Transaction
ID: 49121ab5ff...4969
Inputs (2)
Spent
Address:
Output transaction:
Settlement height:
Value:
0.01 ERG
Tokens:
Loading assets...
Spent
Address:
Output transaction:
Settlement height:
Value:
0.1470992 ERG
Outputs (3)
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:
0.1430992 ERG
Transaction Details
Confirmations: 87,985
Total coins transferred: 0.1570992 ERG
Fees: 0.004 ERG
Fees per byte: 0.000001565 ERG
Raw Transaction Data
{
"id": "49121ab5ff92ce7ea8d80792423669d7ea11bbd2f0e0255b17d1582945e24969",
"blockId": "2459bcec305b028c8326f434b0730e4ab415dcc3413f33dbebd64da59d6ad439",
"inclusionHeight": 1673227,
"timestamp": 1765205867766,
"index": 1,
"globalIndex": 9932077,
"numConfirmations": 87985,
"inputs": [
{
"boxId": "b5569ca6b0830ad9845cf3d030083efef8a5b38d6f6792407f919c847e253921",
"value": 10000000,
"index": 0,
"spendingProof": null,
"outputBlockId": "fd130f529e96b7d575b3763ea54ee9f2d2a6276f5af2d21f60607e8e40ff6665",
"outputTransactionId": "9fc6eba525f78ad639742724cd24c65a9e31d9a5eb4d5ee827303a1b56f98be9",
"outputIndex": 0,
"outputGlobalIndex": 52114883,
"outputCreatedAt": 1673219,
"outputSettledAt": 1673222,
"ergoTree": "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",
"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 1\n4: 0\n5: 1\n6: 3\n7: 0\n8: 69\n9: 82\n10: 71\n11: 1\n12: 2\n13: 5\n14: 0\n15: 0\n16: 1\n17: 1\n18: 1\n19: 0\n20: 0\n21: 2\n22: 2\n23: 1\n24: 1\n25: 1\n26: 1\n27: 3\n28: 2\n29: 3\n30: 0\n31: 1\n32: 2\n33: 10000000\n34: 10000000\n35: 10000000\n36: 1\n37: 2\n38: 3\n39: 2\n40: 3\n41: 2\n42: 0\n43: 2\n44: 10000000\n45: 10000000\n46: 10000000\n47: 1\n48: false\n49: 1\n50: 0\n51: 1\n52: 2\n53: 1\n54: 0\n55: 1\n56: 0\n57: 10000000\n58: 0\n59: 3\n60: 2\n61: 0\n62: 0\n63: 0\n64: 0\n65: 0\n66: 0\n67: 1\n68: 0\n69: 1\n70: 0\n71: 2\n72: 0\n73: 1\n74: 2\n75: 100\n76: 0\n77: 1\n78: 0\n79: 0\n80: 15\n81: 0\n82: 0\n83: 1\n84: true\n85: 2\n86: 1\n87: 1\n88: 0\n89: 0\n90: 0\n91: 5\n92: 1\n93: 2\n94: 3\n95: 4\n96: 4\n97: 5\n98: 10000000\n99: 2\n100: 10000000\n101: 2\n102: 10000000\n103: 2\n104: 10000000\n105: 3\n106: 2\n107: 0\n108: 0\n109: SigmaProp(ProveDlog(ECPoint(e45f52,5253a8,...)))\n110: 1\n111: 0\n112: 0\n113: 1\n114: 1\n115: 0\n116: true\n117: 0\n118: 0\n119: 0\n120: 0\n121: 0\n122: 0\n123: true\n124: 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 coll14 = SELF.R9[Coll[Long]].get\n val l15 = coll14(placeholder[Int](7))\n val coll16 = SELF.R6[Coll[Byte]].get\n val bool17 = coll16 == Coll[Byte](placeholder[Byte](8), placeholder[Byte](9), placeholder[Byte](10))\n val coll18 = SELF.R5[Coll[Byte]].get\n val l19 = coll14(placeholder[Int](11))\n val i20 = coll1(placeholder[Int](12))\n val i21 = coll1(placeholder[Int](13))\n if (HEIGHT < i3) {(\n val box22 = OUTPUTS(placeholder[Int](14))\n val coll23 = box22.tokens\n val i24 = coll23.size\n val tuple25 = coll23(placeholder[Int](15))\n val tuple26 = coll23(placeholder[Int](16))\n val l27 = tuple26._2\n val i28 = i12 + placeholder[Int](17) - l27.toInt\n val coll29 = box22.R8[Coll[Int]].get\n val box30 = OUTPUTS(placeholder[Int](18))\n val b31 = box30.R4[Byte].get\n val i32 = b31.toInt\n val tuple33 = box30.tokens(placeholder[Int](19))\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool6 && bool5) && (l7 > placeholder[Long](20))) && (OUTPUTS.size >= placeholder[Int](21))) && (i24 >= placeholder[Int](22))) && (\n (tuple25._1 == coll9) && (tuple25._2 == placeholder[Long](23))\n )\n ) && ((tuple26._1 == coll11) && (l27 == tuple10._2 - placeholder[Long](24)))\n ) && (i28 <= i12)\n ) && (((coll29(i32) == coll13(i32) + placeholder[Int](25)) && \n val i34 = i32 + placeholder[Int](26) % placeholder[Int](27)\n coll29(i34) == coll13(i34)\n ) && \n val i34 = i32 + placeholder[Int](28) % placeholder[Int](29)\n coll29(i34) == coll13(i34)\n )\n ) && (coll29(placeholder[Int](30)) + coll29(placeholder[Int](31)) + coll29(placeholder[Int](32)) == i28)\n ) && if (bool17) {(\n val l34 = box22.value\n val l35 = SELF.value\n val l36 = l34 - placeholder[Long](33) - l35 - placeholder[Long](34)\n ((((l36 >= l15) && (l34 == l35 + l36)) && (box30.value == placeholder[Long](35))) && (box30.tokens.size == placeholder[Int](36))) && (\n box30.R6[Long].get == l36\n )\n )} else {(\n val i34 = coll8.size\n val bool35 = (i34 >= placeholder[Int](37)) && (i24 >= placeholder[Int](38))\n bool35 && if (bool35) {(\n val tuple36 = coll23(placeholder[Int](39))\n val l37 = tuple36._2\n val l38 = if (i34 >= placeholder[Int](40)) { coll8(placeholder[Int](41))._2 } else { placeholder[Long](42) }\n val l39 = l37 - l38\n (\n (\n (\n ((((coll8(placeholder[Int](43))._1 == coll16) && (tuple36._1 == coll16)) && (l39 >= l15)) && (l37 == l38 + l39)) && (\n (box22.value == placeholder[Long](44)) && (SELF.value == placeholder[Long](45))\n )\n ) && (box30.value == placeholder[Long](46))\n ) && (box30.tokens.size == placeholder[Int](47))\n ) && (box30.R6[Long].get == l39)\n )} else { placeholder[Boolean](48) }\n )}\n ) && (\n (\n (((box22.R4[Long].get == l7) && (box22.R5[Coll[Byte]].get == coll18)) && (box22.R6[Coll[Byte]].get == coll16)) && (\n box22.R7[Coll[Int]].get == coll1\n )\n ) && (box22.R9[Coll[Long]].get == coll14)\n )\n ) && (box22.propositionBytes == coll4)\n ) && ((tuple33._1 == coll11) && (tuple33._2 == placeholder[Long](49)))\n ) && (((b31 == placeholder[Byte](50)) || (b31 == placeholder[Byte](51))) || (b31 == placeholder[Byte](52)))\n ) && (proveDlog(box30.R5[GroupElement].get).propBytes == INPUTS(placeholder[Int](53)).propositionBytes)\n )\n )} else { if (HEIGHT >= i3 + i20) {(\n val box22 = CONTEXT.dataInputs(placeholder[Int](54))\n val coll23 = box22.tokens\n val l24 = box22.R4[Long].get\n val coll25 = INPUTS.filter({(box25: Box) =>\n val coll27 = box25.tokens\n (coll27.size >= placeholder[Int](55)) && (coll27(placeholder[Int](56))._1 == coll11)\n })\n val i26 = coll25.size\n val tuple27 = if (bool17) {(\n val l27 = SELF.value - placeholder[Long](57)\n (l27, l27 == coll25.fold(placeholder[Long](58), {(tuple28: (Long, Box)) => tuple28._1 + tuple28._2.R6[Long].get }) + l19)\n )} else { if (coll8.size >= placeholder[Int](59)) {(\n val l27 = coll8(placeholder[Int](60))._2\n (l27, l27 == coll25.fold(placeholder[Long](61), {(tuple28: (Long, Box)) => tuple28._1 + tuple28._2.R6[Long].get }) + l19)\n )} else { (placeholder[Long](62), (i26 == placeholder[Int](63)) && (l19 == placeholder[Long](64))) } }\n val box28 = OUTPUTS(placeholder[Int](65))\n val coll29 = box28.tokens\n val i30 = coll29.size\n val tuple31 = coll29(placeholder[Int](66))\n val tuple32 = coll29(placeholder[Int](67))\n val coll33 = box28.R7[Coll[Int]].get\n val i34 = coll33(placeholder[Int](68))\n val coll35 = coll25.filter({(box35: Box) => box35.R4[Byte].get == if (l24 > l7) { placeholder[Byte](69) } else { if (l24 < l7) { placeholder[Byte](70) } else { placeholder[Byte](71) } } })\n val bool36 = coll35.size > placeholder[Int](72)\n val coll37 = box28.R9[Coll[Long]].get\n val l38 = coll37(placeholder[Int](73))\n val l39 = tuple27._1\n val l40 = l39 * placeholder[Int](74).toLong / placeholder[Long](75)\n val l41 = l39 - l40\n val bool42 = l39 > placeholder[Long](76)\n sigmaProp((((((((((((((((((bool6 && bool5) && ((coll23.size >= placeholder[Int](77)) && (coll23(placeholder[Int](78))._1 == coll18))) && (l24 > placeholder[Long](79))) && (HEIGHT - box22.creationInfo._1 <= placeholder[Int](80))) && tuple27._2) && if (i26 > placeholder[Int](81)) { coll25.forall({(box43: Box) =>\n val tuple45 = box43.tokens(placeholder[Int](82))\n ((((tuple45._1 == coll11) && (tuple45._2 == placeholder[Long](83))) && box43.R4[Byte].isDefined) && box43.R5[GroupElement].isDefined) && box43.R6[Long].isDefined\n }) } else { placeholder[Boolean](84) }) && (i30 >= placeholder[Int](85))) && ((tuple31._1 == coll9) && (tuple31._2 == placeholder[Long](86)))) && ((tuple32._1 == coll11) && (tuple32._2 == i12 + placeholder[Int](87).toLong))) && (box28.R8[Coll[Int]].get == Coll[Int](placeholder[Int](88), placeholder[Int](89), placeholder[Int](90)))) && ((((((((box28.R4[Long].get == l24) && ((i34 >= HEIGHT) && (i34 <= HEIGHT + placeholder[Int](91)))) && (coll33(placeholder[Int](92)) == i2)) && (coll33(placeholder[Int](93)) == i20)) && (coll33(placeholder[Int](94)) == i12)) && (coll33(placeholder[Int](95)) == coll1(placeholder[Int](96)) + i21)) && (coll33(placeholder[Int](97)) == i21)) && (box28.R6[Coll[Byte]].get == coll16))) && (box28.R5[Coll[Byte]].get == coll18)) && (box28.propositionBytes == coll4)) && if (bool36) { if (bool17) { (box28.value == placeholder[Long](98)) && (i30 == placeholder[Int](99)) } else { (box28.value == placeholder[Long](100)) && (i30 == placeholder[Int](101)) } } else { if (bool17) { (box28.value == placeholder[Long](102) + l38) && (i30 == placeholder[Int](103)) } else { ((box28.value == placeholder[Long](104)) && (i30 == placeholder[Int](105))) && (coll29(placeholder[Int](106))._2 == l38) } }) && (coll37(placeholder[Int](107)) == l15)) && (l38 == if (bool36) { placeholder[Long](108) } else { l41 })) && if (bool42) {(\n val coll43 = OUTPUTS.filter({(box43: Box) => box43.propositionBytes == placeholder[SigmaProp](109).propBytes })\n if (bool17) { (coll43.size >= placeholder[Int](110)) && (coll43(placeholder[Int](111)).value >= l40) } else {(\n val coll44 = coll43(placeholder[Int](112)).tokens.filter({(tuple44: (Coll[Byte], Long)) => tuple44._1 == coll16 })\n ((coll43.size >= placeholder[Int](113)) && (coll44.size >= placeholder[Int](114))) && (coll44(placeholder[Int](115))._2 >= l40)\n )}\n )} else { placeholder[Boolean](116) }) && if (bool36 && bool42) { coll35.forall({(box43: Box) =>\n val coll45 = proveDlog(box43.R5[GroupElement].get).propBytes\n val coll46 = OUTPUTS.filter({(box46: Box) => box46.propositionBytes == coll45 })\n val l47 = coll35.fold(placeholder[Long](117), {(tuple47: (Long, Box)) =>\n val box49 = tuple47._2\n val l50 = tuple47._1\n if (proveDlog(box49.R5[GroupElement].get).propBytes == coll45) { l50 + box49.R6[Long].get } else { l50 }\n }) * l41 / coll35.fold(placeholder[Long](118), {(tuple47: (Long, Box)) => tuple47._1 + tuple47._2.R6[Long].get })\n if (bool17) { coll46.fold(placeholder[Long](119), {(tuple48: (Long, Box)) => tuple48._1 + tuple48._2.value }) >= l47 } else { coll46.fold(placeholder[Long](120), {(tuple48: (Long, Box)) =>\n val coll50 = tuple48._2.tokens.filter({(tuple50: (Coll[Byte], Long)) => tuple50._1 == coll16 })\n val l51 = tuple48._1\n if (coll50.size > placeholder[Int](121)) { l51 + coll50(placeholder[Int](122))._2 } else { l51 }\n }) >= l47 }\n }) } else { placeholder[Boolean](123) })\n )} else { sigmaProp(placeholder[Boolean](124)) } }\n}",
"address": "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",
"assets": [
{
"tokenId": "41cbb45f6a9f3718195c9ae6856ac1660e5f748491ecd9f2d110826797808cf8",
"index": 0,
"amount": 1,
"name": " ",
"decimals": 0,
"type": "EIP-004"
},
{
"tokenId": "a682e0218e179888589de611d3cc2d96be2e3d29200367979e4b9449abe1411d",
"index": 1,
"amount": 11,
"name": " ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
"R5": {
"serializedValue": "0e206a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66",
"sigmaType": "Coll[SByte]",
"renderedValue": "6a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66"
},
"R6": {
"serializedValue": "0e03455247",
"sigmaType": "Coll[SByte]",
"renderedValue": "455247"
},
"R8": {
"serializedValue": "1003000000",
"sigmaType": "Coll[SInt]",
"renderedValue": "[0,0,0]"
},
"R7": {
"serializedValue": "100686a0cc010a02140204",
"sigmaType": "Coll[SInt]",
"renderedValue": "[1673219,5,1,10,1,2]"
},
"R9": {
"serializedValue": "11028084af5f00",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000,0]"
},
"R4": {
"serializedValue": "05e09cd7900e",
"sigmaType": "SLong",
"renderedValue": "1896539952"
}
}
},
{
"boxId": "e8df4f6de2e67572ad88d276b12adaafc6175b2d7a1254f72a3b0e4a2bfdf0c5",
"value": 147099200,
"index": 1,
"spendingProof": "30113fcec97223eede5e3a21a396965183af9a9cb33a73a1232c80bfa697be5616b68842d53b380edf72255480dab2d40e1a5b1247b25d87",
"outputBlockId": "2b28ede0a559afe3d8535ed83f0879681b735f7834d9d37e32b14556a3eb2989",
"outputTransactionId": "ebb8309ffaea2ba43bfc7e68cdfbf55aafdc83dad00b6b49cbe457a23b1608a8",
"outputIndex": 3,
"outputGlobalIndex": 52113078,
"outputCreatedAt": 1673158,
"outputSettledAt": 1673159,
"ergoTree": "0008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(848b1c,dd161b,...)))}",
"address": "9hUBLNSpZWLngoKBCUMpR6cG28UEJ97ogcsw2AJDNF47BBdycTR",
"assets": [],
"additionalRegisters": {}
}
],
"dataInputs": [
{
"boxId": "bc87181f4592b3b243a8709285d0608c5ea9b13636f69f7ca16dc3d405455577",
"value": 10000000,
"index": 0,
"outputBlockId": "8172a671c9e427765f4bf380efa55e990731324fdb09b41049aec09b453c12b5",
"outputTransactionId": "01b5f8b1208a6ce02b3f375e734ddc649b4d01c9a69a4363306bb31a1af839d1",
"outputIndex": 0,
"ergoTree": "1004040204000e2019b7f2e2f11052c020800c8b620660f9f0b5fd5b3f2beacc8b44af960477a6940e2030e273698c85bbe66319904c499bfefbd76f51487688d674b20623715ff0741bd801d6018cb2db6308b2a473000073010001d1ec93720173029372017303",
"address": "PViBL5acX6Pm6nD3FJQ3fZXESZTq8imJ47LJLMWtrhqm2nP5cVwMfXoHoqhnfvxUUKenebtEbLwZFTWPFRXJNsqLYDNWMtYAbvmqWgxCCPeH1fECQYtdZksCMwJrcmpLtNgfeADVEnmcUCPeTee8",
"assets": [],
"additionalRegisters": {
"R4": {
"serializedValue": "05b486ed920e",
"sigmaType": "SLong",
"renderedValue": "1898815898"
},
"R5": {
"serializedValue": "04c867",
"sigmaType": "SInt",
"renderedValue": "6628"
}
}
}
],
"outputs": [
{
"boxId": "4c887de3dff95a49c705be36cf1b70677ee86a2424c5abc95648637d20650a50",
"transactionId": "49121ab5ff92ce7ea8d80792423669d7ea11bbd2f0e0255b17d1582945e24969",
"blockId": "2459bcec305b028c8326f434b0730e4ab415dcc3413f33dbebd64da59d6ad439",
"value": 10000000,
"index": 0,
"globalIndex": 52114997,
"creationHeight": 1673226,
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"ergoTreeConstants": "0: 1\n1: 0\n2: 1\n3: 1\n4: 0\n5: 1\n6: 3\n7: 0\n8: 69\n9: 82\n10: 71\n11: 1\n12: 2\n13: 5\n14: 0\n15: 0\n16: 1\n17: 1\n18: 1\n19: 0\n20: 0\n21: 2\n22: 2\n23: 1\n24: 1\n25: 1\n26: 1\n27: 3\n28: 2\n29: 3\n30: 0\n31: 1\n32: 2\n33: 10000000\n34: 10000000\n35: 10000000\n36: 1\n37: 2\n38: 3\n39: 2\n40: 3\n41: 2\n42: 0\n43: 2\n44: 10000000\n45: 10000000\n46: 10000000\n47: 1\n48: false\n49: 1\n50: 0\n51: 1\n52: 2\n53: 1\n54: 0\n55: 1\n56: 0\n57: 10000000\n58: 0\n59: 3\n60: 2\n61: 0\n62: 0\n63: 0\n64: 0\n65: 0\n66: 0\n67: 1\n68: 0\n69: 1\n70: 0\n71: 2\n72: 0\n73: 1\n74: 2\n75: 100\n76: 0\n77: 1\n78: 0\n79: 0\n80: 15\n81: 0\n82: 0\n83: 1\n84: true\n85: 2\n86: 1\n87: 1\n88: 0\n89: 0\n90: 0\n91: 5\n92: 1\n93: 2\n94: 3\n95: 4\n96: 4\n97: 5\n98: 10000000\n99: 2\n100: 10000000\n101: 2\n102: 10000000\n103: 2\n104: 10000000\n105: 3\n106: 2\n107: 0\n108: 0\n109: SigmaProp(ProveDlog(ECPoint(e45f52,5253a8,...)))\n110: 1\n111: 0\n112: 0\n113: 1\n114: 1\n115: 0\n116: true\n117: 0\n118: 0\n119: 0\n120: 0\n121: 0\n122: 0\n123: true\n124: 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 coll14 = SELF.R9[Coll[Long]].get\n val l15 = coll14(placeholder[Int](7))\n val coll16 = SELF.R6[Coll[Byte]].get\n val bool17 = coll16 == Coll[Byte](placeholder[Byte](8), placeholder[Byte](9), placeholder[Byte](10))\n val coll18 = SELF.R5[Coll[Byte]].get\n val l19 = coll14(placeholder[Int](11))\n val i20 = coll1(placeholder[Int](12))\n val i21 = coll1(placeholder[Int](13))\n if (HEIGHT < i3) {(\n val box22 = OUTPUTS(placeholder[Int](14))\n val coll23 = box22.tokens\n val i24 = coll23.size\n val tuple25 = coll23(placeholder[Int](15))\n val tuple26 = coll23(placeholder[Int](16))\n val l27 = tuple26._2\n val i28 = i12 + placeholder[Int](17) - l27.toInt\n val coll29 = box22.R8[Coll[Int]].get\n val box30 = OUTPUTS(placeholder[Int](18))\n val b31 = box30.R4[Byte].get\n val i32 = b31.toInt\n val tuple33 = box30.tokens(placeholder[Int](19))\n sigmaProp(\n (\n (\n (\n (\n (\n (\n (\n (\n (\n (\n ((((bool6 && bool5) && (l7 > placeholder[Long](20))) && (OUTPUTS.size >= placeholder[Int](21))) && (i24 >= placeholder[Int](22))) && (\n (tuple25._1 == coll9) && (tuple25._2 == placeholder[Long](23))\n )\n ) && ((tuple26._1 == coll11) && (l27 == tuple10._2 - placeholder[Long](24)))\n ) && (i28 <= i12)\n ) && (((coll29(i32) == coll13(i32) + placeholder[Int](25)) && \n val i34 = i32 + placeholder[Int](26) % placeholder[Int](27)\n coll29(i34) == coll13(i34)\n ) && \n val i34 = i32 + placeholder[Int](28) % placeholder[Int](29)\n coll29(i34) == coll13(i34)\n )\n ) && (coll29(placeholder[Int](30)) + coll29(placeholder[Int](31)) + coll29(placeholder[Int](32)) == i28)\n ) && if (bool17) {(\n val l34 = box22.value\n val l35 = SELF.value\n val l36 = l34 - placeholder[Long](33) - l35 - placeholder[Long](34)\n ((((l36 >= l15) && (l34 == l35 + l36)) && (box30.value == placeholder[Long](35))) && (box30.tokens.size == placeholder[Int](36))) && (\n box30.R6[Long].get == l36\n )\n )} else {(\n val i34 = coll8.size\n val bool35 = (i34 >= placeholder[Int](37)) && (i24 >= placeholder[Int](38))\n bool35 && if (bool35) {(\n val tuple36 = coll23(placeholder[Int](39))\n val l37 = tuple36._2\n val l38 = if (i34 >= placeholder[Int](40)) { coll8(placeholder[Int](41))._2 } else { placeholder[Long](42) }\n val l39 = l37 - l38\n (\n (\n (\n ((((coll8(placeholder[Int](43))._1 == coll16) && (tuple36._1 == coll16)) && (l39 >= l15)) && (l37 == l38 + l39)) && (\n (box22.value == placeholder[Long](44)) && (SELF.value == placeholder[Long](45))\n )\n ) && (box30.value == placeholder[Long](46))\n ) && (box30.tokens.size == placeholder[Int](47))\n ) && (box30.R6[Long].get == l39)\n )} else { placeholder[Boolean](48) }\n )}\n ) && (\n (\n (((box22.R4[Long].get == l7) && (box22.R5[Coll[Byte]].get == coll18)) && (box22.R6[Coll[Byte]].get == coll16)) && (\n box22.R7[Coll[Int]].get == coll1\n )\n ) && (box22.R9[Coll[Long]].get == coll14)\n )\n ) && (box22.propositionBytes == coll4)\n ) && ((tuple33._1 == coll11) && (tuple33._2 == placeholder[Long](49)))\n ) && (((b31 == placeholder[Byte](50)) || (b31 == placeholder[Byte](51))) || (b31 == placeholder[Byte](52)))\n ) && (proveDlog(box30.R5[GroupElement].get).propBytes == INPUTS(placeholder[Int](53)).propositionBytes)\n )\n )} else { if (HEIGHT >= i3 + i20) {(\n val box22 = CONTEXT.dataInputs(placeholder[Int](54))\n val coll23 = box22.tokens\n val l24 = box22.R4[Long].get\n val coll25 = INPUTS.filter({(box25: Box) =>\n val coll27 = box25.tokens\n (coll27.size >= placeholder[Int](55)) && (coll27(placeholder[Int](56))._1 == coll11)\n })\n val i26 = coll25.size\n val tuple27 = if (bool17) {(\n val l27 = SELF.value - placeholder[Long](57)\n (l27, l27 == coll25.fold(placeholder[Long](58), {(tuple28: (Long, Box)) => tuple28._1 + tuple28._2.R6[Long].get }) + l19)\n )} else { if (coll8.size >= placeholder[Int](59)) {(\n val l27 = coll8(placeholder[Int](60))._2\n (l27, l27 == coll25.fold(placeholder[Long](61), {(tuple28: (Long, Box)) => tuple28._1 + tuple28._2.R6[Long].get }) + l19)\n )} else { (placeholder[Long](62), (i26 == placeholder[Int](63)) && (l19 == placeholder[Long](64))) } }\n val box28 = OUTPUTS(placeholder[Int](65))\n val coll29 = box28.tokens\n val i30 = coll29.size\n val tuple31 = coll29(placeholder[Int](66))\n val tuple32 = coll29(placeholder[Int](67))\n val coll33 = box28.R7[Coll[Int]].get\n val i34 = coll33(placeholder[Int](68))\n val coll35 = coll25.filter({(box35: Box) => box35.R4[Byte].get == if (l24 > l7) { placeholder[Byte](69) } else { if (l24 < l7) { placeholder[Byte](70) } else { placeholder[Byte](71) } } })\n val bool36 = coll35.size > placeholder[Int](72)\n val coll37 = box28.R9[Coll[Long]].get\n val l38 = coll37(placeholder[Int](73))\n val l39 = tuple27._1\n val l40 = l39 * placeholder[Int](74).toLong / placeholder[Long](75)\n val l41 = l39 - l40\n val bool42 = l39 > placeholder[Long](76)\n sigmaProp((((((((((((((((((bool6 && bool5) && ((coll23.size >= placeholder[Int](77)) && (coll23(placeholder[Int](78))._1 == coll18))) && (l24 > placeholder[Long](79))) && (HEIGHT - box22.creationInfo._1 <= placeholder[Int](80))) && tuple27._2) && if (i26 > placeholder[Int](81)) { coll25.forall({(box43: Box) =>\n val tuple45 = box43.tokens(placeholder[Int](82))\n ((((tuple45._1 == coll11) && (tuple45._2 == placeholder[Long](83))) && box43.R4[Byte].isDefined) && box43.R5[GroupElement].isDefined) && box43.R6[Long].isDefined\n }) } else { placeholder[Boolean](84) }) && (i30 >= placeholder[Int](85))) && ((tuple31._1 == coll9) && (tuple31._2 == placeholder[Long](86)))) && ((tuple32._1 == coll11) && (tuple32._2 == i12 + placeholder[Int](87).toLong))) && (box28.R8[Coll[Int]].get == Coll[Int](placeholder[Int](88), placeholder[Int](89), placeholder[Int](90)))) && ((((((((box28.R4[Long].get == l24) && ((i34 >= HEIGHT) && (i34 <= HEIGHT + placeholder[Int](91)))) && (coll33(placeholder[Int](92)) == i2)) && (coll33(placeholder[Int](93)) == i20)) && (coll33(placeholder[Int](94)) == i12)) && (coll33(placeholder[Int](95)) == coll1(placeholder[Int](96)) + i21)) && (coll33(placeholder[Int](97)) == i21)) && (box28.R6[Coll[Byte]].get == coll16))) && (box28.R5[Coll[Byte]].get == coll18)) && (box28.propositionBytes == coll4)) && if (bool36) { if (bool17) { (box28.value == placeholder[Long](98)) && (i30 == placeholder[Int](99)) } else { (box28.value == placeholder[Long](100)) && (i30 == placeholder[Int](101)) } } else { if (bool17) { (box28.value == placeholder[Long](102) + l38) && (i30 == placeholder[Int](103)) } else { ((box28.value == placeholder[Long](104)) && (i30 == placeholder[Int](105))) && (coll29(placeholder[Int](106))._2 == l38) } }) && (coll37(placeholder[Int](107)) == l15)) && (l38 == if (bool36) { placeholder[Long](108) } else { l41 })) && if (bool42) {(\n val coll43 = OUTPUTS.filter({(box43: Box) => box43.propositionBytes == placeholder[SigmaProp](109).propBytes })\n if (bool17) { (coll43.size >= placeholder[Int](110)) && (coll43(placeholder[Int](111)).value >= l40) } else {(\n val coll44 = coll43(placeholder[Int](112)).tokens.filter({(tuple44: (Coll[Byte], Long)) => tuple44._1 == coll16 })\n ((coll43.size >= placeholder[Int](113)) && (coll44.size >= placeholder[Int](114))) && (coll44(placeholder[Int](115))._2 >= l40)\n )}\n )} else { placeholder[Boolean](116) }) && if (bool36 && bool42) { coll35.forall({(box43: Box) =>\n val coll45 = proveDlog(box43.R5[GroupElement].get).propBytes\n val coll46 = OUTPUTS.filter({(box46: Box) => box46.propositionBytes == coll45 })\n val l47 = coll35.fold(placeholder[Long](117), {(tuple47: (Long, Box)) =>\n val box49 = tuple47._2\n val l50 = tuple47._1\n if (proveDlog(box49.R5[GroupElement].get).propBytes == coll45) { l50 + box49.R6[Long].get } else { l50 }\n }) * l41 / coll35.fold(placeholder[Long](118), {(tuple47: (Long, Box)) => tuple47._1 + tuple47._2.R6[Long].get })\n if (bool17) { coll46.fold(placeholder[Long](119), {(tuple48: (Long, Box)) => tuple48._1 + tuple48._2.value }) >= l47 } else { coll46.fold(placeholder[Long](120), {(tuple48: (Long, Box)) =>\n val coll50 = tuple48._2.tokens.filter({(tuple50: (Coll[Byte], Long)) => tuple50._1 == coll16 })\n val l51 = tuple48._1\n if (coll50.size > placeholder[Int](121)) { l51 + coll50(placeholder[Int](122))._2 } else { l51 }\n }) >= l47 }\n }) } else { placeholder[Boolean](123) })\n )} else { sigmaProp(placeholder[Boolean](124)) } }\n}",
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{
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"index": 0,
"amount": 1,
"name": " ",
"decimals": 0,
"type": "EIP-004"
},
{
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"index": 1,
"amount": 11,
"name": " ",
"decimals": 0,
"type": "EIP-004"
}
],
"additionalRegisters": {
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"sigmaType": "Coll[SByte]",
"renderedValue": "6a2b821b5727e85beb5e78b4efb9f0250d59cd48481d2ded2c23e91ba1d07c66"
},
"R6": {
"serializedValue": "0e03455247",
"sigmaType": "Coll[SByte]",
"renderedValue": "455247"
},
"R8": {
"serializedValue": "1003000000",
"sigmaType": "Coll[SInt]",
"renderedValue": "[0,0,0]"
},
"R7": {
"serializedValue": "10069ca0cc010a02140604",
"sigmaType": "Coll[SInt]",
"renderedValue": "[1673230,5,1,10,3,2]"
},
"R9": {
"serializedValue": "11028084af5f00",
"sigmaType": "Coll[SLong]",
"renderedValue": "[100000000,0]"
},
"R4": {
"serializedValue": "05b486ed920e",
"sigmaType": "SLong",
"renderedValue": "1898815898"
}
},
"spentTransactionId": "57e4b18d17cf2365230d79a3e47e297135d4f7e230cbd33b17424ba6d95d37a2",
"mainChain": true
},
{
"boxId": "fb0175ce0dcab586a55fc69a3390fd279f4b3f1aadd2d1e7244152762c5a1ad1",
"transactionId": "49121ab5ff92ce7ea8d80792423669d7ea11bbd2f0e0255b17d1582945e24969",
"blockId": "2459bcec305b028c8326f434b0730e4ab415dcc3413f33dbebd64da59d6ad439",
"value": 4000000,
"index": 1,
"globalIndex": 52114998,
"creationHeight": 1673226,
"settlementHeight": 1673227,
"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)}",
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"mainChain": true
},
{
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"index": 2,
"globalIndex": 52114999,
"creationHeight": 1673226,
"settlementHeight": 1673227,
"ergoTree": "0008cd03848b1c77c1a24096d22ef8a8f78f4d97a5f411ff2d89138bc8bdca2cbac600b2",
"ergoTreeConstants": "",
"ergoTreeScript": "{SigmaProp(ProveDlog(ECPoint(848b1c,dd161b,...)))}",
"address": "9hUBLNSpZWLngoKBCUMpR6cG28UEJ97ogcsw2AJDNF47BBdycTR",
"assets": [],
"additionalRegisters": {},
"spentTransactionId": "57e4b18d17cf2365230d79a3e47e297135d4f7e230cbd33b17424ba6d95d37a2",
"mainChain": true
}
],
"size": 2556,
"isUnconfirmed": false
}