Mailman 3 October 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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ANN: Scipy 0.16.1 release
by Ralf Gommers Oct. 25, 2015

Oct. 25, 2015

Hi all, I'm happy to announce the availability of the Scipy 0.16.1 release. This is a bugfix only release; it contains no new features compared to 0.16.0. The sources and binary installers can be found at: - Source tarballs: at https://github.com/scipy/scipy/releases and on PyPi. - OS X: there are wheels on PyPi, so simply install with pip. - Windows: .exe installers can be found on https://github.com/scipy/scipy/releases Cheers, Ralf ========================== SciPy 0.16.1 Release Notes ========================== SciPy 0.16.1 is a bug-fix release with no new features compared to 0.16.0. Issues closed for 0.16.1 ------------------------ - `#5077 <https://github.com/scipy/scipy/issues/5077>`__: cKDTree not indexing properly for arrays with too many elements - `#5127 <https://github.com/scipy/scipy/issues/5127>`__: Regression in 0.16.0: solve_banded errors out in patsy test suite - `#5149 <https://github.com/scipy/scipy/issues/5149>`__: linalg tests apparently cause python to crash with numpy 1.10.0b1 - `#5154 <https://github.com/scipy/scipy/issues/5154>`__: 0.16.0 fails to build on OS X; can't find Python.h - `#5173 <https://github.com/scipy/scipy/issues/5173>`__: failing stats.histogram test with numpy 1.10 - `#5191 <https://github.com/scipy/scipy/issues/5191>`__: Scipy 0.16.x - TypeError: _asarray_validated() got an unexpected... - `#5195 <https://github.com/scipy/scipy/issues/5195>`__: tarballs missing documentation source - `#5363 <https://github.com/scipy/scipy/issues/5363>`__: FAIL: test_orthogonal.test_j_roots, test_orthogonal.test_js_roots Pull requests for 0.16.1 ------------------------ - `#5088 <https://github.com/scipy/scipy/pull/5088>`__: BUG: fix logic error in cKDTree.sparse_distance_matrix - `#5089 <https://github.com/scipy/scipy/pull/5089>`__: BUG: Don't overwrite b in lfilter's FIR path - `#5128 <https://github.com/scipy/scipy/pull/5128>`__: BUG: solve_banded failed when solving 1x1 systems - `#5155 <https://github.com/scipy/scipy/pull/5155>`__: BLD: fix missing Python include for Homebrew builds. - `#5192 <https://github.com/scipy/scipy/pull/5192>`__: BUG: backport as_inexact kwarg to _asarray_validated - `#5203 <https://github.com/scipy/scipy/pull/5203>`__: BUG: fix uninitialized use in lartg 0.16 backport - `#5204 <https://github.com/scipy/scipy/pull/5204>`__: BUG: properly return error to fortran from ode_jacobian_function... - `#5207 <https://github.com/scipy/scipy/pull/5207>`__: TST: Fix TestCtypesQuad failure on Python 3.5 for Windows - `#5352 <https://github.com/scipy/scipy/pull/5352>`__: TST: sparse: silence warnings about boolean indexing - `#5355 <https://github.com/scipy/scipy/pull/5355>`__: MAINT: backports for 0.16.1 release - `#5356 <https://github.com/scipy/scipy/pull/5356>`__: REL: update Paver file to ensure sdist contents are OK for releases. - `#5382 <https://github.com/scipy/scipy/pull/5382>`__: 0.16.x backport: MAINT: work around a possible numpy ufunc loop... - `#5393 <https://github.com/scipy/scipy/pull/5393>`__: TST:special: bump tolerance levels for test_j_roots and test_js_roots - `#5417 <https://github.co

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access to odeint intermediate results for later interpolation
by David Mikolas Oct. 24, 2015

Oct. 24, 2015

I've read that sometimes one saves the intermediate results from numerical integration so that it can be re-interpolated for other points in time. For example, an efficient integration would use variable step size, and when it detects that the current step has passed one or more of the time points requested, it would use the same coefficients to calculate results at the requested time point instead of recalculating. If this is happening in odeint - where can I read about it. Maybe a "classic" reference to the odepack, or maybe the FORTRAN (though it may not be commented). Is there any possibility this could be accessed within python?

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fromstring and int64
by Carlos Medrano Oct. 22, 2015

Oct. 22, 2015

Hello, I am having an issue with function fromstring and long integers (int64). It seems it cannot read properly long numbers. I use scipy version 0.14.0 and numpy 1.8.2. I have the problem also if I use numpy directly. import scipy s='0 1445367600061 -35960 39671 79230' scipy.fromstring(s, sep=' ', dtype=scipy.int64) I get this array([ 0, 2147483647, -35960, 39671, 79230], dtype=int64) which is wrong in the second element However if I write to a file the string s and use loadtxt, I get the right values: f=open('dumf.txt','w') f.write(s) f.close() scipy.loadtxt('dumf.txt', dtype=scipy.int64) I get: array([0, 1445367600061, -35960, 39671, 79230], dtype=int64) I think this can be a bug a I would like to check on the mailing list first and see if other people have the same behaviour. Regards Carlos Medrano

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If you use GPL in our neighborhood then you break the chain, ...
by josef.pktd＠gmail.com Oct. 21, 2015

Oct. 21, 2015

... and something bad will happen to us. Dear developer, One of the great features of development in our neighborhood is that almost all code is BSD licensed or has a license that is compatible with it. This allows us to freely use and copy (with attribution) each others code, which makes some packages a great source of inspiration or provides code snippets for reuse. I think this is also a reason why Python became so successful. Not only is the code readable but everybody is also legally allowed to copy the code and adjust it to individual special requirements. GPL breaks the mutual sharing, because we cannot benefit back from the changes, improvements, adjustments and extensions. If you really want or need to license your code as GPL to protect a specific application or a GUI, then please consider dual licensing in a BSD compatible way the backend, the statistical backend as far as I'm concerned. Thank you for your attention. Josef

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Opportunity to contribute: 'pip upgrade'
by Nathaniel Smith Oct. 19, 2015

Oct. 19, 2015

Hi all, Just wanted to bring this to the attention of a wider audience -- Right now, if you're using pip to manage packages in a virtualenv, then upgrading to a new version of some package is *super annoying*, because you run pip install -U <whatever package> and then it starts upgrading not just the package you requested, but all the packages that it depends on. And if one of those packages is numpy or scipy or whatever, then suddenly your laptop is overheating and what should have been a 10 second process takes an hour and might fail and arrrghh frustrating. Then this also has nasty knock-on effects at the ecosystem level, because it motivates lots of numerical python packages to simply lie about what their dependencies are, on the theory that 'pip install -U' can't mess up a dependency that it can't see. Which resolves the immediate problem, but is obviously not a good long-term solution. >From some recent discussions on distutils-sig, one outcome was that the pip maintainers are actually totally happy to fix this if anyone wants to write a patch -- basically the idea would be to add a 'pip upgrade' command that works the way you'd expect (only upgrades the named package, plus whatever other packages are minimally required in order to satisfy its new dependencies -- basically the equivalent of 'pip install foo=<latest version>'), and deprecate 'install -U': https://github.com/pypa/pip/issues/59#issuecomment-147149208 So if anyone is feeling inspired to make a highly-visible fix to one of the most-widely-used Python programs, and earn the undying gratitude of lots of maintainers and users, then writing a patch to implement 'pip upgrade' and submitting it upstream would be a great opportunity for that ;-) -n -- Nathaniel J. Smith -- http://vorpus.org

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new feature: optimize.curve_fit with bounds
by Ralf Gommers Oct. 19, 2015

Oct. 19, 2015

Hi all, Curve fitting with bounds is a feature that has often been requested by users in the past, so I'd like to advertise the excellent GSoC work of Nikolay that's now included in Scipy master and will be in 0.17.0: 1. A new function optimize.least_squares: https://github.com/scipy/scipy/pull/5044 2. Adding bounds to optimize.curve_fit: https://github.com/scipy/scipy/pull/5147 Up-to-date html docs: http://scipy.github.io/devdocs/optimize.html Cheers, Ralf

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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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