Fix numpy.ma.fix_invalid issue in NumPy 2.1.0 by replacing with numpy.ma.masked_invalid

[kounelisagis]

For an unknown reason, numpy.ma.fix_invalid behaves differently between NumPy 2.1.0 and NumPy 2.0.0. Specifically, when passing a pandas Series containing a numpy.nan value, numpy.ma.fix_invalid now makes changes in-place, even if the copy argument is set to its default value of True. This issue occurs only with pandas Series, not with NumPy arrays, for example.

Nevertheless, we don't actually need the numpy.ma.fix_invalid function since we handle NaNs later using numpy.nan_to_num. It would be wiser (and likely more performant) to use numpy.ma.masked_invalid, which simply creates a MaskedArray instance and allows us to obtain the mask from there.

cc: @jdblischak
Closes #2040

---

>>> import pandas as pd, numpy as np
>>> pd.__version__; np.__version__
'2.2.2'
'2.1.0'
>>> my_series = pd.Series([1.0, 2.0, np.nan, 0.0, 1.0])
>>> my_series
0    1.0
1    2.0
2    NaN
3    0.0
4    1.0
dtype: float64
>>> np.ma.fix_invalid(my_series)
masked_array(data=[1.0, 2.0, --, 0.0, 1.0],
             mask=[False, False,  True, False, False],
       fill_value=1e+20)
>>> my_series
0    1.000000e+00
1    2.000000e+00
2    1.000000e+20
3    0.000000e+00
4    1.000000e+00
dtype: float64

>>> import pandas as pd, numpy as np
>>> pd.__version__; np.__version__
'2.2.2'
'2.0.0'
>>> my_series = pd.Series([1.0, 2.0, np.nan, 0.0, 1.0])
>>> my_series
0    1.0
1    2.0
2    NaN
3    0.0
4    1.0
dtype: float64
>>> np.ma.fix_invalid(my_series)
masked_array(data=[1.0, 2.0, --, 0.0, 1.0],
             mask=[False, False,  True, False, False],
       fill_value=1e+20)
>>> my_series
0    1.0
1    2.0
2    NaN
3    0.0
4    1.0
dtype: float64

[teo-tsirpanis]

numpy.ma.fix_invalid behaves differently between NumPy 2.1.0 and NumPy 2.0.0

Is there an issue on NumPy about that? Can you open one if not?

[teo-tsirpanis]

Change seems fine. Launched nightlies from this branch and will approve if passed.

[kounelisagis]

numpy.ma.fix_invalid behaves differently between NumPy 2.1.0 and NumPy 2.0.0

Is there an issue on NumPy about that? Can you open one if not?

I couldn't find an existing issue, but I can open a new one.

[teo-tsirpanis]

One previously failing job now succeeds. Thanks!