Add equalent np.convolve (just full mode)#7
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Oceania2018 merged 1 commit intoSciSharp:masterfrom Oct 17, 2018
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dotChris90
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Oct 17, 2018
dotChris90
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- according to issue implement numpy.convolve #6
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Hi @dotChris90 , the np.convolve looks great, could you please add the convolve to the Implemented APIs list in the README? |
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Keep this open due to same and valid mode is not finished yet. |
Nucs
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Implements fixes detailed in docs/NPYITER_FIXES_REQUIRED.md to improve NumPy compatibility of the NpyIter implementation. Fix #1: Coalescing Always Runs - Changed NpyIterRef.Initialize() to always coalesce axes after construction unless MULTI_INDEX flag is set - Matches NumPy's nditer_constr.c line 395-396 behavior Fix #2: Inner Stride Cache - Added InnerStrides[MaxOperands] array to NpyIterState - Added UpdateInnerStrides() method to gather inner strides - GetInnerStrideArray() now returns contiguous array matching NumPy's NpyIter_GetInnerStrideArray() format Fix #3: op_axes Parameter Implementation - Added ApplyOpAxes() method to support axis remapping - Supports -1 entries for broadcast/reduction axes - Enables reduction operations via custom axis mapping Fix #4: Multi-Index Support - Added GetMultiIndex(Span<long>) for coordinate retrieval - Added GotoMultiIndex(ReadOnlySpan<long>) for coordinate jumping - Added HasMultiIndex property - HASMULTIINDEX flag tracked during construction Fix #5: Ranged Iteration - Added ResetToIterIndexRange(start, end) for parallel chunking - Added IterStart, IterEnd, and IsRanged properties - RANGE flag tracks ranged iteration mode Fix #6: Buffer Copy Type Dispatch - Added non-generic CopyToBuffer/CopyFromBuffer overloads - Runtime dtype dispatch for all 12 NumSharp types - Enables dtype-agnostic iteration code Fix #7: Flag Bit Positions Documented - Added documentation explaining NumSharp's flag bit layout - Legacy compatibility flags use bits 0-7 - NumPy-equivalent flags use bits 8-15 - Semantic meaning matches NumPy, positions differ Fix #8: MaxDims Increased to 64 - Changed MaxDims from 32 to 64 to match NPY_MAXDIMS - Supports high-dimensional array iteration Test coverage: - 13 new tests for coalescing, multi-index, ranged iteration, inner strides, and MaxDims validation - All 5666 non-OpenBugs tests pass Note: Full axis reordering before coalescing (for complete 1D coalescing of contiguous arrays) not yet implemented. Current implementation coalesces adjacent compatible axes only.
Nucs
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Apr 23, 2026
Explicit the hierarchy — Tier A/B/C were always sub-tiers of Layer 3
(the baked-ufunc layer). Numbering them `3A/3B/3C` makes the
relationship visible at a glance:
Layer 1 — ForEach (delegate)
Layer 2 — ExecuteGeneric (struct-generic)
Layer 3 — ExecuteBinary / Unary / ... (baked)
Tier 3A — ExecuteRawIL (sub-tier: custom IL)
Tier 3B — ExecuteElementWise (sub-tier: templated)
Tier 3C — ExecuteExpression / Call (sub-tier: DSL)
100 references touched across 6 files:
docs/website-src/docs/NDIter.md — prose, TOC, anchor links, worked-
example heading anchors (#6, #7, #8)
src/NumSharp.Core/Backends/Iterators/NpyExpr.cs — header comment
src/NumSharp.Core/Backends/Iterators/NpyIter.Execution.Custom.cs
— file header, region comments for each tier entry point
src/NumSharp.Core/Backends/Kernels/ILKernelGenerator.InnerLoop.cs
— factory method docstrings
test/NumSharp.UnitTest/Backends/Iterators/NpyIterCustomOpTests.cs
— class docstring, region comments, 10 test method names
(TierA_* → Tier3A_*, TierB_* → Tier3B_*, TierC_* → Tier3C_*)
test/NumSharp.UnitTest/Backends/Iterators/NpyIterCustomOpEdgeCaseTests.cs
— region comments, 2 test method names (Validate_TierA_* →
Validate_Tier3A_*)
No behavior changes. 264/264 NpyExpr + custom-op tests pass on net8 +
net10. Full suite still green (0 regressions).
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