numpy.ma.MaskedArray.put#
method
- ma.MaskedArray.put(indices, values, mode='raise')[source]#
Set storage-indexed locations to corresponding values.
Sets self._data.flat[n] = values[n] for each n in indices. If values is shorter than
indices
then it will repeat. If values has some masked values, the initial mask is updated in consequence, else the corresponding values are unmasked.- Parameters:
- indices1-D array_like
Target indices, interpreted as integers.
- valuesarray_like
Values to place in self._data copy at target indices.
- mode{‘raise’, ‘wrap’, ‘clip’}, optional
Specifies how out-of-bounds indices will behave. ‘raise’ : raise an error. ‘wrap’ : wrap around. ‘clip’ : clip to the range.
Notes
values can be a scalar or length 1 array.
Examples
>>> x = np.ma.array([[1,2,3],[4,5,6],[7,8,9]], mask=[0] + [1,0]*4) >>> x masked_array( data=[[1, --, 3], [--, 5, --], [7, --, 9]], mask=[[False, True, False], [ True, False, True], [False, True, False]], fill_value=999999) >>> x.put([0,4,8],[10,20,30]) >>> x masked_array( data=[[10, --, 3], [--, 20, --], [7, --, 30]], mask=[[False, True, False], [ True, False, True], [False, True, False]], fill_value=999999)
>>> x.put(4,999) >>> x masked_array( data=[[10, --, 3], [--, 999, --], [7, --, 30]], mask=[[False, True, False], [ True, False, True], [False, True, False]], fill_value=999999)