numpy.ma.compress_rowcols()

numpy.ma.compress_rowcols(x, axis=None) [source]

Suppress the rows and/or columns of a 2-D array that contain masked values.

The suppression behavior is selected with the axis parameter.

If axis is None, both rows and columns are suppressed.
If axis is 0, only rows are suppressed.
If axis is 1 or -1, only columns are suppressed.

Parameters:

Parameters:	x : array_like, MaskedArray The array to operate on. If not a MaskedArray instance (or if no array elements are masked), `x` is interpreted as a MaskedArray with `mask` set to `nomask`. Must be a 2D array. axis : int, optional Axis along which to perform the operation. Default is None.
Returns:	compressed_array : ndarray The compressed array.

x : array_like, MaskedArray

The array to operate on. If not a MaskedArray instance (or if no array elements are masked), x is interpreted as a MaskedArray with mask set to nomask. Must be a 2D array.

axis : int, optional

Axis along which to perform the operation. Default is None.

Returns:

compressed_array : ndarray

The compressed array.

Examples

>>> x = np.ma.array(np.arange(9).reshape(3, 3), mask=[[1, 0, 0],
...                                                   [1, 0, 0],
...                                                   [0, 0, 0]])
>>> x
masked_array(data =
 [[-- 1 2]
 [-- 4 5]
 [6 7 8]],
             mask =
 [[ True False False]
 [ True False False]
 [False False False]],
       fill_value = 999999)

>>> np.ma.compress_rowcols(x)
array([[7, 8]])
>>> np.ma.compress_rowcols(x, 0)
array([[6, 7, 8]])
>>> np.ma.compress_rowcols(x, 1)
array([[1, 2],
       [4, 5],
       [7, 8]])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.ma.compress_rowcols.html

doc_NumPy

2025-01-10 15:47:30

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