masked_where(condition, a, copy=True)

Return a as an array masked where :None:None:`condition` is True. Any masked values of a or :None:None:`condition` are also masked in the output.

Parameters

condition : array_like

Masking condition. When :None:None:`condition` tests floating point values for equality, consider using masked_values instead.

a : array_like

Array to mask.

copy : bool

If True (default) make a copy of a in the result. If False modify a in place and return a view.

Returns

result : MaskedArray

The result of masking a where :None:None:`condition` is True.

Mask an array where a condition is met.

See Also

masked_equal

Mask where equal to a given value.

masked_greater

Mask where greater than a given value.

masked_greater_equal

Mask where greater than or equal to a given value.

masked_inside

Mask inside a given interval.

masked_invalid

Mask invalid values (NaNs or infs).

masked_less

Mask where less than a given value.

masked_less_equal

Mask where less than or equal to a given value.

masked_not_equal

Mask where :None:None:`not` equal to a given value.

masked_outside

Mask outside a given interval.

masked_values

Mask using floating point equality.

Examples

This example is valid syntax, but we were not able to check execution

>>> import numpy.ma as ma
... a = np.arange(4)
... a
array([0, 1, 2, 3])

This example is valid syntax, but we were not able to check execution

>>> ma.masked_where(a <= 2, a)
masked_array(data=[--, --, --, 3],
             mask=[ True,  True,  True, False],
       fill_value=999999)

Mask array :None:None:`b` conditional on a.

This example is valid syntax, but we were not able to check execution

>>> b = ['a', 'b', 'c', 'd']
... ma.masked_where(a == 2, b)
masked_array(data=['a', 'b', --, 'd'],
             mask=[False, False,  True, False],
       fill_value='N/A',
            dtype='<U1')

Effect of the copy argument.

This example is valid syntax, but we were not able to check execution

>>> c = ma.masked_where(a <= 2, a)
... c
masked_array(data=[--, --, --, 3],
             mask=[ True,  True,  True, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> c[0] = 99
... c
masked_array(data=[99, --, --, 3],
             mask=[False,  True,  True, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> a
array([0, 1, 2, 3])

This example is valid syntax, but we were not able to check execution

>>> c = ma.masked_where(a <= 2, a, copy=False)
... c[0] = 99
... c
masked_array(data=[99, --, --, 3],
             mask=[False,  True,  True, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> a
array([99,  1,  2,  3])

When :None:None:`condition` or a contain masked values.

This example is valid syntax, but we were not able to check execution

>>> a = np.arange(4)
... a = ma.masked_where(a == 2, a)
... a
masked_array(data=[0, 1, --, 3],
             mask=[False, False,  True, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> b = np.arange(4)
... b = ma.masked_where(b == 0, b)
... b
masked_array(data=[--, 1, 2, 3],
             mask=[ True, False, False, False],
       fill_value=999999)

This example is valid syntax, but we were not able to check execution

>>> ma.masked_where(a == 3, b)
masked_array(data=[--, 1, --, --],
             mask=[ True, False,  True,  True],
       fill_value=999999)

See :

Back References

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

numpy.ma.extras.mask_rows numpy.ma.extras.mask_cols numpy.ma.core.masked_less_equal numpy.ma.core.masked_greater dask.array.ma.masked_where dask.array.ma.set_fill_value numpy.ma.core.masked_values numpy.ma.core.masked_inside numpy.ma.core.masked_object numpy.ma.core.masked_equal numpy.ma.core.masked_greater_equal numpy.ma.core.masked_invalid numpy.ma.core.masked_less numpy.ma.core.masked_not_equal numpy.ma.core.mask_rowcols numpy.ma.core.masked_outside

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GitHub : /numpy/ma/core.py#1821
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