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Le 21/02/2013 17:33, Sudheer Joseph a écrit :
> Thank you Pierre,
> I will test the other options. I did not
> know the number limitation in case of plt.xcorr.
> Thanks a lot
> with best regards,
Just for reference :
http://stackoverflow.com/questions/6991471/computing-cross-correlation-function
You'll see that (cross)correlation in Python a long ongoing topic.
best,
Pierre

Thank you Pierre,
               I will test the other options. I did not know the number limitation in case of plt.xcorr.
Thanks a lot
with best regards,
Sudheer
***************************************************************
Sudheer Joseph 
Indian National Centre for Ocean Information Services
Ministry of Earth Sciences, Govt. of India
POST BOX NO: 21, IDA Jeedeemetla P.O.
Via Pragathi Nagar,Kukatpally, Hyderabad; Pin:5000 55
Tel:+91-40-23886047(O),Fax:+91-40-23895011(O),
Tel:+91-40-23044600(R),Tel:+91-40-9440832534(Mobile)
E-mail:sjo...@gm...;sud...@ya...
Web- http://oppamthadathil.tripod.com
***************************************************************
________________________________
 From: Pierre Haessig <pie...@cr...>
To: mat...@li... 
Sent: Thursday, 21 February 2013 9:52 PM
Subject: Re: [Matplotlib-users] cross correlation
 
Hi Sudheer,
Le 21/02/2013 02:22, Sudheer Joseph a écrit : 
Thank you very much Smith and Paul,
>                     I was away from office due to a medical situation. So could not respond and thank you regarding the help. I have got the results now and the tips from both of you were extremely useful. I am facing an issue with the code when I call plt.xcorr, in a loop. it builds up usage of memory by python and reaches to the RAM what ever available ( in my 4 GB laptop it reaches almost full and in my 24 GB desktop it reaches the available. I suspected the plot not being closed during each iteration so have given a plt.close('all') in the loop. after which it is taking a good time to run the code which was otherwise faster until ram usage reaches its maximum.
>Is there a way to get out of this situation?. I am attaching the code here and also the link to the data I am using. If possible kindly help.
>
Thanks for sharing the code. By a quick look at gen_xcorr_wnd.py,
 you are generating a quite high number (about len(lons)*len(lats))
 of xcorr series over 365 lags. Here are two thoughts about why I
 would not recommend using xcorr from matplotlib for this job :
1) There is an overhead in creating a plot object which is
 unnecessary since you're only interested in correlation values
2) internally, plt.xcorr uses numpy.correlate
 (https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/axes.py#L4319 and https://github.com/numpy/numpy/blob/master/numpy/core/numeric.py#L731) which is quite fast but unfortunately cannot be well tuned in terms of the output length (only three modes : 'valid', 'same' or 'full'. Matplotlib uses 'full' )
All this to say that when you're interested in 365 correlation
 values, the internal computations takes place on (N+M-1) points
 (where N, M are the length of the input vectors, i.e. 2189 if I'm
 right) and so about 90 % of the output is thrown away.
This being said, there is a tiny issue : I don't know a good module
 which has the (x)correlation function. statsmodel has acf (aka
 correlation) but I don't remember if there is crosscorrelation. For
 acf has two computation modes : one based on fft, one based on
 numpy.correlate which suffer from the same problem as matplotlib's
 xcorr ( https://github.com/statsmodels/statsmodels/blob/master/statsmodels/tsa/stattools.py#L347)
best,
Pierre
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Hi Sudheer,
Le 21/02/2013 02:22, Sudheer Joseph a écrit :
> Thank you very much Smith and Paul,
> I was away from office due
> to a medical situation. So could not respond and thank you regarding
> the help. I have got the results now and the tips from both of you
> were extremely useful. I am facing an issue with the code when I call
> plt.xcorr, in a loop. it builds up usage of memory by python and
> reaches to the RAM what ever available ( in my 4 GB laptop it reaches
> almost full and in my 24 GB desktop it reaches the available. I
> suspected the plot not being closed during each iteration so have
> given a plt.close('all') in the loop. after which it is taking a good
> time to run the code which was otherwise faster until ram usage
> reaches its maximum.
> Is there a way to get out of this situation?. I am attaching the code
> here and also the link to the data I am using. If possible kindly help.
>
Thanks for sharing the code. By a quick look at gen_xcorr_wnd.py, you
are generating a quite high number (about len(lons)*len(lats)) of xcorr
series over 365 lags. Here are two thoughts about why I would not
recommend using xcorr from matplotlib for this job :
1) There is an overhead in creating a plot object which is unnecessary
since you're only interested in correlation values
2) internally, plt.xcorr uses numpy.correlate
(https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/axes.py#L4319
and
https://github.com/numpy/numpy/blob/master/numpy/core/numeric.py#L731)
which is quite fast but unfortunately cannot be well tuned in terms of
the output length (only three modes : 'valid', 'same' or 'full'.
Matplotlib uses 'full' )
All this to say that when you're interested in 365 correlation values,
the internal computations takes place on (N+M-1) points (where N, M are
the length of the input vectors, i.e. 2189 if I'm right) and so about 90
% of the output is thrown away.
This being said, there is a tiny issue : I don't know a good module
which has the (x)correlation function. statsmodel has acf (aka
correlation) but I don't remember if there is crosscorrelation. For acf
has two computation modes : one based on fft, one based on
numpy.correlate which suffer from the same problem as matplotlib's xcorr
(
https://github.com/statsmodels/statsmodels/blob/master/statsmodels/tsa/stattools.py#L347)
best,
Pierre

Objective:
produce multi-page pdfs using xelatex so I can have advanced latex and stix 
fonts (using xits package)
I've used pdf multipage with the recipe:
import matplotlib as mpl
mpl.use ('pdf')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
pdf = PdfPages('test_uw3.pdf')
for page in ...
 fig = plt.figure() 
 pdf.savefig (fig)
 plt.close()
pdf.close()
Now I'm interested in using xelatex (to use stix fonts). So I saw the 
I should use pgf
If I add:
from matplotlib.backends.backend_pgf import FigureCanvasPgf
matplotlib.backend_bases.register_backend('pdf', FigureCanvasPgf)
as suggested by
http://matplotlib.org/users/pgf.html
I get an error:
Traceback (most recent call last):
 File "./read_hist3.py", line 121, in <module>
 pdf.savefig (fig)
 File "/usr/lib64/python2.7/site-packages/matplotlib/backends/backend_pdf.py", 
line 2258, in savefig
 figure.savefig(self, format='pdf', **kwargs)
 File "/usr/lib64/python2.7/site-packages/matplotlib/figure.py", line 1363, in 
savefig
 self.canvas.print_figure(*args, **kwargs)
 File "/usr/lib64/python2.7/site-packages/matplotlib/backend_bases.py", line 
2093, in print_figure
 **kwargs)
 File "/usr/lib64/python2.7/site-packages/matplotlib/backend_bases.py", line 
1943, in _print_method
 return print_method(*args, **kwargs)
 File "/usr/lib64/python2.7/site-packages/matplotlib/backends/backend_pgf.py", 
line 830, in print_pdf
 raise ValueError("filename must be a path or a file-like object")
ValueError: filename must be a path or a file-like object
Any ideas?

Dear Jody,
This is the original code that I am using:
http://old.nabble.com/Taylor-diagram-(2nd-take)-p33364690.html
It is a code that plots Taylor diagrams. 
I would like to get ticks every two points in the standard deviation axis of
the Taylor diagrams to avoid overlapping of labels (as I am making a figure
with several small Taylor Diagrams subplots).
Thanks!
Patricia
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Hi,
could you use a loop to solve it?
arr1list = [np.arange(10) + i for i in range(10)]
arr2list = [np.arange(10) -i for i in range(10)]
for arr1,arr2 in zip(arr1list,arr2list):
 plot(arr1,arr2)
you can use a more object oriented way:
fig = plt.figure()
ax = fig.add_subplot()
for arr1,arr2 in zip(arr1list,arr2list):
 ax.plot(arr1,arr2)
code not tested.
cheers,
Chao
On Thu, Feb 21, 2013 at 4:17 AM, lkz2366 [via matplotlib] <
ml-...@n5...> wrote:
> I am confused on how to plot a variable number of XY plots on a single
> chart. I want to superimpose XY plots on a single chart but the number of
> plots is unknown until runtime.
> For example, if I want to plot 4 plots the code would be:
> figure()
> plot(x1,y1,x2,y2,x3,y3,x4,y4)
> show()
>
> But the number of plots is variable and could be anywhere from 5-30. Any
> ideas on how I can do this?
> I already have the rest of my program working. The program reads all of
> the data from all of the files in a target directory and writes the data to
> X and Y lists.
> Thanks for any help.
>
> ------------------------------
> If you reply to this email, your message will be added to the discussion
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Perhaps you could include some code that illustrates what you are trying to do? I'm confused if you are trying to do something simple and are just going about it the wrong way, or if you are doing something hard. 
If I do 
ax=axes()
ax.plot(arange(1.,10.))
xticks(range(0,10,2))
yticks(range(0,10,2))
I get ticks every 2 points.
Thanks, Jody
On Feb 20, 2013, at 11:34 AM, patricia <ptr...@ho...> wrote:
> Dear Jody,
> No, I tried it also...
> ax.axis["left"].xticks() results in error: 'AxisArtist' object has no
> attribute 'xticks'
> ax.xticks() results in error: 'Floating AxesHostAxesSubplot' object has no
> attribute 'xticks'
> plt.xticks() or just xticks() does not produce any change. 
> Any idea?
> 
> http://www.ce.mu.edu.tr/sharedoc/python-matplotlib-doc-.0.1/html/mpl_toolkits/axes_grid/users/axisartist.html#gridhelper 
> gives some explanation with the The GridHelperRectlinear, but I cannot make
> it work
> 
> Thanks,
> Patricia
> 
> 
> 
> --
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> 
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--
Jody Klymak 
http://web.uvic.ca/~jklymak/

I'm using the recently added PGF/Tikz support to save figures as .pgf
commands to include in a Latex document (I love this new feature!).
The final rendered figures look great after running through pdflatex, but
occasionally it's impractical to use pure vector drawing instructions.
For example, I'm currently working on a figure with 6 subplots, each
containing a scatter type plot with ~400k markers. The resulting .pgf file
is ~350MB.
Is it possible to rasterize the individual axes plots (to .png say) and
then generate a 'hybrid' .pgf output where things like axes ticks, labels,
etc are still vectorized, but the excessively dense scatter plot are
treated as imshow plots are and imported a raster images?
I've tried setting 'rasterized' = True on both the axes and the plot
command, but no dice.
Sample code:
p = np.random.randn(400000,4) # of course I have actual data, but this
should produce the same problem when saving
count = 0
for i in xrange(4):
 for j in xrange(i+1,4):
 count += 1
 ax = fig.add_subplot(2,3, count, rasterized=True)
 ax.plot(p[:,i], p[:,j], 'k.', markersize=0.25, rasterized=True)
Any advice or insight would be greatly appreciated.
Thanks

Thank you very much Smith and Paul,
                     I was away from office due to a medical situation. So could not respond and thank you regarding the help. I have got the results now and the tips from both of you were extremely useful. I am facing an issue with the code when I call plt.xcorr, in a loop. it builds up usage of memory by python and reaches to the RAM what ever available ( in my 4 GB laptop it reaches almost full and in my 24 GB desktop it reaches the available. I suspected the plot not being closed during each iteration so have given a plt.close('all') in the loop. after which it is taking a good time to run the code which was otherwise faster until ram usage reaches its maximum.
Is there a way to get out of this situation?. I am attaching the code here and also the link to the data I am using. If possible kindly help.
ftp ftpser.incois.gov.in
user temp
password incoistemp
cd /home0/temp/comp
bin
mget qu_test.nc.gz gunzip qu_test.nc.gz
 
***************************************************************
Sudheer Joseph 
Indian National Centre for Ocean Information Services
Ministry of Earth Sciences, Govt. of India
POST BOX NO: 21, IDA Jeedeemetla P.O.
Via Pragathi Nagar,Kukatpally, Hyderabad; Pin:5000 55
Tel:+91-40-23886047(O),Fax:+91-40-23895011(O),
Tel:+91-40-23044600(R),Tel:+91-40-9440832534(Mobile)
E-mail:sjo...@gm...;sud...@ya...
Web- http://oppamthadathil.tripod.com
***************************************************************
________________________________
 From: Sterling Smith <sm...@fu...>
To: Sudheer Joseph <sud...@ya...> 
Cc: Paul Hobson <pmh...@gm...>; "mat...@li..." <mat...@li...> 
Sent: Friday, 8 February 2013 10:23 PM
Subject: Re: [Matplotlib-users] cross correlation
 
Sudheer,
For the documentation you are looking for
print ax1.xcorr.__doc__
(Paul tried to give you the IPython method of getting that documentation which is by typing a ? (or ??) after the desired object.)
In the documentation (at the link you gave http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.xcorr), it says that there are three objects returned by xcorr:
Return value is a tuple (*lags*, *c*, *line*) where:
 - *lags* are a length ``2*maxlags+1`` lag vector
 - *c* is the ``2*maxlags+1`` auto correlation vector
 - *line* is a :class:`~matplotlib.lines.Line2D` instance
  returned by :func:`~matplotlib.pyplot.plot`.
So the error you were getting is due to the fact that you have only specified two variables to hold the three returned objects.
Try:
lags,c,line = ax1.xcorr .....
(Note that you have xcorr and lags backwards in your attempt.)
-Sterling
On Feb 8, 2013, at 1:56AM, Sudheer Joseph wrote:
> Thank you verymuch Hobson,
>                   However I think I did not understand the suggestion by you fully( pardon my ignorance). I use the below test code from matplotlib site. How does one make a call to get lags and correlation corresponding to the x and y values in the plot. a Print command of 
> In [23]: print ax1.xcorr
> <bound method AxesSubplot.xcorr of <matplotlib.axes.AxesSubplot object at 0x44c1410>>
> results as above. Is it possible to assign the xcorr,lags=ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True, lw=2) ? with a different syntax? I get below error when I try the above .
> In [27]: xcorr,lags=ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True, lw=2)
> ---------------------------------------------------------------------------
> ValueError                Traceback (most recent call last)
> /home/sjo/work/PY_WORK/stats/<ipython-input-27-e1e58c045ad4> in <module>()
> ----> 1 xcorr,lags=ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True, lw=2)
> 
> ValueError: too many values to unpack
> 
> 
> 
> import matplotlib.pyplot as plt
> import numpy as np
> x,y = np.random.randn(2,100)
> fig = plt.figure()
> ax1 = fig.add_subplot(211)
> ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True, lw=2)
> ax1.grid(True)
> ax1.axhline(0, color='black', lw=2)
> ax2 = fig.add_subplot(212, sharex=ax1)
> ax2.acorr(x, usevlines=True, normed=True, maxlags=50, lw=2)
> ax2.grid(True)
> ax2.axhline(0, color='black', lw=2)
> plt.show()
> 
> 
> From: Paul Hobson <pmh...@gm...>
> To: Sudheer Joseph <sud...@ya...> 
> Cc: "mat...@li..." <mat...@li...> 
> Sent: Thursday, 7 February 2013 10:31 PM
> Subject: Re: [Matplotlib-users] cross correlation
> 
> 
> 
> 
> On Thu, Feb 7, 2013 at 3:24 AM, Sudheer Joseph <sud...@ya...> wrote:
> Dear Users,
>       I am relatively new to Matplotlib. I wanted to find cross correlation between 2 time series for my research and was looking at options available with python and found http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.xcorr . However I wanted to save the results in a netcdf file for further use. ie the correlation, lags and significance if possible. Is there a way to get the corr and lags from the axis.xcorr ?? any help in this matter will be greatly appreciated. 
> Sudheer
> 
> Sudheer,
> 
> A call to axes.xcorr returns the lags, correlation (from np.correlate) and the line artists on the figure.
> 
> In IPython, doing "plt.xcorr??" should provide sufficient information. It's a pretty simple method.
> -paul
> 
> 
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