How to invert numpy.where (np.where) function
mask = X > 0imask = np.logical_not(mask)For example
Edit: Sorry for being so concise before. Shouldn't be answering things on the phone :P
As I noted in the example, it's better to just invert the boolean mask. Much more efficient/easier than going back from the result of where.
The bottom of the np.where docstring suggests to use np.in1d for this.
>>> x = np.array([1, 3, 4, 1, 2, 7, 6])>>> indices = np.where(x % 3 == 1)[0]>>> indicesarray([0, 2, 3, 5])>>> np.in1d(np.arange(len(x)), indices)array([ True, False, True, True, False, True, False], dtype=bool)(While this is a nice one-liner, it is a lot slower than @Bi Rico's solution.)