Thank you all for your replies. It's not an urgent problem:
1. Jens gave us a link to an existing third party lib, althought it's
not clear to me how it will work without pytest (i.e. with standard
unittest).
2. My workaround is simply to use top level test functions as you
suggest, and the re
Fabien,
The @image_comparison operator is still somehwat of a black box for me. But
I can confirm your observation that it only works on top-level test
functions, not within a class.
It's on my long, and slowly shifting backlog of things to try to improve.
-paul
On Thu, Jul 30, 2015 at 6:47 AM,
Have u tried ?
plt.ylabel(r'$\alpha$')
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-
Thomas Robitailles pytest image comparison plugin might also be of
interest
https://github.com/astrofrog/pytest-mpl
Jens
tor. 30. jul. 2015 kl. 14.43 skrev Thomas Caswell :
>
> Paul Hobson expressed interest in making it easier to use the image
> comparison tests out side of the mpl test suite
Paul Hobson expressed interest in making it easier to use the image
comparison tests out side of the mpl test suite
Tom
On Thu, Jul 30, 2015, 9:28 AM Fabien wrote:
> Hi all,
>
> is it possible to use the @image_comparison decorator for tests
> generated within a unittest.TestCase class?
>
> Wit
Hi all,
is it possible to use the @image_comparison decorator for tests
generated within a unittest.TestCase class?
With my attempts so far the decorator was indeed instanicated at run
time but the test was not called, i.e. the test would allways pass...
Running the test with decorator from ou
On 07/30/2015 10:07 AM, Eric Firing wrote:
> Forcing the scalar to be a 1-element array would still leave the API
> inconsistent with what you show for Normalize. One solution is to
> flag a scalar at the start, and then de-reference at the end. Would
> you like to submit a PR to take care of thi
Forcing the scalar to be a 1-element array would still leave the API
inconsistent with what you show for Normalize. One solution is to
flag a scalar at the start, and then de-reference at the end. Would
you like to submit a PR to take care of this?
---
On 07/29/2015 10:34 PM, Paul Hobson wrote:
> See the following example:
>
> import matplotlib as mpl
> c = mpl.cm.get_cmap()
> bnorm = mpl.colors.BoundaryNorm([0,1,2], c.N)
> nnorm = mpl.colors.Normalize(0, 2)
>
> # This works:
> In [8]: c(nnorm(1.1))
> Out[8]: (0.64
