matplotlib-users Mailing List for matplotlib (Page 10)

On Wed, May 12, 2010 at 5:58 AM, Yannick Copin
<yan...@la...> wrote:
> gs = gridspec.GridSpec(3, 3)
> ax1 = gs[0, :]
>
I'm inclined to leave the GridSpec as it is and I prefer to have a
separate class for this (if we go for it). My inclination is to modify
subplot2grid to return such an instance. e.g.,
grid = gridspec.subplot2grid((2,2))
ax1 = grid[0,:]
Regards,
-JJ

On Tue, May 11, 2010 at 1:38 PM, John Hunter <jd...@gm...> wrote:
> This looks sufficiently general and useful that we may simply want it
> to live in the main tree (not as a toolkit) and have subplot2grd
> helper functionality available directly from pyplot.
>
Okay.
I'll merge this into the main tree and commit.
Regards,
-JJ

Hi,
Jae-Joon Lee <lee.j.joon@...> writes:
> gridspec is a module that implements matplotlib’s Subplot slightly
> differently. Current matplotlib’s Subplot only allows a Subplot to
> occupy a single cell of the n x m grid. gridspec enables a Subplot to
> occupy multiple cells.
Very interesting indeed. If I may comment on the usability, I wish function
gridspec.subplot could become directly a method of Gridspec. The current example:
gs = gridspec.GridSpec(3, 3)
ax1 = gridspec.subplot(gs[0, :])
ax2 = gridspec.subplot(gs[1,:-1])
ax3 = gridspec.subplot(gs[1:, -1])
ax4 = gridspec.subplot(gs[-1,0])
ax5 = gridspec.subplot(gs[-1,-2])
could be written in a much simpler way then, such as:
gs = gridspec.GridSpec(3, 3)
ax1 = gs[0, :]
ax2 = gs[1,:-1]
ax3 = gs[1:, -1]
ax4 = gs[-1,0]
ax5 = gs[-1,-2]
I would LOVE it!
+1 for getting these functionnalities straight in matplotlib: subplot management
always take a decent part of my scripts...
Cheers,

> -----Original Message-----
> From: Jae-Joon Lee [mailto:lee...@gm...]
> Sent: Tuesday, May 11, 2010 8:58 AM
> To: Matplotlib Users
> Subject: [Matplotlib-users] introducing mpl_toolkits.gridspec
> 
> Hi,
> 
> gridspec is a module that implements matplotlib’s Subplot slightly
> differently. Current matplotlib’s Subplot only allows a Subplot to
> occupy a single cell of the n x m grid. gridspec enables a Subplot to
> occupy multiple cells.
> 
> http://leejjoon.github.com/mpl_toolkits-gridspec/
This is really awesome! Thanks for all the time and hard work, JJ.
-paul

Hi folks,
I just created a tiny prototype of an 'oscilloscope'. I get live data from a
robot via UDP. My network class calls the update() of the oscilloscope. The
oscilloscope is part of an existing GTK app which runs on an Ubuntu.
I have three questions:
1) Since it's my first animation with matplotlib I'm not sure if this is really
 the best way to do it (probably not :)). I especially dislike the creation of
 np.array which could take a bit once I have a lot of data.
2) Is the integration in a GTK app like it is now ok or is there a better way?
 I don't want to loose the zoom and move ability of the standard plot figure
 though. And I need fast results so I don't want to spent to much time
 tweaking this.
3) I get a *weird* X error when calling the update method from the network
 class which probably doesn't have to do anything with matplotlib but I'm
 asking anyway :)
 robocup@robocup2-laptop:~/fumanoid/Desktop-Debug-YUV422$ ../install.py
 /usr/lib/pymodules/python2.6/matplotlib/backends/backend_gtk.py:621:
 DeprecationWarning: Use the new widget gtk.Tooltip
 test from 0: 254/508
 The program 'install.py' received an X Window System error.
 This probably reflects a bug in the program.
 The error was 'RenderBadPicture (invalid Picture parameter)'.
 (Details: serial 11627 error_code 158 request_code 148 minor_code 7)
 (Note to programmers: normally, X errors are reported asynchronously;
 that is, you will receive the error a while after causing it.
 To debug your program, run it with the --sync command line
 option to change this behavior. You can then get a meaningful
 backtrace from your debugger if you break on the gdk_x_error() function.)
 Sometimes it crashes instantly, sometimes it works for a few calls.
 Calling update() from the interactive shell works fine though and displays
 everything. So I don't know if it's really X like the error message
 suggests or what. Did anybody of you experience something like this?
This is the oscilloscope:
import numpy as np
import matplotlib
#matplotlib.use('GTKAgg') # do this before importing pylab
# does not really change anything
import pylab
import matplotlib.pyplot as plt
class Oscilloscope():
 def __init__(self):
 # var for a moving window; not implemented yet
 self.NO_OF_DATA_TO_PLOT = 0
 plt.ion()
 self.fig = plt.figure()
 self.ax = self.fig.add_subplot(111)
 self.ax.grid()
 # list of raw data
 self.raw_data_x = []
 self.raw_data_y = []
 self.graph_lim = dict(x_min=None, x_max=None,
 y_min=None, y_max=None)
 # get line of data to be able to extend it later
 self.line, = self.ax.plot(np.array(self.raw_data_x),
 np.array(self.raw_data_y))
 # open the figure window
 self.fig.canvas.draw()
 def update(self, x, y):
 """Draw new data consisting of x and y."""
 print 'in update'
 self.raw_data_x.append(x)
 self.raw_data_y.append(y)
 # add new data
 self.line.set_xdata(np.array( self.raw_data_x))
 self.line.set_ydata(np.array(self.raw_data_y))
 # redraw the canvas
 self._limit_plot(x, y)
 self.fig.canvas.draw()
Best,
 Stefan

It is version 0.99.1.2.
On 05/11/2010 12:54 PM, Michael Droettboom wrote:
> Is this with matplotlib 0.99.1.2, or SVN trunk? 0.99.1.2 has a known 
> bug in the path simplification algorithm.
>
> Mike
>
> Lane Brooks wrote:
>> I am seeing a problem with the path.simplify rcParam. When it is 
>> enabled, I see spikes in my plots appear and disappear when I resize 
>> the plotting window. When it is disabled, this does not happen. 
>> Attached are pictures showing the effect. In the first image, there 
>> is no spike at x=2559. In the second plot, I resized the window 
>> slightly and the spike appears.
>>
>> Is this the expected behavior or is this a bug?
>>
>> Thanks,
>> Lane
>>
>> ------------------------------------------------------------------------
>>
>>
>> ------------------------------------------------------------------------
>>
>> ------------------------------------------------------------------------
>>
>> ------------------------------------------------------------------------------ 
>>
>>
>> 
>> ------------------------------------------------------------------------
>>
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Is this with matplotlib 0.99.1.2, or SVN trunk? 0.99.1.2 has a known 
bug in the path simplification algorithm.
Mike
Lane Brooks wrote:
> I am seeing a problem with the path.simplify rcParam. When it is 
> enabled, I see spikes in my plots appear and disappear when I resize 
> the plotting window. When it is disabled, this does not happen. 
> Attached are pictures showing the effect. In the first image, there is 
> no spike at x=2559. In the second plot, I resized the window slightly 
> and the spike appears.
>
> Is this the expected behavior or is this a bug?
>
> Thanks,
> Lane
>
> ------------------------------------------------------------------------
>
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------------
>
> 
> ------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

I am seeing a problem with the path.simplify rcParam. When it is 
enabled, I see spikes in my plots appear and disappear when I resize the 
plotting window. When it is disabled, this does not happen. Attached are 
pictures showing the effect. In the first image, there is no spike at 
x=2559. In the second plot, I resized the window slightly and the spike 
appears.
Is this the expected behavior or is this a bug?
Thanks,
Lane

On Tue, May 11, 2010 at 11:39 AM, Jae-Joon Lee <lee...@gm...> wrote:
>> 2) Do you plan on checking this into mpl trunk (still as a mpl_toolkit module)?
This looks sufficiently general and useful that we may simply want it
to live in the main tree (not as a toolkit) and have subplot2grd
helper functionality available directly from pyplot.
JDH

Le mardi 11 mai 2010 à 12:39 -0400, Jae-Joon Lee a écrit :
> > 2) Do you plan on checking this into mpl trunk (still as a
> mpl_toolkit module)?
> Not at this moment. But, will consider if there is enough interest.
+1

On 5/11/2010 11:57 AM, Jae-Joon Lee wrote:
> http://leejjoon.github.com/mpl_toolkits-gridspec/
Yea!
Thanks!
Alan Isaac

On Tue, May 11, 2010 at 12:10 PM, Ryan May <rm...@gm...> wrote:
> 1) How does this relate to the functionality present in your axes_grid toolkit?
axes_grid toolkit is more flexible and is mainly meant to work with
axes with images. gridspec is more for normal axes.
As a matter of fact, the multiple axes created by axes_grid toolkit
usually occupies the area of a single subplot. So, to me, axes_grid
toolkit is something that allows me to divide the area of a single
subplot for multiple images, and gridspec is a replacement of the
subplot.
> 2) Do you plan on checking this into mpl trunk (still as a mpl_toolkit module)?
Not at this moment. But, will consider if there is enough interest.
Regards,
-JJ

On Tue, May 11, 2010 at 10:57 AM, Jae-Joon Lee <lee...@gm...> wrote:
> gridspec is a module that implements matplotlib’s Subplot slightly
> differently. Current matplotlib’s Subplot only allows a Subplot to
> occupy a single cell of the n x m grid. gridspec enables a Subplot to
> occupy multiple cells.
>
> http://leejjoon.github.com/mpl_toolkits-gridspec/
>
> The code is hosted in the github repo
>
> http://github.com/leejjoon/mpl_toolkits-gridspec
>
> and the source can be downloaded from
>
> http://github.com/leejjoon/mpl_toolkits-gridspec/downloads
>
> This is motivated from the discussion in the mailing list a while ago.
>
> http://sourceforge.net/mailarchive/message.php?msg_id=4A0DA94E.1040500%40american.edu
>
> I originally prepared this as a patch for matplotlib
> (http://article.gmane.org/gmane.comp.python.matplotlib.general/19097),
> but never committed. Instead, it is packaged as a mpl_tookit module.
Looks interesting, I'll have to take a look when I get a chance. Two
early questions:
1) How does this relate to the functionality present in your axes_grid toolkit?
2) Do you plan on checking this into mpl trunk (still as a mpl_toolkit module)?
Ryan
-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Hi,
 gridspec is a module that implements matplotlib’s Subplot slightly
differently. Current matplotlib’s Subplot only allows a Subplot to
occupy a single cell of the n x m grid. gridspec enables a Subplot to
occupy multiple cells.
 http://leejjoon.github.com/mpl_toolkits-gridspec/
The code is hosted in the github repo
 http://github.com/leejjoon/mpl_toolkits-gridspec
and the source can be downloaded from
 http://github.com/leejjoon/mpl_toolkits-gridspec/downloads
This is motivated from the discussion in the mailing list a while ago.
http://sourceforge.net/mailarchive/message.php?msg_id=4A0DA94E.1040500%40american.edu
I originally prepared this as a patch for matplotlib
(http://article.gmane.org/gmane.comp.python.matplotlib.general/19097),
but never committed. Instead, it is packaged as a mpl_tookit module.
Regards,
-JJ

Folks,
Is there a way to "unpick" data that was previously "picked"?
The issue is that pick, is very precise. I cannot depend on a identical 
click, in the exact same location, to create the "unpick" tool and 
behavior that I am looking for.
It occurs to me that it is possible to create an "unpick" event by 
creating a matrix of data that surrounds the unpick location and then if 
the picked data point is within this matrix of data, I can process and 
remove the originally picked point from the location I am storing the 
original pick locations.
Maybe Pygame or a collision tool might work also, but I have to study to 
find out.
Is there another preferred way that you see? or can recommend?
Thank You and Best Regards,
Michael Frauens

Hi all,
When creating a new colormap, with a script based on the example given here:
http://www.scipy.org/Cookbook/Matplotlib/Show_colormaps
When plotting the data, and when adding the colobar, I get this error:
In [27]: Exception in Tkinter callback
Traceback (most recent call last):
 File "/usr/lib/python2.6/lib-tk/Tkinter.py", line 1413, in __call__
 return self.func(*args)
 File 
"/usr/lib/pymodules/python2.6/matplotlib/backends/backend_tkagg.py", 
line 212, in resize
 self.show()
 File 
"/usr/lib/pymodules/python2.6/matplotlib/backends/backend_tkagg.py", 
line 215, in draw
 FigureCanvasAgg.draw(self)
 File 
"/usr/lib/pymodules/python2.6/matplotlib/backends/backend_agg.py", line 
314, in draw
 self.figure.draw(self.renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/artist.py", line 46, in 
draw_wrapper
 draw(artist, renderer, *kl)
 File "/usr/lib/pymodules/python2.6/matplotlib/figure.py", line 774, in 
draw
 for a in self.axes: a.draw(renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/artist.py", line 46, in 
draw_wrapper
 draw(artist, renderer, *kl)
 File "/usr/lib/pymodules/python2.6/matplotlib/axes.py", line 1721, in draw
 a.draw(renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 
699, in draw
 return Collection.draw(self, renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/artist.py", line 46, in 
draw_wrapper
 draw(artist, renderer, *kl)
 File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 
201, in draw
 self.update_scalarmappable()
 File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 
477, in update_scalarmappable
 self._facecolors = self.to_rgba(self._A, self._alpha)
 File "/usr/lib/pymodules/python2.6/matplotlib/cm.py", line 167, in to_rgba
 x = self.cmap(x, alpha=alpha, bytes=bytes)
 File "/usr/lib/pymodules/python2.6/matplotlib/colors.py", line 488, in 
__call__
 if not self._isinit: self._init()
 File "/usr/lib/pymodules/python2.6/matplotlib/colors.py", line 632, in 
_init
 self._lut[:-3, 2] = makeMappingArray(self.N, self._segmentdata['blue'])
 File "/usr/lib/pymodules/python2.6/matplotlib/colors.py", line 416, in 
makeMappingArray
 raise TypeError("data must be convertable to an array")
TypeError: data must be convertable to an array
When I don't change the example from the cookbook, I still get the same 
error, and no image. Previously, I didn't get this error. I'm using 
Python 2.6 and MPL 0.99.0 on Ubuntu 9.10.
Any help would be great!
Marius.

On 5/10/10 2:21 PM, Michael Hearne wrote:
> I have found a (possible) bug in Basemap - when using basemap.fillcontinents(), I see the chosen continent color only when the map I create includes some ocean. If I am in the interior of a continent (I've tested with North America and Asia), the continent color is white.
> 
Michael: If there are no continent boundaries inside the map projection 
region, basemap does not draw anything (hence you see the axis 
background color). In that case, you should just set the axis 
background color to whatever you wanted the continent color to be.
-Jeff
> A code sample is below. My version information:
> Basemap: 0.99.4
> Matplotlib: 0.99.1.1
> numpy: 1.4.0
> Python: 2.6.4
>
> To replicate my results, please try the following:
> ./maptest.py 37.894507 -121.816406 #map center is somewhere in the Bay Area in California
> ./maptest.py 41.880332 -100.47821 #map center is somewhere in Nebraska
>
> The script creates a file called "output.png" in the calling directory. In the California case, I see the ocean as blue, and the land as a sort of annoying salmon color. In the Nebraska case, I see white with blue denoting the various rivers and lakes in the area.
>
> Am I mis-using the basemap method calls in some way?
>
> Thanks,
>
> Mike
>
> --------------------------------------------------------------------
> #!/usr/bin/env python
>
> import matplotlib
> #use the non-interactive matplotlib setting
> matplotlib.use('agg')
> from mpl_toolkits.basemap import Basemap
> import numpy as np
> from pylab import *
> import sys
>
> clat = float(sys.argv[1])
> clon = float(sys.argv[2])
>
> figwidth = 5.4
>
>
> bounds = (clon-4, clon+4, clat-4, clat+4)
> dx = (bounds[1] - bounds[0])*111191 * np.cos(clat * np.pi/180)
> dy = (bounds[3] - bounds[2])*111191
> aspect = dy/dx
> figheight = aspect * figwidth
>
> fig = figure(figsize=(figwidth,figheight),edgecolor='g',facecolor='g')
> ax1 = fig.add_axes([0,0,1.0,1.0])
> mapcontour = Basemap(llcrnrlon=bounds[0],llcrnrlat=bounds[2],
> urcrnrlon=bounds[1],urcrnrlat=bounds[3],
> resolution='h',projection='merc',lat_ts=clat)
> water_color = [.47,.60,.81]
> mapcontour.drawrivers(color=water_color)
> mapcontour.drawcountries(color='k',linewidth=2.0)
> mapcontour.drawcoastlines()
> mapcontour.fillcontinents(color=[1.0,0.8,0.8],lake_color=water_color)
>
> plt.savefig('output.png')
> --------------------------------------------------------------------
>
>
> ------------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 

I have found a (possible) bug in Basemap - when using basemap.fillcontinents(), I see the chosen continent color only when the map I create includes some ocean. If I am in the interior of a continent (I've tested with North America and Asia), the continent color is white.
A code sample is below. My version information:
Basemap: 0.99.4
Matplotlib: 0.99.1.1
numpy: 1.4.0
Python: 2.6.4
To replicate my results, please try the following:
./maptest.py 37.894507 -121.816406 #map center is somewhere in the Bay Area in California
./maptest.py 41.880332 -100.47821 #map center is somewhere in Nebraska
The script creates a file called "output.png" in the calling directory. In the California case, I see the ocean as blue, and the land as a sort of annoying salmon color. In the Nebraska case, I see white with blue denoting the various rivers and lakes in the area.
Am I mis-using the basemap method calls in some way?
Thanks,
Mike
--------------------------------------------------------------------
#!/usr/bin/env python
import matplotlib
#use the non-interactive matplotlib setting
matplotlib.use('agg')
from mpl_toolkits.basemap import Basemap
import numpy as np
from pylab import *
import sys
clat = float(sys.argv[1])
clon = float(sys.argv[2])
figwidth = 5.4
bounds = (clon-4, clon+4, clat-4, clat+4)
dx = (bounds[1] - bounds[0])*111191 * np.cos(clat * np.pi/180)
dy = (bounds[3] - bounds[2])*111191
aspect = dy/dx
figheight = aspect * figwidth
 
fig = figure(figsize=(figwidth,figheight),edgecolor='g',facecolor='g')
ax1 = fig.add_axes([0,0,1.0,1.0])
mapcontour = Basemap(llcrnrlon=bounds[0],llcrnrlat=bounds[2],
 urcrnrlon=bounds[1],urcrnrlat=bounds[3],
 resolution='h',projection='merc',lat_ts=clat)
water_color = [.47,.60,.81]
mapcontour.drawrivers(color=water_color)
mapcontour.drawcountries(color='k',linewidth=2.0)
mapcontour.drawcoastlines()
mapcontour.fillcontinents(color=[1.0,0.8,0.8],lake_color=water_color)
plt.savefig('output.png') 
--------------------------------------------------------------------

It seems to be failing on the minus signs in the text, due to a recent 
(incorrect) change to declared encoding of the postscript file.
This has been corrected in r8305.
You didn't mention which version of matplotlib you are running... I'm 
not sure this bug would be in the latest released version, only SVN trunk.
Mike
afancy wrote:
> Hi,
>
> Could anybody help me to take a look my following code? When I save it 
> to eps format, the eps file is corrupted. But i can save as pdf format 
> successfully instead.
>
> Regards
> tommy
>
>
> from matplotlib.font_manager import FontProperties
> data = ((16.31, 76.35, 62.62, 135.2),
> (6.4, 12.64, 87, 124.8 ),
> (6.08,60.18,75.2,100.59))
>
> color=('b','r','g','y')
> width = 0.2 
> fig = plt.figure()
> fig.set_size_inches((4.2,4.2))
>
> ax = fig.add_axes((0.2,0.1,0.75,0.
> 8))
> rects=[]
> xticks=[]
> patterns = ('...','//','xx', '\\\\')
>
> for i in range(len(data)):
> row = data[i]
> for j in range(len(row)):
> rect, = ax.bar(i+width*j, row[j], width,fill=False, 
> edgecolor='black', hatch=patterns[j])
> rect.set_hatch(patterns[j])
> rect.set_fill(False)
> if i==0:
> rects.append(rect)
> xticks.append(i+2*width)
> 
> ax.set_xticks(xticks) 
> ax.set_xticklabels(('Q1(s,p1,*)','Q2(s,p2,*)','Q3(s,p3,*)')) 
> ax.set_ylabel('Resp. time (ms)')
> lg=fig.legend(rects, 
> ('3XL-Array','3XL-MP','Jena2(db-based)','Jena2(file-based)'), 
> loc=(0.65,0.7), prop=FontProperties(size=9))
> lg.draw_frame(False)
> draw() 
> fig.savefig("4b.eps", format="eps", bbox_inches='tight') # Failed 
> to save, the eps is corrupted 
> #fig.savefig("4b.pdf", format="pdf", bbox_inches='tight') # pdf 
> format can be save correctly.
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------------
>
> 
> ------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

Hi,
Could anybody help me to take a look my following code? When I save it to
eps format, the eps file is corrupted. But i can save as pdf format
successfully instead.
Regards
tommy
from matplotlib.font_manager import FontProperties
data = ((16.31, 76.35, 62.62, 135.2),
 (6.4, 12.64, 87, 124.8 ),
 (6.08,60.18,75.2,100.59))
color=('b','r','g','y')
width = 0.2
fig = plt.figure()
fig.set_size_inches((4.2,4.2))
ax = fig.add_axes((0.2,0.1,0.75,0.
8))
rects=[]
xticks=[]
patterns = ('...','//','xx', '\\\\')
for i in range(len(data)):
 row = data[i]
 for j in range(len(row)):
 rect, = ax.bar(i+width*j, row[j], width,fill=False,
edgecolor='black', hatch=patterns[j])
 rect.set_hatch(patterns[j])
 rect.set_fill(False)
 if i==0:
 rects.append(rect)
 xticks.append(i+2*width)
ax.set_xticks(xticks)
ax.set_xticklabels(('Q1(s,p1,*)','Q2(s,p2,*)','Q3(s,p3,*)'))
ax.set_ylabel('Resp. time (ms)')
lg=fig.legend(rects,
('3XL-Array','3XL-MP','Jena2(db-based)','Jena2(file-based)'),
loc=(0.65,0.7), prop=FontProperties(size=9))
lg.draw_frame(False)
draw()
fig.savefig("4b.eps", format="eps", bbox_inches='tight') # Failed to
save, the eps is corrupted
#fig.savefig("4b.pdf", format="pdf", bbox_inches='tight') # pdf format
can be save correctly.

I just noticed something else now:
When tick labels are explicitly supplied, that may not actually
reflect in the return result of get_ticks. Specifically, I set the
tick labels in a color bar, but get_ticklabels() returns a list of
empty text objects Text(0,0,'').
For regular axes, that seems to work better.
Bug?
Cheers,
Nico
On Sat, May 8, 2010 at 10:36 AM, Nico Schlömer <nic...@gm...> wrote:
> Hi,
>
> say, is there a way to query an axis object whether or not the tick
> labels are drawn?
>
> I looked at -- one the x-axis -- get_xticks( and get_xticklabels()
> which in two different situations would spit out a list of doubles
> (the tick positions) and a list of text entries of the form
> Text(0,0,''). In one plot, though, the tick labels are drawn, not in
> the other one.
>
> Cheers,
> Nico
>

You may also try saving as SVG and then loading in Inkscape and using 
its various "artistic" vector plugins to achieve similar results.
Mike
John Hunter wrote:
> On Fri, May 7, 2010 at 1:09 PM, Eric Firing <ef...@ha...> wrote:
> 
>> On 05/06/2010 08:02 PM, oyster wrote:
>> 
>>> I know matplotlib mimics matlab, which offers scientific look.
>>> but can we use matplotlib to get a skecth(in other words,
>>> hand-drawing) style for bar/pie/etc in none formalist paper? for
>>> example, http://teethgrinder.co.uk/open-flash-chart/gallery-bar-7.php
>>> thanks
>>> 
>> With a considerable effort you could use mpl's capabilities to program
>> this sort of thing, but it will not be added as an option.
>> 
>
> JJ's demo_ribbon_box is pretty close -- you just need to create a base
> image you want stretched to the bar height.
>
> import matplotlib.pyplot as plt
> import numpy as np
> from matplotlib.image import BboxImage
>
> from matplotlib._png import read_png
> import matplotlib.colors
> from matplotlib.cbook import get_sample_data
>
> class RibbonBox(object):
>
> original_image = read_png(get_sample_data("Minduka_Present_Blue_Pack.png",
> asfileobj=False))
> cut_location = 70
> b_and_h = original_image[:,:,2]
> color = original_image[:,:,2] - original_image[:,:,0]
> alpha = original_image[:,:,3]
> nx = original_image.shape[1]
>
> def __init__(self, color):
> rgb = matplotlib.colors.colorConverter.to_rgb(color)
>
> im = np.empty(self.original_image.shape,
> self.original_image.dtype)
>
>
> im[:,:,:3] = self.b_and_h[:,:,np.newaxis]
> im[:,:,:3] -= self.color[:,:,np.newaxis]*(1.-np.array(rgb))
> im[:,:,3] = self.alpha
>
> self.im = im
>
>
> def get_stretched_image(self, stretch_factor):
> stretch_factor = max(stretch_factor, 1)
> ny, nx, nch = self.im.shape
> ny2 = int(ny*stretch_factor)
>
> stretched_image = np.empty((ny2, nx, nch),
> self.im.dtype)
> cut = self.im[self.cut_location,:,:]
> stretched_image[:,:,:] = cut
> stretched_image[:self.cut_location,:,:] = \
> self.im[:self.cut_location,:,:]
> stretched_image[-(ny-self.cut_location):,:,:] = \
> self.im[-(ny-self.cut_location):,:,:]
>
> self._cached_im = stretched_image
> return stretched_image
>
>
>
> class RibbonBoxImage(BboxImage):
> zorder = 1
>
> def __init__(self, bbox, color,
> cmap = None,
> norm = None,
> interpolation=None,
> origin=None,
> filternorm=1,
> filterrad=4.0,
> resample = False,
> **kwargs
> ):
>
> BboxImage.__init__(self, bbox,
> cmap = cmap,
> norm = norm,
> interpolation=interpolation,
> origin=origin,
> filternorm=filternorm,
> filterrad=filterrad,
> resample = resample,
> **kwargs
> )
>
> self._ribbonbox = RibbonBox(color)
> self._cached_ny = None
>
>
> def draw(self, renderer, *args, **kwargs):
>
> bbox = self.get_window_extent(renderer)
> stretch_factor = bbox.height / bbox.width
>
> ny = int(stretch_factor*self._ribbonbox.nx)
> if self._cached_ny != ny:
> arr = self._ribbonbox.get_stretched_image(stretch_factor)
> self.set_array(arr)
> self._cached_ny = ny
>
> BboxImage.draw(self, renderer, *args, **kwargs)
>
>
> if 1:
> from matplotlib.transforms import Bbox, TransformedBbox
> from matplotlib.ticker import ScalarFormatter
>
> fig = plt.gcf()
> fig.clf()
> ax = plt.subplot(111)
>
> years = np.arange(2004, 2009)
> box_colors = [(0.8, 0.2, 0.2),
> (0.2, 0.8, 0.2),
> (0.2, 0.2, 0.8),
> (0.7, 0.5, 0.8),
> (0.3, 0.8, 0.7),
> ]
> heights = np.random.random(years.shape) * 7000 + 3000
>
> fmt = ScalarFormatter(useOffset=False)
> ax.xaxis.set_major_formatter(fmt)
>
> for year, h, bc in zip(years, heights, box_colors):
> bbox0 = Bbox.from_extents(year-0.4, 0., year+0.4, h)
> bbox = TransformedBbox(bbox0, ax.transData)
> rb_patch = RibbonBoxImage(bbox, bc, interpolation="bicubic")
>
> ax.add_artist(rb_patch)
>
> ax.annotate(r"%d" % (int(h/100.)*100),
> (year, h), va="bottom", ha="center")
>
> patch_gradient = BboxImage(ax.bbox,
> interpolation="bicubic",
> zorder=0.1,
> )
> gradient = np.zeros((2, 2, 4), dtype=np.float)
> gradient[:,:,:3] = [1, 1, 0.]
> gradient[:,:,3] = [[0.1, 0.3],[0.3, 0.5]] # alpha channel
> patch_gradient.set_array(gradient)
> ax.add_artist(patch_gradient)
>
>
> ax.set_xlim(years[0]-0.5, years[-1]+0.5)
> ax.set_ylim(0, 10000)
>
> fig.savefig('ribbon_box.png')
> plt.show()
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------------
> 
> ------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

I believe there's only a handful of characters available as 
sub/superscript in Unicode:
http://www.unicode.org/charts/PDF/U2070.pdf
Mike
Gökhan Sever wrote:
> Hello,
>
> I have tendency to use unicode strings for my simple units e.g. 
> plt.xlabel(u"Concentration (# cm−3)")
>
> Wondering if it is possible to subscript and/or superscript any 
> character in unicode strings? In other words could the following be 
> done via unicode only?
>
> plt.title(r"N$_{ccn} = C s^k$")
>
>
> Thanks.
> 
> Gökhan
> ------------------------------------------------------------------------
>
> ------------------------------------------------------------------------------
>
> 
> ------------------------------------------------------------------------
>
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

Hello,
I have tendency to use unicode strings for my simple units e.g.
plt.xlabel(u"Concentration (# cm−3)")
Wondering if it is possible to subscript and/or superscript any character in
unicode strings? In other words could the following be done via unicode
only?
plt.title(r"N$_{ccn} = C s^k$")
Thanks.
Gökhan

Hi,
say, is there a way to query an axis object whether or not the tick
labels are drawn?
I looked at -- one the x-axis -- get_xticks( and get_xticklabels()
which in two different situations would spit out a list of doubles
(the tick positions) and a list of text entries of the form
Text(0,0,''). In one plot, though, the tick labels are drawn, not in
the other one.
Cheers,
Nico