matplotlib-devel Mailing List for matplotlib

Tony S Yu wrote:
> 
> On Sep 26, 2008, at 5:01 PM, Eric Firing wrote:
>> Also, if an image cannot be resolved by the output device, info is 
>> lost--one might not see anything at a location where there actually is 
>> a value--whereas with markers, a marker will always show up, and the 
>> only problem is that one can't necessarily distinguish a single point 
>> from a cluster.
>>
>> The real problem with all-zero values is that plot can't handle 
>> "plot([],[])".  One can work around this by putting in bogus values to 
>> plot a single point, saving the line, and then setting the line data 
>> to empty; or, better, by not using the high-level plot command, but by 
>> generating the Line2D object and adding it to the axes.  The Line2D 
>> initializer is happy with empty x and y sequences. I think if you use 
>> this approach it will kill two bugs (failure on all-zeros with sparse 
>> and full arrays) with one very simple stone.
>>
>> Eric
> 
> 
> Thanks for the tip Eric. Below is a patch for spy that implements Eric's 
> suggestion. This patch seems to work for a couple simple tests on my 
> end: sparse and dense arrays with non-zero and all-zero values.
> 
> A couple of notes:
> 
> * the call to `add_artist` isn't needed to show the correct plot, but it 
> may be helpful for debugging.
> 
> * the docstring for `spy` suggests that a Line2D instance is returned, 
> but `spy` currently returns a list with a Line2D instance. I set 
> all-zero arrays to return a list also, for consistency.

Tony,

Changes to spy and a few other things are in svn 6127.

Regarding your last point, the docstring made more sense than the 
original implementation, so I changed the implementation to correspond 
to it.  I hope this does not cause more trouble than it is worth; if it 
looks like it will, then I can easily change the behavior back and 
modify the docstring.  It seems silly to always return a list with a 
single item, though, and I doubt that many people are making heavy use 
of the return value of the spy method anyway.

Regarding your original idea, that sparse arrays should be handled like 
ordinary arrays, with only nonzero values plotted:  I think this is 
going too far, and not far enough, so I did the following:

1) If "precision" is None or a non-zero value, the behavior for sparse 
and ordinary arrays is identical.  Previously, the precision kwarg was 
silently ignored for sparse arrays.  Now it is used.

2) If "precision" is 0, then one gets the old behavior: all locations 
with data are shown, regardless of value.  It seems to me that one 
really wants to have this behavior available, to see how much of a 
sparse array is filled in.

I am not entirely comfortable with the way the "precision" kwarg is 
being used to control this, but it seemed preferable to adding another 
kwarg.  Alternatives could include swapping the roles of 0 and None, or 
letting precision take a string value to specify the old behavior.

Actually, I think the most logical thing would be to let the default 
None give the old behavior, and require precision=0 to get the new 
behavior.  What do you think?  Is it OK if I make this change?  It is 
more consistent with the old behavior.

I also changed the behavior so that if a sparse array is input, with no 
marker specifications, it simply makes a default marker plot instead of 
raising an exception.

Eric

> 
> 
> -Tony
> 
> 
> 
> Index: matplotlib/lib/matplotlib/axes.py
> ===================================================================
> --- matplotlib/lib/matplotlib/axes.py    (revision 6123)
> +++ matplotlib/lib/matplotlib/axes.py    (working copy)
> @@ -6723,9 +6723,9 @@
>          else:
>              if hasattr(Z, 'tocoo'):
>                  c = Z.tocoo()
> -                y = c.row
> -                x = c.col
> -                z = c.data
> +                nonzero = c.data != 0.
> +                y = c.row[nonzero]
> +                x = c.col[nonzero]
>              else:
>                  Z = np.asarray(Z)
>                  if precision is None: mask = Z!=0.
> @@ -6733,8 +6733,12 @@
>                  y,x,z = mlab.get_xyz_where(mask, mask)
>              if marker is None: marker = 's'
>              if markersize is None: markersize = 10
> -            lines = self.plot(x, y, linestyle='None',
> -                         marker=marker, markersize=markersize, **kwargs)
> +            if len(x) == 0:
> +                lines = [mlines.Line2D([], [])]
> +                self.add_artist(lines[0])
> +            else:
> +                lines = self.plot(x, y, linestyle='None',
> +                             marker=marker, markersize=markersize, 
> **kwargs)
>              nr, nc = Z.shape
>              self.set_xlim(xmin=-0.5, xmax=nc-0.5)
>              self.set_ylim(ymin=nr-0.5, ymax=-0.5)
> Index: matplotlib/examples/pylab_examples/masked_demo.py
> ===================================================================
> --- matplotlib/examples/pylab_examples/masked_demo.py    (revision 6123)
> +++ matplotlib/examples/pylab_examples/masked_demo.py    (working copy)
> @@ -1,4 +1,4 @@
> -#!/bin/env python
> +#!/usr/bin/env python
>  '''
>  Plot lines with points masked out.
> 
> Index: matplotlib/examples/misc/rec_groupby_demo.py
> ===================================================================
> --- matplotlib/examples/misc/rec_groupby_demo.py    (revision 6123)
> +++ matplotlib/examples/misc/rec_groupby_demo.py    (working copy)
> @@ -2,7 +2,7 @@
>  import matplotlib.mlab as mlab
> 
> 
> -r = mlab.csv2rec('data/aapl.csv')
> +r = mlab.csv2rec('../data/aapl.csv')
>  r.sort()
> 
>  def daily_return(prices):
> 

Tony S Yu wrote:
> 
> On Sep 26, 2008, at 5:01 PM, Eric Firing wrote:
>> Also, if an image cannot be resolved by the output device, info is 
>> lost--one might not see anything at a location where there actually is 
>> a value--whereas with markers, a marker will always show up, and the 
>> only problem is that one can't necessarily distinguish a single point 
>> from a cluster.
>>
>> The real problem with all-zero values is that plot can't handle 
>> "plot([],[])".  One can work around this by putting in bogus values to 
>> plot a single point, saving the line, and then setting the line data 
>> to empty; or, better, by not using the high-level plot command, but by 
>> generating the Line2D object and adding it to the axes.  The Line2D 
>> initializer is happy with empty x and y sequences. I think if you use 
>> this approach it will kill two bugs (failure on all-zeros with sparse 
>> and full arrays) with one very simple stone.
>>
>> Eric
> 
> 
> Thanks for the tip Eric. Below is a patch for spy that implements Eric's 
> suggestion. This patch seems to work for a couple simple tests on my 
> end: sparse and dense arrays with non-zero and all-zero values.

Tony,

Thanks.  I will take care of this shortly, along with fixing the failure 
of plot([],[]) and maybe a few other things.

Eric

> 
> A couple of notes:
> 
> * the call to `add_artist` isn't needed to show the correct plot, but it 
> may be helpful for debugging.
> 
> * the docstring for `spy` suggests that a Line2D instance is returned, 
> but `spy` currently returns a list with a Line2D instance. I set 
> all-zero arrays to return a list also, for consistency.
> 
> 
> -Tony
> 
> 
> 
> Index: matplotlib/lib/matplotlib/axes.py
> ===================================================================
> --- matplotlib/lib/matplotlib/axes.py    (revision 6123)
> +++ matplotlib/lib/matplotlib/axes.py    (working copy)
> @@ -6723,9 +6723,9 @@
>          else:
>              if hasattr(Z, 'tocoo'):
>                  c = Z.tocoo()
> -                y = c.row
> -                x = c.col
> -                z = c.data
> +                nonzero = c.data != 0.
> +                y = c.row[nonzero]
> +                x = c.col[nonzero]
>              else:
>                  Z = np.asarray(Z)
>                  if precision is None: mask = Z!=0.
> @@ -6733,8 +6733,12 @@
>                  y,x,z = mlab.get_xyz_where(mask, mask)
>              if marker is None: marker = 's'
>              if markersize is None: markersize = 10
> -            lines = self.plot(x, y, linestyle='None',
> -                         marker=marker, markersize=markersize, **kwargs)
> +            if len(x) == 0:
> +                lines = [mlines.Line2D([], [])]
> +                self.add_artist(lines[0])
> +            else:
> +                lines = self.plot(x, y, linestyle='None',
> +                             marker=marker, markersize=markersize, 
> **kwargs)
>              nr, nc = Z.shape
>              self.set_xlim(xmin=-0.5, xmax=nc-0.5)
>              self.set_ylim(ymin=nr-0.5, ymax=-0.5)
> Index: matplotlib/examples/pylab_examples/masked_demo.py
> ===================================================================
> --- matplotlib/examples/pylab_examples/masked_demo.py    (revision 6123)
> +++ matplotlib/examples/pylab_examples/masked_demo.py    (working copy)
> @@ -1,4 +1,4 @@
> -#!/bin/env python
> +#!/usr/bin/env python
>  '''
>  Plot lines with points masked out.
> 
> Index: matplotlib/examples/misc/rec_groupby_demo.py
> ===================================================================
> --- matplotlib/examples/misc/rec_groupby_demo.py    (revision 6123)
> +++ matplotlib/examples/misc/rec_groupby_demo.py    (working copy)
> @@ -2,7 +2,7 @@
>  import matplotlib.mlab as mlab
> 
> 
> -r = mlab.csv2rec('data/aapl.csv')
> +r = mlab.csv2rec('../data/aapl.csv')
>  r.sort()
> 
>  def daily_return(prices):
> 

On Sep 26, 2008, at 5:01 PM, Eric Firing wrote:
> Also, if an image cannot be resolved by the output device, info is  
> lost--one might not see anything at a location where there actually  
> is a value--whereas with markers, a marker will always show up, and  
> the only problem is that one can't necessarily distinguish a single  
> point from a cluster.
>
> The real problem with all-zero values is that plot can't handle  
> "plot([],[])".  One can work around this by putting in bogus values  
> to plot a single point, saving the line, and then setting the line  
> data to empty; or, better, by not using the high-level plot command,  
> but by generating the Line2D object and adding it to the axes.  The  
> Line2D initializer is happy with empty x and y sequences. I think if  
> you use this approach it will kill two bugs (failure on all-zeros  
> with sparse and full arrays) with one very simple stone.
>
> Eric


Thanks for the tip Eric. Below is a patch for spy that implements  
Eric's suggestion. This patch seems to work for a couple simple tests  
on my end: sparse and dense arrays with non-zero and all-zero values.

A couple of notes:

* the call to `add_artist` isn't needed to show the correct plot, but  
it may be helpful for debugging.

* the docstring for `spy` suggests that a Line2D instance is returned,  
but `spy` currently returns a list with a Line2D instance. I set all- 
zero arrays to return a list also, for consistency.


-Tony



Index: matplotlib/lib/matplotlib/axes.py
===================================================================
--- matplotlib/lib/matplotlib/axes.py	(revision 6123)
+++ matplotlib/lib/matplotlib/axes.py	(working copy)
@@ -6723,9 +6723,9 @@
          else:
              if hasattr(Z, 'tocoo'):
                  c = Z.tocoo()
-                y = c.row
-                x = c.col
-                z = c.data
+                nonzero = c.data != 0.
+                y = c.row[nonzero]
+                x = c.col[nonzero]
              else:
                  Z = np.asarray(Z)
                  if precision is None: mask = Z!=0.
@@ -6733,8 +6733,12 @@
                  y,x,z = mlab.get_xyz_where(mask, mask)
              if marker is None: marker = 's'
              if markersize is None: markersize = 10
-            lines = self.plot(x, y, linestyle='None',
-                         marker=marker, markersize=markersize,  
**kwargs)
+            if len(x) == 0:
+                lines = [mlines.Line2D([], [])]
+                self.add_artist(lines[0])
+            else:
+                lines = self.plot(x, y, linestyle='None',
+                             marker=marker, markersize=markersize,  
**kwargs)
              nr, nc = Z.shape
              self.set_xlim(xmin=-0.5, xmax=nc-0.5)
              self.set_ylim(ymin=nr-0.5, ymax=-0.5)
Index: matplotlib/examples/pylab_examples/masked_demo.py
===================================================================
--- matplotlib/examples/pylab_examples/masked_demo.py	(revision 6123)
+++ matplotlib/examples/pylab_examples/masked_demo.py	(working copy)
@@ -1,4 +1,4 @@
-#!/bin/env python
+#!/usr/bin/env python
  '''
  Plot lines with points masked out.

Index: matplotlib/examples/misc/rec_groupby_demo.py
===================================================================
--- matplotlib/examples/misc/rec_groupby_demo.py	(revision 6123)
+++ matplotlib/examples/misc/rec_groupby_demo.py	(working copy)
@@ -2,7 +2,7 @@
  import matplotlib.mlab as mlab


-r = mlab.csv2rec('data/aapl.csv')
+r = mlab.csv2rec('../data/aapl.csv')
  r.sort()

  def daily_return(prices):

Tony S Yu wrote:
> On Sep 26, 2008, at 2:28 PM, John Hunter wrote:
> 
>> On Fri, Sep 26, 2008 at 12:39 PM, Tony S Yu <to...@mi...> wrote:
>>
>>> +                if all(nonzero == False):
>>> +                    raise ValueError('spy cannot plot sparse zeros
>>> matrix')
>> Is raising an exception the right choice here -- why can't we plot an
>> all zeros image?
>>
>> JDH
> 
> I guess you could plot sparse all-zero matrices with image mode.  My  
> only hesitation is that sparse arrays tend to be very large and (I  
> imagine) this would lead to very slow performance. I assumed this was  
> the reason image mode wasn't adapted to use sparse arrays.

Also, if an image cannot be resolved by the output device, info is 
lost--one might not see anything at a location where there actually is a 
value--whereas with markers, a marker will always show up, and the only 
problem is that one can't necessarily distinguish a single point from a 
cluster.

The real problem with all-zero values is that plot can't handle 
"plot([],[])".  One can work around this by putting in bogus values to 
plot a single point, saving the line, and then setting the line data to 
empty; or, better, by not using the high-level plot command, but by 
generating the Line2D object and adding it to the axes.  The Line2D 
initializer is happy with empty x and y sequences. I think if you use 
this approach it will kill two bugs (failure on all-zeros with sparse 
and full arrays) with one very simple stone.

Eric

> 
> Actually, now that I think about it: you could plot a trivially small  
> image and just adjust the coordinates so that they correspond to the  
> original matrix shape. Is this what you were thinking?
> 
> I should note that a dense zero array also fails to plot with spy *if  
> marker mode is used*.
> 
> -T
> 
> -------------------------------------------------------------------------
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> _______________________________________________
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On Sep 26, 2008, at 3:38 PM, John Hunter wrote:

> On Fri, Sep 26, 2008 at 2:36 PM, Tony S Yu <to...@mi...> wrote:
>>
>> Actually, now that I think about it: you could plot a trivially  
>> small image
>> and just adjust the coordinates so that they correspond to the  
>> original
>> matrix shape. Is this what you were thinking?
>
> This is something I considered, but I was thinking less about the
> implementation and more about the functionality.  I don't want to
> raise an exception unless the input doesn't make sense.  I would
> rather the user start at a boring image and figure out why it is blank
> that deal with an exception.

Yeah, I agree this is much friendlier.

>> I should note that a dense zero array also fails to plot with spy  
>> *if marker
>> mode is used*.
>
> Can you fix this along with spy2?

I assume you mean spy, not spy2 (I just searched through the  
matplotlib files and saw that spy2 hasn't existed since 2006). I'll  
work on a patch to return a blank plot using the method described  
above (unless someone chimes in with a better suggestion).

-Tony

On Fri, Sep 26, 2008 at 2:36 PM, Tony S Yu <to...@mi...> wrote:

> I guess you could plot sparse all-zero matrices with image mode.  My only
> hesitation is that sparse arrays tend to be very large and (I imagine) this
> would lead to very slow performance. I assumed this was the reason image
> mode wasn't adapted to use sparse arrays.
>
> Actually, now that I think about it: you could plot a trivially small image
> and just adjust the coordinates so that they correspond to the original
> matrix shape. Is this what you were thinking?

This is something I considered, but I was thinking less about the
implementation and more about the functionality.  I don't want to
raise an exception unless the input doesn't make sense.  I would
rather the user start at a boring image and figure out why it is blank
that deal with an exception.

> I should note that a dense zero array also fails to plot with spy *if marker
> mode is used*.

Can you fix this along with spy2?

JDH

On Sep 26, 2008, at 2:28 PM, John Hunter wrote:

> On Fri, Sep 26, 2008 at 12:39 PM, Tony S Yu <to...@mi...> wrote:
>
>> +                if all(nonzero == False):
>> +                    raise ValueError('spy cannot plot sparse zeros
>> matrix')
>
> Is raising an exception the right choice here -- why can't we plot an
> all zeros image?
>
> JDH

I guess you could plot sparse all-zero matrices with image mode.  My  
only hesitation is that sparse arrays tend to be very large and (I  
imagine) this would lead to very slow performance. I assumed this was  
the reason image mode wasn't adapted to use sparse arrays.

Actually, now that I think about it: you could plot a trivially small  
image and just adjust the coordinates so that they correspond to the  
original matrix shape. Is this what you were thinking?

I should note that a dense zero array also fails to plot with spy *if  
marker mode is used*.

-T

On Fri, Sep 26, 2008 at 12:39 PM, Tony S Yu <to...@mi...> wrote:

> +                if all(nonzero == False):
> +                    raise ValueError('spy cannot plot sparse zeros
> matrix')

Is raising an exception the right choice here -- why can't we plot an
all zeros image?

JDH

When sparse matrices have explicit zero values, `axes.spy` plots those  
zero values. This behavior seems unintentional. For example, the  
following code should have a main diagonal with markers missing in the  
middle, but `spy` currently plots a full main diagonal.

#~~~~~~~~~~~
import scipy.sparse as sparse
import matplotlib.pyplot as plt

sp = sparse.spdiags([[1,1,1,0,0,0,1,1,1]], [0], 9, 9)
plt.spy(sp, marker='.')
#~~~~~~~~~~~

Below is a patch which only plots the nonzero entries in a sparse  
matrix. Note, sparse matrices with all zero entries raises an error;  
this behavior differs from dense matrices. I could change this  
behavior, but I wanted to minimize the code changed.

Cheers,

-Tony

PS: this patch also includes two trivial changes to some examples.

Index: lib/matplotlib/axes.py
===================================================================
--- lib/matplotlib/axes.py	(revision 6122)
+++ lib/matplotlib/axes.py	(working copy)
@@ -6723,9 +6723,11 @@
          else:
              if hasattr(Z, 'tocoo'):
                  c = Z.tocoo()
-                y = c.row
-                x = c.col
-                z = c.data
+                nonzero = c.data != 0.
+                if all(nonzero == False):
+                    raise ValueError('spy cannot plot sparse zeros  
matrix')
+                y = c.row[nonzero]
+                x = c.col[nonzero]
              else:
                  Z = np.asarray(Z)
                  if precision is None: mask = Z!=0.
Index: examples/pylab_examples/masked_demo.py
===================================================================
--- examples/pylab_examples/masked_demo.py	(revision 6122)
+++ examples/pylab_examples/masked_demo.py	(working copy)
@@ -1,4 +1,4 @@
-#!/bin/env python
+#!/usr/bin/env python
  '''
  Plot lines with points masked out.

Index: examples/misc/rec_groupby_demo.py
===================================================================
--- examples/misc/rec_groupby_demo.py	(revision 6122)
+++ examples/misc/rec_groupby_demo.py	(working copy)
@@ -2,7 +2,7 @@
  import matplotlib.mlab as mlab


-r = mlab.csv2rec('data/aapl.csv')
+r = mlab.csv2rec('../data/aapl.csv')
  r.sort()

  def daily_return(prices):

Robert Kern <rob...@gm...>
writes:

 > L*u*v* or its cylindrical-coordinate cousin L*t*theta* (or
 > LCH_uv). "Choosing Color Palettes for Statistical Graphics" is a
 > nice paper talking about an implementation in R (although they do
 > seem to misname L*t*theta* as HCL, which officially is different):
 >
 >    http://eeyore.ucdavis.edu/stat250/epub-wu-01_abd.pdf

That link did not work for me, this looks to be an alternative:

http://epub.wu-wien.ac.at/dyn/virlib/wp/eng/mediate/epub-wu-01_abd.pdf?ID=epub-wu-01_abd

-- 
Pete Forman                -./\.-  Disclaimer: This post is originated
WesternGeco                  -./\.-   by myself and does not represent
pet...@we...    -./\.-   the opinion of Schlumberger or
http://petef.22web.net           -./\.-   WesternGeco.

On Thursday 25 September 2008 11:53:04 am John Hunter wrote:
> On Thu, Sep 25, 2008 at 9:31 AM, Darren Dale <dsd...@gm...> wrote:
> > I noticed this morning that my Times and Palatino system fonts are not
> > being found anymore. I removed my fontManager.cache and ran my script
> > with verbose=debug, and it looks like creatFontDict found them, but then
> > findfont cant:
>
> I recently fixed another bug related to font finding when an explicit
> file name was passed -- I wonder if I broke a normal use case.  It's a
> simple change shown in the diff below.  Could you manually revert on
> your end and see if it makes a difference.  If so, I'll have to find
> another solution to the problem I was fixing.
>
>
> johnh@flag:mpl> svn diff lib/matplotlib/font_manager.py -r6097:6098
> Index: lib/matplotlib/font_manager.py
> ===================================================================
> --- lib/matplotlib/font_manager.py      (revision 6097)
> +++ lib/matplotlib/font_manager.py      (revision 6098)
> @@ -955,7 +955,7 @@
>          fname = prop.get_file()
>          if fname is not None:
>              verbose.report('findfont returning %s'%fname, 'debug')
> -            return fname[0]
> +            return fname
>
>          if fontext == 'afm':
>              fontdict = self.afmdict

I tried this, but it didnt change anything. I ended up checking the values of 
the keys in the fontdict, and noticed that rather than "Times" I needed to 
use "Times New Roman", for example. Maybe this is a change in my font 
packages, or maybe my configuration was always out of whack and I hadnt 
noticed because I was using usetex up until now, in which case I apologize 
for noise.

On Thu, Sep 25, 2008 at 9:31 AM, Darren Dale <dsd...@gm...> wrote:
> I noticed this morning that my Times and Palatino system fonts are not being
> found anymore. I removed my fontManager.cache and ran my script with
> verbose=debug, and it looks like creatFontDict found them, but then findfont
> cant:

I recently fixed another bug related to font finding when an explicit
file name was passed -- I wonder if I broke a normal use case.  It's a
simple change shown in the diff below.  Could you manually revert on
your end and see if it makes a difference.  If so, I'll have to find
another solution to the problem I was fixing.


johnh@flag:mpl> svn diff lib/matplotlib/font_manager.py -r6097:6098
Index: lib/matplotlib/font_manager.py
===================================================================
--- lib/matplotlib/font_manager.py      (revision 6097)
+++ lib/matplotlib/font_manager.py      (revision 6098)
@@ -955,7 +955,7 @@
         fname = prop.get_file()
         if fname is not None:
             verbose.report('findfont returning %s'%fname, 'debug')
-            return fname[0]
+            return fname

         if fontext == 'afm':
             fontdict = self.afmdict

Jeff Whitaker wrote:
> Ryan May wrote:
>> Jeff,
>>
>> I just noticed that the 0.99.1 tarball for Basemap does not include a 
>> pdf of the docs, while 0.99 did.  Was this intentional or just an 
>> oversight?  I only ask because it broke the gentoo option for 
>> installing   the docs.
>>
>> Ryan
>>
>>   
> Ryan:  That wasn't the real docs, it was just a pdf of a tutorial I gave 
> for a class.  It was included by mistake.  The real docs (which are not 
> yet finished) are at:
> 
> http://matplotlib.sf.net/basemap/doc/html
> 
> You can build them yourself if you want, they are in the basemap/doc 
> directory.

Yeah, I noticed that, but haven't tried getting sphinx running here.  I 
was more wondering if it was an oversight or if the gentoo package 
(really, just compiling script) just be modified to no longer look for 
the pdf.  Clearly, it's the latter.

Thanks,

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Ryan May wrote:
> Jeff,
>
> I just noticed that the 0.99.1 tarball for Basemap does not include a 
> pdf of the docs, while 0.99 did.  Was this intentional or just an 
> oversight?  I only ask because it broke the gentoo option for installing 
>   the docs.
>
> Ryan
>
>   
Ryan:  That wasn't the real docs, it was just a pdf of a tutorial I gave 
for a class.  It was included by mistake.  The real docs (which are not 
yet finished) are at:

http://matplotlib.sf.net/basemap/doc/html

You can build them yourself if you want, they are in the basemap/doc 
directory.

-Jeff

-- 
Jeffrey S. Whitaker         Phone : (303)497-6313
NOAA/OAR/CDC  R/PSD1        FAX   : (303)497-6449
325 Broadway                Boulder, CO, USA 80305-3328

Jeff,

I just noticed that the 0.99.1 tarball for Basemap does not include a 
pdf of the docs, while 0.99 did.  Was this intentional or just an 
oversight?  I only ask because it broke the gentoo option for installing 
  the docs.

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

I noticed this morning that my Times and Palatino system fonts are not being 
found anymore. I removed my fontManager.cache and ran my script with 
verbose=debug, and it looks like creatFontDict found them, but then findfont 
cant:

$ python characteristics_size_plots.py
matplotlib data path /usr/lib64/python2.5/site-packages/matplotlib/mpl-data
loaded rc file /home/darren/.matplotlib/matplotlibrc
matplotlib version 0.98.3
verbose.level debug
interactive is False
units is False
platform is linux2
loaded modules: 
['_bisect', 'numpy.ma.types', 'xml.sax.urlparse', 'distutils', 'matplotlib.errno', 'pylab', 'numpy.core.defchararray', 'xml._xmlplus', 'matplotlib.tempfile', 'distutils.sysconfig', 'ctypes._endian', 'encodings.encodings', 'matplotlib.dateutil', 'matplotlib.colors', 'numpy.core.numerictypes', 'numpy.testing.sys', 'numpy.core.info', 'xml', 'numpy.fft.types', 'numpy.ma.operator', 'distutils.dep_util', 'numpy.ma.cPickle', 'struct', 'numpy.random.info', 'tempfile', 'base64', 'numpy.linalg', 'matplotlib.threading', 'numpy.testing.operator', 'enthought.pyface', 'imp', 'numpy.testing', 'collections', 'numpy.core.umath', 'numpy.lib.pkgutil', 'pytz.os', 'numpy.lib.numpy', 'numpy.core.scalarmath', 'numpy.ma.sys', 'matplotlib.matplotlib', 'string', 'numpy.testing.os', 'matplotlib.locale', 'numpy.lib.arraysetops', 'numpy.testing.unittest', 'numpy.lib.math', 'encodings.utf_8', 'matplotlib.__future__', 'pytz.tzinfo', 'numpy.testing.re', 'itertools', 'numpy.version', 'numpy.lib.re', 'distutils.re', 'ctypes.os', 'numpy.core.os', 'numpy.lib.type_check', 'httplib', 'enthought.traits', 'bisect', 'signal', 'enthought.pyface.ui', 'numpy.lib.types', 'numpy.lib._datasource', 'random', 'numpy.ma.extras', 'numpy.fft.fftpack_lite', 'matplotlib.cbook', 'ctypes.ctypes', 'xml.sax.xmlreader', 'matplotlib.pytz', 'numpy.__builtin__', 'distutils.log', 'xml.sax.saxexts', 'cStringIO', 'numpy.ma.core', 'numpy.numpy', 'matplotlib.StringIO', 'locale', 'numpy.add_newdocs', 'numpy.lib.getlimits', 'numpy.random.numpy', 'xml.sax.saxlib', 'pkgutil', 'numpy.testing.types', 'numpy.lib.sys', 'encodings', 'numpy.ma.itertools', 'scikits', 'dateutil', 'numpy.lib.io', 'pytz.cStringIO', 'numpy.imp', 'enthought', 'threading', 'numpy.testing.decorators', 'matplotlib.warnings', 'rfc822', 'matplotlib.string', 'pytz.pytz', 'urllib', 'matplotlib.sys', 're', 'numpy.lib._compiled_base', 'new', 'numpy.random.mtrand', 'math', 'numpy.fft.helper', 'fcntl', 'numpy.ma.warnings', 'matplotlib.numpy', 'UserDict', 'numpy.lib.function_base', 'distutils.os', 'matplotlib', 'numpy.core.types', 'numpy.lib.ufunclike', 'numpy.lib.info', 'ctypes', '_xmlplus', 'ctypes.struct', 'codecs', 'numpy.core._sort', 'numpy.os', 'md5', '_locale', 'matplotlib.sre_constants', 'matplotlib.os', 'thread', 'StringIO', 'numpy.core.memmap', 'traceback', 'pkg_resources', 'numpy.testing.warnings', 'xml.sax.sax2exts', 'weakref', 'numpy.core._internal', 'numpy.fft.fftpack', 'numpy.testing.imp', 'numpy.linalg.lapack_lite', 'distutils.sys', 'os', 'numpy.lib.warnings', 'numpy.lib.itertools', '__future__', 'matplotlib.copy', 'xml.sax.types', 'matplotlib.traceback', '_sre', 'unittest', 'numpy.core.sys', 'numpy.random', 'numpy.linalg.numpy', '__builtin__', 'numpy.lib.twodim_base', 'matplotlib.re', 'numpy.core.cPickle', 'operator', 'numpy.testing.parametric', 'numpy.core.arrayprint', 'distutils.string', 'numpy.lib.arrayterator', 'ctypes._ctypes', 'ctypes.sys', 'matplotlib.datetime', 'posixpath', 'numpy.lib.financial', 'numpy.core.multiarray', 'errno', '_socket', 'binascii', 'sre_constants', 'datetime', 'numpy.ma', 'matplotlib.md5', 'types', 'pytz.sys', 'xml.sax.handler', 'numpy.core.numpy', 'numpy', 'pytz.pkg_resources', 'matplotlib.types', 'numpy.core.defmatrix', 'xml.sax.os', 'cPickle', 'matplotlib.xml', 'xml.sax.string', '_codecs', 'numpy.lib.operator', 'numpy.__config__', 'pytz', 'matplotlib.pyparsing', 'numpy.lib.stride_tricks', 'numpy.ma.numpy', 'copy', 'numpy.core.re', '_struct', '_types', 'numpy.core.fromnumeric', 'hashlib', 'numpy.ctypeslib', 'numpy.lib.scimath', 'numpy.fft', 'numpy.lib', 'xml.sax.saxutils', 'posix', 'encodings.aliases', 'enthought.traits.ui', 'matplotlib.fontconfig_pattern', 'exceptions', 'sre_parse', 'pytz.bisect', 'sets', 'numpy.core.cStringIO', 'numpy.core.ctypes', 'mimetools', 'distutils.distutils', 'copy_reg', 'sre_compile', 'xml.sax', '_hashlib', '_random', 'pytz.struct', 'numpy.lib.__future__', 'site', 'numpy.lib.polynomial', 'numpy._import_tools', 'numpy.core.copy_reg', 'xml.sax.urllib2', 'zipimport', 'xml.sys', '__main__', 'numpy.fft.info', 'numpy.core.records', 'shutil', 'numpy.lib.cPickle', 'numpy.sys', 'matplotlib.weakref', 'numpy.core._dotblas', 'numpy.testing.traceback', 'strop', 'numpy.testing.numpytest', 'numpy.core.numeric', 'pytz.tzfile', 'numpy.linalg.info', 'encodings.codecs', 'gettext', 'pytz.datetime', 'numpy.ctypes', 'numpy.core', 'matplotlib.rcsetup', 'matplotlib.time', 'zlib', 'pytz.sets', 'xml.sax._exceptions', 'xml.sax.codecs', 'stat', '_ssl', 'numpy.lib.utils', 'numpy.lib.index_tricks', 'warnings', 'encodings.types', '_ctypes', 'numpy.lib.shape_base', 'distutils.util', 'urllib2', 'numpy.fft.numpy', 'sys', 'numpy.core.warnings', 'socket', 'numpy.core.__builtin__', 'xml.sax.sys', 'numpy.lib.format', 'numpy.lib.os', 'numpy.testing.nosetester', 'os.path', 'pytz.gettext', 'numpy.lib.shutil', 'distutils.spawn', 'matplotlib.distutils', '_weakref', 'distutils.errors', 'urlparse', 'linecache', 'matplotlib.shutil', 'numpy.lib.cStringIO', 'time', 'numpy.lib.machar', 'numpy.testing.numpy', 'numpy.linalg.linalg', 'numpy.testing.utils']
$HOME=/home/darren
CONFIGDIR=/home/darren/.matplotlib
font search path 
['/usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf', '/usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/afm']
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraBd.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMoBd.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMoIt.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraIt.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz1Sym.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraBI.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz4Sym.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMoBI.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz5Sym.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz2SymBol.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz3Sym.ttf
trying 
fontname /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/Vera.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniIta.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraBd.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMoBd.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmmi10.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralItalic.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMoIt.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraIt.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz1Sym.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraBI.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz4Sym.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMoBI.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz5Sym.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmb10.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz2SymBol.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz3Sym.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/Vera.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz2Sym.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBol.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraSeBd.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmex10.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUniBolIta.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneral.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz4SymBol.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz3SymBol.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraMono.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmtt10.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXSiz1SymBol.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmsy10.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBolIta.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXGeneralBol.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmr10.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraSe.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/STIXNonUni.ttf
createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/cmss10.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeSerifBold.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMBatnan.otf
createFontDict: /home/darren/.fonts/cmmi10.ttf
createFontDict: /usr/share/fonts/corefonts/ariblk.ttf
createFontDict: /usr/share/fonts/corefonts/courbi.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMNisibinOutline.otf
createFontDict: /usr/local/share/fonts/OpenType/PalatinoLTStd-Italic.otf
createFontDict: /usr/local/share/fonts/Adobe/FreeMonoBoldOblique.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMMardin.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSerifCondensed-BoldItalic.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntUpSma.otf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntSmaBol.otf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraMoBI.ttf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraSeBd.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeSansBoldOblique.ttf
createFontDict: /usr/share/fonts/TTF/luxisb.ttf
createFontDict: /usr/share/fonts/corefonts/trebucbi.ttf
createFontDict: /usr/share/fonts/corefonts/georgiab.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeSans.ttf
createFontDict: /home/darren/.fonts/msam10.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz3Sym.otf
createFontDict: /usr/share/fonts/texcm-ttf/cmmi10.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSans-Bold.ttf
createFontDict: /usr/share/fonts/corefonts/georgiai.ttf
createFontDict: /usr/share/fonts/corefonts/impact.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz1SymBol.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansCondensed.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz4SymBol.otf
createFontDict: /home/darren/.fonts/cmsy10.ttf
createFontDict: /usr/share/fonts/TTF/luxirri.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntUpSmaBol.otf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraBd.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMQenNeshrin.otf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraIt.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansCondensed-Oblique.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMTalada.otf
createFontDict: /usr/share/fonts/corefonts/trebucbd.ttf
createFontDict: /home/darren/.fonts/cmex10.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntUpDisBol.otf
createFontDict: /usr/share/fonts/OTF/GohaTibebZemen.otf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraMoBd.ttf
createFontDict: /usr/local/share/fonts/TrueType/PalatinoLTStd-BoldItalic.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMAntioch.otf
createFontDict: /usr/share/fonts/corefonts/couri.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz2Sym.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSerif.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntSma.otf
createFontDict: /usr/share/fonts/corefonts/verdanai.ttf
createFontDict: /usr/share/fonts/corefonts/verdanab.ttf
createFontDict: /usr/local/share/fonts/TrueType/greek.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMUrhoy.otf
createFontDict: /usr/share/fonts/OTF/SyrCOMJerusalemBold.otf
createFontDict: /usr/local/share/fonts/Adobe/FreeSerifItalic.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSerif-Bold.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMMardinBold.otf
createFontDict: /usr/share/fonts/TTF/luxisbi.ttf
createFontDict: /usr/share/fonts/corefonts/arial.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeMonoOblique.ttf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraMoIt.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMJerusalem.otf
createFontDict: /home/darren/.fonts/PalatinoLTStd-Italic.otf
createFontDict: /usr/local/share/fonts/Adobe/FreeMono.ttf
createFontDict: /usr/share/fonts/TTF/luximb.ttf
createFontDict: /usr/share/fonts/corefonts/timesi.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMTurAbdin.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSans-Oblique.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXGeneralItalic.otf
createFontDict: /usr/local/share/fonts/OpenType/PalatinoLTStd-Roman.otf
createFontDict: /usr/share/fonts/TTF/luximr.ttf
createFontDict: /usr/share/fonts/corefonts/comicbd.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXGeneralBolIta.otf
createFontDict: /usr/share/fonts/OTF/SyrCOMMidyat.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSerif-Italic.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeMonoBold.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansMono-BoldOblique.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSans-ExtraLight.ttf
createFontDict: /usr/share/fonts/corefonts/cour.ttf
createFontDict: /usr/local/share/fonts/TrueType/PalatinoLTStd-Bold.ttf
createFontDict: /usr/share/fonts/TTF/GohaTibebZemen.ttf
createFontDict: /usr/share/fonts/corefonts/andalemo.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansMono.ttf
createFontDict: /usr/share/fonts/corefonts/georgiaz.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeSansBold.ttf
createFontDict: /usr/share/fonts/corefonts/trebuc.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntUpDis.otf
createFontDict: /usr/local/share/fonts/OpenType/PalatinoLTStd-Bold.otf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz4Sym.otf
createFontDict: /usr/share/fonts/texcm-ttf/cmsy10.ttf
createFontDict: /usr/share/fonts/TTF/luxisr.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMEdessa.otf
createFontDict: /usr/share/fonts/OTF/SyrCOMUrhoyBold.otf
createFontDict: /usr/local/share/fonts/OpenType/PalatinoLTStd-BoldItalic.otf
createFontDict: /home/darren/.fonts/PalatinoLTStd-Roman.otf
createFontDict: /usr/share/fonts/TTF/luxirbi.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz2SymBol.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansMono-Oblique.ttf
createFontDict: /home/darren/.fonts/cmr10.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntUpBol.otf
createFontDict: /usr/share/fonts/TTF/luximbi.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMJerusalemItalic.otf
createFontDict: /usr/share/fonts/corefonts/ariali.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXNonUniBolIta.otf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraBI.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXNonUniIta.otf
createFontDict: /usr/share/fonts/TTF/luximri.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMKharput.otf
createFontDict: /usr/share/fonts/OTF/SyrCOMNisibin.otf
createFontDict: /usr/share/fonts/texcm-ttf/cmex10.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntDis.otf
createFontDict: /usr/share/fonts/OTF/SyrCOMMalankara.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSans-BoldOblique.ttf
createFontDict: /home/darren/.fonts/PalatinoLTStd-Bold.otf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz5Sym.otf
createFontDict: /home/darren/.fonts/cmbx10.ttf
createFontDict: /usr/local/share/fonts/TrueType/PalatinoLTStd-Roman.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXNonUni.otf
createFontDict: /usr/lib/openoffice/share/fonts/truetype/opens___.ttf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraSe.ttf
createFontDict: /home/darren/.fonts/PalatinoLTStd-BoldItalic.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansCondensed-BoldOblique.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMBatnanBold.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSerifCondensed.ttf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/VeraMono.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMJerusalemOutline.otf
createFontDict: /usr/share/fonts/corefonts/verdana.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXGeneral.otf
createFontDict: /usr/share/fonts/TTF/luxisri.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXVar.otf
createFontDict: /usr/local/share/fonts/OpenType/STIXSiz3SymBol.otf
createFontDict: /usr/share/fonts/corefonts/comic.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansCondensed-Bold.ttf
createFontDict: /usr/local/share/fonts/Adobe/FreeSansOblique.ttf
createFontDict: /home/darren/.fonts/msbm10.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMCtesiphon.otf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntDisBol.otf
createFontDict: /usr/share/fonts/texcm-ttf/cmr10.ttf
createFontDict: /usr/share/fonts/corefonts/arialbd.ttf
createFontDict: /usr/share/fonts/OTF/SyrCOMAdiabene.otf
createFontDict: /usr/share/fonts/dejavu/DejaVuSansMono-Bold.ttf
createFontDict: /usr/share/fonts/corefonts/georgia.ttf
createFontDict: /usr/share/fonts/corefonts/verdanaz.ttf
createFontDict: /usr/local/share/fonts/OpenType/STIXIntUp.otf
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createFontDict: /usr/share/fonts/corefonts/arialbi.ttf
createFontDict: /usr/share/fonts/dejavu/DejaVuSans.ttf
createFontDict: /usr/share/fonts/ttf-bitstream-vera/Vera.ttf
createFontDict: /usr/share/fonts/corefonts/timesbi.ttf
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createFontDict: /usr/local/share/fonts/Adobe/FreeSerif.ttf
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createFontDict: /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/afm/phvr8an.afm
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createFontDict: /usr/share/fonts/Type1/l047013t.afm
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createFontDict: /usr/share/fonts/Type1/l048033t.afm
createFontDict: /usr/share/fonts/Type1/l049013t.afm
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createFontDict: /usr/share/fonts/Type1/c0649bt_.afm
createFontDict: /usr/share/fonts/Type1/c0419bt_.afm
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createFontDict: /usr/share/fonts/Type1/l048013t.afm
createFontDict: /usr/share/fonts/default/ghostscript/n019024l.afm
createFontDict: /usr/share/fonts/Type1/UTB_____.afm
createFontDict: /usr/share/fonts/default/ghostscript/b018032l.afm
createFontDict: /usr/share/fonts/default/ghostscript/n019003l.afm
createFontDict: /usr/share/fonts/default/ghostscript/b018012l.afm
createFontDict: /usr/share/fonts/default/ghostscript/n022024l.afm
createFontDict: /usr/share/fonts/default/ghostscript/p052024l.afm
createFontDict: /usr/share/fonts/default/ghostscript/p052004l.afm
createFontDict: /usr/share/fonts/Type1/UTI_____.afm
createFontDict: /usr/share/fonts/default/ghostscript/z003034l.afm
createFontDict: /usr/share/fonts/default/ghostscript/u004006t.afm
createFontDict: /usr/share/fonts/Type1/courb.afm
createFontDict: /usr/share/fonts/default/ghostscript/b018035l.afm
createFontDict: /usr/share/fonts/default/ghostscript/c059016l.afm
generated new fontManager
backend Qt4Agg version 0.9.1
        findfont failed Times
        findfont failed Palatino
        findfont found Bitstream Vera Serif, normal, normal 400, normal, 8.33
findfont 
returning /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraSe.ttf
        findfont failed Times
        findfont failed Palatino
        findfont found Bitstream Vera Serif, normal, normal 400, normal, 8.33
findfont 
returning /usr/lib64/python2.5/site-packages/matplotlib/mpl-data/fonts/ttf/VeraSe.ttf
        findfont failed Times
        findfont failed Palatino
        findfont found Bitstream Vera Serif, normal, normal 400, normal, 8.33
[this findfont report repeats many times]

Thanks.  Fixed.

Manuel Metz wrote:
> Hi Mike,
>
>   I just stumbled over this bug report (#2126188) on sourceforge. This 
> seems to appear in version 5471, committed by you.
>
> Manuel
>

-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

Hi Mike,

   I just stumbled over this bug report (#2126188) on sourceforge. This 
seems to appear in version 5471, committed by you.

Manuel

Paul Kienzle wrote:

> Also a linear perceptual scale would work better than HSV but I don't
> know of one off hand.

L*u*v* or its cylindrical-coordinate cousin L*t*theta* (or LCH_uv). "Choosing 
Color Palettes for Statistical Graphics" is a nice paper talking about an 
implementation in R (although they do seem to misname L*t*theta* as HCL, which 
officially is different):

   http://eeyore.ucdavis.edu/stat250/epub-wu-01_abd.pdf

For the "real" HCL, which also might be useful:

   http://mmis.doc.ic.ac.uk/mmir2005/CameraReadyMissaoui.pdf

The main problem with perceptual colorspaces is that they do not map neatly to 
the color gamut of the RGB or CMYK colorspaces of typical rendering devices.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco

Jae-Joon Lee wrote:
>> I believe you are looking for the scanline boolean algebra -- search
>> the antigrain demo page
>>
>>  http://www.antigrain.com/demo/index.html
>>
>> for scanline_boolean.cpp.  Of course, we would need to support the
>> other major backends too....
>>
>>     
>
> I'm not sure if scanline_boolean does what I want (but I have to admit
> that I haven't looked at its code carefully yet). Do you know if it is
> possible to stroke along the union of the two paths (this is what I
> want)? My impression is that scanline thing is for filling the path.
> Anyhow, I'll take a more look.
>   
You should probably be able to take the union of two stroked paths -- 
which is not a geometry package like lib2geom would do, but it should be 
good enough/fast enough.

Of course, any solution will have to work with all backends, not just Agg.
>   
>> This appears to be LGPL, so we will not be using it in the main distro.
>>
>>     
>
> Yes, it's LGPL.
> And I didn't mean to include it in mpl.
> Anyhow, I think I'll go with the first method for the moment.
>   
It sounds like this method should also be the most portable between 
backends.  I doubt efficiency is a concern, because there's a real upper 
limit on the number of these annotations before things become illegible.

Cheers,
Mike

-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

>
> Well merging is obviously better. I wrote YAArrow to support
> plain-vanilla annotations.  AFAIK, they are used nowhere else, so as
> long as we could come up with one arrow class that works with
> plain-vanilla and fancy annotations, that would be good.  But it may
> be easier said than done.  These annotation arrows are really helper
> classes that are instantiated by higher level functions (eg users most
> likely won't be creating them themselves) and since they all have the
> basic patch interface, I don't think having a proliferation of them is
> the worst thing in the world, though the ideal is to have as few
> classes as possible that serve as many cases as possible.
>
>

Thanks.
Yes, merging seems better to me too. And it seems that I can slightly
tweak the current interface of my class so that it get along well with
pre-existing classes.
I'll work on the merge and post the patch sometime soon.

>
> I believe you are looking for the scanline boolean algebra -- search
> the antigrain demo page
>
>  http://www.antigrain.com/demo/index.html
>
> for scanline_boolean.cpp.  Of course, we would need to support the
> other major backends too....
>

I'm not sure if scanline_boolean does what I want (but I have to admit
that I haven't looked at its code carefully yet). Do you know if it is
possible to stroke along the union of the two paths (this is what I
want)? My impression is that scanline thing is for filling the path.
Anyhow, I'll take a more look.

>
> This appears to be LGPL, so we will not be using it in the main distro.
>

Yes, it's LGPL.
And I didn't mean to include it in mpl.
Anyhow, I think I'll go with the first method for the moment.

Thanks,

-JJ

On Sep 23, 2008, at 8:29 PM, Tom Holroyd wrote:

> Repost; the list bounced my last attempt.
>
> On Fri, 2008-09-19 at 18:42 -0400, Tom Holroyd wrote:
>> On Thu, 2008-09-18 at 20:40 +0200, Jouni K. Seppänen wrote:
>>> I would prefer something like the following options:
>>>
>>>     fc={'orange': 20, 'white': None}
>>>     fc=[[20, 'orange'], [None, 'white']]
>>>     fc=ColorMixture('orange', 20, 'white') # where ColorMixture  
>>> is a fairly
>>>                                            # trivial class
>>
>> +1
>>
>> simpler, easier to read & write, less ad-hoc
>>
>> I'd go ahead and make ColorMixture a fancy class with __rmul__ and
>> __add__ methods to allow things like
>> 	orange = ColorMixture(255, 165, 0)
>> 	blue = ColorMixture(0, 0, 255)
>> 	mycolor = .7 * orange + .2 * blue

hsv mixing is much more useful.  Take a known color and you can imagine
what a darker/lighter or paler/deeper version would look like, such as
dark green or pale blue.  These are just value and saturation.  Even hue
can be imagined to some degree (bluish, greenish, etc.) to move one hue
toward another, but that is harder to imagine across the circle
(e.g, greenish purple or bluish yellow).

Rather than averaging it would be easier to move some percentage toward
the other color, such as blue, but hue 20% toward green.

This can probably be expressed in operations on a color mixture class
as above.

Also a linear perceptual scale would work better than HSV but I don't
know of one off hand.

- Paul

Hi,

Sounds fine, though I would note that about half of the code that was in
numerical_methods originally came from cbook, not mlab.  This code fits
equally well in mlab, so I don't have anything against putting it there.

Thanks for taking care of this - I have been busy with other things.

Cheers,
David



On Tue, 2008-09-23 at 13:24 -0500, John Hunter wrote:
> On Tue, Sep 16, 2008 at 3:26 AM, David M. Kaplan <Dav...@ir...> wrote:
> > Hi,
> >
> > I would just undo what I have done rather than putting a lot of moved
> > messages all over the place.  I personally find the mix of matlab and
> > non-matlab stuff in mlab confusing, but I will go with the group
> > consensus.
> 
> Since noone else had anything to add here, I moved all the
> numerical_methods methods back into mlab until we have a more
> comprehensive solution that is friendly to the existing codebase (one
> of my apps was just bitten by it...)
> 
> JDH
-- 
**********************************
David M. Kaplan
Charge de Recherche 1
Institut de Recherche pour le Developpement
Centre de Recherche Halieutique Mediterraneenne et Tropicale
av. Jean Monnet
B.P. 171
34203 Sete cedex
France

Phone: +33 (0)4 99 57 32 27
Fax: +33 (0)4 99 57 32 95
http://www.ur097.ird.fr/team/dkaplan/index.html
**********************************

Repost; the list bounced my last attempt.

On Fri, 2008-09-19 at 18:42 -0400, Tom Holroyd wrote:
> On Thu, 2008-09-18 at 20:40 +0200, Jouni K. Seppänen wrote:
> > I would prefer something like the following options:
> > 
> >     fc={'orange': 20, 'white': None}
> >     fc=[[20, 'orange'], [None, 'white']]
> >     fc=ColorMixture('orange', 20, 'white') # where ColorMixture is a fairly
> >                                            # trivial class
> 
> +1
> 
> simpler, easier to read & write, less ad-hoc
> 
> I'd go ahead and make ColorMixture a fancy class with __rmul__ and
> __add__ methods to allow things like
> 	orange = ColorMixture(255, 165, 0)
> 	blue = ColorMixture(0, 0, 255)
> 	mycolor = .7 * orange + .2 * blue
> 
> like,
> 
> class cm:
>   def __init__(self, r, g, b):
>     self.r = r
>     self.g = g
>     self.b = b
>   def __rmul__(self, a):
>     return cm(a * self.r, a * self.g, a * self.b)
>   def __add__(self, a):
>     return cm(a.r + self.r, a.g + self.g, a.b + self.b)
> 
-- 
Elephants can paint.
http://www.elephantart.com/catalog/thailand.php

In article 
<88e...@ma...>,
 "John Hunter" <jd...@gm...> wrote:

> On Thu, Sep 18, 2008 at 2:33 PM, Russell E. Owen <rowen@u.washington.edu> 
> wrote:
> > The versions of pytz and dateutil that are included with matplotlib
> > 0.98.3 are outdated....
> 
> Hey Russell, thanks for the head's up.
> 
> For our source installs, by default we install them only if they are
> not on the system, but you can configure this with setup.cfg to
> always, never or conditionally install them.
> 
> I have updated the mpl versions to the ones you point to above.

I just discovered that matplotlib 0.98.3 is not compatible with pytz 
2008c due to an unexpected change in pytz. The following fix works (I 
chucked it into __init__.py near the beginning).

# the following fix for compatibility with pytz 1.4.1 is from
# <http://www.mail-archive.com/pyt...@py.../msg07816.html>
import pytz
try:
    import pytz.zoneinfo
except ImportError:
    pytz.zoneinfo = pytz.tzinfo
    pytz.zoneinfo.UTC = pytz.UTC

-- Russell