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fix_invalid(a, mask=False, copy=True, fill_value=None)

Invalid data means values of :None:None:`nan`, :None:None:`inf`, etc.

Notes

A copy is performed by default.

Parameters

a : array_like

Input array, a (subclass of) ndarray.

mask : sequence, optional

Mask. Must be convertible to an array of booleans with the same shape as :None:None:`data`. True indicates a masked (i.e. invalid) data.

copy : bool, optional

Whether to use a copy of a (True) or to fix a in place (False). Default is True.

fill_value : scalar, optional

Value used for fixing invalid data. Default is None, in which case the a.fill_value is used.

Returns

b : MaskedArray

The input array with invalid entries fixed.

Return input with invalid data masked and replaced by a fill value.

Examples

This example is valid syntax, but we were not able to check execution
>>> x = np.ma.array([1., -1, np.nan, np.inf], mask=[1] + [0]*3)
... x masked_array(data=[--, -1.0, nan, inf], mask=[ True, False, False, False], fill_value=1e+20)
This example is valid syntax, but we were not able to check execution
>>> np.ma.fix_invalid(x)
masked_array(data=[--, -1.0, --, --],
             mask=[ True, False,  True,  True],
       fill_value=1e+20)
This example is valid syntax, but we were not able to check execution
>>> fixed = np.ma.fix_invalid(x)
... fixed.data array([ 1.e+00, -1.e+00, 1.e+20, 1.e+20])
This example is valid syntax, but we were not able to check execution
>>> x.data
array([ 1., -1., nan, inf])
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.ma.fix_invalid

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GitHub : /numpy/ma/core.py#718
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