Mailman 3 September 2015 - 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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Playing numpy array over speakers
by Todd Oct. 17, 2015

Oct. 17, 2015

Is anyone aware of a well-maintained, simple, cross-platform python package that can play a numpy array as sound over speakers? I am aware of https://wiki.python.org/moin/Audio/. However, in all the cases there, as far as I can find they either do not support numpy arrays, are not cross-platform, cannot playback sound at all, or are unmaintained. There is also PySoundCard, which would do what I need but also appears to be unmaintained (no release in over a year, and no commits in 5 months, no release with serious bugfixes mentioned in commits).

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Alternative for scipy.sparse.sparsetools for use from outside of scipy
by Lev Konstantinovskiy Oct. 12, 2015

Oct. 12, 2015

Hi, Getting deprecation warning for sparsetools. Is there an alternative to switch to? The use is sparsetools.csc_matvecs in gensim https://github.com/piskvorky/gensim/blob/9a1c2c954e2f72213023fc01f0e3330600… 303f/gensim/models/lsimodel.py warning on import: gensim/home/ubuntu/.vew/ds26/lib/python2.6/site- packages/numpy/lib/utils.py:95: DeprecationWarning: `scipy.sparse.sparsetools` is deprecated! scipy.sparse.sparsetools is a private module for scipy.sparse, and should not be used. warnings.warn(depdoc, DeprecationWarning) Thanks

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Fwd: ANN: SfePy 2015.3
by Robert Cimrman Sept. 30, 2015

Sept. 30, 2015

FYI: resending due to mailing list problems last week, apologies if you already got this. -------- Forwarded Message -------- I am pleased to announce release 2015.3 of SfePy. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method or by the isogeometric analysis (preliminary support). It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: http://groups.google.com/group/sfepy-devel Git (source) repository, issue tracker, wiki: http://github.com/sfepy Highlights of this release -------------------------- - preliminary support for parallel computing - unified evaluation of basis functions (= isogeometric analysis fields can be evaluated in arbitrary points) - (mostly) fixed finding of reference element coordinates of physical points - several new or improved examples For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1 (rather long and technical). Best regards, Robert Cimrman on behalf of the SfePy development team --- Contributors to this release in alphabetical order: Robert Cimrman Vladimir Lukes

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ODR multiresponse multidimensional
by Thomas Howells Sept. 29, 2015

Sept. 29, 2015

Dear Pythonistas, I'm new to the mailing list, my question here is related to scipy's Orthogonal Distance Regression (ODR) wrapper module. My apologies if you've received this before, I had some trouble with the mail delivery system. >From perusal of the documentation for the wrapper and the underlying Fortran routines, it seems the Fortran code can handle a dataset that is both multiresponse and multidimensional. I have such a dataset that I would like to try and use the algorithm for; however as far as I can tell the ODR wrapper doesn't have the machinery to support this usage. It's possible I've missed something, so I'm interested if anyone has any experience with this sort of problem. If not I may dig into the wrapper a bit more and see if the functionality I want could be added. Thanks, Thomas Howells

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ANN: numtraits v0.2
by Thomas Robitaille Sept. 29, 2015

Sept. 29, 2015

Hi everyone, (apologies if you already saw this on the numpy-discussion list. I am resending it to the scipy-user and ipython-user mailing lists since these were down last week) We have released a small experimental package called numtraits that builds on top of the traitlets package and provides a NumericalTrait class that can be used to validate properties such as: * number of dimension (for arrays) * shape (for arrays) * domain (e.g. positive, negative, range of values) * units (with support for astropy.units, pint, and quantities) The idea is to be able to write a class like: class Sphere(HasTraits): radius = NumericalTrait(domain='strictly-positive', ndim=0) position = NumericalTrait(shape=(3,)) and all the validation will then be done automatically when the user sets 'radius' or 'position'. In addition, tuples and lists can get automatically converted to arrays, and default values can be specified. You can read more about the package and see examples of it in use here: https://github.com/astrofrog/numtraits and it can be easily installed with pip install numtraits The package supports both Python 3.3+ and Legacy Python (2.7) :) At this point, we would be very interested in feedback - the package is still very young and we can still change the API if needed. Please open issues with suggestions! Cheers, Tom and Francesco

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Numpy 1.10.0rc2 released
by Charles R Harris Sept. 29, 2015

Sept. 29, 2015

Hi all, I'm pleased to announce the availability of Numpy 1.10.0rc12. Sources and 32 bit binary packages for Windows may be found at Sourceforge <https://sourceforge.net/projects/numpy/files/NumPy/1.10.0rc2/?upload_just_c…>. There have been a few fixes since rc1. If there are no more problems I hope to release the final in a week or so. Cheers Chuck

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New version of "scipy lecture notes"
by Gael Varoquaux Sept. 28, 2015

Sept. 28, 2015

Dear Pythonistas, We have just released a new version of the "scipy lecture notes": http://www.scipy-lectures.org/ These are a consistent set of materials to learn the core aspects of the scientific Python ecosystem, from beginner to expert. They are written and maintained by a set of volunteers and published under a CC-BY license. Highlights of the latest version includes: * a chapter giving a introduction to statistics in Python * a new layout with emphasis on readability including on small devices * fully doctesting for Python 2 and 3 compatibility We hope that you will find these notes useful, for you, your colleagues, or your students. Gaël

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