Mailman 3 May 2017 - 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

3 4

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

July 28, 2022

LinkedIn ------------ Jelle Feringa requested to add you as a connection on LinkedIn: ------------------------------------------ Jose, I'd like to add you to my professional network on LinkedIn. - Jelle Accept invitation from Jelle Feringa http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/Q6WKH0LACopGJkAw_6fSqajo6R7VM… View invitation from Jelle Feringa http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/Q6WKH0LACopGJkAw_6fSqajo6R7VM… ------------------------------------------ DID YOU KNOW your LinkedIn profile helps you control your public image when people search for you? Setting your profile as public means your LinkedIn profile will come up when people enter your name in leading search engines. Take control of your image! http://www.linkedin.com/e/-3wy1w2-gpkzwpgn-5n/ewp/inv-22/ -- (c) 2011, LinkedIn Corporation

2 1

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

5 5

scale parameter at 0
by Mainak Jas May 29, 2017

May 29, 2017

Hi everyone, I was wondering if anyone had an insight into what happens in scipy when the scale parameter becomes 0. In particular, I was looking into lévy stable distribution. If we do in scipy: >>> from scipy.stats import levy_stable >>> levy_stable.rvs(alpha=0.99, beta=1, scale=0, loc=1, size=5) I get: >>> array([ 1., 1., 1., 1., 1.]) But when I look in wikipedia <https://en.wikipedia.org/wiki/L%C3%A9vy_distribution>, it tells me that the scale parameter should be greater than 0. Maybe it's a more general question for all distributions, but I'm interested in this one particularly. Why doesn't scipy throw an error when scale parameter is 0? Thanks. Best regards, Mainak

3 4

low memory labeled component clustering
by Edward Richards May 27, 2017

May 27, 2017

I would like a LCC algorithm that produces sparse results. What I have in mind would be similar to MATLAB's bwconncomp and return a sparse data structure instead of a dense label array. I am new to image processing, and have only a surface understanding of the LCC algorithm. I am hoping that the experts out there can let me know if my goal is tenable (or hopefully already implemented), before I dive too deeply into the ndimage.label source code. I am working on a detection algorithm, and the data is 3D and can be very large in shape but sparse. I would like to process a bunch of data at once to avoid edge effects. Currently I am maxing out my computers RAM (32 GB) processing a (50, 200, 523264) element array. This array has only ~3 million non-zero elements, or 0.00056 sparsity. For each cluster I only need; the max value, it's location, and the number of elements. Currently, the data is stored as a list of sparse matrices. Is it possible to have the only 3D representation of the data be a Boolean array that I pass to a clustering algorithm? For my problem, it is better to take reasonable performance hits than hold temporary arrays in memory. Thank you, Ned

1 0

scipy optimization: inequality constraint type
by Kirill Balunov May 26, 2017

May 26, 2017

Hi, I've tried some scipy optimization routines, they work great!!! But I wondered, why historically for inequality constraints the type was chosen to be "greater than or equal" type? This is inconsistent with the classical formulation of non-linear programming problems. Thanks! -gdg

2 8

Alergia algorithm
by klaus schilling May 19, 2017

May 19, 2017

is there already a module implementing, on top of sci-py, the Alergia-algorithm for the construction of stochastic finite automata from prefix tree models? Klaus Schilling

1 0

ANN: SfePy 2017.2
by Robert Cimrman May 19, 2017

May 19, 2017

I am pleased to announce release 2017.2 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 (limited support). It is distributed under the new BSD license. Home page: http://sfepy.org Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/ Git (source) repository, issue tracker: https://github.com/sfepy/sfepy Highlights of this release -------------------------- - simplified and unified implementation of some homogenized coefficients - support for saving custom structured data to HDF5 files - new tutorial on preparing meshes using FreeCAD/OpenSCAD and Gmsh For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1 (rather long and technical). Cheers, Robert Cimrman --- Contributors to this release in alphabetical order: Robert Cimrman Jan Heczko Lubos Kejzlar Vladimir Lukes Matyas Novak

1 0

NumPy 1.13.0rc2 released
by Charles R Harris May 18, 2017

May 18, 2017

Hi All, I'm pleased to announce the NumPy 1.13.0rc2 release. This release supports Python 2.7 and 3.4-3.6 and contains many new features. It is one of the most ambitious releases in the last several years. Some of the highlights and new functions are *Highlights* - Operations like ``a + b + c`` will reuse temporaries on some platforms, resulting in less memory use and faster execution. - Inplace operations check if inputs overlap outputs and create temporaries to avoid problems. - New __array_ufunc__ attribute provides improved ability for classes to override default ufunc behavior. - New np.block function for creating blocked arrays. *New functions* - New ``np.positive`` ufunc. - New ``np.divmod`` ufunc provides more efficient divmod. - New ``np.isnat`` ufunc tests for NaT special values. - New ``np.heaviside`` ufunc computes the Heaviside function. - New ``np.isin`` function, improves on ``in1d``. - New ``np.block`` function for creating blocked arrays. - New ``PyArray_MapIterArrayCopyIfOverlap`` added to NumPy C-API. Wheels for the pre-release are available on PyPI. Source tarballs, zipfiles, release notes, and the changelog are available on github <https://github.com/numpy/numpy/releases/tag/v1.13.0rc2>. A total of 102 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - A. Jesse Jiryu Davis + - Alessandro Pietro Bardelli + - Alex Rothberg + - Alexander Shadchin - Allan Haldane - Andres Guzman-Ballen + - Antoine Pitrou - Antony Lee - B R S Recht + - Baurzhan Muftakhidinov + - Ben Rowland - Benda Xu + - Blake Griffith - Bradley Wogsland + - Brandon Carter + - CJ Carey - Charles Harris - Christoph Gohlke - Danny Hermes + - David Hagen + - David Nicholson + - Duke Vijitbenjaronk + - Egor Klenin + - Elliott Forney + - Elliott M Forney + - Endolith - Eric Wieser - Erik M. Bray - Eugene + - Evan Limanto + - Felix Berkenkamp + - François Bissey + - Frederic Bastien - Greg Young - Gregory R. Lee - Importance of Being Ernest + - Jaime Fernandez - Jakub Wilk + - James Cowgill + - James Sanders - Jean Utke + - Jesse Thoren + - Jim Crist + - Joerg Behrmann + - John Kirkham - Jonathan Helmus - Jonathan L Long - Jonathan Tammo Siebert + - Joseph Fox-Rabinovitz - Joshua Loyal + - Juan Nunez-Iglesias + - Julian Taylor - Kirill Balunov + - Likhith Chitneni + - Loïc Estève - Mads Ohm Larsen - Marein Könings + - Marten van Kerkwijk - Martin Thoma - Martino Sorbaro + - Marvin Schmidt + - Matthew Brett - Matthias Bussonnier + - Matthias C. M. Troffaes + - Matti Picus - Michael Seifert - Mikhail Pak + - Mortada Mehyar - Nathaniel J. Smith - Nick Papior - Oscar Villellas + - Pauli Virtanen - Pavel Potocek - Pete Peeradej Tanruangporn + - Philipp A + - Ralf Gommers - Robert Kern - Roland Kaufmann + - Ronan Lamy - Sami Salonen + - Sanchez Gonzalez Alvaro - Sebastian Berg - Shota Kawabuchi - Simon Gibbons - Stefan Otte - Stefan Peterson + - Stephan Hoyer - Søren Fuglede Jørgensen + - Takuya Akiba - Tom Boyd + - Ville Skyttä + - Warren Weckesser - Wendell Smith - Yu Feng - Zixu Zhao + - Zè Vinícius + - aha66 + - drabach + - drlvk + - jsh9 + - solarjoe + - zengi + Cheers, Chuck

1 0

Install Scipy with Anaconda's MKL libraries
by David Hagen May 18, 2017

May 18, 2017

Anaconda now comes with free MKL libraries. I am trying to install the development branch of Scipy into an Anaconda environment, which means running the full Scipy install, not just the wheel. Scipy needs BLAS/LAPACK in order to compile, so the built in MKL seems to make sense. However, it seems that Scipy can't find the MKL libraries because it gives the "no lapack/blas resources found" error during setup.py when running a pip install. Is there an environment variable I need to set in order to tell Scipy's setup where my LAPACK library lives? Here is exactly what I am running: conda create --name scipy_master python=3.6 numpy cython activate scipy_master pip install https://github.com/scipy/scipy/tarball/master I asked this on Stack Overflow <https://stackoverflow.com/questions/43559959/compiling-scipy-with-anacondas…> last week but didn't get an answer.

7 29