Transaction
ID: 20e73af42a...e8cb
Inputs (3)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.21 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Outputs (5)
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.004 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.196 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.004 ERG
Spent
Address:
Spent in transaction:
Settlement height:
Value:
0.016 ERG
Transaction Details
Confirmations: 95,750
Total coins transferred: 0.23 ERG
Fees: 0.004 ERG
Fees per byte: 0.000001599 ERG
Raw Transaction Data
{
"id": "20e73af42acd98a2e54499090296aee7f2f7339185a444d07ca9ff40ae96e8cb",
"blockId": "03b3e3e84d070c2df09cc28c1e1c1554d14a1c3bcd18de7cc3a80b214fec2789",
"inclusionHeight": 1669391,
"timestamp": 1764743515357,
"index": 4,
"globalIndex": 9903496,
"numConfirmations": 95750,
"inputs": [
{
"boxId": "e220b2159063720f9f24643507425544856c67008d9516a5b2f366e579774596",
"value": 210000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "08ce73a674ca60dfc7865a696dcfac55dc13520829cb95172be5eb80c2a3c9c1",
"outputTransactionId": "4ed06620d84a52a0f1200b2ee9b6886f904b4df2c06f214853b45f7e4db46fb7",
"outputIndex": 0,
"outputGlobalIndex": 51983647,
"outputCreatedAt": 1668879,
"outputSettledAt": 1668880,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 1\n4: 0\n5: 1\n6: 3\n7: 69\n8: 82\n9: 71\n10: 2\n11: 0\n12: 0\n13: 1\n14: 1\n15: 1\n16: 0\n17: 0\n18: 2\n19: 2\n20: 1\n21: 1\n22: 1\n23: 1\n24: 3\n25: 2\n26: 3\n27: 0\n28: 1\n29: 2\n30: 10000000\n31: 10000000\n32: 10000000\n33: 1\n34: 3\n35: 3\n36: 2\n37: 2\n38: 10000000\n39: 10000000\n40: 10000000\n41: 1\n42: false\n43: 1\n44: 0\n45: 1\n46: 2\n47: 0\n48: 1\n49: 0\n50: 10000000\n51: 0\n52: 3\n53: 2\n54: 0\n55: 0\n56: 0\n57: 0\n58: 0\n59: 1\n60: 0\n61: 1\n62: 0\n63: 2\n64: 0\n65: 2\n66: 100\n67: 0\n68: 1\n69: 0\n70: 0\n71: 0\n72: 0\n73: 1\n74: true\n75: 2\n76: 1\n77: 1\n78: 0\n79: 0\n80: 0\n81: 10\n82: 1\n83: 2\n84: 3\n85: 10000000\n86: 2\n87: 10000000\n88: 2\n89: 10000000\n90: 2\n91: 10000000\n92: 3\n93: 2\n94: 2\n95: SigmaProp(ProveDlog(ECPoint(e45f52,5253a8,...)))\n96: 1\n97: 0\n98: 0\n99: 1\n100: 1\n101: 0\n102: true\n103: 0\n104: 0\n105: 0\n106: 0\n107: 0\n108: 0\n109: true\n110: false",
"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Int]].get\n val i2 = coll1(placeholder[Int](0))\n val i3 = coll1(placeholder[Int](1)) + i2\n val coll4 = SELF.propositionBytes\n val bool5 = OUTPUTS.filter({(box5: Box) => box5.propositionBytes == coll4 }).size == placeholder[Int](2)\n val bool6 = INPUTS.filter({(box6: Box) => box6.propositionBytes == coll4 }).size == placeholder[Int](3)\n val l7 = SELF.R4[Long].get\n val coll8 = SELF.tokens\n val coll9 = coll8(placeholder[Int](4))._1\n val tuple10 = coll8(placeholder[Int](5))\n val coll11 = tuple10._1\n val i12 = coll1(placeholder[Int](6))\n val coll13 = SELF.R8[Coll[Int]].get\n val l14 = SELF.R9[Long].get\n val coll15 = SELF.R6[Coll[Byte]].get\n val bool16 = coll15 == Coll[Byte](placeholder[Byte](7), placeholder[Byte](8), placeholder[Byte](9))\n val coll17 = SELF.R5[Coll[Byte]].get\n val i18 = coll1(placeholder[Int](10))\n if (HEIGHT < i3) {(\n val box19 = OUTPUTS(placeholder[Int](11))\n val coll20 = box19.tokens\n val i21 = coll20.size\n val tuple22 = coll20(placeholder[Int](12))\n val tuple23 = coll20(placeholder[Int](13))\n val l24 = tuple23._2\n val i25 = i12 + placeholder[Int](14) - l24.toInt\n val coll26 = box19.R8[Coll[Int]].get\n val box27 = OUTPUTS(placeholder[Int](15))\n val b28 = box27.R4[Byte].get\n val i29 = b28.toInt\n val tuple30 = box27.tokens(placeholder[Int](16))\n val opt31 = box27.R6[Coll[Byte]]\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((bool6 && bool5) && (l7 > placeholder[Long](17))) && (OUTPUTS.size >= placeholder[Int](18))) && (i21 >= placeholder[Int](19))\n ) && ((tuple22._1 == coll9) && (tuple22._2 == placeholder[Long](20)))\n ) && ((tuple23._1 == coll11) && (l24 == tuple10._2 - placeholder[Long](21)))\n ) && (i25 <= i12)\n ) && (((coll26(i29) == coll13(i29) + placeholder[Int](22)) && \n val i32 = i29 + placeholder[Int](23) % placeholder[Int](24)\n coll26(i32) == coll13(i32)\n ) && \n val i32 = i29 + placeholder[Int](25) % placeholder[Int](26)\n coll26(i32) == coll13(i32)\n )\n ) && (coll26(placeholder[Int](27)) + coll26(placeholder[Int](28)) + coll26(placeholder[Int](29)) == i25)\n ) && if (bool16) {(\n val l32 = box19.value\n val l33 = SELF.value\n val l34 = l32 - placeholder[Long](30) - l33 - placeholder[Long](31)\n ((((l34 >= l14) && (l32 == l33 + l34)) && (box27.value == placeholder[Long](32))) && (box27.tokens.size == placeholder[Int](33))) && (\n box27.R7[Long].get == l34\n )\n )} else {(\n val bool32 = (coll8.size >= placeholder[Int](34)) && (i21 >= placeholder[Int](35))\n bool32 && if (bool32) {(\n val tuple33 = coll8(placeholder[Int](36))\n val tuple34 = coll20(placeholder[Int](37))\n val l35 = tuple34._2\n val l36 = tuple33._2\n val l37 = l35 - l36\n (\n (\n (\n ((((tuple33._1 == coll15) && (tuple34._1 == coll15)) && (l37 >= l14)) && (l35 == l36 + l37)) && (\n (box19.value == placeholder[Long](38)) && (SELF.value == placeholder[Long](39))\n )\n ) && (box27.value == placeholder[Long](40))\n ) && (box27.tokens.size == placeholder[Int](41))\n ) && (box27.R7[Long].get == l37)\n )} else { placeholder[Boolean](42) }\n )}\n ) && (\n (\n (((box19.R4[Long].get == l7) && (box19.R5[Coll[Byte]].get == coll17)) && (box19.R6[Coll[Byte]].get == coll15)) && (\n box19.R7[Coll[Int]].get == coll1\n )\n ) && (box19.R9[Long].get == l14)\n )\n ) && (box19.propositionBytes == coll4)\n ) && ((tuple30._1 == coll11) && (tuple30._2 == placeholder[Long](43)))\n ) && (((b28 == placeholder[Byte](44)) || (b28 == placeholder[Byte](45))) || (b28 == placeholder[Byte](46)))\n ) && box27.R5[Coll[Byte]].isDefined\n ) && (opt31.isDefined && (opt31.get == coll9))\n )\n )} else { if (HEIGHT >= i3 + i18) {(\n val box19 = CONTEXT.dataInputs(placeholder[Int](47))\n val coll20 = box19.tokens\n val l21 = box19.R4[Long].get\n val coll22 = INPUTS.filter({(box22: Box) =>\n val coll24 = box22.tokens\n (coll24.size >= placeholder[Int](48)) && (coll24(placeholder[Int](49))._1 == coll11)\n })\n val i23 = coll22.size\n val tuple24 = if (bool16) {(\n val l24 = SELF.value - placeholder[Long](50)\n (l24, l24 == coll22.fold(placeholder[Long](51), {(tuple25: (Long, Box)) => tuple25._1 + tuple25._2.R7[Long].get }))\n )} else { if (coll8.size >= placeholder[Int](52)) {(\n val l24 = coll8(placeholder[Int](53))._2\n (l24, l24 == coll22.fold(placeholder[Long](54), {(tuple25: (Long, Box)) => tuple25._1 + tuple25._2.R7[Long].get }))\n )} else { (placeholder[Long](55), i23 == placeholder[Int](56)) } }\n val box25 = OUTPUTS(placeholder[Int](57))\n val coll26 = box25.tokens\n val i27 = coll26.size\n val tuple28 = coll26(placeholder[Int](58))\n val tuple29 = coll26(placeholder[Int](59))\n val coll30 = box25.R7[Coll[Int]].get\n val i31 = coll30(placeholder[Int](60))\n val coll32 = coll22.filter({(box32: Box) => box32.R4[Byte].get == if (l21 > l7) { placeholder[Byte](61) } else { if (l21 < l7) { placeholder[Byte](62) } else { placeholder[Byte](63) } } })\n val bool33 = coll32.size > placeholder[Int](64)\n val l34 = tuple24._1\n val l35 = l34 * placeholder[Int](65).toLong / placeholder[Long](66)\n val l36 = l34 - l35\n val bool37 = l34 > placeholder[Long](67)\n sigmaProp(((((((((((((((bool6 && bool5) && ((coll20.size >= placeholder[Int](68)) && (coll20(placeholder[Int](69))._1 == coll17))) && (l21 > placeholder[Long](70))) && tuple24._2) && if (i23 > placeholder[Int](71)) { coll22.forall({(box38: Box) =>\n val tuple40 = box38.tokens(placeholder[Int](72))\n (((((tuple40._1 == coll11) && (tuple40._2 == placeholder[Long](73))) && box38.R4[Byte].isDefined) && box38.R5[Coll[Byte]].isDefined) && box38.R6[Coll[Byte]].isDefined) && box38.R7[Long].isDefined\n }) } else { placeholder[Boolean](74) }) && (i27 >= placeholder[Int](75))) && ((tuple28._1 == coll9) && (tuple28._2 == placeholder[Long](76)))) && ((tuple29._1 == coll11) && (tuple29._2 == i12 + placeholder[Int](77).toLong))) && (box25.R8[Coll[Int]].get == Coll[Int](placeholder[Int](78), placeholder[Int](79), placeholder[Int](80)))) && (((((((box25.R4[Long].get == l21) && ((i31 >= HEIGHT) && (i31 <= HEIGHT + placeholder[Int](81)))) && (coll30(placeholder[Int](82)) == i2)) && (coll30(placeholder[Int](83)) == i18)) && (coll30(placeholder[Int](84)) == i12)) && (box25.R9[Long].get == l14)) && (box25.R6[Coll[Byte]].get == coll15))) && (box25.R5[Coll[Byte]].get == coll17)) && (box25.propositionBytes == coll4)) && if (bool33) { if (bool16) { (box25.value == placeholder[Long](85)) && (i27 == placeholder[Int](86)) } else { (box25.value == placeholder[Long](87)) && (i27 == placeholder[Int](88)) } } else { if (bool16) { (box25.value == placeholder[Long](89) + l36) && (i27 == placeholder[Int](90)) } else { (((box25.value == placeholder[Long](91)) && (i27 == placeholder[Int](92))) && (coll26(placeholder[Int](93))._1 == coll15)) && (coll26(placeholder[Int](94))._2 == l36) } }) && if (bool37) {(\n val coll38 = OUTPUTS.filter({(box38: Box) => box38.propositionBytes == placeholder[SigmaProp](95).propBytes })\n if (bool16) { (coll38.size >= placeholder[Int](96)) && (coll38(placeholder[Int](97)).value >= l35) } else {(\n val coll39 = coll38(placeholder[Int](98)).tokens.filter({(tuple39: (Coll[Byte], Long)) => tuple39._1 == coll15 })\n ((coll38.size >= placeholder[Int](99)) && (coll39.size >= placeholder[Int](100))) && (coll39(placeholder[Int](101))._2 >= l35)\n )}\n )} else { placeholder[Boolean](102) }) && if (bool33 && bool37) { coll32.forall({(box38: Box) =>\n val coll40 = box38.R5[Coll[Byte]].get\n val coll41 = OUTPUTS.filter({(box41: Box) => box41.propositionBytes == coll40 })\n val l42 = coll32.fold(placeholder[Long](103), {(tuple42: (Long, Box)) =>\n val box44 = tuple42._2\n val l45 = tuple42._1\n if (box44.R5[Coll[Byte]].get == coll40) { l45 + box44.R7[Long].get } else { l45 }\n }) * l36 / coll32.fold(placeholder[Long](104), {(tuple42: (Long, Box)) => tuple42._1 + tuple42._2.R7[Long].get })\n if (bool16) { coll41.fold(placeholder[Long](105), {(tuple43: (Long, Box)) => tuple43._1 + tuple43._2.value }) >= l42 } else { coll41.fold(placeholder[Long](106), {(tuple43: (Long, Box)) =>\n val coll45 = tuple43._2.tokens.filter({(tuple45: (Coll[Byte], Long)) => tuple45._1 == coll15 })\n val l46 = tuple43._1\n if (coll45.size > placeholder[Int](107)) { l46 + coll45(placeholder[Int](108))._2 } else { l46 }\n }) >= l42 }\n }) } else { placeholder[Boolean](109) })\n )} else { sigmaProp(placeholder[Boolean](110)) } }\n}",
"address": "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",
"assets": [
{
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"index": 0,
"amount": 1,
"name": "BG",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 1,
"amount": 4,
"name": "BvB P",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e206a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66",
"sigmaType": "Coll[SByte]",
"renderedValue": "6a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "455247"
},
"R8": {
"serializedValue": "1003020200",
"sigmaType": "Coll[SInt]",
"renderedValue": "[1,1,0]"
},
"R7": {
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"sigmaType": "Coll[SInt]",
"renderedValue": "[1668867,50,5,5]"
},
"R9": {
"serializedValue": "0580897a",
"sigmaType": "SLong",
"renderedValue": "1000000"
},
"R4": {
"serializedValue": "05eafdde870e",
"sigmaType": "SLong",
"renderedValue": "1887166325"
}
}
},
{
"boxId": "c060e81c29ff556a03d68e1541a320cbb8267eaf42163044b82e34329cfe6612",
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"index": 1,
"spendingProof": null,
"outputBlockId": "08ce73a674ca60dfc7865a696dcfac55dc13520829cb95172be5eb80c2a3c9c1",
"outputTransactionId": "4ed06620d84a52a0f1200b2ee9b6886f904b4df2c06f214853b45f7e4db46fb7",
"outputIndex": 1,
"outputGlobalIndex": 51983648,
"outputCreatedAt": 1668879,
"outputSettledAt": 1668880,
"ergoTree": "19a7010d0402040004020100040002000201020204000402040004020404d802d601b5a4d9010163d801d603db63087201ed92b172037300938cb2720373010001e4c6a7060ed602e4c6a7040295ef93b172017302d17303d802d603b27201730400d604e4c672030710d1ededecec937202730593720273069372027307938cb2db6308a7730800018cb2db630872037309000192a39a9ab27204730a00b27204730b00b27204730c00",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: false\n4: 0\n5: 0\n6: 1\n7: 2\n8: 0\n9: 1\n10: 0\n11: 1\n12: 2",
"ergoTreeScript": "{\n val coll1 = INPUTS.filter({(box1: Box) =>\n val coll3 = box1.tokens\n (coll3.size >= placeholder[Int](0)) && (coll3(placeholder[Int](1))._1 == SELF.R6[Coll[Byte]].get)\n })\n val b2 = SELF.R4[Byte].get\n if (!(coll1.size == placeholder[Int](2))) { sigmaProp(placeholder[Boolean](3)) } else {(\n val box3 = coll1(placeholder[Int](4))\n val coll4 = box3.R7[Coll[Int]].get\n sigmaProp(\n (\n (((b2 == placeholder[Byte](5)) || (b2 == placeholder[Byte](6))) || (b2 == placeholder[Byte](7))) && (\n SELF.tokens(placeholder[Int](8))._1 == box3.tokens(placeholder[Int](9))._1\n )\n ) && (HEIGHT >= coll4(placeholder[Int](10)) + coll4(placeholder[Int](11)) + coll4(placeholder[Int](12)))\n )\n )}\n}",
"address": "g9ax6LjaqrXeDXmbBaaTMGCR5NTRkVRPqQwu6kiw1KPhKbVtoX2FZo7D6ymmda5hJREm1P6kbY9MsYh6hVFYbn9jPyiTTgbBbn87Gti1MJdPVsBfRuAz693nqa9RozRTU3f1gq26pMH4Dgzg5HeGQVtD9qTifp9kqWLQa9pqVftq1g6yvH1QLpbGDT3Xrit6JJqYcZRVH4BRcXnZVyUXz6VrrkB77xhsVykYrY4C5Dw2eG",
"assets": [
{
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"index": 0,
"amount": 1,
"name": "BvB P",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
"serializedValue": "0201",
"sigmaType": "SByte",
"renderedValue": "1"
},
"R5": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd039ada8253425dab7c6c6be231cd1bf7cbd1c3b654e1fdd60d30ead80956e4e58f"
},
"R6": {
"serializedValue": "0e2017b17c29e4511d26b008bdbafccaa7fea9c89b2681febbc302af3993ef533761",
"sigmaType": "Coll[SByte]",
"renderedValue": "17b17c29e4511d26b008bdbafccaa7fea9c89b2681febbc302af3993ef533761"
},
"R7": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
}
}
},
{
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"value": 10000000,
"index": 2,
"spendingProof": null,
"outputBlockId": "3bf0db076f3bf4e668f56e887dfa9335e91403b962f7b3a98a44041f44fe7f1c",
"outputTransactionId": "ef34b274054ea3205f8a7ee8dd8a0b43e16021fa6d85c4e021825db1eba834c7",
"outputIndex": 1,
"outputGlobalIndex": 51983626,
"outputCreatedAt": 1668878,
"outputSettledAt": 1668879,
"ergoTree": "19a7010d0402040004020100040002000201020204000402040004020404d802d601b5a4d9010163d801d603db63087201ed92b172037300938cb2720373010001e4c6a7060ed602e4c6a7040295ef93b172017302d17303d802d603b27201730400d604e4c672030710d1ededecec937202730593720273069372027307938cb2db6308a7730800018cb2db630872037309000192a39a9ab27204730a00b27204730b00b27204730c00",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: false\n4: 0\n5: 0\n6: 1\n7: 2\n8: 0\n9: 1\n10: 0\n11: 1\n12: 2",
"ergoTreeScript": "{\n val coll1 = INPUTS.filter({(box1: Box) =>\n val coll3 = box1.tokens\n (coll3.size >= placeholder[Int](0)) && (coll3(placeholder[Int](1))._1 == SELF.R6[Coll[Byte]].get)\n })\n val b2 = SELF.R4[Byte].get\n if (!(coll1.size == placeholder[Int](2))) { sigmaProp(placeholder[Boolean](3)) } else {(\n val box3 = coll1(placeholder[Int](4))\n val coll4 = box3.R7[Coll[Int]].get\n sigmaProp(\n (\n (((b2 == placeholder[Byte](5)) || (b2 == placeholder[Byte](6))) || (b2 == placeholder[Byte](7))) && (\n SELF.tokens(placeholder[Int](8))._1 == box3.tokens(placeholder[Int](9))._1\n )\n ) && (HEIGHT >= coll4(placeholder[Int](10)) + coll4(placeholder[Int](11)) + coll4(placeholder[Int](12)))\n )\n )}\n}",
"address": "g9ax6LjaqrXeDXmbBaaTMGCR5NTRkVRPqQwu6kiw1KPhKbVtoX2FZo7D6ymmda5hJREm1P6kbY9MsYh6hVFYbn9jPyiTTgbBbn87Gti1MJdPVsBfRuAz693nqa9RozRTU3f1gq26pMH4Dgzg5HeGQVtD9qTifp9kqWLQa9pqVftq1g6yvH1QLpbGDT3Xrit6JJqYcZRVH4BRcXnZVyUXz6VrrkB77xhsVykYrY4C5Dw2eG",
"assets": [
{
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"index": 0,
"amount": 1,
"name": "BvB P",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R4": {
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"sigmaType": "SByte",
"renderedValue": "0"
},
"R5": {
"serializedValue": "0e240008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2",
"sigmaType": "Coll[SByte]",
"renderedValue": "0008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2"
},
"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "17b17c29e4511d26b008bdbafccaa7fea9c89b2681febbc302af3993ef533761"
},
"R7": {
"serializedValue": "058084af5f",
"sigmaType": "SLong",
"renderedValue": "100000000"
}
}
}
],
"dataInputs": [
{
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"value": 10000000,
"index": 0,
"outputBlockId": "bc36565416a012ca7336402d3f15c25706ec6a0a2b22fd76b18177115489b6ee",
"outputTransactionId": "348dcc59682befc81452b6a5984ac31f2503dfd1ab1a5c3a2078674f57dc34c6",
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"ergoTree": "1004040204000e2019b7f2e2f11052c020800c8b620660f9f0b5fd5b3f2beacc8b44af960477a6940e2030e273698c85bbe66319904c499bfefbd76f51487688d674b20623715ff0741bd801d6018cb2db6308b2a473000073010001d1ec93720173029372017303",
"address": "PViBL5acX6Pm6nD3FJQ3fZXESZTq8imJ47LJLMWtrhqm2nP5cVwMfXoHoqhnfvxUUKenebtEbLwZFTWPFRXJNsqLYDNWMtYAbvmqWgxCCPeH1fECQYtdZksCMwJrcmpLtNgfeADVEnmcUCPeTee8",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "05d8fbe5f50d",
"sigmaType": "SLong",
"renderedValue": "1868349164"
},
"R5": {
"serializedValue": "04cc5f",
"sigmaType": "SInt",
"renderedValue": "6118"
}
}
}
],
"outputs": [
{
"boxId": "cc03aa470b40c3fcab960bfe694bb806d171b093c0ca3ef34ceffea8d9af5e6f",
"transactionId": "20e73af42acd98a2e54499090296aee7f2f7339185a444d07ca9ff40ae96e8cb",
"blockId": "03b3e3e84d070c2df09cc28c1e1c1554d14a1c3bcd18de7cc3a80b214fec2789",
"value": 10000000,
"index": 0,
"globalIndex": 51999921,
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"ergoTreeScript": "{\n val coll1 = SELF.R7[Coll[Int]].get\n val i2 = coll1(placeholder[Int](0))\n val i3 = coll1(placeholder[Int](1)) + i2\n val coll4 = SELF.propositionBytes\n val bool5 = OUTPUTS.filter({(box5: Box) => box5.propositionBytes == coll4 }).size == placeholder[Int](2)\n val bool6 = INPUTS.filter({(box6: Box) => box6.propositionBytes == coll4 }).size == placeholder[Int](3)\n val l7 = SELF.R4[Long].get\n val coll8 = SELF.tokens\n val coll9 = coll8(placeholder[Int](4))._1\n val tuple10 = coll8(placeholder[Int](5))\n val coll11 = tuple10._1\n val i12 = coll1(placeholder[Int](6))\n val coll13 = SELF.R8[Coll[Int]].get\n val l14 = SELF.R9[Long].get\n val coll15 = SELF.R6[Coll[Byte]].get\n val bool16 = coll15 == Coll[Byte](placeholder[Byte](7), placeholder[Byte](8), placeholder[Byte](9))\n val coll17 = SELF.R5[Coll[Byte]].get\n val i18 = coll1(placeholder[Int](10))\n if (HEIGHT < i3) {(\n val box19 = OUTPUTS(placeholder[Int](11))\n val coll20 = box19.tokens\n val i21 = coll20.size\n val tuple22 = coll20(placeholder[Int](12))\n val tuple23 = coll20(placeholder[Int](13))\n val l24 = tuple23._2\n val i25 = i12 + placeholder[Int](14) - l24.toInt\n val coll26 = box19.R8[Coll[Int]].get\n val box27 = OUTPUTS(placeholder[Int](15))\n val b28 = box27.R4[Byte].get\n val i29 = b28.toInt\n val tuple30 = box27.tokens(placeholder[Int](16))\n val opt31 = box27.R6[Coll[Byte]]\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (((bool6 && bool5) && (l7 > placeholder[Long](17))) && (OUTPUTS.size >= placeholder[Int](18))) && (i21 >= placeholder[Int](19))\n ) && ((tuple22._1 == coll9) && (tuple22._2 == placeholder[Long](20)))\n ) && ((tuple23._1 == coll11) && (l24 == tuple10._2 - placeholder[Long](21)))\n ) && (i25 <= i12)\n ) && (((coll26(i29) == coll13(i29) + placeholder[Int](22)) && \n val i32 = i29 + placeholder[Int](23) % placeholder[Int](24)\n coll26(i32) == coll13(i32)\n ) && \n val i32 = i29 + placeholder[Int](25) % placeholder[Int](26)\n coll26(i32) == coll13(i32)\n )\n ) && (coll26(placeholder[Int](27)) + coll26(placeholder[Int](28)) + coll26(placeholder[Int](29)) == i25)\n ) && if (bool16) {(\n val l32 = box19.value\n val l33 = SELF.value\n val l34 = l32 - placeholder[Long](30) - l33 - placeholder[Long](31)\n ((((l34 >= l14) && (l32 == l33 + l34)) && (box27.value == placeholder[Long](32))) && (box27.tokens.size == placeholder[Int](33))) && (\n box27.R7[Long].get == l34\n )\n )} else {(\n val bool32 = (coll8.size >= placeholder[Int](34)) && (i21 >= placeholder[Int](35))\n bool32 && if (bool32) {(\n val tuple33 = coll8(placeholder[Int](36))\n val tuple34 = coll20(placeholder[Int](37))\n val l35 = tuple34._2\n val l36 = tuple33._2\n val l37 = l35 - l36\n (\n (\n (\n ((((tuple33._1 == coll15) && (tuple34._1 == coll15)) && (l37 >= l14)) && (l35 == l36 + l37)) && (\n (box19.value == placeholder[Long](38)) && (SELF.value == placeholder[Long](39))\n )\n ) && (box27.value == placeholder[Long](40))\n ) && (box27.tokens.size == placeholder[Int](41))\n ) && (box27.R7[Long].get == l37)\n )} else { placeholder[Boolean](42) }\n )}\n ) && (\n (\n (((box19.R4[Long].get == l7) && (box19.R5[Coll[Byte]].get == coll17)) && (box19.R6[Coll[Byte]].get == coll15)) && (\n box19.R7[Coll[Int]].get == coll1\n )\n ) && (box19.R9[Long].get == l14)\n )\n ) && (box19.propositionBytes == coll4)\n ) && ((tuple30._1 == coll11) && (tuple30._2 == placeholder[Long](43)))\n ) && (((b28 == placeholder[Byte](44)) || (b28 == placeholder[Byte](45))) || (b28 == placeholder[Byte](46)))\n ) && box27.R5[Coll[Byte]].isDefined\n ) && (opt31.isDefined && (opt31.get == coll9))\n )\n )} else { if (HEIGHT >= i3 + i18) {(\n val box19 = CONTEXT.dataInputs(placeholder[Int](47))\n val coll20 = box19.tokens\n val l21 = box19.R4[Long].get\n val coll22 = INPUTS.filter({(box22: Box) =>\n val coll24 = box22.tokens\n (coll24.size >= placeholder[Int](48)) && (coll24(placeholder[Int](49))._1 == coll11)\n })\n val i23 = coll22.size\n val tuple24 = if (bool16) {(\n val l24 = SELF.value - placeholder[Long](50)\n (l24, l24 == coll22.fold(placeholder[Long](51), {(tuple25: (Long, Box)) => tuple25._1 + tuple25._2.R7[Long].get }))\n )} else { if (coll8.size >= placeholder[Int](52)) {(\n val l24 = coll8(placeholder[Int](53))._2\n (l24, l24 == coll22.fold(placeholder[Long](54), {(tuple25: (Long, Box)) => tuple25._1 + tuple25._2.R7[Long].get }))\n )} else { (placeholder[Long](55), i23 == placeholder[Int](56)) } }\n val box25 = OUTPUTS(placeholder[Int](57))\n val coll26 = box25.tokens\n val i27 = coll26.size\n val tuple28 = coll26(placeholder[Int](58))\n val tuple29 = coll26(placeholder[Int](59))\n val coll30 = box25.R7[Coll[Int]].get\n val i31 = coll30(placeholder[Int](60))\n val coll32 = coll22.filter({(box32: Box) => box32.R4[Byte].get == if (l21 > l7) { placeholder[Byte](61) } else { if (l21 < l7) { placeholder[Byte](62) } else { placeholder[Byte](63) } } })\n val bool33 = coll32.size > placeholder[Int](64)\n val l34 = tuple24._1\n val l35 = l34 * placeholder[Int](65).toLong / placeholder[Long](66)\n val l36 = l34 - l35\n val bool37 = l34 > placeholder[Long](67)\n sigmaProp(((((((((((((((bool6 && bool5) && ((coll20.size >= placeholder[Int](68)) && (coll20(placeholder[Int](69))._1 == coll17))) && (l21 > placeholder[Long](70))) && tuple24._2) && if (i23 > placeholder[Int](71)) { coll22.forall({(box38: Box) =>\n val tuple40 = box38.tokens(placeholder[Int](72))\n (((((tuple40._1 == coll11) && (tuple40._2 == placeholder[Long](73))) && box38.R4[Byte].isDefined) && box38.R5[Coll[Byte]].isDefined) && box38.R6[Coll[Byte]].isDefined) && box38.R7[Long].isDefined\n }) } else { placeholder[Boolean](74) }) && (i27 >= placeholder[Int](75))) && ((tuple28._1 == coll9) && (tuple28._2 == placeholder[Long](76)))) && ((tuple29._1 == coll11) && (tuple29._2 == i12 + placeholder[Int](77).toLong))) && (box25.R8[Coll[Int]].get == Coll[Int](placeholder[Int](78), placeholder[Int](79), placeholder[Int](80)))) && (((((((box25.R4[Long].get == l21) && ((i31 >= HEIGHT) && (i31 <= HEIGHT + placeholder[Int](81)))) && (coll30(placeholder[Int](82)) == i2)) && (coll30(placeholder[Int](83)) == i18)) && (coll30(placeholder[Int](84)) == i12)) && (box25.R9[Long].get == l14)) && (box25.R6[Coll[Byte]].get == coll15))) && (box25.R5[Coll[Byte]].get == coll17)) && (box25.propositionBytes == coll4)) && if (bool33) { if (bool16) { (box25.value == placeholder[Long](85)) && (i27 == placeholder[Int](86)) } else { (box25.value == placeholder[Long](87)) && (i27 == placeholder[Int](88)) } } else { if (bool16) { (box25.value == placeholder[Long](89) + l36) && (i27 == placeholder[Int](90)) } else { (((box25.value == placeholder[Long](91)) && (i27 == placeholder[Int](92))) && (coll26(placeholder[Int](93))._1 == coll15)) && (coll26(placeholder[Int](94))._2 == l36) } }) && if (bool37) {(\n val coll38 = OUTPUTS.filter({(box38: Box) => box38.propositionBytes == placeholder[SigmaProp](95).propBytes })\n if (bool16) { (coll38.size >= placeholder[Int](96)) && (coll38(placeholder[Int](97)).value >= l35) } else {(\n val coll39 = coll38(placeholder[Int](98)).tokens.filter({(tuple39: (Coll[Byte], Long)) => tuple39._1 == coll15 })\n ((coll38.size >= placeholder[Int](99)) && (coll39.size >= placeholder[Int](100))) && (coll39(placeholder[Int](101))._2 >= l35)\n )}\n )} else { placeholder[Boolean](102) }) && if (bool33 && bool37) { coll32.forall({(box38: Box) =>\n val coll40 = box38.R5[Coll[Byte]].get\n val coll41 = OUTPUTS.filter({(box41: Box) => box41.propositionBytes == coll40 })\n val l42 = coll32.fold(placeholder[Long](103), {(tuple42: (Long, Box)) =>\n val box44 = tuple42._2\n val l45 = tuple42._1\n if (box44.R5[Coll[Byte]].get == coll40) { l45 + box44.R7[Long].get } else { l45 }\n }) * l36 / coll32.fold(placeholder[Long](104), {(tuple42: (Long, Box)) => tuple42._1 + tuple42._2.R7[Long].get })\n if (bool16) { coll41.fold(placeholder[Long](105), {(tuple43: (Long, Box)) => tuple43._1 + tuple43._2.value }) >= l42 } else { coll41.fold(placeholder[Long](106), {(tuple43: (Long, Box)) =>\n val coll45 = tuple43._2.tokens.filter({(tuple45: (Coll[Byte], Long)) => tuple45._1 == coll15 })\n val l46 = tuple43._1\n if (coll45.size > placeholder[Int](107)) { l46 + coll45(placeholder[Int](108))._2 } else { l46 }\n }) >= l42 }\n }) } else { placeholder[Boolean](109) })\n )} else { sigmaProp(placeholder[Boolean](110)) } }\n}",
"address": "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",
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{
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"index": 0,
"amount": 1,
"name": "BG",
"decimals": 0,
"type": "EIP-004"
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"index": 1,
"amount": 6,
"name": "BvB P",
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"additionalRegisters": {
"R5": {
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"sigmaType": "Coll[SByte]",
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"R6": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "455247"
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"R8": {
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"sigmaType": "Coll[SInt]",
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