matplotlib-users Mailing List for matplotlib

Hi!

I'm using matplotlib and pygtk to write a viewer for multiple sequence 
alignments. (Big matrices (~100x1000) of characters, usually colored by 
cell according to chemical properties). Now I've run into trouble since 
the rendering of the actual characters is very slow. I have included a 
small example that illustrates this. Set SHOW_LETTERS = False to see the 
change in rendering speed. The difference is even greater when using 
real data, so I would very much appreciate suggestions as to how I could 
improve it.

My strategy:
I create an image with the same dimension as the msa, and where each 
pixel is colored according to properties of the corresponding character 
in the msa. I plot this in the background of the figure using imshow(). 
At each redraw (refresh, resize, zoom...) I determine the size that each 
image pixel occupies at the current canvas size, and pick a font where 
one letter will fit inside this square. Then I put the corresponding msa 
  letter into this square using text()/add_artist().

Would it be possible to use only one Text instance that would hold all 
letters, and somehow stretch that to the desired size? If so, could I 
expect better performance?

Does anyone have a better idea?

Thanks for an awesome plotting package!
/Joel Hedlund

Le lundi 25 d=E9cembre 2006 16:00, Allan Noriel Estrella a =E9crit=A0:
> Has anyone tried freezing matplotlib embedded in a wx app (using py2ece,
> cx_freeze or pyinstaller)? The setup.py in the FAQ seems to be outdated. I
> want to freeze the embedding_in_wx.py in the examples. Do you have any
> suggestions or cookbook steps that I can follow?

it looks there were no answer to your question!

I tried too the FAQ=20
http://matplotlib.sourceforge.net/faq.html#PY2EXE

and it does not work at least with my enthough installation directories see=
ms=20
to be very different from the one suggested.

I also tried http://www.py2exe.org/index.cgi/MatPlotLib without success

I tried the simpelst thing=20

from pylab import *
plot([1,2,3])
show()

no chance!
I don't know if someone could help, is there a better backend for freezing,=
=20
maybe wxpython?

Someone already succeded with a recent matplotlib ?
I'm using 0.87.3 (on windows)

> I think that it was also connected with very slow rendering.

I second that. Rendering is very slow when this occurs.

A workaround is to slice the image and just plot the visible pixels, and
then to use the 'extent' keyword argument to position the slice on the
axis, e.g:

imagesc(img[a:b,ymin:ymax,:], extent=(a,b,ymin,ymax), aspect='auto')

/Joel

Darren Dale wrote:
> Hi Joel,
> 
> On Thursday 01 February 2007 11:09:11 am Joel Hedlund wrote:
>> I believe I've found a bug in matplotlib which manifests after
>> imshow(img, aspect='auto') when only a small portion of the image is
>> displayed, e.g: when (xmax-xmin) << img.shape[1]. The effect of the bug
>> is that the transparency for the entire image seems to vary, seemingly
>> as a periodic funtion of (xmax-xmin). Explicitly setting the alpha
>> channel for each pixel has no effect.
>>
>> The attached script generates a random image of a certain size, and
>> plots it in four different subplots. The only thing that differs between
>> the subplots are slight variations in x_max. The four subplots are labeled:
>>
>> 1) The background image is visible.
>> 2) The background image is not visible!
>> 3) The background image is faded!
>> 4) The background image is again visible!
>>
>> which reflects the actual result on my system. As the subplots are
>> scaled (for example by resizing the window), the intensity then varies
>> in a periodic manner in each of the subplots.
>>
>> The expected result is of course that the background should be fully
>> visible in all subplots.
> 
> I can verify this behavior, more or less. I observe that the figure.dpi rc 
> setting influences the results (I tried 86.23 and 200).

This sounds like the same bug that was noted a few months ago, in which 
  repeated zooming to a very small part of the image ends up washing out 
the color entirely.  I think that it was also connected with very slow 
rendering.

Eric

Hi,

I am having some difficulties understanding the following matplotlib  
behavior.
The script below draws two plots and then updates each one with new  
data. The
imshow() command is used to set the initial data. The data is then  
updated with
the set_data() method of the return object from imshow(). The second  
plot
works fine, however, the first plot does not update itself after the  
set_data() command
and subsequent draw() command. I am baffled as to the reason for this  
and was wondering
what the correct behavior should be.

I am using matplotlib version '0.87.7', numpy version '1.0' and  
python version '2.4.2'.

Cheers

The script.

>
> import pylab, numpy
>
> pylab.ion()
>
> ## make figure 0, works fine
>
> fig0 = pylab.figure()
> pylab.title('data0')
> image0 = pylab.imshow(numpy.zeros((2,2), 'd'))
> pylab.colorbar()
> pylab.draw()
> raw_input('fig 0')
>
> ## make figure 1, works fine
>
> fig1 = pylab.figure()
> pylab.title('data1')
> image1 = pylab.imshow(numpy.zeros((2,2), 'd'))
> pylab.colorbar()
> pylab.draw()
> raw_input('fig 1')
>
> ## redraw figure 0 with new data, this figure does not update itself
>
> newdata = numpy.array(((0.,1.),(2.,3.)))
> pylab.figure(fig0.number)
> image0.set_data(newdata)
> pylab.clim(vmax=3, vmin=0)
> pylab.draw()
> raw_input('fig 0')
>
> ## redraw figure 1 with new data, works fine
>
> pylab.figure(fig1.number)
> image1.set_data(newdata)
> pylab.clim(vmax=3, vmin=0)
> pylab.draw()
> raw_input('fig 1')


--
Daniel Wheeler

Hello,

I tried to use some affine transformations, but it didn't match to get it works.
I use matplotlib 0.87.5 with python 2.4.3 and Numeric 24.2 on winXP.

I tried for example :
plot([1,0,1],[0,1,0], transform = matplotlib.transforms.Affine(0,1,1,0,0,0))

Then I got :
Traceback (most recent call last):
  File "<input>", line 1, in ?
  File "C:\Python24\lib\site-packages\matplotlib\pylab.py", line 2019, in plot
    ret =  gca().plot(*args, **kwargs)
  File "C:\Python24\lib\site-packages\matplotlib\axes.py", line 2124, in plot
    self.add_line(line)
  File "C:\Python24\lib\site-packages\matplotlib\axes.py", line 879, in add_line
    xys = self._get_verts_in_data_coords(
  File "C:\Python24\lib\site-packages\matplotlib\axes.py", line 934, in _get_verts_in_data_coords
    xys = trans.numerix_xy(asarray(xys))
ValueError: Domain error on Transformation::numerix_xy
>>> plot([1,0,1],[0,1,0], transform = matplotlib.transforms.Affine(1,0,0,1,0,0))
Traceback (most recent call last):
  File "<input>", line 1, in ?
  File "C:\Python24\lib\site-packages\matplotlib\pylab.py", line 2019, in plot
    ret =  gca().plot(*args, **kwargs)
  File "C:\Python24\lib\site-packages\matplotlib\axes.py", line 2124, in plot
    self.add_line(line)
  File "C:\Python24\lib\site-packages\matplotlib\axes.py", line 879, in add_line
    xys = self._get_verts_in_data_coords(
  File "C:\Python24\lib\site-packages\matplotlib\axes.py", line 934, in _get_verts_in_data_coords
    xys = trans.numerix_xy(asarray(xys))
ValueError: Domain error on Transformation::numerix_xy

Thanks a lot,

Nicolas
 
 		
---------------------------------
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Hi Joel,

On Thursday 01 February 2007 11:09:11 am Joel Hedlund wrote:
> I believe I've found a bug in matplotlib which manifests after
> imshow(img, aspect='auto') when only a small portion of the image is
> displayed, e.g: when (xmax-xmin) << img.shape[1]. The effect of the bug
> is that the transparency for the entire image seems to vary, seemingly
> as a periodic funtion of (xmax-xmin). Explicitly setting the alpha
> channel for each pixel has no effect.
>
> The attached script generates a random image of a certain size, and
> plots it in four different subplots. The only thing that differs between
> the subplots are slight variations in x_max. The four subplots are labeled:
>
> 1) The background image is visible.
> 2) The background image is not visible!
> 3) The background image is faded!
> 4) The background image is again visible!
>
> which reflects the actual result on my system. As the subplots are
> scaled (for example by resizing the window), the intensity then varies
> in a periodic manner in each of the subplots.
>
> The expected result is of course that the background should be fully
> visible in all subplots.

I can verify this behavior, more or less. I observe that the figure.dpi rc 
setting influences the results (I tried 86.23 and 200).

I,
I have a problem with showing plot. When I run this code:

figure(1)
semilogx(data[:,0],data[:,1])
savefig('try.png')
show()


It save the plot properly, but it doesn't show it. I tried to run it
with "--verbose-helpful" and this is the output:


matplotlib data path
/usr/local/lib/python2.4/site-packages/matplotlib/mpl-data
$HOME=/users/caronna
CONFIGDIR=/users/caronna/.matplotlib
loaded rc file
/usr/local/lib/python2.4/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 0.87.7
verbose.level helpful
interactive is False
platform is linux2
numerix numpy 1.0.1
font search path
['/usr/local/lib/python2.4/site-packages/matplotlib/mpl-data']
loaded ttfcache file /users/caronna/.matplotlib/ttffont.cache
backend Agg version v2.2

Does anyone know what's the problem?

Thanks,
Chiara

Hi!

I believe I've found a bug in matplotlib which manifests after=20
imshow(img, aspect=3D'auto') when only a small portion of the image is=20
displayed, e.g: when (xmax-xmin) << img.shape[1]. The effect of the bug=20
is that the transparency for the entire image seems to vary, seemingly=20
as a periodic funtion of (xmax-xmin). Explicitly setting the alpha=20
channel for each pixel has no effect.

The attached script generates a random image of a certain size, and=20
plots it in four different subplots. The only thing that differs between=20
the subplots are slight variations in x_max. The four subplots are labele=
d:

1) The background image is visible.
2) The background image is not visible!
3) The background image is faded!
4) The background image is again visible!

which reflects the actual result on my system. As the subplots are=20
scaled (for example by resizing the window), the intensity then varies=20
in a periodic manner in each of the subplots.

The expected result is of course that the background should be fully=20
visible in all subplots.

Additional details:

$ python test.py --verbose-helpful
matplotlib data path /usr/lib/python2.4/site-packages/matplotlib/mpl-data
$HOME=3D/home/bioinfo/yohell
CONFIGDIR=3D/home/bioinfo/yohell/.matplotlib
loaded rc file=20
/usr/lib/python2.4/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 0.87.7
verbose.level helpful
interactive is False
platform is linux2
numerix numpy 1.0
font search path ['/usr/lib/python2.4/site-packages/matplotlib/mpl-data']
loaded ttfcache file /home/bioinfo/yohell/.matplotlib/ttffont.cache
backend WXAgg version 2.6.1.2pre

In this example I used the WXAgg backend, but GTKAgg shows the same=20
results. I've also reproduced this bug on a WinXP machine.

Thanks for an excellent plotting package!
/Joel Hedlund
Link=F6ping University

Hi all,

I want to use imshow to plot an array of floats using
interpolation='nearest' so that every gridbox has a distinct color. Also I
want to limit the number of colors to a rather small number, e.g. 10. The
problem is that the tick labels are not at the edge of each color in the
colorbar, but somewhere in between.

An example is the trunk/matplotlib/examples/poormans_contour.py which does
not work in my case.

from pylab import *


delta = 0.01
x = arange(-3.0, 3.0, delta)
y = arange(-3.0, 3.0, delta)
X,Y = meshgrid(x, y)
Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = Z2 - Z1 # difference of Gaussians

cmap = cm.get_cmap('jet', 10)    # 10 discrete colors

im = imshow(Z, cmap=cmap, interpolation='bilinear')
axis('off')
colorbar()
#savefig('test')
show()

Is there a solution?


Ciao Claas

Hi Derek,
I forgot to mention: you can pass throught your problem by using a masked=20
array instead of a simple array, and it should work fine, the 'default'=20
parameter is here to fill missing value by -1.e20, then these directions wi=
ll=20
be dropped if your speed_classes not include that missing value (generally =
we=20
compute on positives speeds).

Le Jeudi 01 F=E9vrier 2007 13:17, Derek Hohls a =E9crit=A0:
> Lionel
>
> I have encountered a problem with windrose.  In some cases, one or more
> of the
> wind direction values are null [''] - the program then fails on line
> 200:
>    values =3D select( [greater_equal( direction, wind_classes[i]
> )],[speed], default=3D-1.e20 )
> Is it possible for you to upgrade the program to perform error
> trapping
> and simply skip (i.e. not process) any values that are null (and handle
> the
> exceptional case that all of them might, in fact, be null).
>
> Thanks!
> Derek


=2D-=20
Lionel Roubeyrie - lro...@li...
LIMAIR
http://www.limair.asso.fr

Lionel
 
I have encountered a problem with windrose.  In some cases, one or more
of the
wind direction values are null [''] - the program then fails on line
200:
   values = select( [greater_equal( direction, wind_classes[i]
)],[speed], default=-1.e20 )
Is it possible for you to upgrade the program to perform error
trapping
and simply skip (i.e. not process) any values that are null (and handle
the
exceptional case that all of them might, in fact, be null).
 
Thanks!
Derek

>>> Lionel Roubeyrie <lro...@li...> 2006/10/18 05:57:55 PM
>>>

Hi Derek,
happy to see you use it, here is windrose0.5 with some improvments :-)

> * do not outline the colors in black; its hard to see
smaller/shorter
> lines
Done

> * the % labels need either to go along a vector NOT used to draw
data,
> or
> be drawn last (on top of data); or a combination of both
Now "%" is set with the external label. I don't find how to set labels
(and 
grids) above patches, ax.set_axisbelow(False) doesn't work :-( But for
the 
moment you can use labangle parameter to move the labels.

> * the 0.0% label can probably be omitted from the centre
> * drawing a title("") on the plot is still problematic (it
overwrites
> the "N" in some cases)
0.0 is not longer draw

> * default background color should be white
Hum, everybody can set it directly from matplotlibrc or creating an
polar axis 
before.

> * a legend title will *very* useful
Waiting for polar axes legend improvments :-)

>
> And a question - is it possible to restrict the plot to a portion of
> the area;
> say to the left, with a "rectangle" of the space available to the
> right; or
> up to the top, with a "rectangle" of the space available to the
> bottom.
> Plots often have to annotated and its useful to have some working
> space
> to do this.
Don't know if I really understand what you want, but why don't you use
subplot 
to split your figures?
>
> Thanks for all the good work!
> Derek

>PS Does anyone else using this program get the strange "[" and "]"
>signs around the data ranges in the legend - how can this be turned
off?
You're the first saying you use it :-)
Maybe differents progs versions. I use:
|datas|[42]>matplotlib.__version__
   Out [42]:'0.87.5'
|datas|[43]>scipy.__version__
   Out [43]:'0.5.1'
|datas|[44]>numpy.__version__
   Out [44]:'1.0b5'

Lionel

-- 
Lionel Roubeyrie - lro...@li... 
LIMAIR
http://www.limair.asso.fr 


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 Hi folks,
  
  reposting... has anyone a clue that might help in the right direction??
  
  was my question too hard or would it help better if I rephrased it ?
  
  thanks so much 
  
  maser
 
maser rati <mas...@ya...> wrote: Hi Folks,
 
 I was wondering how to set the Matplotlib classic Toolbar in order to display only existent data when the back/forward arrows are clicked (i.e, the pan feature) for a subplot that displays plotted data. 
 
 How to set the code in the matplotlib toolbar to only display the data from the file? ( clicking the left arrow when the left most point is at the start of the data file should result in freezing of the plot and a similar action when the right arrow is clicked when the right most point is at the end of the data file). 
 
 I'm not sure if my post was  sufficiently as clear as spring water. Any suggestions would be greatly appreciated.
 
 Great forum, by the way.. 
 
 Thanks.
 -Maser
   

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