matplotlib-users Mailing List for matplotlib

> Hi Erik -- if you succeed, then we'll have convincing proof that
> compiling mpl on solaris is easier than giving up the sauce.

Well, it has turned out to be easier than giving up the sauce (at least
for me), but only by a whisker.  In the end, the fix is incredibly simple
(if you consider recompiling python and manually adjusting the
auto-produced pyconfig.h incredibly simple, anyway).  After two solid days
of commenting this and that out, recompiling everything and its mother 76
different ways from Sunday, poring over a legion of Solaris sys includes,
slaughtering a few spotlessly white lambs and one pure black sheep,
wrapping the bones and tendons and viscera in a double layer of fat and
burning the offering to Delphic Apollo, I found the answer:

1) download Python 2.4.2
2) after extracting it and running ./configure, edit the generated
pyconfig.h as follows:
	i) if _XOPEN_SOURCE is defined to be 600 (i.e., if the line
	"#define _XOPEN_SOURCE 600" appears in the file), redefine it to
	500
	ii) if _XOPEN_SOURCE_EXTENDED is defined at all (i.e. if the line
        "#define _XOPEN_SOURCE_EXTENDED 1" appears in the file),
	comment out its definition
3) make && make install

The problem was with Solaris's support for the X/Open standards.  To make
a long story short, you can use Open Group Technical Standard, Issue 6
(XPG6/UNIX 03/SUSv3) (_XOPEN_SOURCE == 600) if and only if you are using
an ISO C99 compiler.  If you use X/Open CAE Specification, Issue 5
(XPG5/UNIX 98/SUSv2) (_XOPEN_SOURCE == 500), you don't have to use an ISO
C99 compiler.  For full details, see the Solaris header file
/usr/include/sys/feature_tests.h.

This is why muhpubuh (AKA matplotlib---long story) compiles
on Solaris 10 if you have the big bucks and can afford Sun's OpenStudio 10
compiler.  gcc does not have full C99 support yet.  In particular, its
lack of support for the wide character library makes the build go
bust.  (See, e.g., http://gcc.gnu.org/c99status.html.)

There is one remaining item I find extremely puzzling about the whole
affair, though.  Since I don't have a recent glib/gtk+ library installed,
and didn't want to make more hoops for myself to jump through, I attempted
to build muhpuhbuh without gtk+ support.  Nothing I did would get it to
build without gtk+ support, though.  I finally commented out every line in
setup.py and setupext.py that had anything to with gtk+ (the variables
BUILD_GTKAGG, BUILD_GTK, etc., the conditional code-blocks if BUILD_GTK:,
if BUILD_GTKAGG:, etc., the functions build_gdk, build_gtkagg, etc.), but
to no avail.  There, in my
local/lib/python2.4/site-packages/matplotlib/backends/, big as life, are
backend_gtk.py, backend_gtkagg.py, etc.  When I tried to import pylab from
the command-line interpreter, I naturally got lots of errors from those
spurious backends complaining about not being able to find libgobject.so,
etc.  I finally had to manually change the backend parameter in my
.matplotlibrc to TkAgg to get it to work.  What's up with that?

E

Travis Brady wrote:

>I'd like to make a map of the U.S. where I draw the state lines and
>apply a color to each state based on a ratio I've got in my data.  I'm
>staring at the example here:
>http://matplotlib.sourceforge.net/screenshots/plotmap.py, but what I'm
>trying to do is much simpler so I'm wondering if there's a helper
>function somewhere.
>
>thanks,
>
>Travis
>  
>
Travis: I posted an example of how to color state polygons with random 
colors earlier - here's a modification that colors the states based on 
population density.  It shows how to use a colormap to choose the colors 
based upon your data - I think this is closer to what you were asking for.

-Jeff

-- 
Jeffrey S. Whitaker         Phone  : (303)497-6313
Meteorologist               FAX    : (303)497-6449
NOAA/OAR/CDC  R/CDC1        Email  : Jef...@no...
325 Broadway                Office : Skaggs Research Cntr 1D-124
Boulder, CO, USA 80303-3328 Web    : http://tinyurl.com/5telg

>>>>> "Jeff" == Jeff Peery <jef...@se...> writes:


    Jeff> I know this bug has already been posted. I was wondering if
    Jeff> there is a way to get around it? ... 

Use scatter, which is functionally equivalent and supports alpha.

JDH

>>>>> "Erik" == Erik Curiel <ec...@ke...> writes:

    Erik> interpreter.  Any suggestions about where to start looking,
    Erik> and what to look for, to debug this will be greatly
    Erik> appreciated.

    Erik> _transforms_module::new_value _transforms_module::new_value
    Erik> _transforms_module::new_point Point::Point
    Erik> _transforms_module::new_value _transforms_module::new_value

   ...snip snip

You have VERBOSE=True in setup.py.  While this is fine, it's really
only useful when debugging segfaults in the extension code (not python
exceptions).  When debugging python level problems, it suffices to run
with 

  > python myscript.py --verbose-helpful
  > python myscript.py --verbose-debug

The default verbose setting is set in your rc file
http://matplotlib.sf.net/matplotlibrc

    Erik> line 9, in ?  from backend_agg import FigureCanvasAgg File
    Erik> "/home/erik/util/lib/python2.4/site-packages/matplotlib/backends/backend_agg.py",
    Erik> line 94, in ?  from _nc_backend_agg import RendererAgg as
    Erik> _RendererAgg ImportError: No module named _nc_backend_agg

Hmmm..  Do you have Numeric installed?  Ie, in the environment in
which you are building, can you do

> python
>>> import Numeric

matplotlib supports both Numeric and numarray via the numerix module,
and builds two extensions for each extension code module, ie,
_nc_backend_agg and _na_backend_agg.  Which one it builds depends on
what it finds at compile time (Numeric or numarray).  If for example
you have only numarray installed, it will build only for numarray.
Unfortunately, the rc file is pretty dumb, and doesn't reflect these
dynamic compile time settings.  

But the default rc setting for numerix is Numeric.  My guess is that
this is your problem, and can be fixed either by setting numerix :
numarray or installing Numeric and recompiling.

In any case, you will want to turn off VERBOSE in setup.py, flush the
build subdir, and recompile.

Another lurking gotcha along these lines is the backend setting.

  backend      : GTKAgg     # the default backend
  numerix      : Numeric    # Numeric or numarray

As with numerix, the backend setting requires you have the appropriate
GUI toolkit installed (eg pygtk) often at compile time if you want to
use a GUI.  If you are only doing offline image production you can
make the backend Agg.  See also 

  http://matplotlib.sf.net/backends.html.

JDH