Re: [Matplotlib-users] [matplotlib-devel] crazy ideas for MPL

[Gary Ruben]

Is this an ideas thread?
How about a "copy image to clipboard" button for the toolbar.

Gary R.

Pierre GM wrote:
> Eh, can I play ?
> * Something I'd really like to see is a way to access a given patch/ 
> line/collection/... by a string (a name) instead of having to find the  
> corresponding element in a list. That would mean converting lists into  
> dictionaries, or at least provide a way to map the list to a dictionary.
> An example of application would be "del lines['first']" to delete the  
> line named 'first'. By default, if no name is explicitly given to an  
> object, we could use the order in which it is drawn...


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Re: [Matplotlib-users] complex layouts of plots in matplotlib

[Gary Ruben]

Hi Per,

The just-released mpl 0.99 contains Jae-Joon Lee's AxesGrid Toolkit

and Andrew Straw's support for axis spines 


I think these address both your questions. The list of new features is here:


Gary

per freem wrote:
> Hi all,
> 
> i am wondering if there is a way or an interface in matplotlib to
> design complex plot layouts. what i mean is something analogous to the
> 'layout' function of R, where you can say what portion of space each
> plot will take. i think this allows for more sophisticated layouts
> than the usual square matrix layouts that the 'subplot' function
> produces (unless i am missing some other usage of 'subplot').

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[Matplotlib-users] axes_grid examples

[Gary Ruben]

Many of the axes_grid examples in the thumbnail gallery don't work out 
of the box with the latest matplotlib 0.99 because they rely on 
demo_image and demo_axes_divider modules. Should these have been 
packaged with 0.99 or were they left out deliberately?

Gary R.

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Re: [Matplotlib-users] axes_grid examples

[Gary Ruben]

Thanks John.

John Hunter wrote:
> On Mon, Aug 10, 2009 at 5:05 AM, Gary Ruben wrote:
>> Many of the axes_grid examples in the thumbnail gallery don't work out
>> of the box with the latest matplotlib 0.99 because they rely on
>> demo_image and demo_axes_divider modules. Should these have been
>> packaged with 0.99 or were they left out deliberately?
> 
> We've addressed this already in svn HEAD, but the fixes won't be out
> until mpl1.0.  For now, just drop the attached file in the same
> directory as your example code (you may also need to touch a
> __init__.py in that dir.


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Re: [Matplotlib-users] best format for MS word?

[Gary Ruben]

I haven't tried it myself, but this converter may do the trick. If it 
works, can you report back? I'd be interested to know:


Gary R.

Shixin Zeng wrote:
> Hi,
> 
> Could someone tell me what's the best format that matplotlib can
> produce for insertion to MS word? I'm working on a paper using MS
> word. I used matplotlib to produce the pictures in "png' format, but
> my professor doesn't satisfy with the quality of the pictures, he asks
> me to do it in "emf" format, but I can't get an "emf" output from
> matplotlib. While other vector formats that are supported by
> matplotlib are not supported by MS word. I have worked days on
> producing this pictures, I don't want to abandon them just because
> they can't be imported to MS word. I really like to produce my
> pictures by using matplotlib, but I can't really throw away MS word. I
> also tried pstoedit to try to convert to emf from the ps, but it
> doesn't work on my system due to some weired missing procedure entry
> points in imagick dll.
> 
> I'm kinda in a hurry, any help would be greatly appreciated.
> 
> Best Regards
> 
> Shixin Zeng
> 
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Re: [Matplotlib-users] plt.gray dont' work with plt.scatter?

[Gary Ruben]

gray() sets the default colormap for raster-based plot commands like 
imshow(), matshow() and figimage(). For scatter(), you need to set the 
colors of plot elements invidually. Setting the facecolor in the 
scatter() command will work for the example you tried:

scatter(x,y,s=area, marker='^', facecolor=(.7,.7,.7), c='r')

Gary R.

lotrpy wrote:
> Hello, Sorry for my broken english. I copy the source code from
> http://matplotlib.sourceforge.net/examples/pylab_examples/scatter_demo.html
>  
> Just Insert one line "gray()" before the last line "show()".
> But the picture is sitll colorful. not a gray picture.
> It there somethig I missed. Thanks in advance.

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Re: [Matplotlib-users] plotting asymmetric error bars?

[Gary Ruben]

Hi Per,

You need 2*N, not N*2 arrays here. I think you're also trying to use 
absolute values so you probably need something like this:

plt.errorbar([1,2,3],[1,2,3],yerr=np.abs(a.T-[1,2,3]))

I hope this is what you're after,

Gary R.

per freem wrote:
> hi all,
> 
> i am trying to plot asymmetric yaxis error bars. i have the following code:
> 
> import matplotlib.pyplot as plt
> a = array([[ 0.5,  1.5],
>[ 0.7,  2.2],
>[ 2.8,  3.1]])
> plt.errorbar([1,2,3],[1,2,3],yerr=a)


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Re: [Matplotlib-users] imshow smoothing

[Gary Ruben]

Yes. Use interpolation='nearest' instead.

Gary R.

Michael Hearne wrote:
> Running the test script below gives me the image I have attached, which 
> looks like it has been smoothed.
> 
> Does imshow perform some sort of smoothing on the data it displays?  If 
> so, is there a way to turn this off?
> 
> #!/usr/bin/env python
> 
> from pylab import *
> 
> data = array([[1,2,3,4],[5,6,7,8]])
> imshow(data,interpolation=None)
> savefig('output.png')
> close('all')

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Re: [Matplotlib-users] query abuot plotting polygons using a basemap projection

[Gary Ruben]

Thank you Jeff. I'll try out this solution.

Gary.

Jeff Whitaker wrote:


> Gary:  You might be able to use the _geoslib module to compute the 
> intersections of those polygons with the map boundary.  I do a similar 
> thing with the coastline polygons in the _readboundarydata function.
> The _boundarypolyll and _boundarypolyxy instance variables have the 
> vertices of the map projection region polygons in lat/lon and projection 
> coords.  You could do somethig like this:
> 
>from mpl_toolkits.basemap import _geoslib
>poly = _geoslib.Polygon(b) # a geos Polygon instance 
> describing your polygon)
>b = self._boundarypolyxy.boundary
>bx = b[:,0]; by= b[:,1]
>boundarypoly = _geoslib.Polygon(b) # a geos Polygon instance 
> describing the map region
>if poly.intersects(boundarypoly):
>geoms = poly.intersection(boundarypoly)
>polygons = [] # polygon intersections to plot.
>for psub in geoms:
>b = psub.boundary # boundary of an intersection
>polygons.append(zip(b[:,0],b[:,1]))
> 
> -Jeff



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Re: [Matplotlib-users] Circular colormaps

[Gary Ruben]

Hi Ariel,

You might find the attached function helpful here. Try creating a new 
colormap using the example in the docstring (you could also try setting 
high=0.8) - basically this will let you turn down the saturation which 
will hopefully solve your problem. You may also find the plot option 
useful to see what the individual colour channels are doing if you 
decide to make a new colormap of your own - you just need to ensure that 
the r, g, and b values match at both ends.


Gary


Ariel Rokem wrote:

Hi everyone,

I am interested in using a circular colormap, in order to represent a 
phase variable, but I don't like 'hsv' (which is circular). In 
particular, I find that it induces perceptual distortion, where values 
in the green/yellow part of the colormap all look the same. Are there 
any circular colormaps except for 'hsv'? If not - how would you go about 
constructing a new circular colormap? 


Thanks,

Ariel
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University of California, Berkeley
http://argentum.ucbso.berkeley.edu/ariel
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib._cm as _cm


def rescale_cmap(cmap_name, low=0.0, high=1.0, plot=False):
'''
Example 1:
my_hsv = rescale_cmap('hsv', low = 0.3) # equivalent scaling to 
cplot_like(blah, l_bias=0.33, int_exponent=0.0)
Example 2:
my_hsv = rescale_cmap(cm.hsv, low = 0.3)
'''
if type(cmap_name) is str:
cmap = eval('_cm._%s_data' % cmap_name)
else:
cmap = eval('_cm._%s_data' % cmap_name.name)
LUTSIZE = plt.rcParams['image.lut']
r = np.array(cmap['red'])
g = np.array(cmap['green'])
b = np.array(cmap['blue'])
range = high - low
r[:,1:] = r[:,1:]*range+low
g[:,1:] = g[:,1:]*range+low
b[:,1:] = b[:,1:]*range+low
_my_data = {'red':   tuple(map(tuple,r)),
'green': tuple(map(tuple,g)),
'blue':  tuple(map(tuple,b))
   }
my_cmap = colors.LinearSegmentedColormap('my_hsv', _my_data, LUTSIZE)

if plot:
plt.figure()
plt.plot(r[:,0], r[:,1], 'r', g[:,0], g[:,1], 'g', b[:,0], b[:,1], 'b', 
lw=3)
plt.axis(ymin=-0.2, ymax=1.2)

return my_cmap
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Re: [Matplotlib-users] query abuot plotting polygons using a basemap projection

[Gary Ruben]

Hi Jeff,

I finally had a chance to try this. I can't get it to work but I think 
I'm close - for some reason, the way I'm creating the geos polygons 
seems to always intersect the boundary polygon. It's hard to think of a 
good minimal example for this so I've attached an example that 
illustrates the problem - it tries to plot an icosahedron on the 
Mollweide plot.


Gary R.

Jeff Whitaker wrote:

Gary Ruben wrote:

I'm plotting a coverage map of a sphere using the Mollweide plot in
basemap. The attachment is an example that is produced by sending an
array of polygons (one polygon per row described as four corners, one
per column) described using polar (theta) and azimuthal (phi) angles to
the following function. As a kludge, I discard any polygons that cross
the map boundary, but this produces artefacts and it would be better to
subdivide these and keep the parts. I was wondering whether there's a
function I missed that allows me to add polygons and performs the split
across the map boundary.

Gary R.


Gary:  You might be able to use the _geoslib module to compute the 
intersections of those polygons with the map boundary.  I do a similar 
thing with the coastline polygons in the _readboundarydata function.
The _boundarypolyll and _boundarypolyxy instance variables have the 
vertices of the map projection region polygons in lat/lon and projection 
coords.  You could do somethig like this:


   from mpl_toolkits.basemap import _geoslib
   poly = _geoslib.Polygon(b) # a geos Polygon instance 
describing your polygon)

   b = self._boundarypolyxy.boundary
   bx = b[:,0]; by= b[:,1]
   boundarypoly = _geoslib.Polygon(b) # a geos Polygon instance 
describing the map region

   if poly.intersects(boundarypoly):
   geoms = poly.intersection(boundarypoly)
   polygons = [] # polygon intersections to plot.
   for psub in geoms:
   b = psub.boundary # boundary of an intersection
   polygons.append(zip(b[:,0],b[:,1]))

-Jeff


from mpl_toolkits.basemap import Basemap, _geoslib
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
import numpy as np
from numpy import pi

icosahedron = \
[[0.53,0.,-0.53,0.53,-0.53,0.,0.53,-0.53,0.,0.53,0.,
  -0.53,0.85,0.53,0.85,0.85,0.85,0.53,-0.85,-0.53,-0.85,
  -0.85,-0.85,-0.53,0.,0.85,0.,0.,0.,-0.85,0.,0.,0.85,
  0.,-0.85,0.,0.,0.53,0.85,0.,0.85,0.53,0.53,0.,0.85,
  0.53,0.85,0.,-0.53,0.,-0.85,-0.53,-0.85,0.,-0.53,
  -0.85,0.,-0.53,0.,-0.85],
 [0.,0.85,0.,0.,0.,-0.85,0.,0.,0.85,0.,-0.85,0.,0.53,
  0.,-0.53,0.53,-0.53,0.,-0.53,0.,0.53,-0.53,0.53,0.,
  0.85,0.53,0.85,0.85,0.85,0.53,-0.85,-0.85,-0.53,-0.85,
  -0.53,-0.85,0.85,0.,0.53,0.85,0.53,0.,0.,-0.85,-0.53,
  0.,-0.53,-0.85,0.,0.85,0.53,0.,0.53,0.85,0.,-0.53,
  -0.85,0.,-0.85,-0.53],
 [0.85,0.53,0.85,0.85,0.85,0.53,-0.85,-0.85,-0.53,-0.85,
  -0.53,-0.85,0.,0.85,0.,0.,0.,-0.85,0.,0.85,0.,0.,0.,
  -0.85,0.53,0.,-0.53,0.53,-0.53,0.,0.53,-0.53,0.,0.53,
  0.,-0.53,0.53,0.85,0.,-0.53,0.,-0.85,0.85,0.53,0.,
  -0.85,0.,-0.53,0.85,0.53,0.,-0.85,0.,-0.53,0.85,0.,
  0.53,-0.85,-0.53,0.]]

icosahedron1 = \
[[0.53, 0.  ,-0.53, 0.53,-0.53, 0.  ],
 [0.  , 0.85, 0.   ,0.  , 0.  ,-0.85],
 [0.85, 0.53, 0.85 ,0.85, 0.85, 0.53]]


def pointsOnSphere():
x,y,z = np.array(icosahedron)/0.851
return 180/pi*np.arcsin(z), 180/pi*np.arctan2(y,x)


if __name__=='__main__':
if 0:
from enthought.mayavi import mlab
x,y,z = icosahedron
sphere = mlab.triangular_mesh(x, y, z, \
np.arange(len(x)).reshape(-1,3), representation = 'wireframe')
mlab.show()
raise SystemExit

# Make Mollweide plot
m = Basemap(projection='moll', lon_0=0, resolution='c')

# draw the edge of the map projection region (the projection limb)
m.drawmapboundary()

theta, phi = pointsOnSphere()
theta.shape = phi.shape = (-1,3)
print theta.shape[0], 'polys'

ax = plt.gca()  # get current axes instance
# create a geos Polygon instance describing the map region
boundarypoly = _geoslib.Polygon(m._boundarypolyxy.boundary)
for i in range(theta.shape[0]):
pts = np.vstack((phi[i], theta[i])).T
polypts = np.array([m(*pt) for pt in pts])  # to projection coords
poly = _geoslib.Polygon(polypts) # geos polygon for testing
if poly.intersects(boundarypoly):
for psub in poly.intersection(boundarypoly):
b = psub.boundary   # boundary of an intersection
polypts = zip(b[:,0],b[:,1])
c = (1,) + tuple(np.random.random(2))   # warm colour
poly = Polygon(polypts, facecolor=c, edgecolor=c)
ax.add_patch(poly)
else:
c = tuple(np.random.random(2)) + 

Re: [Matplotlib-users] separate sub-forum for basemap?

[Gary Ruben]

IMO I don't think the traffic level on either pure mpl or basemap 
warrants a split.

Gary R.

Dr. Phillip M. Feldman wrote:
> It seems as though there are enough basemap-related posts that it might be
> worth creating a separate basemap-specific sub-forum of the matplotlib
> forum.

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Re: [Matplotlib-users] Arrows between points in a plot?

[Gary Ruben]

Hi Michael,

Take a look at the quiver demo


and the annotation2 demo


More generally, have a look through the examples and gallery pages



Gary R.

Michael Cohen wrote:
> Hi all,
> 
> I have a plot that has say 6 black X's, each separate, and 6 blue X's, 
> also separate, denoting where x's 1-6 have moved to (from black to blue).
> Currently each point is plotted with a separate plot function.
> I would like to generate a plot where each black x and blue x pair has 
> an arrow pointing from one to the other.
> 
> Currently I plot them like this:
> 
> x1black = value
> y1black = value
> plot([x1black],[y1black],'kx',markersize=10,markeredgewidth=2)
> x1blue = value
> y1blue = value
> plot([x1blue],[y1blue],'bx',markersize=10,markeredgewidth=2)
> 
> If I plotted,
> plot([x1black,x1blue],[y1black,y1blue])
> I could make the line between them into an arrow, but I wouldn't be able 
> to make one blue and the other black.
> 
> Also, I'd like to be able to curve my arrows to make them less confusing 
> in case they intersect too much.
> 
> 
> Can anyone point me to the right functions?
> 
> Cheers
> Michael

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Re: [Matplotlib-users] I Need a Couple of Tips for Windows to Get Started on IPython

[Gary Ruben]

In Windows I recommend running iPython inside Console 

particularly for its vastly improved copy and pasting.

Gary R.

phob...@geosyntec.com wrote:
> Third Google result for "copy paste in DOS prompt"
> http://www.copy--paste.org/copy-paste-between-dos-windows.htm
> 
> Note that right-clicking is going to execute behavior, not bring up a 
> contextual menu.
> 
> -p
> 
>> -Original Message-
>> From: Wayne Watson [mailto:sierra_mtnv...@sbcglobal.net]
>> Sent: Monday, December 07, 2009 12:57 PM
>> To: Gary Pajer
>> Cc: matplotlib-users@lists.sourceforge.net
>> Subject: Re: [Matplotlib-users] I Need a Couple of Tips for Windows to
>> Get Started on IPython
>>
>> Right-click does nothing on the IPython window.
>>
>> The Windows command console is, I think, a lost cause all together. I've
>> tried a right-click on it with the same result as in IPython.
>> I'm using Win XP, and I hope they improve on Win 7, which I plan to
>> install on all my machines this month.
>>

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Re: [Matplotlib-users] I Need a Couple of Tips for Windows to Get Started on IPython

[Gary Ruben]

Wayne Watson wrote:
> I thought the console was the only way to use IPython. I go to 
> Start->Allprograms->IPython, and select IPython. Oh, I see *Console" is 
> something of a replacement for the Win Cmd Console. Is there some site 
> that shows off it's features?

Not that I know of.

By the way, in case you haven't set it up a shortcut to Console that 
starts up IPython, I did it like this:

I created a shortcut to console in my start menu:

Properties|Shortcut
Target: "C:\Program Files\Console2\Console.exe"
Start in: "C:\Program Files\Console2"

Then in Console, under Edit|Settings|Tabs

Create a tab with
Main|Title & icon|Title: iPython
Shell|Shell: C:\PYTHON25\Scripts\ipython.exe -pylab -wthread -p pylab
Shell|Startup dir: C:\Python25

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Re: [Matplotlib-users] define color cycle in matplotlibrc

[Gary Ruben]

One nice thing about gnuplot is the option its GUI provides to toggle 
between using coloured lines and using black lines with various dashed 
patterns. I think it would be nice in matplotlib to also be able to have 
a default series of dashed patterns that could automatically be cycled 
through.

Gary R

Eric Firing wrote:
> Dominik Szczerba wrote:
>> -BEGIN PGP SIGNED MESSAGE-
>> Hash: SHA1
>>
>> OK I started hacking and added a color_cycle property to matplotlibrc.
>> Would you be so kind to add this fix to the official version? Thanks!
>> Dominik
> 
> Your basic idea--that the colorcycle should be settable in 
> rcParams--makes good sense, but the implementation needs some changes, 
> maybe including a bit of redesign of the color cycle handling.  I will 
> look into it.  A little discussion on the devel list may be required.  I 
> think we will want to completely decouple lines.color from a new 
> lines.colorcycle, but maybe there is some good reason, other than 
> history, for why they are coupled.

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Re: [Matplotlib-users] define color cycle in matplotlibrc

[Gary Ruben]

I'm happy for it to remain just a suggestion and not a reality. I 
mentioned it in case it was easy to implement alongside the color cycle 
but it seems it is not. Thanks for considering it anyway Eric,

Gary

Eric Firing wrote:
> Dominik Szczerba wrote:
>> -BEGIN PGP SIGNED MESSAGE-
>> Hash: SHA1
>>
>> Eric Firing wrote:
>>> Dominik Szczerba wrote:
>>> OK I started hacking and added a color_cycle property to matplotlibrc.
>>> Would you be so kind to add this fix to the official version? Thanks!
>>> Dominik

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[Matplotlib-users] basemap problem

[Gary Ruben]

I just installed the latest EPD 6.0.2 Python 2.6-based distribution in 
WinXP. The mpl version is 0.99.1.1 and I installed basemap using the 
basemap-0.99.4.win32-py2.6.exe binary installer. I'm getting this 
traceback. Any ideas?
Gary

--

In [1]: from mpl_toolkits.basemap import Basemap
---
ValueErrorTraceback (most recent call last)

C:\PYTHON26\ in ()

C:\Python26\lib\site-packages\mpl_toolkits\basemap\__init__.py in ()
  36 from matplotlib.lines import Line2D
  37 from matplotlib.transforms import Bbox
---> 38 import pyproj, sys, os, math, dbflib
  39 from proj import Proj
  40 import numpy as np

C:\Python26\lib\site-packages\mpl_toolkits\basemap\pyproj.py in ()
  46 CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. """
  47
---> 48 from _proj import Proj as _Proj
  49 from _geod import Geod as _Geod
  50 from _proj import _transform

C:\PYTHON26\c_numpy.pxd in _proj (src/_proj.c:3234)()

ValueError: numpy.dtype does not appear to be the correct type object

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Re: [Matplotlib-users] basemap problem

[Gary Ruben]

Hang on - I just noticed EPD says it contains basemap already, so maybe 
installing over the top of it did something - I'll trying uninstalling 
and doing a repair of EPD.

Gary

Gary Ruben wrote:
> I just installed the latest EPD 6.0.2 Python 2.6-based distribution in 
> WinXP. The mpl version is 0.99.1.1 and I installed basemap using the 
> basemap-0.99.4.win32-py2.6.exe binary installer. I'm getting this 
> traceback. Any ideas?
> Gary

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Re: [Matplotlib-users] basemap problem

[Gary Ruben]

OK, that worked. Sorry for the noise. I forgot basemap gets put under 
site-packages/mpl_toolkits. When I installed a second copy using the 
basemap binary installer, it went under site-packages and caused some 
sort of conflict.

Gary

Gary Ruben wrote:
> Hang on - I just noticed EPD says it contains basemap already, so maybe 
> installing over the top of it did something - I'll trying uninstalling 
> and doing a repair of EPD.
> 
> Gary
> 
> Gary Ruben wrote:
>> I just installed the latest EPD 6.0.2 Python 2.6-based distribution in 
>> WinXP. The mpl version is 0.99.1.1 and I installed basemap using the 
>> basemap-0.99.4.win32-py2.6.exe binary installer. I'm getting this 
>> traceback. Any ideas?
>> Gary


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Re: [Matplotlib-users] save image from array?

[Gary Ruben]

Hi Nico,
I'm pretty sure the functionality is buried in there but unfortunately I 
couldn't figure out how to put it into the imsave function, so for now I 
think you have to resort to using PIL to do this.
Gary R.

Nico Schlömer wrote:
> Hi,
> 
> I see that with imsave() it's possible to save an image based on its
> cmap. Is there also functionality in matplotlib to to store a file
> based on RGB(alpha) information?
> 
> Cheers,
> Nico


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Re: [Matplotlib-users] Using colourmap from matplotlib

[Gary Ruben]

I haven't tried it, but maybe it's to do with the fact that you're 
quantising the colourmap to 256 values; I think matplotlib computes the 
exact rgb values using interpolation. If the only reason you're using 
PIL is to get a .bmp file, maybe you could save the file straight from 
matplotlib as a .png then externally convert it to a .bmp

Gary R.

Ciarán Mooney wrote:
> Hi,
> 
> I am trying to create an image from an array using PIL, numpy and a
> colourmap from matplotlib.

> I'd like to get something that looks the same. I don't think the
> problems are because of the colourmap but rather because of my log
> scaling. Could someone please explain how matplotlib scales the image
> to make it look so nice?
> 
> Regards,
> 
> Ciarán

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Re: [Matplotlib-users] visualizing colormaps for complex functions

[Gary Ruben]

Hi Guy,

I am also interested in the answer to this. The cplot function in the 
mpmath module does exactly this using matplotlib, but very 
inefficiently, as it computes the colour of each pixel in the image in 
hls colour-space and generates the corresponding rgb value directly. I 
suspect this is how it has to be done, as colormaps in matplotlib are 1D 
sequences and the black-white (lightness) value is really another 
dimension. However mpmath's method can be improved by doing the mapping 
using array operations instead of computing it for each pixel.


I've attached a function I wrote to reproduce the Sage cplot command in 
my own work. It's a bit old and can be improved. It takes the Arg and 
Abs of a complex array as the first two arguments - you can easily 
change this to compute these inside the function if you prefer. The line
np.vectorize(hls_to_rgb) can be replaced - recent versions of matplotlib 
have a vectorized function called hsv_to_rgb() inside colors.py - so you 
replace the return line with the commented-out version if you first 
import hsv_to_rgb from colors.


I hope this helps.

I'm also curious: the plots you point to also show plots of the function 
"extrema", which are the phase singularities - does mathematica have a 
function that gives you these, or did you write your own function to 
find them?


regards,
Gary

Guy Rutenberg wrote:

Hi,

Is there a way to generate colormaps for complex-valued functions using 
matplotlib? The type of plots I'm looking for are like the plots in:

http://commons.wikimedia.org/wiki/User:Jan_Homann/Mathematics

Thanks in advance,

Guy
def cplot_like(ph, intens=None, int_exponent=1.0, s=1.0, l_bias=1.0, drape=0, 
is_like_mpmath=False):
'''
Implements the mpmath cplot-like default_color_function
The combined image is generated in hls colourspace then transformed to rgb
*phase*
A filename or 2D n x m array containing phase data in the range -pi->pi
*intens*
If None, set to 1.0
A filename or 2D n x m array containing intensity or amplitude data in 
the range 0->max
*int_exponent*
Default 1.0 applies the intens mask directly to the hls 
lightness-channel
0.6 works well when drape==0
*s*
saturation. Defaults to 1.0. mpmath uses 0.8.
*l_bias*
biases the mean lightness value away from 0.5. mpmath uses 1.0.
Examples are: l_bias=2 -> mean=0.33 (ie darker), l_bias=0.5 -> 
mean=0.66 (lighter)
*drape*
If >1, drapes a structured maximum filter of size drape x drape over 
the intensity data
*is_like_mpmath*
If True, sets int_exponent = 0.3, s = 0.8
'''
from colorsys import hls_to_rgb

if type(ph) is str:
cph = plt.imread(ph)/256.*2*pi-pi  # -pi->pi
if len(cph.shape) == 3: cph = cph[...,0]  # if ph is RGB or RGBA, 
extract the R-plane
else:
cph = ph.copy()

if intens is None:
cintens = np.ones_like(cph)
elif type(intens) is str:
cintens = plt.imread(intens)/255. # 0->1
if len(cintens.shape) == 3: cintens = cintens[...,0]   # if intens is 
RGB or RGBA, extract the R-plane
else:
cintens = intens.copy()
cintens /= cintens.max() # autoscale intensity data 
to 0->1

if drape > 1:
# envelope the intensity
cintens = maximum_filter(cintens, size=drape)

h = ((cph + pi) / (2*pi)) % 1.0

if is_like_mpmath:
# apply mpmath values
int_exponent = 0.3
s = 0.8

l = 1.0 - l_bias/(l_bias+cintens**int_exponent)
v_hls_to_rgb = np.vectorize(hls_to_rgb)

#~ return hsv_to_rgb(dstack((h,np.ones_like(h),l)))
return dstack(v_hls_to_rgb(h,l,s))--
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Re: [Matplotlib-users] plot rgb spectrum

[Gary Ruben]

Hi Tymoteusz,

I think this does what you want (see attached).

I'm not sure about 3D though.

Gary R.

Tymoteusz Jankowski wrote:

Hi!

Can anyone help me to achive this?
I'd like to plot rgb spectrum with matplotlib.
For example let the x axis be green element, and for example... let the y  
axis be red element.

Eventually i'd like to plot 3D figure with all of three elements RGB.
Regards,
T.


import matplotlib.pyplot as plt
import numpy as np

a = np.outer(np.arange(0,256), np.ones(256,dtype=np.uint8))
rgb = np.zeros((256,256,3), dtype=np.uint8)
rgb[:,:,0] = a
rgb[:,:,1] = a.T
plt.imshow(rgb, origin='lower', interpolation='nearest')
plt.show()--
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[Matplotlib-users] Documentation suggestions (longish post)

[Gary Ruben]

I've been helping a fairly new Python user (an astronomer using 
numpy/scipy/matplotlib) in my office get up to speed with matplotlib and 
thought I'd pass on a couple of small thoughts about the documentation 
which we think would make life clearer for new users. I'm putting this 
out for discussion, because it may be totally off-the-mark. On the other 
hand, it may point to some easy changes to make things clearer for new 
users.

First, I think that a new user, presented with the mpl homepage, reads 
the intro on that page, then perhaps clicks through to either the 
pyplot, examples, or gallery pages. They may take example code from 
examples or gallery and modify them for their own plots, but they will 
at some point be referencing the pyplot page (this is also my 
most-visited page on the site).

The matplotlib.pyplot page would really benefit from a few introductory 
paragraphs or even a single sentence with a link to the relevant section 
in the docs, explaining what the relationship of pyplot is to the other 
parts of mpl.
Specifically, I think confusion arises because the explanation about the 
stateful nature of the pyplot interface is (I think) first mentioned at 
the start of the pyplot tutorial page, and is perhaps not emphasized 
enough. It may also be worth stating somewhere in the front-page mpl 
intro that it is recommended that new users do the pyplot tutorial.

The signatures that a new user sees are full of *args and **kwargs which 
is confusing for the new user. There is an explanation in the coding 
guide so perhaps another paragraph or sentence+link to this would help, 
but I think it's probably not a good idea to be directing new users into 
the coding guide. I know about the history of this and I gather that 
most or all of the args are actually tabulated in the documentation now, 
but new users don't necessarily know what *args and **kwargs mean. I 
think there's still a general lack of consistency in the pyplot docs 
related to this. Some docstrings have the call signature shown, with 
default values shown. It's confusing that some kwargs have explicit 
descriptions and appear in the call signature whereas others are just 
"additional kwargs". This split seems to me to be exposing the 
underlying implementation of the function to the user. I don't know 
whether there is logic behind this.

The final area of confusion is to do with jargon, as this seems to creep 
into examples and list discussions. The introduction to the Artist 
Tutorial is quite useful for understanding mpl's plotting model. 
However, for the new user, it is pretty much impenetrable due to the 
jargon and references to other libraries and coding concepts that a new 
user doesn't need to know. I think a gentler description of mpl's 
plotting model in the introduction or in a standalone small chapter 
would be helpful for new users.

Gary R.

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Re: [Matplotlib-users] different behaviour in Windows and Linux

[Gary Ruben]

Thanks for verifying this Sünnje. It looks like an Agg bug. I just tried 
changing to the GTK backend in Linux and the problem disappears.

Gary

Sunnje L Basedow wrote:
> Hi Gary,
> I just tested your example, also on Intrepid with 0.98.3, and I get the
> exact same behaviour as you, with white pixels in the left column. But I
> have no idea why, sorry.
> Sünnje

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[Matplotlib-users] different behaviour in Windows and Linux

[Gary Ruben]

I'm wondering whether someone can reproduce the following problem I'm 
seeing in Ubuntu Intrepid.

I often use matplotlib to save images created with imshow to take 
advantage of matplotlib's colour maps. I've noticed that the behaviour 
is different for 0.98.3 between Windows XP-32 and Ubuntu Intrepid. I 
don't remember seeing this problem with earlier versions. This minimal 
example demonstrates the problem:

--

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm

px = 3
rcFig = {'figsize': (1, 1),
  'dpi': px,
  'subplot.bottom': 0,
  'subplot.left': 0,
  'subplot.right': 1,
  'subplot.top': 1,
  }
plt.rc('figure', **rcFig)

a = np.ones((px, px))
plt.axis('off')
plt.imshow(a, cmap=cm.gray)
plt.savefig('mpl_out.png', dpi=px)

--

In Windows I get the correct behaviour - in this case a 3x3 image with 
all black pixels:

bbb
bbb
bbb

However, in Linux the leftmost column of pixels is white

wbb
wbb
wbb

By the way, I think an imsave function that just saved an array as an 
image with a specified colourmap and clims would be a nice addition to 
matplotlib.image. Is there another way to achieve the same 1-to-1 array 
element-to-pixel image saving applying colourmaps and clims?

thanks,
Gary R.

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Re: [Matplotlib-users] different behaviour in Windows and Linux

[Gary Ruben]

I just realised that the example I gave may not be the best since it's 
not obvious what the autoscaling will do when all array values are 
equal. Nevertheless, even when the array contains a range of values and 
I use a greyscale colourmap, I'm seeing the leftmost pixel column set to 
all white when the array values in that column are all zeros and the 
image is written in Linux, whereas it's black when written in Windows.

Gary


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Re: [Matplotlib-users] different behaviour in Windows and Linux

[Gary Ruben]

Thanks for the rapid fix Mike.

regards,
Gary

Michael Droettboom wrote:
> There is an explicit offset of one pixel on the left when it sets up a 
> clip box in Agg.  I don't know why this is there, but it dates back to 
> 0.98.0, and earlier versions did something completely different.  I can 
> only guess it was to compensate for an earlier bug in the precise 
> drawing of the axes rectangle.  I can't explain why it would have 
> different behavior on Windows vs. Linux, though.
> 
> I have fixed this in SVN r6465 and am including a patch below (which 
> unfortunately requires a recompile).
> 
> Cheers,
> Mike

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Re: [Matplotlib-users] unfilled markers?

[Gary Ruben]

Has the mec always been black? I thought it used to be the same as the 
line colour. I expected it to default to the line colour, as Che expected.

Gary R.

Norbert Nemec wrote:
> Sorry for my misleading words - I did not correctly recall my own work 
> from back then...
> 
> In fact, the code as it is does not change the mec automatically when 
> the mfc of a filled_marker is set to "None" but leaves it black. I did 
> consider adding an automation to change but decided against it. The 
> logic would have become too complex and hard to predict.
> 
> What you can do is setting the mec afterwards using get_color on the 
> plot like
> 
> pl, = plot(x,y,"-o",mfc="None")
> pl.set_mec(pl.get_color())
> 
> Hope that helps?
> 
> Greetings,
> Norbert

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Re: [Matplotlib-users] unfilled markers?

[Gary Ruben]

Thanks John,

That shows how long it is since I used line markers in my plots. Because 
I use them so infrequently, I'm probably not the best one to suggest it, 
but I think it would be nicer for the default colour to match the line 
colour by default, or for an option to be added to allow its simple 
selection without users having to search through the mailing list to 
find Norbert's solution. If I was publishing a colour plot with line 
markers I would definitely want to do this.

Gary

John Hunter wrote:
> On Mon, Jan 26, 2009 at 6:17 AM, Gary Ruben wrote:
>> Has the mec always been black? I thought it used to be the same as the
>> line colour. I expected it to default to the line colour, as Che expected.
> 
> It's been this way since at least 2004:
> 
>   
> http://matplotlib.svn.sourceforge.net/viewvc/matplotlib/trunk/matplotlib/lib/matplotlib/__init__.py?revision=540&view=markup
> 
> JDH


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Re: [Matplotlib-users] unfilled markers?

[Gary Ruben]

Hi Norbert,

Both of your proposals (b) and (c) sound better to me than the current 
behaviour, although they don't sound as obvious to me as simply 
defaulting to always setting the mec to the line colour unless 
overridden using mec="k" - you could label this proposal (d).

Since others seem to have been happy with the black edges and I don't 
know how much extra logic (and consequently extra overhead) is required 
to change to (d), I'd be easily persuaded that (b) or (c) would be OK 
since, as you say, the black edge of filled markers is a matter of style 
preference and if black edges are not wanted on a particular plot that 
uses filled markers, the edge width can simply be set to zero. The 
decision might be guided by whichever results in the simplest logic or 
least overhead.

regards,
Gary

Norbert Nemec wrote:
> Before my work in 2004, the colors were not following the line color at 
> all, which was clearly bad behavior.
> 
> Now, there are two categories: filled markers (with edge color black and 
> filling following the line color) and non-filled markers (with edge 
> color following line color).
> 
> The black edge of filled markers is a matter of style which I personally 
> like and would not want to change.
> 
> The thing that was up for dispute was only about what the edge color of 
> filled markers should do when the filling is switched off. I see three 
> ways to solve this:
> 
> a) Leave it black. (current behavior)
> b) Switch mec to line color if mfc is either "none" or "white".
> c) Switch mec to line color if mfc is not "auto"
> 
> b) or c) might be what people would expect and prefer, but I feared that 
> it would be one step too many in built-in intelligence. But then - maybe 
> c) would be ok? After all, switching from c) to a) by an explicit 
> mec="k" is simple and obvious, the other way around takes a bit more.
> 
> Greetings,
> Norbert

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Re: [Matplotlib-users] unfilled markers?

[Gary Ruben]

It just occurred to me that another option might be to simply add a new 
colour option "line" for mec and mfc which would instruct them to pick 
up the current line colour.

Gary

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[Matplotlib-users] imsave() function

[Gary Ruben]

Hi all,

I've attached a candidate imsave() to complement imread() in the 
image.py module. Would my use of pyplot instead of the oo interface 
preclude its inclusion in image.py? Also, I noticed some problems when I 
ran the tests with the Wx backends with mpl 0.98.5.2 in Win32. Both of 
the Wx backends produce incorrect, but different, results.


Gary R.
import numpy as np
import matplotlib as mpl
# Backend tests - uncomment in turn
# mpl.use('Agg')
# mpl.use('TkAgg')
# mpl.use('WxAgg') # problem in Win32 with mpl 0.98.5.2
# mpl.use('Wx')# several problems in Win32 with mpl 0.98.5.2
# mpl.use('GTK')
# mpl.use('GTKAgg')
import matplotlib.pyplot as plt
from matplotlib import rcParams
import matplotlib.image as mpi
from matplotlib import cm


def imsave(fname, arr, clims=None, cmap=None, format=None, origin=None):
"""
Saves a 2D array as a bitmapped image with one pixel per element.
The output formats available depend on the backend being used.

Arguments:
  *fname*:
A string containing a path to a filename, or a Python file-like object.
If *format* is *None* and *fname* is a string, the output
format is deduced from the extension of the filename.
  *arr*:
A 2D array.
Keyword arguments:
  *clims*:
clims sets the color scaling for the image.
It is a tuple (vmin, vmax) that is passed through to the pyplot clim 
function.
If either *vmin* or *vmax* is None, the image min/max respectively
will be used for color scaling.
  *cmap*:
cmap is a colors.Colormap instance.
  *format*:
One of the file extensions supported by the active
backend.  Most backends support png, pdf, ps, eps and svg.
  *origin*
[ 'upper' | 'lower' ] Indicates where the [0,0] index of
the array is in the upper left or lower left corner of
the axes. Defaults to the rc image.origin value.
"""
ydim, xdim = arr.shape
if cmap is None: cmap = eval('cm.' + rcParams['image.cmap'])
if origin is None: origin = rcParams['image.origin']
f = plt.figure(figsize=(xdim,ydim), dpi=1)
plt.axes([0,0,xdim,ydim])
plt.axis('off')
plt.figimage(arr, cmap=cmap, origin=origin)
if clims is not None: plt.clim(*clims)
plt.savefig(fname, dpi=1, format=format)


# tests
imsave('test1.png', np.tri(100), origin='lower')
imsave('test2.png', np.tri(100), origin='upper')
imsave('test3png', np.random.random((100,100)), cmap=cm.Oranges, format='png')
imsave('test4.png', 
np.hstack((np.tri(100)+np.tri(100)[:,::-1],np.vstack((np.eye(50),np.ones((50,50))*0.75,cmap=cm.gray)
imsave('test5.png', 
np.vstack((np.tri(100),np.hstack((np.eye(50),np.ones((50,50))*0.25,cmap=cm.gray)
imsave('test6.png', np.vstack((np.ones((100,100)),np.zeros((50,100)
imsave('test7.png', np.eye(2))
imsave('test8.png', np.array([[1]]))
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[Matplotlib-users] memory usage (leakage?) in ipython interactive mode

[Gary Ruben]

Is there a summary somewhere of the current state of knowledge about 
memory leaks when using the pylab interface interactively? Doing 
plot(rand(100)) or matshow(rand(1000,1000)) for example eats a big 
chunk of memory (tried with TkAgg and WxAgg in Windows (mpl v0.98.5.2) 
and Linux (mpl v0.98.3)), most of which is not returned when the window 
is closed. The same goes if you create an array, plot it, and explicitly 
del it after closing the window. I've seen lots of posts over the years 
about memory leaks, but there's nothing in the FAQ about this. I found 
old posts about similar things, but nothing that had a clear resolution.

thanks,
Gary

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Re: [Matplotlib-users] memory usage (leakage?) in ipython interactive mode

[Gary Ruben]

Hi Michael,

Thanks for your explanation. It turns out that it is a combination of
(1) and (3). I hadn't thought about (1) and I hadn't done enough
playing to see the python interpreter releasing blocks of memory. As
you suggested, the "solution" is to limit the iPython cache by using
the iPython -cs option.

thanks for your help,
Gary

Michael Droettboom wrote:
> There are at least three possible causes of what you're seeing here:
> 
> 1) ipython stores references to all results in the console.  (ipython 
> maintains a history of results so they can easily be accessed later).  I 
> don't recall the details, but it may be possible to turn this feature 
> off or limit the number of objects stored.
> 
> 2) matplotlib stores references to all figures until they are explicitly 
> closed with pyplot.close(fignum)
> 
> 3) Python uses pools of memory, and is often imposes a significant delay 
> returning memory to the operating system.  It is actually very hard to 
> determine from the outside whether something is leaking or just pooling 
> without compiling a special build of Python with memory pooling turned off.
> 
> In general, interactive use is somewhat at odds with creating many large 
> plots in a single session, since all of the nice interactive features 
> (history etc.) do not know automagically when the user is done with 
> certain objects.
> 
> I am not aware of any memory leaks in current versions of matplotlib 
> with *noninteractive* use, other than small leaks caused by bugs in 
> older versions of some of the GUI toolkits (notably gtk+).  If you find 
> a script that produces a leak reproducibly, please share so we can track 
> down the cause.
> 
> Gary Ruben wrote:
>> Doing plot(rand(100)) or matshow(rand(1000,1000)) for example eats 
>> a big chunk of memory (tried with TkAgg and WxAgg in Windows (mpl 
>> v0.98.5.2) and Linux (mpl v0.98.3)), most of which is not returned 
>> when the window is closed. The same goes if you create an array, plot 
>> it, and explicitly del it after closing the window.
> Can you elaborate on these steps?  It's possible that the del has little 
> effect, since del only deletes a single reference to the object, not all 
> references which may be keeping it alive (such as the figure, which 
> matplotlib itself keeps a reference to).  In general, you need to 
> explicitly call pyplot.close(fignum) to delete a figure.
> 
> Cheers,
> Mike
> 

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[Matplotlib-users] On changing the default tick pad

[Gary Ruben]

Whilst agreeing with Kaushik's sentiments on the greatness of 
matplotlib, I thought his example plot nicely illustrates a layout wart 
that I think is easily fixed by changing the default xtick.major.pad, 
xtick.minor.pad, ytick.major.pad and ytick.minor.pad values from 4 to 6.
As well as preventing the x- and y-axis labels running into each other 
in Kaushik's example, the most common case of a 2D plot with 0 lower 
bound on both the x- and y-axes [e.g. plot(rand(10))] looks better with 
the default font when pad=6. Just to bolster my case, according to the 
gestalt theory "Law of Proximity" 
, the labels, which are 
currently closer to each other at the axis intersection than to the axes 
themselves become separated enough from one another so that they become 
visually associated with the axes in this region.

As an aside, I went looking for Matlab plotting examples and some appear 
to match the pad=4 padding whereas others are more like pad=6.

Of course I shall change this in my matplotlibrc file. I just thought 
I'd see if I could provoke a revolution,

Gary R.

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Re: [Matplotlib-users] 3D plots

[Gary Ruben]

Hi Etienne,

Sorry to hear about your disappointment. You can read about the attempt 
to resurrect the 3D plotting capabilities here:


Unfortunately, this doesn't help you right now.
Depending on the type of 3D plotting you want to do, some suggestions 
for other packages that support 3D plotting from Python and work now are:
Mayavi2's mlab interface 

gnuplot.py 
DISLIN 
R via RPy 

and I'm pretty sure there are more too.

Right now, if mayavi2 looks like it'll do what you want, I'd recommend 
it as your next stop. And in my opinion, I wouldn't say that your time 
spent learning matplotlib was wasted - 2D plotting is usually useful and 
matplotlib may soon again have limited 3D capability.

Gary R.

Etienne Gaudrain wrote:
> Hello list !
> 
> This is probably a recurrent topic, or even more probably HAVE been a 
> recurrent topic... So sorry, sorry, sorry... I wanted to search the 
> archives but Sourceforge is very slow today (...).
> 
> Anyway, here is my question:
> 
> Is it right that Matplotlib can no longer plot 3D graphes?

> Does it mean that all my efforts to understand and learn Matplotlib are 
> just a big waste of time since I need another package now that I need 3D 
> plot? So I ask you for advice: should I forget completely Matplotlib and 
> move to MayaVI2? Or is there any plan to bring 3D back into Matplotlib, 
> I mean to make a proper and complete alternative to Matlab?
> 
> Or am I just upset because I am missing something. I only plot data 
> every 4 or 6 months, and I really don't expect to see major 
> functionalities to have disappeared when I come back to plotting data... 
> is it a wrong expectation?
> 
> Thanks !!
> -Etienne


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Re: [Matplotlib-users] load signed data joins problem

[Gary Ruben]

How about

f = open(file)
s = f.read()
f.close()
a = s.replace('E-','EE').replace('-',' -').replace('EE','E-')
x = np.fromstring(a, sep=' ')

Gary R.

darkside wrote:
> I think that not all de numbers use the same number of characters, the 
> problem is the signed ones. This numbers use one more character for '-' 
> and join the previous column.
> Your idea is quite good, but I don't know how to do it:
> If I use the pylab.load code, I suppose that I have to put something in 
> "converters" option, but I haven't found how to use it.
> The other option I have found is using 'readline' of python
> 
> fin = open (file, 'r')
> datos1 = fin.readline()
> fin.close()
> 
> but I don't know how to split it and it seems a very rude way of doing it.
> 
> Thank you very much


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Re: [Matplotlib-users] matplotlibrc customizing

[Gary Ruben]

> When I f.e. change
> 
> #xtick.labelsize  : 14  (from '12')
> #xtick.direction  : out (from 'in')

Uncomment the lines.

#xtick.labelsize  : 14
#xtick.direction  : out

to

xtick.labelsize  : 14
xtick.direction  : out

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Re: [Matplotlib-users] PIL + pyplot.savefig() size change

[gary ruben]

The dpi value, which can be overridden, will determine the size of the
output image. It looks to me like you just want the output to always
be the same size as your input image, so use imsave() instead of
imshow() followed by savefig() for this:
i.e. just do

map = Basemap(..)
pilImg = Image.open('bkgmap.gif')
rgba = pil_to_array(pilImg)
pyplot.imsave('outimg.png', rgba)

On Fri, Sep 23, 2011 at 9:10 AM, Isidora  wrote:
> Hi,
>
> I am new to matplotlib so I may not have found the right answer because I am 
> looking in the wrong places.
>
> I wrote a script to draw lines on a 800x600 pixels GIF background map. The 
> output image I get is 620x450.  Could someone let me know what I am doing 
> wrong?
>
> Code Snippet:
>
> map = Basemap(..)
> pilImg = Image.open('bkgmap.gif')
> rgba = pil_to_array(pilImg)
> map.imshow(rgba)
> # Plot some lines and labels here
> 
> pyplot.savefig('outimg.png',format='PNG',bbox_inches='tight',pad_inches=0)
>
>
> Thank you
>
>
>
>
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[Matplotlib-users] how do I specify the line join and cap style?

[gary ruben]

Is it possible to control the join and cap styles of lines and
patches? Is there an example for this? I'm trying to add a scale
marker to a plot, but lines have rounded ends by default, so I'm
currently changing these manually in Inkscape to miter join and butt
cap. Here is a minimal example, based on the code here:

import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar

def add_sizebar(ax, size):
  asb =  AnchoredSizeBar(ax.transData,
 size,
 str(size),
 loc=8,
 pad=0.1, borderpad=0.5, sep=5,
 frameon=False)
  ax.add_artist(asb)

add_sizebar(plt.gca(), 0.5)

plt.draw()
plt.show()


What I'd like is a 2pt wide line with butt-style cap ends,

thanks,
Gary

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Re: [Matplotlib-users] how do I specify the line join and cap style?

[gary ruben]

Thanks for the workaround JJ. I've filed a feature request,

Gary

On Mon, Dec 13, 2010 at 9:54 PM, Jae-Joon Lee  wrote:
> It seems that there is no option to change join and cap style for
> patches (only lines have them).
> While there could be other ways, one workaround is to use patheffect.
>
> Below is a modified version of your example.
>
> Meanwhile, I think the situation needs to be fixed, i.e., Patches
> should implement set_capstyle and set_joinstyle. Can you file a
> feature request on the tracker?
>
> Regards,
>
> -JJ
>
>
>
> import matplotlib.pyplot as plt
> from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
>
> from matplotlib.patheffects import Stroke
>
> def add_sizebar(ax, size):
>  asb =  AnchoredSizeBar(ax.transData,
>    size,
>    str(size),
>    loc=8,
>    pad=0.1, borderpad=0.5, sep=5,
>    frameon=False)
>  ax.add_artist(asb)
>
>  mypatch = asb.size_bar.get_children()[0]
>  mypatch.set_path_effects([Stroke(joinstyle='miter',
>                                  capstyle='butt')]) # override
> joinstyle and capstyle
>
> add_sizebar(plt.gca(), 0.5)
>
>
> plt.draw()
> plt.show()
>
>
>
>
> On Mon, Dec 13, 2010 at 9:16 AM, gary ruben  wrote:
>> Is it possible to control the join and cap styles of lines and
>> patches? Is there an example for this? I'm trying to add a scale
>> marker to a plot, but lines have rounded ends by default, so I'm
>> currently changing these manually in Inkscape to miter join and butt
>> cap. Here is a minimal example, based on the code here:
>>
>> import matplotlib.pyplot as plt
>> from mpl_toolkits.axes_grid1.anchored_artists import AnchoredSizeBar
>>
>> def add_sizebar(ax, size):
>>  asb =  AnchoredSizeBar(ax.transData,
>>     size,
>>     str(size),
>>     loc=8,
>>     pad=0.1, borderpad=0.5, sep=5,
>>     frameon=False)
>>  ax.add_artist(asb)
>>
>> add_sizebar(plt.gca(), 0.5)
>>
>> plt.draw()
>> plt.show()
>>
>>
>> What I'd like is a 2pt wide line with butt-style cap ends,
>>
>> thanks,
>> Gary
>>
>> --
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>> new data types, scalar functions, improved concurrency, built-in packages,
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Re: [Matplotlib-users] Memory usage

[gary ruben]

You're not doing this from ipython are you? It's cache hangs onto the
plot object references and stops python's garbage collector from
releasing them. If so, you can disable the cache as a workaround. A
better option would be if ipython implemented an option to avoid
caching references to matplotlib objects.

Gary R.

On Fri, Jan 14, 2011 at 2:59 AM, Benjamin Root  wrote:
> On Thu, Jan 13, 2011 at 7:54 AM, CASOLI Jules  wrote:
>>
>> Hello to all,
>>
>> This is yet another question about matplotlib not freeing memory, when
>> closing a figure (using close()).
>> Here is what I'm doing (tried with several backends, on MacOSX and Linux,
>> with similar results):
>> 
>> import matplotlib as mpl
>> from matplotlib import pylot as plt
>> import numpy as np
>>
>> a = np.arange(100)
>> mpl.cbook.report_memory()
>> # -> output: 54256
>> plt.plot(a)
>> mpl.cbook.report_memory()
>> # -> output: 139968
>> plt.close()
>> mpl.cbook.report_memory()
>> # -> output: 138748
>> 
>>
>> Shouldn't plt.close() close the figure _and_ free the memory used by it?
>> What am I doing wrong ?
>> I tried several other ways to free the memory, such as f = figure(); ... ;
>> del f, without luck.
>>
>> Any help appreciated !
>>
>> P.S. : side question : how come the call to plot take so much memory (90MB
>> for a 8MB array ?). I have read somewhere that each point is coded on three
>> RGB floats, but it only means an approx. 12MB plot... (plus small overhead)
>>
>> Jules
>>
>>
>
> Jules,
>
> Which version of Matplotlib are you using and which backend?  On my Linux
> install of matplotlib (development branch) using GTKAgg, the memory usage
> does get high during the call to show(), but returns to (near) normal
> amounts after I close.  An interesting observation is that if the
> interactive mode is off, the memory usage returns back to just a few
> kilobytes above where it was before, but if interactive mode was turned on,
> the memory usage returned to being a few hundred kilobytes above where it
> started.
>
> Ben Root
>
> P.S. - As a side note, estimating the memory size of these plots from the
> given data isn't as straight-forward as multiplying by three (actually, it
> would be four because of the transparency value in addition to rgb).  There
> are many other parts of the graph that needs to be represented (all having
> rgba values) but there are also a lot of simplifications that are done to
> reduce the amount of memory needed to represent these objects.
>
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Re: [Matplotlib-users] Memory usage

[gary ruben]

No problem. This caught me out a long time ago and has also caught out
a few people I know.

On Fri, Jan 14, 2011 at 8:23 PM, CASOLI Jules  wrote:
> Hooo, well done! This is it.
>
> I didn't knew about caching...
> I was indeed using ipython, but I did led some test using the basic python 
> interpreter,with same results, so I did not mention this point.
> In fact, python's basic interpreter still records the last three outputs. As 
> my tests were really short (plt.close() ; mpl.cbook.report_memory() ; 
> gc.collect() is only two lines before the collect, only o)ne o,f theme 
> outputt ing something) even pyhton's caching was still at work, and the 
> garbage collector could not free anything.
>
> Thanks a lot, and also thanks to Ben for taking interest !
>
> Jules
>
> PS : Gary, sorry, for the duplicated mail...

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Re: [Matplotlib-users] Trouble with imshow

[gary ruben]

You might want to try out the visvis module instead of matplotlib for
interactive viewing of large 2D images - my system is also Win64 with
4GB and visvis.imshow() handles a 4k*4k image. You'll probably also
want to disable ipython's object caching if you're doing a lot of this
interactive viewing of large images.

Gary R

On Thu, Feb 3, 2011 at 10:59 AM, Christoph Gohlke  wrote:
> On 2/2/2011 3:33 PM, Robert Abiad wrote:
>> Hello All,
>>
>> I'm very new to python, so bear with me.
>>
>> I'd like to use python to do my image processing, but I'm running into 
>> behavior that doesn't make
>> sense to me.  I'm using Windows 7 Pro (64-bit) with 4 gigs of memory, python 
>> 2.6.6, and the newest
>> versions of ipython, pyfits, matplotlib (1.0.1), numpy (1.5.1), scipy.  I'm 
>> loading in a fits file
>> that's 26 MB (~16 Mpixels).  When I load my image in ImageJ, I can see 
>> memory usage go up by 50MB,
>> but when I try displaying the image using imshow(), my memory usage goes up 
>> by around 500MB, each
>> time.  If I close the figure and replot it, imshow() crashes.  I don't know 
>> if I'm doing something
>> wrong, or if it's a new or known bug.  I tried the same thing on Linux and 
>> got the same result.
>> Here's a transcript.
>>
>>     Welcome to pylab, a matplotlib-based Python environment.
>>     For more information, type 'help(pylab)'.
>>
>> In [1]: import pyfits
>>
>> In [2]: from Tkinter import *
>>
>> In [3]: import tkFileDialog
>>
>> In [4]: image=pyfits.getdata(tkFileDialog.askopenfilename())
>>
>> In [5]: imshow(image)
>> Out[5]:
>>
>> In [6]: close()
>>
>> In [7]: imshow(image,origin='lower')
>> Out[7]:
>>
>> In [8]: close()
>>
>> In [9]: imshow(image[100:3600,100:3600],origin='lower')
>> Out[9]:
>>
>> In [10]: Exception in Tkinter callback
>> Traceback (most recent call last):
>>     File "C:\app\Python2.6\lib\lib-tk\Tkinter.py", line 1410, in __call__
>>       return self.func(*args)
>>     File "C:\app\Python2.6\lib\lib-tk\Tkinter.py", line 495, in callit
>>       func(*args)
>>     File 
>> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_tkagg.py", 
>> line 263, in
>> idle_draw
>>       self.draw()
>>     File 
>> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_tkagg.py", 
>> line 248, in draw
>>       FigureCanvasAgg.draw(self)
>>     File 
>> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_agg.py", 
>> line 394, in draw
>>       self.figure.draw(self.renderer)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", line 55, 
>> in draw_wrapper
>>       draw(artist, renderer, *args, **kwargs)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\figure.py", line 
>> 798, in draw
>>       func(*args)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", line 55, 
>> in draw_wrapper
>>       draw(artist, renderer, *args, **kwargs)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\axes.py", line 1946, 
>> in draw
>>       a.draw(renderer)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", line 55, 
>> in draw_wrapper
>>       draw(artist, renderer, *args, **kwargs)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", line 354, 
>> in draw
>>       im = self.make_image(renderer.get_image_magnification())
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", line 569, 
>> in make_image
>>       transformed_viewLim)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", line 201, 
>> in _get_unsampled_image
>>       x = self.to_rgba(self._A, self._alpha)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\cm.py", line 193, in 
>> to_rgba
>>       x = self.norm(x)
>>     File "C:\app\Python2.6\lib\site-packages\matplotlib\colors.py", line 
>> 820, in __call__
>>       result = (val-vmin) / (vmax-vmin)
>>     File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 3673, 
>> in __div__
>>       return divide(self, other)
>>     File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 1077, 
>> in __call__
>>       m |= filled(domain(da, db), True)
>>     File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 772, in 
>> __call__
>>       return umath.absolute(a) * self.tolerance>= umath.absolute(b)
>> MemoryError
>>
>>
>> Thanks for any help,
>> -robert
>>
>
>
> These are previous discussions on the issue:
>
> 
> 
> 
>
> Christoph
>
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Re: [Matplotlib-users] Trouble with imshow

[gary ruben]

Christoph, if you're looking at special casing uint8's, you might want
to keep in mind that uint16 greyscale images are also quite common as
camera outputs in experimental setups. I think that the solution to
this should ideally minimise memory usage for any greyscale image, be
it uint8, uint16, float32 or float64. i.e. avoiding conversion to RGBA
for any single-plane 2D array type would be best IMHO,

Gary R.

On Thu, Feb 3, 2011 at 5:38 PM, Robert Abiad  wrote:
>
>
> On 2/2/2011 6:06 PM, Eric Firing wrote:
>> On 02/02/2011 03:08 PM, Robert Abiad wrote:
>>> On 2/2/2011 3:59 PM, Christoph Gohlke wrote:
 On 2/2/2011 3:33 PM, Robert Abiad wrote:
> Hello All,
>
> I'm very new to python, so bear with me.
>
> I'd like to use python to do my image processing, but I'm running into 
> behavior that doesn't make
> sense to me.  I'm using Windows 7 Pro (64-bit) with 4 gigs of memory, 
> python 2.6.6, and the newest
> versions of ipython, pyfits, matplotlib (1.0.1), numpy (1.5.1), scipy.  
> I'm loading in a fits file
> that's 26 MB (~16 Mpixels).  When I load my image in ImageJ, I can see 
> memory usage go up by 50MB,
> but when I try displaying the image using imshow(), my memory usage goes 
> up by around 500MB, each
> time.  If I close the figure and replot it, imshow() crashes.  I don't 
> know if I'm doing something
> wrong, or if it's a new or known bug.  I tried the same thing on Linux 
> and got the same result.
> Here's a transcript.
>
>        Welcome to pylab, a matplotlib-based Python environment.
>        For more information, type 'help(pylab)'.
>
> In [1]: import pyfits
>
> In [2]: from Tkinter import *
>
> In [3]: import tkFileDialog
>
> In [4]: image=pyfits.getdata(tkFileDialog.askopenfilename())
>
> In [5]: imshow(image)
> Out[5]:
>
> In [6]: close()
>
> In [7]: imshow(image,origin='lower')
> Out[7]:
>
> In [8]: close()
>
> In [9]: imshow(image[100:3600,100:3600],origin='lower')
> Out[9]:
>
> In [10]: Exception in Tkinter callback
> Traceback (most recent call last):
>        File "C:\app\Python2.6\lib\lib-tk\Tkinter.py", line 1410, in 
> __call__
>          return self.func(*args)
>        File "C:\app\Python2.6\lib\lib-tk\Tkinter.py", line 495, in callit
>          func(*args)
>        File 
> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_tkagg.py",
>  line 263, in
> idle_draw
>          self.draw()
>        File 
> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_tkagg.py",
>  line 248, in draw
>          FigureCanvasAgg.draw(self)
>        File 
> "C:\app\Python2.6\lib\site-packages\matplotlib\backends\backend_agg.py", 
> line 394, in draw
>          self.figure.draw(self.renderer)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", 
> line 55, in draw_wrapper
>          draw(artist, renderer, *args, **kwargs)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\figure.py", 
> line 798, in draw
>          func(*args)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", 
> line 55, in draw_wrapper
>          draw(artist, renderer, *args, **kwargs)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\axes.py", line 
> 1946, in draw
>          a.draw(renderer)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\artist.py", 
> line 55, in draw_wrapper
>          draw(artist, renderer, *args, **kwargs)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", 
> line 354, in draw
>          im = self.make_image(renderer.get_image_magnification())
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", 
> line 569, in make_image
>          transformed_viewLim)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\image.py", 
> line 201, in _get_unsampled_image
>          x = self.to_rgba(self._A, self._alpha)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\cm.py", line 
> 193, in to_rgba
>          x = self.norm(x)
>        File "C:\app\Python2.6\lib\site-packages\matplotlib\colors.py", 
> line 820, in __call__
>          result = (val-vmin) / (vmax-vmin)
>        File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 
> 3673, in __div__
>          return divide(self, other)
>        File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 
> 1077, in __call__
>          m |= filled(domain(da, db), True)
>        File "C:\app\Python2.6\lib\site-packages\numpy\ma\core.py", line 
> 772, in __call__
>          return umath.absolute(a) * self.tolerance>= umath.absolute(b)
> MemoryError
>
>
> Thanks for any help,
>>>

Re: [Matplotlib-users] jitter in matplotlib?

[gary ruben]

I haven't seen this done before so I don't know if there's a standard
way. The idea seems to be to take some points which are real data,
create a random variable for each point with the points' position as
the mean, then choose some number of points from each distribution to
create some new points clustered around the original data. Some
examples online seem to use uniform distributions and Poisson
distributions or mixtures of these (uniform for the x-variable and
Poisson for the y). If my take on this is correct, you can use
scipy.stats to do this - an example is in the attached file which
creates Gaussian distributions for each of the x and y coordinates
then creates an equal number of new points for each of the seed
points. The online examples I saw seem to choose random numbers of new
points for each seed point. I didn't bother trying to cover all the
possibilities. Hopefully this is helpful,

Gary R.

On Thu, Feb 24, 2011 at 3:04 PM, Uri Laserson  wrote:
> Hi all,
> I am interested in jittering points in a plot.  I searched the forum, but I
> am amazed at the dearth of results on the topic.  I am referring to
> something like this:
> http://goo.gl/Db47s
> or
> http://goo.gl/BjIZt
>
> Is there a standard way people do this with MPL?
> Thanks!
> Uri
> ...
> Uri Laserson
> Graduate Student, Biomedical Engineering
> Harvard-MIT Division of Health Sciences and Technology
> M +1 917 742 8019
> laser...@mit.edu


jitter.py
Description: Binary data
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Re: [Matplotlib-users] LaTeX matplotlib Bug?

[gary ruben]

Um, how about r"$80--120$" instead of r"$80--120" ?

On Wed, Apr 6, 2011 at 9:56 AM, Sean Lake  wrote:
> Hello all,
>
> I'm trying to specify a range of numbers in a particular legend using LaTeX. 
> In order to do so I'm feeding it the string: r"$80--120". The output should 
> be have an endash, "80–120", but I'm getting "80--120". This is a standard 
> feature of LaTeX ( http://en.wikibooks.org/wiki/LaTeX/Formatting ), so I 
> don't know what's going on.
>
> Thanks,
> Sean Lake
>
> uname -a
> Darwin dynamic_051.astro.ucla.edu 10.7.0 Darwin Kernel Version 10.7.0: Sat 
> Jan 29 15:17:16 PST 2011; root:xnu-1504.9.37~1/RELEASE_I386 i386
>
> (You also have a bug on this web page: 
> http://matplotlib.sourceforge.net/faq/troubleshooting_faq.html#reporting-problems
>  , The line python -c `import matplotlib; print matplotlib.__version__` 
> should not have back-ticks)
> /sw/bin/python2.6 -c 'import matplotlib; print matplotlib.__version__'
> 1.0.0
>
> Got matplotlib via fink:
> fink --version
> Package manager version: 0.29.21
> Distribution version: selfupdate-rsync Sun Apr  3 02:28:24 2011, 10.6, x86_64
> Trees: local/main stable/main stable/crypto unstable/main unstable/crypto
>
> matplotlibrc file:
> text.usetex : True
>
> #backend : MacOSX
> backend : GTKAgg
> #backend : ps
> #backend : pdf
>
>
>
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Re: [Matplotlib-users] Boundary edges of a set of points

[gary ruben]

If you generate a big list of all the edges from the triangle data,
you should get repeat entries only for all the internal edges. You
could then find all the duplicates using this recipe
http://stackoverflow.com/questions/1920145/how-to-find-duplicate-elements-in-array-using-for-loop-in-python-like-c-c
i.e.
dups = [x for x in list_a if list_a.count(x) > 1]

After removing all of these, you should be left with just the boundary edges.

Gary R.

On Fri, Apr 29, 2011 at 7:56 AM, Luke  wrote:
> Ian,
>  Thanks for the response and the example code.  I guess what I'm
> trying to do might be well defined.  Here is a plot that should
> illustrate the data I'm working with:
>
> http://biosport.ucdavis.edu/blog/copy_of_steady_benchmark_tau.png
>
> The green and red regions are being displayed by plotting each and
> every point in my data set that is stable.  So the set of points I was
> describing in my original message looks like these green and red
> regions.
>
> What I would like is just the boundary of the stable region, which
> maybe isn't a very well defined statement.  The convex hull of these
> points would enclose a part of the x-y plane that isn't stable, so I
> don't want to include it in my plot.
>
> I am thinking that perhaps the approach I should be taking should
> involve contouring the real part of the eigenvalues which determine
> the stability, and then plot the zero-level curve.  I'll have to think
> about that some more.
>
> Is it clear what I am trying to do?  If so, do you think the Delaunay
> triangulation is the right way to go?
>
> ~Luke
>
> On Thu, Apr 28, 2011 at 2:14 PM, Ian Thomas  wrote:
>> On 28 April 2011 08:51, Luke  wrote:
>>>
>>> I have a set of unstructured (x,y) points which I would like to
>>> compute a boundary polygon for.  I don't want the convex hull.
>>>
>>> I was able to use matplotlib.tri to get a Delaunay triangulation for
>>> my points by following the examples online, but I'm having trouble
>>> masking everything but the triangles with a boundary edge.
>>> Additionally, once I get this, I'm not clear on how to plot just the
>>> boundary.
>>>
>>> Here is what it seems like the mask should be, assume triang comes
>>> from matplotlib.tri.Triangulation().
>>>
>>> mask = np.where(np.where(triang.neighbors < 0, 0, 1).all(axis=1), 1, 0)
>>> triang.set_mask(mask)
>>>
>>> but, when I plot triang using plot.triplot(), or plt.plot() to plot
>>> the edges, I am getting a bunch of extra stuff that isn't just the
>>> boundary triangles/edges.
>>>
>>> Anybody have example code for properly masking and plotting only the
>>> boundary edges?
>>>
>>> ~Luke
>>
>> Luke,
>>
>> I am not entirely clear exactly what you want to do, but I'll try to help.
>>
>> Your masking of the triangulation masks the triangles not the edges, and so
>> your triplot call displays those triangles that include a boundary edge but
>> also the other edges of those triangles.  As you say, this isn't what you
>> want.
>>
>> I've attached an example script that follows on from your idea of testing
>> triang.neighbors to determine the boundary edges, and displays just  those
>> edges.  However, this is the convex hull as, by definition, the boundary of
>> an unconstrained Delaunay triangulation is the convex hull.  As you don't
>> want the convex hull, I am not clear what you want instead.
>>
>> If I have misunderstood your requirements and/or you have further questions,
>> please post your example code as it is much easier for others on the mailing
>> list to correct existing code than come up with their own freestanding
>> example.
>>
>> I hope some of this helps!
>> Ian Thomas
>>
>
>
>
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Re: [Matplotlib-users] continous colour bar

[gary ruben]

The pre-defined hsv colour map has this property - can you use that?
Otherwise, yes, it is possible to define any map you like.

Gary R

On Fri, Jul 8, 2011 at 12:55 PM, Ben Elliston  wrote:
> Hi.
>
> I have a set of data with a range of (say) 0 to 100.  Is it possible
> to get matplotlib to use the same colour for 0 and 100, so that the
> colours "meet" at the ends of the color bar?
>
> One workaround is to just manipulate the data (eg. using abs (x-50)),
> but I would rather not, if possible.
>
> Thanks, Ben

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[Matplotlib-users] alpha settings in mplot3d

[gary ruben]

I haven't had a chance to look properly at the new mplot3d
improvements that Ben Root has been working on, but I wonder whether
it is easy now to set the axis properties so that the patches that
form the axes no longer have an alpha value of 0.5? I really want them
to be solid. The use case is that I often save images in a vector
format for editing within inkscape, do some fiddling, then re-export
as eps or pdf. If there are any semi-transparent objects, inkscape
will rasterize the whole image, so it becomes necessary to first go
through and manually set the alphas of all these patches to 1.0 before
saving.
A cursory look at the new code makes me hopeful that this is now
possible since the setting from _AXINFO has been moved to the Axis
constructor. Does that mean I'll be able to do something like
ax._axinfo['x']['color']=(0.3,0.3,0.3,1) with the new version?

Gary

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Re: [Matplotlib-users] alpha settings in mplot3d

[gary ruben]

Thanks Ben, that works nicely. Good work :) (except that inkscape is
not nearly as good as matplotlib itself at optimising the resulting
vector-based pdf to keep the file size down - not mpl's fault though).
I just remembered, while trying this out, that there are two of every
object forming the axis parts - two of every patch, grid line, tick
line and label. It was this way before the latest changes also, but is
there a reason, or is it a bug? It doesn't impact visually though.

thanks for the great work on this,
Gary

On Wed, Jul 20, 2011 at 12:41 PM, Benjamin Root  wrote:
> On Tue, Jul 19, 2011 at 9:25 PM, gary ruben  wrote:
>>
>> I haven't had a chance to look properly at the new mplot3d
>> improvements that Ben Root has been working on, but I wonder whether
>> it is easy now to set the axis properties so that the patches that
>> form the axes no longer have an alpha value of 0.5? I really want them
>> to be solid. The use case is that I often save images in a vector
>> format for editing within inkscape, do some fiddling, then re-export
>> as eps or pdf. If there are any semi-transparent objects, inkscape
>> will rasterize the whole image, so it becomes necessary to first go
>> through and manually set the alphas of all these patches to 1.0 before
>> saving.
>> A cursory look at the new code makes me hopeful that this is now
>> possible since the setting from _AXINFO has been moved to the Axis
>> constructor. Does that mean I'll be able to do something like
>> ax._axinfo['x']['color']=(0.3,0.3,0.3,1) with the new version?
>>
>> Gary
>>
>
> Gary,
>
> Glad to hear that you are kicking the tires.  To make it clear, the _axinfo
> dictionary is in the Axis3D object (of which there are 3 in a Axes3D
> object).  So, it would be something like:
>
> ax.xaxis._axinfo['color'] = (0.3, 0.3, 0.3, 1)
>
> At least, in theory.  Part of the reason why I did not want to make this
> dictionary official is because the above would not actually work as
> expected.  Although something similar for tick line colors might, for
> example.  Because of the inconsistencies and because I did not want to paint
> myself into a corner, I have made this dictionary explicitly "users beware".
>
> However, there is hope for your problem!  Use ax.xaxis.set_pane_color((0.3,
> 0.3, 0.3, 1)) instead!
>
> Let me know if you encounter any other problems.
> Ben Root
>
>

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Re: [Matplotlib-users] Some more mplot3d questions

[gary ruben]

Hi Ben,
Comments inline...

On Fri, Jul 22, 2011 at 1:31 AM, Benjamin Root  wrote:
>
>
> On Thu, Jul 21, 2011 at 1:10 AM, gary ruben  wrote:
>>
>> I'm trying to make a surface plot using the latest version of mplot3d
>> from the git trunk and I have a couple of questions. The attached
>> image is close to what I would like. The associated plot command I am
>> using is
>>
>> ax.plot_surface(X, Y, Z, rstride=1, cstride=1, alpha=0.8, shade=True,
>>    cmap=plt.cm.summer,
>>    color='k',
>>    facecolors='k',
>>    lightsource = LightSource(azdeg=0, altdeg=0),
>>    )
>>
>> 1. Is there support now to automatically annotate the axis so that a
>> multiplier is added, as occurs in 2D plots, or should I do this
>> manually by rescaling the data for the moment?
>
> Yes, offset text is now automatic and should activate in similar manner as
> it does for regular 2D axis formatters.  You were one order of magnitude off
> from automatically triggering it.  Also, I should note that it might be
> better to use "ax = fig.gca(projection='3d')" instead of "ax = Axes3D(fig)"
> because the former will leave more of a margin, which would allow the offset
> text to be fully visible.

Thanks. That's actually what I am doing but I cropped the output image
before attaching it.

> If you want the full figure area, then you may
> need to fiddle with the ax.zaxis._axinfo['label']['space_factor'] to bring
> it and the axis label closer to the axis.

Thanks. That's useful to know.

> The odd thing that I am encountering right now while investigating your
> problem is that I can't seem to force the use of the offset.  It could just
> be that I am doing it wrong, but I will look closer.

Yes, I had set 'axes.formatter.limits' : (-2, 2) hoping to trigger it
- I guess that's what you tried.

>> 2. Currently, it doesn't appear possible to shade the surface patches
>> according to just a base facecolor and their orientation to a light
>> source. Do I have to define a new colormap with a constant/single
>> colour to achieve this?
>
> Looking over the plot_surface code, this appears to be the case, however,
> looking back over the LightSource code, I believe it might be possible to
> update plot_surface to operate on situations where no cmap is specified.  I
> will take a look today at that possibility and see if I can get it out for
> the v1.1.0 release.

That would be great - it is a very good way to visualize a surface so
it should be made as simple as possible.

>> 3. I have set alpha=0.8 to allow the wireframe lines to show through a
>> little. When shade=False, the wireframe is visible but I lose
>> orientation-based shading. Is there a way to overlay the wireframe
>> properly when shade=True?
>>
>
> In plot_surface, when shade=True, it appears that both the facecolors and
> the edgecolors are set to the same colors.  The only reason why the lines
> show up when you set transparency is that that alpha value is applied only
> to the faces and not the edges.  Specifically, the logic is as follows:
>
> if fcolors is specified, then set that color for both facecolor and
> edgecolor.
> Else, if a cmap is specified, then give the polygon collection the data,
> limits and norm it needs to determine color itself.
> Else, then use the value of "color" to specify only the facecolors.
>
> I think the first branch of this logic is a bit wonky.

I agree, since fcolors must be specified in order to trigger the
lightsource-based shading.

> I am inclined to
> make a small change that would only set the edgecolors if 'edgecolors' was
> not provided as a kwarg.  This would enable users to specify the edgecolor
> they want without worrying about something else over-riding it.  The only
> problem seems to be that there would be no shading of these grid lines.
> Would that still be acceptable to you?

Absolutely acceptable. In fact I think it is preferable not to shade them.

> Thanks for your valuable feedback!
> Ben Root

Thanks for being responsive to it :)
regards,
Gary

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[Matplotlib-users] Can I change pixel aspect with axes_grid

[gary ruben]

Usually imshow(arr, aspect='auto') or imshow(arr, aspect=2.0) will
display the image with pixels having some aspect ratio other than 1:1
However, I cannot get this to work when using imshow within an AxesGrid axis.
Is there a way to get an array shown with imshow() within an AxesGrid
axis to have a pixel aspect other than 1:1 ?
If not, is there a simple way to add a shared colorbar when using subplots() ?

Gary

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Re: [Matplotlib-users] Can I change pixel aspect with axes_grid

[gary ruben]

Thanks Eric and JJ,

Both of your answers are solutions to my problem actually.
I spent a while trying to figure this out and didn't get anywhere.
This was an exercise in frustration with matplotlib's documentation.
Thankfully this list and its members are here to save us. I assumed it
was just a simple flag or option I had missed and this turned out to
be the case. I had even tried setting aspect=False when creating my
AxesGrid object and setting aspect="auto", but because I was poking
around in the dark, I must not have set both at the same time. I also
thought I'd seen an example of this somewhere, which is what Eric
pointed out, but even thinking I'd seen it, I couldn't find it again.
I had looked in the gallery but missed the example - looking back at
the gallery now, I think it might be because every other related
example uses the jet colour scheme and it simply didn't register.

regards,
Gary

On Sat, Aug 20, 2011 at 6:49 PM, Jae-Joon Lee  wrote:
> If you want aspect="auto", this must also be set when you create ImageGrid.
> A simple example is attached.
> If you want a fixed aspect other than 1, it is doable but gets a bit
> tricky. Let me know if this is what you want.
>
> Regards,
>
> -JJ
>
>
>
> from mpl_toolkits.axes_grid1 import ImageGrid
>
> fig = plt.figure(1)
>
> grid = ImageGrid(fig, 111, (2, 1),
>                 aspect=False,
>                 label_mode='L', cbar_mode="single",
>                 )
>
> arr = np.arange(100).reshape((10, 10))
> im1 = grid[0].imshow(arr, aspect="auto")
> im2 = grid[1].imshow(arr, aspect="auto")
>
> grid[0].cax.colorbar(im1)
>
>
>
>
> On Sat, Aug 20, 2011 at 2:43 PM, gru...@bigpond.net.au
>  wrote:
>> Usually imshow(arr, aspect='auto') or imshow(arr, aspect=2.0) will
>> display the image with pixels having some aspect ratio other than 1:1
>> However, I cannot get this to work when using imshow within an AxesGrid axis.
>> Is there a way to get an array shown with imshow() within an AxesGrid
>> axis to have a pixel aspect other than 1:1 ?
>> If not, is there a simple way to add a shared colorbar when using subplots() 
>> ?
>>
>> Gary
>>
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Re: [Matplotlib-users] How do you Plot data generated by a python script?

[gary ruben]

As you show it, mass will be a string, so you'll need to convert it to
a float first, then add it to a list. You can then manipulate the
values in the list to compute your mean, or whatever, which matplotlib
can use as input to its plot() function or whichever type of plot
you're after. Alternatively, since the Python numpy module is made for
manipulating data like this, it can probably read your data in a
single function call and easily compute the things you want. However,
if you are really that new to programming, you may struggle, so I'd
suggest reading first going to scipy.org and reading up on numpy. When
you understand the basics of numpy, matplotlib's documentation should
make a lot more sense.

Gary

On Thu, Aug 25, 2011 at 6:48 AM, surfcast23  wrote:
>
> I am fairly new to programing and have a question regarding matplotlib. I
> wrote a python script that reads in data from the outfile of another program
> then prints out the data from one column.
>
> f = open( 'myfile.txt','r')
> for line in f:
> if line != ' ':
>  line = line.strip()       # Strips end of line character
>  columns = line.split() # Splits into coloumn
>  mass = columns[8]    # Column which contains mass values
>  print(mass)
>
> What I now need to do is have matplotlib take the values printed in 'mass'
> and plot number versus mean mass. I have read the documents on the
> matplotlib website, but they don't really address how to get data from a
> script(or I just did not see it) If anyone can point me to some
> documentation that explains how I do this it would be really appreciated.
>  Thanks in advance
>
> --
> View this message in context: 
> http://old.nabble.com/How-do-you-Plot-data-generated-by-a-python-script--tp32328822p32328822.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
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[Matplotlib-users] from pylab import * imports oldnumeric

[Gary Ruben]

I just picked up a problem posted over on the numpy list. I noticed that
from pylab import * is importing the oldnumeric-wrapper versions of
zeros(), ones() and empty(), and presumably other things too, into the
interactive namespace. Shouldn't it be picking up the versions from
numpy's main namespace for interactive use?

I picked this up because I use "ipython -pylab" and noticed that zeros()
etc. was generating integers instead of floats by default.

In ipython:

   Welcome to pylab, a matplotlib-based Python environment.
   For more information, type 'help(pylab)'.

In [1]: zeros?
Type:   function
Base Class: 
String Form:
Namespace:  Interactive
File:   c:\python24\lib\site-packages\numpy\oldnumeric\functions.py
Definition: zeros(shape, typecode='l', savespace=0, dtype=None)
Docstring:
 zeros(shape, dtype=int) returns an array of the given
dimensions which is initialized to all zeros


In [2]: import numpy as n

In [3]: n.zeros?
Type:   builtin_function_or_method
Base Class: 
String Form:
Namespace:  Interactive
Docstring:
 zeros((d1,...,dn),dtype=float,order='C')

Return a new array of shape (d1,...,dn) and type typecode with all
it's entries initialized to zero.

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Re: [Matplotlib-users] from pylab import * imports oldnumeric

[Gary Ruben]

Christopher Barker wrote:
 > Gary Ruben wrote:
 >> I just picked up a problem posted over on the numpy list. I noticed that
 >> from pylab import * is importing the oldnumeric-wrapper versions of
 >> zeros(), ones() and empty(), and presumably other things too, into the
 >> interactive namespace. Shouldn't it be picking up the versions from
 >> numpy's main namespace for interactive use?
 >
 > My understanding is that pylab (and Numerix) is maintaining backward
 > compatibility with itself, so the oldnumeric  form is the right one.
 >
 > Another reason NOT to EVER use "import *"

The way I tripped over this was using "ipython -pylab", which is doing 
this under the hood, so it's a little uglier in this case. What would be 
the effect on pylab using the newer numpy interactive namespace instead? 
I wonder whether matplotlib could check whether it has been imported by 
ipython interactively and import the newer namespace in this case, or 
whether there's a good argument for just dropping this little backward 
compatibility wart?

 > Before too long, hopefully we'll only have to deal with numpy.
 >
 > -Chris

I'll just cross-post Fernando (ipython) Perez's solution from the numpy 
list to aid anyone else who falls into this trap:

--

Until mpl drops support for the compatibility layers, you may want to
set up a simple pylab profile.  In ~/.ipython make a file called
'ipythonrc-pylab' consisting of:

###
# Load default config
include ipythonrc

# Add single-line python statements here
execute from numpy import *


Since pylab does a 'from .num?. import *' this will ensure that the
top-level visible functions are the current numpy ones, not the
compatibility layer ones.  You then start things with:

ipython -pylab -p pylab

and you'll get:

In [1]: zeros?
Type:   builtin_function_or_method
Base Class: 
Namespace:  Interactive
Docstring:
 zeros((d1,...,dn),dtype=float,order='C')

 Return a new array of shape (d1,...,dn) and type typecode with all
 it's entries initialized to zero.



Not ideal, but it's a little hack that will work in practice until we
finish crossing the muddy river of backwards compatibility.

Cheers,

f

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Re: [Matplotlib-users] Protocol for unanswered queries on this list?

[Gary Ruben]

Derek Hohls wrote:
> Hi
>  
> I appreciate that this is a totally voluntary support list, but
> I was wondering what the protocol was when queries that
> I have posted go unanswered...
>  
> Should I -
> (a) repost them "as is"?
> (b) rewrite them slightly and post them again

Probably the best approach.

> (c) assume no one has any interest in answering them (and give up)
> (d) something else??
>  
> The queries I am referring to are:
> http://sourceforge.net/mailarchive/message.php?msg_id=38032560 
> and
> http://sourceforge.net/mailarchive/message.php?msg_id=38021694 
>  
> (The latter especially, I am sure is within matplotlib current
> capabilities... and a hint or two will set me on the right track!)
>  
> Thanks
> Derek

I had a quick look and for the first part of the second question:

> (a) what is the syntax for the fill() command - I have tried
> ax.fill(0.5,0.5,'b') and get an error:
> TypeError: zip argument #1 must support iteration

The TypeError is saying that the argument expected should be a Python 
type supporting iteration, such as a numpy array, a list or a tuple. 
i.e. this produces a rectangle:

ax.fill([1,1,2,2],[3,4,4,3],'b')

where the two lists contain the x- and y-coordinate polygon vertices, 
respectively, ordered clockwise from the lower left.

It would take me a bit of mucking around to work out what the bar 
coordinates are - hopefully an expert will pipe in with the answer. You 
probably need to work out how to apply the get_verts method to the patch 
collection. I find using ipython interactively is the best way to learn 
to do this.

Gary R.

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Re: [Matplotlib-users] matlab, idle, interactivity and teaching

[Gary Ruben]

I have to agree with Giorgio in general. Unfortunately, the threading 
support required by matplotlib isn't implemented in pyScripter, which 
means that it's a nice environment until you want to do some plotting, 
when it becomes a bit flaky. I haven't checked eclipse's behaviour with 
matplotlib.

Gary R.

Giorgio F. Gilestro wrote:
> A really great IDE for windows users is pyScripter (
> http://mmm-experts.com/Products.aspx?ProductId=4 )
> It's probably the best I could try so far (and it's free).
> 
> cheers
> 
> On 3/30/07, Tim Hirzel <[EMAIL PROTECTED]> wrote:
>> As for a good IDE. I really like eclipse with pydev.  For easy
>> student/beginner setup, easyclipse has a nice python eclipse distribution
>>
>> http://www.easyeclipse.org/site/distributions/index.html
>>
>> I think I've tried near every python IDE setup out there over the last
>> couple years, and this one wins for me.
>>
>> tim

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Re: [Matplotlib-users] confusion about what part of numpy pylab imports

[Gary Ruben]

Hi Mark,
this thread may help:
http://thread.gmane.org/gmane.comp.python.numeric.general/13399/focus=13421

Essentially, pylab uses a compatibility layer to ease the task of 
supporting the three array packages - currently this uses the Numeric 
version of the ones and zeros functions giving the behaviour you observe 
- this will be fixed when pylab drops support for the older packages, 
which should be soon.

Gary R.

Mark Bakker wrote:
> Hello list -
> 
> I am confused about the part of numpy that pylab imports.
> Apparently, pylab imports 'zeros', but not the 'zeros' from numpy, as it 
> returns integers by default, rather than floats.
> The same holds for 'ones' and 'empty'.
> Example:
>  >>> from pylab import *
>  >>> zeros(3)
> array([0, 0, 0])
>  >>> from numpy import *
>  >>> zeros(3)
> array([ 0.,  0.,  0.])
> 
> Can this be fixed? Any explanation how this happens? Pylab just imports 
> part of numpy, doesn't it?
> 
> Thanks,
> 
> Mark


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Re: [Matplotlib-users] basemap stereographic projection problem

[Gary Ruben]

Many thanks for the special case code Jeff,
This appears to work well.
I see you picked up on our confusion about the -180 to 180 longitude 
range. I'll pass this on and look at clipping the lines outside the 
circle later,
regards,
Gary

Jeff Whitaker wrote:
> [EMAIL PROTECTED] wrote:
>> I've been trying to help a friend who wants to plot directional data 
>> on a "Wulff net" 
>> <http://en.wikipedia.org/wiki/Pole_figure#Geometry_in_the_pole_figure>, 
>> which is a stereographic projection plot. She wants to plot points 
>> specified by latitude and longitude in degrees. We hoped to be able to 
>> use the basemap toolkit's "stere" plot, centred at lat_0=0, lon_0=0, 
>> with limits set at +/-90deg lat and +/-180deg lon, but we keep getting 
>> tracebacks and I wondered whether this is possible, based on a comment 
>> from Jeff Whitaker 
>> <http://www.nabble.com/-basemap--stereographic-projection-bounding-boxes-tf2170166.html#a6000978>
>>  
>> which implies that basemap's stereographic projection code can't 
>> handle these default limits. Is this the case? Would it be asking too 
>> much to request a small sample of generating some Wulff-net axes? 
>> Plotting points on these seems simple enough. We started with the 
>> polarmaps.py example and the code below is as close as we could get. 
>> Any suggestions would be welco
>>  me.
>>
>> Gary Ruben
>>
>> -- 
>>
>> from matplotlib.toolkits.basemap import Basemap
>> from pylab import *
>>
>> # loop over projections, one for each panel of the figure.
>> fig = figure(figsize=(4,4))
>> # setup map projection
>> m = 
>> Basemap(projection='stere',lat_0=0.,lon_0=0.,llcrnrlat=-50.,llcrnrlon=-120., 
>> urcrnrlat=90., urcrnrlon=90.)
>>ax = fig.add_subplot(1,1,1)
>> # draw parallels and meridians.
>> m.drawparallels(arange(-180.,180.,10.))
>> m.drawmeridians(arange(-90.,90.,10.))
>> # draw boundary around map region.
>> m.drawmapboundary()
>> show()
>>
>>
>> -
> Gary:
> 
> How about this?
> 
> import pylab as p
> from matplotlib.toolkits.basemap import Basemap
> from matplotlib.patches import Circle, Polygon
> w=25483988.0
> map = Basemap(lon_0=0,lat_0=0,projection='stere',width=w,height=w)
> print map.llcrnrlat,map.llcrnrlon,map.urcrnrlat,map.urcrnrlon
> map.drawparallels(p.arange(-80,81,10))
> map.drawmeridians(p.arange(-90,91,10))
> ax = p.gca()
> circ = Circle(map(0,0),0.5*w)
> circ.set_fill(False)
> circ.set_edgecolor('k')
> circ.set_linewidth(1.0)
> circ.set_clip_on(True)
> ax.add_patch(circ)
> #ax.set_frame_on(False)
> p.show()
> 
> It should be possible to get rid of the lines extending outside the 
> circular region by filling the region between the circle and the 
> bounding square.
> 
> HTH,
> 
> -Jeff


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[Matplotlib-users] contourf question

[Gary Ruben]

I'm notice that contourf behaves differently to contour by default in 
where it decides to position contours. For example, using pylab, if you try

a=tri(10)
contourf(a,0)
contour(a,1)

I'd have expected the contours to line up, but they don't. Is there a 
way to get contourf to place its contours at the same position as contour?

thanks,
Gary

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Re: [Matplotlib-users] IDL Font question

[Gary Ruben]

IDL uses the Hershey vector fonts


The problem is that these are not trutype fonts, so the easiest solution 
is probably to find some free sans-serif font that looks close to 
Hershey on a free font site.

HTH,
Gary R.

Jose Gomez-Dans wrote:
> Hi,
> Some colleagues have sent some plots which they generated using IDL
> (boo!!! hiss!! :D), and they look quite dissimilar to my matplotlib
> ones. I would like to mimic their layout as much as possible, which so
> far is a success. The only problem is that I don't know what font to
> use. In IDL, I believe it is called "Roman" (there's an smudged
> example here: ).
> Does anyone know a suitable alternative?
> 
> Thanks!
> Jose

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[Matplotlib-users] pylab axis query and possible bug

[Gary Ruben]

Hi listees,

I often generate plots using the pylab interface plot() function to 
overlay an imshow() image. The minimal script below demonstrates a 
problem, which may be a bug, or may be a deliberate change introduced 
into mpl 0.91.1. It works fine with mpl 0.90.1 but gives a traceback 
with 0.91.1 - it seems not to be happy with the subplot limits. 
Commenting out the "note 1" line lets it run and demonstrates my real 
question. With scatter(), the first subplot doesn't rescale, but if line 
"note 2" is commented out and "note 3" is uncommented, it rescales. How 
do I prevent the rescaling? I prefer plot() instead of scatter() in this 
case because of the plot origin.

thanks,
Gary R.

--

from pylab import *

rcFig = {'figsize': (2,1),
  'dpi': 256,
  'subplot.hspace': 0.0,
  'subplot.wspace': 0.0,
  'subplot.bottom': 0.0,
  'subplot.left':   0.0,
  'subplot.right':  1.0,
  'subplot.top':1.0,
  }
rc('figure', **rcFig)# note 1

subplot(121)
axis('off')
imshow(rand(20,20))
subplot(122)
axis('off')
imshow(rand(20,20))
subplot(121)
scatter([5,10],[5,10])# note 2
#~ plot([5,10],[5,10], 'o') # note 3
show()

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[Matplotlib-users] pylab axis query and possible bug

[Gary Ruben]

Retrying. Sorry if this appears twice.

Hi listees,

I often generate plots using the pylab interface plot() function to
overlay an imshow() image. The minimal script below demonstrates a
problem, which may be a bug, or may be a deliberate change introduced
into mpl 0.91.1. It works fine with mpl 0.90.1 but gives a traceback
with 0.91.1 - it seems not to be happy with the subplot limits.
Commenting out the "note 1" line lets it run and demonstrates my real
question. With scatter(), the first subplot doesn't rescale, but if line
"note 2" is commented out and "note 3" is uncommented, it rescales. How
do I prevent the rescaling? I prefer plot() instead of scatter() in this
case because of the plot origin.

thanks,
Gary R.

--

from pylab import *

rcFig = {'figsize': (2,1),
  'dpi': 256,
  'subplot.hspace': 0.0,
  'subplot.wspace': 0.0,
  'subplot.bottom': 0.0,
  'subplot.left':   0.0,
  'subplot.right':  1.0,
  'subplot.top':1.0,
  }
rc('figure', **rcFig)# note 1

subplot(121)
axis('off')
imshow(rand(20,20))
subplot(122)
axis('off')
imshow(rand(20,20))
subplot(121)
scatter([5,10],[5,10])# note 2
#~ plot([5,10],[5,10], 'o') # note 3
show()

--



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Re: [Matplotlib-users] pylab axis query and possible bug

[Gary Ruben]

Beautiful!
Many thanks John.

Gary R.

John Hunter wrote:

> You can manually turn off autoscaling on the axes instance with the
> following, and both scatter and plot should then work as you want.
> 
> ax1 = subplot(121)
> axis('off')
> ax1.imshow(rand(20,20))
> ax2 = subplot(122)
> axis('off')
> ax2.imshow(rand(20,20))
> 
> ax1.set_autoscale_on(False)
> #ax1.scatter([5,10],[5,10])# note 2
> ax1.plot([5,10],[5,10], 'o') # note 3
> show()

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Re: [Matplotlib-users] scatter plot onto background image

[Gary Ruben]

Hi Jibo,

I'm not sure of your reasons for wanting to do this, but you might find
the psychopy package of interest:
http://www.psychopy.org/

Gary R.

He Jibo wrote:
> Hi, Everyone,
>  
> I want to create a scatter plot onto a background image. Anybody could 
> help me?Thank you!
>  
> The background.PNG is shown full screen with a resolution of 1024*768. 
> The data in the fixation_xy.txt is the coordinates of eye-movement data, 
> first column for X axis, second column for Y axis. I wish to do a 
> scatter plot with the data onto background.PNG. Please give me a helping 
> hand how could I do this with matplotlib.
>  
> Thank you !
>  
> Jibo
>  
> 
> 
> -- 
> Best Regards,
> 
>  He Jibo
> [EMAIL PROTECTED] 
> 
> [EMAIL PROTECTED] 

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Re: [Matplotlib-users] automatically choose line markers/styles?

[Gary Ruben]

Just an idea: Maybe you could also auto cycle between dash types if only 
the colour and not the dash type is specified in a plot command. The 
gnuplot default would be one model, or the predefined patterns in 
CorelDraw or Inkscape etc. Personally I don't see this as a high 
priority though.

Gary R.


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Re: [Matplotlib-users] wx backend scaling problem

[Gary Ruben]

Gary Ruben wrote:

The attached test.py

Oops. Here it is.
Gary R.
import matplotlib as mpl
#~ mpl.use('PDF')
#~ mpl.use('Agg')
#~ mpl.use('TkAgg')
mpl.use('WXAgg')
#~ mpl.use('SVG')
#~ mpl.use('PS')
from pylab import *

pts = 128
rcFig = {'figsize': (2,1),
 'dpi': pts,
 'subplot.hspace': 0.0,
 'subplot.wspace': 0.0,
 'subplot.bottom': 0.0,
 'subplot.left':   0.0,
 'subplot.right':  1.0,
 'subplot.top':1.0,
 }
rc('figure', **rcFig)

subplot(121)
axis('off')
imshow(rand(pts,pts))

subplot(122)
axis('off')
imshow(tri(pts))

savefig('test',dpi=pts)
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Re: [Matplotlib-users] wx backend scaling problem

[Gary Ruben]

Hi Michael,

Michael Droettboom wrote:
> Well, that was a good puzzle!

Glad I got your neurons firing.

> This seems like a safe fix to me, but anyone who currently extends the 
> Wx Frame (meaning the whole window etc.) and is unknowingly compensating 
> for this effect may have problems after my change.

Many thanks for looking at this. I applied your fix and it works for me.

Gary R.

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Re: [Matplotlib-users] 3d bar plots

[Gary Ruben]

Hi Jonathan,
A couple of people have suggested trying pyqwt. Since the answer is that 
matplotlib won't do it, why not just use DISLIN?
Gary

Jonathan Taylor wrote:
> 
> Hi,
> 
> Was wondering if anyone knows if there was any way to reproduce this 
> kind of
> example:
> 
> http://www.mps.mpg.de/dislin/exa_bars3d.html
> 
> i.e. a 3d barplot.
> 
> Thanks,
> 
> Jonathan


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Re: [Matplotlib-users] Improved dashing for black and white plots?

[Gary Ruben]

On this topic, here is something I used the other day (just some 
different dash sequences):

e, = plot(x, y, 'k', label=r'$\theta_3=%1.2f$'%(th3))
setp(e, dashes={0:(1,0), 1:(2,2), 2:(10,4), 3:(10,4,4,4), 4:(10,2,2,2), 
5:(15,2,6,2)}[i])

Maybe we should just blatantly copy the gnuplot sequence, although the 
sequence might be gpl'ed!
One question which arises is that it wasn't clear what to set dashes to 
to get a solid line. I ended up doing the 0: case above i.e. (1,0), but 
I suspect this isn't ideal because it might generate lots of unwanted 
line segments. I think I tried None and (1) and it didn't work. Perhaps 
(999,0) would be better?

Gary R.


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Re: [Matplotlib-users] problem with enthon's mpl.

[Gary Ruben]

Hi Rob,

A couple of us reported this last week on the scipy list and I think it 
should be fixed in the version which was just released by Enthought, so 
if your friend will persevere and grab the latest version, it should be 
OK - I hope to try it out today.

Gary R.

Rob Hetland wrote:
> 
> I am trying to help somebody get going on numpy/scipy/mpl.  She is 
> having trouble when starting enthon's matplotlib.  She is a PC user (I 
> am a unix/mac person), so I really don't know where to start finding the 
> problem.  Below is her note to me.  Any advice would be helpful.
> 
> 
> """
> I got the enthought python etc. distribution (dated 7/5/06) again after
> talking to you, and still get the same error with "from pylab import *"
> Unfortunately, I can't grab the text from the ipython shell window, but
> the gist is that pylab.m, tries to import Xaxis and Yaxis from axis,
> axis.py tries to get FontProperties from font_manager.py, which in turn
> looks for ft2font in matplotlib.   Which is where the error message box
> saying "entry point _ctype could not be located in the dll lib
> msvcr71.dll" gets created.  Maybe we should get another dummy tester to
> try it.  My system has several mscvr71.dll's and it's probably choosing to
> use the wrong one
> """


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Re: [Matplotlib-users] Can you set numerix in a script?

[Gary Ruben]

Christopher Barker wrote:
> To script that test, I need to be able to set numerix in a script, 
> rather than in matplotlibrc. Can that be done?

Yep, just do

from pylab import *
rcParams['numerix'] = 'numpy'

> While we're at it, it would be great if ANY of the config items in 
> matplotlibrc could, instead, be set at run time in a script. I now a 
> number of them can, but is there a standard way to do, and will it work 
> with ALL the items in there?

rcParams is the standard way and I think works for all items.

> Another note: it seems that numerix is very good at taking input from 
> any of the Num* packages, regardless of which one is being used 
> internally. Given that, I'm thinking of aiming for the future with my 
> OS-X package, and just using numpy, and not bothering to build in 
> support for the other two. any thoughts.
> 
> -Chris

If I was developing something now, I would only bother supporting numpy.

Gary R.


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Re: [Matplotlib-users] problem with enthon's mpl.

[Gary Ruben]

I tried it out and it is fixed in the latest Enthought release 1.0.0beta4

Gary Ruben wrote:
> Hi Rob,
> 
> A couple of us reported this last week on the scipy list and I think it 
> should be fixed in the version which was just released by Enthought, so 
> if your friend will persevere and grab the latest version, it should be 
> OK - I hope to try it out today.
> 
> Gary R.
> 
> Rob Hetland wrote:
>> I am trying to help somebody get going on numpy/scipy/mpl.  She is 
>> having trouble when starting enthon's matplotlib.  She is a PC user (I 
>> am a unix/mac person), so I really don't know where to start finding the 
>> problem.  Below is her note to me.  Any advice would be helpful.
>>
>>
>> """
>> I got the enthought python etc. distribution (dated 7/5/06) again after
>> talking to you, and still get the same error with "from pylab import *"
>> Unfortunately, I can't grab the text from the ipython shell window, but
>> the gist is that pylab.m, tries to import Xaxis and Yaxis from axis,
>> axis.py tries to get FontProperties from font_manager.py, which in turn
>> looks for ft2font in matplotlib.   Which is where the error message box
>> saying "entry point _ctype could not be located in the dll lib
>> msvcr71.dll" gets created.  Maybe we should get another dummy tester to
>> try it.  My system has several mscvr71.dll's and it's probably choosing to
>> use the wrong one
>> """



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Re: [Matplotlib-users] histogram bug

[Gary Ruben]

Note: I just verified that this was introduced into 0.87.4.
0.87.3 doesn't exhibit the problem. See attachment.

Gary R.

[EMAIL PROTECTED] wrote:

The following minimal script reveals a rendering problem with displaying a 
histogram on a log vertical axis.
I'm using matplotlib0.87.4 in WinXP with python 2.3.5 Enthon.

from pylab import *
hist(rand(100), 20, bottom=1)
setp(gca(), yscale="log")
show()


Gary R.




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Re: [Matplotlib-users] Weird resizing issue

[Gary Ruben]

I see weird behaviour like this in Windows too. In my case, the 
horizontal size of the plot window increases as the pointer is moved 
inside a plot region. i.e. the aspect ratio of the window changes 
erratically, I think between two sizes. Sometimes it remains at the 
incorrect shape when the mouse pointer is shifted outside the plot area 
and sometimes it pops back to the correct shape. Is this the behaviour 
you see? I don't know how to avoid it. I noticed that shifting the 
pointer out of the plot area by moving through the bottom of the window 
seems to avoid the possibility of the window remaining with the 
incorrect aspect. I seem to remember seeing this behaviour on an old 
version of matplotlib. I thought it disappeared and has perhaps 
returned. My memory is hazy on this.

Gary R.

Tommy Grav wrote:
> I am using matplotlib to display a couple of fits-images and then use
> the mouse to select a source in the image. However, when I click on
> the window containing the image to get it into focus the window starts
> resizing itself based on the movement of the mouse. I am on a mac
> with OS 10.4 and are using TkAgg. Has anyone seen this before and
> know how to avoid it from happening?
> 
> Cheers
>Tommy
> 
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Re: [Matplotlib-users] histogram bug

[Gary Ruben]

More information on this bug: on my WinXP laptop, it seems to only 
manifest under some circumstances. When running the script from inside 
SciTE or ipython, it seems more or less repeatable (sometimes it won't 
show on the first run but does from then on), but if the .py file is run 
directly from the windows explorer, it doesn't show up. On my win98 
desktop, however, it shows up regardless.

Gary Ruben wrote:
> Note: I just verified that this was introduced into 0.87.4.
> 0.87.3 doesn't exhibit the problem. See attachment.
> 
> Gary R.
> 
> [EMAIL PROTECTED] wrote:
>> The following minimal script reveals a rendering problem with 
>> displaying a histogram on a log vertical axis.
>> I'm using matplotlib0.87.4 in WinXP with python 2.3.5 Enthon.
>>
>> from pylab import *
>> hist(rand(100), 20, bottom=1)
>> setp(gca(), yscale="log")
>> show()
>>
>>
>> Gary R.


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Re: [Matplotlib-users] Creating Dendrograms

[Gary Ruben]

Perhaps NetworkX  will do what you want, 
depending on how much control you need over the node placement. There 
are a few more suggestions for general graph plotting solutions here:
.
hth
Gary R.

R. Padraic Springuel wrote:
> Can Matplotlib create dendrograms?  As best I can tell, there isn't a 
> plotting function for doing so directly, but maybe one could make one by 
> combining a series of commands.  Has anyone done this?  Does anyone know 
> if it is possible, or if there is another package that would do the job 
> if it isn't?

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[Matplotlib-users] problems with vector output formats

[Gary Ruben]

There may be problems i.e. bugs in the eps and svg backends, as I often 
try (sometimes unsuccessfully) to edit these in inkscape and/or 
CorelDraw and sometimes, but not always, get 'badly formed eps file' 
messages from Corel, or spurious lines appearing in svg files in 
inkscape and Corel, for example. Do others get this too?

A suggestion:
When saving in a vector format, is it possible to remove objects totally 
outside the bounding box from the output files in some smart way? I 
guess this is currently left up to the individual backends to decide on, 
but perhaps implementing some filtering functions for the backends to 
use would encourage their use and help make output files smaller.

Gary R.

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[Matplotlib-users] zorder of legend

[Gary Ruben]

While I think of it, I think the default zorder of legends should be 
bigger so that, by default it overlays all plot lines and symbols.

Gary R.

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Re: [Matplotlib-users] zorder of legend

[Gary Ruben]

Sorry John,

I see this was fixed a while ago - I was still using 0.87.3 from the 
last Enthought edition. Now that there's a scipy installer, I should 
upgrade numpy/scipy/mpl to something more current.

Gary R.

Gary Ruben wrote:
> While I think of it, I think the default zorder of legends should be 
> bigger so that, by default it overlays all plot lines and symbols.
> 
> Gary R.

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Re: [Matplotlib-users] Problem with savefig and usetex

[Gary Ruben]

I haven't tried it, but my guess is the '\' character is the problem.

> pylab.xlabel('10$^3$ M$_\odot$')

Try
pylab.xlabel(r'10$^3$ M$_\odot$')
  ^
  Add raw string marker.

or maybe
pylab.xlabel('10$^3$ M$_\\odot$')

Gary R.

Nicolas Champavert wrote:
> Hello,
> 
>   I have some problems when trying to save a figure with usetex=True. 
> Sometimes, it is not possible to save the figure when trying to put an 
> xlabel with LaTeX inside.
> It works with pylab.xlabel('M$_\odot$') but not with 
> pylab.xlabel('10$^3$ M$_\odot$') (see below). Do you know why ?



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