Mailman 3 May 2014 - SciPy-User

How to display a RGB image (MFISH)?
by jp April 2, 2023

April 2, 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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Normalization for optimization in python
by Yuxiang Wang April 27, 2015

April 27, 2015

Dear all, During optimization, it is often helpful to normalize the input parameters to make them on the same order of magnitude, so the convergence can be much better. For example, if we want to minimize f(x), while a reasonable approximation is x0=[1e3, 1e-4], it might be helpful to normalize x0[0] and x0[1] to about the same order of magnitude (often O(1)). My question is, I have been using scipy.optimize and specifically, the L-BFGS-B algorithm. I was wondering that, do I need to normalize that manually by writing a function, or the algorithm already did it for me? Thank you! -Shawn -- Yuxiang "Shawn" Wang Gerling Research Lab University of Virginia yw5aj(a)virginia.edu +1 (434) 284-0836 https://sites.google.com/a/virginia.edu/yw5aj/

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GMRES iteration number
by Jonathan Tu June 10, 2014

June 10, 2014

Hi, Is there any way to access the number of iterations it takes to complete a GMRES computation? I've checked the documentation at http://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.sparse.lin… and it doesn't appear so. I am doing some testing with passing in initial guesses x0, and I am interested to know whether or not this significantly reduces the required number of iterations. Thanks, Jonathan Tu

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find zero
by nicky van foreest May 31, 2014

May 31, 2014

Hi, I am trying to find a zero in an array V that is positive at the left some index i, say, and negative at the right of i. V is not necessarily descending, so that numpy.searchsorted does not always find the right answer. My solution to find i is like this i = np.searchsorted(V<0, 0.5) This, however, seems a bit overkill, as the complexity of this algorithm is at least as large as the length of V, (due to V<0) . Does anybody know of a smarter, a more direct, solution? Of course, I can build a function, use scipy.optimize.brentq, but that appears to be even more overkill. thanks Nicky

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Re: [SciPy-User] [Numpy-discussion] ANN: Pandas 0.14.0 released
by Matthew Brett May 30, 2014

May 30, 2014

Hi, On Fri, May 30, 2014 at 3:16 PM, Neal Becker <ndbecker2(a)gmail.com> wrote: > pip install --user --up pandas > Downloading/unpacking pandas from > https://pypi.python.org/packages/source/p/pandas/pandas-0.14.0.tar.gz#md5=b… > ... > > Downloading/unpacking numpy>=1.6.1 from > https://pypi.python.org/packages/source/n/numpy/numpy-1.8.1.tar.gz#md5=be95… > (from pandas) > Downloading numpy-1.8.1.tar.gz (3.8MB): 3.8MB downloaded > Running setup.py egg_info for package numpy > Running from numpy source directory. > > warning: no files found matching 'tools/py3tool.py' > warning: no files found matching '*' under directory 'doc/f2py' > warning: no previously-included files matching '*.pyc' found anywhere in > distribution > warning: no previously-included files matching '*.pyo' found anywhere in > distribution > warning: no previously-included files matching '*.pyd' found anywhere in > distribution > Downloading/unpacking six from > https://pypi.python.org/packages/source/s/six/six-1.6.1.tar.gz#md5=07d606ac… > (from python-dateutil->pandas) > Downloading six-1.6.1.tar.gz > Running setup.py egg_info for package six > > no previously-included directories found matching 'documentation/_build' > Installing collected packages: pandas, pytz, numpy, six > .... > > What? I already have numpy-1.8.0 installed (also have six, pytz). Yes, this is a very unfortunate feature of pip --upgrade - it does a recursive upgrade of all dependent packages: http://pip.readthedocs.org/en/latest/reference/pip_install.html#cmdoption-U https://github.com/pypa/pip/issues/304 Maybe you could just do: pip install --ignore-install pandas instead? Cheers, Matthew

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ANN: Pandas 0.14.0 released
by Jeff Reback May 30, 2014

May 30, 2014

Hello, We are proud to announce v0.14.0 of pandas, a major release from 0.13.1. This release includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. This was 4 months of work with 1014 commits by 121 authors encompassing 757 issues. We recommend that all users upgrade to this version. *Highlights:* - Officially support Python 3.4 - SQL interfaces updated to use sqlalchemy - Display interface changes - MultiIndexing Using Slicers - Ability to join a singly-indexed DataFrame with a multi-indexed DataFrame - More consistency in groupby results and more flexible groupby specifications - Holiday calendars are now supported in CustomBusinessDay - Several improvements in plotting functions, including: hexbin, area and pie plots - Performance doc section on I/O operations See a full description of Whatsnew for v0.14.0 here: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html *What is it:* *pandas* is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. Documentation: http://pandas.pydata.org/pandas-docs/stable/ Source tarballs, windows binaries are available on PyPI: https://pypi.python.org/pypi/pandas windows binaries are courtesy of Christoph Gohlke and are built on Numpy 1.8 macosx wheels will be available soon, courtesy of Matthew Brett Please report any issues here: https://github.com/pydata/pandas/issues Thanks The Pandas Development Team Contributors to the 0.14.0 release - Acanthostega - Adam Marcus - agijsberts - akittredge - Alex Gaudio - Alex Rothberg - AllenDowney - Andrew Rosenfeld - Andy Hayden - ankostis - anomrake - Antoine Mazières - anton-d - bashtage - Benedikt Sauer - benjamin - Brad Buran - bwignall - cgohlke - chebee7i - Christopher Whelan - Clark Fitzgerald - clham - Dale Jung - Dan Allan - Dan Birken - danielballan - Daniel Waeber - David Jung - David Stephens - Douglas McNeil - DSM - Garrett Drapala - Gouthaman Balaraman - Guillaume Poulin - hshimizu77 - hugo - immerrr - ischwabacher - Jacob Howard - Jacob Schaer - jaimefrio - Jason Sexauer - Jeff Reback - Jeffrey Starr - Jeff Tratner - John David Reaver - John McNamara - John W. O'Brien - Jonathan Chambers - Joris Van den Bossche - jreback - jsexauer - Julia Evans - Júlio - Katie Atkinson - kdiether - Kelsey Jordahl - Kevin Sheppard - K.-Michael Aye - Matthias Kuhn - Matt Wittmann - Max Grender-Jones - Michael E. Gruen - michaelws - mikebailey - Mike Kelly - Nipun Batra - Noah Spies - ojdo - onesandzeroes - Patrick O'Keeffe - phaebz - Phillip Cloud - Pietro Battiston - PKEuS - Randy Carnevale - ribonoous - Robert Gibboni - rockg - sinhrks - Skipper Seabold - SplashDance - Stephan Hoyer - Tim Cera - Tobias Brandt - Todd Jennings - TomAugspurger - Tom Augspurger - unutbu - westurner - Yaroslav Halchenko - y-p - zach powers

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leastsq and multiprocessing
by Frédéric Parrenin May 30, 2014

May 30, 2014

Dear all, Following these posts: http://stackoverflow.com/questions/10489134/multithreaded-calls-to-the-obje… It seems it is possible to make leastsq take part of multiple processors. I was wondering: given that the tendency of processors is to have more and more cores nowadays, why this is not done by default in leastsq? Best regards, Frédéric Parrenin

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about opening netcdf file
by lily li May 28, 2014

May 28, 2014

Hi scipy users, I want to ask that how to open a NetCDF file? I tried to import netCDF4, but it says no such module. So which module or package to install beforehand? Thanks very much.

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