Mailman 3 June 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

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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

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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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Selecting elements in a numpy array by their indices contained in two arrays
by Éric Depagne June 27, 2017

June 27, 2017

Hi list. Suppose I have a numpy array A (4,4) and two 1D array, one (X1) that would contain (2,2,1,1) and the other one X2 that would be (3,3,3,3). Is there a way to select all the elements of A that have indices between X1 and X2? In the current case, that would mean selecting A[2:3,0], A[2:3,1], A[1:3,2] and A[1:3,3] Thanks. Éric. -- Un clavier azerty en vaut deux ---------------------------------------------------------- Éric Depagne eric(a)depagne.org

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Convert linkage matrix to tree (scipy.cluster.hierarchy.to_tree, python3)
by Robert Winkler June 26, 2017

June 26, 2017

Hi, I want to translate a linkage matrix to a tree (to convert it in further steps to newick format). The linkage matrix looks like this: |[[0.1.1.2.][2.4.4.3.][3.5.6.4.]]| When I run the code ('from ete3 import Tree'): |T =scipy.cluster.hierarchy.to_tree(Z)root =Tree()root.dist =0root.name ="root"item2node ={T:root}| the program terminates at item2node with the error message: Exception "unhandled TypeError" unhashable type: 'ClusterNode' Any ideas? Robert The data, I run Y = scipy.cluster.hierarchy.linkage(refspec_array, 'complete') print(Y) T = scipy.cluster.hierarchy.to_tree(Y) look like this: [ ('1', 0.0, 0.0, 0.0, 0.0, 4.38755898755899, 0.0, 0.0, 11.4813953488372, 0.0, 0.0, 0.0, 0.0, 0.0, 3.37222222222222, 17.453347427766, 0.0, 0.0, 0.0, 6.10327695560254, 0.0, 0.0, 0.0, 12.4255813953488, 0.0, 5.1536069904491, 0.0, 0.0, 15.016330162086, 3.16285714285714, 3.83170731707317, 0.0, 18.7087586831773, 7.88292682926829, 45.4125613035912, 10.4775101513474, 12.0366102889359, 0.0, 0.0, 0.0, 3.2839463523674, 14.2130258077626, 70.5372093023256, 13.6720930232558, 19.715657343224, 4.91362382790954, 7.00714285714286, 0.0, 3.6776026026026, 0.0, 15.3790697674419, 4.15201131363922, 56.9372093023256, 0.0, 0.0, 0.0, 22.5604743447767, 0.0, 8.04212974296206, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 19.002380952381, 4.03296703296703, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 4.67, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0) ('2', 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.27097625891554, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.80990740740741, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 21.6565696834911, 6.580014781966, 19.9112912622229, 0.0, 0.0, 0.0, 0.0, 5.2982335122579, 52.672519005238, 25.1761382113821, 58.6225154191197, 6.53954083820578, 5.0235253034919, 0.0, 5.59207185091331, 6.8450632459782, 41.9248475609756, 8.94831608491355, 17.9927195135152, 3.56784893267652, 0.0, 0.0, 14.6637340301974, 10.2320372068382, 87.4304539295393, 17.6128532713899, 3.61942687747036, 4.9223667570009, 21.7575067583061, 4.87, 10.0497729362015, 7.4825, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)..]

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EuroSciPy 2017 call for contributions - extension of deadline
by Pierre de Buyl June 26, 2017

June 26, 2017

(Apologies if you receive multiple copies of this message) 10th European Conference on Python in Science August 28 - September 1, 2017 in Erlangen, Germany The Call for Papers is extended to July 02, 2017 23:00 CEST Description: The EuroSciPy meeting is a cross-disciplinary gathering focused on the use and development of the Python language in scientific research. This event strives to bring together both users and developers of scientific tools, as well as academic research and state of the art industry. Erlangen is one of Germany's major science hubs and located north of Munich (90 minutes by train). The Call for Papers is extended to July 02, 2017 23:00 CEST Regards, The EuroSciPy team https://www.euroscipy.org/2017/

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scipy.special.mathieu_modcem1 is not equal to the corresponding function in gsl
by Ming Lu June 24, 2017

June 24, 2017

Consider this code in python: import scipy.special as sp q=24 x=1.83 sp.mathieu_modcem1(0,q,x)[0] the result is: -0.094807461318619515 Translate into c++ with gsl: # include <iostream> # include <gsl/gsl_sf.h> int main() { double q = 24; double x = 1.83; double y = gsl_sf_mathieu_Mc(1,0,q,x); std::cout << y << std::endl; return 0; } the result is: -0.118824 What's the problem?

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ANN: SciPy 0.19.1 release
by Ralf Gommers June 23, 2017

June 23, 2017

On behalf of the Scipy development team I am pleased to announce the availability of Scipy 0.19.1. This is a bugfix-only release, no new features are included. This release requires Python 2.7 or 3.4-3.6 and NumPy 1.8.2 or greater. Source tarballs and release notes can be found at https://github.com/scipy/scipy/releases/tag/v0.19.1. OS X and Linux wheels are available from PyPI: https://pypi.python.org/pypi/scipy/0.19.1 Thanks to everyone who contributed! Cheers, Ralf -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 ========================== SciPy 0.19.1 Release Notes ========================== SciPy 0.19.1 is a bug-fix release with no new features compared to 0.19.0. The most important change is a fix for a severe memory leak in ``integrate.quad``. Authors ======= * Evgeni Burovski * Patrick Callier + * Yu Feng * Ralf Gommers * Ilhan Polat * Eric Quintero * Scott Sievert * Pauli Virtanen * Warren Weckesser A total of 9 people contributed to this release. People with a "+" by their names contributed a patch for the first time. This list of names is automatically generated, and may not be fully complete. Issues closed for 0.19.1 - ------------------------ - - `#7214 <https://github.com/scipy/scipy/issues/7214>`__: Memory use in integrate.quad in scipy-0.19.0 - - `#7258 <https://github.com/scipy/scipy/issues/7258>`__: ``linalg.matrix_balance`` gives wrong transformation matrix - - `#7262 <https://github.com/scipy/scipy/issues/7262>`__: Segfault in daily testing - - `#7273 <https://github.com/scipy/scipy/issues/7273>`__: ``scipy.interpolate._bspl.evaluate_spline`` gets wrong type - - `#7335 <https://github.com/scipy/scipy/issues/7335>`__: scipy.signal.dlti(A,B,C,D).freqresp() fails Pull requests for 0.19.1 - ------------------------ - - `#7211 <https://github.com/scipy/scipy/pull/7211>`__: BUG: convolve may yield inconsistent dtypes with method changed - - `#7216 <https://github.com/scipy/scipy/pull/7216>`__: BUG: integrate: fix refcounting bug in quad() - - `#7229 <https://github.com/scipy/scipy/pull/7229>`__: MAINT: special: Rewrite a test of wrightomega - - `#7261 <https://github.com/scipy/scipy/pull/7261>`__: FIX: Corrected the transformation matrix permutation - - `#7265 <https://github.com/scipy/scipy/pull/7265>`__: BUG: Fix broken axis handling in spectral functions - - `#7266 <https://github.com/scipy/scipy/pull/7266>`__: FIX 7262: ckdtree crashes in query_knn. - - `#7279 <https://github.com/scipy/scipy/pull/7279>`__: Upcast half- and single-precision floats to doubles in BSpline... - - `#7336 <https://github.com/scipy/scipy/pull/7336>`__: BUG: Fix signal.dfreqresp for StateSpace systems - - `#7419 <https://github.com/scipy/scipy/pull/7419>`__: Fix several issues in ``sparse.load_npz``, ``save_npz`` - - `#7420 <https://github.com/scipy/scipy/pull/7420>`__: BUG: stats: allow integers as kappa4 shape parameters Checksums ========= MD5 ~~~ 72415e8da753eea97eb9820602931cb5 scipy-0.19.1-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl e0022540df2735eb0475071b266d5d71 scipy-0.19.1-cp27-cp27m-manylinux1_i686.whl f513eb4ea2086de169a502df7efb91c7 scipy-0.19.1-cp27-cp27m-manylinux1_x86_64.whl 906c3c59209d6249b5d8ce14cfa01382 scipy-0.19.1-cp27-cp27mu-manylinux1_i686.whl afbf8ffb4a4fe7c18e34cb8a313c18ee scipy-0.19.1-cp27-cp27mu-manylinux1_x86_64.whl 5ba945b3404644244ab469883a1723f0 scipy-0.19.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 9c02cdd79e4ffadddcce7b2212039816 scipy-0.19.1-cp34-cp34m-manylinux1_i686.whl 79c0ba3618466614744de9a2f5362bbc scipy-0.19.1-cp34-cp34m-manylinux1_x86_64.whl 602a741a54190e16698ff8b2fe9fd27c scipy-0.19.1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl d6c2ecadd4df36eb61870227fae42d3a scipy-0.19.1-cp35-cp35m-manylinux1_i686.whl e7167c0a9cf270f89437e2fd09731636 scipy-0.19.1-cp35-cp35m-manylinux1_x86_64.whl fc2e4679e83590ff19c1a5c5b1aa4786 scipy-0.19.1-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 458615e9a56429a72038531dd5dcb3cb scipy-0.19.1-cp36-cp36m-manylinux1_i686.whl 65b1667ac56861da4cbc609960ed735b scipy-0.19.1-cp36-cp36m-manylinux1_x86_64.whl b704ebe9a28b8fe83d9f238d40031266 scipy-0.19.1.tar.gz cad6bac0638b176f72c00fe81ed54d19 scipy-0.19.1.tar.xz eb69261e5026ef2f3b9ae827caa7e5b8 scipy-0.19.1.zip SHA256 ~~~~~~ 1e8fedf602859b541ebae78667ccfc53158edef58d9ee19ee659309004565952 scipy-0.19.1-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 023ee29faa76c184a607e21076f097dc32f3abba7c71ece374588f95920aa993 scipy-0.19.1-cp27-cp27m-manylinux1_i686.whl 2a26d06a642e3c9107ca06df125f5dc5507abe2b87fd7865415d03ab654b0b43 scipy-0.19.1-cp27-cp27m-manylinux1_x86_64.whl b3e97be2cd9f052d984fc5ba2d441897971b744c64d658617944c47bc366f8ff scipy-0.19.1-cp27-cp27mu-manylinux1_i686.whl 78713101b32af384c564837fd7ae665a2a72cb6d49edbd8f32148d74724a65a8 scipy-0.19.1-cp27-cp27mu-manylinux1_x86_64.whl 2c9e87d556b83a8e11de7a064856c3997bbaff7f9cf62bf63ff0623751549e4c scipy-0.19.1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl b87a923ed390ba0aafcbbcc6f0e023d495f19d2bd22ae59bdef3b0aec6485b39 scipy-0.19.1-cp34-cp34m-manylinux1_i686.whl 2dc9bcfaa585d9d941fb1add0d160556fe8587c3800264a77643695565a2d279 scipy-0.19.1-cp34-cp34m-manylinux1_x86_64.whl 93825cc80c638d901099f657dfff852ad2421beb51cb7d1d3f91157741ebe287 scipy-0.19.1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 4118647273c907ed984da52b71fa2bbb30229f1820fb79b1ed087c8bc9a20cca scipy-0.19.1-cp35-cp35m-manylinux1_i686.whl 4c26ef44e8bb2cd2aef11c60d163caa04670d6f42996789b209526677310ded2 scipy-0.19.1-cp35-cp35m-manylinux1_x86_64.whl 2a3b6ceadbb58d8b8d4a329f8219f9e6f17757ec6c85baf03987bbd2b728c263 scipy-0.19.1-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl 909be30bdd1d8cd57609760ea72a1499543169ed6ea5c66fad50946582682cf8 scipy-0.19.1-cp36-cp36m-manylinux1_i686.whl 4de84e3870228e8afd55a6e63e762aa7c9d1e3bd9a9ef5ab716835a69c77d257 scipy-0.19.1-cp36-cp36m-manylinux1_x86_64.whl 9147f7b8b5ed4b80fefe82057a6d0d4bf3a50375a1d573407f84686d3b82c3bb scipy-0.19.1.tar.gz 0dca04c4860afdcb066cab4fd520fcffa8c85e9a7b5aa37a445308e899d728b3 scipy-0.19.1.tar.xz 2cc1baed85f7f702d958ad19e5d11c9dad917e981d3d0c299a7f0fd15027516a scipy-0.19.1.zip -----BEGIN PGP SIGNATURE----- Version: GnuPG v1 iQEcBAEBAgAGBQJZTTG2AAoJEO2+o3i/Gl69V8gH/3S199hh1Fcl0a05VOCgt7aZ zRKvdZhYkqGvWoWX+YwJBaZn0aXThJfIDE2lAGt4S9PyxObBKzsujI8OLIZF4zU5 PtAARrooOqDEH1CC39k2gscF9GBhxAlxwntM2Hd8h+4xsklAhFVxn4UT0M8igBoX txpaIqghzBJnenkMq6lqrj7vhupuulz0zrMnJU4LetpdSxX1lb5sGvWmZDTKd/nr xmthQ4TmHPbf9jAYCtLI4V6OUGFGLQ+d7IqiYvU+DVKNZFEgyPMnvN9QvSdu6diR JBEIBcijxM0BqjPwRoavCQjCHk37kR/G3UsgcEyHO2tr5zuOXogjjBo3Bei8jnI= =lFXD -----END PGP SIGNATURE-----

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Re: [SciPy-User] Strange behaviour of scipy.interpolate.interp1d in with kind="zero"
by Propadovic Nenad June 22, 2017

June 22, 2017

Hello Oleksandr, thank you for the swift answer. I think we can settle for an untreated edge case and/or an inconsistency. The values at times 0.004, 0.008, 0.012, 0.016 are exactly what I expect, after all: the exact values that the original signal at the exact points in time. I will file a bug, as you proposed. Regards, Nenad > Hi Nenad: > > This probably how the kind="zero" is implemented (uses a constant value > from the left side of the interval) and since in your case you do not have > any data to the right of the point, it is never used. > > Maybe it could be called bug.... (You could try to submit an issue on > github) > > Apparently, now for it to work as you want, you would need to extend your > sig a bit: > > import numpy > from scipy.interpolate import interp1d > t = numpy.array([0.000, 0.004, 0.008, 0.012, 0.016, 0.02, 0.03]) > sig = numpy.array([0, 1, 2, 3, 4, 5, 6]) > t_new = numpy.array([0.0, 0.001, 0.003, 0.004, 0.008, 0.012, 0.016, 0.0196, > 0.02]) > f = interp1d(t, sig, kind='zero') > s_resampled = f(t_new) > print(s_resampled) > [ 0. 0. 0. 1. 2. 3. 4. 4. 5.] > > > Cheers >

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Strange behaviour of scipy.interpolate.interp1d in with kind="zero"
by Propadovic Nenad June 21, 2017

June 21, 2017

Hello everybody, please consider the following code: --- import numpy from scipy.interpolate import interp1d t = numpy.array([0.000, 0.004, 0.008, 0.012, 0.016, 0.02]) sig = numpy.array([0, 1, 2, 3, 4, 5]) t_new = numpy.array([0.0, 0.001, 0.003, 0.004, 0.008, 0.012, 0.016, 0.0196, 0.02]) f = interp1d(t, sig, kind='zero') s_resampled = f(t_new) print s_resampled --- The result I get on my machine is: >C:\Anaconda2\pythonw -u "test_zero_order_hold.py" [ 0. 0. 0. 1. 2. 3. 4. 4. 4.] >Exit code: 0 Now why is the last value 4, and not 5? I'd expect it to be 5, as the last timestamps in t and t_new are identical. Is this a bug in interp1d or am I missing something important - if so, what? Thanks a lot, in advance, Nenad

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