Updating the shrink keyword functionality in masked_values (Trac #2082)

[numpy-gitbot]

Original ticket http://projects.scipy.org/numpy/ticket/2082 on 2012-03-15 by trac user gsever, assigned to @pierregm.

Considering this simple case:

x = np.array([1, 1.1, 2, 1.1, 3])

ma.masked_values(x, 1.5)
masked_array(data = [ 1.   1.1  2.   1.1  3. ],
      mask = False,
      fill_value=1.5)

ma.masked_values(x, 1.5, shrink=False)
masked_array(data = [ 1.   1.1  2.   1.1  3. ],
      mask = False,
      fill_value=1.5)

Setting the 'shrink' keyword to False should create a mask with False filled array provided the condition is not met. The improved shrink keyword handling should yield the following masked array.

ma.masked_values(x, 1.5, shrink=False)
masked_array(data = [1.0 1.1 2.0 1.1 3.0],
             mask = [False False False False False],
       fill_value = 1.5)

The documentation about masked_values is at:
http://docs.scipy.org/doc/numpy/reference/generated/numpy.ma.masked_values.html