From: Fago, Matt  AES <Matt.F<ago@it...>  20081125 20:05:17

[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 223 and 224). 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 224). 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 This email 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 email in error please notify the sender. Please note that any views or opinions presented in this email are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this email and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this email. 
From: Fago, Matt  AES <Matt.F<ago@it...>  20081201 16:03:42

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: matplotlibusers@... 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 223 and 224). 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 224). 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 This email 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 email in error please notify the sender. Please note that any views or opinions presented in this email are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this email and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this email. 
From: Ryan May <rmay31@gm...>  20081201 17:58:50

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 
From: Ryan May <rmay31@gm...>  20081201 18:20:09

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 
From: Ryan May <rmay31@gm...>  20081201 20:58:56

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 onesided 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 
From: Andrew Straw <strawman@as...>  20081201 21:40:39

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 onesided 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 
From: John Hunter <jdh2358@gm...>  20081201 21:53:35

On Mon, Dec 1, 2008 at 3:40 PM, Andrew Straw <strawman@...> 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 
From: Fago, Matt  AES <Matt.F<ago@it...>  20081201 22:08:00

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 onesided 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/technotes/1700/1702.html To me, as Matplotlib is striving to be Matlabcompatible, 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 [rmay31@...] Sent: Monday, December 01, 2008 1:58 PM To: Fago, Matt  AES Cc: Matplotlib Users Subject: Re: [Matplotlibusers] 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 onesided 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 email 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 email in error please notify the sender. Please note that any views or opinions presented in this email are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this email and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this email. 
From: Ryan May <rmay31@gm...>  20081201 22:31:59

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 onesided 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/technotes/1700/1702.html > > To me, as Matplotlib is striving to be Matlabcompatible, 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 onesided 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 Matlabcompatible waywhen 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: Fago, Matt  AES <Matt.F<ago@it...>  20081201 22:50:55

> From: Ryan May [mailto:rmay31@...] > 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 onesided 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 > Matlabcompatible waywhen 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 This email 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 email in error please notify the sender. Please note that any views or opinions presented in this email are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this email and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this email. 
From: Fago, Matt  AES <Matt.F<ago@it...>  20081208 15:10:50

So what is to be done here? It seems to me that at least the factor of two should be fixed for onesided 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 [rmay31@...] Sent: Monday, December 01, 2008 3:31 PM To: Fago, Matt  AES Cc: Matplotlib Users Subject: Re: [Matplotlibusers] 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 onesided 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/technotes/1700/1702.html > > To me, as Matplotlib is striving to be Matlabcompatible, 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 onesided 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 Matlabcompatible waywhen 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 email 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 email in error please notify the sender. Please note that any views or opinions presented in this email are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this email and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this email. 
From: John Hunter <jdh2358@gm...>  20081208 15:17:50

On Mon, Dec 8, 2008 at 9:10 AM, Fago, Matt  AES <Matt.Fago@...> wrote: > > So what is to be done here? It seems to me that at least the factor of two should be > fixed for onesided 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 
From: Ryan May <rmay31@gm...>  20081208 16:56:50

John Hunter wrote: > On Mon, Dec 8, 2008 at 9:10 AM, Fago, Matt  AES <Matt.Fago@...> wrote: >> So what is to be done here? It seems to me that at least the factor of two should be >> fixed for onesided 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 onesided 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 
From: John Hunter <jdh2358@gm...>  20081208 17:16:01

On Mon, Dec 8, 2008 at 10:56 AM, Ryan May <rmay31@...> 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 
From: Ryan May <rmay31@gm...>  20081208 19:20:47

John Hunter wrote: > On Mon, Dec 8, 2008 at 10:56 AM, Ryan May <rmay31@...> 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 
From: Ryan May <rmay31@gm...>  20081208 21:58:51

John Hunter wrote: > On Mon, Dec 8, 2008 at 10:56 AM, Ryan May <rmay31@...> 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 
From: Fernando Perez <fperez.net@gm...>  20081208 23:38:40

On Mon, Dec 8, 2008 at 1:58 PM, Ryan May <rmay31@...> 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: Fago, Matt  AES <Matt.F<ago@it...>  20081209 16:12:40

> 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 This email 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 email in error please notify the sender. Please note that any views or opinions presented in this email are solely those of the author and do not necessarily represent those of ITT Corporation. The recipient should check this email and any attachments for the presence of viruses. ITT accepts no liability for any damage caused by any virus transmitted by this email. 
From: Ryan May <rmay31@gm...>  20081125 20:15:22

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 223 and 224). 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 224). > > 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 