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Copy of a fortran array uses unnecessary transpose #1257

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EmilyBourne opened this issue Dec 14, 2022 · 3 comments · Fixed by #1256
Closed

Copy of a fortran array uses unnecessary transpose #1257

EmilyBourne opened this issue Dec 14, 2022 · 3 comments · Fixed by #1256
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blocked Cannot be solved/merged until something else is fixed bug Language:Fortran

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@EmilyBourne
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Describe the bug

A clear and concise description of what the bug is.

To Reproduce

Provide code to reproduce the behavior:

    a = np.array([[1,  2,  4,  8, 16],
             [1,  2,  4,  8, 16],
             [1,  2,  4,  8, 16],
             [1,  2,  4,  8, 16],
             [1,  2,  4,  8, 16]], order="F")
    b = np.array(a, order="F")

Error details

Provide the generated code, or the error message:

    allocate(a(0:4_i64, 0:4_i64))
    a = transpose(reshape([[1_i64, 2_i64, 4_i64, 8_i64, 16_i64], [1_i64, &
          2_i64, 4_i64, 8_i64, 16_i64], [1_i64, 2_i64, 4_i64, 8_i64, &
          16_i64], [1_i64, 2_i64, 4_i64, 8_i64, 16_i64], [1_i64, 2_i64, &
          4_i64, 8_i64, 16_i64]], [5_i64, 5_i64]))
    allocate(b(0:4_i64, 0:4_i64))
    b = transpose(a)

Expected behavior

a should not be transposed to create b

Language

Fortran

Additional context

Identified in PR #1256
@EmilyBourne EmilyBourne added bug Language:Fortran blocked Cannot be solved/merged until something else is fixed labels Dec 14, 2022
@EmilyBourne
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EmilyBourne commented Dec 14, 2022 •
edited

Blocked by #1128

@EmilyBourne EmilyBourne mentioned this issue Dec 14, 2022
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@EmilyBourne
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Blocked by #1258 as tests can't be added

@yguclu yguclu mentioned this issue Jul 28, 2023
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@EmilyBourne
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Duplicate of #1241

@EmilyBourne EmilyBourne marked this as a duplicate of #1241 Aug 15, 2023
@EmilyBourne EmilyBourne mentioned this issue Aug 15, 2023
Merged
@EmilyBourne EmilyBourne linked a pull request Aug 15, 2023 that will close this issue
Improve np.array implementation #1256
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yguclu added a commit that referenced this issue Aug 25, 2023
@jalalium @EmilyBourne @yguclu
Improve np.array implementation (#1256)
536be30 
- Ensure `np.array` can be called with one variable argument (previously
this caused an infinite loop over the elements of the array).
- Simplify `_print_NumpyArray` to reduce duplication and fix #1241 and
fix duplicate #1257.
- Improve `np.array` implementation to correct the default order and add
the `ndmin` parameter.
- Add tests for new code.
- Clean up `test_arrays.py` so failures reference the relevant issue,
tuples use `==` instead of `np.array_equal`, and a more comprehensive
check is carried out on returned arrays including checking the datatype
and ordering.

---------

Co-authored-by: EmilyBourne <louise.bourne@gmail.com>
Co-authored-by: Yaman Güçlü <yaman.guclu@gmail.com>
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Improve np.array implementation pyccel/pyccel
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