matplotlib-users Mailing List for matplotlib

> To: Nils Wagner <nw...@me...>
> Cc: SciPy Users List <sci...@sc...>,
> 	mat...@li...
> Subject: Re: [Matplotlib-users] Visualizing Sparsity Pattern of matrices
> From: John Hunter <jdh...@ac...>
> Date: 2004年11月11日 09:16:03 -0600
> 
> 
>>>>>>"Nils" == Nils Wagner <nw...@me...> writes:
> 
> 
> Nils> Hi all, Structure plots provide a quick visual check on the
> Nils> sparsity pattern of the matrix. A structure plot is a
> Nils> rectangular array of dots; a dot is black if the
> Nils> corresponding matrix element is nonzero otherwise it is
> Nils> white.
> 
> Nils> Is it possible to generate such plots with scipy or should
> Nils> we switch over to matplotlib ?
> 
> Here's another implementation that uses images - likely to be much
> faster for very large matrices.
Hi,
As part of a programming environment for optimization in Python (soon to 
be released hopefully), I use Matplotlib for the graphics. I created 
several functions imitating Matlab's spy() using scatter(). My sparse 
matrices are represented in linked-list, compressed column or compressed 
row storage using the PySparse implementation
	http://people.web.psi.ch/geus/pyfemax/pysparse.html
Using scatter, I can plot the sparsity pattern of matrices with several 
thousands of lines and columns in a blink on my 1.7GHz P4 laptop. Using 
color maps, you can even color your dots according to the magnitude of 
the element they represent (a 2-dimensional "city plot" of a matrix).
Dominique

>>>>> "Dimitri" == Dimitri D'Or <dim...@fs...> writes:
 Dimitri> Hello, I would like to know if there is a mean for
 Dimitri> testing on the hold status of a figure, i.e. to know if
 Dimitri> hold is 'on' or 'off' ?
 Dimitri> In fact, I use frequently the ISHOLD function in Matlab
 Dimitri> and I can't find a similar one in Matplotlib.
A sin of omission. I just added it to CVS. If you don't have CVS
access, in the meantime, you can either use the ax._ishold variable to
inspect the axes hold status, or add the following
to matplotlib.axes.Axes:
 def ishold(self):
 'return the HOLD status of the axes'
 return self._hold
and to matplotlib.matlab
 def ishold(b=None):
 """
 Return the hold status of the current axes
 """
 return gca().ishold() 
Should cure what ails ya ...
JDH

>>>>> "Shin" == Shin <sd...@em...> writes:
 Shin> Currently, figure() is the same as figure(1). But, I think
 Shin> a better behavior of figure is: figure() is the same as
 Shin> figure(n+1) where n is the maximum handle number of opened
 Shin> figures. So, figure() always creates a new figure. This is
 Shin> exactly MATLAB is doing. Any comment?
Looks like a bug - thanks.
Is anybody relying on the fact the figure() currently returns the
current figure if it exists? This is basically the role of gcf,
anyway, which creates a figure none exists and returns it, otherwise
it returns the current figure.
So figure should auto-increment, as you suggest.
JDH

>>>>> "Shin" == Shin <sd...@em...> writes:
 Shin> Thanks. Let me ask another question. How can I get the
 Shin> current mode? I like to recover mode after drawing
 Shin> everything in non-interactive mode. From help document,
 Shin> interactive() seems not to give current mode.
>>> from matplotlib import interactive, is_interactive
>>> print is_interactive()
False
Sorry that these features aren't documented :-(
By the way, ipython already has all of this built-in. In the pylab
mode you start in interactive mode. But you can "run" a code snippent
using the run command, which turns off interactive mode for the
duration of the run, restoring the original interactive state when the
run finishes.
JDH

Hello,
I would like to know if there is a mean for testing on the hold status of a 
figure, i.e. to know if hold is 'on' or 'off' ?
In fact, I use frequently the ISHOLD function in Matlab and I can't find a 
similar one in Matplotlib.
Thank you,
Dimitri

Currently, figure() is the same as figure(1).
But, I think a better behavior of figure is:
figure() is the same as figure(n+1) where n is the maximum handle number 
of opened figures. So, figure() always creates a new figure.
This is exactly MATLAB is doing.
Any comment?
Daehyok Shin
UNC-CH

Thanks. Let me ask another question.
How can I get the current mode?
I like to recover mode after drawing everything in non-interactive mode.
 From help document, interactive() seems not to give current mode.
Daehyok Shin
John Hunter wrote:
> 
> from matplotlib import interactive
> from matplotlib.matlab import *
> 
> plot([1,2,3])
> interactive(False) # turn off interactive mode
> xlabel('hi mom')
> ylabel('bye')
> title('all done')
> interactive(False) # turn it back on
> draw() # draw the canvas
> 
> JDH
> 
> 
> 
> 
> 
> 
> 
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