Re: [Matplotlib-users] Permission error after installing MPL 1.0 on Mac

2010-09-15 Thread tom
Jeremy Conlin  writes:

> 
> I recently installed MPL on two Macs, one running 10.6 and another
> running 10.5.  When I try to plot, I get the following error:
> 
> TclError: couldn't open
>
"/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/
site-packages/matplotlib/mpl-data/images/home.ppm":
> permission denied
> 
> After checking, it's true that only the owner has read permissions.
> This is easy enough on my end, but I wonder if there is a problem with
> the distributed installer that should have the correct permissions for
> these images.
> 
> Has anyone else seen this problem or is it just me?
> 
> Jeremy

> 


I'm having the exact same problem. I recently installed python 2.6 on 2
different macs, one using OS X 10.5 and one using 10.6.  One is a powerPC and
one's intel, but I get the same error. 



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[Matplotlib-users] Composing image from hex tiles using RegularPolyCollection

2014-04-25 Thread Tom Grydeland
Hi all,

I will explain what I’m trying to achieve first, then the approaches I’ve 
attempted so far, with results.

I have data on a 2D grid which I want to present as an image — a la 
pyplot.imshow() — except that the grid is hexagonal, not rectangular.  The grid 
can be represented in multiple ways, I use a regular 2D array with the 
convention that the lower left hex is (0,0), x increases to the right (crossing 
vertical hex boundaries) and y increases upwards slanting to the right.

Ideally, I’d also be able to have a colorbar.

I’m giving my routines three input vectors: x, y and c.  X and y are initially 
integers, then transformed to centerpoint coordinates using
 x, y = x+.5*y, y*np.cos(np.pi/6)
while c is used to look up values in a colormap.

I first tried to adapt ‘scatter_demo2.py’ to my needs.  Unfortunately, the 
pyplot.scatter routine fails when given ‘c’ or ’s’ keywords, as has been 
reported elsewhere by somebody else:
   
http://stackoverflow.com/questions/20524888/attributeerror-numpy-ndarray-object-has-no-attribute-get-matrix

I’ve dug around in the code for a bit without finding out how this arises.  It 
seems to me it has to do with how transforms are being handed around and at 
what point their representation is changed from objects to pure matrices.  This 
backend appears to expect to see objects only, but is handed matrices instead.  
I’ve hacked my way around that one in backends/backend_macosx.py by changing 
lines around 79-80 from
   master_transform = master_transform.get_matrix()
   all_transforms = [t.get_matrix() for t in all_transforms]
to
   try:
   master_transform = master_transform.get_matrix()
   except AttributeError: pass
   try:
   all_transforms = [t.get_matrix() for t in all_transforms]
   except AttributeError: pass
(which is a dirty hack, but I don’t know how to do it right)

Now I can run the scatter_demo2 script, and I can obviously have it produce 
hexes at uniform size, but the size of the hexagons are set independently of 
the axes.  Good for symbols used to mark arbitrary coordinates, not so good 
when I try to cover the plane without gaps.

Next, I’ve tried creating the patches one by one, essentially this:

   r = 1./np.sqrt(3)
   for xy, cc in zip(zip(x, y), c):
   hexp = mpl.patches.RegularPolygon(xy, 6, radius=r, facecolor=cc, 
edgecolor=’none')
   ax.add_patch(hexp)
   ax.autoscale_view()
   ax.figure.canvas.draw()

This works as I want it to, but becomes unbearably slow when the number of 
hexes grows beyond a few thousand.

Given that RegularPolygon can do the trick, it seems likely that 
RegularPolyCollection should also be able to?

This is what I tried:

   ax = gca()
   collection = RegularPolyCollection(
   6, # a pentagon
   rotation=(np.pi/7,),
   sizes=(.5/np.sqrt(3),),
   facecolors = cc,
   edgecolors = None,
   linewidths = (1,),
   offsets = zip(xx,yy),
   transOffset = ax.transData,
   )
   #collection.set_transform(ax.transData)
   ax.add_collection(collection, autolim=True)

   ax.autoscale_view()
   ax.figure.canvas.draw()

This produces dots of minute sizes at the desired coordinates.  I can tweak the 
size to make them bigger, but they don’t scale with the axes, as for the 
scatter_demo script used initially.  Digging in the docs, I found a reference 
to the set_transform() method of Artists, so I tried setting that to 
ax.transData (the line commented out in the above snippet), and voila! I have 
hexagons covering the plane again.  Strangely enough, they’re not in the right 
place anymore (and the locations change when zooming in or out), the sizes 
aren’t _quite_ right, the autoscaling of axes appear to believe the patches are 
where I wanted them to be, not where they appear on the plot, results are very 
different if saving to a figure instead of drawing to a figure window, etc.

Is there a way I can make RegularPolyCollection patches transform with axes 
coordinates in the same way that RegularPolygon patches do?

Am I barking up the wrong tree, is there another, blindingly obvious, way I 
should be doing this?

The observant reader will also notice the strange rotation keyword given to 
RegularPolyCollection.  This keyword is ignored in the macosx backend, and I 
have been unable to find out why.

Thank you for all tips and pointers

--Tom Grydeland


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Re: [Matplotlib-users] zoom a plot

2014-09-15 Thread Tom Young
Thank you for your quick answer. I understand the performance issue you
mentioned. For now it is only a proof of concept.

I just figured out how to do it in theory by using
figure.subplot.left|right|bottom|top plus a few other settings.

I'll certainly look at the webagg backend. Are there any examples available?



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[Matplotlib-users] [Ann] Early-bird registration extended for EuroSciPy 2015

2015-07-01 Thread Tom Pohl
Head over to https://www.euroscipy.org/2015/ for more information.
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Re: [Matplotlib-users] dynamically add subplots to figure

2009-07-16 Thread Tom Vaughan
On Tue, Jun 2, 2009 at 07:33, John Hunter wrote:
> On Tue, Jun 2, 2009 at 9:03 AM, Tom Vaughan  wrote:
>> Is it possible to add subplots to a figure if I don't know in advance
>> how many subplots I need to add?
>>
>> What I do now is I call add_subplot like add_subplot(i, 1, i) where i
>> is 1 initially, and just increases by 1 on each call. This almost
>> works. Except the first plot takes up the whole figure, the second
>> plot is placed on top of the bottom half of the first plot, etc. Is
>> there a way to "resize" the plots when a subplot is added? Or how
>> would I "re-plot" the previous subplots?
>
> See the Axes.change_geometry command
>
>  http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.SubplotBase.change_geometry

twinx() does not return an axes that contains the change_geometry
method. How then can I do the equivalent on this axes? Calling twinx()
again on the original axes after change_geometry() has been called
does not do the trick. Thanks.

-Tom

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Re: [Matplotlib-users] pylab

2009-08-11 Thread Tom K.



Sebastian Haase-3 wrote:
> 
> Thanks for the info -- very informative -- maybe this post could be
> somehow added or linked to from http://www.scipy.org/PyLab
> 
> -- Sebastian Haase
> 
Sebastian - I've done as you suggest... I added a link to this post on
nabble - do you think there is a better URL for it than 
   http://www.nabble.com/pylab-td24910613.html ?



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Re: [Matplotlib-users] dynamically add subplots to figure

2009-08-12 Thread Tom Vaughan
Great. That worked. Thanks!

-Tom


On Thu, Jul 16, 2009 at 11:23, Jae-Joon Lee wrote:
> One work around is to call
>
>  self.figure.subplots_adjust()
>
> after geometry changed. After this call, the twinx-ed axes will have
> the same axes position as the original one.
>
> Another option is to use mpl_toolkits.axes_grid
> (http://matplotlib.sourceforge.net/mpl_toolkits/axes_grid/users/overview.html#parasiteaxes).
> But the previous solution seems to be much easier for you.
> Regards,
>
> -JJ
>
>
> On Thu, Jul 16, 2009 at 1:16 PM, Tom Vaughan wrote:
>> On Tue, Jun 2, 2009 at 07:33, John Hunter wrote:
>>> On Tue, Jun 2, 2009 at 9:03 AM, Tom Vaughan  wrote:
>>>> Is it possible to add subplots to a figure if I don't know in advance
>>>> how many subplots I need to add?
>>>>
>>>> What I do now is I call add_subplot like add_subplot(i, 1, i) where i
>>>> is 1 initially, and just increases by 1 on each call. This almost
>>>> works. Except the first plot takes up the whole figure, the second
>>>> plot is placed on top of the bottom half of the first plot, etc. Is
>>>> there a way to "resize" the plots when a subplot is added? Or how
>>>> would I "re-plot" the previous subplots?
>>>
>>> See the Axes.change_geometry command
>>>
>>>  http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.SubplotBase.change_geometry
>>
>> twinx() does not return an axes that contains the change_geometry
>> method. How then can I do the equivalent on this axes? Calling twinx()
>> again on the original axes after change_geometry() has been called
>> does not do the trick. Thanks.
>>
>> -Tom
>>
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[Matplotlib-users] Gridspy dashboard - Web based Matplotlib

2009-11-05 Thread Tom Leys
Hi.

I would like to introduce my usage of Matplotlib...

"
Gridspy provides you with an interactive view of resource usage in your 
building. It gives you hard data on your consumption patterns and helps 
you to make informed decisions.
...
The Gridspy allows you to access and monitor your consumption patterns 
in real-time using a standard web browser on your PC, laptop or mobile 
phone. The data is presented in high resolution and updated each second 
as you watch. The moment a light is turned on in your house, you can see 
the change on your Gridspy dashboard from across the room or across the 
planet.
"

We use Matplotlib to prepare graphs in PNG format that form an essential 
part of our dashboard here (it loads nice and fast, trust me):
http://your.gridspy.co.nz/powertech/

The blog discusses our Python Twisted backend, and other stuff:
http://blog.gridspy.co.nz/

Finally you can follow my progress as I take this product to market on 
twitter:
http://www.twitter.com/gridspy/

It has been a fantastic system to work with, and it was easy to generate 
beautiful and meaningful graphs. Thanks to everyone who has made this 
possible!

What is everyone else working on?

-Tom

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[Matplotlib-users] How to make little sparklines

2009-11-07 Thread Tom Leys
Hi

I was asked off list how I created the little sparklines using Matplotlib.

There are two ways I create these:

The live graphs on the demo page (http://your.gridspy.co.nz/powertech/)
are created by a great little jquery app (so yeah, not matplotlib):
http://omnipotent.net/jquery.sparkline/

To get the data to the browser in order to render the sparkline, you
will need some sort of mechanism similar to Ajax (or at least a form of
it) called Comet. There is a great tutorial on using orbited for this here

http://cometdaily.com/2008/10/10/scalable-real-time-web-architecture-part-2-a-live-graph-with-orbited-morbidq-and-jsio/

If any of you need more help doing that, I am happy to provide some
source code examples.

If instead, you want to create static line graphs using matplotlib such
as those on this page:
http://your.gridspy.co.nz/powertech/history/04Nov2009.htm
http://your.gridspy.co.nz/powertech/graph/tiny/3-3-04Nov2009.png?c=2 (an
example)

To render static sparklines I use the following matplot lib code:

def render_simple_line(sensors, resolution = 'hour', span = 1,
   start=None, end=None, fig=None, column=0):
"""Builds a figure that shows the given sensors at the given
resolution and span in the given time period.
"""

if fig is None:
fig=Figure()
fig.set_facecolor('white')
fig.set_edgecolor('white')
axes = fig.add_axes([0.00,0.00,1.0,1.0], axisbg='w', frame_on=False)
axes.set_xticks([])
axes.set_yticks([])
axes.set_axis_off()

if start is None:
start = datetime.datetime.now()
if end is None:
end = start + datetime.timedelta(days=1)
first_date = start.strftime('%Y-%m-%d')
last_date  = end.strftime('%Y-%m-%d')


desc = [("mean", pk) for pk in sensors]
np_table = data_table_matrix(desc, resolution, first_date,
last_date, span )
#note that np_table[0] is datetime objects and [1] is data
if np_table.size == 0:
return None

#replace nulls with 0
np_table[1:][np_table[1:] == np.array([None])] = 0
#replace -ve values
np_table[1:][np_table[1:] < np.array([0])] = 0

axes.xaxis.set_major_formatter(DateFormatter('%H'))
fig.autofmt_xdate()

base = np.zeros(np_table.shape[1])

color = color_list[column % len(color_list)][1]
axes.fill_between(np_table[0], base, np_table[column + 1], facecolor
= color)

return fig

I pass fig in so it is easy to pass a figure from the ipython console,
since ipython makes special figures that are interactive.

-Tom

PS: Dan - I replied to your email directly but it bounced.


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[Matplotlib-users] How to make little sparklines

2009-11-09 Thread Tom Leys
Hi

I was asked off list how I created the little sparklines using Matplotlib.

There are two ways I create these:

The live graphs on the demo page (http://your.gridspy.co.nz/powertech/) 
are created by a great little jquery app (so yeah, not matplotlib):
http://omnipotent.net/jquery.sparkline/

To get the data to the browser in order to render the sparkline, you
will need some sort of mechanism similar to Ajax (or at least a form of
it) called Comet. There is a great tutorial on using orbited for this here

http://cometdaily.com/2008/10/10/scalable-real-time-web-architecture-part-2-a-live-graph-with-orbited-morbidq-and-jsio/

If any of you need more help doing that, I am happy to provide some 
source code examples.

If instead, you want to create static line graphs using matplotlib such 
as those on this page:
http://your.gridspy.co.nz/powertech/history/04Nov2009.htm
http://your.gridspy.co.nz/powertech/graph/tiny/3-3-04Nov2009.png?c=2 (an
example)

To render static sparklines I use the following matplot lib code:

def render_simple_line(sensors, resolution = 'hour', span = 1,
   start=None, end=None, fig=None, column=0):
"""Builds a figure that shows the given sensors at the given
resolution and span in the given time period.
"""

if fig is None:
fig=Figure()
fig.set_facecolor('white')
fig.set_edgecolor('white')
axes = fig.add_axes([0.00,0.00,1.0,1.0], axisbg='w', frame_on=False)
axes.set_xticks([])
axes.set_yticks([])
axes.set_axis_off()

if start is None:
start = datetime.datetime.now()
if end is None:
end = start + datetime.timedelta(days=1)
first_date = start.strftime('%Y-%m-%d')
last_date  = end.strftime('%Y-%m-%d')


desc = [("mean", pk) for pk in sensors]
np_table = data_table_matrix(desc, resolution, first_date,
last_date, span )
#note that np_table[0] is datetime objects and [1] is data
if np_table.size == 0:
return None

#replace nulls with 0
np_table[1:][np_table[1:] == np.array([None])] = 0
#replace -ve values
np_table[1:][np_table[1:] < np.array([0])] = 0

axes.xaxis.set_major_formatter(DateFormatter('%H'))
fig.autofmt_xdate()

base = np.zeros(np_table.shape[1])

color = color_list[column % len(color_list)][1]
axes.fill_between(np_table[0], base, np_table[column + 1], facecolor
= color)

return fig

I pass fig in so it is easy to pass a figure from the ipython console,
since ipython makes special figures that are interactive.

-Tom

PS: Dan - I replied to your email directly but it bounced.

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Re: [Matplotlib-users] matplotlib slow compared to gnuplot?

2009-11-11 Thread Tom Leys
It looks like you are storing your source data in a python list. Matplotlib 
runs much faster if you store your data using a numpy array instead. 

I'm no expert, but it certianly sped up my graph drawing.

-Tom



Message: 5
Date: Wed, 11 Nov 2009 08:53:58 -0600
From: Mike Anderson 
Subject: [Matplotlib-users] matplotlib slow compared to gnuplot?
To: matplotlib-users@lists.sourceforge.net
Message-ID: 
Content-Type: text/plain; charset=us-ascii; format=flowed; delsp=yes

Hi all,

Previously I was a user of gnuplot but have been giving matplotlib a  
try.  One thing I've run in to right away is that matplotlib appears  
to be significantly slower.

A script to produce a dozen plots was taking me ~1 second with  
gnuplot, and now takes me ~18 seconds with matplotlib.

I'm curious if anyone knows how to speed things up.  To figure out  
what is taking most of the time, I've used cProfile and pstats and  
below is the top 15 functions taking the most time.
   (note: "plotStackedJobsVsTime" is my function that uses matplotlib.)

My script, for the curious, is at
   
http://www.hep.wisc.edu/cms/comp/routerqMonitor/prodJobMonitorPlots_matplotlib.py
and produces these plots:
   http://www.hep.wisc.edu/cms/comp/routerqMonitor/index.html


Any hints at what I can do to speed up my script?  Or is it out of my  
hands because it's all in matplotlib?

Thanks for any help,
Mike



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[Matplotlib-users] Incomplete rendering of line plot

2010-04-23 Thread Tom Aldcroft
I've run into a case where the rendering in a line plot is incomplete
and some lines are not drawn at all.  Basically I have a dataset (see
below) where I know two points go to a value of zero.   When I plot
the points and do interactive pan/zoom sometimes the line going down
to zero is there and sometimes not.  After a bunch of playing around
trying to reduce the problem to a minimum the script below is what I
got.  If I tried to make the 'y' array much smaller then the problem
went away.  I played with antialias and interactive settings with no
benefit.  Changing the window size can also produce the same effect
I'm describing.  Finally, when I use savefig to save in various
formats the results varied, perhaps just a side-effect of the size of
the saved figure.

I'm using Matplotlib 0.99.1.1 built from source with the TkAgg backend
on CentOS-5 with python 2.6.  This same problem was also evident using
GtkAgg and MacOSX backends so I don't think the details of my build
are relevant (but I can supply if needed).

Thanks, Tom

import numpy
import matplotlib.pyplot as plt

y = numpy.array([
 4., 2., 2., 3., 3., 2., 2., 6., 6., 5., 5., 4., 4.,
 7., 7., 2., 2., 4., 4., 2., 2., 2., 2., 4., 4., 4.,
 4., 4., 4., 7., 7., 3., 3., 5., 5., 4., 4., 5., 5.,
 4., 4., 7., 7., 6., 6., 2., 2., 2., 2., 5., 5., 4.,
 4., 4., 4., 6., 6., 3., 3., 4., 4., 3., 3., 2., 2.,
 3., 3., 4., 4., 4., 4., 4., 4., 6., 6., 5., 5., 4.,
 4., 7., 7., 3., 3., 4., 4., 4., 4., 5., 5., 4., 4.,
 7., 7., 3., 3., 4., 4., 4., 4., 6., 6., 4., 4., 4.,
 4., 4., 4., 2., 2., 5., 5., 6., 6., 3., 3., 5., 5.,
 4., 4., 0., 0., 5., 5., 1., 1., 4., 4., 5., 5., 4.])

plt.figure()
plt.plot(y)

plt.figure()
plt.plot(y)
plt.xlim(-7200, 6500)
# Does it go down to 0 now?

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[Matplotlib-users] Radar / Spider Chars

2008-06-03 Thread Tom Edwards
Hello all,

Just a quick question which I can't seem to find an answer to on google
or in the documentation. Is it possible to produce a Radar or Spider
chart: http://en.wikipedia.org/wiki/Radar_chart with Matplotlib?

I can see that you can produce polar plots, however the only references
I can find to "radar" plots are the "radar" green colour in the examples
file.

Just wondering whether it was worth pursuing this technique or using a
different method (if anyone knows of a python library that can do this I
would appreciate it?)

Kind regards,

Tom



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[Matplotlib-users] Radar / Spider Chars

2008-06-03 Thread Tom Edwards
Hello all,

Just a quick question which I can't seem to find an answer to on google 
or in the documentation. Is it possible to produce a Radar or Spider 
chart: http://en.wikipedia.org/wiki/Radar_chart with Matplotlib?

I can see that you can produce polar plots, however the only references 
I can find to "radar" plots are the "radar" green colour in the examples 
file.

Just wondering whether it was worth pursuing this technique or using a 
different method (if anyone knows of a python library that can do this I 
would appreciate it?)

Kind regards,

Tom

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Re: [Matplotlib-users] [IPython-user] 'pause' in order to cycle though a bunch of plots

2008-11-14 Thread Tom Denniston
I've had the same problem.  You can write a pause function using the
python input() function but it hangs the GIL and as a result your
window becomes unresponsive.  If anyone knows a GIL friendly way to
pause i would also be very interested.


On Fri, Nov 14, 2008 at 1:12 PM, Benjamin J. Racine
<[EMAIL PROTECTED]> wrote:
> I use pause in matlab to cycle through an interactive do-loop and view a
> bunch of plots in interactively...
>
> Don't bother reproducing it here, but I am just wondering if this is
> possible in ipython/matplotlib
>
> Many thanks,
>
> Ben Racine
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>

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[Matplotlib-users] fourier demo

2009-01-11 Thread Tom K.

Hi, I am cross-posting this from wxPython users list since the demo is an
example wxPython app with embedded matplotlib objects.

To the wxpython / matplotlib community: 

I wanted to share the enclosed "Fourier Demo" GUI, which is a
reimplementation of one of the very first MATLAB GUIs that I worked on at
MathWorks in 1993 (right when Handle Graphics was introduced in   
MATLAB 4).   It presents you with two waveforms - a Fourier transform pair -
and allows you to manipulate some parameters (via clicking the waveforms and
dragging, and controls) and shows how the waveforms are related. 

I was very happy about how easily it came together and the performance of
the resulting GUI.  In particular the matplotlib events and interaction with
wx is quite nice.  The 'hitlist' of matplotlib figures is very convenient.

Note this is some of my first wx GUI programming so if you see anything that
could be handled with a better pattern / class / etc, I  am very open to
such suggestions! 

Sincerely, 
   Tom K. 
http://www.nabble.com/file/p21407452/sigdemo.py sigdemo.py 

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[Matplotlib-users] FourierDemo now on wxPyWiki

2009-01-16 Thread Tom Krauss
After some positive feedback and subsequent discussion on the  
wxPython users list, I decided to add a wiki page for the Fourier  
Demo I posted earlier:

   http://wiki.wxpython.org/MatplotlibFourierDemo

Robin, et. al., do you think this warrants moving up into a new  
category (e.g. RecipesMatplotlib) in the Recipes section?  I added it  
in the RecipesOther but there are so many recipes there that it seems  
kind of buried.

Best,
   Tom K.

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Re: [Matplotlib-users] Help with simply plotting 2d array, please

2009-02-25 Thread Tom K.



LKeene wrote:
> 
> 
> - I have a numpy.ndarray of data with 350 rows and 500 columns. How do
> I display it in the upper-left hand corner of the frame client with no
> tick marks/labels, etc...just the colormap at screen
> coords(0,0)->(349,499)  (rows,columns)? Could someone post a few lines
> to do this? Thanks so much in advance!
> 
> -L
> 

Hmm... interesting problem...

Here's a simple example where the image fills the frame - note the
properties such as xticks, yticks = [], position=[0,0,1,1], and the size of
the Frame itself... on my platform (Mac OS X) the height of the frame should
be 22 pixels more than the image (discovered by trial and error).  

The border of the axes is still visible in black - obscuring the outer
pixels of the image - does anyone know how to shut that off?

import matplotlib
matplotlib.interactive(False)
matplotlib.use('WXAgg')
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg
from matplotlib.figure import Figure
from  matplotlib.pyplot import setp

import numpy as np

import wx

class MatplotlibFrame(wx.Frame):
def __init__(self, *args, **kwargs):
wx.Frame.__init__(self, *args, **kwargs)
self.figure = Figure()
print self.figure
self.canvas = FigureCanvasWxAgg(self, -1, self.figure)

self.subplot = self.figure.add_subplot(111)
#cdata = np.random.rand(351, 501)
cdata = np.zeros((351, 501))
cdata[::50, ::50] = 1
self.subplot.imshow(cdata, aspect='equal', interpolation='nearest')
setp(self.subplot, xticks=[], yticks=[], position=[0,0,1,1])

def repaint(self):
self.canvas.draw()


class App(wx.App):
def OnInit(self):
frame = MatplotlibFrame(parent=None, title="an image", size=(501,
351+22))
frame.Show()
return True

app = App()
app.MainLoop()


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[Matplotlib-users] dynamically add subplots to figure

2009-06-02 Thread Tom Vaughan
Is it possible to add subplots to a figure if I don't know in advance
how many subplots I need to add?

What I do now is I call add_subplot like add_subplot(i, 1, i) where i
is 1 initially, and just increases by 1 on each call. This almost
works. Except the first plot takes up the whole figure, the second
plot is placed on top of the bottom half of the first plot, etc. Is
there a way to "resize" the plots when a subplot is added? Or how
would I "re-plot" the previous subplots?

Thanks.

-Tom

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Re: [Matplotlib-users] dynamically add subplots to figure

2009-06-02 Thread Tom Vaughan
On Tue, Jun 2, 2009 at 07:33, John Hunter wrote:
> On Tue, Jun 2, 2009 at 9:03 AM, Tom Vaughan  wrote:
>> Is it possible to add subplots to a figure if I don't know in advance
>> how many subplots I need to add?
>>
>> What I do now is I call add_subplot like add_subplot(i, 1, i) where i
>> is 1 initially, and just increases by 1 on each call. This almost
>> works. Except the first plot takes up the whole figure, the second
>> plot is placed on top of the bottom half of the first plot, etc. Is
>> there a way to "resize" the plots when a subplot is added? Or how
>> would I "re-plot" the previous subplots?
>
> See the Axes.change_geometry command
>
>  http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.SubplotBase.change_geometry
>
> As in this example::
>
>    import matplotlib.pyplot as plt
>
>    # start with one
>    fig = plt.figure()
>    ax = fig.add_subplot(111)
>    ax.plot([1,2,3])
>
>    # now later you get a new subplot; change the geometry of the existing
>    n = len(fig.axes)
>    for i in range(n):
>        fig.axes[i].change_geometry(n+1, 1, i+1)

Awesome. Thanks.

Strangely this doesn't quite work for me. Luckily I keep a list of my
subplots. So I do:

def new_subplot(self):
nsubplots = len(self.__subplots) + 1

for i, subplot in enumerate(self.__subplots):
subplot.change_geometry(nsubplots, 1, i + 1)

subplot = self.figure.add_subplot(nsubplots, 1, nsubplots)
subplot.grid(True)

self.__subplots.append(subplot)
self.__subplot = subplot

Interestingly, if I were to 'print dir(self.figure.axes[i])' I can see
the change_geometry attribute, but when I attempt to call it, I am
told "AttributeError: 'AxesSubplot' object has no attribute
'change_geomtry'" This lead me to what I have above.

Thanks.

-Tom

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Re: [Matplotlib-users] dynamically add subplots to figure

2009-06-02 Thread Tom Vaughan
On Tue, Jun 2, 2009 at 08:40, John Hunter wrote:
> On Tue, Jun 2, 2009 at 10:18 AM, Tom Vaughan  wrote:
>
>> Interestingly, if I were to 'print dir(self.figure.axes[i])' I can see
>> the change_geometry attribute, but when I attempt to call it, I am
>> told "AttributeError: 'AxesSubplot' object has no attribute
>> 'change_geomtry'" This lead me to what I have above.
>>
>
> Check your spelling: 'change_geomtry'

Whoops. Thanks.

-Tom

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Re: [Matplotlib-users] dynamically add subplots to figure

2009-06-02 Thread Tom Vaughan
On Tue, Jun 2, 2009 at 07:33, John Hunter wrote:
> On Tue, Jun 2, 2009 at 9:03 AM, Tom Vaughan  wrote:
>> Is it possible to add subplots to a figure if I don't know in advance
>> how many subplots I need to add?
>>
>> What I do now is I call add_subplot like add_subplot(i, 1, i) where i
>> is 1 initially, and just increases by 1 on each call. This almost
>> works. Except the first plot takes up the whole figure, the second
>> plot is placed on top of the bottom half of the first plot, etc. Is
>> there a way to "resize" the plots when a subplot is added? Or how
>> would I "re-plot" the previous subplots?
>
> See the Axes.change_geometry command
>
>  http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.SubplotBase.change_geometry

To follow-up on this a bit, the second, third, etc subplots all seem
to get stuck with the first subplot's x-axis. Let's say the first plot
is -60 to 60, and the second plot is 2 - 4. The data in the second
plot is plotted on the correct scale (2 to 4), but I still see -60 to
60.

Actually, this isn't entirely correct. When I add a third subplot, the
second subplot becomes correct. So the -60 to 60 only sticks to the
most recently added subplot.

Any ideas?

Thanks.

-Tom

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Re: [Matplotlib-users] dynamically add subplots to figure

2009-06-02 Thread Tom Vaughan
On Tue, Jun 2, 2009 at 11:59, John Hunter wrote:
> On Tue, Jun 2, 2009 at 1:51 PM, Tom Vaughan  wrote:
>> On Tue, Jun 2, 2009 at 07:33, John Hunter wrote:
>>> On Tue, Jun 2, 2009 at 9:03 AM, Tom Vaughan  wrote:
>>>> Is it possible to add subplots to a figure if I don't know in advance
>>>> how many subplots I need to add?
>>>>
>>>> What I do now is I call add_subplot like add_subplot(i, 1, i) where i
>>>> is 1 initially, and just increases by 1 on each call. This almost
>>>> works. Except the first plot takes up the whole figure, the second
>>>> plot is placed on top of the bottom half of the first plot, etc. Is
>>>> there a way to "resize" the plots when a subplot is added? Or how
>>>> would I "re-plot" the previous subplots?
>>>
>>> See the Axes.change_geometry command
>>>
>>>  http://matplotlib.sourceforge.net/api/axes_api.html#matplotlib.axes.SubplotBase.change_geometry
>>
>> To follow-up on this a bit, the second, third, etc subplots all seem
>> to get stuck with the first subplot's x-axis. Let's say the first plot
>> is -60 to 60, and the second plot is 2 - 4. The data in the second
>> plot is plotted on the correct scale (2 to 4), but I still see -60 to
>> 60.
>>
>> Actually, this isn't entirely correct. When I add a third subplot, the
>> second subplot becomes correct. So the -60 to 60 only sticks to the
>> most recently added subplot.
>>
>> Any ideas?
>
> post some code
>

I thought this might be required...

We have a variety of telemetry applications that all require some sort
of visual display of data. We've created a widget based upon
matplotlib that can be used stand-alone (reads JSON formatted data
files), or within PyGTK applications and can plot data sets in
"real-time". So the whole thing is excessively complex. I'd be happy
to package up the whole thing if anyone is interested. Currently it
requires the latest Ubuntu release with several additional development
libraries like GLib. What I've posted below is just the abstract plot
widget.

I think the relevant parts are:

from matplotlib.figure import Figure
self.figure = Figure()

self.__subplots = []
self.subplot_new()

self.__axl = self.figure.gca()
self.__axl.yaxis.set_label_position('left')
self.__axl.yaxis.tick_left()

self.__axr = self.__axl.twinx()
self.__axr.yaxis.set_label_position('right')
self.__axr.yaxis.tick_right()

and then:

def subplot_new(self):
nsubplots = len(self.__subplots) + 1

subplot = self.figure.add_subplot(nsubplots, 1, nsubplots)
subplot.grid(True)

self.__subplots.append(subplot)
self.__subplot = subplot

for i, subplot in enumerate(self.__subplots):
subplot.change_geometry(nsubplots, 1, i + 1)

and then:

def __plot__(self, x, y, style='-', color=0xFF,
xlabel=None, ylabel=None):
IBackend.__plot__(self, x, y, style=style,
color=color, xlabel=xlabel, ylabel=ylabel)

if xlabel != None:
self.__subplot.set_xlabel(xlabel)
if ylabel != None:
self.__subplot.set_ylabel(ylabel)

self.__subplot.plot(x, y, style, color='#%06X' % (color))
self.__subplot.grid(True)

def plotr(self, *args, **kwargs):
self.figure.sca(self.__axr)
if not kwargs.has_key('color'):
kwargs['color'] = 0x00FF00
self.__plot__(*args, **kwargs)

def plotl(self, *args, **kwargs):
self.figure.sca(self.__axl)
if not kwargs.has_key('color'):
kwargs['color'] = 0xFF
self.__plot__(*args, **kwargs)

The whole thing:

from __future__ import with_statement

# standard python libraries
try:
import json
except:
import simplejson as json

import re
import os
import time

# matplotlib.sf.net
import matplotlib
import numpy

# www.gtk.org
import gtk

# our own libraries
from elrond.macros import clamp
from elrond.util import Object, Property

def parse(f):
x = []
y = []

fd = open(f, 'r')
lines = [l.strip() for l in fd.readlines()]
fd.close()

for i, line in enumerate(lines):
data = filter(lambda x: x != '', re.split('[, ]', line.strip()))

try:
   

[Matplotlib-users] set gca()

2011-11-27 Thread Tom Bennett
Hi,

I am new to Matplotlib. I am using matplotlib under ipython. A
function script generates a figure that has three subplots. The thing is
that I would like to continue to interact with a specific subplot under the
interactive prompt through pylab after I run that function. However, gca()
returns the last subplot which is not what I want.

The question is if there is any way to tell gca() which Axes is the current
Axes.

Thanks,
Tom
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[Matplotlib-users] Dark or inverted color scheme

2012-05-25 Thread Tom Aldcroft
Is there a simple way to essentially invert the default plotting color
scheme so that the figure background is black and all text, ticks,
axes, axis labels, etc are white?  I think what I want is to redefine
the RGB definitions of the standard color values 'b', 'y', 'k', etc so
that I can make a plot figure with a black background using the same
script as one for the normal white background.

A spent a little while googling and didn't find anything apart from
specifically setting different colors for every single plot element.
This would be tiresome.

Thanks in advance for any help,
Tom

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Re: [Matplotlib-users] who (F/OSS science) uses matplotlib?

2012-06-05 Thread Tom Dimiduk
On 06/05/2012 10:14 AM, Kevin Hunter wrote:
> At 10:47pm -0400 Sun, 03 Jun 2012, Tom Dimiduk wrote:
>> Very few people outside my group use it at the moment, but that looks
>> to be changing at least a bit. I will hopefully get a paper out about
>> the code by the end of the summer.
>
> I'm in a similar boat with the research on which I'm working, paper and
> all.  I don't know if folks will end up using it or not, but at least it
> is available (github), if not well advertised to the (decidedly small)
> niche of folks who would be interested.
>

What is your project?

Like probably anyone in this situation, I have written a bunch of little 
convenience tools working with images, a simple matplotlib based gui to 
provide richer imshow image interaction (clicking to get pixel 
coordinates), more user friendly wrappers around scipy functions to do 
what is at least the most common case for us, and things of that sort.

Is any of this stuff I should be looking to upstream or split off into 
the start of a scientific imaging library for python?

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[Matplotlib-users] contour3D custom levels possible?

2010-08-01 Thread Tom Arens
Hello everyone,

does anybody know why the contour3D function has a fixed set of levels?

contour3D(X, Y, Z, levels=10, **kwargs)

I want to plot only one line for one level. With "contourf" it works:



from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt

fig = plt.figure()
ax = axes3d.Axes3D(fig)
X, Y, Z = axes3d.get_test_data(0.05)
cset = ax.contourf(X, Y, Z, 0)  # doesn't work with contour
ax.clabel(cset, fontsize=9, inline=1)

plt.show()



Many greetings,
Tom

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Re: [Matplotlib-users] contour3D custom levels possible?

2010-08-01 Thread Tom Arens
Hello,

I thought that it has to be like Ben wrote:

-def contour(self, X, Y, Z, levels=10, **kwargs):
+def contour(self, X, Y, Z, *args, **kwargs):


Your suggestion Eric ( contour(X, Y, Z, [0] ) doesn't work as the levels
are still the same.

Can you translate this thread for a "normal" user? Is this a bug and
will be fixed in a newer version of matplotlib or what do I have to do
to get "less levels"?

Thank you for your help.
Tom



Am 01.08.2010 20:12 schrieb Eric Firing:
> On 08/01/2010 07:35 AM, Benjamin Root wrote:
>> On Sun, Aug 1, 2010 at 9:55 AM, Tom Arens > <mailto:tak...@gmx.de>> wrote:
>>
>> Hello everyone,
>>
>> does anybody know why the contour3D function has a fixed set of levels?
>>
>> contour3D(X, Y, Z, levels=10, **kwargs)
>>
>> I want to plot only one line for one level. With "contourf" it works:
>>
>>
>>
>> from mpl_toolkits.mplot3d import axes3d
>> import matplotlib.pyplot as plt
>>
>> fig = plt.figure()
>> ax = axes3d.Axes3D(fig)
>> X, Y, Z = axes3d.get_test_data(0.05)
>> cset = ax.contourf(X, Y, Z, 0)  # doesn't work with contour
>> ax.clabel(cset, fontsize=9, inline=1)
>>
>> plt.show()
>>
>>
>>
>> Many greetings,
>> Tom
>>
>>
>> Hmm, interesting.  Looking at the contour3d call signature, it appears
>> that 'levels' was put into the call signature to basically remove that
>> keyword argument from the kwargs that get passed down to the 2-d version
>> of contour.  It is never used in the body of contour3d().
>>
>> I would guess that this is might be a remnant of some original code that
>> actually used the levels parameter.  Simply removing levels=0 from the
>> call signature seems to fix it (and passing [0] to levels as well since
>> it expects a sequence).
>>
>> As a matter of consistency, I think the call signature should be changed
>> to better match the call signature for contourf3d() and for the 2-d
>> version of contour().
> 
> Ben,
> 
> Good idea, go ahead.  The contourf3d docstring can also be modified to 
> match your change to the contour3d docstring.
> 
> I would consider all this as bug-fixing, so it can go in branch and trunk.
> 
> Thanks.
> 
> Eric
> 
>>
>> Ben Root
>>
> 
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[Matplotlib-users] [ANN] grima -- pygtk+ widget that embeds matplotlib

2010-09-07 Thread Tom Vaughan
Hello,

Today we have made Grima available as free software under the MIT
license. Grima is a pygtk+ widget that embeds matplotlib. Basically,
this means that Grima allows matplotlib to play nicely with the GTK+
main loop. Grima is hosted on GitHub at http://github.com/cdsi/grima.

Please note that this is a very early alpha release. There is very
little documentation on how to use Grima, or on its future plans. Our
needs are related to being able to visualize arbitrary sets of time
series data (like device measurements), as well as store and retrieve
this data in a modular way. We plan to provide a mechanism to work
with structured JSON data in couchdb or redis. For now, applications
simply pass x and y values per the current matplotlib API. We have
decided to make Grima available at this point so that others have the
opportunity to evolve it beyond our own limited scope. Contributions
(ideas, critiques, patches) are welcomed. To start, please take a look
at: http://github.com/cdsi/grima/blob/master/bin/grima-subplot.py.

I am more than happy to answer any questions. You may contact me
directly at t...@creativedigitalsys.com, or at
cdsi-l...@googlegroups.com. The latter is a Google Group that covers
Grima as well as some other bits of free software also released today.
A list of these are up at http://github.com/cdsi.

Thank you,
-Tom

PS - A special thanks to the matplotlib community, and to
http://unpythonic.blogspot.com/2007/08/using-threads-in-pygtk.html for
all of the excellent work upon which Grima is based.

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Re: [Matplotlib-users] caveats found installing matplotlib from svn source on python 2.7 in mac os x Leopard

2011-01-02 Thread Tom K.


ayg256 wrote:
> 
> First of all, thanks to the matplotlib developers for all the great job. 
> I
> have just successfully installed matplotlib from source (r8827) in my
> macbook for python 2.7. However, I found a couple of bumps in the road
> that
> I'd like to share:
> 
> ...
> 
> Cheers,
> 
> AY
> 

Dear AY,

Thanks so much for posting your followup.  I just went through building
matplotlib 1.0.0 from source on my new iMac and your directions were
invaluable.  I did need to make some minor modifications to match the
peculiarities of my setup - for example I am installing it with python 2.6.  

PYC FILE ISSUES
After install and the manual copy to /Library/Python/2.6/site-packages
(which is where numpy and scipy get built on this machine), the pyc files
are pointing to /usr/local/lib still, which is something that shows up in
ipython when browsing functions, and in backtraces... apparently this is a
bug in python that got fixed in 2.7.  To work around, I just remade the pyc
files.  I recompiled them all with compileall.compile_dir.  The copying and
pyc compilation had to be done with sudo commands since I didn't have
permissions.

FOURIER DEMO - PROBLEM AND FIX IN "lines.py"
Next I tried my wx-based gui http://wiki.wxpython.org/MatplotlibFourierDemo.
It raised assertions in lines.py, particularly the part where it tries to
access
path, affine =
self._transformed_path.get_transformed_path_and_affine()
(line 286) 
since self._transformed_path is None.
When I fixed that by inserting
if self._transformed_path is None:
self._transform_path()
then it ran into problems with
   ind += self.ind_offset
since ind_offset didn't exist.
I fixed that by adding 
if hasattr(self, 'ind_offset'): 

Is modifying lines.py the only way to fix this, or should I do something
else in the fourier demo?

Best regards, Happy New Year to all, etc, 
 - Tom K.

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[Matplotlib-users] memory usage with repeated imshow

2011-02-09 Thread Tom Dimiduk
I am using matplotlib pylab in association with ipython -pylab to show 
many large (~2000x2000 or larger) images.  Each time I show another 
image it consumes more memory until eventually exhausting all system 
memory and making my whole system unresponsive.

The easiest way to replicate this behaviour is with
a = ones((,))
imshow(a)

optionally

close()

and then

imshow(a)

again.  I am using ipython .10.1 and matplotlib 0.99.3.  Is there 
something I should be doing differently to avoid this problem?  Is it 
fixed in a later version?

Thanks,
Tom

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Re: [Matplotlib-users] Any update on streamline plot

2011-02-13 Thread Tom Flannaghan

Hi,

I've written a script to roughly emulate the elegant streamline plots found in 
Mathematica. The code is available at 
http://www.atm.damtp.cam.ac.uk/people/tjf37/streamplot.py and example plots at 
http://www.atm.damtp.cam.ac.uk/people/tjf37/streamlines1.png and 
streamlines2.png. It's a pretty hacky script, but fast and fairly robust. If 
anyone finds this script useful and has comments/suggestions, I'm happy to do a 
bit more work.

It would also be helpful if anyone has suggestions on a particular issue I had. 
Currently, to plot variable-width lines (i.e. streamlines2.png) I use a plot 
command for each line segment which is very slow and nasty. Is there a better 
way I'm missing?

Tom


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Re: [Matplotlib-users] memory usage with repeated imshow

2011-02-14 Thread Tom Dimiduk
Thank you for your help.  I upgraded to the latest development version, 
and as you said, memory use dropped a ton.  I will have to test more to 
confirm that the problem is completely gone, but this appears to bring 
memory usage down to something quite manageable (at least on my 8gb box 
...).

Tom

On 02/09/2011 07:30 PM, Robert Abiad wrote:
> Tom,
>
> I just went through this, though with version 1.01 of mpl, so it may be 
> different.  You can read the
> very long thread at:
>
> http://www.mail-archive.com/matplotlib-users@lists.sourceforge.net/msg20031.html
>
> Those who maintain mpl don't think there is a memory leak. What I found was 
> that imshow() does
> consume a lot of memory (now fixed in the development version) and that the 
> first 2 or so uses build
> on each other, but after that it levels off giving back memory after close(). 
>  There is a
> discrepancy between what python reports it's using and what the OS reports (I 
> had 500MB from the OS,
> but only 150MB from python).  There is a chance that ipython is caching your 
> results (try ipython
> -pylab -cs 0), but when I ran without ipython, python still had a large 
> portion of memory.
>
> -robert
>
> On 2/9/2011 3:52 PM, Tom Dimiduk wrote:
>> I am using matplotlib pylab in association with ipython -pylab to show
>> many large (~2000x2000 or larger) images.  Each time I show another
>> image it consumes more memory until eventually exhausting all system
>> memory and making my whole system unresponsive.
>>
>> The easiest way to replicate this behaviour is with
>> a = ones((,))
>> imshow(a)
>>
>> optionally
>>
>> close()
>>
>> and then
>>
>> imshow(a)
>>
>> again.  I am using ipython .10.1 and matplotlib 0.99.3.  Is there
>> something I should be doing differently to avoid this problem?  Is it
>> fixed in a later version?
>>
>> Thanks,
>> Tom
>>
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Re: [Matplotlib-users] Any update on streamline plot

2011-02-16 Thread Tom Flannaghan

> Ben, John:  Later this week or next, I'll take a crack at adding both of 
> these 
to quiver.py and 
> axes.py (one under the name "streamlines", the other as "streamplot").  

This is a great idea. I've had some time to improve the code, and so you have 
something better to work with! If you have any questions or need the code 
modifying, I'm happy to help - should have free time at the weekend and next 
week. I've also added density in both directions (nice idea - hadn't thought 
about this) and variable color as well as width.

The new code is at http://www.atm.damtp.cam.ac.uk/people/tjf37/streamplot.py 
and 
there are new sample plots at 
http://www.atm.damtp.cam.ac.uk/people/tjf37/streamlines1.png and 
http://www.atm.damtp.cam.ac.uk/people/tjf37/streamlines2.png .

> You probably want to use a compound path (one object for the entire
> plot).  See the tutorial 
athttp://matplotlib.sourceforge.net/users/path_tutorial.html, in
> particular the compound path for the histogram example near the end,
> and let me know if you have any questions.

John, thanks for the hints. In the end I used a LineCollection for each 
streamline because I didn't see how to set different properties (colour and 
width) for different portions of the line in the compound path. LineCollection 
performs well enough for this plot so I'm happy with this solution.

Tom


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[Matplotlib-users] Imshow x and y transposed?

2011-03-15 Thread Tom Dimiduk
It appears to me that when imshow tells you that the mouse cursor is at
x=50, y=100

That corresponds to array element
im[100, 50]

Is there a reason imshow does not have x be the first coordinate of the 
array as I would think of as conventional usage?

Tom

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Re: [Matplotlib-users] Imshow x and y transposed?

2011-03-15 Thread Tom Dimiduk
Ah thanks.  I am used to the general math/physics convention of x axis 
being first.  Caught between conventions I guess.  Good to know why 
things are done differently.

I am using the mouse click event.xdata and event.ydata as indexes into 
an array.  From what you say, it looks like I want to use
im[im.shape[1]-y, x] to get the pixel a user clicked on.  Is that correct?

Thanks agaian,
Tom

On 03/15/2011 05:35 PM, Eric Firing wrote:
> On 03/15/2011 10:23 AM, Tom Dimiduk wrote:
>> It appears to me that when imshow tells you that the mouse cursor is at
>> x=50, y=100
>>
>> That corresponds to array element
>> im[100, 50]
>>
>> Is there a reason imshow does not have x be the first coordinate of the
>> array as I would think of as conventional usage?
>
> That is not conventional usage.  Instead, for images, it common for the
> image to correspond to a printout of memory, using the C convention.
> Hence the column index is X, and incrementing the row index yields the
> next line down on the page, thereby corresponding to a decrease in the Y
> coordinate.
>
> Eric
>
>>
>> Tom
>
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[Matplotlib-users] Qt4 Backend Gui Keycode patch

2011-04-11 Thread Tom Dimiduk
The arrow keys were not being correctly detected in the Qt4 backend of 
the matplotlib gui code, so I went in and hooked up keycodes for them.


I haven't submitted patches before, but I thought this was worth passing 
on, so I have attached it.  Is this something worth submitting?  How 
would I go about doing that?


Tom
--- backend_qt4.py  2011-04-11 11:37:21.200228001 -0400
+++ /home/tdimiduk/download/matplotlib/lib/matplotlib/backends/backend_qt4.py   
2011-04-11 11:44:46.77000 -0400
@@ -126,11 +126,7 @@
 keyvald = { QtCore.Qt.Key_Control : 'control',
 QtCore.Qt.Key_Shift : 'shift',
 QtCore.Qt.Key_Alt : 'alt',
-QtCore.Qt.Key_Return : 'enter',
-QtCore.Qt.Key_Left : 'left',
-QtCore.Qt.Key_Right : 'right',
-QtCore.Qt.Key_Up : 'up',
-QtCore.Qt.Key_Down : 'down'
+QtCore.Qt.Key_Return : 'enter'
}
 # left 1, middle 2, right 3
 buttond = {1:1, 2:3, 4:2}
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Re: [Matplotlib-users] Best way to cycle through numpy images using scroll?

2011-08-17 Thread Tom Dimiduk
Here is how am solving this problem.  It isn't terribly fast either, but 
it works for me.  I wrote something with pygame that was faster, but it 
had its own set of problems.

Tom

---

import numpy as np
import pylab

class plotter:
 def __init__(self, im, i=0):
 self.im = im
 self.i = i
 self.vmin = im.min()
 self.vmax = im.max()
 self.fig = pylab.figure()
 pylab.gray()
 self.ax = self.fig.add_subplot(111)
 self.draw()
 self.fig.canvas.mpl_connect('key_press_event',self.key)

 def draw(self):
 if self.im.ndim is 2:
 im = self.im
 if self.im.ndim is 3:
 im = self.im[...,self.i]
 self.ax.set_title('image {0}'.format(self.i))

 pylab.show()

 self.ax.imshow(im, vmin=self.vmin, vmax=self.vmax, 
interpolation=None)


 def key(self, event):
 old_i = self.i
 if event.key=='right':
 self.i = min(self.im.shape[2]-1, self.i+1)
 elif event.key == 'left':
 self.i = max(0, self.i-1)
 if old_i != self.i or old_j != self.j:
 self.draw()
 self.fig.canvas.draw()


def show(im, i=0):
 plotter(im, i)


On 08/17/2011 01:26 PM, Keith Hughitt wrote:
> I'm also looking into a similar issue, and would be interested to see
> what approaches others have taken.
>
> Has anyone found a good framework-independent solution?
>
> Keith
>
> On Wed, Aug 10, 2011 at 5:15 PM, David Just  <mailto:just.da...@mayo.edu>> wrote:
>
> I have an array of images stored as an array of numpy arrays.   I
> need to be able to efficiently scroll through that set of images.
>My first attempt at doing this goes something like this:
>
> --init--
>
> self.ax <http://self.ax> = pyplot.imshow(imgdta[0],
> interpolation='spline36', cmap=cm.gray, picker=True)  # draw the
> plot @UndefinedVariable
>  pyplot.axes().set_axis_off()
>  self.fig = self.ax.get_figure()
>  self.canvas = FigureCanvasGTKAgg(self.fig)
>
> --onscroll--
>  self.ax.set_array(imdta[n]) # 0 < n < num_images
>  self.canvas.draw()
>
>
> This method of changing the image data does not seem to be very
> preferment.  It takes ~.25 seconds to go from one image to the next.
>Can anybody suggest a faster way?  This also ends up in a canvas
> that’s much larger than I need, is there a better way to define my
> view area?
>
>
> Thank you,
> Dave.
>
> 
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Re: [Matplotlib-users] Best way to cycle through numpy images using scroll?

2011-08-17 Thread Tom Dimiduk
Excellent!  That sped things up quite a bit.  I can now flip through my 
small images with no perceivable delay.  I will look forward to trying 
out the new interpolation setting when it gets here, since I have some 
larger images that still lag slightly.

If others want, I can repost my code with Ben's changes.

Thanks a bunch!
Tom

On 08/17/2011 03:30 PM, Benjamin Root wrote:
> Two issues with your code that should significantly speed things up.
>
> First, by calling imshow() each time for the draw, there is significant
> overhead caused by this.  Instead -- (and this is a huge speedup) --
> save the object returned by the first call to imshow().  That object has
> a method ".set_array()" that will allow you to just change the data
> contained within the AxesImage object.  This is *much* faster than
> calling imshow() repeatedly.  Note that the array going into set_array()
> will have to be of the same shape as the original image.
>
> Second, by setting the "interpolation" kwarg to *None*, you are merely
> telling imshow() to use the default interpolation specified in your
> rcParams file.  Instead, you probably want "nearest".  Actually,
> supposedly, the upcoming release is supposed to support a new value
> "none" for absolutely no interpolation at all.  The idea would be that
> one would pre-interpolate the image data before sending it to imshow()
> and have imshow set to do no interpolations at all.  Therefore, the
> images display much faster.
>
> I hope this helps!
> Ben Root

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[Matplotlib-users] equivalent of currentpoint?

2007-01-08 Thread Tom Krauss
Hi,

  I am very new to matplotlib (running 0.87.5 on Mac OS X) and just  
joined this maillist today.  I just discovered "getp" and "setp"  
today, very nice!

  I am wondering if there is an analog of the axes and/or figure's  
'currentpoint' property to access the current mouse location, and the  
figure's 'windowbuttonmotionfcn' (and up and down respectively) for  
responding to mouse click events?

   Thanks in advance,
  Tom Krauss


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Re: [Matplotlib-users] equivalent of currentpoint?

2007-01-08 Thread Tom Krauss
I just found Section 3.14 Event Handling in the User's Guide, so  
never mind!  Thanks anyway and sorry for the newbie spam - I broke  
the rule about reading the manual first before asking!   I will try  
some examples.
  - Tom

On Jan 8, 2007, at 3:58 PM, Tom Krauss wrote:
>  I am wondering if there is an analog of the axes and/or figure's  
> 'currentpoint' property to access the current mouse location, and  
> the figure's 'windowbuttonmotionfcn' (and up and down respectively)  
> for responding to mouse click events?


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Re: [Matplotlib-users] multiple lines, multiple plots, single figure

2007-01-19 Thread Tom Denniston
if you're building an app i would suggest using the OO interface.
There are good examples in the examples directory.  But basically you
get a figure either by constructing it or using pylab.gcf and you can
add_axes to the figure and plot on them.  It is much more scalable for
an app than the pylab interface.

as for your original question, i'm afraid i've never seen the behavior
before and don't have a good answer.

--Tom


On 1/19/07, Jonathon Anderson <[EMAIL PROTECTED]> wrote:
> It's definitely not the behavior I'm seeing here. In my matploblibrc file,
> hold is set to True. Is there another value that might be influencing this?
>
> In any case, I don't want the behavior to be dependent on a config file: I'm
> building an application. Do you know how I might specify this behavior at
> run-time?
>
> ~jonathon
>
>
> On 1/19/07, Tom Denniston
> <[EMAIL PROTECTED]> wrote:
> > It might depend on what's in your matplotlib rc file but by default
> > the behavior I have always seen was each plot command adds to the
> > current figure (pylab.gcf()) until you do a pylab.clf().
> >
> > So the two commands lists you have below end up being functionally
> equivalent.
> >
> > --Tom
> >
> > On 1/19/07, Jonathon Anderson < [EMAIL PROTECTED]> wrote:
> > > I have several lines of data that I want to plot on the same graph, but
> > > every time I run the pylab.plot() function it redraws the graph from
> > > nothing. I've tried pylab.plot(*, hold=True) and pylab.hold(True), but
> it
> > > still happens. Can I add data to an existing figure, or do I have to
> pass
> > > all the data at once?
> > >
> > > e.g., Do I have to do this:
> > >
> > > pylab.plot(x1, y1, x2, y2, x3, y3, ...)
> > >
> > > or can I do this:
> > >
> > > pylab.plot(x1, y1)
> > > pylab.plot(x2, y2)
> > > pylab.plot(x3, y3)
> > > ...
> > >
> > > ~jonathon anderson
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Re: [Matplotlib-users] Matplotlib plotting performance

2007-07-05 Thread Tom Denniston

Oops that was the TKAgg profile results.  These are the WxAgg results
attached.  Sorry about that.

On 7/5/07, Tom Denniston <[EMAIL PROTECTED]> wrote:

I've been trying to profile and speed up an app that uses matplotlib.
I tried to write an example using simple pylab commands to reproduce
the slowness.  What I found was I could get a huge speedup just
avoiding unnecessary redraws.  I'm down now to passable behavior.
Plotting 6 series in two windows takes about one and a quarter
seconds.  I would like to improve this further, however, if it is
possible which is why I am posting.

The results with show() in between plots are:

In [5]: run u:/tdennist/test2.py
10.128132637

In [6]: run u:/tdennist/test2.py
10.3122053602

And without the superfluous draws:


In [7]: run u:/tdennist/test2.py
1.83904865901

In [8]: run u:/tdennist/test2.py
1.86751011294

In [9]: run u:/tdennist/test2.py
1.84959890227


Where 1.85 seconds is the time to do 2 iteractions of drawing 2 plots
with 3 lines each.  So about 0.9 to 1.0 sec to draw the plots once.

Is there anything obvious I can do to speed this up?  I looked a
profile results of this and found most of the time is spent in "draw"
functions.  I attached the profile results in kcachegrind format for
the faster method.

Under the animation section there is a suggestion that things are
faster if you pre allocate the line and then just update it's x or y
data.  Given the profile results, however, I don't think this would
help much and it would be kinda inconvenient for my app because I
don't know how many series I am gonna plot up front.

Also at the very bottom is the contents of my rc params.  I am using
WxAgg on windows with matplotlib 0.90.1 and python 2.5.



Code
---


import timeit

setup='''
import matplotlib
matplotlib.use('WXAgg')
from matplotlib.widgets import Cursor
import pylab, numpy
pylab.clf()
#pylab.show()
'''
code='''
fig = pylab.gcf()
p1 = fig.add_axes([0.075, 0.05, 0.8, .4], axisbg='#33')
cursor = Cursor(p1, useblit=True, color='green', linewidth=2.5 )
p2 = fig.add_axes([0.075, 0.55, 0.8, .4], axisbg='#33')
def test(n):
   for i in range(3):
   p1.plot(numpy.random.rand(n))
   #pylab.show()

   for i in range(3):
   p2.plot(numpy.random.rand(n))
   #pylab.show()


test(1000)
pylab.show()
'''

print timeit.Timer(code, setup=setup).timeit(2)



rc Params


figure.subplot.right 0.9
mathtext.cal cmsy10.ttf
font.fantasy fantasy
xtick.minor.pad 3
tk.pythoninspect False
legend.labelsep 0.005
image.aspect equal
font.cursive cursive
figure.subplot.hspace 0.2
xtick.direction in
axes.facecolor w
ytick.direction in
legend.pad 0.2
axes.axisbelow False
lines.markersize 6
figure.dpi 80
text.usetex False
text.fontangle normal
patch.edgecolor k
ps.useafm False
lines.solid_joinstyle miter
font.monospace monospace
xtick.minor.size 2
figure.subplot.wspace 0.2
savefig.edgecolor w
text.fontvariant normal
image.cmap jet
axes.edgecolor k
tk.window_focus False
text.fontsize medium
font.serif serif
savefig.facecolor w
ytick.minor.size 2
mathtext.mathtext2 False
numerix numpy
font.stretch normal
text.dvipnghack False
ytick.color k
lines.linestyle -
xtick.color k
xtick.major.pad 3
text.fontweight normal
patch.facecolor b
figure.figsize (8, 6)
axes.linewidth 1.0
lines.linewidth 0.5
savefig.dpi 150
verbose.fileo sys.stdout
svg.image_noscale False
font.size 12.0
lines.antialiased True
polaraxes.grid True
toolbar toolbar2
pdf.compression 6
grid.linewidth 0.5
figure.facecolor 0.75
ps.usedistiller False
legend.isaxes True
figure.edgecolor w
mathtext.tt cmtt10.ttf
contour.negative_linestyle (6.0, 6.0)
image.interpolation bilinear
lines.markeredgewidth 0.5
legend.axespad 0.02
lines.marker None
lines.solid_capstyle projecting
axes.titlesize large
backend TkAgg
xtick.major.size 5
legend.fontsize small
legend.shadow False
mathtext.it cmmi10.ttf
font.variant normal
xtick.labelsize small
legend.handletextsep 0.02
ps.distiller.res 6000
patch.linewidth 0.5
lines.dash_capstyle butt
lines.color b
figure.subplot.top 0.9
legend.markerscale 0.6
patch.antialiased True
font.style normal
grid.linestyle :
axes.labelcolor k
text.color k
mathtext.rm cmr10.ttf
interactive True
savefig.orientation portait
svg.image_inline True
ytick.major.size 5
axes.grid False
plugins.directory .matplotlib_plugins
grid.color k
timezone UTC
ytick.major.pad 3
legend.handlelen 0.05
lines.dash_joinstyle miter
datapath 
c:\local\python25\lib\site-packages\matplotlib-0.87.7-py2.5-win32.egg\matplotlib\mpl-data
image.lut 256
figure.subplot.bottom 0.1
legend.numpoints 4
font.sans-serif sans-serif
font.family serif
axes.labelsize medium
ytick.minor.pad 3
axes.hold True
verbose.level silent
mathtext.nonascii cmex10.ttf
figure.subplot.left 0.125
text.fontstyle normal
font.weight normal
matht

[Matplotlib-users] Irregular Dates

2007-07-18 Thread Tom Haddon
Hi Folks,

Newbie question here...

I have a question about plotting data with irregular dates. Here's a
sample of my data (completely fabricated):

2007-06-29 20:22:03, 612
2007-07-18 09:07:03, 658
2007-07-19 11:07:05, 600
2007-07-19 15:12:07, 734
etc., etc., etc..

What I mean by this is that I'm not collecting the data at regular time
intervals. So I'd like to plot this, and have found that the plot_date
function seems to be designed for specific known time intervals. Instead
I am currently converting each timestamp to an integer in seconds since
the epoch, and then plotting that. It works fine, except that I'd then
like to be able to display the correct dates in for the x-axis rather
than integers. I'm not sure how to override the values that are
displayed on the x-axis. Can anyone help out?

Here's my current code (this is within Django - import statements
omitted):

start_date = datetime.date(2006, 3, 1)
end_date = datetime.date(2007, 3, 31)

logs = Item.objects.filter(processing_start__range=(start_date,
end_date))

dates = [float(time.mktime(p.processing_start.timetuple())) for p in
logs]
durations = [float(p.duration()) for p in logs]

matplotlib.use('Cairo')
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot(dates, durations)
ax.set_title('Durations from %s to %s' % (start_date, end_date))
ax.grid(True)
ax.set_xlabel('Date')
ax.set_ylabel('Duration in Minutes')
canvas.draw()
imdata=StringIO()
fig.savefig(imdata,format='png')
return HttpResponse(imdata.getvalue(), mimetype='image/png')

Any help appreciated.

Thanks, Tom
-- 


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Re: [Matplotlib-users] Irregular Dates

2007-07-18 Thread Tom Haddon
On Wed, 2007-07-18 at 18:37 -0500, John Hunter wrote:
> On 7/18/07, Tom Haddon <[EMAIL PROTECTED]> wrote:
> \> What I mean by this is that I'm not collecting the data at regular time
> > intervals. So I'd like to plot this, and have found that the plot_date
> > function seems to be designed for specific known time intervals. Instead
> 
> Nope, it makes so assumption about the intervals between your dates.

I think you mean it makes no assumption about the intervals between my
dates? If so, I must be missing something. How am I supposed to pass the
data to the plot_date function? If I pass it in as integers from epoch I
get an error saying "year is out of range". If I pass it in as datetime
objects I get an error saying "TypeError: float is required".

Thanks, Tom

> 
> JDH
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Re: [Matplotlib-users] Irregular Dates

2007-07-19 Thread Tom Haddon
On Wed, 2007-07-18 at 20:02 -0500, John Hunter wrote:
> On 7/18/07, Tom Haddon <[EMAIL PROTECTED]> wrote:
> > I think you mean it makes no assumption about the intervals between my
> > dates? If so, I must be missing something. How am I supposed to pass the
> > data to the plot_date function? If I pass it in as integers from epoch I
> > get an error saying "year is out of range". If I pass it in as datetime
> > objects I get an error saying "TypeError: float is required".
> > m +1.415.871.4180
> > www.greenleaftech.net
> 
> Use the function matplotlib.dates.epoch2num to convert your epoch data
> into the mpl date format.  That or use "plot" with native python
> datetime obects in the latest mpl release.

John,

Thanks for the help so far. Think I'm making progress. However, I now
have a graph that's solid blue (the default line color, I guess). No
line, just solid blue.

Here's the data:

dates = [732748.962546, 732748.898183, 732748.846273, 732748.793252,
732748.569873, 732748.351782, 732748.296273, 732748.24015,
732748.046238, 732747.990046, 732747.484074, 732747.428762,
732746.858449, 732746.171238, 732745.759757, 732744.970671,
732744.879271, 732744.759259, 732744.344653, 732744.282025,
732744.169954, 732744.101169, 732744.047153, 732743.997037,
732743.412755, 732743.274005, 732743.124907, 732743.074074,
732743.019931, 732742.921481, 732742.870613, 732742.611551,
732742.300451, 732742.249977, 732741.995475, 732741.687882,
732741.425336, 732741.361088, 732741.117581, 732740.613704,
732739.330208, 732738.073218, 732738.013472, 732737.963576,
732737.912951, 732737.587951, 732737.522905, 732737.46213,
732737.405926, 732737.072662, 732736.909317, 732736.861215,
732736.810127, 732736.702442, 732736.411354, 732736.291123]
durations = [66.969, 68.234, 64.36,
67.61, 72.016, 71.0833329,
65.203, 72.25, 64.906, 72.344,
73.234, 68.953, 72.313,
62.969, 69.547, 71.313,
63.984, 68.171, 69.266,
65.937, 67.437, 71.703,
68.86, 62.816667, 63.266,
68.953, 67.094, 64.0, 69.234,
69.781, 64.031, 64.313, 63.75,
63.43, 63.5, 63.234, 63.383,
67.813, 63.101, 63.914,
67.781, 61.484, 64.047,
62.734, 64.171, 62.586,
66.61, 63.101, 67.297,
64.187, 63.203, 60.367, 63.25,
63.203, 64.383334, 62.5]

And here's the code:

matplotlib.use('Cairo')
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot_date(dates, durations)
ax.set_title('Title')
ax.grid(True)
ax.set_xlabel('Date')
ax.set_ylabel('Duration in Minutes')
canvas.draw()
imdata=StringIO()
fig.savefig(imdata,format='png')
return HttpResponse(imdata.getvalue(), mimetype='image/png')

Any ideas what I'm missing?

Thanks, Tom

> 
> JDH
-- 


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www.greenleaftech.net


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[Matplotlib-users] [Fwd: Re: Irregular Dates]

2007-07-19 Thread Tom Haddon
Hmm, looks like I was just missing a third argument '-' from the
plot_date function.

Thanks, Tom

 Forwarded Message ----
From: Tom Haddon <[EMAIL PROTECTED]>
To: John Hunter <[EMAIL PROTECTED]>
Cc: matplotlib-users@lists.sourceforge.net
Subject: Re: [Matplotlib-users] Irregular Dates
Date: Thu, 19 Jul 2007 13:39:58 -0700

On Wed, 2007-07-18 at 20:02 -0500, John Hunter wrote:
> On 7/18/07, Tom Haddon <[EMAIL PROTECTED]> wrote:
> > I think you mean it makes no assumption about the intervals between my
> > dates? If so, I must be missing something. How am I supposed to pass the
> > data to the plot_date function? If I pass it in as integers from epoch I
> > get an error saying "year is out of range". If I pass it in as datetime
> > objects I get an error saying "TypeError: float is required".
> > m +1.415.871.4180
> > www.greenleaftech.net
> 
> Use the function matplotlib.dates.epoch2num to convert your epoch data
> into the mpl date format.  That or use "plot" with native python
> datetime obects in the latest mpl release.

John,

Thanks for the help so far. Think I'm making progress. However, I now
have a graph that's solid blue (the default line color, I guess). No
line, just solid blue.

Here's the data:

dates = [732748.962546, 732748.898183, 732748.846273, 732748.793252,
732748.569873, 732748.351782, 732748.296273, 732748.24015,
732748.046238, 732747.990046, 732747.484074, 732747.428762,
732746.858449, 732746.171238, 732745.759757, 732744.970671,
732744.879271, 732744.759259, 732744.344653, 732744.282025,
732744.169954, 732744.101169, 732744.047153, 732743.997037,
732743.412755, 732743.274005, 732743.124907, 732743.074074,
732743.019931, 732742.921481, 732742.870613, 732742.611551,
732742.300451, 732742.249977, 732741.995475, 732741.687882,
732741.425336, 732741.361088, 732741.117581, 732740.613704,
732739.330208, 732738.073218, 732738.013472, 732737.963576,
732737.912951, 732737.587951, 732737.522905, 732737.46213,
732737.405926, 732737.072662, 732736.909317, 732736.861215,
732736.810127, 732736.702442, 732736.411354, 732736.291123]
durations = [66.969, 68.234, 64.36,
67.61, 72.016, 71.0833329,
65.203, 72.25, 64.906, 72.344,
73.234, 68.953, 72.313,
62.969, 69.547, 71.313,
63.984, 68.171, 69.266,
65.937, 67.437, 71.703,
68.86, 62.816667, 63.266,
68.953, 67.094, 64.0, 69.234,
69.781, 64.031, 64.313, 63.75,
63.43, 63.5, 63.234, 63.383,
67.813, 63.101, 63.914,
67.781, 61.484, 64.047,
62.734, 64.171, 62.586,
66.61, 63.101, 67.297,
64.187, 63.203, 60.367, 63.25,
63.203, 64.383334, 62.5]

And here's the code:

matplotlib.use('Cairo')
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot_date(dates, durations)
ax.set_title('Title')
ax.grid(True)
ax.set_xlabel('Date')
ax.set_ylabel('Duration in Minutes')
canvas.draw()
imdata=StringIO()
fig.savefig(imdata,format='png')
return HttpResponse(imdata.getvalue(), mimetype='image/png')

Any ideas what I'm missing?

Thanks, Tom

> 
> JDH
-- 


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mailto:[EMAIL PROTECTED]
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www.greenleaftech.net


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Re: [Matplotlib-users] 3D plotting support

2007-08-14 Thread Tom Denniston
You might take a look at tvtk.mlab and mavayi.

http://www.scipy.org/Cookbook/MayaVi



On 8/14/07, Eric Firing <[EMAIL PROTECTED]> wrote:
> Kaushik Ghose wrote:
> > Hi Everyone,
> >
> > I vaguely remember a comment from a poster a short while back that
> > suggested that 3D support in matplotlib was not serious. I would like to
> > ask what plans there are for 3D plotting support in this great library.
>
> There are no plans.  The topic keeps coming up, but no one has come
> forward to put steady work into it.  It is not entirely clear how much
> can be done using the present approach, which is a layer on top of a
> fundamentally 2D framework.
>
> Eric
> >
> > thanks!
> > -Kaushik
>
>
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[Matplotlib-users] matlab porting question

2007-08-17 Thread Tom Vaughan
Hi,

What's the equivalent command in matplotlib to matlab's "surf"? I
assume it's Axes3D.plot_surface. But this doesn't see to work. The
code to be ported is:

s = surf(linspace(0,2,100), linspace(-1,1,100), fe');

But in matplotlib I've come up with:

terrain = R.randn(100, 100) / 1

nbumps = 20

f = lambda x: [int(v) for v in x]

bumpsx = 100 * R.rand(1, nbumps)
bumpsx = map(f, bumpsx.round())
bumpsy = 100 * R.rand(1, nbumps)
bumpsy = map(f, bumpsy.round())

f = lambda x: [abs(v) for v in x]

terrain[bumpsx, bumpsy] = map(f, abs(R.randn(1, nbumps))) # TODO:
abs(randn(nbumps, nbumps))

f = lambda x, y: I.lfilter((N.ones((1, x,)) / x)[0], 1, y)

fterrain = (f(20, f(15, terrain).conj().T)).conj().T

x = N.linspace(0, 2, 100)
y = N.linspace(-1, 1, 100)
z = fterrain

surface = axes3d.plot_surface(x, y, z)

The problem is that x, y, and z all should have the same shape (or at
least I assume from the simple3d.py example). But in what's above, x
and y have a shape of (100,), and z has a shape of (100,100). What
should I do instead?

I'm more than happy to share all the source code if that would be
instructive. Thanks.

-Tom

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[Matplotlib-users] autoscale question

2007-08-22 Thread Tom Vaughan
Hi,

I have matplotlib 0.90.1 on YellowDog 3 PPC with Python 2.5 and all
the support libraries built by hand, and matplotlib-0.90.1 on Ubuntu
Feisty x86 via `aptitude install`. And let's say I have:

import pylab
pylab.plot([2.2, 2.3, 2.4], [0, 5, 1])
pylab.show()

Why on the YellowDog 3 system would the x-axis show up as 0 - 2.5, and
on the Ubuntu Feisty system would the x-axis show up as 2.2 - 2.4? I
am attempting to resolve an autoscale problem elsewhere, and I must of
screwed something up when I built matplotlib. But what?

Thanks.

-Tom

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Re: [Matplotlib-users] autoscale question

2007-08-28 Thread Tom Vaughan
On 8/23/07, Fabrice Silva <[EMAIL PROTECTED]> wrote:
> Le Wed, 22 Aug 2007 18:21:40 -0700, Tom Vaughan a écrit:
>
> > Why on the YellowDog 3 system would the x-axis show up as 0 - 2.5, and
> > on the Ubuntu Feisty system would the x-axis show up as 2.2 - 2.4? I am
> > attempting to resolve an autoscale problem elsewhere, and I must of
> > screwed something up when I built matplotlib. But what?
>
> Are you sure you have the same pref defined in conf files like
> ~/.matplotlib/.matplotlibrc for example ?

i deleted these on both machines. is there a way to force a particular
behaviour using ~/.matplotlib/.matplotlibrc?

-tom

>
>
>
> --
> Fabrice Silva
> [EMAIL PROTECTED]
> 06.15.59.07.61
>
>
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Re: [Matplotlib-users] autoscale question

2007-08-28 Thread Tom Vaughan
On 8/22/07, John Hunter <[EMAIL PROTECTED]> wrote:
> On 8/22/07, Tom Vaughan <[EMAIL PROTECTED]> wrote:
>
> > Why on the YellowDog 3 system would the x-axis show up as 0 - 2.5, and
> > on the Ubuntu Feisty system would the x-axis show up as 2.2 - 2.4? I
> > am attempting to resolve an autoscale problem elsewhere, and I must of
> > screwed something up when I built matplotlib. But what?
>
> The only explanation that makes sense to me is that you are picking up
> different versions of mpl.  Did you ever install from svn on any
> system?  You can print
>
> >>> import matplotlib
> >>> print matplotlib.__version__
>
> but that doesn't always help, because frequently different svn
> versions will print the same version number.  We should adopt the
> numpy and scipy system of tagging the version w/ the svn revision
> number
>
> JDH
>

sorry for the tardy reply (fsck'd mail filter)...

on yellowdog 3...

Python 2.5.1 (r251:54863, Jun 21 2007, 14:27:05)
[GCC 4.1.1] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib
>>> print matplotlib.__version__
0.90.1

on ubuntu feisty...

Python 2.5.1 (r251:54863, May  2 2007, 16:56:35)
[GCC 4.1.2 (Ubuntu 4.1.2-0ubuntu4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import matplotlib
>>> print matplotlib.__version__
0.87.7

funny. i thought these were the same version. so is the 0.90.1
behaviour the correct behavior?

thanks.

-tom

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[Matplotlib-users] Default Image Size

2007-08-28 Thread Tom Haddon
Hi Folks,

I'm creating a basic graph as follows:

revnos = [ p['revno'] for p in data ]
durations = [ p['duration'] for p in data ]

majorFormatter = FormatStrFormatter('%d')

matplotlib.use('Cairo')
fig = Figure()
canvas = FigureCanvas(fig)
ax = fig.add_subplot(111)
ax.plot(revnos, durations, '-')
ax.set_title('PQM pre-commit hook durations from Revision %s to %s' %
(revnos[0], revnos[-1]))
ax.xaxis.set_major_formatter(majorFormatter)

ax.grid(True)
ax.set_xlabel('Revision')
ax.set_ylabel('Duration in Minutes')
canvas.draw()
fig.savefig(OUTPUTFILE)

Seems to give me a default size of 1200x900 (which I assume is somehow
related to my screen size) - I've tried altering the fig = line as
follows:

fig = Figure(figsize=(8,6), dpi=100)

but can't seem to change the output size of the image.

Thanks, Tom
-- 


--
Tom Haddon
mailto:[EMAIL PROTECTED]
m +1.415.871.4180
www.greenleaftech.net


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[Matplotlib-users] edgecolor with usetex=True, usedistiller='pdf'

2007-09-23 Thread Tom Johnson
Hello,

When using usetex=True and

 savefig(file, facecolor='w', edgecolor='w')

The behavior of the generated EPS file is more like:
   facecolor=None
   edgecolor='w'

That is, the image's facecolor is tranparent...taking on the background
color of the latex document---while the edgecolor is definitely white.

This seems inconsistent to me, and I was wondering if there was a quick
solution.  I actually like that the facecolor is transparent (or
nonexistent)...and I would like the same to hold for the edgecolor.  As of
now, I have an ugly white border around my image.

Also, it seems like there needs to be an extra keyword or option.  Suppose
someone wanted a white facecolor in the (usetex=True) EPS file.  It doesn't
seem like this is currently possible.  It would be nice if I could specify:

savefig(file, facecolor=None, edgecolor=None)

Thoughts?




\documentclass{article}
\usepackage{pstricks}
\usepackage{graphicx}
\begin{document}
\psframe*[linecolor=blue](-10in,-10in)(10in,10in)
\includegraphics{test}



from matplotlib import rc, rcParams
rc('text', usetex=True)
rc('ps', usedistiller='xpdf')
from pylab import *
subplot(111,axisbg='red')
plot(range(10))
savefig('test.eps', facecolor='white', edgecolor='white')
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Re: [Matplotlib-users] edgecolor with usetex=True, usedistiller='pdf'

2007-09-23 Thread Tom Johnson
On 9/23/07, Tom Johnson <[EMAIL PROTECTED]> wrote:
>
>
> Also, it seems like there needs to be an extra keyword or option.  Suppose
> someone wanted a white facecolor in the (usetex=True) EPS file.  It doesn't
> seem like this is currently possible.  It would be nice if I could specify:
>
> savefig(file, facecolor=None, edgecolor=None)


It would also be nice if we could specify the axis background color to be
None as well (again, perhaps only useful when creating an EPS)...when using
the plot command.
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Re: [Matplotlib-users] edgecolor with usetex=True, usedistiller='pdf'

2007-09-26 Thread Tom Johnson
Any comments on this?  The behavior is, at best, inconsistent.  At worst,
the current behavior is incorrect, as it is not possible to have a white
facecolor when using usetex/xpdf.

On 9/23/07, Tom Johnson <[EMAIL PROTECTED]> wrote:
>
> On 9/23/07, Tom Johnson <[EMAIL PROTECTED]> wrote:
> >
> >
> > Also, it seems like there needs to be an extra keyword or option.
> > Suppose someone wanted a white facecolor in the (usetex=True) EPS file.  It
> > doesn't seem like this is currently possible.  It would be nice if I could
> > specify:
> >
> > savefig(file, facecolor=None, edgecolor=None)
>
>
> It would also be nice if we could specify the axis background color to be
> None as well (again, perhaps only useful when creating an EPS)...when using
> the plot command.
>
>
>
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[Matplotlib-users] Equal Aspect Ratio with colorbar

2007-09-26 Thread Tom Johnson
How can I keep a 1:1 aspect ratio after adding a colorbar?

ratio='exact' seems to include the colorbar in the calculations.  For
example, if I have a circle and color itI want it to still look like a
circle (rather than an ellipse) after adding the colorbar.

~t
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Re: [Matplotlib-users] edgecolor with usetex=True, usedistiller='pdf'

2007-09-27 Thread Tom Johnson
On 9/27/07, Darren Dale <[EMAIL PROTECTED]> wrote:
> On Thursday 27 September 2007 01:28:46 am Tom Johnson wrote:
> > On 9/26/07, Darren Dale <[EMAIL PROTECTED]> wrote:
> > > I used your script to create the eps file, and created the attached
> > > postscript
> > > (you need an \end{document} in your latex code).
> >
> > Whoops!
> >
> >
> > Do you see anything wrong
> >
> > > with the resulting postscript? It looks fine to me.
> >
> > Indeed.  I didn't realize this before, but the problem is actually with the
> > pdf.  I have attached it.  Can you confirm that your pdf looks like mine?
>
> No, it does not look like yours. See attached.


Interesting.


>
> > Mine looks like this no matter which viewer I use (acrobat, evince, xpdf).
> > This makes me wonder if it is 1) the eps file or 2) the compilation
> > process.
>
> It is probably a problem with either ghostscript or pdftops.
>
> > Actually, the problem exists as early as the dvi file.
>
> The dvi looks fine here, and so does my pdf. It is often the case that
> problems with usetex are solved by updating the external dependencies. I am
> using:
>
> GPL Ghostscript 8.60
> pdftops version 3.00
> pdfeTeX 3.141592-1.30.5-2.2 (tetex-3.0_p1)
>
>
>


Hmm...I have:

ESP Ghostscript 8.15.04 (2007-03-14)
pdftops version 3.01(coming from libpoppler1 version 0.5.4-0ubuntu8)
pdfeTeX 3.141592-1.21a-2.2 (tetex-3.0.dfsg.3-4)

The CUPS page (http://www.cups.org/espgs/index.php) indicates that ESP
8.15.04 and GPL 8.57 have merged into 8.60.  This is probably the
solution.  So I will give that a try as a first fix and report back to
the list.

However, it will be a little while before I can provide a status
updateI have a presentation very soon and do not have the time to
regenerate all my images so that the background matches my
presentation background.  Since my setup had been creating
'transparent' facecolors, I did not bother setting facecolor at all
and kept the default. :(

Thanks!

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Re: [Matplotlib-users] edgecolor with usetex=True, usedistiller='pdf'

2007-09-27 Thread Tom Johnson
On 9/27/07, Tom Johnson <[EMAIL PROTECTED]> wrote:
> However, it will be a little while before I can provide a status
> updateI have a presentation very soon and do not have the time to
> regenerate all my images so that the background matches my
> presentation background.  Since my setup had been creating
> 'transparent' facecolors, I did not bother setting facecolor at all
> and kept the default. :(

Assuming that GPL 8.60 fixes the problem, do you anticipate that mpl
will move to support None as a color?  I realize this is a nontrivial
change to the color functionality...but there is a major portability
benefit.  With None as an option, I would probably always set the axis
background color, figure facecolor, and figure edgecolor to None.
Then, my figures would work no matter which theme I selected for my
presentationand it avoids the situation I am in now, which
requires significant time to regenerate images.


>
> Thanks!
>

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[Matplotlib-users] Histogram on shared axis

2007-11-25 Thread Tom Johnson
Is it possible to have a figure with two-plots such that

   f(x) is plotted against x   onaxis 1  (on the right)

   histogram of f(x) is plotted horizontally (on the right) sharing
the y-axis of axis 1



(sorry, this is proportional font, ascii art)


f(x)
 ^
  |
  |
  |
 counts  < ->  x


I want count=0 to be on the shared y-axis.  Perhaps log of counts as
well...so normal histogram options.

Thanks.

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Re: [Matplotlib-users] Histogram on shared axis

2007-11-25 Thread Tom Johnson
>histogram of f(x) is plotted horizontally (on the right) sharing
> the y-axis of axis 1

Typo:

   histogram of f(x) is plotted horizontally (on the LEFT) sharing the
y-axis of axis 1

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[Matplotlib-users] Colormap for LineCollection

2007-11-26 Thread Tom Johnson
I would like to plot a set of lines where the color of each line is
parametrized.  Then I want to add a colorbar to the plot.

For example, suppose I plot y=x+b for various values of b.  For each
line, I would like to set the color to a particular value of b.  When
plotting, all b values are normalized and applied to a colormap.  The
colormap will show all colors...

I can create a LineCollection containing all my lines...but I must
specify the colors as RGB tuplesand I haven't figured out how to
add a colorbar such that the scale on the colorbar will match the
parametrized b values.

Ideas?

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[Matplotlib-users] Adjust width between subplots

2007-11-27 Thread Tom Johnson
I'd like to make the separation distance between two subplots to be
much smaller. How can I achieve this?

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Re: [Matplotlib-users] Adjust width between subplots

2007-11-27 Thread Tom Johnson
On Nov 27, 2007 11:48 AM, John Hunter <[EMAIL PROTECTED]> wrote:
> Use the subplots_adjust paramters, eg
>
> fig.subplots_adjust(hspace=0)
>

This wasn't working for me...

from pylab import *
f = gcf()
f.subplots_adjust(hspace=0)
f.add_subplot(121)
f.add_subplot(122)
show()

Adjusting the space after adding the subplots did not work either (using SVN).

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Re: [Matplotlib-users] Adjust width between subplots

2007-11-27 Thread Tom Johnson
Doh!  Sorry, I adjusted the wrong space.

On Nov 27, 2007 11:56 AM, Tom Johnson <[EMAIL PROTECTED]> wrote:
> On Nov 27, 2007 11:48 AM, John Hunter <[EMAIL PROTECTED]> wrote:
> > Use the subplots_adjust paramters, eg
> >
> > fig.subplots_adjust(hspace=0)
> >
>
> This wasn't working for me...
>
> from pylab import *
> f = gcf()
> f.subplots_adjust(hspace=0)
> f.add_subplot(121)
> f.add_subplot(122)
> show()
>
> Adjusting the space after adding the subplots did not work either (using SVN).
>

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[Matplotlib-users] Nested Subplots?

2007-12-04 Thread Tom Johnson
Is it possible to have nested subplots?

I would like to have 2 rowswith the top row having two columns and
the bottom row having one column.

For the bottom plot, I'd like to be able to choose between the following:
  1) The size of the bottom plot expands to fill the entire horizontal space.
  2) The size of the bottom plot is unchanged (same as the other two
plots) and is simply centered in the bottom row.

x  x
  x

Thanks.

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[Matplotlib-users] Scatter Plot, Legend

2007-12-09 Thread Tom Johnson
I am plotting multiple scatter plots to the same axis.  For each
scatter plot, all points have the same shape and color.  I would like
the legend to display the shape and color of the data points in each
collection (rather than displaying a rectangle for the color).  The
result should be similar to the output from:

   plot(range(10), 'bo', label='1')
   legend()

The benefit with scatter is that I can have each data point being a
different size.

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Re: [Matplotlib-users] transparent background for encapsulated postscript output

2007-12-17 Thread Tom Johnson
On Dec 14, 2007 11:28 AM, Jeff Whitaker <[EMAIL PROTECTED]> wrote:
> Mike:  Postscript doesn't support alpha transparency.  It might work
> with PDF though.

pstricks (tex) provides transparency...

http://tug.org/PSTricks/main.cgi?file=Examples/Colors/colors#transparency
http://tug.org/PSTricks/main.cgi?file=pst-plot/3D/examples#coor


Is there any way to get similar hacks into matplotlib?  I'm guessing
this is a lot of work though.

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[Matplotlib-users] draw_if_interactive and ipython

2007-12-17 Thread Tom Johnson
Hi all,

I wasn't sure if this should be sent to matplotlib or ipython.  I'm
got a number of questions, and any help would be greatly appreciated.
The docstring for draw_if_interactive says:

"""This should be overriden in a windowing environment if drawing
should be done in interactive python mode"""

(there should be two d's in overridden)

First, I'm not quite sure what this meansdoesn't 'interactive'
imply 'interactive python mode'?  So shouldn't this function always
need overriding (strange that this doesn't have two d's)?

The definition is:

if matplotlib.is_interactive():

figManager = Gcf.get_active()
if figManager is not None:
figManager.canvas.draw()

Now, when I load with ipython -pylab, the definition is:

def wrapper(*args,**kw):
wrapper.called = False
out = func(*args,**kw)
wrapper.called = True
return out

Ipython says the definition is in genutils.py (ipython) but I can't
find it in there, and I don't know what "func" is.  This is the
ipython part of my email:  What does this function mean/do...and where
can I find where 'func' is defined.


Finally, the real reason for my email.  I've been writing functions
which perform more complicated plot commands.  In general, I don't
want the substeps to be shown, so I call matplotlib.interactive(False)
and then restore the state at the end of the function.  Then I call
pylab.draw_if_interactive(). The first issue is that this doesn't
really work.  Essentially this is what I am doing:

$ ipython -pylab
In [1]: ioff()
In [2]: plot(range(10))
In [3]: ion()
In [4]: draw_if_interactive()

On doing this, nothing shows up, unless I call show().  But the
following works without calling show

$ ipython -pylab
In [1]: plot(range(10))

Why?



Assuming I can get this to work...it seems like a good solution so
long as my functions are called from "ipython -pylab", but I would
also like to be able to call such functions inside a GUIand I am
concerned with the ramifications of the pylab.draw_if_interactive()
call.  The only pylab command in the plot functions is the
draw_if_interactive...and my (wxPython) GUI uses OO matplotlib
throughout.  Is this an issue? Do I need to overwrite this function?
If so, what needs to change so that I can use my functions in a GUI
(where I manually call draw) and in ipython.  The quickest solution is
to have each function accept an keyword which tells it whether or not
to call draw_if_interactive()...but this is pain...and doesn't seem
very elegant.  None of the matplotlib functions call
draw_if_interactive()...so perhaps there is another way to temporarily
turn off interactive mode and then restore the state.

Thanks.

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[Matplotlib-users] matplotlib/__init__.py

2008-01-13 Thread Tom Johnson
I was looking at rc_params() and saw

if not os.path.exists(fname):
message = 'could not find rc file; returning defaults'
ret =  dict([ (key, tup[0]) for key, tup in defaultParams.items()])
warnings.warn(message)
return ret

Is this correct?  It seems that it returns a regular dictionary rather
than an instance of RcParams.

~tj

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[Matplotlib-users] Forcing draw_if_interactive() to bring up new window...

2008-01-29 Thread Tom Johnson
I have functions which plot multiple items to an axis.  Often, I have
the function explicitly turn interactive mode off and then I turn it
back on to what it was before my function was called.  At the end of
my function, I call draw_if_interactive().

Suppose the user had interactive mode on prior to the function call.
The problem I am having is that draw_if_interactive() seems to have no
effect---no figure is drawn unless the user makes a subsequent call to
show().  Is there a way around this?

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[Matplotlib-users] Differences in appearance between FigureCanvasAgg and FigureCanvasWxAgg

2006-06-09 Thread Tom Denniston
FigureCanvasAgg seems to make fonts appear much larger that
FigureCanvasWxAgg.  I am trying to get plots generated interactively
in a wx window to appear the same as those that I generate in a no
display batch script that outputs .png files.  I use FigureCanvasWxAgg
for the former and FigureCanvasAgg for the latter.  Is there a reason
why the same font size would appear much larger in FigureCanvasAgg
than FigureCanvasWxAgg.  Is there another, better, way to achieve
uniformity accross png outputs and wx on screen display?

It doesn't look like one can use the FigureCanvasAgg for wx embedding
or the FigureCanvasWxAgg for png generation because the former will
not accept a parent window and the latter requires one.

If anyone has any ideas I would greatly appreciate suggestions.

--Tom


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Re: [Matplotlib-users] Differences in appearance between FigureCanvasAgg and FigureCanvasWxAgg

2006-06-11 Thread Tom Denniston
Thank you John.  I will try as you  suggest.  I really appreciate your help.

--Tom

On 6/10/06, John Hunter <[EMAIL PROTECTED]> wrote:
> >>>>> "Tom" == Tom Denniston <[EMAIL PROTECTED]> writes:
>
>Tom> FigureCanvasAgg seems to make fonts appear much larger that
>Tom> FigureCanvasWxAgg.  I am trying to get plots generated
>Tom> interactively in a wx window to appear the same as those that
>Tom> I generate in a no display batch script that outputs .png
>Tom> files.  I use FigureCanvasWxAgg for the former and
>Tom> FigureCanvasAgg for the latter.  Is there a reason why the
>Tom> same font size would appear much larger in FigureCanvasAgg
>Tom> than FigureCanvasWxAgg.  Is there another, better, way to
>Tom> achieve uniformity accross png outputs and wx on screen
>Tom> display?
>
>Tom> It doesn't look like one can use the FigureCanvasAgg for wx
>Tom> embedding or the FigureCanvasWxAgg for png generation because
>Tom> the former will not accept a parent window and the latter
>Tom> requires one.
>
>Tom> If anyone has any ideas I would greatly appreciate
>Tom> suggestions.
>
> backend_agg and backend_wxagg both use the same underlying pixel
> buffer, so you should be able to get uniformity between them.  Note,
> matplotlib has a different default dpi setting for figures for display
> and saving, and you might want to try forcing them to be the same with
>
> dpi = 72
> fig = figure(dpi=dpi)
> plot something
> fig.savefig(somefile, dpi=dpi)
>
> If that doesn't help, the only other possibility is that the
> PIXELS_PER_INCH defaults are getting you screwed up.  This was
> included for display devices which have a different number of pixels
> per inch; see
> http://groups.google.com/groups?q=screen+dpi+x11&hl=en&lr=&ie=UTF-8&oe=UTF-8&safe=off&selm=7077.26e81ad5%40swift.cs.tcd.ie&rnum=5
> for some info about screen dpi.  I vaguely recall that there was some
> good reason for including the pixels_per_inch constant *and* dpi,, but
> now I suspect the system may be overdetermined and we should drop this
> and just use the dpi setting.  In any case, each backend defines their
> own (see src/_backend_wxagg.cpp and backends/backend_wx.py) and the
> defaults are different in backend_agg and backend_wx).
>
>
> If the dpi suggestion above doesn't work, try setting PIXELS_PER_INCH
> in backend_wx.py to 72.
>
> JDH
>
>
>


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[Matplotlib-users] Line plots and missing data

2006-06-27 Thread Tom Denniston
When you do a line scatter plot in excel and data is missing between
two observations excel doesn't connect those two observations with a
line.  So what you see is a line with gaps where the data is missing.
Missing data is
defined as having x values but no y value or vice versa.  Is there a
good way to get similar behavior in matplotlib?

I tried to attach a bmp that had an example but the mail server
rejected it on the grounds it was too large.

--Tom

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Re: [Matplotlib-users] Line plots and missing data

2006-06-27 Thread Tom Denniston
Thanks John and Darren.  I think i'll use the nan trick for now but
the masked array looks  incredibly powerful.  I'll take a look at the
masked array demo.  Thanks once again for your help and  some really
awesome plotting software!

--Tom

On 6/27/06, Darren Dale <[EMAIL PROTECTED]> wrote:
> On Tuesday 27 June 2006 14:16, Tom Denniston wrote:
> > When you do a line scatter plot in excel and data is missing between
> > two observations excel doesn't connect those two observations with a
> > line.  So what you see is a line with gaps where the data is missing.
> > Missing data is
> > defined as having x values but no y value or vice versa.  Is there a
> > good way to get similar behavior in matplotlib?
>
> If you are using 0.87.3, you can do this:
>
> plot([1.1, 2, nan, 3, 5])
>
>
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[Matplotlib-users] Alpha and colorbar using contourf

2006-11-09 Thread Tom Denniston
When I use contourf with an alpha argument and the "hot" color scheme.  The alpha causes the colors to come out lighter but the colorbar does not adjust accordingly.  Is this a bug or do I simply need to adjust the colorbar in some manner?

 
 
 
Below is an adaptation of pcolor.py from the screenshots page and attached is the output I see.
 
I am using matplotlib 0.87.7:

In [3]: matplotlib.__version__Out[3]: '0.87.7'
 --
 
 

from __future__ import divisionfrom pylab import *
def func3(x,y):    return (1- x/2 + x**5 + y**3)*exp(-x**2-y**2)
dx, dy = 0.025, 0.025x = arange(-3.0, 3.0, dx)y = arange(-3.0, 3.0, dy)X,Y = meshgrid(x, y)
Z = func3(X, Y)
cset = contourf(Z, arange(-1.2,1.6,0.5),   origin='lower',   extent=(-3,3,-3,3), alpha=.5   )
axis('off')hot()colorbar()title('Some like it hot')show('example')


example.png
Description: PNG image
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Re: [Matplotlib-users] Alpha and colorbar using contourf

2006-11-09 Thread Tom Denniston
Thanks Eric.
On 11/9/06, Eric Firing <[EMAIL PROTECTED]> wrote:
Tom,This is a bug.  It looks like I completely forgot about handling alphawhen I rewrote the colorbar code.  I will try to get it fixed in the
next few days.  Thanks for the report.EricTom Denniston wrote:> When I use contourf with an alpha argument and the "hot" color scheme.> The alpha causes the colors to come out lighter but the colorbar does
> not adjust accordingly.  Is this a bug or do I simply need to adjust the> colorbar in some manner?>>>> Below is an adaptation of pcolor.py from the screenshots page and> attached is the output I see.
>> I am using matplotlib 0.87.7:>> In [3]: matplotlib.__version__> Out[3]: '0.87.7'>>  -->>>>
> from __future__ import division> from pylab import *>> def func3(x,y):> return (1- x/2 + x**5 + y**3)*exp(-x**2-y**2)>> dx, dy = 0.025, 0.025> x = arange(-3.0, 3.0
, dx)> y = arange(-3.0, 3.0, dy)> X,Y = meshgrid(x, y)>> Z = func3(X, Y)>>> cset = contourf(Z, arange(-1.2,1.6,0.5),>origin='lower',>extent=(-3,3,-3,3), alpha=.5
>)>>> axis('off')> hot()> colorbar()> title('Some like it hot')> show('example')>>> 
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Re: [Matplotlib-users] Alpha and colorbar using contourf

2006-11-14 Thread Tom Denniston
Thanks, Eric.  I will try it.
On 11/14/06, Eric Firing <[EMAIL PROTECTED]> wrote:
Tom,I have made several changes in svn to improve the ability of colorbar totrack changes in colormap and alpha.  It works with imshow, pcolor, and
contourf.  The implementation could be improved--maybe later.  Here areminimal illustrations you can use with ipython -pylab:figure(); C = pcolor(rand(3,3)); colorbar(); C.set_alpha(0.5); draw()figure(); C = contourf(rand(3,3)); colorbar(); 
C.set_alpha(0.5); draw()figure(); C = imshow(rand(3,3)); colorbar(); C.set_alpha(0.4); draw()The agg backend has trouble rendering the "continuous" colorbar withnon-unit alpha; it comes out somewhat striped.  Turning on antialiasing
makes it better for small to moderate alpha, but causes similarartifacts to appear for alpha=1, so I don't know of any good solution.Good appearance is more important for the most common case of alpha=1,so I am leaving antialiasing off.  I haven't checked other backends that
support alpha.Eric-Take Surveys. Earn Cash. Influence the Future of ITJoin SourceForge.net's Techsay panel and you'll get the chance to share your
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[Matplotlib-users] artist.py

2006-12-05 Thread Tom Denniston
I've been profiling some of my code which builds many somewhat complex
graphs.  I've noticed that it spends almost all it's time in the
__init__ of the artist class.  The time there is almost entirely spent
on calling identity_transform which builds a SeperableTransform that
does no transforming--from what I can tell--which is consistent with
the name.  The identity transform function buid a bunch of other
objects all of which are the same each time.  My question is, does it
really need to build all these objects over and over again.  Given
that Artist's __init__ is called by so many things wouldn't it be
better to have some static constants to define these default
transformation functions?  Am I missing something subtle or would this
be an improvement?


What do people think?




def zero(): return Value(0)

def one() : return Value(1)

def origin():
return Point( zero(), zero() )

def unit_bbox():
"""
Get a 0,0 -> 1,1 Bbox instance
"""
return  Bbox( origin(), Point( one(), one() ) )

def identity_affine():
"""
Get an affine transformation that maps x,y -> x,y
"""

return Affine(one(), zero(), zero(), one(), zero(), zero())

def identity_transform():
"""
Get an affine transformation that maps x,y -> x,y
"""
return SeparableTransformation(unit_bbox(), unit_bbox(),
   Func(IDENTITY),
   Func(IDENTITY))

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Re: [Matplotlib-users] artist.py

2006-12-06 Thread Tom Denniston
Sorry meant to send this to the whole list:


John,

Thanks for the fix.  After reading Eric's email I started to question
my profiling results but I still (without your fix) seem to see a
significant time when in Artist when generating large volumes of
graphs.  I need to rebuild my matplotlib against svn and test your fix
now to see if that solves the problem.

Thanks for your help.


--Tom



On 12/5/06, John Hunter <[EMAIL PROTECTED]> wrote:
> >>>>> "Christopher" == Christopher Barker <[EMAIL PROTECTED]> writes:
>
>Christopher> This sounds like a job for properties! make
>Christopher> _transform a property, and code that gets and sets it
>Christopher> directly should still work. though People that were
>Christopher> accessing an underscored name directly should expect
>Christopher> this kind of problem.
>
> The matplotlib artist kwarg properties act like python properties or
> enthought traits, with some advantages and disadvantages over each
> (mostly disadvantages, alas).  We've discussed migrating to one or
> another over the years, but haven't bitten the bullet.  At each point
> it's easier to extend the exiting implementation than refactor the
> whole bit; the tyranny of small decisions.
>
> Here are some of the pros and cons as I see them of enthought traits
> vs python properties
>
>   Pros:
>   * compatibility with the rest of the enthought tool suite
>   * built in observer pattern
>   * automatic UI for wx users
>   * performance is better than python properties last time I looked
>   * matplotlib ships with enthought traits built in
>
>   Cons:
>   * smaller user base than python properties may imply
> fewer 3rd party enhancements, less support, etc
>   * we have to maintain our copy of enthought traits to keep it
> current and building or require an additional dependency
>
> I spent some time working on matplotlib rc properties as enthought
> traits as a precursor to porting matplotlib properties to traits.
> Here is some example code showing how to define some representative rc
> properties and construct a matplotlib artist using traits.  Because
> matplotlib ships with enthought traits already, you can run this
> script with just matplotlib.  Unfortunately, we do not ship the ex UI
> component so you can't test that part.  I'm  a bit of a traits newbie
> so there are probably better ways to do what I have done below.
>
> import sys, os, re
> import matplotlib.enthought.traits as traits
> from matplotlib.cbook import is_string_like
> from matplotlib.artist import Artist
>
> doprint = True
> flexible_true_trait = traits.Trait(
>True,
>{ 'true':  True, 't': True, 'yes': True, 'y': True, 'on':  True, True: 
> True,
>  'false': False, 'f': False, 'no':  False, 'n': False, 'off': False, 
> False: False
>   } )
> flexible_false_trait = traits.Trait( False, flexible_true_trait )
>
> colors = {
>'c' : '#00bfbf',
>'b' : '#ff',
>'g' : '#008000',
>'k' : '#00',
>'m' : '#bf00bf',
>'r' : '#ff',
>'w' : '#ff',
>'y' : '#bfbf00',
>'gold' : '#FFD700',
>'peachpuff': '#FFDAB9',
>'navajowhite'  : '#FFDEAD',
>}
>
> def hex2color(s):
>"Convert hex string (like html uses, eg, #efefef) to a r,g,b tuple"
>return tuple([int(n, 16)/255.0 for n in (s[1:3], s[3:5], s[5:7])])
>
> class RGBA(traits.HasTraits):
># r,g,b,a in the range 0-1 with default color 0,0,0,1 (black)
>r = traits.Range(0., 1., 0.)
>g = traits.Range(0., 1., 0.)
>b = traits.Range(0., 1., 0.)
>a = traits.Range(0., 1., 1.)
>def __init__(self, r=0., g=0., b=0., a=1.):
>self.r = r
>self.g = g
>self.b = b
>self.a = a
>def __repr__(self):
>return 'r,g,b,a = (%1.2f, %1.2f, %1.2f, %1.2f)'%\
>   (self.r, self.g, self.b, self.a)
>
> def tuple_to_rgba(ob, name, val):
>tup = [float(x) for x in val]
>if len(tup)==3:
>r,g,b = tup
>return RGBA(r,g,b)
>elif len(tup)==4:
>r,g,b,a = tup
>return RGBA(r,g,b,a)
>else:
>raise ValueError
> tuple_to_rgba.info = 'a RGB or RGBA tuple of floats'
>
> def hex_to_rgba(ob, name,

[Matplotlib-users] Using Apple's freetype2 for mpl on OS X

2006-12-18 Thread Tom Loredo

Hi folks-

I'd like to report a possible way for OS X mpl users to use Apple's freetype2
(in their X11), to see if there are any problems with it I may need to be
aware of, and if not, to offer it as a possible solution to others installing
mpl from source on OS X.  I know Apple's freetype2 was "broken" in Panther,
but it's possible things are different with Tiger.

The basic issue is that Apple's X11 installs a version of freetype2 under
/usr/X11R6/ which might be usable by mpl, and which can conflict with other
copies users might install to build mpl.

With Panther (10.3), I followed mpl build instructions and installed my own
freetype2.  I tried two different methods:  using i-Installer, and directly
from source (into /usr/local/).  Both approaches worked fine with mpl.
However, using either version led to problems with other X11 software I tried
to install.  The issues I remember had to do with GTK (i.e., installing PyGTK
and an unrelated GTK app, geda, from source).  There were troublesome issues
having to do with freetype2 and some other X11 libs.  According to some
anecdotal reports I found online, it appears Apple did something strange to
the freetype version (at least in Panther versions of X11), so gcc/ld would
link against it even if a more recent version was in /usr/local/, but then
there would be freetype issues at runtime.  My eventual solution involved
removing various parts of Apple's X11, and putting links in /usr/X11R6/ to the
new installs in /usr/local/.  (I have a script to do this, if anyone needs
it.)

This was such a headache that when I just upgraded to Tiger (10.4; a clean
install), I thought I'd see if mpl could be installed using the new freetype2 
in Apple's X11.  (I also did not install zlib, since 10.4 includes it in
/usr/lib/.)  To do so, I had to modify "add_ft2font_flags" in setupext.py,
adding this to the top:

# Added to provide access to Apple's freetype2 when their X11 is installed
if sys.platform=='darwin':
# Add paths to Apple's X11R6.
module.library_dirs.extend(
['/usr/X11R6/lib'])

module.include_dirs.extend(
['/usr/X11R6/include'])

(Also, the docstring is incorrect and should be fixed to refer to freetype2
rather than gd.)  With this change, mpl built without any errors, and as far
as I can tell so far, is working just fine.  I've come across a few missing
font/font replacement warnings, but I don't know whether installing a new
freetype2 would have avoided these.

If anyone can see a problem with this procedure, please let me know.
Otherwise, it means that Tiger users who have installed Apple's X11 need to
install just one library (libpng) before installing mpl, so long as the above
change is made to setupext.py.  I don't know if the change would have any
ramifications for those who don't install X11 or who do install it and *also*
install freetype2 in /usr/local/.  If no problems are anticipated, perhaps
the change can be incorporated into mpl.

Thanks for any feedback on this.

-Tom


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[Matplotlib-users] Py2exe missing buttons icons on navigation toolbar

2011-02-06 Thread Tom van der Hoeven
Hello,

I have a simple program
---graf.py--

import matplotlib.pyplot as plt
plt.plot([1,2,3,8,0,9,1,10,5])
plt.ylabel('some numbers')
plt.show()
--
If I look to a matplotlib figures on my screen using the exe made with 
py2exe I mis all the buttons but one of the navigation bar.
If I work direct with the Python interpreted they are there.
I use the current version of Pythonxy

 setup.py --
from distutils.core import setup
import py2exe
import matplotlib

name = 'graf.py'
INCLUDES = [ 'sip' , 'matplotlib.numerix.random_array'
   #, 'PyQt4._qt'
, 'matplotlib.backends'
, 
'matplotlib.backends.backend_qt4agg']
#['matplotlib.backends.backend_qt4agg']
EXCLUDES = []
[ '_gtkagg' , '_tkagg' , 'Tkconstants' , 'Tkinter' ,'tcl' ]
#['_tkagg' , '_ps' , '_fltkagg' , 'Tkinter' , 'Tkconstants' , '_cairo' , 
'_gtk' , 'gtkcairo' ,
# 'pydoc' , 'sqlite3' , 'bsddb' , 'curses' , 'tcl' , 
'_wxagg' , '_gtagg' , '_cocoaagg' , '_wx' ]
DLL_EXCLUDES = ['MSVCP90.dll']
ICON_RESOURSES = []
OTHER_RESOURCES = []
DATA_FILES = matplotlib.get_py2exe_datafiles()

setup(name = name,
   version  = '1.0',
   options  = { "py2exe" : { 'compressed'   : 1,
 'optimize' : 2,
 'bundle_files' : 2,
 'includes' : INCLUDES,
     'excludes' : EXCLUDES,
 'dll_excludes' : DLL_EXCLUDES } 
} ,
   console  = [ { 'script'  : name,
  'icon_resources'  : ICON_RESOURSES,
  'other_resources' : OTHER_RESOURCES, } ] ,
   description  = 'Hele mooie',
   author   = 'Tom van der Hoeven',
   author_email = 't...@vanderhoeven.biz' ,
   maintainer   = 'Tom van der Hoeven',
   maintainer_email = 't...@vanderhoeven.biz',
   license  = '',
   url  = 'http://projecthomepage.com',
   data_files   = DATA_FILES,
   )
-
can you help me

Tom

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Re: [Matplotlib-users] Py2exe missing buttons icons on navigation toolbar

2011-02-06 Thread Tom van der Hoeven
Dear Sebastian,

Your solution is simple, well described and it works with minimal effort
Thank you so much!
I hope the Matplotlib devellopers will take some action.

Tom

Op 6-2-2011 13:16, Sebastian Voigt schreef:
> Hello Tom,
>
> I encountered the same problem recently. The toolbar icons are a mix of
> png and svg images. The png images are displayed properly while the svg
> icons are not shown.  This is a problem with PyQt. I found a proposal on
> the web, where you should add the line
>
>   import PyQt4.QtXml
>
> somewhere to your code. This is because xml support is needed to read
> svg files. However, this did not work for me. Instead I now use a rather
> ugly workaround: I rename the original *.png icon files to *.svg for
> those icons that are expected to be svg files. Qt will then find an svg
> file but it's clever enough to load it as png.
> Save those modified files somewhere as resources. Add them to the
> data_files list in your setup script and they will overwrite the
> original files at every build so you don't have to care any more.
>
> You can find out which files have to be renamed by looking into
> PACKAGEPATH/matplotlib/backends/backend_qt4.py line 399 and below.
> Another approach would be to directly rename the files in
> NavigationToolbar2QT._init_toolbar() to *.png since matplotlib provides
> png and svg files for every icon.
>
> Greetings,
>   Sebastian
>
>
> Am 06.02.2011 11:20, schrieb Tom van der Hoeven:
>> Hello,
>>
>> I have a simple program
>> ---graf.py--
>>
>> import matplotlib.pyplot as plt
>> plt.plot([1,2,3,8,0,9,1,10,5])
>> plt.ylabel('some numbers')
>> plt.show()
>> --
>> If I look to a matplotlib figures on my screen using the exe made with
>> py2exe I mis all the buttons but one of the navigation bar.
>> If I work direct with the Python interpreted they are there.
>> I use the current version of Pythonxy
>>
>>  setup.py --
>> from distutils.core import setup
>> import py2exe
>> import matplotlib
>>
>> name = 'graf.py'
>> INCLUDES = [ 'sip' , 'matplotlib.numerix.random_array'
>>  #, 'PyQt4._qt'
>>   , 'matplotlib.backends'
>>   ,
>> 'matplotlib.backends.backend_qt4agg']
>> #['matplotlib.backends.backend_qt4agg']
>> EXCLUDES = []
>> [ '_gtkagg' , '_tkagg' , 'Tkconstants' , 'Tkinter' ,'tcl' ]
>> #['_tkagg' , '_ps' , '_fltkagg' , 'Tkinter' , 'Tkconstants' , '_cairo' ,
>> '_gtk' , 'gtkcairo' ,
>>   # 'pydoc' , 'sqlite3' , 'bsddb' , 'curses' , 'tcl' ,
>> '_wxagg' , '_gtagg' , '_cocoaagg' , '_wx' ]
>> DLL_EXCLUDES = ['MSVCP90.dll']
>> ICON_RESOURSES = []
>> OTHER_RESOURCES = []
>> DATA_FILES = matplotlib.get_py2exe_datafiles()
>>
>> setup(name = name,
>>  version  = '1.0',
>>  options  = { "py2exe" : { 'compressed'   : 1,
>>'optimize' : 2,
>>'bundle_files' : 2,
>>'includes' : INCLUDES,
>>'excludes' : EXCLUDES,
>>        'dll_excludes' : DLL_EXCLUDES }
>> } ,
>>  console  = [ { 'script'  : name,
>> 'icon_resources'  : ICON_RESOURSES,
>> 'other_resources' : OTHER_RESOURCES, } ] ,
>>  description  = 'Hele mooie',
>>  author   = 'Tom van der Hoeven',
>>  author_email = 't...@vanderhoeven.biz' ,
>>  maintainer   = 'Tom van der Hoeven',
>>  maintainer_email = 't...@vanderhoeven.biz',
>>  license  = '',
>>  url  = 'http://projecthomepage.com',
>>  data_files   = DATA_FILES,
>>  )
>> -
>> can you help me
>>
>> Tom