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Fix sqrt!/sin!/cos! mutating elements outside matrix view - #123

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Quafadas merged 2 commits into
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copilot/fix-matrix-view-operations
Aug 4, 2026
Merged

Fix sqrt!/sin!/cos! mutating elements outside matrix view#123
Quafadas merged 2 commits into
mainfrom
copilot/fix-matrix-view-operations

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Copilot AI commented Aug 4, 2026 •
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In-place sqrt!, sin!, and cos! on non-contiguous matrix views (e.g. column-selected submatrices) corrupted data outside the view. sqrt! and sin! had if blocks with no else, so the fast-path SIMD call on the full raw array ran and the scalar view-aware loop ran afterward. cos! had no view-aware fallback at all — it only ever called the raw-array SIMD path, silently mutating data beyond the view's bounds on non-contiguous layouts.

Changes

  • sqrt!: wrap the scalar per-element loop in the missing else branch so it only runs on non-contiguous layouts.
  • sin!: same fix — added missing else.
  • cos!: added the missing non-contiguous fallback branch (mirroring sqrt!/sin!/log!), so it now correctly falls back to layout.linearIndex-based iteration instead of unconditionally hitting the raw array.
// before
def `sqrt!`: Unit =
  if m.hasSimpleContiguousMemoryLayout then vecxt.doublearrays.`sqrt!`(m.raw)
  end if
  // scalar loop always runs too, using linearIndex — corrupts data on views
  ...

// after
def `sqrt!`: Unit =
  if m.hasSimpleContiguousMemoryLayout then vecxt.doublearrays.`sqrt!`(m.raw)
  else
    // scalar loop only runs for non-contiguous layouts
    ...

Tests

  • Added regression tests asserting that sqrt!, sin!, and cos! on a column-sliced submatrix leave untouched columns of the backing array unmodified.

Copilot AI linked an issue Aug 4, 2026 that may be closed by this pull request
Matrixc View operations mutates elements outside it #122
Closed
@Quafadas
Fix missing else clauses in sqrt!/sin!/cos! for non-contiguous matrix…
b6f6e20 
… views

Co-authored-by: Quafadas <24899792+Quafadas@users.noreply.github.com>
Copilot AI changed the title [WIP] Fix matrix view operations to include else clause Fix sqrt!/sin!/cos! mutating elements outside matrix view Aug 4, 2026
Copilot AI requested a review from Quafadas August 4, 2026 14:18
@Quafadas
Quafadas marked this pull request as ready for review August 4, 2026 14:27
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Bytecode audit (Tier 1) — ⚠️ no failures, 1 WARN

JDK 25.0.1 (major 25), OpenJDK 64-Bit Server VM

Vector lanes (DoubleVector.SPECIES_PREFERRED.length()): 4

threshold value provenance
MaxTrivialSize 6 discovered
MaxInlineSize 35 discovered
FreqInlineSize 325 discovered
MaxInlineLevel 15 discovered
InlineSmallCode 2500 discovered
NodeCountInliningCutoff 18000 assumed
HugeMethodLimit 8000 assumed

-XX:HugeMethodLimit= was rejected on the command line: a develop flag compiled out of this product build, so 8000 is taken from the HotSpot source and cannot be confirmed against the running JVM.

metric now baseline delta
cheatsheet methods 97 — —
total bytes 42067 51103 -17.7%
distinct library ops 198 178 +11.2%
bytes per op 212.5 287.1 -26.0%
severity check at method detail
WARN C1 cheatsheet.scala:118 CheatsheetTest$.matrixRangeSlicing 5643 bytes, past 68% of HugeMethodLimit=8000 (assumed)
Annotated methods (164)
method annotations bytes budget used loop at
vecxt.intarrays$.$plus @Thin 24 69% of 35 no intarrays.scala:546
vecxt.intarrays$.$minus @Thin 24 69% of 35 no intarrays.scala:399
vecxt.NDArrayFloatOps$.compareGeneral @HotPath 195 60% of 325 yes ndarrayFloatOps.scala:67
vecxt.NDArrayFloatOps$.binaryOpGeneral @HotPath 195 60% of 325 yes ndarrayFloatOps.scala:20
vecxt.NDArrayIntOps$.compareGeneral @HotPath 186 57% of 325 yes ndarrayIntOps.scala:67
vecxt.NDArrayIntOps$.binaryOpGeneral @HotPath 186 57% of 325 yes ndarrayIntOps.scala:19
vecxt.NDArrayDoubleOps$.compareGeneral @HotPath 186 57% of 325 yes ndarrayDoubleOps.scala:74
vecxt.NDArrayDoubleOps$.binaryOpGeneral @HotPath 186 57% of 325 yes ndarrayDoubleOps.scala:24
vecxt.doublearrays$.clamp$bang @AllocFree @HotPath 180 55% of 325 yes doublearrays.scala:872
vecxt.matrix$Layout.linearIndex @Thin 19 54% of 35 no matrix.scala:48
vecxt.floatarrays$.clamp$bang @AllocFree @HotPath 172 53% of 325 yes floatarrays.scala:417
vecxt.NDArrayFloatOps$.compareScalarGeneral @HotPath 165 51% of 325 yes ndarrayFloatOps.scala:94
vecxt.NDArrayFloatOps$.binaryOpInPlaceGeneral @HotPath 162 50% of 325 yes ndarrayFloatOps.scala:119
vecxt.NDArrayDoubleOps$.compareScalarGeneral @HotPath 157 48% of 325 yes ndarrayDoubleOps.scala:102
vecxt.NDArrayIntOps$.compareScalarGeneral @HotPath 156 48% of 325 yes ndarrayIntOps.scala:94
vecxt.NDArrayIntOps$.binaryOpInPlaceGeneral @HotPath 153 47% of 325 yes ndarrayIntOps.scala:119
vecxt.NDArrayDoubleOps$.binaryOpInPlaceGeneral @HotPath 153 47% of 325 yes ndarrayDoubleOps.scala:131
vecxt.NDArrayIntOps$.unaryOpGeneral @HotPath 152 47% of 325 yes ndarrayIntOps.scala:42
vecxt.NDArrayDoubleOps$.unaryOpGeneral @HotPath 152 47% of 325 yes ndarrayDoubleOps.scala:48
vecxt.intarrays$.$minus @Thin 16 46% of 35 no intarrays.scala:519
vecxt.doublearrays$.fillLinspace @AllocFree @HotPath 133 41% of 325 yes doublearrays.scala:34
vecxt.intarrays$.increments @HotPath 121 37% of 325 yes intarrays.scala:219
vecxt.ndarray$.mkNDArray @Thin 13 37% of 35 no ndarray.scala:188
vecxt.doublearrays$.increments @HotPath 110 34% of 325 yes doublearrays.scala:397
vecxt.intarrays$.dot @AllocFree @HotPath 108 33% of 325 yes intarrays.scala:372
vecxt.doublearrays$.unary_$minus @HotPath 108 33% of 325 yes doublearrays.scala:172
vecxt.doublearrays$.tanh @HotPath 108 33% of 325 yes doublearrays.scala:365
vecxt.doublearrays$.tan @HotPath 108 33% of 325 yes doublearrays.scala:354
vecxt.doublearrays$.sqrt @HotPath 108 33% of 325 yes doublearrays.scala:317
vecxt.doublearrays$.sinh @HotPath 108 33% of 325 yes doublearrays.scala:339
vecxt.doublearrays$.sin @HotPath 108 33% of 325 yes doublearrays.scala:328
vecxt.doublearrays$.log1p @HotPath 108 33% of 325 yes doublearrays.scala:306
vecxt.doublearrays$.log10 @HotPath 108 33% of 325 yes doublearrays.scala:295
vecxt.doublearrays$.log @HotPath 108 33% of 325 yes doublearrays.scala:284
vecxt.doublearrays$.expm1 @HotPath 108 33% of 325 yes doublearrays.scala:273
vecxt.doublearrays$.exp @HotPath 108 33% of 325 yes doublearrays.scala:262
vecxt.doublearrays$.cosh @HotPath 108 33% of 325 yes doublearrays.scala:251
vecxt.doublearrays$.cos @HotPath 108 33% of 325 yes doublearrays.scala:240
vecxt.doublearrays$.cbrt @HotPath 108 33% of 325 yes doublearrays.scala:229
vecxt.doublearrays$.atan @HotPath 108 33% of 325 yes doublearrays.scala:218
vecxt.doublearrays$.asin @HotPath 108 33% of 325 yes doublearrays.scala:207
vecxt.doublearrays$.acos @HotPath 108 33% of 325 yes doublearrays.scala:196
vecxt.doublearrays$.abs @HotPath 108 33% of 325 yes doublearrays.scala:184
vecxt.intarrays$.$less @HotPath 106 33% of 325 yes intarrays.scala:48
vecxt.intarrays$.$less$eq @HotPath 106 33% of 325 yes intarrays.scala:52
vecxt.intarrays$.$greater @HotPath 106 33% of 325 yes intarrays.scala:56
vecxt.intarrays$.$greater$eq @HotPath 106 33% of 325 yes intarrays.scala:60
vecxt.intarrays$.$eq$colon$eq @HotPath 106 33% of 325 yes intarrays.scala:40
vecxt.intarrays$.$bang$colon$eq @HotPath 106 33% of 325 yes intarrays.scala:44
vecxt.floatarrays$.unary_$minus @HotPath 104 32% of 325 yes floatarrays.scala:114
vecxt.floatarrays$.tanh @HotPath 104 32% of 325 yes floatarrays.scala:303
vecxt.floatarrays$.tan @HotPath 104 32% of 325 yes floatarrays.scala:292
vecxt.floatarrays$.sqrt @HotPath 104 32% of 325 yes floatarrays.scala:259
vecxt.floatarrays$.sinh @HotPath 104 32% of 325 yes floatarrays.scala:281
vecxt.floatarrays$.sin @HotPath 104 32% of 325 yes floatarrays.scala:270
vecxt.floatarrays$.log1p @HotPath 104 32% of 325 yes floatarrays.scala:248
vecxt.floatarrays$.log10 @HotPath 104 32% of 325 yes floatarrays.scala:237
vecxt.floatarrays$.log @HotPath 104 32% of 325 yes floatarrays.scala:226
vecxt.floatarrays$.expm1 @HotPath 104 32% of 325 yes floatarrays.scala:215
vecxt.floatarrays$.exp @HotPath 104 32% of 325 yes floatarrays.scala:204
vecxt.floatarrays$.cosh @HotPath 104 32% of 325 yes floatarrays.scala:193
vecxt.floatarrays$.cos @HotPath 104 32% of 325 yes floatarrays.scala:182
vecxt.floatarrays$.cbrt @HotPath 104 32% of 325 yes floatarrays.scala:171
vecxt.floatarrays$.atan @HotPath 104 32% of 325 yes floatarrays.scala:160
vecxt.floatarrays$.asin @HotPath 104 32% of 325 yes floatarrays.scala:149
vecxt.floatarrays$.acos @HotPath 104 32% of 325 yes floatarrays.scala:138
vecxt.floatarrays$.abs @HotPath 104 32% of 325 yes floatarrays.scala:126
vecxt.intarrays$.mean @Thin 11 31% of 35 no intarrays.scala:287
vecxt.doublearrays$.tanh$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.tan$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.sqrt$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.sinh$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.sin$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.log1p$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.log10$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.log$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.expm1$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.exp$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.cosh$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.cos$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.cbrt$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.atan$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.asin$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.acos$bang @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.abs$bang @AllocFree @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.doublearrays$.$minus$bang @AllocFree @HotPath 98 30% of 325 yes doublearrays.scala:151
vecxt.floatarrays$.increments @HotPath 97 30% of 325 yes floatarrays.scala:652
vecxt.doublearrays$.$times$times$bang @HotPath 95 29% of 325 yes doublearrays.scala:372
vecxt.intarrays$.$less @HotPath 94 29% of 325 yes intarrays.scala:139
vecxt.intarrays$.$less$eq @HotPath 94 29% of 325 yes intarrays.scala:143
vecxt.intarrays$.$greater @HotPath 94 29% of 325 yes intarrays.scala:147
vecxt.intarrays$.$greater$eq @HotPath 94 29% of 325 yes intarrays.scala:151
vecxt.intarrays$.$eq$colon$eq @HotPath 94 29% of 325 yes intarrays.scala:131
vecxt.intarrays$.$bang$colon$eq @HotPath 94 29% of 325 yes intarrays.scala:135
vecxt.floatarrays$.tanh$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.tan$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.sqrt$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.sinh$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.sin$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.log1p$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.log10$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.log$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.expm1$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.exp$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.cosh$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.cos$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.cbrt$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.atan$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.asin$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.acos$bang @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.abs$bang @AllocFree @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.floatarrays$.$minus$bang @AllocFree @HotPath 93 29% of 325 yes floatarrays.scala:94
vecxt.intarrays$.variance @Thin 10 29% of 35 no intarrays.scala:304
vecxt.intarrays$.std @Thin 10 29% of 35 no intarrays.scala:361
vecxt.doublearrays$.variance @AllocFree @Thin 10 29% of 35 no doublearrays.scala:541
vecxt.doublearrays$.$minus$eq @AllocFree @HotPath 92 28% of 325 yes doublearrays.scala:1063
vecxt.doublearrays$.$plus$eq @AllocFree @HotPath 90 28% of 325 yes doublearrays.scala:998
vecxt.doublearrays$.$times$eq @AllocFree @HotPath 88 27% of 325 yes doublearrays.scala:1135
vecxt.doublearrays$.productSIMD @AllocFree @HotPath 86 26% of 325 yes doublearrays.scala:700
vecxt.floatarrays$.$times$times$bang @HotPath 85 26% of 325 yes floatarrays.scala:314
vecxt.doublearrays$.sumSIMD @AllocFree @HotPath 85 26% of 325 yes doublearrays.scala:677
vecxt.doublearrays$.fma$bang @AllocFree @HotPath 85 26% of 325 yes doublearrays.scala:1038
vecxt.intarrays$.$plus$eq @AllocFree @HotPath 84 26% of 325 yes intarrays.scala:555
vecxt.intarrays$.$minus$eq @AllocFree @HotPath 84 26% of 325 yes intarrays.scala:527
vecxt.floatarrays$.$times$eq @AllocFree @HotPath 84 26% of 325 yes floatarrays.scala:874
vecxt.floatarrays$.$plus$eq @AllocFree @HotPath 84 26% of 325 yes floatarrays.scala:772
vecxt.floatarrays$.$minus$eq @AllocFree @HotPath 84 26% of 325 yes floatarrays.scala:812
vecxt.ndarrayOps.expandDims @Thin 9 26% of 35 no ndarrayOps.scala
vecxt.intarrays.stdDev @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.meanAndVariance @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.lte @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.lte @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.lt @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.lt @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.gte @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.gte @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.gt @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays.gt @Thin 9 26% of 35 no intarrays.scala
vecxt.intarrays$.variance @Thin 9 26% of 35 no intarrays.scala:291
vecxt.intarrays$.stdDev @Thin 9 26% of 35 no intarrays.scala:364
vecxt.intarrays$.std @Thin 9 26% of 35 no intarrays.scala:357
vecxt.intarrays$.meanAndVariance @Thin 9 26% of 35 no intarrays.scala:308
vecxt.doublearrays.meanAndVariance @Thin 9 26% of 35 no doublearrays.scala
vecxt.doublearrays$.meanAndVariance @Thin 9 26% of 35 no doublearrays.scala:555
vecxt.intarrays$.minSIMD @AllocFree @HotPath 82 25% of 325 yes intarrays.scala:575
vecxt.intarrays$.maxSIMD @AllocFree @HotPath 82 25% of 325 yes intarrays.scala:595
vecxt.floatarrays$.productSIMD @AllocFree @HotPath 82 25% of 325 yes floatarrays.scala:537
vecxt.intarrays$.sumSIMD @AllocFree @HotPath 81 25% of 325 yes intarrays.scala:265
vecxt.floatarrays$.sumSIMD @AllocFree @HotPath 81 25% of 325 yes floatarrays.scala:516
vecxt.floatarrays$.fma$bang @AllocFree @HotPath 80 25% of 325 yes floatarrays.scala:340
vecxt.floatarrays$.$times$eq @AllocFree @HotPath 78 24% of 325 yes floatarrays.scala:926
vecxt.ndarray.shapeArray @Thin 8 23% of 35 no ndarray.scala
vecxt.matrix$Matrix.rows @Thin 8 23% of 35 no matrix.scala:129
vecxt.matrix$Matrix.rowStride @Thin 8 23% of 35 no matrix.scala:135
vecxt.matrix$Matrix.offset @Thin 8 23% of 35 no matrix.scala:141
vecxt.matrix$Matrix.numel @Thin 8 23% of 35 no matrix.scala:144
vecxt.matrix$Matrix.isDenseRowMajor @Thin 8 23% of 35 no matrix.scala:150
vecxt.matrix$Matrix.isDenseColMajor @Thin 8 23% of 35 no matrix.scala:147
vecxt.matrix$Matrix.hasSimpleContiguousMemoryLayout @Thin 8 23% of 35 no matrix.scala:162
vecxt.matrix$Matrix.cols @Thin 8 23% of 35 no matrix.scala:132
vecxt.matrix$Matrix.colStride @Thin 8 23% of 35 no matrix.scala:138
vecxt.intarrays$.countsToIdx @HotPath 70 22% of 325 yes intarrays.scala:244
vecxt.intarrays$.$minus$eq @AllocFree @HotPath 67 21% of 325 yes intarrays.scala:408
vecxt.floatarrays$.$plus$eq @AllocFree @HotPath 24 7% of 325 no floatarrays.scala:731
Method sizes
band methods
<= 6 (trivial, always inlined) 1411
7-35 (inlinable cold) 3568
36-325 (inlinable when hot) 703
326-8000 (not inlined) 90
> 8000 (NEVER JIT COMPILED) 0
bytes method module at
5643 CheatsheetTest$.matrixRangeSlicing experiments cheatsheet.scala:118
3815 CheatsheetTest$.matrixReverseSlicing experiments cheatsheet.scala:125
3801 CheatsheetTest$.ndArrayInt experiments cheatsheet.scala:416
3779 CheatsheetTest$.ndArrayBoolean experiments cheatsheet.scala:430
3061 CheatsheetTest$.ndArrayFloat experiments cheatsheet.scala:395
3015 CheatsheetTest$.ndArrayFloatReductions experiments cheatsheet.scala:405
2811 CheatsheetTest$.matrixCreation experiments cheatsheet.scala:72
2597 CheatsheetTest$.matrixOps experiments cheatsheet.scala:167
2500 vecxt_re.Tower.show vecxt_re Tower.scala:63
1594 vecxt.ndarrayOps$.apply vecxt ndarrayOps.scala:452
1460 CheatsheetTest$.indexingAndSlicing experiments cheatsheet.scala:98
1435 vecxt.JvmDoubleMatrix$.$plus$eq vecxt doublematrix.scala:315
1420 vecxt.JvmFloatMatrix$.floatmatrixAddScalarInPlace vecxt floatmatrix.scala:442
1420 vecxt.JvmFloatMatrix$.floatmatrixSubScalarInPlace vecxt floatmatrix.scala:514
1308 CheatsheetTest$.arrayManipulation experiments cheatsheet.scala:305
1122 vecxt.Svd$.pinv vecxt svd.scala:42
1040 vecxt.JvmFloatMatrix$.floatmatrixSubVector vecxt floatmatrix.scala:336
1028 CheatsheetTest$.matrixFloat experiments cheatsheet.scala:445
984 vecxt.JvmDoubleMatrix$.$plus$eq vecxt doublematrix.scala:227
969 vecxt_re.Scenarr$.combine vecxt_re scenarr.scala:160
960 vecxt.JvmFloatMatrix$.floatmatrixAddVectorInPlace vecxt floatmatrix.scala:248
960 vecxt.JvmFloatMatrix$.floatmatrixSubVectorInPlace vecxt floatmatrix.scala:360
923 CheatsheetTest$.matrixInt experiments cheatsheet.scala:461
908 vecxt.Svd$.svd vecxt svd.scala:135
896 vecxt_re.NegativeBinomial$.volweightedMle vecxt_re NegativeBinomial.scala:281
Proposed baseline 
{
  "jdkMajor": 25,
  "c9": { "totalBytes": 42067, "distinctOps": 198 },
  "annotated": {
    "vecxt.NDArrayDoubleOps$.binaryOpGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayDoubleOps$.binaryOpInPlaceGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)V": 153,
    "vecxt.NDArrayDoubleOps$.compareGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayDoubleOps$.compareScalarGeneral(Lvecxt/ndarray$NDArray;DLscala/Function2;)Lvecxt/ndarray$NDArray;": 157,
    "vecxt.NDArrayDoubleOps$.unaryOpGeneral(Lvecxt/ndarray$NDArray;Lscala/Function1;)Lvecxt/ndarray$NDArray;": 152,
    "vecxt.NDArrayFloatOps$.binaryOpGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 195,
    "vecxt.NDArrayFloatOps$.binaryOpInPlaceGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)V": 162,
    "vecxt.NDArrayFloatOps$.compareGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 195,
    "vecxt.NDArrayFloatOps$.compareScalarGeneral(Lvecxt/ndarray$NDArray;FLscala/Function2;)Lvecxt/ndarray$NDArray;": 165,
    "vecxt.NDArrayIntOps$.binaryOpGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayIntOps$.binaryOpInPlaceGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)V": 153,
    "vecxt.NDArrayIntOps$.compareGeneral(Lvecxt/ndarray$NDArray;Lvecxt/ndarray$NDArray;Lscala/Function2;)Lvecxt/ndarray$NDArray;": 186,
    "vecxt.NDArrayIntOps$.compareScalarGeneral(Lvecxt/ndarray$NDArray;ILscala/Function2;)Lvecxt/ndarray$NDArray;": 156,
    "vecxt.NDArrayIntOps$.unaryOpGeneral(Lvecxt/ndarray$NDArray;Lscala/Function1;)Lvecxt/ndarray$NDArray;": 152,
    "vecxt.doublearrays$.$minus$bang([D)V": 98,
    "vecxt.doublearrays$.$minus$eq([DD)V": 92,
    "vecxt.doublearrays$.$plus$eq([DD)V": 90,
    "vecxt.doublearrays$.$times$eq([D[D)V": 88,
    "vecxt.doublearrays$.$times$times$bang([DD)V": 95,
    "vecxt.doublearrays$.abs$bang([D)V": 98,
    "vecxt.doublearrays$.abs([D)[D": 108,
    "vecxt.doublearrays$.acos$bang([D)V": 98,
    "vecxt.doublearrays$.acos([D)[D": 108,
    "vecxt.doublearrays$.asin$bang([D)V": 98,
    "vecxt.doublearrays$.asin([D)[D": 108,
    "vecxt.doublearrays$.atan$bang([D)V": 98,
    "vecxt.doublearrays$.atan([D)[D": 108,
    "vecxt.doublearrays$.cbrt$bang([D)V": 98,
    "vecxt.doublearrays$.cbrt([D)[D": 108,
    "vecxt.doublearrays$.clamp$bang([DDD)V": 180,
    "vecxt.doublearrays$.cos$bang([D)V": 98,
    "vecxt.doublearrays$.cos([D)[D": 108,
    "vecxt.doublearrays$.cosh$bang([D)V": 98,
    "vecxt.doublearrays$.cosh([D)[D": 108,
    "vecxt.doublearrays$.exp$bang([D)V": 98,
    "vecxt.doublearrays$.exp([D)[D": 108,
    "vecxt.doublearrays$.expm1$bang([D)V": 98,
    "vecxt.doublearrays$.expm1([D)[D": 108,
    "vecxt.doublearrays$.fillLinspace([DDD)V": 133,
    "vecxt.doublearrays$.fma$bang([DDD)V": 85,
    "vecxt.doublearrays$.increments([D)[D": 110,
    "vecxt.doublearrays$.log$bang([D)V": 98,
    "vecxt.doublearrays$.log([D)[D": 108,
    "vecxt.doublearrays$.log10$bang([D)V": 98,
    "vecxt.doublearrays$.log10([D)[D": 108,
    "vecxt.doublearrays$.log1p$bang([D)V": 98,
    "vecxt.doublearrays$.log1p([D)[D": 108,
    "vecxt.doublearrays$.meanAndVariance([D)Lvecxt/MeanAndVariance;": 9,
    "vecxt.doublearrays$.productSIMD([D)D": 86,
    "vecxt.doublearrays$.sin$bang([D)V": 98,
    "vecxt.doublearrays$.sin([D)[D": 108,
    "vecxt.doublearrays$.sinh$bang([D)V": 98,
    "vecxt.doublearrays$.sinh([D)[D": 108,
    "vecxt.doublearrays$.sqrt$bang([D)V": 98,
    "vecxt.doublearrays$.sqrt([D)[D": 108,
    "vecxt.doublearrays$.sumSIMD([D)D": 85,
    "vecxt.doublearrays$.tan$bang([D)V": 98,
    "vecxt.doublearrays$.tan([D)[D": 108,
    "vecxt.doublearrays$.tanh$bang([D)V": 98,
    "vecxt.doublearrays$.tanh([D)[D": 108,
    "vecxt.doublearrays$.unary_$minus([D)[D": 108,
    "vecxt.doublearrays$.variance([DLvecxt/VarianceMode;)D": 10,
    "vecxt.doublearrays.meanAndVariance([DLvecxt/VarianceMode;)Lvecxt/MeanAndVariance;": 9,
    "vecxt.floatarrays$.$minus$bang([F)V": 93,
    "vecxt.floatarrays$.$minus$eq([FF)V": 84,
    "vecxt.floatarrays$.$plus$eq([FF)V": 84,
    "vecxt.floatarrays$.$plus$eq([F[F)V": 24,
    "vecxt.floatarrays$.$times$eq([FF)V": 78,
    "vecxt.floatarrays$.$times$eq([F[F)V": 84,
    "vecxt.floatarrays$.$times$times$bang([FF)V": 85,
    "vecxt.floatarrays$.abs$bang([F)V": 93,
    "vecxt.floatarrays$.abs([F)[F": 104,
    "vecxt.floatarrays$.acos$bang([F)V": 93,
    "vecxt.floatarrays$.acos([F)[F": 104,
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    "vecxt.floatarrays$.asin([F)[F": 104,
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    "vecxt.ndarray$.mkNDArray(Ljava/lang/Object;[I[II)Lvecxt/ndarray$NDArray;": 13,
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  }
}

@Quafadas
Quafadas merged commit 69fa174 into main Aug 4, 2026
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Copilot AI mentioned this pull request Aug 4, 2026
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Matrixc View operations mutates elements outside it

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