matplotlib-users Mailing List for matplotlib (Page 1454)

>>>>> "matthew" == matthew arnison <ma...@ca...> writes:
 matthew> Hi, I am happily using matplotlib-0.50e. I tried eps
 matthew> output and it worked very nicely. The problem with plot
 matthew> lines not being clipped by a manual axis in the PS
 matthew> backend also seems to have been fixed.
Good to hear ..
 matthew> I have some feedback on the default tick
 matthew> behaviour. matplotlib seems to pick a number of ticks,
 matthew> and then divides through to get the tick values. This
 matthew> results in some ugly long tick labels, making it hard to
 matthew> quickly gauge the range between two points on a graph.
 matthew> E.g. if the y range of a plot is 1.927 to 1.948, then
 matthew> matplotlib puts ticks at (1.927, 1.931, 1.935, ...,
 matthew> 1.948)
I agree this is an important issue. It's also a difficult one. If
matplotlib just had to make a good choice for the axis limits and tick
values for a single plot, it wouldn't be too hard. What becomes
harder is to do this in the presence of interactivity. Once you allow
the user to pan and zoom, you have some other considerations. For
example, if the tick locations or the number of ticks/grids on the
axis move while you pan or zoom, that is visually disturbing. The
easiest way to optimize the tick locations is to have some flexibility
in choosing the number of ticks, but after the initial plot, this
number is set for the rest of the interactive session which makes it
harder.
So enough excuses! I agree that the current implementation is
suboptimal and will give it some more thought. Out of curiosity: do
the undersirable tick locs appear more frequently for you on an
initial plot or after interacting with the plot.
 matthew> Another slight niggle. If I set the axis range manually,
 matthew> then if a data point is exactly equal to the end of the
 matthew> axis range then it won't be plotted. 
This is a consequence of the way python and Numeric do ranges, and
doesn't really have anything to do with matplotlib. eg, the Numeric
function arange
 >>> from Numeric import *
 >>> arange(0.0, 1.0, 0.2)
 array([ 0. , 0.2, 0.4, 0.6, 0.8])
 >>> range(5)
 [0, 1, 2, 3, 4]
Ie, ignore the end point is the default behavior of python.
JDH

>>>>> "Jean-Baptiste" == Jean-Baptiste Cazier <Jea...@de...> writes:
 Jean-Baptiste> Hi ! I am using with delight the new object_picker
 Jean-Baptiste> tools as of version 0.42b It works fine but I can
 Jean-Baptiste> not find out how to draw the legend, labels, title,
 Jean-Baptiste> etc... Neither the ax (Subplot), nor the fig
 Jean-Baptiste> (ArtistPickerFigure) have those methods. How could
 Jean-Baptiste> I access them ?
First, I recommend upgrading the 0.50 series as there have been APi
changes that affect the object_picker code (the examples.object_picker
demo script is updated). Better to catch up sooner rather than later.
Second, I don't really understand your question. If you want to "draw
the legend, labels, ...", you simply call the draw method. All of
these things (Legend, Text, etc..) are derived from Artist, which
implements a "draw" method. so you can call
 legend.draw()
 label.draw()
and so on?
Then later you say "those methods" using the plural. I don't know
what you mean..... Could you elaborate, and perhaps provide some code
with comments showing where you are stuck?
Thanks,
JDH

>>>>> "Kuzminski," == Kuzminski, Stefan R <SKu...@fa...> writes:
 Kuzminski> Some notes on compiling GD backend for windows. 1)
 Kuzminski> _gdmodule.c needs to be modified in 2 places to
 Kuzminski> compile on windows
Hi Stephan,
I've been following your instructions on building gdmodule and I've
gotten pretty far. I have a couple of questions for you.
Did you use the prebuilt gd (not gdmodule) or the dll supplied at the
web site. I built it myself, and when I try to build gdmodule, I get
errors like 
_gdmodule.obj : error LNK2001: unresolved external symbol _gdFontGiantRep
_gdmodule.obj : error LNK2001: unresolved external symbol _gdFontLargeRep
The export to these symbols are dependent on the following
preprocessor options (from gd.h)
#ifdef BGDWIN32
#define BGD_EXPORT_DATA_IMPL __declspec(dllexport)
#else
#ifdef WIN32
#define BGD_EXPORT_DATA_IMPL __declspec(dllimport)
#else
/* 2.0.20: should be nothing at all */
#define BGD_EXPORT_DATA_IMPL
#endif /* WIN32 */
#endif /* BGDWIN32 */
In gdfontl.c, there is some code
 BGD_EXPORT_DATA_IMPL gdFontPtr gdFontLarge = &gdFontLargeRep;
I set BGDWIN32 option when building the gd DLL, but I still don't seem
to get _gdFontLargeRep exported to the gd.dll. For example, if I grep
the dll for gdFontLarge, I see that symbol but not gdFontLargeRep.
Ditto for the prebuilt bgd.dll. 
Did you encounter this problem and do you have any insights here?
Thanks,
John Hunter

Hi !
I am using with delight the new object_picker tools as of version 0.42b
It works fine but I can not find out how to draw the legend, labels, title,=
 etc...
Neither the ax (Subplot), nor the fig (ArtistPickerFigure) have those metho=
ds.
How could I access them ?
Thanks
Kve=F0ja
Jean-Baptiste
--=20
-----------------------------
Jea...@de...
Department of Statistics
deCODE genetics Sturlugata,8
570 2993 101 Reykjav=EDk

Hi again,
I'm having more trouble with matplotlib ticks today. I wrote a little demo 
script that illustrates some of the problems:
...
#!/usr/bin/python
from matplotlib.matlab import *
xx = arange(0.002, 0.0101, 0.001)
print xx
# an instance of yy = rand(9), so all values are between 0 and 1
yy = [ 5.94692328e-04, 1.62328354e-01, 7.56822907e-01, 2.28180047e-02,
 3.23820274e-01, 3.93120900e-01, 6.41332889e-01, 1.22474302e-02,
 5.03485402e-01]
subplot(211)
plot(xx, yy)
subplot(212)
plot(xx, yy)
autoaxis = axis()
print autoaxis
axis(autoaxis)
show()
...
* the x axis includes *two* 0.004 and *two* 0.008; this really worried me 
until I realised it was a cosmetic rounding / significant figures issue, 
however it's bad enough to be seriously misleading. I think the actual 
tick values are something like 0.0036 and 0.0044 but are both rounded to 
0.004.
* the data points lie *between* the x axis ticks, this is a side-effect of 
the above
* the poor choice of tick positions on the y axis -- they should be 
in round numbers like 0.2, 0.4, etc. The most significant varying figure 
should be a multiple of 1, 2, or 5.
* the tick labels should all have the same number of significant figures, 
e.g. 0.00, 0.15, 0.30, 0.45, 0.60, ... for the y axis
* after manually setting the axis (lower subplot), the last point is not 
plotted
I hope you find this feedback useful. I had a go at fixing it in axis.py,
but it's a) fiddly and b) I don't quite understand which part has
precendence when the axis changes during a zoom or pan. Getting the ticks
right depends on the correct bounds for the axis and the choice of
numticks. I noticed you have logic to clean up the bounds (vmin and vmax)
but not the ticklocs.
Thanks for matplotlib.
Cheers,
Matthew.

Hi john,
 After the refactoring you did for version 0.5 I am having a funny 
behavior in a plot embedded in wx:
the frame appers with the size of the toolbar, but if I resize the frame 
the plot is there and is not resizable, it justs stays the same no 
matter the size of the canvas(frame?).
I've made the changes to my original module acording to the revised 
'embedding_in_wx.py' example, which runs fine.
Here is my ploting module:
===============================================
import matplotlib
matplotlib.use('WX')
 
from matplotlib.backends.backend_wx import Toolbar, FigureManager, 
FigureCanvasWx
from matplotlib.figure import Figure
from matplotlib.axes import Subplot
import Numeric as numpy
from RandomArray import *
from MLab import *
from wxPython.wx import *
def create(parent):
 return PlotFigure(parent)
class PlotFigure(wxFrame):
 def __init__(self,parent):
 wxFrame.__init__(self,None,-1,"Results")
 self.fig = Figure((5,4), 75)
 self.canvas = FigureCanvasWx(self,-1,self.fig)
 self.toolbar = Toolbar(self.canvas)
 self.toolbar.Realize()
 # On Windows, default frame size behaviour is incorrect
 # you don't need this under Linux
 tw, th = self.toolbar.GetSizeTuple()
 fw, fh = self.canvas.GetSizeTuple()
 self.toolbar.SetSize(wxSize(fw, th))
 
 # Create a figure manager to manage things
 self.figmgr = FigureManager(self.canvas, 1, self)
 
 # Now put all into a sizer
 sizer = wxBoxSizer(wxVERTICAL)
 # This way of adding to sizer prevents resizing
 #sizer.Add(self.fig, 0, wxLEFT|wxTOP)
 
 # This way of adding to sizer allows resizing
 sizer.Add(self.toolbar, 1, wxLEFT|wxTOP|wxGROW)
 
 # Best to allow the toolbar to resize!
 sizer.Add(self.toolbar, 0, wxGROW)
 self.SetSizer(sizer)
 self.Fit()
 
 def plotLine(self,y, leg, tit='Time Series'):
 """
 Generate line plots
 """
 # Use ths line if using a toolbar
 a = self.figmgr.add_subplot(211)
 
 # Or this one if there is no toolbar
 #a = Subplot(self.fig, 211)
 styles = ('-', '--', ':', '.', 'o', '^', 'v', '<', '>', 's', '+')
 colors = ('b', 'g', 'r', 'c', 'm', 'y', 'k')
 s = 0
 c = 0
 for i in range(numpy.shape(y)[0]):
 if s > len(styles)-1:
 s = 0
 if c > len(colors)-1:
 c = 0
 style = styles[s]
 color = colors[c]
 a.plot(y[i,:],style+color) # plot each line with a different 
combination of color and style
 if c == len(colors)-1:
 s += 1
 c += 1
 a.set_title(tit)
 a.legend(leg)
 self.toolbar.update()
===============================================
which I call like this: (I import the plotting module as PF)
self.fig = PF.create(None)
 leg = self.modict["slabels"]
 tit = 'Time Series and Final State'
 self.fig.plotLine(results, leg, tit)
 
 self.fig.plotBar(results, leg)
 
 self.fig.Show()

>>>>> "Engelsma," == Engelsma, Dave <D.E...@La...> writes:
Hi David, please post questions directly to the matplotlib-users list.
 Engelsma> Hello -- Is it possible to save figures (I'm using the
 Engelsma> .eps feature) without having to show the plots/charts
 Engelsma> on the user's screen? I'd like to be able to save the
 Engelsma> figures to disk without showing them on the
 Engelsma> screen. Currently, it seems that the figures will not
 Engelsma> save to disk, unless I issue the show() command after
 Engelsma> the savefig. I'd like to eliminate having to call
 Engelsma> show().
From your email, it sounds like you are using the GTK backend and
saving figures with the ps backend. If you just want to save the
figures as PS and not show them to the screen, use the ps backend
directly as described on
http://matplotlib.sourceforge.net/backends.html
 > python myscript.py -dPS
or
 import matplotlib
 matplotlib.use('PS')
 from matplotlib.matlab import *
 t = arange(0.0, 3.0, 0.01)
 for i in range(1,10):
 figure(1)
 s = sin(2*pi*i*t)
 plot(t,s)
 savefig('plot%02d' % i)
 close(1)
In either case, there is no need to call 'show'. If you want to make
multiple figures, you need to clear them between each save, as I did
here by closing the figure.
If you really want to use the GTK backend to make PS figures without
showing the figure, there are some things that will enable this, but I
don't see any reasons to go this route. Let me know.
JDH

Hi,
I am happily using matplotlib-0.50e. I tried eps output and it worked very 
nicely. The problem with plot lines not being clipped by a manual axis in 
the PS backend also seems to have been fixed.
...
I have some feedback on the default tick behaviour. matplotlib seems to
pick a number of ticks, and then divides through to get the tick values.
This results in some ugly long tick labels, making it hard to quickly
gauge the range between two points on a graph.
E.g. if the y range of a plot is 1.927 to 1.948, then matplotlib puts
ticks at (1.927, 1.931, 1.935, ..., 1.948)
I think it would be better (and closer to the plotting behaviour of 
other software) if matplotlib picked ticks that were "round", even if that 
means the endpoints of the axes are slightly outside the range of the 
data.
So the ticks for the example above would become:
(1.925, 1.930, 1.935, ..., 1.950)
I guess this would be more complicated to implement than the current 
algorithm, but it would make life easier when interpreting graphs from 
matplotlib!
...
Another slight niggle. If I set the axis range manually, then if a data
point is exactly equal to the end of the axis range then it won't be 
plotted. Making the axis range slightly longer is clumsy. This also 
violates the principle of least surprise, because automatic axis ranges do 
not have this behaviour. A simple way to see the problem is to compare the 
output of the two plots below:
>>> xvals = arange(0.0, 1.0, 0.1)
>>> plot(xvals, [sin(x) for x in xvals])
[<matplotlib.lines.Line2D instance at 0x93fa844>]
>>> show()
>>> plot(xvals, [sin(x) for x in xvals])
[<matplotlib.lines.Line2D instance at 0x9249d2c>]
>>> autoaxis = axis()
>>> autoaxis
[0.0, 0.90000000000000002, 0.0, 0.80000000000000004]
>>> axis(autoaxis)
>>> show()
Presumably the logic for picking the datapoints to plot should use <= not
<.
Cheers,
Matthew.

>>>>> "Flavio" == Flavio Codeco Coelho <fcc...@ci...> writes:
 Flavio> Hi John, What do you think of adding a button to the
 Flavio> standara toolbar allowing the plotted data to be save in
 Flavio> CSV format?
My initial thought is this would be hard to do well. Axes can contain
an arbitrary combination of lines, text and patches (of which there
are many types). The lines can be different lengths. The plot can
contain an arbitrary number of axes. How to export these in a
meaningful way so that the code on the other side can load and use it
is not clear to me.
Perhaps you should write a function 
 def line_to_csv(l, fname):
 # export the x and y line data to csv
likewise you may want
 def hist_output_to_csv(args) 
and call these functions from your python script as necessary. Take a
look at the file examples/object_picker.py (requires gtk backend),
where you can select an individual line with the mouse. It wouldn't
be hard to plug an export to csv function together with this picker
functionality.
But it seems that for the most part these are specialized use cases
that may be better handled on your end by writing your own functions
and subclassing the NavigationToolbar to add your own buttons (easy to
do, I can provide some example code if you like) because I suspect
there would be little agreement about what export functionality is
desirable.
 Flavio> Talking about plots, I am writing a module to calculate
 Flavio> Kernel density estimates (a kind of continuous histogram)
 Flavio> would you be interested in adding it to matplotlib?
Please send me the module code and some demo script and I'll take a
look. I'm happy to include useful numerical and statistical code in
matplotlib.mlab or wherever appropriate. Maybe a few online
references where I can read about kernel density estimates too...
Thanks!
JDH

>>>>> "Nils" == Nils Wagner <nw...@me...> writes:
 Nils> ~/cvs/matplotlib/htdocs/screenshots> /usr/bin/python
 Nils> makeshots.py Making screenshot simple_plot.py Traceback
 Nils> (most recent call last): File "simple_plot.py", line 1, in ?
 Nils> from matplotlib.matlab import * File
 Nils> "/usr/local/lib/python2.1/site-packages/matplotlib/matlab.py",
 Nils> line 109, in ? from mlab import * File
 Nils> "/usr/local/lib/python2.1/site-packages/matplotlib/mlab.py",
 Nils> line 147 else: numFreqs = NFFT//2+1 ^ SyntaxError: invalid
 Nils> syntax
matplotlib requires python2.2, which supports 
 from __future__ import division
That line should be the on or near the first code line of
matplotlib/mlab.py. When this is imported, the integer division //
operator is defined.
See what's new in python2.2
http://www.python.org/doc/2.2.3/whatsnew/node7.html
I'm surprised you didn't get an error on the call to
from __future__ import division.
JDH

Nils Wagner wrote:
> ~/cvs/matplotlib/htdocs/screenshots> /usr/bin/python makeshots.py
> Making screenshot simple_plot.py
> Traceback (most recent call last):
> File "simple_plot.py", line 1, in ?
> from matplotlib.matlab import *
> File "/usr/local/lib/python2.1/site-packages/matplotlib/matlab.py",
> line 109, in ?
> from mlab import *
> File "/usr/local/lib/python2.1/site-packages/matplotlib/mlab.py", line
> 147
> else: numFreqs = NFFT//2+1
> ^
> SyntaxError: invalid syntax
> 
Not a syntax error any more in Python 2.3.
<quote>
In [1]: 3//2
Out[1]: 1
In [2]: 3/2
Out[2]: 1
In [3]: from __future__ import division
In [4]: 3//2
Out[4]: 1
In [5]: 3/2
Out[5]: 1.5
</quote>
Regards,
ST
--

~/cvs/matplotlib/htdocs/screenshots> /usr/bin/python makeshots.py
Making screenshot simple_plot.py
Traceback (most recent call last):
 File "simple_plot.py", line 1, in ?
 from matplotlib.matlab import *
 File "/usr/local/lib/python2.1/site-packages/matplotlib/matlab.py",
line 109, in ?
 from mlab import *
 File "/usr/local/lib/python2.1/site-packages/matplotlib/mlab.py", line
147
 else: numFreqs = NFFT//2+1
 ^
SyntaxError: invalid syntax

John Hunter wrote:
> http://matplotlib.sourceforge.net
> 	
> What's new in matplotlib 0.42
> 
> EPS output from PS backend
> 
> Just add an eps extension
> 
> PS and EPS save from GTK and WX backends with bugs fixed
> 
[snipped]
Thanks very much. I did an upgrade via CVS and the eps output works fine.
A slight glitch though. I think John has changed the AFMPATH
environmental variable to MATPLOTLIBDATA (which is a more appropriate
name) so people installing matplotlib in non-default places will have to
set it instead.
Regards,
ST
--

Hi John,
What do you think of adding a button to the standara toolbar allowing 
the plotted data to be save in CSV format?
It woul be very convenient when the user wants to take the data to 
another plotting program, and the plot is a good place to save because 
the data is already sorted out. In some types of plots such as the 
histogram, the plot woul allow for saving the actual data that 
represents the histogram (such as class intervals or mid points and 
frequencies) instead of the raw data.
What do you think?
Talking about plots, I am writing a module to calculate Kernel density 
estimates (a kind of continuous histogram) would you be interested in 
adding it to matplotlib?
cheers,
Flavio

John Hunter wrote:
> http://matplotlib.sourceforge.net
> 	
> What's new in matplotlib 0.42
> 
> EPS output from PS backend
> 
> Just add an eps extension
> 
> PS and EPS save from GTK and WX backends with bugs fixed
> 
[snipped]
Thanks very much. I did an upgrade via CVS and the eps output works fine.
A slight glitch though. I think John has changed the AFMPATH 
environmental variable to MATPLOTLIBDATA (which is a more appropriate 
name) so people installing matplotlib in non-default places will have to 
set it instead.
Regards,
ST
--

>>>>> "LUK" == LUK ShunTim <shu...@po...> writes:
 LUK> A slight glitch though. I think John has changed the AFMPATH
 LUK> environmental variable to MATPLOTLIBDATA (which is a more
 LUK> appropriate name) so people installing matplotlib in
 LUK> non-default places will have to set it instead.
ps backend is setup to use both, the idea that you may have some AFM
files independent of matplotlib, and some that ship with matplotlib.
The MATPLOTLIBDATA is indeed for people installing in nonstandard
places. But if AFMPATH is not working for you, I need to know since
this is a bug.
Thanks!
John Hunter

First of all, thanks for matplotlib. 
This is far and away the best python plotting package I have come
across.
I've attached a patch for axes.py that allows 'stacked bar charts' to be
produced using the bar function.
The idea with a stacked bar chart is that you have several series of
data that naturally stack up on top of each other. You can achieve
this effect with a small fix to the bar function. All you have to do is
to specify the offsets along the y-axis for each value being plotted (by
default these offsets would be all zero, equivalent to the existing
function).
See stacked_bar.py for an example of how you might use this.
The patch adds an extra keyword arguement , yoff, to plot.
This allows you to supply a list of offsets for the values to be
plotted.
Using this you can 'stack' up results by using successive calls to bar,
so long as you are careful to get the offsets right.
John

S=E6ll !
I am trying to plot very small number for the Y-axis on semilogy but they d=
o not appear at all unless one of the value is higher
Moreover the labels on the Y axis become 0 below 0.001
>> semilogy([1.0, 2.3, 3.3],[9.4e-05, 9.4e-05, 9.4e-05]) <-- does not =
work
[<matplotlib.lines.Line2D instance at 0x935255c>]
>> semilogy([1.0, 2.3, 3.3],[9.4e-04, 9.4e-05, 9.4e-05])	<--- work
[<matplotlib.lines.Line2D instance at 0x940e964>]
Should I use a specific "long" definition of my floating number ?
Takk
Jean-Baptiste
--=20
-----------------------------
Jea...@de...
Department of Statistics
deCODE genetics Sturlugata,8
570 2993 101 Reykjav=EDk

I've spent the last couple of days refactoring the matplotlib
backends, fixing bugs and adding some functionality. Here's a
synopsis of what's new. I encourage everyone to try it out so
complaints and bugs can be handled before the major release.
** Note there are some API changes so please read about this below **
** Note, GD users, GD rendering is significantly improved in my
 opinion. However, some of new functionality requires a recent
 version of gd and a patch of the latest gdmodule, see below **
What's new in matplotlib 0.50e
 GD supports clipping and antialiased line drawing. The line object
 has a new 'antialiased' property, that if true, the backend will
 render the line antialiased if supported. **You will need to
 upgrade to gd-2.0.15 or later and gdmodule-0.51. You will also need
 to replace _gdmodule.c with the code as described at
 http://matplotlib.sourceforge.net/backends.html#GD.
wild and wonderful bar charts
 You can provide an optional argument 'bottom' to the bar command to
 determine where the bottom of each bar is, default 0 for all. This
 enables stacked bar plots and candelstick plots --
 examples/bar_stacked.py. Thanks to David Moore and John Gill for
 suggestions and code.
Bugfixes (by backend)
 * All : the yticks on the right hand side were placed incorrectly,
 now fixed
 * All : ticklabels now make a more intelligent choice about how
 many significant digits to display
 * GD : An int truncation bug was causing the dotted lines to
 disappear
 * GD and GTK : Fixed line width to scale with DPI
 * GD : Fixed small text layout bug
 * GD : Fixed the constant for GD which maps pixels per inch - this
 should give better agreement with other backends witht he
 relative sizes of objects
 * GTK : Dash spacing was not properly scaling with DPI
Figure backend refactored
 The figure functionality was split into a backend independent
 component Figure and a backend dependent component
 FigureCanvasBase. This completes the transition to a totally
 abstract figure interface and improves the ability the switch
 backends. See the file
 http://matplotlib.sourceforge.net/API_CHANGES that comes with the
 src distro for information on migrating applications to the new API.
 All the backend specific examples have been updated to the new API.
Enjoy,
John Hunter

>>>>> "Nils" == Nils Wagner <nw...@me...> writes:
 Nils> ~/cvs/matplotlib/htdocs> /usr/bin/python process_docs.py
 Nils> Converting matplotlib.afm.html to template Converting
 Nils> matplotlib.artist.html to template Converting
 Nils> matplotlib.axes.html to template Converting
 Nils> matplotlib.axis.html to template Converting
 Nils> matplotlib.backend_bases.html to template Converting
 Nils> matplotlib.backends.backend_gd.html to template Traceback
 Nils> (most recent call last): File "process_docs.py", line 28, in
 Nils> ? s = file('../docs/' + fname).read() IOError: [Errno 2] No
 Nils> such file or directory:
 Nils> '../docs/matplotlib.backends.backend_gd.html'
Are you aware that the htdocs build the matplotlib web page, which can
be found at http://matplotlib.sourceforge.net. In other words, unless
you want to edit the web page docs, there is not much need to build
them yourself since they are available online.
If all you want is the pydoc documentation, this is online at
 http://matplotlib.sourceforge.net/matlab_commands.html and
 http://matplotlib.sourceforge.net/classdocs.html
If you really want to build the html docs yourself, from your error
message it looks like you do not have gd module properly installed.
Can you do this?
 >> import matplotlib
 >> matplotlib.use('GD')
 >> from matplotlib.matlab import *
If not, then GD is not installed properly and you need to follow the
install instructions at
http://matplotlib.sourceforge.net/backends.html#GD.
You will need to have all backends working before you can build the
htdocs.
One last word of warning, since you are building htdocs, you are using
CVS, right? CVS has undergone a lot of changes in the last 2 days,
particularly the GD backend, and if you have the latest CVS version,
GD won't run properly without a patched gdmodule. Stay tuned for
another post with all the required info for using the latest CVS.
JDH

~/cvs/matplotlib/htdocs> /usr/bin/python process_docs.py
 Converting matplotlib.afm.html to template
 Converting matplotlib.artist.html to template
 Converting matplotlib.axes.html to template
 Converting matplotlib.axis.html to template
 Converting matplotlib.backend_bases.html to template
 Converting matplotlib.backends.backend_gd.html to template
Traceback (most recent call last):
 File "process_docs.py", line 28, in ?
 s = file('../docs/' + fname).read()
IOError: [Errno 2] No such file or directory:
'../docs/matplotlib.backends.backend_gd.html'

John Hunter wrote:
>>>>>>"LUK" == LUK ShunTim <shu...@po...> writes:
> 
> 
> LUK> Yes. I did "python log_demo.py", got the gtk GUI and clicked
> LUK> on the "save" icon to produce the eps file. So it is as you
> LUK> said, it comes from the GUI backend. No warning when I did
> LUK> "python log_demo.py -dPS"
> 
> OK, now we at least know where the problem is. I don't get such an
> error message on my system (rhl9, pygtk-2.0.0). What platform are you
> on, and what versions of GTK and pygtk are you running?
> 
> JDH
> 
> 
> 
W2K, Enthought python 2.3, pygtk 2.0, gtk 2.0
Regards,
ST

>>>>> "LUK" == LUK ShunTim <shu...@po...> writes:
 LUK> Yes. I did "python log_demo.py", got the gtk GUI and clicked
 LUK> on the "save" icon to produce the eps file. So it is as you
 LUK> said, it comes from the GUI backend. No warning when I did
 LUK> "python log_demo.py -dPS"
OK, now we at least know where the problem is. I don't get such an
error message on my system (rhl9, pygtk-2.0.0). What platform are you
on, and what versions of GTK and pygtk are you running?
JDH

John Hunter wrote:
>>>>>>"LUK" == LUK ShunTim <shu...@po...> writes:
> 
> LUK> ** (log_demo.py:1264): WARNING **: Couldn't load font "Times
> LUK> 9.599609375" falling back to "Sans 9.599609375"
> 
> LUK> CVS.
> 
> Are you sure you are getting this message from the PS backend??? This
> looks more like a message coming from one of the GUI backends. I
> don't generate any error messages like this in matplotlib.
> 
> With a fresh cvs checkout:
> 
> hunter:~/tmp/matplotlib> grep -ri 'falling back to' .
> 
> turns up nothing.
> 
> JDH
> 
> 
> 
> 
Yes. I did "python log_demo.py", got the gtk GUI and clicked on the "save" icon 
to produce the eps file. So it is as you said, it comes from the GUI backend. No 
warning when I did "python log_demo.py -dPS"
Regards,
ST
--

>>>>> "LUK" == LUK ShunTim <shu...@po...> writes:
 LUK> ** (log_demo.py:1264): WARNING **: Couldn't load font "Times
 LUK> 9.599609375" falling back to "Sans 9.599609375"
 LUK> CVS.
Are you sure you are getting this message from the PS backend??? This
looks more like a message coming from one of the GUI backends. I
don't generate any error messages like this in matplotlib.
With a fresh cvs checkout:
hunter:~/tmp/matplotlib> grep -ri 'falling back to' .
turns up nothing.
JDH