matplotlib-users Mailing List for matplotlib

Hi:
I am trying to make a 1row by 3 column plot with subplot, and I want
the first plot (subplot(131)) to have equal aspect ratio, but the rest
can auto scale.
My code results in an empty plot for the 1st column subplot whenever I
try to use the set_aspect('equal')
Any ideas?
Thanks
John
figure(1)
hold(True)
subplot(131)
plot(RX,RY)
title('Geometry')
xlabel('um')
ylabel('um')
scatter(AX,AY,c='green',marker='s')
plot([AX,0],[AY,0],linewidth=3,c='green')
scatter(BX,BY,c='purple',marker='s')
plot([0,BX],[0,BY],linewidth=3,c='purple')
scatter(DX,DY,c='red',marker='o')
axes().set_aspect('equal')
hold(False)
subplot(132)
scatter(e1.real,gi,marker='s')
title('E1 by tooth')
subplot(133)
scatter(e2.real,gi,marker='+')
title('E2 by tooth')
show()

HI,
 
Is there a way to get the size of the bounding box for the axes which
includes the axes labels and tick marks? It looks like
Axes.get_position/set_position refers to the inner position (i.e the actual
plot area).
 
 
In matlab (http://www.mathworks.com/help/techdoc/ref/axes_props.html) this
was the outer and inner position of an axes. I would like to get the outer
position (i.e the yellow box in
http://www.mathworks.com/help/techdoc/ref/axes_props.html)
 
Thanks
Jeremy
 
Jeremy Lewi
Engineering Scientist
The Intellisis Corporation
jl...@in...
 

Same here.
-paul h.
On Fri, Sep 17, 2010 at 2:21 PM, Jeffrey Blackburne
<jbl...@gm...> wrote:
> I get a solid line for plt.step like you do.
>
> MPL 1.0.0, SVN revision 8657.
>
> -Jeff
>
>
> On Sep 17, 2010, at 4:34 PM, Gökhan Sever wrote:
>
>> Hello,
>>
>> Can someone confirm me if this creates a dashed line for a simple step plot?
>>
>> # this is fine
>> plt.plot(range(10), "g--")
>>
>> # plots solid line!
>> plt.step(range(10), "g--")
>>
>> Thanks,
>>
>> --
>> Gökhan
>> ------------------------------------------------------------------------------
>> Start uncovering the many advantages of virtual appliances
>> and start using them to simplify application deployment and
>> accelerate your shift to cloud computing.
>> http://p.sf.net/sfu/novell-sfdev2dev_______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
> ------------------------------------------------------------------------------
> Start uncovering the many advantages of virtual appliances
> and start using them to simplify application deployment and
> accelerate your shift to cloud computing.
> http://p.sf.net/sfu/novell-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

I get a solid line for plt.step like you do.
MPL 1.0.0, SVN revision 8657.
-Jeff
On Sep 17, 2010, at 4:34 PM, Gökhan Sever wrote:
> Hello,
> 
> Can someone confirm me if this creates a dashed line for a simple step plot?
> 
> # this is fine
> plt.plot(range(10), "g--")
> 
> # plots solid line!
> plt.step(range(10), "g--")
> 
> Thanks,
> 
> -- 
> Gökhan
> ------------------------------------------------------------------------------
> Start uncovering the many advantages of virtual appliances
> and start using them to simplify application deployment and
> accelerate your shift to cloud computing.
> http://p.sf.net/sfu/novell-sfdev2dev_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

Hello,
Can someone confirm me if this creates a dashed line for a simple step plot?
# this is fine
plt.plot(range(10), "g--")
# plots solid line!
plt.step(range(10), "g--")
Thanks,
-- 
Gökhan

teq-2 wrote:
> 
> 
> Has anyone ever added a print button to the pyplot toolbar? And in general
> how is it possible to modify that toolbar instead of creating a new one?
> 
> -Tim
> 
> 
The actual toolbar is defined in the backend. It is not difficult to modify
it.
For the Qt4agg backend on windows look for NavigationToolbar2QT in:
c:\Python26\Lib\site-packages\matplotlib\backends\backend_qt4.py
-- 
View this message in context: http://old.nabble.com/pyplot-toolbar-tp29741179p29741292.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Is there a way to set the legend font color? I am plotting multiple sets of
data using different colors. I basically want to set each legend font color
the same as the corresponding data line color. Here is an example.
x = arange(0,10,0.1)
y1 = sin(x)
y2 = cos(x)
plot(x,y1,'r-',x,y2,'b--')
I want the legend font for y1 to be in red and the legend font for y2 to be
in blue. 
Can anybody help? Thanks.
-- 
View this message in context: http://old.nabble.com/legend-font-color-tp29741260p29741260.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Has anyone ever added a print button to the pyplot toolbar? And in general
how is it possible to modify that toolbar instead of creating a new one?
-Tim

mm.to_rgba(var.flat) doesn't work as plot_surface facecolors, but 
mm.to_rgba(var) does!
Thanks for the hint
mma
Benjamin Root wrote:
> On Fri, Sep 17, 2010 at 8:59 AM, Martinho MA <mm...@ua... 
> <mailto:mm...@ua...>> wrote:
>
> Hello
>
> I am trying to calculate the facecolors for the Axes3D.plot_surface
> function, to have something similar to matlab surf 4th argument!!
> Something like plot_surface(x,y,z,facecolors=calc_colors(v))
>
> So, I need to obtain the colors corresponding to the values of v! I
> created the function calc_colors:
>
>
> import pylab
> import numpy as np
> from matplotlib.colors import rgb2hex
>
> def calc_colors(var):
> colors = np.empty(var.shape, dtype='S7')
> mm=pylab.cm.ScalarMappable()
> mm.set_clim((var.min(),var.max()))
> mm.set_cmap(pylab.cm.jet)
> colors.flat= [rgb2hex(mm.to_rgba(k)[:-1]) for k in var.flat]
> return colors
>
>
> Well I believe this is not the smartest way to calculate the colors !!
> At least it is quite slow !
> Can someone give me a better solution for this problem?
>
> than you
> mma
>
>
> I might be wrong, but can't mm.to_rgba() take var.flat as an input, 
> thereby giving you an array of colors as output? Also, I don't think 
> it is necessary to call rgb2hex() because matplotlib will just convert 
> that hex back into rgba. I believe you should be able to just return 
> the result of mm.to_rgba(var.flat).
>
> I hope that helps,
> Ben Root
>

Hi folks,
I have a data set that is in the form of an irregular 2D grid with
associated values, one for each node. I would like to plot this as a
raised surface, with colours that indicate the z-value. Somehow I
didn't find just quite the example I was looking for. After digging
around in the matplotlib and mpl_toolkits.mplot3d I was able to solve
the problem. To save the next person the trouble, here is my
annotated example. Comments and improvements are most welcome. I'd
be happy to have a version of this included as an official example, if
it passes muster.
Please note that randomly tesselating like this does generate dodgy
surfaces occasionally, but that's the nature of any Delaunay
triangulation in a case like this one.
Best regards
-- Simon
#!/usr/bin/python
#
# Demonstration of how to plot a triangulated surface.
#
# We randomly tesselate the (x,y) plane and compute two quadratic functions
# over those points. The plot displays the two surfaces, each coloured by the
# average z-location of the triangle.
#
import random as rn
import numpy as np
# Matplot lib and its associated toolkits
import matplotlib.delaunay     as dl
import mpl_toolkits.mplot3d.art3d as ar3
import mpl_toolkits.mplot3d.axes3d as ax3
import matplotlib.pyplot      as plt
# Generate 200 random points between -2.0 and 2.0.
x = np.empty( [ 204 ] )
y = np.empty( [ 204 ] )
x[0:200] = np.random.uniform( -2.0, 2.0, [200] )
y[0:200] = np.random.uniform( -2.0, 2.0, [200] )
# Put corners on the range for interest
x[200:204] = [ -2.0,-2.0, 2.0, 2.0 ]
y[200:204] = [ -2.0,-2.0, 2.0, 2.0 ]
# Create a triangulation of our region. We will re-use this for both curves.
circumcenters, edges, tri_points, tri_neighbors = dl.delaunay(x, y)
# Compute the first function of (x,y)
z = 2.0 - 1.0 * ( x[:]**2 + y[:]**2 ) - 0.5*y[:]
# Construct the triangles for the surface.
verts = ( [ np.array( [ [ x[ t[0] ] , y[ t[0] ] , z[ t[0] ] ]
           , [ x[ t[1] ] , y[ t[1] ] , z[ t[1] ] ]
           , [ x[ t[2] ] , y[ t[2] ] , z[ t[2] ] ] ] )
      for t in tri_points
     ]
    )
# To get a coloured plot, we need to assign a value to each face that dictates
# the colour. In this case we'll just use the average z co-ordinate of the
# three triangle vertices. One of these values is required for each face
# (triangle).
z_color = np.array( [ ( np.sum( v_p[:,2] ) / 3.0 ) for v_p in verts ] )
# Choiced for colour maps are :
#  autumn bone cool copper flag gray hot hsv jet pink prism spring summer
#  winter spectral
cmhot = plt.cm.get_cmap("hot")
# Our triangles are now turned into a collection of polygons using the vertex
# array. We assign the colour map here, which will figure out its required
# ranges all by itself.
triCol = ar3.Poly3DCollection( verts, cmap=cmhot )
# Set the value array associated with the polygons.
triCol.set_array  ( z_color )
# Let's repeat the process for a second function.
z2 = 2.0 + 1.0 * ( x[:]**2 + y[:]**2 ) - 0.5*y[:]
# Construct the vertices, this time re-using the triangulation but using a new
# z co-ordinate.
verts2 = ( [ np.array( [ [ x[ t[0] ] , y[ t[0] ] , z2[ t[0] ] ]
            , [ x[ t[1] ] , y[ t[1] ] , z2[ t[1] ] ]
            , [ x[ t[2] ] , y[ t[2] ] , z2[ t[2] ] ] ] )
      for t in tri_points
     ]
    )
# We require a new array of values that will tell our colour map what to do.
z2_color = np.array( [ ( np.sum( v_p[:,2] ) / 3.0 ) for v_p in verts ] )
# Let's choose a different colour map this time.
cmjet = plt.cm.get_cmap("jet")
# We need a new set of 3D polygons, since this is a new surface.
triCol2 = ar3.Poly3DCollection( verts2, cmap=cmjet )
# Let's set the edge colour to black and make the triangle edges into thicker,
# dashed lines. Then we assign the array of values that will be used to colour
# the surface.
triCol2.set_edgecolor('k')
triCol2.set_linewidth( 2.0 )
triCol2.set_linestyle( 'dashed' )
triCol2.set_array( z2_color )
# Create the plotting figure and the 3D axes.
fig = plt.figure()
ax = ax3.Axes3D(fig)
# Add our two collections of 3D polygons directly. The collections have all of
# the point and color information. We don't need the add_collection3d method,
# since that method actually converts 2D polygons to 3D polygons. We already
# have 3D polygons.
ax.add_collection( triCol )
ax.add_collection( triCol2 )
# Add a label, for interest
ax.text3D( 0.0, 0.0, 2.1, "Peak/Trough" )
# If we don't bound the axes correctly the display will be off.
ax.set_xlim3d(-2, 2)
ax.set_ylim3d(-2, 2)
ax.set_zlim3d( np.min(z), np.max(z2) )
# We could also print to a file here.
plt.show()
--
1129 Ibbetson Lane
Mississauga, Ontario#!/usr/bin/python
L5C 1K9    Canada

On Fri, Sep 17, 2010 at 8:59 AM, Martinho MA <mm...@ua...> wrote:
> Hello
>
> I am trying to calculate the facecolors for the Axes3D.plot_surface
> function, to have something similar to matlab surf 4th argument!!
> Something like plot_surface(x,y,z,facecolors=calc_colors(v))
>
> So, I need to obtain the colors corresponding to the values of v! I
> created the function calc_colors:
>
>
> import pylab
> import numpy as np
> from matplotlib.colors import rgb2hex
>
> def calc_colors(var):
> colors = np.empty(var.shape, dtype='S7')
> mm=pylab.cm.ScalarMappable()
> mm.set_clim((var.min(),var.max()))
> mm.set_cmap(pylab.cm.jet)
> colors.flat= [rgb2hex(mm.to_rgba(k)[:-1]) for k in var.flat]
> return colors
>
>
> Well I believe this is not the smartest way to calculate the colors !!
> At least it is quite slow !
> Can someone give me a better solution for this problem?
>
> than you
> mma
>
>
I might be wrong, but can't mm.to_rgba() take var.flat as an input, thereby
giving you an array of colors as output? Also, I don't think it is
necessary to call rgb2hex() because matplotlib will just convert that hex
back into rgba. I believe you should be able to just return the result of
mm.to_rgba(var.flat).
I hope that helps,
Ben Root

Hello Tony,
thanks a lot for the code, I'll try it out !
Regards,
Erik
On Fri, 2010年09月17日 at 09:46 -0400, Tony S Yu wrote:
> On Sep 17, 2010, at 8:58 AM, Erik Janssens wrote:
> 
> > Hi,
> > 
> > I'm using matplotlib in a pyqt context, as described
> > in the book 'Matplotlib for python developers'.
> > 
> > When the window is large enough, everything works
> > fine, but when the window is too small part of
> > the x-axis labels get chopped.
> > 
> > Is there a way to prevent this ? Preferable
> > in combination with the user being able to
> > resize the window.
> > 
> > Thanks a lot,
> > 
> > Erik
> 
> 
> Hi Erik,
> 
> Last I checked there was nothing automatic for adjusting the spacing around subplots. You can do so manually using ``plt.subplots_adjust`` (see for example, http://matplotlib.sourceforge.net/examples/pylab_examples/subplots_adjust.html).
> 
> A while back, I wrote some functions to calculate a good set of parameters for subplots_adjust (see attached; examples in if-main block at bottom). I've been using these functions pretty regularly, and it works pretty well for my purposes. 
> 
> Best,
> -Tony
> 
> Some usage notes:
> 
> The function has to draw the figure a couple of times to calculate correct spacing. When redrawing the figure (e.g. when you resize the window), you'd have to re-call the function, which would redraw the figure a couple of times before drawing the final figure. That's all to say: this is a fairly slow function. If you don't have subplots (like in your example), you can call "layout.tight_borders()" (instead of "layout.tight()"), which only requires a single redraw.
> 
> When I originally posted this to the developers list, the functions didn't work with the GtkAgg backend. As far as I know, this hasn't changed. It should work fine for Qt4Agg, macosx, and TkAgg backends.
> 
> 

Hello
I am trying to calculate the facecolors for the Axes3D.plot_surface 
function, to have something similar to matlab surf 4th argument!!
Something like plot_surface(x,y,z,facecolors=calc_colors(v))
So, I need to obtain the colors corresponding to the values of v! I 
created the function calc_colors:
import pylab
import numpy as np
from matplotlib.colors import rgb2hex
def calc_colors(var):
 colors = np.empty(var.shape, dtype='S7')
 mm=pylab.cm.ScalarMappable()
 mm.set_clim((var.min(),var.max()))
 mm.set_cmap(pylab.cm.jet)
 colors.flat= [rgb2hex(mm.to_rgba(k)[:-1]) for k in var.flat]
 return colors
Well I believe this is not the smartest way to calculate the colors !! 
At least it is quite slow !
Can someone give me a better solution for this problem?
than you
mma

On Sep 17, 2010, at 8:58 AM, Erik Janssens wrote:
> Hi,
> 
> I'm using matplotlib in a pyqt context, as described
> in the book 'Matplotlib for python developers'.
> 
> When the window is large enough, everything works
> fine, but when the window is too small part of
> the x-axis labels get chopped.
> 
> Is there a way to prevent this ? Preferable
> in combination with the user being able to
> resize the window.
> 
> Thanks a lot,
> 
> Erik
Hi Erik,
Last I checked there was nothing automatic for adjusting the spacing around subplots. You can do so manually using ``plt.subplots_adjust`` (see for example, http://matplotlib.sourceforge.net/examples/pylab_examples/subplots_adjust.html).
A while back, I wrote some functions to calculate a good set of parameters for subplots_adjust (see attached; examples in if-main block at bottom). I've been using these functions pretty regularly, and it works pretty well for my purposes. 
Best,
-Tony
Some usage notes:
The function has to draw the figure a couple of times to calculate correct spacing. When redrawing the figure (e.g. when you resize the window), you'd have to re-call the function, which would redraw the figure a couple of times before drawing the final figure. That's all to say: this is a fairly slow function. If you don't have subplots (like in your example), you can call "layout.tight_borders()" (instead of "layout.tight()"), which only requires a single redraw.
When I originally posted this to the developers list, the functions didn't work with the GtkAgg backend. As far as I know, this hasn't changed. It should work fine for Qt4Agg, macosx, and TkAgg backends.

Hi,
I'm using matplotlib in a pyqt context, as described
in the book 'Matplotlib for python developers'.
When the window is large enough, everything works
fine, but when the window is too small part of
the x-axis labels get chopped.
Is there a way to prevent this ? Preferable
in combination with the user being able to
resize the window.
Thanks a lot,
Erik
http://www.python-camelot.com

http://matplotlib.sourceforge.net/examples/pylab_examples/accented_text.html
hth,
Alan Isaac

Hi there,
I've been looking for a way to automatically set the extension of a
file when saving a plot via the navigationBar 'save' button. In my
case, when I change the file type, the extension of the default
filename ('image.png') won't change. I'd like it to change to the
extension of the file type I selected.
best
carlos
-- 
Prof. Carlos Henrique Grohmann - Geologist D.Sc.
Institute of Geosciences - Univ. of São Paulo, Brazil
http://www.igc.usp.br/pessoais/guano
http://lattes.cnpq.br/5846052449613692
Linux User #89721
________________
Can’t stop the signal.

Jae-Joon Lee wrote:
> 
> 
> Another option is to use mpl_toolkits.axisartist (distributed with mpl
> 1.0). However, learning curve of the axisartist is also steep. You may
> play around with the last figure in the example below.
> 
> http://matplotlib.sourceforge.net/examples/axes_grid/demo_floating_axes.html
> 
> 
Jae-Joon,
Thanks for the quick reply and good advice.
Second option you recommended is seemed to work well.
My code modified from example is attached.
But, in semi-circle domain I can't write contour label using clabel(). 
Do you know the reason why? http://old.nabble.com/file/p29737063/test2.py
test2.py 
For reference my system is python(x,y) on Windows and mpl version is 1.0
Thanks again.
Kenshi
-- 
View this message in context: http://old.nabble.com/contour-plot-in-semi-circle-domain-tp29699332p29737063.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On 16 September 2010 22:52, Jeremy Conlin <jlc...@gm...> wrote:
> I have a colorbar which has some ticks, but I would like to add my own
> ticks without replacing any of the existing ones. In addition, I
> would like to give the ticks a different labels like "min" and "max".
> Can someone show how this might be done?
http://matplotlib.sourceforge.net/examples/pylab_examples/colorbar_tick_labelling_demo.html
should give you some ideas to get started.
Cheers,
Scott

On 16 September 2010 20:38, Mario Juric <mj...@cf...> wrote:
>    I'm looking at Basemap as a backend for plotting maps of the sky in
> different projections, and so far it seems like a really good match!
> Excellent work!
>
>    The only problem that I don't know how to solve is that in astronomy
> the longitude on maps typically increases from right to left (we're
> looking at the celestial sphere from the "inside"). Is there any way (or
> a trick) to make Basemap do this?
Not my field, but I recently bumped into this
http://www.astro.rug.nl/software/kapteyn-beta/index.html
Maybe it's useful to you?
Cheers,
Scott

On Thu, Sep 16, 2010 at 5:33 PM, Carlos Grohmann
<car...@gm...>wrote:
> Hello all,
>
> Is it OK to remove the fonts I don't use? (I use only sans-serif) By
> Ok I mean not only from the practical poin tof view (that is, will the
> app run?) but also from the _legal_ point of view (am I obliged to
> distribute all those fonts?)
>
>
Carlos,
Just to make it very clear, matplotlib is open sourced. You are free to
modify the package to your heart's content, however you see fit. Matplotlib
only asks that you keep the copyright notice with the distributed software
(in particular, the matplotlib/license/LICENSE file applies here, as well as
others.)
With regards to fonts, refer to the matplotlib/license/LICENSE_STIX file.
My understanding of that license (though, IANAL), is that you don't have to
worry about anything above and beyond just simply including the license file
unless you are eliminating individual glyphs from a font (or adding
glyphs). However, I don't see any reason why you can't constrain yourself
to a particular font. Note that you are not allowed to sell any particular
font in the package, though you are allowed to charge a distribution fee for
the "font software".
Generally speaking, my rule of thumb is that if you are distributing
open-source software in the same spirit you have received it, you are
satisfying the spirit of the licenses. The only thing remaining is whether
the source code has to accompany the software or not. The core part of
matplotlib is BSD licensed (or similar) and does not require that (although
it is encouraged!).
Important! Note that the basemap package is GPL-licensed, and is required to
have its source code accompany its software. However, unless your program
*depends* on basemap for it to function, the source code to your program is
not required to be GPL-ed.
And, as always, I am not a lawyer. I am merely conveying my understanding
and experience with software licensing. Anyone else is free to add to
and/or correct what I have said here.
I hope this helps!
Ben Root