Thread: [Matplotlib-users] Matplotlib PSD bug?

[I'm not sure if this is best in 'devel' or 'users']

I'm trying to compute PSDs using matplotlib.mlab.psd and came across the "PSD amplitudes" thread from last year:

   http://sourceforge.net/mailarchive/message.php?msg_id=472101A6.9080206%40isla.hawaii.edu

Using the latest version of psd on svn trunk (rev 6429) that added support for pad_to, I can now compute the Matlab pwelch
example using matplotlib. This example is given in the Signal Processing Toolbox User's Guide:

    http://www.mathworks.com/access/helpdesk/help/pdf_doc/signal/signal_tb.pdf

(look on pages 2-23 and 2-24). Note I do not have easy access to Matlab itself, so I'm just using this published example.

The Matlab code is as follows:

    randn('state',1)
    fs = 1000;             % Sampling frequency
    t = (0:0.3*fs)./fs;    % 301 samples
    A = [2 8];             % Sinusoid amplitudes (row vector)
    f = [150;140];         % Sinusoid frequencies (column vector)
    xn = A*sin(2*pi*f*t) + 5*randn(size(t));
    Hs = spectrum.welch('rectangular',150,50);
    psd(Hs,xn,'Fs',fs,'NFFT',512);

This produces a fairly noisy signal from -20 to -10 dB, with a strong peak of ~6 dB at 150 Hz (see the plot on page 2-24).

While my equivalent (?) python code is:

    from scipy import *
    from mlabsvn import psd     # This is a local copy of svn revision 6429 of matplotlib.mlab
    from pylab import *
    fs=1000
    t=linspace(0,0.3,0.3*fs+1)
    A=[2,8]
    f=[150,140]
    xn=A[0]*sin(2*pi*f[0]*t) + A[1]*sin(2*pi*f[1]*t) + 5*randn(len(t))
    Pxx,freqs = psd(xn,Fs=fs,NFFT=150,noverlap=75,pad_to=512)

    figure()
    plot(freqs, 10*log10(Pxx) )
    show()

However, this produces a peak of over 30 dB at 150 Hz. Unless there is a mistake in my code above, there seems to be a
significant difference between the matplotlib and matlab implementations.

I noticed that the values 10*log10(Pxx/len(xn)) produces results that match much better. Without looking more closely at the
code for psd and reviewing Bendat and Piersol I cannot be sure that this is the correct fix.

Does anyone else have any insight?  When is the next release planned, and how likely is a fix?


Thanks,
Matt


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I found bug number 1859027 and have appended the below to the bug report.

When is the next release due and how likely is this to get fixed? I might have time myself
to help in a week or so, but would appreciate some help if someone else has time too (who
has looked at the source before...)

Thanks,
Matt

________________________________________
From: Fago, Matt - AES
Sent: Tuesday, November 25, 2008 1:04 PM
To: mat...@li...
Subject: Matplotlib PSD bug?

[I'm not sure if this is best in 'devel' or 'users']

I'm trying to compute PSDs using matplotlib.mlab.psd and came across the "PSD amplitudes" thread from last year:

   http://sourceforge.net/mailarchive/message.php?msg_id=472101A6.9080206%40isla.hawaii.edu

Using the latest version of psd on svn trunk (rev 6429) that added support for pad_to, I can now compute the Matlab pwelch
example using matplotlib. This example is given in the Signal Processing Toolbox User's Guide:

    http://www.mathworks.com/access/helpdesk/help/pdf_doc/signal/signal_tb.pdf

(look on pages 2-23 and 2-24). Note I do not have easy access to Matlab itself, so I'm just using this published example.

The Matlab code is as follows:

    randn('state',1)
    fs = 1000;             % Sampling frequency
    t = (0:0.3*fs)./fs;    % 301 samples
    A = [2 8];             % Sinusoid amplitudes (row vector)
    f = [150;140];         % Sinusoid frequencies (column vector)
    xn = A*sin(2*pi*f*t) + 5*randn(size(t));
    Hs = spectrum.welch('rectangular',150,50);
    psd(Hs,xn,'Fs',fs,'NFFT',512);

This produces a fairly noisy signal from -20 to -10 dB, with a strong peak of ~6 dB at 150 Hz (see the plot on page 2-24).

While my equivalent (?) python code is:

    from scipy import *
    from mlabsvn import psd     # This is a local copy of svn revision 6429 of matplotlib.mlab
    from pylab import *
    fs=1000
    t=linspace(0,0.3,0.3*fs+1)
    A=[2,8]
    f=[150,140]
    xn=A[0]*sin(2*pi*f[0]*t) + A[1]*sin(2*pi*f[1]*t) + 5*randn(len(t))
    Pxx,freqs = psd(xn,Fs=fs,NFFT=150,noverlap=75,pad_to=512)

    figure()
    plot(freqs, 10*log10(Pxx) )
    show()

However, this produces a peak of over 30 dB at 150 Hz. Unless there is a mistake in my code above, there seems to be a
significant difference between the matplotlib and matlab implementations.

I noticed that the values 10*log10(Pxx/len(xn)) produces results that match much better. Without looking more closely at the
code for psd and reviewing Bendat and Piersol I cannot be sure that this is the correct fix.

Does anyone else have any insight?  When is the next release planned, and how likely is a fix?


Thanks,
Matt


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Please note that any views or opinions presented in this e-mail are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this e-mail and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this e-mail.

Fago, Matt - AES wrote:
> I found bug number 1859027 and have appended the below to the bug report.
> 
> When is the next release due and how likely is this to get fixed? I might have time myself
> to help in a week or so, but would appreciate some help if someone else has time too (who
> has looked at the source before...)

I'm sitting down to look at this right now.  Can you tell me if you have 
this problem with 0.98.3 as well?

Thanks,

Ryan

Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma

Ryan May wrote:
> Fago, Matt - AES wrote:
>> I found bug number 1859027 and have appended the below to the bug report.
>>
>> When is the next release due and how likely is this to get fixed? I 
>> might have time myself
>> to help in a week or so, but would appreciate some help if someone 
>> else has time too (who
>> has looked at the source before...)
> 
> I'm sitting down to look at this right now.  Can you tell me if you have 
> this problem with 0.98.3 as well?

Nevermind, I just realized you can't really do the example without the 
new support for pad_to. I'm still looking...

Ryan

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

Fago, Matt - AES wrote:
> I cannot really compute the example without the pad_to support in svn. Nevertheless, using something similar (nfft=128, noffset=64) gives similarly erroneous results.
> 
> Did you add 'pad_to'? If so, thanks!

Good to know. I recently (within the last month) did a bunch of work on 
psd, based in a large part on work done by one of my colleagues, Sean 
Arms.  I was worried some of this had broken existing code, but it 
appears more likely that this was already a problem.

After much playing, and reading the Matlab docs, it looks like the 
difference is that Matlab normalizes by the sampling frequency.  Also, 
if a one-sided psd is returned, it multiplies everything by 2.  If I 
apply these two scaling factors, I get results in line with those 
produced by Matlab.

Now, this scaling was not performed by the old code, so this is not a 
new incompatibility (bug?) with Matlab.  Also, while I have not reviewed 
the reference specified in the docstring (Bendat and Piersol 1986), the 
book I have handy (Stoica and Moses 2005) does not mention scaling by 
the sampling frequency, nor does the included Matlab code perform any 
such scaling.

So what should be done here?  I would be opposed to making such scaling 
the default, as IMHO it tries to do too much and I would have to work 
around it to get the more "raw" numbers.  However, I am not opposed to 
adding (yet another) option to do such scaling.

Other opinions?

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

Ryan May wrote:
> Fago, Matt - AES wrote:
>> I cannot really compute the example without the pad_to support in svn. Nevertheless, using something similar (nfft=128, noffset=64) gives similarly erroneous results.
>>
>> Did you add 'pad_to'? If so, thanks!
> 
> Good to know. I recently (within the last month) did a bunch of work on 
> psd, based in a large part on work done by one of my colleagues, Sean 
> Arms.  I was worried some of this had broken existing code, but it 
> appears more likely that this was already a problem.
> 
> After much playing, and reading the Matlab docs, it looks like the 
> difference is that Matlab normalizes by the sampling frequency.  Also, 
> if a one-sided psd is returned, it multiplies everything by 2.  If I 
> apply these two scaling factors, I get results in line with those 
> produced by Matlab.
> 
> Now, this scaling was not performed by the old code, so this is not a 
> new incompatibility (bug?) with Matlab.  Also, while I have not reviewed 
> the reference specified in the docstring (Bendat and Piersol 1986), the 
> book I have handy (Stoica and Moses 2005) does not mention scaling by 
> the sampling frequency, nor does the included Matlab code perform any 
> such scaling.
> 
> So what should be done here?  I would be opposed to making such scaling 
> the default, as IMHO it tries to do too much and I would have to work 
> around it to get the more "raw" numbers.  However, I am not opposed to 
> adding (yet another) option to do such scaling.

Hi Ryan,

I appreciate the work you're doing on this, and while I don't have any
very strong opinions on the API questions you raise, I would request
that you include in the docstrings information at least at the level of
the above, listing the scaling issue, the sources you've followed and
how and why you've chosen to follow them or deviate, and differences
with the default behavior of other software. I recently helped a
colleague use Matlab's PSD/pwelch functions and had to spend some time
sending in sine waves of various frequencies and amplitudes to figure
out what the results meant. If matplotlib gives different results by
default, I think it should 1) justify why and 2) indicate what option(s)
may be set to get results equivalent to other systems, including Matlab.

Thanks again,
Andrew

On Mon, Dec 1, 2008 at 3:40 PM, Andrew Straw <str...@as...> wrote:

> I appreciate the work you're doing on this, and while I don't have any
> very strong opinions on the API questions you raise, I would request
> that you include in the docstrings information at least at the level of
> the above, listing the scaling issue, the sources you've followed and
> how and why you've chosen to follow them or deviate, and differences
> with the default behavior of other software. I recently helped a
> colleague use Matlab's PSD/pwelch functions and had to spend some time
> sending in sine waves of various frequencies and amplitudes to figure
> out what the results meant. If matplotlib gives different results by
> default, I think it should 1) justify why and 2) indicate what option(s)
> may be set to get results equivalent to other systems, including Matlab.

My preference is to strive for matlab compatability here.  I am pretty
sure it was compatible with matlab in my original tests to several
significant digits, but I no longer have the test code and my memory
is fuzzy because it was over 5 years ago.  But I intended this
function to be matlab compatible, and if it is not I would prefer to
see it compatible even if it means breaking some existing code.  It is
possible that the original code did not scale with sampling frequency
and was compatible, but over time we've made enhancements that broke
compatibility.  Its been a long time since I used and tested against
matlab.

If there is good reason to add support for an alternate scaling, we
can easily support it with kwargs.  But since the signature and
origins of this function were matlab compatibility, I think it is
least confusing if the default output has similar scaling.

JDH

I suppose the issue is: what is correct? Or is it a matter of definition?

I don't have Stoica and Moses, but Bendat and Piersol eqn 11.102:

    One_Sided_PSD = 2/(n_d * N * dt) * Sum(FFT^2)

where there are n_d is the number of averages and N is the number of points in the FFT.
That seems to be scaling by the length? I'm fairly certain that the factor of two (as shown
above) is required for a one-sided PSD, as that comes from 'removing' the negative
frequency range.

Note that Matlab shows such scaling (by 2/L) even when computing the power spectra directly
from a raw (unaveraged) FFT:

   http://www.mathworks.com/support/tech-notes/1700/1702.html

To me, as Matplotlib is striving to be Matlab-compatible, the default behaviour should be to
give results as close to the Matlab implementation as possible. One could always have an
option to turn off the scaling.

Note that the Matplotlib results also seem to have significantly less frequency resolution than
the Matlab results. Is this the case, or am I not using noffset, nfft, and pad_to correctly?

Thanks for your help,
Matt


________________________________________
From: Ryan May [rm...@gm...]
Sent: Monday, December 01, 2008 1:58 PM
To: Fago, Matt - AES
Cc: Matplotlib Users
Subject: Re: [Matplotlib-users] Matplotlib PSD bug?

Fago, Matt - AES wrote:
> I cannot really compute the example without the pad_to support in svn. Nevertheless, using something similar (nfft=128, noffset=64) gives similarly erroneous results.
>
> Did you add 'pad_to'? If so, thanks!

Good to know. I recently (within the last month) did a bunch of work on
psd, based in a large part on work done by one of my colleagues, Sean
Arms.  I was worried some of this had broken existing code, but it
appears more likely that this was already a problem.

After much playing, and reading the Matlab docs, it looks like the
difference is that Matlab normalizes by the sampling frequency.  Also,
if a one-sided psd is returned, it multiplies everything by 2.  If I
apply these two scaling factors, I get results in line with those
produced by Matlab.

Now, this scaling was not performed by the old code, so this is not a
new incompatibility (bug?) with Matlab.  Also, while I have not reviewed
the reference specified in the docstring (Bendat and Piersol 1986), the
book I have handy (Stoica and Moses 2005) does not mention scaling by
the sampling frequency, nor does the included Matlab code perform any
such scaling.

So what should be done here?  I would be opposed to making such scaling
the default, as IMHO it tries to do too much and I would have to work
around it to get the more "raw" numbers.  However, I am not opposed to
adding (yet another) option to do such scaling.

Other opinions?

Ryan

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

This e-mail and any files transmitted with it may be proprietary and are intended solely for the use of the individual or entity to whom they are addressed. If you have received this e-mail in error please notify the sender.
Please note that any views or opinions presented in this e-mail are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this e-mail and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this e-mail.

Fago, Matt - AES wrote:
> I suppose the issue is: what is correct? Or is it a matter of definition?
> 
> I don't have Stoica and Moses, but Bendat and Piersol eqn 11.102:
> 
>     One_Sided_PSD = 2/(n_d * N * dt) * Sum(FFT^2)
> 
> where there are n_d is the number of averages and N is the number of points in the FFT.
> That seems to be scaling by the length? I'm fairly certain that the factor of two (as shown
> above) is required for a one-sided PSD, as that comes from 'removing' the negative
> frequency range.
> 
> Note that Matlab shows such scaling (by 2/L) even when computing the power spectra directly
> from a raw (unaveraged) FFT:
> 
>    http://www.mathworks.com/support/tech-notes/1700/1702.html
>
> To me, as Matplotlib is striving to be Matlab-compatible, the default behaviour should be to
> give results as close to the Matlab implementation as possible. One could always have an
> option to turn off the scaling.

Yeah, scaling by a factor of two for one-sided is definitely correct now 
that I think about it.  Note, however, that the scaling by the length is 
not the problem. In fact, the current psd implementation does this 
correctly when it corrects for the power in the window.  The problem 
stems from matlab scaling by the sampling frequency.  Stoica and Moses 
don't do this, nor does Welch 1967.  I'm all for doing things in a 
Matlab-compatible way--when they're correct.  One of the reasons I 
stopped using Matlab was that it tried to be too smart for me.

> Note that the Matplotlib results also seem to have significantly less frequency resolution than
> the Matlab results. Is this the case, or am I not using noffset, nfft, and pad_to correctly?

It's not that you're using those incorrectly, but rather that you failed 
to notice that the default window is the Hanning window, not 
rectangular.  Try adding window=mlab.window_none to the call. (Sorry, I 
meant to mention that before in my reply.

Ryan

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

> From: Ryan May [mailto:rm...@gm...]
> Fago, Matt - AES wrote:
> > I suppose the issue is: what is correct? Or is it a matter of
> definition?
[...]
> Yeah, scaling by a factor of two for one-sided is definitely correct now
> that I think about it.  Note, however, that the scaling by the length is
> not the problem. In fact, the current psd implementation does this
> correctly when it corrects for the power in the window.  The problem
> stems from matlab scaling by the sampling frequency.  Stoica and Moses
> don't do this, nor does Welch 1967.  I'm all for doing things in a
> Matlab-compatible way--when they're correct.  One of the reasons I
> stopped using Matlab was that it tried to be too smart for me.

Yes, multiplying by 2/fs does look fairly good. Perhaps this comes about due to the Matlab implementation of the FFT?

> > Note that the Matplotlib results also seem to have significantly less
> > frequency resolution than
> > the Matlab results. Is this the case, or am I not using noffset, nfft,
> > and pad_to correctly?
>
> It's not that you're using those incorrectly, but rather that you failed
> to notice that the default window is the Hanning window, not
> rectangular.  Try adding window=mlab.window_none to the call. (Sorry, I
> meant to mention that before in my reply.

Ah ... many thanks. Silly me.


 - Matt

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So what is to be done here? It seems to me that at least the factor of two should be
fixed for one-sided PSDs, and the 1/fs normalization difference with Matlab
documented. Ideally, I'd think this normalization would be on by default, with the
option to turn it off.

Are you planning to submit a patch, or shall I look into it? If I submit a patch, does matplotlib
require a copyright assignment?

Thanks,
Matt

________________________________________
From: Ryan May [rm...@gm...]
Sent: Monday, December 01, 2008 3:31 PM
To: Fago, Matt - AES
Cc: Matplotlib Users
Subject: Re: [Matplotlib-users] Matplotlib PSD bug?

Fago, Matt - AES wrote:
> I suppose the issue is: what is correct? Or is it a matter of definition?
>
> I don't have Stoica and Moses, but Bendat and Piersol eqn 11.102:
>
>     One_Sided_PSD = 2/(n_d * N * dt) * Sum(FFT^2)
>
> where there are n_d is the number of averages and N is the number of points in the FFT.
> That seems to be scaling by the length? I'm fairly certain that the factor of two (as shown
> above) is required for a one-sided PSD, as that comes from 'removing' the negative
> frequency range.
>
> Note that Matlab shows such scaling (by 2/L) even when computing the power spectra directly
> from a raw (unaveraged) FFT:
>
>    http://www.mathworks.com/support/tech-notes/1700/1702.html
>
> To me, as Matplotlib is striving to be Matlab-compatible, the default behaviour should be to
> give results as close to the Matlab implementation as possible. One could always have an
> option to turn off the scaling.

Yeah, scaling by a factor of two for one-sided is definitely correct now
that I think about it.  Note, however, that the scaling by the length is
not the problem. In fact, the current psd implementation does this
correctly when it corrects for the power in the window.  The problem
stems from matlab scaling by the sampling frequency.  Stoica and Moses
don't do this, nor does Welch 1967.  I'm all for doing things in a
Matlab-compatible way--when they're correct.  One of the reasons I
stopped using Matlab was that it tried to be too smart for me.

> Note that the Matplotlib results also seem to have significantly less frequency resolution than
> the Matlab results. Is this the case, or am I not using noffset, nfft, and pad_to correctly?

It's not that you're using those incorrectly, but rather that you failed
to notice that the default window is the Hanning window, not
rectangular.  Try adding window=mlab.window_none to the call. (Sorry, I
meant to mention that before in my reply.

Ryan

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

This e-mail and any files transmitted with it may be proprietary and are intended solely for the use of the individual or entity to whom they are addressed. If you have received this e-mail in error please notify the sender.
Please note that any views or opinions presented in this e-mail are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this e-mail and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this e-mail.

On Mon, Dec 8, 2008 at 9:10 AM, Fago, Matt - AES <Mat...@it...> wrote:
>
> So what is to be done here? It seems to me that at least the factor of two should be
> fixed for one-sided PSDs, and the 1/fs normalization difference with Matlab
> documented. Ideally, I'd think this normalization would be on by default, with the
> option to turn it off.
>
> Are you planning to submit a patch, or shall I look into it? If I submit a patch, does matplotlib
> require a copyright assignment?

If you submit a patch, we assume you are agreeing to the mpl licensing
terms, so you do not need to explicitly do anything. As for the
decision about how the defaults and kwargs should behave, I'll defer
to you and Ryan.

JDH

John Hunter wrote:
> On Mon, Dec 8, 2008 at 9:10 AM, Fago, Matt - AES <Mat...@it...> wrote:
>> So what is to be done here? It seems to me that at least the factor of two should be
>> fixed for one-sided PSDs, and the 1/fs normalization difference with Matlab
>> documented. Ideally, I'd think this normalization would be on by default, with the
>> option to turn it off.
>>
>> Are you planning to submit a patch, or shall I look into it? If I submit a patch, does matplotlib
>> require a copyright assignment?
> 
> If you submit a patch, we assume you are agreeing to the mpl licensing
> terms, so you do not need to explicitly do anything. As for the
> decision about how the defaults and kwargs should behave, I'll defer
> to you and Ryan.

I'm fine with coding up a patch to handle the scaling.  Since it seems Matlab 
compatibility is the key desire here, making the Matlab scaling the default is 
fine by me.  I, myself, am more than capable of turning on a keyword argument. I 
see two independent changes here:

1) Scaling by factor of two for one-sided psd -- Doesn't need a keyword argument, 
just makes sense.

2) Scaling by 1/Fs. I'm still not sure why Matlab is doing this, other than 
perhaps to make the PSD dB/Hz instead of dB/(rad/s). Needs a new keyword 
argument.  Suggestions on what exactly this should be called? scale_by_freq?

My only other concern is whether this belongs in 0.98.x.  This is a behavior 
change from 0.98.3, not necessarily a bug fix.  I'll defer to John, et al. on 
whether this should go in 0.98.x or go in a later release.

Ryan

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

On Mon, Dec 8, 2008 at 10:56 AM, Ryan May <rm...@gm...> wrote:

> My only other concern is whether this belongs in 0.98.x.  This is a behavior
> change from 0.98.3, not necessarily a bug fix.  I'll defer to John, et al.
> on whether this should go in 0.98.x or go in a later release.

It's a judgement call, but we have always had new features and minor
API changes in the point releases.  Except on the 0.91 maintenance
branch, which is only bugfix, we have continuously added   new stuff
on every release.  When the breakage is likely to be difficult, or the
new feature really significant, we will push the major version.  I
don't think these changes are so significant that they require waiting
until a new major version number, but you may want to consider issuing
a warning in addition to the requisite explanation in the docstring
and CHANGELOG.

JDH

John Hunter wrote:
> On Mon, Dec 8, 2008 at 10:56 AM, Ryan May <rm...@gm...> wrote:
> 
>> My only other concern is whether this belongs in 0.98.x.  This is a behavior
>> change from 0.98.3, not necessarily a bug fix.  I'll defer to John, et al.
>> on whether this should go in 0.98.x or go in a later release.
> 
> It's a judgement call, but we have always had new features and minor
> API changes in the point releases.  Except on the 0.91 maintenance
> branch, which is only bugfix, we have continuously added   new stuff
> on every release.  When the breakage is likely to be difficult, or the
> new feature really significant, we will push the major version.  I
> don't think these changes are so significant that they require waiting
> until a new major version number, but you may want to consider issuing
> a warning in addition to the requisite explanation in the docstring
> and CHANGELOG.

How about making the default None, and if the default is used set to True and 
issue the warning for this release.  In the future the warning is remove and the 
default goes to True.

As long as we're going for Matlab compatibility, what about changing Fs from 
defaulting to 2 to 2*pi?  That seems to be the default.

Ryan

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

John Hunter wrote:
> On Mon, Dec 8, 2008 at 10:56 AM, Ryan May <rm...@gm...> wrote:
> 
>> My only other concern is whether this belongs in 0.98.x.  This is a behavior
>> change from 0.98.3, not necessarily a bug fix.  I'll defer to John, et al.
>> on whether this should go in 0.98.x or go in a later release.
> 
> It's a judgement call, but we have always had new features and minor
> API changes in the point releases.  Except on the 0.91 maintenance
> branch, which is only bugfix, we have continuously added   new stuff
> on every release.  When the breakage is likely to be difficult, or the
> new feature really significant, we will push the major version.  I
> don't think these changes are so significant that they require waiting
> until a new major version number, but you may want to consider issuing
> a warning in addition to the requisite explanation in the docstring
> and CHANGELOG.

The scaling changes are in, as well as the warning and the corresponding lines in 
  api_changes and CHANGELOG.  I also added the converted matlab demo I used to 
figure this stuff out.  Now would probably be the time to see if I did something 
wrong (especially the warning).

Ryan

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

On Mon, Dec 8, 2008 at 1:58 PM, Ryan May <rm...@gm...> wrote:
> John Hunter wrote:

> The scaling changes are in, as well as the warning and the corresponding lines in
>  api_changes and CHANGELOG.  I also added the converted matlab demo I used to
> figure this stuff out.  Now would probably be the time to see if I did something
> wrong (especially the warning).

Question from the peanut gallery: are you guys putting in numerical
tests as part of your unit test suite for this stuff?  Rather than in
the future saying 'I think in December 2008 it used to match matlab'
it would be nice to have some automated testing of this.   Useful if
someone ever wants to optimize it, cythonize it, etc...

Just a thought...

f

> From: Ryan May
> The scaling changes are in, as well as the warning and the corresponding
> lines in
>   api_changes and CHANGELOG.  I also added the converted matlab demo I
> used to
> figure this stuff out.  Now would probably be the time to see if I did
> something
> wrong (especially the warning).

The magnitudes do seem better, and the error message works in a reasonable
way (no warning if explicitly set the new arg).

The plot does still look somewhat different from Matlab (e.g., the peak at 150 Hz is much larger in matplotlib), even with window=window_none. Fernando might have a point about unit tests: perhaps we could somehow get a few numerical values out of Matlab to compare to in a test?

Regardless, much better. Thank you!

 - Matt

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Fago, Matt - AES wrote:
> [I'm not sure if this is best in 'devel' or 'users']
> 
> I'm trying to compute PSDs using matplotlib.mlab.psd and came across the "PSD amplitudes" thread from last year:
> 
>    http://sourceforge.net/mailarchive/message.php?msg_id=472101A6.9080206%40isla.hawaii.edu
> 
> Using the latest version of psd on svn trunk (rev 6429) that added support for pad_to, I can now compute the Matlab pwelch
> example using matplotlib. This example is given in the Signal Processing Toolbox User's Guide:
> 
>     http://www.mathworks.com/access/helpdesk/help/pdf_doc/signal/signal_tb.pdf
> 
> (look on pages 2-23 and 2-24). Note I do not have easy access to Matlab itself, so I'm just using this published example.
> 
> The Matlab code is as follows:
> 
>     randn('state',1)
>     fs = 1000;             % Sampling frequency
>     t = (0:0.3*fs)./fs;    % 301 samples
>     A = [2 8];             % Sinusoid amplitudes (row vector)
>     f = [150;140];         % Sinusoid frequencies (column vector)
>     xn = A*sin(2*pi*f*t) + 5*randn(size(t));
>     Hs = spectrum.welch('rectangular',150,50);
>     psd(Hs,xn,'Fs',fs,'NFFT',512);
> 
> This produces a fairly noisy signal from -20 to -10 dB, with a strong peak of ~6 dB at 150 Hz (see the plot on page 2-24).
> 
> While my equivalent (?) python code is:
> 
>     from scipy import *
>     from mlabsvn import psd     # This is a local copy of svn revision 6429 of matplotlib.mlab
>     from pylab import *
>     fs=1000
>     t=linspace(0,0.3,0.3*fs+1)
>     A=[2,8]
>     f=[150,140]
>     xn=A[0]*sin(2*pi*f[0]*t) + A[1]*sin(2*pi*f[1]*t) + 5*randn(len(t))
>     Pxx,freqs = psd(xn,Fs=fs,NFFT=150,noverlap=75,pad_to=512)
> 
>     figure()
>     plot(freqs, 10*log10(Pxx) )
>     show()
> 
> However, this produces a peak of over 30 dB at 150 Hz. Unless there is a mistake in my code above, there seems to be a
> significant difference between the matplotlib and matlab implementations.
> 
> I noticed that the values 10*log10(Pxx/len(xn)) produces results that match much better. Without looking more closely at the
> code for psd and reviewing Bendat and Piersol I cannot be sure that this is the correct fix.
> 
> Does anyone else have any insight?  When is the next release planned, and how likely is a fix?

I don't have any insight yet, but since I'm the guy who just tweaked it, 
I guess I'm on the hook to fix it. :) I'll try to take a look this 
afternoon.

Ryan

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