matplotlib-users Mailing List for matplotlib

Gideon Simpson wrote:
> If I have a line that I want to animate, I can clearly write:
> 
> lineu, = plot(x,u)
> draw()
> 
> for p in range(0, N):
> 	lineu.set_ydata(u)
> draw()
> 
> Is there an analogue to set_ydata for things plots like contour,  
> contourf, etc.?
> 

No, as presently implemented, you simply have to remake the contour 
(that is, the ContourSet object) with the new data.

Eric

If I have a line that I want to animate, I can clearly write:

lineu, = plot(x,u)
draw()

for p in range(0, N):
	lineu.set_ydata(u)
draw()

Is there an analogue to set_ydata for things plots like contour,  
contourf, etc.?

-gideon

On Wed, Feb 11, 2009 at 2:34 PM, Thomas Robitaille <
tho...@gm...> wrote:

> Hi everyone,
>
> I wish to execute a certain function every time the view interval of
> a figure is updated, for example when it is changed interactively
> using the zoom rectangle or home button in WXAgg. Matplotlib must
> already be calling certain routines, such as the tick locator and
> formatters, but is there a way to execute arbitrary functions when
> the view interval is updated?


You're looking for 'xlim_changed' and 'ylim_changed'.

 I know this can be found here:
http://matplotlib.sourceforge.net/api/axes_api.html

Should we add this to
http://matplotlib.sourceforge.net/users/event_handling.html ?

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
Sent from: Norman Oklahoma United States.

Hi everyone,

I wish to execute a certain function every time the view interval of  
a figure is updated, for example when it is changed interactively  
using the zoom rectangle or home button in WXAgg. Matplotlib must  
already be calling certain routines, such as the tick locator and  
formatters, but is there a way to execute arbitrary functions when  
the view interval is updated?

Thanks for any help,

Thomas

On Wed, Feb 11, 2009 at 20:13, Ryan May <rm...@gm...> wrote:
> On Wed, Feb 11, 2009 at 12:56 PM, Sandro Tosi <mo...@de...> wrote:
>>
>> Hello,
>> I got a script (attached, even if without the datafile has less
>> meaning) that parses a log file and plots 3 datasets. With 0.98.5.3 I
>> got this error
>> RuntimeError: maximum recursion depth exceeded
>>
>> I see the same behavior in .2 but not in 0.98.5. I remembered I've
>> copied this from an example in mpl doc, but that's all.
>>
>> Is that a regression or something wrong in the code?
>
> It looks like your script is trying to plot a list of a strings (which
> contains numbers).  I checked in a fix for this on the trunk but I didn't
> bother on the branch since I figured it wasn't really supported behavior.
> Try converting the strings to numbers and you should be fine.

Indeed: adding int(res.group...) works fine, just nice how it worked
on 0.98.5 and not on .2 .3 :)

Thanks a lot,
-- 
Sandro Tosi (aka morph, morpheus, matrixhasu)
My website: http://matrixhasu.altervista.org/
Me at Debian: http://wiki.debian.org/SandroTosi

I just ran across this, which looks really nice. The author shows how to
use MPL and basemap to download satellite images from the recent fires
in Australia and overlay that with recent thermal hotspot data.

http://pyevolve.sourceforge.net/wordpress/?p=86

On Wed, Feb 11, 2009 at 12:56 PM, Sandro Tosi <mo...@de...> wrote:

> Hello,
> I got a script (attached, even if without the datafile has less
> meaning) that parses a log file and plots 3 datasets. With 0.98.5.3 I
> got this error
> RuntimeError: maximum recursion depth exceeded
>
> I see the same behavior in .2 but not in 0.98.5. I remembered I've
> copied this from an example in mpl doc, but that's all.
>
> Is that a regression or something wrong in the code?


It looks like your script is trying to plot a list of a strings (which
contains numbers).  I checked in a fix for this on the trunk but I didn't
bother on the branch since I figured it wasn't really supported behavior.
Try converting the strings to numbers and you should be fine.

Ryan

-- 
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Hi,

Thanks a lot for your comments.  I did try earlier on to remove the bad points but came across some problems when re-ordering my array. I will try out the method sent to me and check the reference.

Regards, Marjolaine.



>>> <kgd...@gm...> 02/11/09 4:06 PM >>>
Marjolaine,

I am assuming your masked array entries are missing data.  Multivariate analysis with missing data can be handled in several standard ways, however these methods don't appear in most Python libraries.

Here are some references on the topic that will help you:

[1] P.R.C. Nelson and J.F. MacGregor, 1996, "Missing data methods in PCA and PLS: Score calculations with incomplete observations", Chemometrics and Intelligent Laboratory Systems, v35, p 45-65.

[2] F. Arteaga and A. Ferrer, 2002, "Dealing with missing data in MSPC: several methods, different interpretations, some examples", Journal of Chemometrics, v16, p408-418.

Paper [1] deals with building a model with missing data, while paper [2] looks at applying an existing PCA model to new data that contains missing entries.

Hope these help,
Kevin

Marjolaine Rouault wrote:
> 
> Hi,
> 
> I am struggling to do a PCA analysis on a masked array. Anybody has
> suggestions on how to deal with masked array when doing PCAs?
> 
> Best regards, Marjolaine.
>

Quoted from: 
http://www.nabble.com/matplotlib.mlab-PCA-analysis-tp21932808p21932808.html



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Hello,
I got a script (attached, even if without the datafile has less
meaning) that parses a log file and plots 3 datasets. With 0.98.5.3 I
got this error

$ ./ddc_graph.py
Traceback (most recent call last):
  File "./ddc_graph.py", line 39, in <module>
    rc_plot = ax.plot_date(DATES, RC, '-')
  File "/usr/lib/python2.5/site-packages/matplotlib/axes.py", line
3356, in plot_date
    ret = self.plot(x, y, fmt, **kwargs)
  File "/usr/lib/python2.5/site-packages/matplotlib/axes.py", line 3288, in plot
    for line in self._get_lines(*args, **kwargs):
  File "/usr/lib/python2.5/site-packages/matplotlib/axes.py", line
401, in _grab_next_args
    for seg in self._plot_3_args(remaining, **kwargs):
  File "/usr/lib/python2.5/site-packages/matplotlib/axes.py", line
340, in _plot_3_args
    x, y, multicol = self._xy_from_xy(x, y)
  File "/usr/lib/python2.5/site-packages/matplotlib/axes.py", line
215, in _xy_from_xy
    by = self.axes.yaxis.update_units(y)
  File "/usr/lib/python2.5/site-packages/matplotlib/axis.py", line
939, in update_units
    converter = munits.registry.get_converter(data)
  File "/usr/lib/python2.5/site-packages/matplotlib/units.py", line
137, in get_converter
    converter = self.get_converter( thisx )
...
  File "/usr/lib/python2.5/site-packages/matplotlib/units.py", line
137, in get_converter
    converter = self.get_converter( thisx )
  File "/usr/lib/python2.5/site-packages/matplotlib/units.py", line
130, in get_converter
    if converter is None and iterable(x):
RuntimeError: maximum recursion depth exceeded

I see the same behavior in .2 but not in 0.98.5. I remembered I've
copied this from an example in mpl doc, but that's all.

Is that a regression or something wrong in the code?

Thanks,
-- 
Sandro Tosi (aka morph, morpheus, matrixhasu)
My website: http://matrixhasu.altervista.org/
Me at Debian: http://wiki.debian.org/SandroTosi

Hi,

I've managed to take the contents of my CSV file and display it with
matplotlib. I'm having some issues with the way my X-axis is being
displayed.

For the X-axis, I pass in a list that filled with datetime objects, an
example of one element on the list:

datetime.datetime(2007, 12, 17, 20, 28, 15),

Issues (please see the attached cpu.png:

- for some reason a TZ has been inserted
- graphs have white space buffers on either side of the X-axix
- points on X-axis are separated by the hour, instead of values in datetime
object

I have tried many variations of plotdate, etc. If someone could please point
me in the right direction.

Thanks

=================
Code http://www.nabble.com/file/p21958283/cpu.png 
=================

#!/usr/bin/env python

import csv
import sys
import matplotlib.pyplot as plt
import datetime

new_list = []
time = []
cpu = []

fileReader = csv.reader(open("sample.csv", "rb"))
for row in fileReader:
    new_list.append(row)

# Converts papatimes time format into dattime
def time_split(current_line):
    # splits papastats datetime format in useable python list
    dt = datetime.datetime.strptime(current_line[0],"%Y/%m/%d %H:%M:%S")
    time.append(dt)

def cpu_calc(current_line):
    cpu.append(current_line[11].rstrip("%"))

#Iterate over list of CSV values
for i in new_list[1:]:
    time_split(i)
    cpu_calc(i)

plt.plot(time, cpu, 'b-')
#plt.plot_date(time, cpu, fmt='b-', xdate=False, ydate=False, tz=None)

plt.xlabel('Time')
plt.ylabel('CPU %')
plt.title('Daily CPU Usage')
plt.grid(True)
plt.grid(alpha=0.2, color='black', linestyle='-', linewidth=0.1)
plt.show()

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Sent from the matplotlib - users mailing list archive at Nabble.com.

command-w does not seem to close the window.
-gideon

Hi,

I have the following code and am wondering whether there is a more
efficient way to plot multiple curves. Maybe somehow accumulating the
data into a single variable, then calling plot once ... Thanks for any
ideas.

for ofile in files:
    d = mlab.csv2rec(ofile, names = ['date','field'])
    ax.plot(d['date'], d['field'])

On Mon, Feb 9, 2009 at 9:59 PM, Jouni K. Seppänen <jk...@ik...> wrote:

> Ryan May <rm...@gm...> writes:
>
> > On Mon, Feb 9, 2009 at 2:37 PM, A B <pyt...@gm...> wrote:
> >
> > If you're using the full OO interface and creating a figure by making an
> > instance of Figure(), then you shouldn't need to close the figure by
> hand.
> > It should be deleted whenever you delete or replace your instance of
> > Figure.  (If I understand correctly.)
>
> Yes, in the OO interface there is no close() because matplotlib does not
> retain any references to the figure object. Garbage collection will take
> care of reclaiming memory once the user code has no more references to
> the object either.
>
> That said, there have been cases of memory leaks caused by circular
> references among objects that have __del__ methods. I think all known
> leaks have been fixed, but if I were deploying a long-lived application
> that creates lots of figures, I would definitely want to watch its
> memory usage in my exact use case.
>
> --
> Jouni K. Seppänen
> http://www.iki.fi/jks
>

Thank you. The reason I asked the question was that with the OO interface, I
still observed growth in memory consumption (more than I saw after I added
pyplot.close() calls). However, at some point (90M which I still think is a
lot) the growth tapered off and eventually seemed to have stopped.
Essentially, what I do is create a figure, then call plot() on it in a loop
to generate multiple curves, then print_png() on the canvas object.