-
numpy.ma.mask_rows(a, axis=None)
[source] -
Mask rows of a 2D array that contain masked values.
This function is a shortcut to
mask_rowcols
withaxis
equal to 0.See also
-
mask_rowcols
- Mask rows and/or columns of a 2D array.
-
masked_where
- Mask where a condition is met.
Examples
12345678910111213141516171819202122232425262728>>>
import
numpy.ma as ma
>>> a
=
np.zeros((
3
,
3
), dtype
=
np.
int
)
>>> a[
1
,
1
]
=
1
>>> a
array([[
0
,
0
,
0
],
[
0
,
1
,
0
],
[
0
,
0
,
0
]])
>>> a
=
ma.masked_equal(a,
1
)
>>> a
masked_array(data
=
[[
0
0
0
]
[
0
-
-
0
]
[
0
0
0
]],
mask
=
[[
False
False
False
]
[
False
True
False
]
[
False
False
False
]],
fill_value
=
999999
)
>>> ma.mask_rows(a)
masked_array(data
=
[[
0
0
0
]
[
-
-
-
-
-
-
]
[
0
0
0
]],
mask
=
[[
False
False
False
]
[
True
True
True
]
[
False
False
False
]],
fill_value
=
999999
)
-
numpy.ma.mask_rows()

2025-01-10 15:47:30
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