Transaction
ID: 5b3fdd777f...f7e0
Inputs (1)
Spent
Address:
Output transaction:
Settlement height:
Value:
2.01 ERG
Tokens:
Loading assets...
Outputs (3)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
2 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.001 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.0022 ERG
Transaction Details
Confirmations: 19,172
Total coins transferred: 2.01 ERG
Fees: 0.0022 ERG
Fees per byte: 0.000000763 ERG
Raw Transaction Data
{
"id": "5b3fdd777f012f6e93b43ab8215ab12f01f472762a032a93088b35c6aebbf7e0",
"blockId": "bee78e846adde23ff774248d0cb04482f27f77ed25a1cb16cf8c8296d0cb6cc2",
"inclusionHeight": 1748554,
"timestamp": 1774314619412,
"index": 14,
"globalIndex": 10490949,
"numConfirmations": 19172,
"inputs": [
{
"boxId": "907708721375573956480ddb5a479583b611cf609229adf8d8435da0e899fd5c",
"value": 2006400000,
"index": 0,
"spendingProof": "43608fc01de3929a15603a77212f89e9889fcd71a00612ad8e86d1b39fd4f5de6fbb87ab045a60e8c439a4022501e67f6df78743320d160f",
"outputBlockId": "bebb3b8cb2e8d5318405b18857744424b3adb6b726be00ca0899d97fc75f8306",
"outputTransactionId": "d3589ec973046f802f35468cc7f7d725e57ec54e8463493907b4b12a301be7d2",
"outputIndex": 0,
"outputGlobalIndex": 54309564,
"outputCreatedAt": 1748550,
"outputSettledAt": 1748552,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: 0\n8: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n9: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n10: 10\n11: 4\n12: 6\n13: 1000000\n14: false\n15: 5\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 720\n26: 1\n27: 0\n28: 0\n29: 1\n30: 2\n31: 1\n32: 3\n33: 0\n34: 1000000\n35: 0\n36: 0\n37: 0\n38: 17\n39: 0\n40: 0\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 1000\n48: 100\n49: 1000\n50: 0\n51: 100\n52: 0\n53: 2\n54: 0\n55: 17\n56: 1\n57: 2\n58: 17\n59: 0\n60: 17\n61: 1000000\n62: 0\n63: 3\n64: 2000000\n65: 1\n66: 1\n67: 1\n68: 1\n69: 2\n70: 1\n71: 1000000\n72: 0\n73: 1\n74: 2\n75: 1\n76: 0\n77: false\n78: 1\n79: 3\n80: 1000000\n81: 1\n82: 1000000\n83: 1\n84: 1\n85: false\n86: 0\n87: 0\n88: 0\n89: 0\n90: 0\n91: 1000000\n92: 1000000\n93: 0\n94: 0\n95: 1000\n96: 0\n97: 17\n98: 0\n99: 17\n100: 2\n101: 1\n102: 2\n103: 0\n104: true\n105: 1\n106: 2\n107: 0\n108: true\n109: false\n110: 1\n111: 0\n112: 1\n113: 0\n114: 0\n115: 0\n116: 0\n117: 1000000\n118: 0\n119: Coll(49,-126,103,79,7,-37,-71,-115,105,109,56,-19,-91,62,99,-21,59,-11,-2,87,15,113,-34,-24,94,-71,84,-42,-49,-112,59,-70)\n120: 0\n121: 0\n122: 0\n123: true\n124: false\n125: 2\n126: false",
"ergoTreeScript": "{\n val coll1 = SELF.R9[Coll[Coll[Byte]]].get\n val prop2 = proveDlog(decodePoint(coll1(placeholder[Int](0))))\n val coll3 = SELF.tokens\n val tuple4 = (Coll[Byte](), placeholder[Long](1))\n val tuple5 = coll3.getOrElse(placeholder[Int](2), tuple4)\n val coll6 = tuple5._1\n val coll7 = SELF.R7[Coll[Byte]].get\n val bool8 = coll6 == coll7\n val bool9 = !bool8\n val box10 = OUTPUTS(placeholder[Int](3))\n val coll11 = box10.propositionBytes\n val coll12 = prop2.propBytes\n val coll13 = SELF.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = coll13(placeholder[Int](5))\n val coll16 = placeholder[Coll[Byte]](6)\n val l17 = coll13(placeholder[Int](7))\n val coll18 = placeholder[Coll[Byte]](8)\n val coll19 = placeholder[Coll[Byte]](9)\n val l20 = coll13(placeholder[Int](10))\n val l21 = coll13(placeholder[Int](11))\n val l22 = coll13(placeholder[Int](12))\n val l23 = l22 + placeholder[Long](13)\n val coll24 = SELF.R5[Coll[Byte]].get\n val bool25 = if (coll11 == SELF.propositionBytes) {\n (\n (\n (((box10.value >= l23) && (box10.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box10.R5[Coll[Byte]].get == coll24)) && (\n box10.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get\n )\n ) && (box10.R8[Coll[Long]].get == coll13)\n ) && (box10.R9[Coll[Coll[Byte]]].get == coll1)\n } else { placeholder[Boolean](14) }\n val coll26 = SELF.id\n val l27 = coll13(placeholder[Int](15))\n val coll28 = box10.tokens\n val tuple29 = coll28.getOrElse(placeholder[Int](16), tuple4)\n val coll30 = tuple29._1\n val tuple31 = coll28.getOrElse(placeholder[Int](17), tuple4)\n val l32 = tuple5._2\n val l33 = coll13(placeholder[Int](18))\n val l34 = tuple29._2\n val coll35 = tuple31._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l32 == placeholder[Long](21))\n val tuple40 = coll3.getOrElse(placeholder[Int](22), tuple4)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple4)\n val l42 = HEIGHT.toLong\n val l43 = coll13(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll13(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val l49 = tuple46._1\n if (box48.id != coll26) { box48.tokens.fold(l49, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) } else { l49 }\n })\n val bool47 = ((bool25 && (box10.R7[Coll[Byte]].get == coll7)) && \n val coll47 = coll30\n coll47 == coll6\n ) && (l34 == placeholder[Long](29))\n val l48 = tuple31._2\n prop2 && sigmaProp((bool9 && (OUTPUTS.size == placeholder[Int](30))) && (coll11 == coll12)) || sigmaProp(\n (((if ((bool9 && (INPUTS.size == placeholder[Int](31))) && (OUTPUTS.size == placeholder[Int](32))) {(\n val bool49 = l14 == placeholder[Long](33)\n val l50 = l21 * l20 / placeholder[Long](34)\n val bool51 = l50 > placeholder[Long](35)\n ((((((((((if (bool49) {(\n val box52 = CONTEXT.dataInputs(placeholder[Int](36))\n val i53 = l15.toInt\n val l54 = box52.R5[Coll[Long]].get(i53)\n val bool55 = box52.tokens(placeholder[Int](37))._1 == coll16\n val coll56 = box52.R4[Coll[Coll[Byte]]].get(i53)\n if (l15 == placeholder[Long](38)) { bool55 && (l54 > placeholder[Long](39)) } else { if (l17 == placeholder[Long](40)) { ((bool55 && (coll56.size > placeholder[Int](41))) && (l54 > placeholder[Long](42))) && (coll3(placeholder[Int](43))._1 == coll56) } else { (bool55 && (coll56.size > placeholder[Int](44))) && (l54 > placeholder[Long](45)) } }\n )} else {(\n val coll52 = coll3(placeholder[Int](46))._1\n (coll52 == coll18) || (coll52 == coll19)\n )} && if (bool49) { (l20 == placeholder[Long](47)) || (l20 == placeholder[Long](48)) } else { ((l20 == placeholder[Long](49)) && (coll3(placeholder[Int](50))._1 == coll18)) || ((l20 == placeholder[Long](51)) && (coll3(placeholder[Int](52))._1 == coll19)) }) && bool51) && bool25) && (box10.R7[Coll[Byte]].get == coll26)) && (box10.value == SELF.value - l22 - l27)) && (box10.value >= placeholder[Long](53) * l23)) && (coll30 == coll26)) && \n val bool52 = l17 == placeholder[Long](54)\n ((((((((bool52 && bool49) && (l15 != placeholder[Long](55))) && \n val coll53 = coll35\n coll53 == coll24\n ) && (tuple31 == tuple5)) && (l34 == l32 / l33 + placeholder[Long](56))) && (coll28.size == placeholder[Int](57))) || (((bool52 && bool49) && (l15 == placeholder[Long](58))) && \n val l53 = l33 * CONTEXT.dataInputs(placeholder[Int](59)).R5[Coll[Long]].get(placeholder[Int](60)) / placeholder[Long](61)\n val l54 = SELF.value\n (((l53 > placeholder[Long](62)) && (l34 == l54 - placeholder[Long](63) * l22 - l27 - placeholder[Long](64) / l53 + placeholder[Long](65))) && (coll28.size == placeholder[Int](66))) && (box10.value >= l54 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](67)) && bool49) && (coll35 == coll24)) && (tuple31 == tuple5)) && bool51) && (l34 == l32 / l50 + placeholder[Long](68))) && (coll28.size == placeholder[Int](69)))) || ((l14 == placeholder[Long](70)) && \n val l53 = l36 * l20 / placeholder[Long](71)\n ((((l53 > placeholder[Long](72)) && (coll35 == coll24)) && (tuple31 == tuple5)) && (l34 == l32 / l53 + placeholder[Long](73))) && (coll28.size == placeholder[Int](74))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](75)))) && (coll38.size == placeholder[Int](76))) && (box37.value >= l27)\n )} else { placeholder[Boolean](77) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](78))) && (OUTPUTS.size == placeholder[Int](79))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](80)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](81))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](82))) && (coll38.size == placeholder[Int](83))) && (tuple41._1 == coll6)) && (tuple41._2 == l32 - placeholder[Long](84)) } else { placeholder[Boolean](85) }) || if ((bool45 && (l14 == placeholder[Long](86))) && (l46 > placeholder[Long](87))) {(\n val box49 = CONTEXT.dataInputs(placeholder[Int](88))\n val i50 = l15.toInt\n val l51 = box49.R5[Coll[Long]].get(i50)\n val bool52 = l51 > placeholder[Long](89)\n val bool53 = box49.tokens(placeholder[Int](90))._1 == coll16\n val l54 = l33 * l51 / placeholder[Long](91)\n val l55 = l21 * l20 / placeholder[Long](92)\n val bool56 = (l54 > placeholder[Long](93)) && (l55 > placeholder[Long](94))\n val l57 = l54 * l46\n val coll58 = if (l20 == placeholder[Long](95)) { coll18 } else { coll19 }\n val l59 = l55 * l46\n val coll60 = box49.R4[Coll[Coll[Byte]]].get(i50)\n val bool61 = (coll60.size > placeholder[Int](96)) || (l15 == placeholder[Long](97))\n if (l17 == placeholder[Long](98)) { if (l15 == placeholder[Long](99)) {(\n val box62 = OUTPUTS(placeholder[Int](100))\n (((((bool53 && bool52) && bool56) && (box37.value >= l57)) && ((box62.propositionBytes == coll12) && box62.tokens.exists({(tuple63: (Coll[Byte], Long)) => (tuple63._1 == coll58) && (tuple63._2 >= l59) }))) && bool47) && (box10.value >= SELF.value - l57 - l22)\n )} else {(\n val tuple62 = coll3(placeholder[Int](101))\n val box63 = OUTPUTS(placeholder[Int](102))\n (((((((((bool53 && bool61) && bool52) && bool56) && (tuple62._1 == coll60)) && coll38.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll60) && (tuple64._2 >= l57) })) && ((box63.propositionBytes == coll12) && box63.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll58) && (tuple64._2 >= l59) }))) && if (l48 > placeholder[Long](103)) { coll35 == coll60 } else { placeholder[Boolean](104) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l57)\n )} } else {(\n val tuple62 = coll3(placeholder[Int](105))\n val coll63 = tuple62._1\n val box64 = OUTPUTS(placeholder[Int](106))\n (((((((((bool53 && bool61) && bool52) && bool56) && ((coll63 == coll18) || (coll63 == coll19))) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll63) && (tuple65._2 >= l59) })) && ((box64.propositionBytes == coll12) && box64.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll60) && (tuple65._2 >= l57) }))) && if (l48 > placeholder[Long](107)) { coll35 == coll63 } else { placeholder[Boolean](108) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l59)\n )}\n )} else { placeholder[Boolean](109) }) || if ((bool45 && (l14 == placeholder[Long](110))) && (l46 > placeholder[Long](111))) {(\n val tuple49 = coll3(placeholder[Int](112))\n val coll50 = tuple49._1\n val box51 = CONTEXT.dataInputs(placeholder[Int](113))\n val l52 = box51.R8[Coll[Long]].get(l15.toInt)\n val l53 = if (l17 == placeholder[Long](114)) { if (l52 > l21) {(\n val l53 = l52 - l21\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](115) } } else { if (l52 < l21) {(\n val l53 = l21 - l52\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](116) } }\n val l54 = l53 * l20 / placeholder[Long](117)\n val l55 = l54 * l46\n (((((((((coll50 == coll18) || (coll50 == coll19)) && (box51.tokens(placeholder[Int](118))._1 == placeholder[Coll[Byte]](119))) && (l53 > placeholder[Long](120))) && (l54 > placeholder[Long](121))) && coll38.exists({(tuple56: (Coll[Byte], Long)) => (tuple56._1 == coll50) && (tuple56._2 >= l55) })) && if (l48 > placeholder[Long](122)) { coll35 == coll50 } else { placeholder[Boolean](123) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple49._2 - l55)\n )} else { placeholder[Boolean](124) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](125)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](126) }\n )\n}",
"address": "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",
"assets": [
{
"tokenId": "02053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524",
"index": 0,
"amount": 3,
"name": "ERG Call $0.30",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110b000080897a94b7d501b09a2480dac40980c78c022200b09a24d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,1000000,1748426,296600,10000000,2200000,17,0,296600,1000]"
},
"R7": {
"serializedValue": "0e2002053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524",
"sigmaType": "Coll[SByte]",
"renderedValue": "02053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524"
},
"R9": {
"serializedValue": "1a022102795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73240008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73,0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8]"
},
"R4": {
"serializedValue": "0e0e4552472043616c6c2024302e3330",
"sigmaType": "Coll[SByte]",
"renderedValue": "4552472043616c6c2024302e3330"
}
}
}
],
"dataInputs": [],
"outputs": [
{
"boxId": "6cdae2910a6f2ba0d568ef659ffbd0ad843871ae2890436d9140eeff48237c4b",
"transactionId": "5b3fdd777f012f6e93b43ab8215ab12f01f472762a032a93088b35c6aebbf7e0",
"blockId": "bee78e846adde23ff774248d0cb04482f27f77ed25a1cb16cf8c8296d0cb6cc2",
"value": 2003200000,
"index": 0,
"globalIndex": 54309676,
"creationHeight": 1748553,
"settlementHeight": 1748554,
"ergoTree": "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",
"ergoTreeConstants": "0: 0\n1: 0\n2: 0\n3: 0\n4: 8\n5: 7\n6: Coll(-22,123,54,-30,-108,-79,-87,84,-88,7,82,-22,-62,-120,113,23,40,-27,-71,27,11,60,5,-106,84,-116,117,86,101,5,11,-120)\n7: 0\n8: Coll(-91,91,-121,53,-19,26,-103,-28,108,44,-119,-8,-103,74,-84,-33,75,17,9,-67,-49,104,47,30,91,52,71,-100,110,57,38,105)\n9: Coll(3,-6,-14,-53,50,-97,46,-112,-42,-46,59,88,-39,27,-69,108,4,106,-95,67,38,28,-62,31,82,-5,-30,-126,75,-4,-65,4)\n10: 10\n11: 4\n12: 6\n13: 1000000\n14: false\n15: 5\n16: 0\n17: 1\n18: 2\n19: 9\n20: 1\n21: 1\n22: 1\n23: 0\n24: 3\n25: 720\n26: 1\n27: 0\n28: 0\n29: 1\n30: 2\n31: 1\n32: 3\n33: 0\n34: 1000000\n35: 0\n36: 0\n37: 0\n38: 17\n39: 0\n40: 0\n41: 0\n42: 0\n43: 0\n44: 0\n45: 0\n46: 0\n47: 1000\n48: 100\n49: 1000\n50: 0\n51: 100\n52: 0\n53: 2\n54: 0\n55: 17\n56: 1\n57: 2\n58: 17\n59: 0\n60: 17\n61: 1000000\n62: 0\n63: 3\n64: 2000000\n65: 1\n66: 1\n67: 1\n68: 1\n69: 2\n70: 1\n71: 1000000\n72: 0\n73: 1\n74: 2\n75: 1\n76: 0\n77: false\n78: 1\n79: 3\n80: 1000000\n81: 1\n82: 1000000\n83: 1\n84: 1\n85: false\n86: 0\n87: 0\n88: 0\n89: 0\n90: 0\n91: 1000000\n92: 1000000\n93: 0\n94: 0\n95: 1000\n96: 0\n97: 17\n98: 0\n99: 17\n100: 2\n101: 1\n102: 2\n103: 0\n104: true\n105: 1\n106: 2\n107: 0\n108: true\n109: false\n110: 1\n111: 0\n112: 1\n113: 0\n114: 0\n115: 0\n116: 0\n117: 1000000\n118: 0\n119: Coll(49,-126,103,79,7,-37,-71,-115,105,109,56,-19,-91,62,99,-21,59,-11,-2,87,15,113,-34,-24,94,-71,84,-42,-49,-112,59,-70)\n120: 0\n121: 0\n122: 0\n123: true\n124: false\n125: 2\n126: false",
"ergoTreeScript": "{\n val coll1 = SELF.R9[Coll[Coll[Byte]]].get\n val prop2 = proveDlog(decodePoint(coll1(placeholder[Int](0))))\n val coll3 = SELF.tokens\n val tuple4 = (Coll[Byte](), placeholder[Long](1))\n val tuple5 = coll3.getOrElse(placeholder[Int](2), tuple4)\n val coll6 = tuple5._1\n val coll7 = SELF.R7[Coll[Byte]].get\n val bool8 = coll6 == coll7\n val bool9 = !bool8\n val box10 = OUTPUTS(placeholder[Int](3))\n val coll11 = box10.propositionBytes\n val coll12 = prop2.propBytes\n val coll13 = SELF.R8[Coll[Long]].get\n val l14 = coll13(placeholder[Int](4))\n val l15 = coll13(placeholder[Int](5))\n val coll16 = placeholder[Coll[Byte]](6)\n val l17 = coll13(placeholder[Int](7))\n val coll18 = placeholder[Coll[Byte]](8)\n val coll19 = placeholder[Coll[Byte]](9)\n val l20 = coll13(placeholder[Int](10))\n val l21 = coll13(placeholder[Int](11))\n val l22 = coll13(placeholder[Int](12))\n val l23 = l22 + placeholder[Long](13)\n val coll24 = SELF.R5[Coll[Byte]].get\n val bool25 = if (coll11 == SELF.propositionBytes) {\n (\n (\n (((box10.value >= l23) && (box10.R4[Coll[Byte]].get == SELF.R4[Coll[Byte]].get)) && (box10.R5[Coll[Byte]].get == coll24)) && (\n box10.R6[Coll[Byte]].get == SELF.R6[Coll[Byte]].get\n )\n ) && (box10.R8[Coll[Long]].get == coll13)\n ) && (box10.R9[Coll[Coll[Byte]]].get == coll1)\n } else { placeholder[Boolean](14) }\n val coll26 = SELF.id\n val l27 = coll13(placeholder[Int](15))\n val coll28 = box10.tokens\n val tuple29 = coll28.getOrElse(placeholder[Int](16), tuple4)\n val coll30 = tuple29._1\n val tuple31 = coll28.getOrElse(placeholder[Int](17), tuple4)\n val l32 = tuple5._2\n val l33 = coll13(placeholder[Int](18))\n val l34 = tuple29._2\n val coll35 = tuple31._1\n val l36 = coll13(placeholder[Int](19))\n val box37 = OUTPUTS(placeholder[Int](20))\n val coll38 = box37.tokens\n val bool39 = bool8 && (l32 == placeholder[Long](21))\n val tuple40 = coll3.getOrElse(placeholder[Int](22), tuple4)\n val tuple41 = coll38.getOrElse(placeholder[Int](23), tuple4)\n val l42 = HEIGHT.toLong\n val l43 = coll13(placeholder[Int](24))\n val l44 = l43 + placeholder[Long](25)\n val bool45 = if (coll13(placeholder[Int](26)) == placeholder[Long](27)) { (bool39 && (l42 >= l43)) && (l42 <= l44) } else { bool39 && (l42 <= l44) }\n val l46 = INPUTS.fold(placeholder[Long](28), {(tuple46: (Long, Box)) =>\n val box48 = tuple46._2\n val l49 = tuple46._1\n if (box48.id != coll26) { box48.tokens.fold(l49, {(tuple50: (Long, (Coll[Byte], Long))) =>\n val tuple52 = tuple50._2\n val l53 = tuple50._1\n if (tuple52._1 == coll7) { l53 + tuple52._2 } else { l53 }\n }) } else { l49 }\n })\n val bool47 = ((bool25 && (box10.R7[Coll[Byte]].get == coll7)) && \n val coll47 = coll30\n coll47 == coll6\n ) && (l34 == placeholder[Long](29))\n val l48 = tuple31._2\n prop2 && sigmaProp((bool9 && (OUTPUTS.size == placeholder[Int](30))) && (coll11 == coll12)) || sigmaProp(\n (((if ((bool9 && (INPUTS.size == placeholder[Int](31))) && (OUTPUTS.size == placeholder[Int](32))) {(\n val bool49 = l14 == placeholder[Long](33)\n val l50 = l21 * l20 / placeholder[Long](34)\n val bool51 = l50 > placeholder[Long](35)\n ((((((((((if (bool49) {(\n val box52 = CONTEXT.dataInputs(placeholder[Int](36))\n val i53 = l15.toInt\n val l54 = box52.R5[Coll[Long]].get(i53)\n val bool55 = box52.tokens(placeholder[Int](37))._1 == coll16\n val coll56 = box52.R4[Coll[Coll[Byte]]].get(i53)\n if (l15 == placeholder[Long](38)) { bool55 && (l54 > placeholder[Long](39)) } else { if (l17 == placeholder[Long](40)) { ((bool55 && (coll56.size > placeholder[Int](41))) && (l54 > placeholder[Long](42))) && (coll3(placeholder[Int](43))._1 == coll56) } else { (bool55 && (coll56.size > placeholder[Int](44))) && (l54 > placeholder[Long](45)) } }\n )} else {(\n val coll52 = coll3(placeholder[Int](46))._1\n (coll52 == coll18) || (coll52 == coll19)\n )} && if (bool49) { (l20 == placeholder[Long](47)) || (l20 == placeholder[Long](48)) } else { ((l20 == placeholder[Long](49)) && (coll3(placeholder[Int](50))._1 == coll18)) || ((l20 == placeholder[Long](51)) && (coll3(placeholder[Int](52))._1 == coll19)) }) && bool51) && bool25) && (box10.R7[Coll[Byte]].get == coll26)) && (box10.value == SELF.value - l22 - l27)) && (box10.value >= placeholder[Long](53) * l23)) && (coll30 == coll26)) && \n val bool52 = l17 == placeholder[Long](54)\n ((((((((bool52 && bool49) && (l15 != placeholder[Long](55))) && \n val coll53 = coll35\n coll53 == coll24\n ) && (tuple31 == tuple5)) && (l34 == l32 / l33 + placeholder[Long](56))) && (coll28.size == placeholder[Int](57))) || (((bool52 && bool49) && (l15 == placeholder[Long](58))) && \n val l53 = l33 * CONTEXT.dataInputs(placeholder[Int](59)).R5[Coll[Long]].get(placeholder[Int](60)) / placeholder[Long](61)\n val l54 = SELF.value\n (((l53 > placeholder[Long](62)) && (l34 == l54 - placeholder[Long](63) * l22 - l27 - placeholder[Long](64) / l53 + placeholder[Long](65))) && (coll28.size == placeholder[Int](66))) && (box10.value >= l54 - l22 - l27)\n )) || (((((((l17 == placeholder[Long](67)) && bool49) && (coll35 == coll24)) && (tuple31 == tuple5)) && bool51) && (l34 == l32 / l50 + placeholder[Long](68))) && (coll28.size == placeholder[Int](69)))) || ((l14 == placeholder[Long](70)) && \n val l53 = l36 * l20 / placeholder[Long](71)\n ((((l53 > placeholder[Long](72)) && (coll35 == coll24)) && (tuple31 == tuple5)) && (l34 == l32 / l53 + placeholder[Long](73))) && (coll28.size == placeholder[Int](74))\n )\n ) && (box37.propositionBytes == coll1(placeholder[Int](75)))) && (coll38.size == placeholder[Int](76))) && (box37.value >= l27)\n )} else { placeholder[Boolean](77) } || if (((bool8 && (!bool39)) && (INPUTS.size == placeholder[Int](78))) && (OUTPUTS.size == placeholder[Int](79))) { ((((((((((box10.value == SELF.value - l22 - placeholder[Long](80)) && bool25) && (box10.R7[Coll[Byte]].get == coll7)) && (coll30 == coll6)) && (l34 == placeholder[Long](81))) && (tuple31 == tuple40)) && (box37.propositionBytes == coll12)) && (box37.value == placeholder[Long](82))) && (coll38.size == placeholder[Int](83))) && (tuple41._1 == coll6)) && (tuple41._2 == l32 - placeholder[Long](84)) } else { placeholder[Boolean](85) }) || if ((bool45 && (l14 == placeholder[Long](86))) && (l46 > placeholder[Long](87))) {(\n val box49 = CONTEXT.dataInputs(placeholder[Int](88))\n val i50 = l15.toInt\n val l51 = box49.R5[Coll[Long]].get(i50)\n val bool52 = l51 > placeholder[Long](89)\n val bool53 = box49.tokens(placeholder[Int](90))._1 == coll16\n val l54 = l33 * l51 / placeholder[Long](91)\n val l55 = l21 * l20 / placeholder[Long](92)\n val bool56 = (l54 > placeholder[Long](93)) && (l55 > placeholder[Long](94))\n val l57 = l54 * l46\n val coll58 = if (l20 == placeholder[Long](95)) { coll18 } else { coll19 }\n val l59 = l55 * l46\n val coll60 = box49.R4[Coll[Coll[Byte]]].get(i50)\n val bool61 = (coll60.size > placeholder[Int](96)) || (l15 == placeholder[Long](97))\n if (l17 == placeholder[Long](98)) { if (l15 == placeholder[Long](99)) {(\n val box62 = OUTPUTS(placeholder[Int](100))\n (((((bool53 && bool52) && bool56) && (box37.value >= l57)) && ((box62.propositionBytes == coll12) && box62.tokens.exists({(tuple63: (Coll[Byte], Long)) => (tuple63._1 == coll58) && (tuple63._2 >= l59) }))) && bool47) && (box10.value >= SELF.value - l57 - l22)\n )} else {(\n val tuple62 = coll3(placeholder[Int](101))\n val box63 = OUTPUTS(placeholder[Int](102))\n (((((((((bool53 && bool61) && bool52) && bool56) && (tuple62._1 == coll60)) && coll38.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll60) && (tuple64._2 >= l57) })) && ((box63.propositionBytes == coll12) && box63.tokens.exists({(tuple64: (Coll[Byte], Long)) => (tuple64._1 == coll58) && (tuple64._2 >= l59) }))) && if (l48 > placeholder[Long](103)) { coll35 == coll60 } else { placeholder[Boolean](104) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l57)\n )} } else {(\n val tuple62 = coll3(placeholder[Int](105))\n val coll63 = tuple62._1\n val box64 = OUTPUTS(placeholder[Int](106))\n (((((((((bool53 && bool61) && bool52) && bool56) && ((coll63 == coll18) || (coll63 == coll19))) && coll38.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll63) && (tuple65._2 >= l59) })) && ((box64.propositionBytes == coll12) && box64.tokens.exists({(tuple65: (Coll[Byte], Long)) => (tuple65._1 == coll60) && (tuple65._2 >= l57) }))) && if (l48 > placeholder[Long](107)) { coll35 == coll63 } else { placeholder[Boolean](108) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple62._2 - l59)\n )}\n )} else { placeholder[Boolean](109) }) || if ((bool45 && (l14 == placeholder[Long](110))) && (l46 > placeholder[Long](111))) {(\n val tuple49 = coll3(placeholder[Int](112))\n val coll50 = tuple49._1\n val box51 = CONTEXT.dataInputs(placeholder[Int](113))\n val l52 = box51.R8[Coll[Long]].get(l15.toInt)\n val l53 = if (l17 == placeholder[Long](114)) { if (l52 > l21) {(\n val l53 = l52 - l21\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](115) } } else { if (l52 < l21) {(\n val l53 = l21 - l52\n if (l53 > l36) { l36 } else { l53 }\n )} else { placeholder[Long](116) } }\n val l54 = l53 * l20 / placeholder[Long](117)\n val l55 = l54 * l46\n (((((((((coll50 == coll18) || (coll50 == coll19)) && (box51.tokens(placeholder[Int](118))._1 == placeholder[Coll[Byte]](119))) && (l53 > placeholder[Long](120))) && (l54 > placeholder[Long](121))) && coll38.exists({(tuple56: (Coll[Byte], Long)) => (tuple56._1 == coll50) && (tuple56._2 >= l55) })) && if (l48 > placeholder[Long](122)) { coll35 == coll50 } else { placeholder[Boolean](123) }) && bool47) && (box10.value >= SELF.value - l22)) && (l48 >= tuple49._2 - l55)\n )} else { placeholder[Boolean](124) }) || if (l42 > l44) {\n ((((OUTPUTS.size == placeholder[Int](125)) && (coll11 == coll12)) && (box10.value >= SELF.value - l22)) && (coll30 == tuple40._1)) && (l34 == tuple40._2)\n } else { placeholder[Boolean](126) }\n )\n}",
"address": "3Ax4aNq7NeCxX8BSQtiuLXNemUWD2TaEjz1o3RxP8cjWMwbhDbUv1o5kd4NHFcvfL1y7WKVtpx4aUCTw4aAm2238FUtRF85h4CpgB4n4HFrSGK5LAjgPV9TBGGFr2T2FZaxjz1KQkJ5EXVPfHxyTf5GqZfjiCrUipW5jBTzuF7qU4iTd832r2ELWmKVGaJDbcH9TQgUf7NQSTkGeHruG6qVZfQaiz7nWktWR9dnsrpTASUc9oLw7HerWotVE5TKb7SM3HiNLdhyuhM3ZtVb6x5xywHek7oPHWYeDs7TPCbfVeBDRhJJWWr6rpReyFvwHWwQbSGt1LPhvcBz8iQ4QnNC6koqYwy3g71QZf96ppaG6sEkV8dmPnJAgL8KoaipuSdxYYVV2tuXoVZ34zqY6JXXLxcT8wTsyCQD3KZh2cbx7j4iHoVHZiZbffc14YhhocbM6UB9soVWtccgawXLmzwA2gFfZVasm8DbLXjmWgRiPPsBeQWLQfhRJMe1gpz8fqLSYYjqecXCeN2H1ZwQZeuCU81a4n1MT5D2EbQPPRqaLtxJY69McQTqxDJc23KiNouwQxSMSwdzprmsz6Afckos91AhHoL5ZuKJYJLChcgbbLw1Qt8PpsnorAuXJGEtQZGPkUhFmFuQxwtJK9K3MxrmEsh9fDu3KNDei9faNojbF6RBxTVTyyz7QDGfVQaW9gmChB2abMjvTaLsPnUdddwEv4QWbPPVWUm1ViziUtgihcXJDRpoxwkcXM8oFJzJPjDXMsDj1YsJhQ1SG5bx4gdoAoadMM7BfqUdH34WYxdjeBJmS1PJP4Lz2ZFLhyRAKnTsg8QxpSprKPnweMT61Nzv8EWwMFg2KKEy6Aqc3gG4QBMTNFLuUo836d5BB8RwdeuPEBhjYXiyzYjS6EoPQNAyJs1SR6GRcxqXZmKmvzJpRJ2bFcTFe5KLm6bi41k6xwnJmQW3nedGCY9Ed7XYUsiwPoHBZZLfpoth6ibZsaipkdDDtP266WYQPdU5iNGRKeqtJtbniq2bXn4rBxMMBctDyyiuLUo4gPiXUGCwkYhrDknWky2bue69uRjM8kuEF1RwBRxJZh46SSL5qg2JLyySiLd9faDcCRUhf5AoMp9gZRbZVJa2egSDsSZvAFTszb5VEpUoCjbFB6GS1zZk4TufVcqgYpuUtoBvVWoox92DzdqET6xqKNUmoCCGCHZnXfxx7QJyzEo8mfrumS7veM37RARghkk2qtq8eLE9avtfJABN5TeduNRqRTrh1rQEe7aWzyMHrQTKPRiUd1Fr7Xju36k68MKkXhgWfzJHdkkM7B6BTRTvD6TPJGDxwC3R4ymaSzba33fHpw1FDUcVgnCsgmBToHCakmwCDBepSH8ZsUPWNQqu9x931DHRw6MrJEMgxQ5RxcZGc8o4ARVTz9jji75T5sr5CmT683S25xJ2L8mv8Q7L2YJy53fqSCHcBzaJB8zWnbBF5FBaCbuGFK5EGmTJeM9nQptrKQAh3yw281WZXdiixXoDgnUtn5898Y8HdRNg7sZXsPQB8vRsjvngnujicBgTvpEdi8hf3tZt9dcfc71tZL3JL7459bd7K4TtmDhaQkyBtXCaPXZjEnPBBBRtsd9YvWzYWy8gm8WFvo1bH1725rcFDc1Sp1YguVKaLepaFf9FVHjBRu4ecehiSasbgXMKJdb5yZMVTmuVgEziatqYiVctK5Agv3HcrWCn4trC1r7SQSzbCTcpmesqLPrm3zNKbzofkDbauV7LtN1JkPXsSzjBQFqUzGbXiHjMSyqYh7w4yxisAn9eNthmLxHSb55kR2K1d6BJhzru5x48CacfeAyj5Ptd2CwZW6FLsQkbhanHrS3bcfEmkxtQ3U2jCD4CXEhvTEWktnfrtAv5RpmqgidiaTr2iLfQbzFgitiM3nDD1FyJihBiLTTPdhGdK5D8fS3Ft8hZhyVSp46xURLfNZwH1CyEhpQ38nVsLuLpehnsy7JhQNTcwxHqZsQi6Kr7UmpJfdqAUxwG1Ptqj5suBcwp7EmJBjKzj8tnhKTWhAuPsS8nCwCyjJtZi58umSXp8ZhzkKsWt4ZHodRjvUqqjDRSEYpk136NSwVgSphXUondTtDQpULdVLMVwYdd49EdQwLbpyNYpAJmrWUyybXqm589X7iqr4Vuo8PD677NPT7CWwSXN28d2S7XYuxDd7sbka8647ZzEujiDPKu86n1ANwMdmEejHWitT79dNoMKRNQ83L7xjhqUcbEpvgWMR1BhYbrMAY9mAnxTY1p9Znmpt8fJpqoPPVB3yUzSqkc3xSVtmwdVzffLUo2XRxW8mYQ1wBXHF3HMKcU7WhGnde6cwoSvShb8efxg9iVYKGzVt7e56NKBq5RUv7SR6qiLU19c2R4RRUfPR4LQ7GEqu24NhZYSCZZ5ancaBnaki2fxn1YumTYAb94idg8Fo4rf9pwF6DHraT4tdzTagzVt5LC8FR6gruqdUpCaW2iEyqabuh2jjiaA6hN4e5oH9gwJSuGFA8kEPTKYDBtV9RAqKTnH5GtVEVFFMW1SAG3ibn3gXtVb3dihfidgGHW4VcpQWT3MayhvCKTobgCYoPgHYpus8QnsamA3gcVR6674aES53RYPdbJNXobeQ13iYH4mYcPjAfpvi6N64HN1ydCkQZ6UXCfRY8BYqTAK7FUVzQMgENrc4zjuEfyvvNb1biH2LhayK9XN7Hkw6sxNxi37CoydscrcD6nFX7rLEkPkmXFTQaNkDN2W7sRHvNNypJNLu88ProTibiuoByaksBbtmdcbZwcCEJSUoP3o4HT1euCzKLpyCUPXj7m6H6VuZekYdNYBz6etXpo2whGnZKBYTR4L5CDTDYEwfaYRQAMMJYtdD14rPvbLKuAmp2ah8e4ozT4CEoSHigp92NBkmeC8L36ZdH13VJfbkEEau4wh458iYcTXFoETPjDDdXbyidfGpnFmtVGeYsmv6bG1LsALmgkrnDfso2ALNMjP72vJYRah2p82XztrxuumM6XufGbkzd9yrFMKQu6ZFeYzo5FNit3uTBNdyBh36qyvS1QQhnaAbhXymv1rUMoNsWGei1P8bDCUm7kyWG6fynuwMADhXyk5r742ECvusK6hmzHxAgJLQ2Hh655StYtM2Kn1s6rQ9djbsT9VbF7he3fJwFpzMJMsKChSDSpwJv3erqHGTVb8XTZjMdYmaR7qmAs1N9abHih9KcB2w7Kus7irCLkRnGJrThyEtZaPw6b79847xScgVVTtQkS2TzLmTCa2stfM3t1iBYcAZC1iC8FBuckUrUiYg3BQT",
"assets": [
{
"tokenId": "02053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524",
"index": 0,
"amount": 1,
"name": "ERG Call $0.30",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e00",
"sigmaType": "Coll[SByte]",
"renderedValue": ""
},
"R6": {
"serializedValue": "0e0130",
"sigmaType": "Coll[SByte]",
"renderedValue": "30"
},
"R8": {
"serializedValue": "110b000080897a94b7d501b09a2480dac40980c78c022200b09a24d00f",
"sigmaType": "Coll[SLong]",
"renderedValue": "[0,0,1000000,1748426,296600,10000000,2200000,17,0,296600,1000]"
},
"R7": {
"serializedValue": "0e2002053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524",
"sigmaType": "Coll[SByte]",
"renderedValue": "02053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524"
},
"R9": {
"serializedValue": "1a022102795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73240008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8",
"sigmaType": "Coll[Coll[SByte]]",
"renderedValue": "[02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73,0008cd02383747243fed0a3ae9fcf0f3936d92447b57bb34c53faf5c5c0a105fbf42b4c8]"
},
"R4": {
"serializedValue": "0e0e4552472043616c6c2024302e3330",
"sigmaType": "Coll[SByte]",
"renderedValue": "4552472043616c6c2024302e3330"
}
},
"spentTransactionId": "ae34319cac6913e0b8c49eaf68b770488c92451466735fa89fba3dd2214a7434",
"mainChain": true
},
{
"boxId": "bb9db30350d4b5fa3f841c2ab3585947e29eeec15d29b4731a9c63543aeb0b84",
"transactionId": "5b3fdd777f012f6e93b43ab8215ab12f01f472762a032a93088b35c6aebbf7e0",
"blockId": "bee78e846adde23ff774248d0cb04482f27f77ed25a1cb16cf8c8296d0cb6cc2",
"value": 1000000,
"index": 1,
"globalIndex": 54309677,
"creationHeight": 1748553,
"settlementHeight": 1748554,
"ergoTree": "0008cd02795f3b7a0ebae08365c6a3a4e82cad02fb51c7b0e13d53026d695a5ff9287f73",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(795f3b,350403,...)))}",
"address": "9fSWoM7h4mnQBJXzKAaGrVtB6qaQevmB7cZEjEVEAVgTKnYAF6P",
"assets": [
{
"tokenId": "02053345561de94698cae89dab4c000bd72031e4be41e37704da6460a9253524",
"index": 0,
"amount": 2,
"name": "ERG Call $0.30",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {},
"spentTransactionId": "980c0321682e2e91810e49fc3b4bcaffcd03829f33e0b3a70c756395b4fee75a",
"mainChain": true
},
{
"boxId": "ace092d22901a521745e6dc04ef6f4008fcc68edab76e4e6de6d8cb971fdb7d6",
"transactionId": "5b3fdd777f012f6e93b43ab8215ab12f01f472762a032a93088b35c6aebbf7e0",
"blockId": "bee78e846adde23ff774248d0cb04482f27f77ed25a1cb16cf8c8296d0cb6cc2",
"value": 2200000,
"index": 2,
"globalIndex": 54309678,
"creationHeight": 1748553,
"settlementHeight": 1748554,
"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": "7ec4e78ba6e13e43d706ed13ee36fb2e578a391aedb76fd37bb3115c5a360581",
"mainChain": true
}
],
"size": 2882,
"isUnconfirmed": false
}