numpy.ma.where#

ma.where(condition, x=<no value>, y=<no value>)[source]#

Return a masked array with elements from x or y, depending on condition.

Note

When only condition is provided, this function is identical to nonzero. The rest of this documentation covers only the case where all three arguments are provided.

Parameters:

conditionarray_like, bool: Where True, yield x, otherwise yield y.
x, yarray_like, optional: Values from which to choose. x, y and condition need to be broadcastable to some shape.

Returns:

outMaskedArray: An masked array with masked elements where the condition is masked, elements from x where condition is True, and elements from y elsewhere.

See also

numpy.where: Equivalent function in the top-level NumPy module.
nonzero: The function that is called when x and y are omitted

Examples

>>> import numpy as np
>>> x = np.ma.array(np.arange(9.).reshape(3, 3), mask=[[0, 1, 0],
...                                                    [1, 0, 1],
...                                                    [0, 1, 0]])
>>> x
masked_array(
  data=[[0.0, --, 2.0],
        [--, 4.0, --],
        [6.0, --, 8.0]],
  mask=[[False,  True, False],
        [ True, False,  True],
        [False,  True, False]],
  fill_value=1e+20)
>>> np.ma.where(x > 5, x, -3.1416)
masked_array(
  data=[[-3.1416, --, -3.1416],
        [--, -3.1416, --],
        [6.0, --, 8.0]],
  mask=[[False,  True, False],
        [ True, False,  True],
        [False,  True, False]],
  fill_value=1e+20)