Hi folks, I am awaiting my approval to join the numpy-discussion mailing list, at scipy.org. I realize that would be the best place to ask my question. However, numpy is so widely used, I figure that someone here would be able to help.
I like to use numpy.where() to select parts of arrays. I have encountered what I would consider to be a bug when you try to use where() in conjunction with the multiple comparison syntax of Python. Here's a minimal example: Python 3.3.2+ (default, Oct 9 2013, 14:50:09) [GCC 4.8.1] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import numpy as np >>> a = np.arange(10) >>> a array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) >>> b = np.where(a < 5) >>> b (array([0, 1, 2, 3, 4]),) >>> c = np.where(2 < a < 7) Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() Defining b works as I want and expect. The array contains the indices (not the values) of a where a < 5. For my definition of c, I expect (array([3, 4, 5, 6]),). As you can see, I get a ValueError instead. I have seen the error message about "the truth value of an array with more than one element" before, and generally I understand how I (accidentally) provoke it. This time, I don't see it. In defining c, I expect to be stepping through a, one element at a time, just as I did when defining b. Does anyone understand why this happens? Is there a smart work-around? Thanks. -- https://mail.python.org/mailman/listinfo/python-list
