\n23: 0\n24: Coll(-102,89,-37,28,-77,-8,65,99,-118,15,-30,122,-7,-31,-86,-4,-96,82,-69,88,72,-33,-79,59,49,-76,20,-51,66,-10,-74,-66)\n25: 0\n26: 0\n27: 6\n28: 38\n29: 0\n30: 5\n31: 0\n32: 5\n33: 0\n34: 1\n35: 1\n36: 0\n37: 0\n38: 0\n39: 2\n40: 2\n41: -1\n42: 2\n43: 0\n44: 0\n45: -3\n46: 0\n47: 2\n48: 0\n49: 1\n50: 1\n51: 33",
"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 box5 = OUTPUTS(placeholder[Int](5))\n val coll6 = box5.R5[Coll[Long]].get\n val coll7 = box2.R5[Coll[Long]].get\n val l8 = box5.value - box2.value\n val coll9 = coll6.slice(placeholder[Int](6), coll6.size)\n val i10 = coll7.size\n val coll11 = coll4(placeholder[Int](7)).get\n val coll12 = coll11.slice(placeholder[Int](8), coll11.size - placeholder[Int](9) / placeholder[Int](10)).indices\n val coll13 = coll12.map(\n {(i13: Int) =>\n coll11.slice(\n placeholder[Int](11) + placeholder[Int](12) * i13 + placeholder[Int](13), placeholder[Int](14) + placeholder[Int](15) * i13 + placeholder[Int](16)\n )\n }\n )\n val coll14 = coll7.slice(placeholder[Int](17), i10).append(\n coll13.slice(i10 - placeholder[Int](18), coll12.size).map({(coll14: Coll[Byte]) => placeholder[Long](19) })\n )\n val coll15 = box5.tokens\n val l16 = coll15(placeholder[Int](20))._2 - coll3(placeholder[Int](21))._2\n val i17 = coll3.size\n val i18 = coll15.size\n val box19 = OUTPUTS(placeholder[Int](22))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](23))._1 == placeholder[Coll[Byte]](24), allOf(\n Coll[Boolean](\n coll3(placeholder[Int](25))._1 == coll4(placeholder[Int](26)).get.slice(placeholder[Int](27), placeholder[Int](28)), box5.R4[\n Coll[AvlTree]\n ].get == box2.R4[Coll[AvlTree]].get, coll6.slice(placeholder[Int](29), placeholder[Int](30)) == coll7.slice(\n placeholder[Int](31), placeholder[Int](32)\n ), box5.R6[Coll[Coll[Long]]].get == box2.R6[Coll[Coll[Long]]].get, box5.R7[Coll[(AvlTree, AvlTree)]].get == box2.R7[\n Coll[(AvlTree, AvlTree)]\n ].get, box5.R8[Coll[Long]].get == box2.R8[Coll[Long]].get\n )\n ), (l8 >= placeholder[Long](33)) && (coll9(placeholder[Int](34)) - coll14(placeholder[Int](35)) == l8), (l16 >= placeholder[Long](36)) && (\n coll9(placeholder[Int](37)) - coll14(placeholder[Int](38)) == l16\n ), coll3.slice(placeholder[Int](39), i17).zip(coll15.slice(placeholder[Int](40), i17)).forall({(tuple20: ((Coll[Byte], Long), (Coll[Byte], Long))) =>\n val tuple22 = tuple20._1\n val coll23 = tuple22._1\n val tuple24 = tuple20._2\n val i25 = coll13.indexOf(coll23, placeholder[Int](41))\n val l26 = tuple24._2 - tuple22._2\n val i27 = i25 + placeholder[Int](42)\n allOf(Coll[Boolean](coll23 == tuple24._1, i25 >= placeholder[Int](43), l26 == coll9(i27) - coll14(i27), l26 >= placeholder[Long](44)))\n }), coll15.slice(i17, i18).forall({(tuple20: (Coll[Byte], Long)) =>\n val i22 = coll13.indexOf(tuple20._1, placeholder[Int](45))\n val l23 = tuple20._2\n allOf(Coll[Boolean](i22 >= placeholder[Int](46), l23 == coll9(i22 + placeholder[Int](47)), l23 >= placeholder[Long](48)))\n }), i18 >= i17, allOf(\n Coll[Boolean](\n blake2b256(box19.propositionBytes) == coll4(placeholder[Int](49)).get.slice(placeholder[Int](50), placeholder[Int](51)), box19.value >= SELF.value\n )\n )\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": null,
"mainChain": true
},
{
"boxId": "6c50941c9c56ede0b88a744a8091a11c86ba81a2aaed8dd72f8af07bb5d40cf1",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 2000000,
"index": 10,
"globalIndex": 37964206,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"ergoTree": "10fd0104000e20039d2a0a218d7c48c8fd46a8d29431bd056c84882a216a567326c3c7984ec8350e20875ac77837c8d4730a86ee2280434f6290ad9be0b449b43ab92cb3de9b0763370e20bf17b0fcb0799cbd95c05a600b0a6cffe253c01d78df846b38fe9dbd426da61f0e201e211af07c38e28e074b757f277133757d53886fb20301c39a34d30befbb1cc20e20bd571513e4e3e5b0cefd7a1b61e8064247a59fc8784f6cf0bbd3a1a58437644f0e208f90981e071173fb1bb8d89741720a4838ee6614635a2931575f46cc1ba23b610e2004cf35050ba24f0d7978e8f1686e41b991e358ecbbdab0d0ff09b1907a44885b0e20c747ddfe8eafe01bd27b274e86a357f0a6ce663d1419e2f25b8cabd1e11dc5660e20aa0e7e5e3b644454cb49ee12538fc0b3872c1c9b2e3175c57be508e2cd6089980e200ed4d6651566d575eaacb14800660471b315f1bb7c93eb0deb63fdced7ba984f0e2063fa818cbdeff66f6d843caf6465fb59b24e036829ac3bb9b2674fef2af54b550e20fc62c5e1fe04a3da9c1c59ab26553ef88bbfb2d40dbffbfa1645b7ffcf3adb1e0e2036518129ae645d6b4dfdd02c28bb1c5a6fa9a007d23ec213e1b3ed2d0d2047520e20ab6fab0b3fdf9f8a851cde5017713e29c5f7a5d48fc3a52d1a29e43a80074dea0e2067dc14944331352434978b040e03d1c898556f5517aaca4511cab5421f93acfc0e20a4311c726b35b18ef22b834ee0ff57ff370d83cc94c89fc06dd97d00921598710e200cd12d6cce7fef5daa90b45e7a0b3feb7b889c8cb4dbe458f81b91cb2dc0adf70e2066031cbd733590753b2af8ab828cecb95d7b6cf4da6502b31fbed30d9f69e7450e20c303ddf29c040348be5c3181be176ab75e7721e153ceff836a950fd9059d83cd0e20528dc9e30a9e7a9786eea3093fddce3c3e82c87fe4136e059ab4a3baa1a4f5490e2098f0c8e0e406daa97b70598094b9e6626acadac419da667b4d71f33064f8d5dd0e2049760084f7d55ab90470ebf4d4baaf057d8b42d8cc2dab619edaa2998a10479d0e20b3a0e35b4a02dea17ec93a2a84c7dd80173535c011da42de5b1b03c26a58dd450e20eeab3b56ae3fcb0ad2ffc7548748cee3ce641da2998b4a78e1559ec7320e40450e200136ee4c40c4dc5fba3a0486e5074b2b98118e489aec1d0a3c4325f61973edc80e2013256f7c1339c14b928301e25ae54071ad497a192f7cf8193e2661bb0ead7dad0e206e9ef5de67414597d933639b14dc2abe0624163ac56eb6a3b0b14f53ecc050a8040204000e203daa66808e69c25ae932dd66611c5f0b3cbacad1125203e87d8dc491861c71e60e20baaa9b164cb4b80d735e10424e26a471b9621c02efca1746135ac3f6db1014100e20ca0bb5e8cad718225c8f2d0261a0d095f25d5e87460a8633f400dc3cc907912f0e20efc4f603dea6041286a89f5bd516ac96ea5b25da4f08d76c6927e01d61b22adf0e2041f398806552845e52009032105f59e5cb2cb141de63cc737b6d995753c36e810402040c044c040204060400040a0404040c044c0400040c044c0404040e0406041204080416040a041e040e0422041004260412041a040c042a041404320418042e0416040004020404040204000e1c696d2e706169646569612e636f6e7472616374732e616374696f6e2e0404024e02c6021f0248025b029802eb02870215023f027c025702db024f025e02cd02750255026f02dd02bc0240023b024102ac02f80244021f02de028e021602090200040004060408040a040c040e04100412041404000e2000ff963212ba003aeba715c067e92ef299c55f35aed7b6aef4c975ae81a5d3f904040402040c040e044004080402040c04040440040c0402040c04420446044004100402040c040e0412044004140402040c0416044004180402040c043e044004200402040c048c01044004240402040c0430044004280402040c048e020440041c0402040c04380440042c0402040c0418044004340402040c0436044004300402040c047e04400400040204420580897a0400040005feffffffffffffffff0105feffffffffffffffff010406040204420580897a050204020e20c7c537e6c635930ecb4ace95a54926b3ab77698d9f4922f0b1c58ea87156483b0e20a9558e4186cbd5aa5723a852d4c1dc657d9e814382ff888d5a8aec521531301d040004020e1e696d2e706169646569612e636f6e7472616374732e70726f706f73616c2e04040e208830612c52355f6f280d1297f19f67b078c9daa7d7b04b459c91cc644957c2800e20039208bc4eef9a03e8d78b8663a301bb5faddca78be19d7fe535b3c64cbefe420e20892e6f47a10d5c90b87ad4863355cead00c3e2983217ee15533253cd9a6025c20e203a11955c4719e588bce6a7611d27bd1fdfdb57385caee266d8040c894f1c2e1d0e204fd8b0d6d98242726f57b3dfa686126792b8e5056e1d51b6e90d6880cf2dcdc50e20deaecf5b64bad6f5570bad0a610c4e484957cf4782308400bc90404c1d1410da0e2009820fcb8871fb450c3e06b7cb5e27b0455087a366621a9dde7582a019111e3e0e208bc78f1c6aaec91e628e15cf668c16cc1e9bd8e4b9b7e16d6318b5f523a5e9bd040204420580897a04000406040c044c04020402040404080402041204020500050005000580897a040204420580897a040204420580897a040204420580897a040204420580897a040204420580897a040204420580897a04020442d83ed601b2db6501fe730000d602dc640be4c67201046402831b0e730173027303730473057306730773087309730a730b730c730d730e730f7310731173127313731473157316731773187319731a731be4e3000ed603e4b27202731c00d604b2a4731d00d605e4c672040464d606dc640b72050283050e731e731f732073217322e4e3010ed607b4e4b2720673230073247325d60883010e7207d609e4e3031ad60ab27209732600d60be4b27202732700d60cb27209732800d60de4b27202732900d60eb4e4b27206732a00732b732cd60fb4e4b27206732d00732e732fd61083020e720e720fd611b27209733000d612e4b27202733100d613b27209733200d614e4b27202733300d61583010e720ed616b27209733400d617e4b27202733500d618b27209733600d619e4b27202733700d61ab27209733800d61be4b27202733900d61cb27209733a00d61de4b27202733b00d61eb27209733c00d61fe4b27202733d00d620b27209733e00d621e4b27202733f00d622b27209734000d623e4b27202734100d624b27209734200d625e4b27202734300d626b27209734400d627b2a5734500d628db63087227d629db63087204d62ab27228734600d62bb27228734700d62cb2a5734800d62ddb6308722cd62eb2722d734900d62f734ad630e4e3041ad631b2a5734b00d632db63087231d633832102734c734d734e734f7350735173527353735473557356735773587359735a735b735c735d735e735f7360736173627363736473657366736773687369736a736b736cd634e4c672310511d635b27234736d00d636db6903db6503fed637b2a5736e00d638b2a5736f00d639b2a5737000d63ab2a5737100d63bb2a5737200d63cb2a5737300d63db2a5737400d63eb2a5737500d196830701938cb2db6308720173760001737796830d0193dc0c13e4b27202737800037379cb74b47203737ab17203830104737b7208737c720a93dc0c13e4b27202737d0003737ecb74b4720b737fb1720b8301047380017208738101720c93dc0c13e4b272027382010003738301cb74b4720d738401b1720d8302047385017386017210738701721193dc0c13e4b272027388010003738901cb74b47212738a01b17212830204738b01738c017210738d01721393dc0c13e4b27202738e010003738f01cb74b47214739001b172148301047391017215739201721693dc0c13e4b272027393010003739401cb74b47217739501b172178301047396017215739701721893dc0c13e4b272027398010003739901cb74b47219739a01b17219830104739b017215739c01721a93dc0c13e4b27202739d010003739e01cb74b4721b739f01b1721b83010473a001721573a101721c93dc0c13e4b2720273a201000373a301cb74b4721d73a401b1721d83010473a501721573a601721e93dc0c13e4b2720273a701000373a801cb74b4721f73a901b1721f83010473aa01721573ab01722093dc0c13e4b2720273ac01000373ad01cb74b4722173ae01b1722183010473af01721573b001722293dc0c13e4b2720273b101000373b201cb74b4722373b301b1722383010473b401721573b501722493dc0c13e4b2720273b601000373b701cb74b4722573b801b1722583010473b901721573ba0172269683090193cbc27227b4e4b2720273bb010073bc0173bd0192c1722773be0193b2722873bf0100b2722973c00100938c722a01720f938c722a0273c101938c722b017207938c722b0273c20193b1722873c30193e4c67227040e720e9683060193cbc2722cb4720a73c40173c50192c1722c73c601938c722e01720e938c722e0273c70193b1722d73c80193db6401e4c6722c0464db6401e4dc640c720502830d3c0e0e860273c901720c860273ca01720a8602cbb3722fb2723073cb010072118602cbb3722fb2723073cc010072138602cbb373cd01b2723073ce01007216860273cf017218860273d0017220860273d101721a860273d201721c860273d301721e860273d4017222860273d5017226860273d6017224e4e3020e96830c0193cbc27231b4722273d70173d80192c1723173d901938cb2723273da010001b4e4b2720673db010073dc0173dd0193b2723273de0100b2722973df010093b1723273e001afe4c67231040c64d9013f6493db6401723f723391723572368f72359a72367cb4e4b2720673e1010073e20173e301afb4723473e401b17234d9013f0593723f73e501afdc0c0fe4c67231061d01d9013f11723fd9013f0593723f73e601afe4c67231070c3c6464d9013f3c6464ed93db64018c723f01723393db64018c723f027233afe4c672310811d9013f0593723f73e70196830e0192c1723773e80193cbc27237b4721873e90173ea0192c1723873eb0193cbc27238b4722073ec0173ed0192c1723973ee0193cbc27239b4722473ef0173f00192c1723a73f10193cbc2723ab4721a73f20173f30192c1723b73f40193cbc2723bb4721e73f50173f60192c1723c73f70193cbc2723cb4722673f80173f90192c1723d73fa0193cbc2723db4721c73fb0173fc019683020192c1723ec1a793c2723ec2a7",
"ergoTreeConstants": "0: 0\n1: Coll(3,-99,42,10,33,-115,124,72,-56,-3,70,-88,-46,-108,49,-67,5,108,-124,-120,42,33,106,86,115,38,-61,-57,-104,78,-56,53)\n2: Coll(-121,90,-57,120,55,-56,-44,115,10,-122,-18,34,-128,67,79,98,-112,-83,-101,-32,-76,73,-76,58,-71,44,-77,-34,-101,7,99,55)\n3: Coll(-65,23,-80,-4,-80,121,-100,-67,-107,-64,90,96,11,10,108,-1,-30,83,-64,29,120,-33,-124,107,56,-2,-99,-67,66,109,-90,31)\n4: Coll(30,33,26,-16,124,56,-30,-114,7,75,117,127,39,113,51,117,125,83,-120,111,-78,3,1,-61,-102,52,-45,11,-17,-69,28,-62)\n5: Coll(-67,87,21,19,-28,-29,-27,-80,-50,-3,122,27,97,-24,6,66,71,-91,-97,-56,120,79,108,-16,-69,-45,-95,-91,-124,55,100,79)\n6: Coll(-113,-112,-104,30,7,17,115,-5,27,-72,-40,-105,65,114,10,72,56,-18,102,20,99,90,41,49,87,95,70,-52,27,-94,59,97)\n7: Coll(4,-49,53,5,11,-94,79,13,121,120,-24,-15,104,110,65,-71,-111,-29,88,-20,-69,-38,-80,-48,-1,9,-79,-112,122,68,-120,91)\n8: Coll(-57,71,-35,-2,-114,-81,-32,27,-46,123,39,78,-122,-93,87,-16,-90,-50,102,61,20,25,-30,-14,91,-116,-85,-47,-31,29,-59,102)\n9: Coll(-86,14,126,94,59,100,68,84,-53,73,-18,18,83,-113,-64,-77,-121,44,28,-101,46,49,117,-59,123,-27,8,-30,-51,96,-119,-104)\n10: Coll(14,-44,-42,101,21,102,-43,117,-22,-84,-79,72,0,102,4,113,-77,21,-15,-69,124,-109,-21,13,-21,99,-3,-50,-41,-70,-104,79)\n11: Coll(99,-6,-127,-116,-67,-17,-10,111,109,-124,60,-81,100,101,-5,89,-78,78,3,104,41,-84,59,-71,-78,103,79,-17,42,-11,75,85)\n12: Coll(-4,98,-59,-31,-2,4,-93,-38,-100,28,89,-85,38,85,62,-8,-117,-65,-78,-44,13,-65,-5,-6,22,69,-73,-1,-49,58,-37,30)\n13: Coll(54,81,-127,41,-82,100,93,107,77,-3,-48,44,40,-69,28,90,111,-87,-96,7,-46,62,-62,19,-31,-77,-19,45,13,32,71,82)\n14: Coll(-85,111,-85,11,63,-33,-97,-118,-123,28,-34,80,23,113,62,41,-59,-9,-91,-44,-113,-61,-91,45,26,41,-28,58,-128,7,77,-22)\n15: Coll(103,-36,20,-108,67,49,53,36,52,-105,-117,4,14,3,-47,-56,-104,85,111,85,23,-86,-54,69,17,-54,-75,66,31,-109,-84,-4)\n16: Coll(-92,49,28,114,107,53,-79,-114,-14,43,-125,78,-32,-1,87,-1,55,13,-125,-52,-108,-56,-97,-64,109,-39,125,0,-110,21,-104,113)\n17: Coll(12,-47,45,108,-50,127,-17,93,-86,-112,-76,94,122,11,63,-21,123,-120,-100,-116,-76,-37,-28,88,-8,27,-111,-53,45,-64,-83,-9)\n18: Coll(102,3,28,-67,115,53,-112,117,59,42,-8,-85,-126,-116,-20,-71,93,123,108,-12,-38,101,2,-77,31,-66,-45,13,-97,105,-25,69)\n19: Coll(-61,3,-35,-14,-100,4,3,72,-66,92,49,-127,-66,23,106,-73,94,119,33,-31,83,-50,-1,-125,106,-107,15,-39,5,-99,-125,-51)\n20: Coll(82,-115,-55,-29,10,-98,122,-105,-122,-18,-93,9,63,-35,-50,60,62,-126,-56,127,-28,19,110,5,-102,-76,-93,-70,-95,-92,-11,73)\n21: Coll(-104,-16,-56,-32,-28,6,-38,-87,123,112,89,-128,-108,-71,-26,98,106,-54,-38,-60,25,-38,102,123,77,113,-13,48,100,-8,-43,-35)\n22: Coll(73,118,0,-124,-9,-43,90,-71,4,112,-21,-12,-44,-70,-81,5,125,-117,66,-40,-52,45,-85,97,-98,-38,-94,-103,-118,16,71,-99)\n23: Coll(-77,-96,-29,91,74,2,-34,-95,126,-55,58,42,-124,-57,-35,-128,23,53,53,-64,17,-38,66,-34,91,27,3,-62,106,88,-35,69)\n24: Coll(-18,-85,59,86,-82,63,-53,10,-46,-1,-57,84,-121,72,-50,-29,-50,100,29,-94,-103,-117,74,120,-31,85,-98,-57,50,14,64,69)\n25: Coll(1,54,-18,76,64,-60,-36,95,-70,58,4,-122,-27,7,75,43,-104,17,-114,72,-102,-20,29,10,60,67,37,-10,25,115,-19,-56)\n26: Coll(19,37,111,124,19,57,-63,75,-110,-125,1,-30,90,-27,64,113,-83,73,122,25,47,124,-8,25,62,38,97,-69,14,-83,125,-83)\n27: Coll(110,-98,-11,-34,103,65,69,-105,-39,51,99,-101,20,-36,42,-66,6,36,22,58,-59,110,-74,-93,-80,-79,79,83,-20,-64,80,-88)\n28: 1\n29: 0\n30: Coll(61,-86,102,-128,-114,105,-62,90,-23,50,-35,102,97,28,95,11,60,-70,-54,-47,18,82,3,-24,125,-115,-60,-111,-122,28,113,-26)\n31: Coll(-70,-86,-101,22,76,-76,-72,13,115,94,16,66,78,38,-92,113,-71,98,28,2,-17,-54,23,70,19,90,-61,-10,-37,16,20,16)\n32: Coll(-54,11,-75,-24,-54,-41,24,34,92,-113,45,2,97,-96,-48,-107,-14,93,94,-121,70,10,-122,51,-12,0,-36,60,-55,7,-111,47)\n33: 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)\n34: Coll(65,-13,-104,-128,101,82,-124,94,82,0,-112,50,16,95,89,-27,-53,44,-79,65,-34,99,-52,115,123,109,-103,87,83,-61,110,-127)\n35: 1\n36: 6\n37: 38\n38: 1\n39: 3\n40: 0\n41: 5\n42: 2\n43: 6\n44: 38\n45: 0\n46: 6\n47: 38\n48: 2\n49: 7\n50: 3\n51: 9\n52: 4\n53: 11\n54: 5\n55: 15\n56: 7\n57: 17\n58: 8\n59: 19\n60: 9\n61: 13\n62: 6\n63: 21\n64: 10\n65: 25\n66: 12\n67: 23\n68: 11\n69: 0\n70: 1\n71: 2\n72: 1\n73: 0\n74: Coll(105,109,46,112,97,105,100,101,105,97,46,99,111,110,116,114,97,99,116,115,46,97,99,116,105,111,110,46)\n75: 2\n76: 78\n77: -58\n78: 31\n79: 72\n80: 91\n81: -104\n82: -21\n83: -121\n84: 21\n85: 63\n86: 124\n87: 87\n88: -37\n89: 79\n90: 94\n91: -51\n92: 117\n93: 85\n94: 111\n95: -35\n96: -68\n97: 64\n98: 59\n99: 65\n100: -84\n101: -8\n102: 68\n103: 31\n104: -34\n105: -114\n106: 22\n107: 9\n108: 0\n109: 0\n110: 3\n111: 4\n112: 5\n113: 6\n114: 7\n115: 8\n116: 9\n117: 10\n118: 0\n119: Coll(0,-1,-106,50,18,-70,0,58,-21,-89,21,-64,103,-23,46,-14,-103,-59,95,53,-82,-41,-74,-82,-12,-55,117,-82,-127,-91,-45,-7)\n120: 2\n121: 1\n122: 6\n123: 7\n124: 32\n125: 4\n126: 1\n127: 6\n128: 2\n129: 32\n130: 6\n131: 1\n132: 6\n133: 33\n134: 35\n135: 32\n136: 8\n137: 1\n138: 6\n139: 7\n140: 9\n141: 32\n142: 10\n143: 1\n144: 6\n145: 11\n146: 32\n147: 12\n148: 1\n149: 6\n150: 31\n151: 32\n152: 16\n153: 1\n154: 6\n155: 70\n156: 32\n157: 18\n158: 1\n159: 6\n160: 24\n161: 32\n162: 20\n163: 1\n164: 6\n165: 135\n166: 32\n167: 14\n168: 1\n169: 6\n170: 28\n171: 32\n172: 22\n173: 1\n174: 6\n175: 12\n176: 32\n177: 26\n178: 1\n179: 6\n180: 27\n181: 32\n182: 24\n183: 1\n184: 6\n185: 63\n186: 32\n187: 0\n188: 1\n189: 33\n190: 1000000\n191: 0\n192: 0\n193: 9223372036854775807\n194: 9223372036854775807\n195: 3\n196: 1\n197: 33\n198: 1000000\n199: 1\n200: 1\n201: Coll(-57,-59,55,-26,-58,53,-109,14,-53,74,-50,-107,-91,73,38,-77,-85,119,105,-115,-97,73,34,-16,-79,-59,-114,-88,113,86,72,59)\n202: Coll(-87,85,-114,65,-122,-53,-43,-86,87,35,-88,82,-44,-63,-36,101,125,-98,-127,67,-126,-1,-120,-115,90,-118,-20,82,21,49,48,29)\n203: 0\n204: 1\n205: Coll(105,109,46,112,97,105,100,101,105,97,46,99,111,110,116,114,97,99,116,115,46,112,114,111,112,111,115,97,108,46)\n206: 2\n207: 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)\n208: 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)\n209: 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)\n210: 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)\n211: 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)\n212: 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)\n213: 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)\n214: 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)\n215: 1\n216: 33\n217: 1000000\n218: 0\n219: 3\n220: 6\n221: 38\n222: 1\n223: 1\n224: 2\n225: 4\n226: 1\n227: 9\n228: 1\n229: 0\n230: 0\n231: 0\n232: 1000000\n233: 1\n234: 33\n235: 1000000\n236: 1\n237: 33\n238: 1000000\n239: 1\n240: 33\n241: 1000000\n242: 1\n243: 33\n244: 1000000\n245: 1\n246: 33\n247: 1000000\n248: 1\n249: 33\n250: 1000000\n251: 1\n252: 33",
"ergoTreeScript": "{\n val box1 = CONTEXT.dataInputs(placeholder[Int](0))\n val coll2 = box1.R4[AvlTree].get.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](1), placeholder[Coll[Byte]](2), placeholder[Coll[Byte]](3), placeholder[Coll[Byte]](4), placeholder[Coll[Byte]](5), placeholder[\n Coll[Byte]\n ](6), placeholder[Coll[Byte]](7), placeholder[Coll[Byte]](8), placeholder[Coll[Byte]](9), placeholder[Coll[Byte]](10), placeholder[Coll[Byte]](\n 11\n ), placeholder[Coll[Byte]](12), placeholder[Coll[Byte]](13), placeholder[Coll[Byte]](14), placeholder[Coll[Byte]](15), placeholder[Coll[Byte]](\n 16\n ), placeholder[Coll[Byte]](17), placeholder[Coll[Byte]](18), placeholder[Coll[Byte]](19), placeholder[Coll[Byte]](20), placeholder[Coll[Byte]](\n 21\n ), placeholder[Coll[Byte]](22), placeholder[Coll[Byte]](23), placeholder[Coll[Byte]](24), placeholder[Coll[Byte]](25), placeholder[Coll[Byte]](\n 26\n ), placeholder[Coll[Byte]](27)\n ), getVar[Coll[Byte]](0.toByte).get\n )\n val coll3 = coll2(placeholder[Int](28)).get\n val box4 = INPUTS(placeholder[Int](29))\n val avlTree5 = box4.R4[AvlTree].get\n val coll6 = avlTree5.getMany(\n Coll[Coll[Byte]](\n placeholder[Coll[Byte]](30), placeholder[Coll[Byte]](31), placeholder[Coll[Byte]](32), placeholder[Coll[Byte]](33), placeholder[Coll[Byte]](34)\n ), getVar[Coll[Byte]](1.toByte).get\n )\n val coll7 = coll6(placeholder[Int](35)).get.slice(placeholder[Int](36), placeholder[Int](37))\n val coll8 = Coll[Coll[Byte]](coll7)\n val coll9 = getVar[Coll[Coll[Byte]]](3.toByte).get\n val coll10 = coll9(placeholder[Int](38))\n val coll11 = coll2(placeholder[Int](39)).get\n val coll12 = coll9(placeholder[Int](40))\n val coll13 = coll2(placeholder[Int](41)).get\n val coll14 = coll6(placeholder[Int](42)).get.slice(placeholder[Int](43), placeholder[Int](44))\n val coll15 = coll6(placeholder[Int](45)).get.slice(placeholder[Int](46), placeholder[Int](47))\n val coll16 = Coll[Coll[Byte]](coll14, coll15)\n val coll17 = coll9(placeholder[Int](48))\n val coll18 = coll2(placeholder[Int](49)).get\n val coll19 = coll9(placeholder[Int](50))\n val coll20 = coll2(placeholder[Int](51)).get\n val coll21 = Coll[Coll[Byte]](coll14)\n val coll22 = coll9(placeholder[Int](52))\n val coll23 = coll2(placeholder[Int](53)).get\n val coll24 = coll9(placeholder[Int](54))\n val coll25 = coll2(placeholder[Int](55)).get\n val coll26 = coll9(placeholder[Int](56))\n val coll27 = coll2(placeholder[Int](57)).get\n val coll28 = coll9(placeholder[Int](58))\n val coll29 = coll2(placeholder[Int](59)).get\n val coll30 = coll9(placeholder[Int](60))\n val coll31 = coll2(placeholder[Int](61)).get\n val coll32 = coll9(placeholder[Int](62))\n val coll33 = coll2(placeholder[Int](63)).get\n val coll34 = coll9(placeholder[Int](64))\n val coll35 = coll2(placeholder[Int](65)).get\n val coll36 = coll9(placeholder[Int](66))\n val coll37 = coll2(placeholder[Int](67)).get\n val coll38 = coll9(placeholder[Int](68))\n val box39 = OUTPUTS(placeholder[Int](69))\n val coll40 = box39.tokens\n val coll41 = box4.tokens\n val tuple42 = coll40(placeholder[Int](70))\n val tuple43 = coll40(placeholder[Int](71))\n val box44 = OUTPUTS(placeholder[Int](72))\n val coll45 = box44.tokens\n val tuple46 = coll45(placeholder[Int](73))\n val coll47 = placeholder[Coll[Byte]](74)\n val coll48 = getVar[Coll[Coll[Byte]]](4.toByte).get\n val box49 = OUTPUTS(placeholder[Int](75))\n val coll50 = box49.tokens\n val coll51 = Coll[Byte](\n placeholder[Byte](76), placeholder[Byte](77), placeholder[Byte](78), placeholder[Byte](79), placeholder[Byte](80), placeholder[Byte](81), placeholder[Byte](\n 82\n ), placeholder[Byte](83), placeholder[Byte](84), placeholder[Byte](85), placeholder[Byte](86), placeholder[Byte](87), placeholder[Byte](88), placeholder[\n Byte\n ](89), placeholder[Byte](90), placeholder[Byte](91), placeholder[Byte](92), placeholder[Byte](93), placeholder[Byte](94), placeholder[Byte](\n 95\n ), placeholder[Byte](96), placeholder[Byte](97), placeholder[Byte](98), placeholder[Byte](99), placeholder[Byte](100), placeholder[Byte](101), placeholder[\n Byte\n ](102), placeholder[Byte](103), placeholder[Byte](104), placeholder[Byte](105), placeholder[Byte](106), placeholder[Byte](107), placeholder[Byte](108)\n )\n val coll52 = box49.R5[Coll[Long]].get\n val l53 = coll52(placeholder[Int](109))\n val l54 = CONTEXT.preHeader.timestamp\n val box55 = OUTPUTS(placeholder[Int](110))\n val box56 = OUTPUTS(placeholder[Int](111))\n val box57 = OUTPUTS(placeholder[Int](112))\n val box58 = OUTPUTS(placeholder[Int](113))\n val box59 = OUTPUTS(placeholder[Int](114))\n val box60 = OUTPUTS(placeholder[Int](115))\n val box61 = OUTPUTS(placeholder[Int](116))\n val box62 = OUTPUTS(placeholder[Int](117))\n sigmaProp(\n allOf(\n Coll[Boolean](\n box1.tokens(placeholder[Int](118))._1 == placeholder[Coll[Byte]](119), allOf(\n Coll[Boolean](\n coll2(placeholder[Int](120)).get.patch(\n placeholder[Int](121), blake2b256(\n substConstants(coll3.slice(placeholder[Int](122), coll3.size), Coll[Int](placeholder[Int](123)), coll8)\n ), placeholder[Int](124)\n ) == coll10, coll2(placeholder[Int](125)).get.patch(\n placeholder[Int](126), blake2b256(\n substConstants(coll11.slice(placeholder[Int](127), coll11.size), Coll[Int](placeholder[Int](128)), coll8)\n ), placeholder[Int](129)\n ) == coll12, coll2(placeholder[Int](130)).get.patch(\n placeholder[Int](131), blake2b256(\n substConstants(coll13.slice(placeholder[Int](132), coll13.size), Coll[Int](placeholder[Int](133), placeholder[Int](134)), coll16)\n ), placeholder[Int](135)\n ) == coll17, coll2(placeholder[Int](136)).get.patch(\n placeholder[Int](137), blake2b256(\n substConstants(coll18.slice(placeholder[Int](138), coll18.size), Coll[Int](placeholder[Int](139), placeholder[Int](140)), coll16)\n ), placeholder[Int](141)\n ) == coll19, coll2(placeholder[Int](142)).get.patch(\n placeholder[Int](143), blake2b256(\n substConstants(coll20.slice(placeholder[Int](144), coll20.size), Coll[Int](placeholder[Int](145)), coll21)\n ), placeholder[Int](146)\n ) == coll22, coll2(placeholder[Int](147)).get.patch(\n placeholder[Int](148), blake2b256(\n substConstants(coll23.slice(placeholder[Int](149), coll23.size), Coll[Int](placeholder[Int](150)), coll21)\n ), placeholder[Int](151)\n ) == coll24, coll2(placeholder[Int](152)).get.patch(\n placeholder[Int](153), blake2b256(\n substConstants(coll25.slice(placeholder[Int](154), coll25.size), Coll[Int](placeholder[Int](155)), coll21)\n ), placeholder[Int](156)\n ) == coll26, coll2(placeholder[Int](157)).get.patch(\n placeholder[Int](158), blake2b256(\n substConstants(coll27.slice(placeholder[Int](159), coll27.size), Coll[Int](placeholder[Int](160)), coll21)\n ), placeholder[Int](161)\n ) == coll28, coll2(placeholder[Int](162)).get.patch(\n placeholder[Int](163), blake2b256(\n substConstants(coll29.slice(placeholder[Int](164), coll29.size), Coll[Int](placeholder[Int](165)), coll21)\n ), placeholder[Int](166)\n ) == coll30, coll2(placeholder[Int](167)).get.patch(\n placeholder[Int](168), blake2b256(\n substConstants(coll31.slice(placeholder[Int](169), coll31.size), Coll[Int](placeholder[Int](170)), coll21)\n ), placeholder[Int](171)\n ) == coll32, coll2(placeholder[Int](172)).get.patch(\n placeholder[Int](173), blake2b256(\n substConstants(coll33.slice(placeholder[Int](174), coll33.size), Coll[Int](placeholder[Int](175)), coll21)\n ), placeholder[Int](176)\n ) == coll34, coll2(placeholder[Int](177)).get.patch(\n placeholder[Int](178), blake2b256(\n substConstants(coll35.slice(placeholder[Int](179), coll35.size), Coll[Int](placeholder[Int](180)), coll21)\n ), placeholder[Int](181)\n ) == coll36, coll2(placeholder[Int](182)).get.patch(\n placeholder[Int](183), blake2b256(\n substConstants(coll37.slice(placeholder[Int](184), coll37.size), Coll[Int](placeholder[Int](185)), coll21)\n ), placeholder[Int](186)\n ) == coll38\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box39.propositionBytes) == coll2(placeholder[Int](187)).get.slice(\n placeholder[Int](188), placeholder[Int](189)\n ), box39.value >= placeholder[Long](190), coll40(placeholder[Int](191)) == coll41(\n placeholder[Int](192)\n ), tuple42._1 == coll15, tuple42._2 == placeholder[Long](193), tuple43._1 == coll7, tuple43._2 == placeholder[Long](\n 194\n ), coll40.size == placeholder[Int](195), box39.R4[Coll[Byte]].get == coll14\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box44.propositionBytes) == coll10.slice(placeholder[Int](196), placeholder[Int](197)), box44.value >= placeholder[Long](\n 198\n ), tuple46._1 == coll14, tuple46._2 == placeholder[Long](199), coll45.size == placeholder[Int](200), box44.R4[\n AvlTree\n ].get.digest == avlTree5.insert(\n Coll[(Coll[Byte], Coll[Byte])](\n (placeholder[Coll[Byte]](201), coll12), (placeholder[Coll[Byte]](202), coll10), (\n blake2b256(coll47.append(coll48(placeholder[Int](203)))), coll17\n ), (blake2b256(coll47.append(coll48(placeholder[Int](204)))), coll19), (\n blake2b256(placeholder[Coll[Byte]](205).append(coll48(placeholder[Int](206)))), coll22\n ), (placeholder[Coll[Byte]](207), coll24), (placeholder[Coll[Byte]](208), coll32), (placeholder[Coll[Byte]](209), coll26), (\n placeholder[Coll[Byte]](210), coll28\n ), (placeholder[Coll[Byte]](211), coll30), (placeholder[Coll[Byte]](212), coll34), (placeholder[Coll[Byte]](213), coll38), (\n placeholder[Coll[Byte]](214), coll36\n )\n ), getVar[Coll[Byte]](2.toByte).get\n ).get.digest\n )\n ), allOf(\n Coll[Boolean](\n blake2b256(box49.propositionBytes) == coll34.slice(placeholder[Int](215), placeholder[Int](216)), box49.value >= placeholder[Long](217), coll50(\n placeholder[Int](218)\n )._1 == coll6(placeholder[Int](219)).get.slice(placeholder[Int](220), placeholder[Int](221)), coll50(placeholder[Int](222)) == coll41(\n placeholder[Int](223)\n ), coll50.size == placeholder[Int](224), box49.R4[Coll[AvlTree]].get.forall(\n {(avlTree63: AvlTree) => avlTree63.digest == coll51 }\n ), l53 > l54, l53 < l54 + byteArrayToLong(coll6(placeholder[Int](225)).get.slice(placeholder[Int](226), placeholder[Int](227))), coll52.slice(\n placeholder[Int](228), coll52.size\n ).forall({(l63: Long) => l63 == placeholder[Long](229) }), box49.R6[Coll[Coll[Long]]].get.flatMap({(coll63: Coll[Long]) => coll63 }).forall(\n {(l63: Long) => l63 == placeholder[Long](230) }\n ), box49.R7[Coll[(AvlTree, AvlTree)]].get.forall(\n {(tuple63: (AvlTree, AvlTree)) => (tuple63._1.digest == coll51) && (tuple63._2.digest == coll51) }\n ), box49.R8[Coll[Long]].get.forall({(l63: Long) => l63 == placeholder[Long](231) })\n )\n ), allOf(\n Coll[Boolean](\n box55.value >= placeholder[Long](232), blake2b256(box55.propositionBytes) == coll24.slice(\n placeholder[Int](233), placeholder[Int](234)\n ), box56.value >= placeholder[Long](235), blake2b256(box56.propositionBytes) == coll32.slice(\n placeholder[Int](236), placeholder[Int](237)\n ), box57.value >= placeholder[Long](238), blake2b256(box57.propositionBytes) == coll36.slice(\n placeholder[Int](239), placeholder[Int](240)\n ), box58.value >= placeholder[Long](241), blake2b256(box58.propositionBytes) == coll26.slice(\n placeholder[Int](242), placeholder[Int](243)\n ), box59.value >= placeholder[Long](244), blake2b256(box59.propositionBytes) == coll30.slice(\n placeholder[Int](245), placeholder[Int](246)\n ), box60.value >= placeholder[Long](247), blake2b256(box60.propositionBytes) == coll38.slice(\n placeholder[Int](248), placeholder[Int](249)\n ), box61.value >= placeholder[Long](250), blake2b256(box61.propositionBytes) == coll28.slice(placeholder[Int](251), placeholder[Int](252))\n )\n ), allOf(Coll[Boolean](box62.value >= SELF.value, box62.propositionBytes == SELF.propositionBytes))\n )\n )\n )\n}",
"address": "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",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "2d45fe271daf02f45f26b49859f0805122ed98afc8628c9b45f2f2ad37f91ce6",
"mainChain": true
},
{
"boxId": "ed5644878c0319bc724c5e3548792c849fa5d443d5ab48f4cb8f23866c078d15",
"transactionId": "8eec95840c38f69f9cc3143d2a9dfee447187f4e2bce7fdda25ffdbb40f28679",
"blockId": "53db8334b2e12f061fb64ea92aa2b02ecedb2c3c6cc0fcf15cbbc8245c5105cd",
"value": 1000000,
"index": 11,
"globalIndex": 37964207,
"creationHeight": 1221276,
"settlementHeight": 1221279,
"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": "73efd2e0a9bc023c70e6657d2fa3fc08c45000d390ac9cf5b46b2d2aa9058a4b",
"mainChain": true
}
],
"size": 41973,
"isUnconfirmed": false
}