matplotlib-users Mailing List for matplotlib (Page 110)

On Fri, Aug 9, 2013 at 6:57 AM, SquirrelSeq
<ral...@un...>wrote:

> Hello everybody,
>
> I created 3D-Plots with 3D bars in matplotlib. The bars are colored
> according to a colormap.
>
> Unfortunately, only vertical faces have the desired bright colors, whereas
> the top sides of the bars are shaded darker to make it look more 3D.
>
> This makes the colors a lot more difficult to see, depending on the
> perspective.
>
> What can I do in order to switch of shading or to add an ambivalent light
> source?
>
> Best regards
> SquirrelSeq
>
> <http://matplotlib.1069221.n5.nabble.com/file/n41766/overlap_heatmap.png>
>
>
The one way to do it is to patch the source code in the following way.

in mpl_toolkits/mplot3d/axes3d.py, at around line 2355, replace the line:

sfacecolors = self._shade_colors(facecolors, normals)

with

sfacecolors = facecolors

Could you file a github issue requesting a keyword argument to turn this
on/off?

Cheers!
Ben Root

Hi Phil,

Phil Elson wrote:
> Hi Martin,
> 
> Thanks for this - we are really interested in speeding up the scatter and barchart plotting with large data sets. In fact, we've done some work (https://github.com/matplotlib/matplotlib/pull/2156) recently to make the situation better.
> 
> I'd really like to review these changes (against matplotlib master), and the best possible solution to doing this is if you were to submit a pull request. If the changes you have made are logically seperable, then I'd encourage you to make a few PRs, but otherwise, a single PR with all of these changes would be great.

I went through the changes there and they just cope with other pieces of matplotlib.
My changes are general python improvements moving away from str.startswith()
and using generators instead of for loops. Just apply the patches yourself and see.
;)

> 
> Would you mind turning these patches into PR(s)? (https://github.com/matplotlib/matplotlib/compare/)

Um, I don't know what to do on that page, sorry. I don't see how to upload my patch file or patched file
to be compared with master. :(

> 
> Thanks!

I am sorry but I just don't have time to fiddle with github. It is just awkward. I even failed to download
diffs of the changes from https://github.com/matplotlib/matplotlib/pull/2156/commits.

I rather continue studying runsnake output. ;-)

Martin

> 
> Phil
> 
> 
> On 9 August 2013 12:53, Martin Mokrejs <mmo...@fo... <mailto:mmo...@fo...>> wrote:
> 
>     Hi,
>       I am drawing some barcharts and scatter plot and the speed for rendering is awful once you have
>     100 000 of dots. I ran python profiler which lead me to .startswith() calls and some for loops
>     which append do a list repeatedly. This parts could be still sped up I think but a first attempt
>     is here:
> 
> 
>     UNPATCHED 1.2.1
> 
>     real    23m17.764s
>     user    13m25.880s
>     sys     3m37.180s
> 
> 
>     PATCHED:
> 
>     real    6m59.831s
>     user    5m18.000s
>     sys     1m40.360s
> 
> 
> 
>     The patches are simple and because I see elsewhere in the code list expansions I do not see any
>     problems with backwards compatibility (new new python language features are required).
> 
>     Hope this helps,
>     Martin
> 
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> 
> 

Hi Martin,

Thanks for this - we are really interested in speeding up the scatter and
barchart plotting with large data sets. In fact, we've done some work (
https://github.com/matplotlib/matplotlib/pull/2156) recently to make the
situation better.

I'd really like to review these changes (against matplotlib master), and
the best possible solution to doing this is if you were to submit a pull
request. If the changes you have made are logically seperable, then I'd
encourage you to make a few PRs, but otherwise, a single PR with all of
these changes would be great.

Would you mind turning these patches into PR(s)? (
https://github.com/matplotlib/matplotlib/compare/)

Thanks!

Phil


On 9 August 2013 12:53, Martin Mokrejs <mmo...@fo...> wrote:

> Hi,
>   I am drawing some barcharts and scatter plot and the speed for rendering
> is awful once you have
> 100 000 of dots. I ran python profiler which lead me to .startswith()
> calls and some for loops
> which append do a list repeatedly. This parts could be still sped up I
> think but a first attempt
> is here:
>
>
> UNPATCHED 1.2.1
>
> real    23m17.764s
> user    13m25.880s
> sys     3m37.180s
>
>
> PATCHED:
>
> real    6m59.831s
> user    5m18.000s
> sys     1m40.360s
>
>
>
> The patches are simple and because I see elsewhere in the code list
> expansions I do not see any
> problems with backwards compatibility (new new python language features
> are required).
>
> Hope this helps,
> Martin
>
>
> ------------------------------------------------------------------------------
> Get 100% visibility into Java/.NET code with AppDynamics Lite!
> It's a free troubleshooting tool designed for production.
> Get down to code-level detail for bottlenecks, with <2% overhead.
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi,
  I am drawing some barcharts and scatter plot and the speed for rendering is awful once you have
100 000 of dots. I ran python profiler which lead me to .startswith() calls and some for loops
which append do a list repeatedly. This parts could be still sped up I think but a first attempt
is here:


UNPATCHED 1.2.1

real    23m17.764s
user    13m25.880s
sys     3m37.180s


PATCHED:

real    6m59.831s
user    5m18.000s
sys     1m40.360s



The patches are simple and because I see elsewhere in the code list expansions I do not see any
problems with backwards compatibility (new new python language features are required).

Hope this helps,
Martin

[re-sending with also the 3rd patch file, sorry]

Hi,
  I am drawing some barcharts and scatter plot and the speed for rendering is awful once you have
100 000 of dots. I ran python profiler which lead me to .startswith() calls and some for loops
which append do a list repeatedly. This parts could be still sped up I think but a first attempt
is here:


UNPATCHED 1.2.1

real    23m17.764s
user    13m25.880s
sys     3m37.180s


PATCHED:

real    6m59.831s
user    5m18.000s
sys     1m40.360s



The patches are simple and because I see elsewhere in the code list expansions I do not see any
problems with backwards compatibility (new new python language features are required).

Hope this helps,
Martin

Hello everybody,

I created 3D-Plots with 3D bars in matplotlib. The bars are colored
according to a colormap.

Unfortunately, only vertical faces have the desired bright colors, whereas
the top sides of the bars are shaded darker to make it look more 3D.

This makes the colors a lot more difficult to see, depending on the
perspective.

What can I do in order to switch of shading or to add an ambivalent light
source?

Best regards
SquirrelSeq

<http://matplotlib.1069221.n5.nabble.com/file/n41766/overlap_heatmap.png> 



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Hi all,

I am incredibly thrilled, on behalf of the amazing IPython Dev Team,
to announce the official release of IPython 1.0 today, an effort
nearly 12 years in the making.  The previous version (0.13) was
released on June 30, 2012, and in this development cycle we had:

~12 months of work.
~700 pull requests merged.
~600 issues closed (non-pull requests).
contributions from ~150 authors.
~4000 commits.


# A little context

What does "1.0" mean for IPython? Obviously IPython has been a staple
of the scientific Python community for years, and we've made every
effort to make it a robust and production ready tool for a long time,
so what exactly do we mean by tagging this particular release as 1.0?
Basically, we feel that the core design of IPython, and the scope of
the project, is where we want it to be.

What we have today is what we consider a reasonably complete, design-
and scope-wise, IPython 1.0: an architecture for interactive
computing, that can drive kernels in a number of ways using a
well-defined protocol, and rich and powerful clients that let users
control those kernels effectively. Our different clients serve
different needs, with the old workhorse of the terminal still being
very useful, but much of our current development energy going into the
Notebook, obviously.  The Notebook enables interactive exploration to
become Literate Computing, bridging the gaps from individual work to
collaboration and publication, all with an open file format that is a
direct record of the underlying communication protocol.

There are obviously plenty of open issues (many of them very
important) that need fixing, and large and ambitious new lines of
development for the years to come.  But the work of the last four
years, since the summer of 2009 when Brian Granger was able to devote
a summer (thanks to funding from the NiPy project - nipy.org) to
refactoring the old IPython core code, finally opened up or
infrastructure for real innovation. By disentangling what was a useful
but impenetrable codebase, it became possible for us to start building
a flexible, modern system for interactive computing that abstracted
the old REPL model into a generic protocol that kernels could use to
talk to clients. This led at first to the creation of the Qt console,
and then to the Notebook and out-of-process terminal client.  It also
allowed us to (finally!) unify our parallel computing machinery with
the rest of the interactive system, which Min Ragan-Kelley pulled off
in a development tour de force that involved rewriting in a few weeks
a huge and complex Twisted-based system.

We are very happy with how the Notebook work has turned out, and it
seems the entire community agrees with us, as the uptake has been
phenomenal.  Back from the very first "IPython 0.0.1" that I started
in 2001:

https://gist.github.com/fperez/1579699

there were already hints of tools like Mathematica: it was my everyday
workhorse as a theoretical physicist and I found its Notebook
environment invaluable. But as a grad student trying out "just an
afternoon hack" (IPython was my very first Python program as I was
learning the language), I didn't have the resources, skills or vision
to attempt building an entire notebook system, and to be honest the
tools of the day would have made that enterprise a miserable one.  But
those ideas were always driving our efforts, and as IPython started
becoming a project with a team, we made multiple attempts to get a
good Notebook built around IPython.  Those interested can read an old
blog post of mine with the history
(http://blog.fperez.org/2012/01/ipython-notebook-historical.html).
The short story is that in 2011, on our sixth attempt, Brian was again
able to devote a focused summer into using our client-server
architecture and, with the stack of the modern web (Javascript, CSS,
websockets, Tornado, ...), finally build a robust system for Literate
Computing across programming languages.

Today, thanks to the generous support and vision of Josh Greenberg at
the Alfred P. Sloan Foundation, we are working very hard on building
the notebook infrastructure, and this release contains major advances
on that front.  We have high hopes for what we'll do next; as a
glimpse of the future that this enables, now there is a native Julia
kernel that speaks to our clients, notebook included:
https://github.com/JuliaLang/IJulia.jl.


# Team

I can't stress enough how impressed I am with the work people are
doing in IPython, and what a privilege it is to work with colleagues
like these.  Brian Granger and Min Ragan-Kelley joined IPython around
2005, initially working on the parallel machinery, but since ~ 2009
they have become the heart of the project. Today Min is our top
committer and knows our codebase better than anyone else, and I can't
imagine better partners for an effort like this.

And from regulars in our core team like Thomas Kluyver, Matthias
Bussonnier, Brad Froehle and Paul Ivanov to newcomers like Jonathan
Frederic and Zach Sailer, in addition to the many more whose names are
in our logs, we have a crazy amount of energy being poured into
IPython.  I hope we'll continue to harness it productively!

The full list of contributors to this release can be seen here:

http://ipython.org/ipython-doc/rel-1.0.0/whatsnew/github-stats-1.0.html


# Release highlights

* nbconvert: this is the major piece of new functionality in this
cycle, and was an explicit part of our roadmap
(https://github.com/ipython/ipython/wiki/Roadmap:-IPython). nbconvert
is now an IPython subcommand to convert notebooks into other formats
such as HTML or LaTeX, but more importantly, it's a very flexible
system that lets you write custom templates to generate new output
with arbitrary control over the formatting and transformations that
are applied to the input.

We want to stress that despite the fact that a huge amount of work
went into nbconvert, this should be considered a *tech preview*
release. We've come to realize how complex this problem is, and while
we'll make every effort to keep the high-level command-line syntax and
APIs as stable as possible, it is quite likely that the internals will
continue to evolve, possibly in backwards-incompatible ways.  So if
you start building services and libraries that make heavy use of the
nbconvert internals, please be prepared for some turmoil in the months
to come, and ping us on the dev list with questions or concerns.

* Notebook improvements: there has been a ton of polish work in the
notebook at many levels, though the file format remains unchanged from
0.13, so you shouldn't have any problems sharing notebooks with
colleagues still using 0.13.

  - Autosave: probably the most oft-requested feature, the notebook
server now autosaves your files!  You can still hit Ctrl-S to force a
manual save (which also creates a special 'checkpoint' you can come
back to).

  - The notebook supports raw_input(), and thus also %debug. This was
probably the main deficiency of the notebook as a client compared to
the terminal/qtconsole, and it has been finally fixed.

  - Add %%html, %%svg, %%javascript, and %%latex cell magics for
writing raw output in notebook cells.
  - Fix an issue parsing LaTeX in markdown cells, which required users
to type \\\, instead of \\.
  -Images support width and height metadata, and thereby 2x scaling
(retina support).
  - %%file has been renamed %%writefile (%%file) is deprecated.

* The input transofrmation code has been updated and rationalized.
This is a somewhat specialized part of IPython, but of importance to
projects that build upon it for custom environments, like Sympy and
Sage.

Our full release notes are here:

http://ipython.org/ipython-doc/rel-1.0.0/whatsnew/version1.0.html

and the gory details are here:

http://ipython.org/ipython-doc/rel-1.0.0/whatsnew/github-stats-1.0.html


# Installation

Installation links and instructions are at: http://ipython.org/install.html
And IPython is also on PyPI: http://pypi.python.org/pypi/ipython


# Requirements

IPython 1.0 requires Python ≥ 2.6.5 or ≥ 3.2.1. It does not support
Python 3.0, 3.1, or 2.5.


# Acknowledgments

Last but not least, we'd like to acknowledge the generous support of
those who make it possible for us to spend our time working on
IPython.  In particular, the Alfred P. Sloan Foundation today lets us
have a solid team working full-time on the project, and without the
support of Enthought Inc at multiple points in our history, we
wouldn't be where we are today.

The full list of our support is here:

http://ipython.org/index.html#support


Thanks to everyone! Please enjoy IPython 1.0, and report all bugs as usual!

Fernando, on behalf of the IPython Dev Team.

-- 
Fernando Perez (@fperez_org; http://fperez.org)
fperez.net-at-gmail: mailing lists only (I ignore this when swamped!)
fernando.perez-at-berkeley: contact me here for any direct mail

On 2013/08/08 12:33 AM, bruno.pace wrote:
> Hey all!
>
> I have been using interactive mode inside classes for a long time, but now
> I'm just trying to use it in a Shell (idle or even in terminal) and it's not
> working.
>
> I try even simple stuff like:
>
> import matplotlib.pyplot as plt
>
> plt.ion()
> plt.plot([1.6,2.7])
> plt.draw()
>
>
> I have found in a topic that using plt.pause(0.001) would work, and indeed
> it shows the graph. But after
>   a few seconds the window gets unresponsive. Note that when I turn off the
> interactive mode everything works normally as well...
>
> In my application, I am plotting a graph (with networkX) and I have to
> refresh it once in a while. When I use the interactive mode inside of a
> class, everything works fine. But now I'm using a module with no class
> inside (or even in the shell) and it refuses to plot!
>
> Any ideas?

The problem here is one of expectations.  See 
http://matplotlib.org/users/shell.html

Eric

>
> Thanks a lot!
>
> Bruno
>
>
>
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Hey all!

I have been using interactive mode inside classes for a long time, but now
I'm just trying to use it in a Shell (idle or even in terminal) and it's not
working.

I try even simple stuff like:

import matplotlib.pyplot as plt

plt.ion()
plt.plot([1.6,2.7])
plt.draw()


I have found in a topic that using plt.pause(0.001) would work, and indeed
it shows the graph. But after
 a few seconds the window gets unresponsive. Note that when I turn off the
interactive mode everything works normally as well... 

In my application, I am plotting a graph (with networkX) and I have to
refresh it once in a while. When I use the interactive mode inside of a
class, everything works fine. But now I'm using a module with no class
inside (or even in the shell) and it refuses to plot!

Any ideas?

Thanks a lot!

Bruno



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I think by download page, Keith meant project page.

The direct link seems to be http://sourceforge.net/p/matplotlib/mailman/ . Is
that permanent enough? Perhaps SF's structure has changed since the "lists" link
on the MPL website (http://sourceforge.net/mail/?group_id=80706) was last updated.

Martin

On 13-08-07 11:37 AM, Michael Droettboom wrote:
> Hmm...  It takes me to the matplotlib project page on sourceforge, which I
> think is as close to a direct permalink as we can get.  Not sure why it takes
> you somewhere else.  Did you get redirected?
>
> Mike
>
> On 08/07/2013 11:47 AM, kei...@bt... wrote:
>> The link "join the matplotlib mailing lists" actually goes to the
>> sourceforge download page.
>>
>> Keith
>>
>>

I think the function should be np.all(dash_list <= 0.0) instead of np.any?
This works 100% fine on my machine so I think it just hangs if all values
are less than or equal to zero. That hangs on my machine as you stated.

>From digging into that I also realized I could have put (None, None) to get
a solid line in my dash list which is what I desired but I think (1,0) is
more intuitive and doesn't cause any errors. Since dash lists have to be
even number of values, could not just put (1) to get a solid line.

I guess do whichever you think is better.

Cheers,
Jeff




On Tue, Aug 6, 2013 at 4:14 AM, Michael Droettboom <md...@st...> wrote:

>  The problem is that a 0-length dash or space is undefined.  In Agg, it
> causes an infinite loop (presumably because the line cursor never moves).
> Saving it to a PDF file and opening it in Acrobat Reader reveals a blank
> page (presumably because it's doing something smarter, but also basically
> throwing up its hands).  In SVG, you get a solid line, which may or may not
> be the right behavior.
>
> Given that a value of 0 doesn't make much sense anyway, I thought it best
> to just disallow it.  Jeffrey: Do you have a good need for this?
>
> Here's the original PR:
>
> https://github.com/matplotlib/matplotlib/pull/1999
>
> Mike
>
>
> On 08/05/2013 01:36 PM, Benjamin Root wrote:
>
> @mdboom, from git blame, this looks to be specifically introduced by you
> via 7e7b5320<https://github.com/matplotlib/matplotlib/commit/7e7b532057c08541489203697987a924e56a7aeb>on May 15th, and you even added some tests for handling path clipping.
> Perhaps the choice of "<=" should have been just "<"?
>
>
> ------------------------------------------------------------------------------
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>
> _______________________________________________
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>
>
>
>
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>

On 08/07/2013 01:24 PM, Matthew Brett wrote:
> Hi,
>
> On Wed, Aug 7, 2013 at 4:50 AM, Michael Droettboom <md...@st...> wrote:
>> It should look in /usr/include and /usr/local/include by default.  Is it
>> in either place?
> There are no freetype* files in either place, no.  How would they get
> there (other than an explicit install)?
>
I think the usual advice here is to install the freetype development 
packages with MacPorts or homebrew -- but this is probably where I 
should step back at let one of the Mac OS-X folks speak up.

Mike

Hmm...  It takes me to the matplotlib project page on sourceforge, which 
I think is as close to a direct permalink as we can get.  Not sure why 
it takes you somewhere else.  Did you get redirected?

Mike

On 08/07/2013 11:47 AM, kei...@bt... wrote:
> The link "join the matplotlib mailing lists" actually goes to the sourceforge download page.
>
> Keith
>
>
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You can set the rcParam "verbose.level" to "debug-annoying".  Then, when 
it runs through all of your fonts, it should be clear which one caused 
the problem.

Note that I'm in the process of rewriting large parts of the font 
infrastructure as part of MEP14, so these sorts of things should 
hopefully be less common in the future.

Mike

On 08/07/2013 11:56 AM, vwf wrote:
> Hello,
>
> Matplotlib does not like one (or more) of my fonts. Since I own a
> considerable set it is very hard to find out which one violates the
> requirements. Is it possible to let matplotlib which font is the
> problem?
>
> Thanks
>
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Hello,

I found an issue where the figure editor (the checkbox icon in the toolbar) 
incorrectly captures the color properties from the existing curves in the plot:

https://github.com/matplotlib/matplotlib/issues/2274

So I put together a pull request that fixes it:

https://github.com/matplotlib/matplotlib/pull/2275

Could we get someone (or someones?) to give it a whirl, make sure everything 
works as expected and that nothing obvious has broken?

Thanks,

Martin

Hi,

On Wed, Aug 7, 2013 at 4:50 AM, Michael Droettboom <md...@st...> wrote:
> It should look in /usr/include and /usr/local/include by default.  Is it
> in either place?

There are no freetype* files in either place, no.  How would they get
there (other than an explicit install)?

Thanks again,

Matthew

On Wed, Aug 7, 2013 at 11:45 AM, <kei...@bt...> wrote:

> The last line of text below seems to say that setting block to either True
> or False causes an override of the blocking behavior.  I don't think this
> is as intended.   Which way round is it (in fact I find it has no effect)?
>
> The problem I have is that using pyplot.show at the top level of a python
> script works correctly, but as soon as I out the same code inside a
> function, I see no plot.
>
> How do I fix this?
>
> Keith
>
> http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show
>
> matplotlib.pyplot.show(*args, **kw)
>
> In non-interactive mode, display all figures and block until the figures
> have been closed; in interactive mode it has no effect unless figures were
> created prior to a change from non-interactive to interactive mode (not
> recommended). In that case it displays the figures but does not block.
>
> A single experimental keyword argument, block, may be set to True or False
> to override the blocking behavior described above.
>

Which version of matplotlib are you using, and which backend?

import matplotlib
print matplotlib.__version__, matplotlib.get_backend()

Cheers!
Ben Root

The last line of text below seems to say that setting block to either True or False causes an override of the blocking behavior.  I don't think this is as intended.   Which way round is it (in fact I find it has no effect)?

The problem I have is that using pyplot.show at the top level of a python script works correctly, but as soon as I out the same code inside a function, I see no plot.

How do I fix this?

Keith

http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.show

matplotlib.pyplot.show(*args, **kw)

In non-interactive mode, display all figures and block until the figures have been closed; in interactive mode it has no effect unless figures were created prior to a change from non-interactive to interactive mode (not recommended). In that case it displays the figures but does not block.

A single experimental keyword argument, block, may be set to True or False to override the blocking behavior described above.

The link "join the matplotlib mailing lists" actually goes to the sourceforge download page.

Keith

Hello,

Matplotlib does not like one (or more) of my fonts. Since I own a
considerable set it is very hard to find out which one violates the
requirements. Is it possible to let matplotlib which font is the
problem?

Thanks

On Tue, Aug 06, 2013 at 01:46:15AM -0700, ChaoYue wrote:
> I am using mat 1.20 and basemap 1.0.5, I tried your code and don't have the
> same issue.

After building matplotlib 1.2.0 and basemap 1.0.6 packages for Debian
the problem is gone: I have coastlines now.

Thanks

It should look in /usr/include and /usr/local/include by default.  Is it 
in either place?

On 08/06/2013 10:16 PM, Matthew Brett wrote:
> Hi,
>
> Continuing my adventures with setuptools....
>
> I'm installing matplotlib into a clean + numpy virtualenv with python.org 2.7
>
> I have CC=clang in order to involve some header problems with the
> default gcc compiler.
>
> numpy compiles and installs OK.
>
> pip install matplotlib errors with:
>
> clang -fno-strict-aliasing -fno-common -dynamic -isysroot
> /Developer/SDKs/MacOSX10.6.sdk -arch i386 -arch x86_64 -g -O2 -DNDEBUG
> -g -O3 -DPY_ARRAY_UNIQUE_SYMBOL=MPL_matplotlib_ft2font_ARRAY_API
> -DPYCXX_ISO_CPP_LIB=1 -I/usr/local/include -I/usr/include
> -I/usr/X11/include -I.
> -I/Users/mb312/.virtualenvs/py27-mpl/lib/python2.7/site-packages/numpy/core/include
> -I/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7
> -c src/ft2font.cpp -o build/temp.macosx-10.6-intel-2.7/src/ft2font.o
>
> In file included from src/ft2font.cpp:3:
>
> In file included from src/ft2font.h:16:
>
> /usr/X11/include/ft2build.h:56:10: fatal error:
> 'freetype/config/ftheader.h' file not found
>
> #include <freetype/config/ftheader.h>
>
>           ^
>
> 1 error generated.
>
> error: command 'clang' failed with exit status 1
>
> I guess I need freetype installed in /usr/local separately?
>
> Thanks for your help,
>
> Matthew
>
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Hi,

Continuing my adventures with setuptools....

I'm installing matplotlib into a clean + numpy virtualenv with python.org 2.7

I have CC=clang in order to involve some header problems with the
default gcc compiler.

numpy compiles and installs OK.

pip install matplotlib errors with:

clang -fno-strict-aliasing -fno-common -dynamic -isysroot
/Developer/SDKs/MacOSX10.6.sdk -arch i386 -arch x86_64 -g -O2 -DNDEBUG
-g -O3 -DPY_ARRAY_UNIQUE_SYMBOL=MPL_matplotlib_ft2font_ARRAY_API
-DPYCXX_ISO_CPP_LIB=1 -I/usr/local/include -I/usr/include
-I/usr/X11/include -I.
-I/Users/mb312/.virtualenvs/py27-mpl/lib/python2.7/site-packages/numpy/core/include
-I/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7
-c src/ft2font.cpp -o build/temp.macosx-10.6-intel-2.7/src/ft2font.o

In file included from src/ft2font.cpp:3:

In file included from src/ft2font.h:16:

/usr/X11/include/ft2build.h:56:10: fatal error:
'freetype/config/ftheader.h' file not found

#include <freetype/config/ftheader.h>

         ^

1 error generated.

error: command 'clang' failed with exit status 1

I guess I need freetype installed in /usr/local separately?

Thanks for your help,

Matthew

Hi,

On Mon, Aug 5, 2013 at 4:36 PM, Scott Lasley <sl...@sp...> wrote:
>
> On Aug 5, 2013, at 4:43 PM, Matthew Brett <mat...@be...> wrote:
>
>> Hi,
>>
>> On Sun, Aug 4, 2013 at 7:26 PM, Scott Lasley <sl...@sp...> wrote:
>>>
>>> On Aug 4, 2013, at 4:47 PM, Matthew Brett <mat...@be...> wrote:
>>>
>>>> Hi,
>>>>
>>>> Congratulations on the new release.
>>>>
>>>> I just tried installing in a fresh installation of Python 2.7 from Python.org
>>>>
>>>> Am I right in thinking the recommended method is:
>>>>
>>>>   pip install matplotlib
>>>>
>>>> ?  I did this, and then:
>>>>
>>>>>>> import matplotlib.pyplot as plt
>>>> Traceback (most recent call last):
>>>> File "<stdin>", line 1, in <module>
>>>> File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/pyplot.py",
>>>> line 24, in <module>
>>>>   import matplotlib.colorbar
>>>> File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/colorbar.py",
>>>> line 29, in <module>
>>>>   import matplotlib.collections as collections
>>>> File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/collections.py",
>>>> line 23, in <module>
>>>>   import matplotlib.backend_bases as backend_bases
>>>> File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/backend_bases.py",
>>>> line 50, in <module>
>>>>   import matplotlib.textpath as textpath
>>>> File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/textpath.py",
>>>> line 14, in <module>
>>>>   from matplotlib.mathtext import MathTextParser
>>>> File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/mathtext.py",
>>>> line 62, in <module>
>>>>   import matplotlib._png as _png
>>>> ImportError: dlopen(/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/_png.so,
>>>> 2): Library not loaded: /usr/X11/lib/libpng12.0.dylib
>>>> Referenced from:
>>>> /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/_png.so
>>>> Reason: Incompatible library version: _png.so requires version
>>>> 42.0.0 or later, but libpng12.0.dylib provides version 36.0.0
>>>>
>>>> There were no previous versions of matplotlib installed.  This on OSX 10.6:
>>>>
>>>> Python 2.7.5  just installed from python.org
>>>> X11 installed from the Apple installation disks for 10.6 before `pip
>>>> install matplotlib`
>>>> No homebrew etc
>>>>
>>>> Any hints about how I should debug this further?
>>>>
>>>> Thanks a lot for any help,
>>>>
>>>> Matthew
>>>
>>> I was able to install numpy 1.7.1 and matplotlib 1.30 under OS X 10.6.8 with X11 version XQuartz 2.3.6 (xorg-server 1.4.2-apple56) and python 2.7.5 64-bit from python.org using pip 1.4.
>>>
>>> Have you tried running Software Update?  If you installed X11 after updating to 10.6.8 you can run the combo updater ( http://support.apple.com/kb/DL1399 ) to get the latest X11.   Alternately, you could try installing XQuartz from http://xquartz.macosforge.org/landing/
>>
>> Yes, the system was up to date before I installed matplotlib.   Just
>> to check my failing memory, I checked for updates (none), reinstalled
>> and got the same answer.
>>
>> The combo updater looks like it's a fast track to the same outcome as
>> Software update - is it something different?
>
> I don't remember if Software Update detects updates to X11.  What version of X11 are you running?  The version on the Snow Leopard install disks, 2.3.4, is older than version 2.3.6 installed by the combo updater.

Sorry - I am afraid I installed the combo updater over the existing
X11 before I read your email properly, so I don't know what version I
had before.

> As far as I know there is no standalone X11 2.3.6 updater for Snow Leopard.  You'll have to re-install the security updates that came out after the combo updater was released if you use it, which is a bit of a pain.  According to otool -L, the libpng12.0.dylib installed with X11 2.3.6 is version 45, compatibility version 45, so it should work with matplotlib.

Yes, that does work thanks.

> If you don't want to run the combo updater because of possible side effects or install XQuartz you can download libpng from http://sourceforge.net/projects/libpng/files/libpng15/1.5.17/, unpack it and do the standard ./configure, make, sudo make install to install it in /usr/local/lib.  setup.py should find it there.

So, to summarize, pip install for matplotlib will fail on bare-bones
OSX 10.6 unless you do one of:

* Run the combo updater
* Install Quartz X11
* Build your own libpng in /usr/local

Is that a reasonable list?

Is there any way to check for this problem and warn / error at build
time with instructions?

Thanks a lot for the help,

Matthew

On 8/6/2013 3:31 PM, Eric Firing [via matplotlib] wrote:
> Before the *first* import of pyplot, you need to have:
>
> import matplotlib
> matplotlib.use("agg")
>
> or specify any other non-interactive backend.  Alternatively, you can
> specify the backend in a matplotlibrc file.
>
> This assumes you don't actually need an interactive backend.  If you do
> need it, then I suspect you will need to change the strategy you are
> using in your program, ideally eliminating the input thread.  You might
> use a gtk idle event callback to handle the user input, for example.
> The problem here is that python threads and gui toolkits tend not to mix
> well.
>
> I suspect that raw_input is using the PyOS_InputHook, which is also
> being used by gtk, so you are violating the prohibition against
> gui-related activities being in more than one thread.
>
> Eric

Thanks Eric, that did work for me.  I don't necessarily need an 
interactive backend for this, but it could be nice to get it to work.  I 
just tried switching raw_input to sys.stdin.readline, and that seems to 
work even with the interactive backend.

John




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