Mailman 3 June 2013 - SciPy-User

How to display a RGB image (MFISH)?
by jp April 3, 2023

April 3, 2023

Hi, I have written a script to try to combine five images into a three channels RGB images<http://dip4fish.blogspot.com/2011/05/trying-to-combine-mfish-images-into-rg…> . The resulting RGB image looks like a grey scale image instead of a color one. I have three np.array Rnorm, Gnorm, Bnorm which are copied into a rgb array: *rgb = np.zeros((shape[0],shape[1],3),dtype=float) mxr=np.max(R) mxg=np.max(G) mxb=np.max(B) Rnorm=np.uint8((255*(R/mxr)))Gnorm=np.uint8((255*(R/mxg)))Bnorm=np.uint8((255*(R/mxb)))#copy each RGB component in an RGB array rgb[:,:,0]=Rnorm rgb[:,:,1]=Gnorm rgb[:,:,2]=Bnorm* *pylab.subplot(224, aspect='equal',frameon=False, xticks=[], yticks=[]) pylab.imshow(rgb) pylab.show()* Any advice? Thank you Jean-Patrick

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Invitation to connect on LinkedIn
by Jelle Feringa via LinkedIn July 28, 2022

July 28, 2022

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Help required regding Eigenvectors
by Sudheer Phani March 14, 2022

March 14, 2022

Hello All, I have been encountering some strange problems with the calculation of eigen vectors using python. The problem is with the sign of the eigen vectors calculated. On Very few occasions the eigen vectors calculated using python have an opposite sign than the actual eigenvectors, though the magnitude is correct. Can any one of you plz help me in this regard and suggest me some solution if you have encoutered similar problems . Any help in this regd is appreciated Thanks in Advace regds Sudheer

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Allan Variance
by Daniele Nicolodi Feb. 4, 2014

Feb. 4, 2014

Hello, does anyone know or have written and is willing to share some code to compute the Allan variance, modified Allan variance and friends, ideally both from frequency than from phase data? I'm writing my own code, it is not that difficult, but I would prefer the time required for testing and validation doing something more fun. If there is no available code implementing Allan variance, would it be interesting to include in in SciPy? Thank you so much. Best, Daniele

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At.: question about refresh numpy array in a for-cycle
by Josè Luis Mietta Aug. 19, 2013

Aug. 19, 2013

Hi experts! Im writing a code with a numpy array L, the numpy matrix M and the next script: for x in L: for l in srange(N): z= l in L if z is False and M[x,l] != 0: L=np.append(L,l) here, in the end of the cycle, new elements are incorporated to the array 'L'. I want these new elements be considered as 'x' index in the cycle. When I execute the script I see that only the 'originals' elements of L are considered as 'x'. How can i fix it? Waiting for your answers. Thanks a lot!

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ftol and xtol
by pfeldman July 6, 2013

July 6, 2013

It would be very helpful if one could specify `ftol` and `xtol` with any of the optimization algorithms. How difficult would it be to implement this? Phillip -- View this message in context: http://scipy-user.10969.n7.nabble.com/ftol-and-xtol-tp18355.html Sent from the Scipy-User mailing list archive at Nabble.com.

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SciPy ecosystem and Python 3
by Thomas Kluyver July 2, 2013

July 2, 2013

At a conversation over lunch here at the SciPy conference, a few of us mentioned that we're starting to use Python 3 in earnest for our work. For new users, the choice of two major Python versions is confusing and offputting, and we're not going to completely get rid of that confusion until we can simply point new users to Python 3. Most of our introductions, like the SciPy stack install page, point to Python 2 because of the ecosystem, but more and more packages now support Python 3, and we're reaching the point where we could reasonably recommend Python 3 for new users. The aim of this post is to get an overview of where the ecosystem is with: - What packages don't yet support Python 3, or are still too unstable? - How important are each of those: how widely relevant are they, and are substitutes available? - What other conditions need to be met to recommend Python 3? E.g. Scientific Python distros, Linux distro packaging, documentation, etc. Thanks, Thomas

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Re: [SciPy-User] butter() and filtfilt() - differences between MATLAB and scipy
by Paul Blelloch June 28, 2013

June 28, 2013

I ran the same butterworth filter problem and got the following results: >>> w=2./(256./2.) >>> b,a=butter(9,w) >>> b array([ 2.52984969e-14, 1.01193988e-13, 2.36119304e-13, 3.54178956e-13, 3.54178956e-13, 2.36119304e-13, 1.01193988e-13, 2.52984969e-14, 2.81094410e-15]) >>> a array([ 1. , -8.71731939, 33.77839104, -76.36014168, 110.98476353, -107.55300968, 69.49343715, -28.86903222, 6.99664203, -0.75373077]) These numerator values are different from Matlab's, which are: b = Columns 1 through 6 2.7931e-15 2.5138e-14 1.0055e-13 2.3462e-13 3.5193e-13 3.5193e-13 Columns 7 through 10 2.3462e-13 1.0055e-13 2.5138e-14 2.7931e-15 a = Columns 1 through 6 1.0000e+00 -8.7173e+00 3.3778e+01 -7.6360e+01 1.1098e+02 -1.0755e+02 Columns 7 through 10 6.9493e+01 -2.8869e+01 6.9966e+00 -7.5373e-01 I don't know why my numerator values are so different from yours. I'm using a 64-bit MKL optimized version of scipy 0.12.0. The differences between Matlab and scipy are on very small numbers. If you use a lower order filter, where the denominator coefficients are significant there are no differences between Matlab and scipy. The Matlab results may well be more accurate based on a difference in order of operations or something, but when I compared the 'filtfilt' output from the two sets of coefficients applied to white noise I didn't see much difference. What was more interesting to me was that the filtfilt results from Matlab were quite different in the initial transient than the filtfilt results from scipy using the same coefficients. It does appear to me that there's a difference in the application of the filtfilt function. -Paul -----Original Message----- From: scipy-user-bounces(a)scipy.org [mailto:scipy-user-bounces@scipy.org] On Behalf Of scipy-user-request(a)scipy.org Sent: Friday, June 28, 2013 4:42 AM To: scipy-user(a)scipy.org Subject: SciPy-User Digest, Vol 118, Issue 40 Send SciPy-User mailing list submissions to scipy-user(a)scipy.org To subscribe or unsubscribe via the World Wide Web, visit http://mail.scipy.org/mailman/listinfo/scipy-user or, via email, send a message with subject or body 'help' to scipy-user-request(a)scipy.org You can reach the person managing the list at scipy-user-owner(a)scipy.org When replying, please edit your Subject line so it is more specific than "Re: Contents of SciPy-User digest..." Today's Topics: 1. SciPy ecosystem and Python 3 (Thomas Kluyver) 2. Re: noob question: numpy copy vs standard lib copy (Joon Ro) 3. butter() and filtfilt() - differences between MATLAB and scipy (Tristan Strange) 4. Re: butter() and filtfilt() - differences between MATLAB and scipy (Fabrice Silva) 5. Re: butter() and filtfilt() - differences between MATLAB and scipy (Roger Fearick) 6. Re: butter() and filtfilt() - differences between MATLAB and scipy (Tristan Strange) ---------------------------------------------------------------------- Message: 1 Date: Fri, 28 Jun 2013 01:22:37 +0100 From: Thomas Kluyver <takowl(a)gmail.com> Subject: [SciPy-User] SciPy ecosystem and Python 3 To: SciPy Users List <scipy-user(a)scipy.org> Message-ID: <CAOvn4qgHQU1pRmUkR26rrhhq-kenJc4Q=bgukyDboMLsmk=aMw(a)mail.gmail.com> Content-Type: text/plain; charset="iso-8859-1" At a conversation over lunch here at the SciPy conference, a few of us mentioned that we're starting to use Python 3 in earnest for our work. For new users, the choice of two major Python versions is confusing and offputting, and we're not going to completely get rid of that confusion until we can simply point new users to Python 3. Most of our introductions, like the SciPy stack install page, point to Python 2 because of the ecosystem, but more and more packages now support Python 3, and we're reaching the point where we could reasonably recommend Python 3 for new users. The aim of this post is to get an overview of where the ecosystem is with: - What packages don't yet support Python 3, or are still too unstable? - How important are each of those: how widely relevant are they, and are substitutes available? - What other conditions need to be met to recommend Python 3? E.g. Scientific Python distros, Linux distro packaging, documentation, etc. Thanks, Thomas

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butter() and filtfilt() - differences between MATLAB and scipy
by Tristan Strange June 28, 2013

June 28, 2013

Hi all, I'm porting a script form MATLAB to Python and am getting very different results form the butter functions in the languages. In MATLAB when I do the following: w=2/(256/2); [b,a]=butter(9,w,'low'); b comes out as a matrix containing : 2.8109e-15 2.5298e-14 1.0119e-13 2.3612e-13 3.5418e-13 3.5418e-13 2.3612e-13 1.0119e-13 2.5298e-14 2.8109e-15 When done in Python using scipy.signal's butter like so: w = 2.0 / (256.0 / 2.0) b, a = butter(9, w, 'low') I get the following array with only a single value for b: array([ 2.81094410e-15]) and the following warning is issued: /usr/lib/python2.7/dist-packages/scipy/signal/filter_design.py:288: BadCoefficients: Badly conditioned filter coefficients (numerator): the results may be meaningless "results may be meaningless", BadCoefficients) Both functions in MATLAB and Python output the same a. When using these values in filtfilt() I get totally different results. I've tried exporting b from MATLAB and loading it in to Python and passing that in to filtfilt() but still get totally diffreent results. Can anyone tell me how to port this MATLAB code to Python such that the results are the same or explain what the problem is? Many thanks, Tristan

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noob question: numpy copy vs standard lib copy
by psoriasis June 28, 2013

June 28, 2013

I'm new to python. As I understand it, assignment copies by reference and to do otherwise requires a function like the standard library's copy or deepcopy functions. However, from what I see numpy has it's own copy function and using it on a random object (instance of a test class I made up not an array etc) doesn't seem to return the expected copy object. I did try importing the copy module and that worked but then the numpy copy module was "shadowed" but I don't know if that's a problem. Still, I'm sure numpy users need to copy regular objects so what's the standard solution to this? Note: I'm using the latest pythonxy (==> spyder, numpy, etc) Thanks

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