Migrating to NumPy v2.5.0rc1

Breaking Changes

Migration Steps

1. 1
   If you were using `numpy.distutils`, migrate your build system away from it.
2. 2
   Replace usage of `numpy.char.chararray` with an `ndarray` having a string or bytes dtype.
3. 3
   Replace usage of `numpy.char.[as]array` functions with `numpy.[as]array` specifying a string or bytes dtype.
4. 4
   Instead of setting `arr.dtype = new_dtype`, use `arr.view(dtype=new_dtype)` to create a view with a new dtype.
5. 5
   Instead of setting `arr.shape = new_shape`, use `np.reshape(arr, new_shape)` or `arr.reshape(new_shape)`.
6. 6
   When constructing `numpy.timedelta64`, specify an explicit unit like `'s'` or `'D'` instead of using the generic unit.
7. 7
   Replace in-place resizing of arrays with `np.resize(arr, new_shape)`.
8. 8
   Replace calls to `numpy.fix` with `numpy.trunc`.
9. 9
   Replace calls to `numpy.ma.round_` with `numpy.ma.round`.
10. 10
    Replace calls to `numpy.typename` with `numpy.dtype.name`.
11. 11
    Ensure that inputs to `numpy.triu_indices` and `numpy.tril_indices` are integers. Ensure `M`, `k`, and `N` parameters for `numpy.tri` are integers, and `k` for `numpy.tril_indices_from` and `numpy.triu_indices_from` are integers.
12. 12
    If you have custom dtypes or logic in `__array_finalize__` affected by dtype setting changes, review the deprecation note regarding setting `_set_dtype = None` or defining `_set_dtype`.
13. 13
    If you relied on `linalg.eig` or `linalg.eigvals` returning real arrays when eigenvalues were real, you must now explicitly check if the imaginary part is zero and handle the result accordingly.

Release Summary