matplotlib-users Mailing List for matplotlib

I noticed in your output that another figure seems to have been created
(you see its output as "<matplotlib.figure.Figure at 0x1354cb70>"). It
would be useful to add some print statements to figure out exactly which
line is emitting that. Second, you are calling "plt.savefig()" in the
for-loop for the same filename. I suspect that isn't what you want. I am
going to assume that you want to save a final figure after the for-loop is
complete, right?

Also, it would be more clear to use "fig.savefig()" instead of the more
"magical" plt.savefig() as the latter would automatically create a figure
if one didn't exist for some reason.

Ben Root


On Sat, May 16, 2015 at 11:57 AM, Thomas Caswell <tca...@gm...> wrote:

> This is coming out of the pandas plotting tools, you might get better
> answers on their mailing list.
>
> Tom
>
> On Sat, May 16, 2015 at 11:51 AM Juan Wu <wuj...@gm...> wrote:
>
>> Hi, List experts,
>>
>> I have a matplotlib problem when I tried to use a tool called HDDM. As
>> HDDM is another issue, I here just post my problem with Matplotlib. In
>> short, the error alarm appeard when I input fig = plt.figure(). I am a
>> beginner with those stuff.
>>
>> I would appreciate if anyone can give me any good pointers.
>>
>> Thanks so much,
>> Juan
>>
>> ==================
>>
>> In [8]: fig = plt.figure()
>> <matplotlib.figure.Figure at 0x13293890>
>>
>> In [9]: ax = fig.add_subplot(111, xlabel='RT', ylabel='count',
>> title='RT distributions')
>>
>> In [10]: for i, subj_data in data.groupby('subj_idx'):
>>     ...:     subj_data.rt.hist(bins=20, histtype='step', ax=ax)
>>     ...:     plt.savefig('hddm_demo_fig_00.pdf')
>>
>> <matplotlib.figure.Figure at 0x1354cb70>
>> Traceback (most recent call last):
>>
>>   File "<ipython-input-15-3b0b3c83094c>", line 2, in <module>
>>     subj_data.rt.hist(bins=20, histtype='step', ax=ax)
>>
>>   File "C:\Anaconda\lib\site-packages\pandas\tools\plotting.py", line
>> 2830, in hist_series
>>     raise AssertionError('passed axis not bound to passed figure')
>>
>> AssertionError: passed axis not bound to passed figure
>>
>> (relevant link:
>> https://groups.google.com/forum/#!topic/hddm-users/yBeIRJaHGwo
>> there very few experts view and reply questions)
>>
>>
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>
>
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>

Amy,

I expect so (but do not have a system to test on).  Continuum builds
everything on a very old CentOS system and we run our CI tests on ubuntu
12.04 which is of a similar vintage.

The crucial packages are `pkg-config`, `freetype-dev` and `libpng-dev` +
what ever gui framework you want.

Tom


On Mon, May 18, 2015 at 10:24 AM Fort, Amy (Subcontractor) <
Amy...@te...> wrote:

>  *Dear matplotlib-users,*
>
>
>
> *I have a general question on matplotlib.  I see that matplotlib 1.4.3
> supports Python 2.7 (our organization has 2.7.8).  We would like to use
> matplotlib as a plot tool.  Is matplotlib 1.4.3 compatible to run on a
> Linux system with RedHat 5.10?*
>
>
>
> *Thank you.*
>
>
>
> *Amy Fort*
>
>
>
>
>
>
>
>
>
> ------------------------------------------------------------------------------
> One dashboard for servers and applications across Physical-Virtual-Cloud
> Widest out-of-the-box monitoring support with 50+ applications
> Performance metrics, stats and reports that give you Actionable Insights
> Deep dive visibility with transaction tracing using APM Insight.
> http://ad.doubleclick.net/ddm/clk/290420510;117567292;y
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Dear matplotlib-users,

I have a general question on matplotlib.  I see that matplotlib 1.4.3 supports Python 2.7 (our organization has 2.7.8).  We would like to use matplotlib as a plot tool.  Is matplotlib 1.4.3 compatible to run on a Linux system with RedHat 5.10?

Thank you.

Amy Fort

Got my answer here:
http://stackoverflow.com/questions/30301986/matplotlib-imshow-and-pixel-intensity



On Sun, May 17, 2015 at 10:02 PM, Amit Saha <ami...@gm...> wrote:
> Hi all,
>
> Just trying to understand how the value of the matrix fed to imshow()
> function determines the intensity of the pixel in grey scale mode.
> Consider the example code:
>
> import random
> import matplotlib.pyplot as plt
> import matplotlib.cm as cm
>
> def pixels(n=3):
>     pixel_data = []
>     for _ in range(n):
>         row = []
>         for _ in range(n):
>             row.append(random.randint(1, 10))
>         pixel_data.append(row)
>     return pixel_data
>
> if __name__ == '__main__':
>     pixel_data = pixels()
>     print(pixel_data)
>     plt.imshow(pixel_data, origin='lower', cmap=cm.Greys_r)
>     plt.show()
>
>
> The pixel_data here is the 3*3 "matrix":
> [[7, 4, 6], [7, 7, 6], [4, 7, 9]]
>
> How does the values here determine what shade of grey I see in the image?
>
> Thank you in advance.
>
> Best,
> Amit.
>
>
> --
> http://echorand.me



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