Dear folks, I have some code that stopped working with 1.6.0 and I'm wondering if there's a better way to replace it than what I came up with. Here's a condensed version:
x = [()] # list containing an empty tuple; this isn't the only case, but it's one that must be handled correctly y = np.empty(len(x), dtype=object) y[:] = x[:] In 1.5.1 this works, giving y as "array([()], dtype=object)" In 1.6.0, it raises a ValueError: ValueError: output operand requires a reduction, but reduction is not enabled I didn't see anything in the release notes about this; admittedly it's a very small corner case. I also don't understand what the error message is trying to tell me here. Most of the more straightforward ways to construct the desired array don't work because the interpretation of a nested structure is as a multi-dimensional array, which is reasonable. At this point my workaround is to replace the assignment with a loop: for i, v in enumerate(x): y[i] = v but this seems non-Numpyish. Any light on what the error means or a better way to do this would be most welcome. Thanks, Ken _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion