[Matplotlib-users] colorbar() fix limit on Heat map

2008-08-11 Thread stuartornum

Hi All,

You may remember from my previous post I was having problems plotting a
heatmap, however Pete came through for me and made it work.

Anyway, I have almost finished what I want to do. The only issue is fixing
the colorbar() range limit.

Sometimes the my values are 0.01 to 0.2 for example, and other times there
0.01 to 0.99.

So what happens it the colorbar() automagically adjusts the gradient
according to my values, however I do not want it to do that, I want the
graph to be consistantly 0 - 1 (blue - red).

I have tried things like colorbar(0,1), however no luck.

If you could let me know how to fix the range, I would be very grateful.

Regards
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Re: [Matplotlib-users] colorbar() fix limit on Heat map

2008-08-11 Thread Jeff Whitaker
stuartornum wrote:
 Hi All,

 You may remember from my previous post I was having problems plotting a
 heatmap, however Pete came through for me and made it work.

 Anyway, I have almost finished what I want to do. The only issue is fixing
 the colorbar() range limit.

 Sometimes the my values are 0.01 to 0.2 for example, and other times there
 0.01 to 0.99.

 So what happens it the colorbar() automagically adjusts the gradient
 according to my values, however I do not want it to do that, I want the
 graph to be consistantly 0 - 1 (blue - red).

 I have tried things like colorbar(0,1), however no luck.

 If you could let me know how to fix the range, I would be very grateful.

 Regards
   
Stuart:  Use the vmin/vmax keyword arguments if your are using imshow or 
pcolor/pcolormesh.  If you are using contourf,  just specify the contour 
levels to span the range 0-1 (i.e. clevs=linspace(-1,1,15)).

-Jeff

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Re: [Matplotlib-users] colorbar() fix limit on Heat map

2008-08-11 Thread Jeff Whitaker
stuartornum wrote:
 Jeff,

 That worked perfectly ! Thank you.

 One more question... how would I change the colour scheme of the colorbar()?

 Thanks again
   
Stuart:  Use the cmap argument to specify a color map.

Have you checked out the pylab examples?  For me, they are the best way 
to learn how to use matplotlib effectively.

-Jeff


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[Matplotlib-users] SVG and pdf

2008-08-11 Thread Kaushik Ghose
Hi!

This may be a pdf issue or an SVG issue and have nothing to do with matplotlib. 
If so, sorry...

Whenever I produce a figure with matplotlib and 'crop it' using the axis 
command 
the svg comes out fine. However, when I save this svg to pdf using inkscape's 
'cairo' backend the part of the data that was 'cropped' becomes visible in the 
pdf. e.g. if I had plotted data from x = -2 to +10, and then I set the axes to 
only show the data from +3 to +6, the svg comes out fine, but the pdf shows the 
rest of the graph leaking out from the axes.

I currently have to manually crop my data to prevent this.

Thanks!
-K


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Re: [Matplotlib-users] SVG and pdf

2008-08-11 Thread Michael Droettboom
Sounds like a Inkscape/Cairo issue to me, if the PDF it converts doesn't 
match the SVG.  That said, SVG is tricky to get right, and we may be 
able to produce things in a different way that Inkscape will handle 
correctly.  I'll look into this and file a bug with Inkscape and/or 
Cairo if it turns out to be a bug on their end.

Does directly outputting the PDF from matplotlib work as a workaround?

Cheers,
Mike

Kaushik Ghose wrote:
 Hi!

 This may be a pdf issue or an SVG issue and have nothing to do with 
 matplotlib.
 If so, sorry...

 Whenever I produce a figure with matplotlib and 'crop it' using the axis 
 command
 the svg comes out fine. However, when I save this svg to pdf using inkscape's
 'cairo' backend the part of the data that was 'cropped' becomes visible in the
 pdf. e.g. if I had plotted data from x = -2 to +10, and then I set the axes to
 only show the data from +3 to +6, the svg comes out fine, but the pdf shows 
 the
 rest of the graph leaking out from the axes.

 I currently have to manually crop my data to prevent this.

 Thanks!
 -K



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Re: [Matplotlib-users] which basemap with matpotlib 0.91.2

2008-08-11 Thread Jeff Whitaker
Michael Hearne wrote:
 I'm trying to build an application on a newly installed Ubuntu.  I've 
 used apt-get to install scipy and matplotlib.

 numpy version: 1.0.4
 scipy version: 0.6
 matplotlib version: 0.91.2

 What version of basemap is safe to download and build with this 
 configuration?  Doing apt-cache search basemap yields no results, so I 
 assume there isn't an Ubuntu package for that.

 And if someone tells me I need to compile a newer scipy (and it's #$%^! 
 dependencies) from source, I'll scream.

 Thanks,

 Mike

   
Mike:  Basemap's now only supported  for matplotlib  0.98.  For that 
you need numpy 1.1 (you don't need scipy at all). 

-Jeff

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Re: [Matplotlib-users] which basemap with matpotlib 0.91.2

2008-08-11 Thread Michael Hearne
Jeff - Well, that's the problem  - I _do_ need scipy!  Not for basemap, 
but for the rest of my application.  Does your sourceforge repository 
have older copies of  the basemap code?

My complaint about scipy has to do with the fact that I spent a good 
week trying to get scipy's dependencies to install on two Red Hat 
Enterprise Linux systems:  I punted both of them over to an outside 
contractor, who was able to compile scipy on one system, but not the 
other.  And he specializes in that kind of stuff.

--Mike

Jeff Whitaker wrote:
 Michael Hearne wrote:
 I'm trying to build an application on a newly installed Ubuntu.  I've 
 used apt-get to install scipy and matplotlib.

 numpy version: 1.0.4
 scipy version: 0.6
 matplotlib version: 0.91.2

 What version of basemap is safe to download and build with this 
 configuration?  Doing apt-cache search basemap yields no results, 
 so I assume there isn't an Ubuntu package for that.

 And if someone tells me I need to compile a newer scipy (and it's 
 #$%^! dependencies) from source, I'll scream.

 Thanks,

 Mike

   
 Mike:  Basemap's now only supported  for matplotlib  0.98.  For that 
 you need numpy 1.1 (you don't need scipy at all).
 -Jeff


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Re: [Matplotlib-users] which basemap with matpotlib 0.91.2

2008-08-11 Thread Jeff Whitaker
Michael Hearne wrote:
 Jeff - Well, that's the problem  - I _do_ need scipy!  Not for 
 basemap, but for the rest of my application.  Does your sourceforge 
 repository have older copies of  the basemap code?

Mike:  OK, but I don't think upgrading numpy/maplotlib requires you to 
update scipy. 

The SF site does have older copies of basemap, but beware - I'm not 
backporting bugfixes.

-Jeff

 My complaint about scipy has to do with the fact that I spent a good 
 week trying to get scipy's dependencies to install on two Red Hat 
 Enterprise Linux systems:  I punted both of them over to an outside 
 contractor, who was able to compile scipy on one system, but not the 
 other.  And he specializes in that kind of stuff.

 --Mike

 Jeff Whitaker wrote:
 Michael Hearne wrote:
 I'm trying to build an application on a newly installed Ubuntu.  
 I've used apt-get to install scipy and matplotlib.

 numpy version: 1.0.4
 scipy version: 0.6
 matplotlib version: 0.91.2

 What version of basemap is safe to download and build with this 
 configuration?  Doing apt-cache search basemap yields no results, 
 so I assume there isn't an Ubuntu package for that.

 And if someone tells me I need to compile a newer scipy (and it's 
 #$%^! dependencies) from source, I'll scream.

 Thanks,

 Mike

   
 Mike:  Basemap's now only supported  for matplotlib  0.98.  For that 
 you need numpy 1.1 (you don't need scipy at all).
 -Jeff




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[Matplotlib-users] ticks labels

2008-08-11 Thread Jeffrey Fogel
I am having some trouble getting the ticks and labels on my plot to
match what I want and I was hoping that someone here would be able to
help.  Here are what I want (on the yaxis):

logarithmic ticks with major ticks every order of magnitude but labels
ONLY every other magnitude.  Additionally, I would like the labels to
be only the exponent (2 instead of 1e2 or 10^2).  For the minor ticks,
I want a tick at all 9 values between the major ticks.

Here is what I have so far.  For the minor ticks, I have
subsy=[1,2,3,4,5,6,7,8,9] as an argument for semilogy which seems to
work fine.  To have labels every other magnitude I used
ticker.LogLocator(base=100.0), which gives me the labels where I want
them.

The two things I have been unable to figure out are how to add a major
tick at all of the other magnitudes (those without a label) and how to
change the format of the labels so that only the exponent is showing.
I'm sure both of these are straightforward, but I have been unable to
figure them out.  Thanks for your help.

-Jeffrey

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Re: [Matplotlib-users] ticks labels

2008-08-11 Thread John Hunter
On Mon, Aug 11, 2008 at 1:45 PM, Jeffrey Fogel
[EMAIL PROTECTED] wrote:

 The two things I have been unable to figure out are how to add a major
 tick at all of the other magnitudes (those without a label) and how to
 change the format of the labels so that only the exponent is showing.
 I'm sure both of these are straightforward, but I have been unable to
 figure them out.  Thanks for your help.

You can accomplish both in one swoop using a custom formatter instead
of a custom locator.  That is, instead of using a
LogLocator(base=100.0) which isn't giving you ticks where you want
them, use the default log locator, and make a custom formatter to
suppress strings where you don't want them and to use the format you
want.  Eg, something like

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

fig = plt.figure()
ax = fig.add_subplot(111)

N = 1000
x = np.arange(N)
y = np.random.rand(N)*1e8

ax.semilogy(x, y)

class MyFormatter(ticker.LogFormatter):

def __call__(self, val, pos=None):
fx = int(np.log(abs(val))/np.log(self._base) +0.5)
isDecade = self.is_decade(fx)
if not isDecade and self.labelOnlyBase:
return ''
if (fx%2)==1: # odd, skip
return ''

return '%d'%fx


ax.yaxis.set_major_formatter(MyFormatter())
plt.show()

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Re: [Matplotlib-users] ticks labels

2008-08-11 Thread Jae-Joon Lee
A minor comment.
John's code may give incorrect results when exponents are negative.
int() truncates a floating point argument towards zero, e.g.,
int(-1.5) == -1  not -2. I guess calling floor() before int() will
work.

   fx = int(np.floor(np.log(abs(val))/np.log(self._base) +0.5))

-JJ


On Mon, Aug 11, 2008 at 3:23 PM, John Hunter [EMAIL PROTECTED] wrote:
 On Mon, Aug 11, 2008 at 1:45 PM, Jeffrey Fogel
 [EMAIL PROTECTED] wrote:

 The two things I have been unable to figure out are how to add a major
 tick at all of the other magnitudes (those without a label) and how to
 change the format of the labels so that only the exponent is showing.
 I'm sure both of these are straightforward, but I have been unable to
 figure them out.  Thanks for your help.

 You can accomplish both in one swoop using a custom formatter instead
 of a custom locator.  That is, instead of using a
 LogLocator(base=100.0) which isn't giving you ticks where you want
 them, use the default log locator, and make a custom formatter to
 suppress strings where you don't want them and to use the format you
 want.  Eg, something like

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

 fig = plt.figure()
 ax = fig.add_subplot(111)

 N = 1000
 x = np.arange(N)
 y = np.random.rand(N)*1e8

 ax.semilogy(x, y)

 class MyFormatter(ticker.LogFormatter):

def __call__(self, val, pos=None):
fx = int(np.log(abs(val))/np.log(self._base) +0.5)
isDecade = self.is_decade(fx)
if not isDecade and self.labelOnlyBase:
return ''
if (fx%2)==1: # odd, skip
return ''

return '%d'%fx


 ax.yaxis.set_major_formatter(MyFormatter())
 plt.show()

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Re: [Matplotlib-users] windrose OO

2008-08-11 Thread Christopher Barker

Lionel Roubeyrie wrote:
find with this message a modified version of windrose to be OO compliant. 


Lionel,

I've had this message of yours (from March), and finally had a chance to 
use it.


Unfortunately, it seems to use the old Transforms mechanism, so won't 
work with the latest MPL.


have you ported it over yet? Can anyone else help out with a port?

Thanks,

-Chris





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windrose_oo.py
Description: application/python
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Re: [Matplotlib-users] ticks labels

2008-08-11 Thread Jeffrey Fogel
Thanks John, that worked perfectly (with JJ's correction).  I'm fairly
new to python and hadn't considered writing a separate class for it.

-Jeffrey

On Mon, Aug 11, 2008 at 3:53 PM, Jae-Joon Lee [EMAIL PROTECTED] wrote:
 A minor comment.
 John's code may give incorrect results when exponents are negative.
 int() truncates a floating point argument towards zero, e.g.,
 int(-1.5) == -1  not -2. I guess calling floor() before int() will
 work.

   fx = int(np.floor(np.log(abs(val))/np.log(self._base) +0.5))

 -JJ


 On Mon, Aug 11, 2008 at 3:23 PM, John Hunter [EMAIL PROTECTED] wrote:
 On Mon, Aug 11, 2008 at 1:45 PM, Jeffrey Fogel
 [EMAIL PROTECTED] wrote:

 The two things I have been unable to figure out are how to add a major
 tick at all of the other magnitudes (those without a label) and how to
 change the format of the labels so that only the exponent is showing.
 I'm sure both of these are straightforward, but I have been unable to
 figure them out.  Thanks for your help.

 You can accomplish both in one swoop using a custom formatter instead
 of a custom locator.  That is, instead of using a
 LogLocator(base=100.0) which isn't giving you ticks where you want
 them, use the default log locator, and make a custom formatter to
 suppress strings where you don't want them and to use the format you
 want.  Eg, something like

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

 fig = plt.figure()
 ax = fig.add_subplot(111)

 N = 1000
 x = np.arange(N)
 y = np.random.rand(N)*1e8

 ax.semilogy(x, y)

 class MyFormatter(ticker.LogFormatter):

def __call__(self, val, pos=None):
fx = int(np.log(abs(val))/np.log(self._base) +0.5)
isDecade = self.is_decade(fx)
if not isDecade and self.labelOnlyBase:
return ''
if (fx%2)==1: # odd, skip
return ''

return '%d'%fx


 ax.yaxis.set_major_formatter(MyFormatter())
 plt.show()

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Re: [Matplotlib-users] windrose OO

2008-08-11 Thread Christopher Barker
Christopher Barker wrote:
 have you ported it over yet? Can anyone else help out with a port?

Note: it looks pretty easy, if yu know what you are doing:

from matplotlib.transforms import Interval, Value

Then in the code, I inly see Interval and Value used here:

 self.rintv = Interval(Value(0), Value(1))
 self.rintd = Interval(Value(0), Value(1))




Is there a guide to translating code from the old to new Transforms 
structure?

-CHB



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Re: [Matplotlib-users] windrose OO

2008-08-11 Thread John Hunter
On Mon, Aug 11, 2008 at 3:51 PM, Michael Droettboom [EMAIL PROTECTED] wrote:
 Christopher Barker wrote:
 Is there a guide to translating code from the old to new Transforms
 structure?

 Yes, in the API_CHANGES file, in the source distribution.  (I'd link to
 SVN, but it seems Sourceforge's SVN browser is down.)

We keep a copy of this file at http://matplotlib.sf.net/API_CHANGES
that is updated with every release  See also
http://matplotlib.sourceforge.net/MIGRATION.txt

JDH

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Re: [Matplotlib-users] windrose OO

2008-08-11 Thread John Hunter
On Mon, Aug 11, 2008 at 3:51 PM, Michael Droettboom [EMAIL PROTECTED] wrote:
 Christopher Barker wrote:
 Is there a guide to translating code from the old to new Transforms
 structure?

 Yes, in the API_CHANGES file, in the source distribution.  (I'd link to
 SVN, but it seems Sourceforge's SVN browser is down.)

We keep a copy of this file at http://matplotlib.sf.net/API_CHANGES
that is updated with every release  See also
http://matplotlib.sourceforge.net/MIGRATION.txt

JDH

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Re: [Matplotlib-users] Figure existence test

2008-08-11 Thread nobody

Bump...  Does no-one have a solution for this?

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Re: [Matplotlib-users] Figure existence test

2008-08-11 Thread John Hunter
On Mon, Aug 11, 2008 at 4:24 PM, nobody [EMAIL PROTECTED] wrote:

 Bump...  Does no-one have a solution for this?

Sorry for not answering.  There is no elegant way to do this so we
should add support.  In the meantime, the following hack should work

 figs = [manager.canvas.figure for manager in
pylab._pylab_helpers.Gcf.get_all_fig_managers()]

And you asked about testing to see if a figure exists -- do you mean
by figure number?  If so, you could check a number against the num
attribute from the figure list

 somenum in [fig.num for fig in figs]

JDH

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Re: [Matplotlib-users] Custom pan button

2008-08-11 Thread Jonathan Helmus

Sorry folks, I found my own problem.  Looks like the axes pan functions 
were a recent addition to matplotlib and the version I'm using, 0.91.2, 
doesn't have these.  Time to bug the system admin to update to the 0.98 
version.

-Jonathan Helmus

Jonathan Helmus wrote:
 I have been working on a GUI application which uses matplotlib as a wx 
 object.  I'd like to include a pan button on the toolbar of the 
 application but can't seem to get an axes object which has the pan 
 functions (which I'd like to use to tie into the pan code).  I have a 
 self.axes object that identifies itself as matplotlib.axes.Subplot 
 instance... which I use to add lines, set limits, etc but it doesn't 
 have any of the pan functions (start_pan, end_pan, etc).  
 self.canvas.figure.get_axes() (which is what seems to be used in the 
 NavigationToolbar2 class) returns the same Subplot instance. Any 
 suggestions of how to get a axes/Subplot instance which has the pan 
 functions?

 Thanks,
 -Jonathan Helmus
   

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Re: [Matplotlib-users] Custom pan button

2008-08-11 Thread Anthony Floyd
On Mon, Aug 11, 2008 at 1:31 PM, Jonathan Helmus [EMAIL PROTECTED] wrote:


[snip]

 instance... which I use to add lines, set limits, etc but it doesn't
 have any of the pan functions (start_pan, end_pan, etc).
 self.canvas.figure.get_axes() (which is what seems to be used in the
 NavigationToolbar2 class) returns the same Subplot instance. Any
 suggestions of how to get a axes/Subplot instance which has the pan
 functions?

Hi Jonathan,

On earlier versions of Matplotlib, you can use the NavigationToolbar2
class without actually displaying it (the toolbar) in your program.
Instead you can use your custom buttons, keypresses, etc, to tie into
the class' methods.  We've done that with our app, and it works quite
nicely.  In fact, you can borrow the bits you need from that class to
create your own zoom/pan routines.

Cheers,
Anthony.

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