[Numpy-discussion] indexed assignment testcases

[Sebastian Berg]

On So, 2014-07-06 at 15:32 -0400, Benjamin Root wrote:
> 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
> 

The shapes match using broadcasting. Values shape of (1,) can be
broadcast to indexing result shape of (0,).

> 
> 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)
> 
Gives a (maybe not good) deprecation warning in master. But those are
typically invisible...

> 
> a[mask_in] = np.array([2.0]) # This works and repeats 2.0 twice. I
> thought this wasn't supposed to happen anymore?
> 

Again, broadcasting of values onto out shape.

- Sebastian

> 
> Ben Root
> 
> 
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