A quick but not necessarily accurate answer: Don't use Python 2.6. Use
Python 2.5. I don't think matplotlib has been 'certified' for 2.6 yet.
I suggest
(1) uninstall Python 2.6 and numpy for 2.6.
(2) Install Python 2.5 and numpy for 2.5
(3) Install matplotlib for 2.5
Constantine
0
Use Python set and then convert to numpy array?
Pablo Romero
18/03/2009 01:50 PM
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[Matplotlib-users] quick numpy question
quick numpy-related question.
I want to use numpy.arange() to create multiple arrays, and then I want to
join these arrays (or individual elemen
You need to use the numpy 'where' functionality
import numpy as np
x, y, z = np.loadtxt("fileName.dat", unpack=True) # or similar
# x, y and z are now numpy arrays and have built in functionality as
follows:
s = (z < 10.0) & (z**2 > 0.5) # or some other constraint. Produces an
array 's' of
Is it just that the label too close to the border?
"Warren Weckesser" <[EMAIL PROTECTED]>
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13/08/2008 01:13 PM
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[Matplotlib-users] MPL 0.91.2: bottom of xlabel chopped off
Hi,
Sorry if this is in a FAQ some
I would recommend using "pylab.load" for reading the data. For example:
x, y = pylab.load("filename", unpack=True) # with other options as
required
sa6113 <[EMAIL PROTECTED]>
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09/02/2008 07:34 PM
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[Matplotlib-
A good reminder to check that site out. There is alsoTreeMap, which uses
coloured rectangles. http://www.scipy.org/TreeMap
Jessica Lu <[EMAIL PROTECTED]>
Sent by: [EMAIL PROTECTED]
20/12/2007 05:30 AM
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Bryan Fodness <[EMAIL PROTECTED]>, matplotlib
Subject
Re: [Matplotlib-users] d
always look the same.
Best regards,
Brett McSweeney
ray sa <[EMAIL PROTECTED]>
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03/12/2007 09:50 AM
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[Matplotlib-users] continuous plotting..
Hello
I am trying to use this application to plot a diagram
I didn't say infinite power, but infinite power density at the sine wave
frequemcy.
Being per Hz doesn't mean that one computes the PSD using a 1 Hz band! It
means that one divides the power in the band by the width of the band,
which can be anything one chooses.
The formula for S(f) of a si
There is certainly differences (usually of a factor of PI) in the various
definitions used for PSDs, but a simple sign wave has an infinite power
density at the sine wave frequency. Are we agreed on that?
Use of windowing will modify this comment somewhat (so it probably won't
really go to inf
If you lower the resolution (ie increase nFFT) in your program you will
see that the PSD does indeed increase. I think it may be on the way to
infinity.
Joseph Park <[EMAIL PROTECTED]>
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26/10/2007 10:05 AM
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Re:
Are you sure that the answer should be zero? Shouldn't the PSD for a
simple sine wave tend to infinity (depending on the resolution)?
Joseph Park <[EMAIL PROTECTED]>
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26/10/2007 06:50 AM
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[Matplotlib-users] PSD
and some more...
normHist, lower_edges = numpy.histogram(Hlist, bins=100, normed=True)
binWidth = lower_edges[-1]/(len(lower_edges)-1)
cumHist = normHist.cumsum()*binWidth
pylab.plot(lower_edges+binWidth, cumHist) # use upper edge of bin
Brett McSweeney/Broadmeadow/Goninan/AU
20/06/2007
some tweaking...
binWidth = lower_edges[-1]/(len(lower_edges)-1)
[EMAIL PROTECTED]
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20/06/2007 09:14 AM
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Tommy Grav <[EMAIL PROTECTED]>
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Re: [Matplotlib-users] Cumulative histogram
I don'
I don't know about easy, but here is a start:
normHist, lower_edges = numpy.histogram(Hlist, bins=100, normed=True)
binWidth = lower_edges[-1]/len(lower_edges)
cumHist = normHist.cumsum()*binWidth
pylab.plot(lower_edges+0.5*binWidth, cumHist)
Needs some tweaking, no doubt.
Tommy Grav <[EMAIL
Just as a general comment - perhaps not useful in your case - we have the
same sort of requirement and find the periodogram facility (specgram) in
pylab very useful for showing the change in PSD over time - highlighting
resonances and how they vary in proportion to other functions of time
(plot
Hello Andrew,
Sorry for the delay, I have been on holidays. I wrote the code (such as
it is - but the key line is adapted from the scipy web site).
I should have put a copy of the BSD license at the front, I suppose,
(would that be correct?) but it was never intended as more than a quick
in-h
Hi Alan,
I'm not speaking for anyone else, but as far as I'm concerned that code is
public domain.
Cheers,
Brett.
Alan G Isaac <[EMAIL PROTECTED]>
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31/05/2007 01:17 PM
Please respond to
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Re: [Matplotlib-users] Han
Hi Steve,
This is also interest to us - although about 2 million data points is our
maximum so far.
Here is a decimating filter module based on the Savtsky-Golay method.
Brett McSweeney
steve george <[EMAIL PROTECTED]>
Sent by: [EMAIL PROTECTED]
31/05/2007 06:07 AM
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Matplotlib
Thanks John, that works perfectly.
Best regards,
Brett McSweeney
On 4/23/07, [EMAIL PROTECTED]
<[EMAIL PROTECTED]> wrote:
>
> I'm producing series of plots (spectograms) in a program loop using
imshow
> and saving each plot to .png. Even though I close() each plot a
I'm producing series of plots (spectograms) in a program loop using imshow
and saving each plot to .png. Even though I close() each plot after each
savefig(...), the memory does not appear to be freed up, and the memory
useage goes up and up as the program runs (and stalls the computer as it
t
Just started using matplotlib (it's great!) interactively (using ipython,
TkAgg backend) and am moving into saving plots to file.
I edited the matplotlibrc to interactive: False and backend: Agg, and it
works great. (produces .png)
I would normally like to muck around interactively to get the p
Not sure what region[:] is supposed to achieve. You are creating a copy
with the same name, so you are over-riding the original variable.
Hi there
I have a function where I want to display an image, get the user to
zoom in on a region of interest, and then return the axes limits.
But the p
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