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This seems to be a relatively narrow warning, since numpy<=1.24 doesn't throw this warning, nor does WSL2, nor does the native Windows package.
The warning thrown by numpy is:
numpy/core/getlimits.py:542:
"""UserWarning: Signature b'\x00\xd0\xcc\xcc\xcc\xcc\xcc\xcc\xfb\xbf\x00\x00\x00\x00\x00\x00' for <class 'numpy.longdouble'> does not match any known type: falling back to type probe function.This warnings indicates broken support for the dtype! machar = _get_machar(dtype)"""
When importing nibabel, the following stack trace occurs:
This is nearly always np.longdouble, except on Windows, where np.longdouble
is Intel80 storage, but with float64 precision for calculations. In that
case we return float64 on the basis it's the fastest and smallest at the
highest precision.
Given nibabel's intentions here, it seems as though the warning is largely noise? So, I thought I would mention it here in case nibabel wishes to filter this warning.
Note
This seems to be a relatively narrow warning, since
numpy<=1.24
doesn't throw this warning, nor does WSL2, nor does the native Windows package.The warning thrown by
numpy
is:When importing
nibabel
, the following stack trace occurs:import nibabel
->.analyze
->.arrayproxy
->.volumeutils
->.casting
->ok_floats()
nibabel.casting.ok_floats()
->best_float()
->type_info(np.longdouble)
->np.finfo(np.longdouble)
-> warningReading the source code of
best_float()
, I see thatnibabel
actively tries to avoidnp.longdouble
on Windows:nibabel/nibabel/casting.py
Lines 667 to 670 in 0e925ab
Given
nibabel
's intentions here, it seems as though the warning is largely noise? So, I thought I would mention it here in casenibabel
wishes to filter this warning.Related issues:
numpy.longdouble
trigger when importing h5py with numpy>=1.25 h5py/h5py#2357longdouble
support (WSL, not NumPy probably) numpy/numpy#22187The text was updated successfully, but these errors were encountered: