While trying to wrap my head around the issues with matplotlib's tri module and the new numpy indexing, I have made some test cases where I wonder if warnings should be issued.
import numpy as np a = np.ones((10,)) all_false = np.zeros((10,), dtype=bool) a[all_false] = np.array([2.0]) # the shapes don't match here mask_in = np.array([False]*8 + [True, True]) a[mask_in] = np.array([]) # raises ValueError as expected a[mask_in] = np.array([[]]) # no exception because it is 2-D, for some reason (on master, but not release-0.9b1) a[mask_in] = np.array([2.0]) # This works and repeats 2.0 twice. I thought this wasn't supposed to happen anymore? Ben Root
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