Hello,
I am developing a toolkit to parse, analyse and plot some scientific
data using matplotlib. Among them are some application-specific plotting
functions that sort of extend matplotlib.
There are these nice image comparison decorators to test code like that
but I am not sure how to use them for unit testing outside the scope of
matplotlib itself. Is this use case intended and possible for the decorator?
I have experimented with this unsuccessfully in the following way:
There is a tests directory within my package with test functions
decorated like so
@image_comparison(baseline_images=['custom_function'])
def test_custom_function():
# plot stuff...
When I run nosetests, it fails creating some output images in
result_images.
Copying the appropriate files according to [1] to
my_package/tests/baseline_images does not seem to have any effect. There
are neither *-expected* nor *_{pdf,svg}.png files in there, only
custom_function.{pdf,svg,png}. What am I doing wrong?
Eduard
[1] http://matplotlib.org/devel/testing.html
Eduard,
Did you make any progress on this? I'm trying to do the same thing and it's
skipping my tests entirely.
-paul
On Thu, Oct 10, 2013 at 5:41 AM, Eduard Bopp <edu...@ae...>wrote:
> Hello,
>
> I am developing a toolkit to parse, analyse and plot some scientific
> data using matplotlib. Among them are some application-specific plotting
> functions that sort of extend matplotlib.
>
> There are these nice image comparison decorators to test code like that
> but I am not sure how to use them for unit testing outside the scope of
> matplotlib itself. Is this use case intended and possible for the
> decorator?
>
> I have experimented with this unsuccessfully in the following way:
>
> There is a tests directory within my package with test functions
> decorated like so
>
> @image_comparison(baseline_images=['custom_function'])
> def test_custom_function():
> # plot stuff...
>
> When I run nosetests, it fails creating some output images in
> result_images.
>
> Copying the appropriate files according to [1] to
> my_package/tests/baseline_images does not seem to have any effect. There
> are neither *-expected* nor *_{pdf,svg}.png files in there, only
> custom_function.{pdf,svg,png}. What am I doing wrong?
>
> Eduard
>
> [1] http://matplotlib.org/devel/testing.html
>
>
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No, Paul, I haven't really had the time to dig into it myself. I would
also appreciate it very much if anyone could provide an explanation, how
this works and whether it can be used like this.
Eduard
On 11/06/2013 07:55 PM, Paul Hobson wrote:
> Eduard,
>
> Did you make any progress on this? I'm trying to do the same thing and it's
> skipping my tests entirely.
> -paul
>
>
> On Thu, Oct 10, 2013 at 5:41 AM, Eduard Bopp <edu...@ae...>wrote:
>
>> Hello,
>>
>> I am developing a toolkit to parse, analyse and plot some scientific
>> data using matplotlib. Among them are some application-specific plotting
>> functions that sort of extend matplotlib.
>>
>> There are these nice image comparison decorators to test code like that
>> but I am not sure how to use them for unit testing outside the scope of
>> matplotlib itself. Is this use case intended and possible for the
>> decorator?
>>
>> I have experimented with this unsuccessfully in the following way:
>>
>> There is a tests directory within my package with test functions
>> decorated like so
>>
>> @image_comparison(baseline_images=['custom_function'])
>> def test_custom_function():
>> # plot stuff...
>>
>> When I run nosetests, it fails creating some output images in
>> result_images.
>>
>> Copying the appropriate files according to [1] to
>> my_package/tests/baseline_images does not seem to have any effect. There
>> are neither *-expected* nor *_{pdf,svg}.png files in there, only
>> custom_function.{pdf,svg,png}. What am I doing wrong?
>>
>> Eduard
>>
>> [1] http://matplotlib.org/devel/testing.html
>>
>>
>> ------------------------------------------------------------------------------
>> October Webinars: Code for Performance
>> Free Intel webinars can help you accelerate application performance.
>> Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most
>> from
>> the latest Intel processors and coprocessors. See abstracts and register >
>> http://pubads.g.doubleclick.net/gampad/clk?id=60134071&iu=/4140/ostg.clktrk
>> _______________________________________________
>> Matplotlib-devel mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>>
>