compress_rowcols(x, axis=None)
The suppression behavior is selected with the :None:None:`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.
The array to operate on. If not a MaskedArray instance (or if no array elements are masked), x is interpreted as a MaskedArray with :None:None:`mask` set to :None:None:`nomask`. Must be a 2D array.
Axis along which to perform the operation. Default is None.
The compressed array.
Suppress the rows and/or columns of a 2-D array that contain masked values.
>>> 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]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
numpy.ma.extras.compress_rows
numpy.ma.extras.compress_cols
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