Mailman 3 March 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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EuroSciPy 2017
by Robert Pollak May 10, 2017

May 10, 2017

Dear EuroSciPy team, I have noticed that EuroSciPy 2017 in Erlangen is announced as "upcoming" on https://conference.scipy.org/ . Is there already a date fixed? Best regards, Robert

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Announcement: scikit-image 0.13.0
by Juan Nunez-Iglesias March 29, 2017

March 29, 2017

We're happy to (finally) announce the release of scikit-image v0.13.0! Special thanks to our many contributors for making it possible! This release is the result of over a year of work, with over 200 pull requests by 82 contributors. Linux and macOS wheels are available now on PyPI <https://pypi.python.org/pypi/scikit-image>, together with a source distribution. Use "pip install -U scikit-image" to get the latest version! Packages on conda-forge, Windows wheels, and Debian packages should be available within the next few days. scikit-image is an image processing toolbox for SciPy that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. For more information, examples, and documentation, please visit our website: http://scikit-image.org and our gallery of examples http://scikit-image.org/docs/dev/auto_examples/ Highlights ---------- - Improved n-dimensional image support. This release adds nD support to: * ``regionprops`` computation for centroids (#2083) * ``segmentation.clear_border`` (#2087) * Hessian matrix (#2194) - In addition, the following new functions support nD images: * new wavelet denoising function, ``restoration.denoise_wavelet`` (#1833, #2190, #2238, #2240, #2241, #2242, #2462) * new thresholding functions, ``filters.threshold_sauvola`` and ``filters.threshold_niblack`` (#2266, #2441) * new local maximum, local minimum, hmaxima, hminima functions (#2449) - Grey level co-occurrence matrix (GLCM) now works with uint16 images - ``filters.try_all_threshold`` to rapidly see output of various thresholding methods - Frangi and Hessian filters (2D only) (#2153) - New *compact watershed* algorithm in ``segmentation.watershed`` (#2211) - New *shape index* algorithm in ``feature.shape_index`` (#2312) New functions and features -------------------------- - Add threshold minimum algorithm (#2104) - Implement mean and triangle thresholding (#2126) - Add Frangi and Hessian filters (#2153) - add bbox_area to region properties (#2187) - colorconv: Add rgba2rgb() (#2181) - Lewiner marching cubes algorithm (#2052) - image inversion (#2199) - wavelet denoising (from #1833) (#2190) - routine to estimate the noise standard deviation from an image (#1837) - Add compact watershed and clean up existing watershed (#2211) - Added the missing 'grey2rgb' function. (#2316) - Shape index (#2312) - Fundamental and essential matrix 8-point algorithm (#1357) - Add YUV, YIQ, YPbPr, YCbCr colorspaces - Detection of local extrema from morphology (#2449) - shannon entropy (#2416) Documentation improvements -------------------------- - add details about github SSH keys in contributing page (#2073) - Add example for felzenszwalb image segmentation (#2096) - Sphinx gallery for example gallery (#2078) - Improved region boundary RAG docs (#2106) - Add gallery Lucy-Richardson deconvolution algorithm (#2376) - Gallery: Use Horse to illustrate Convex Hull (#2431) - Add working with OpenCV in user guide (#2519) Code improvements ----------------- - Remove lena image from test suite (#1985) - Remove duplicate mean calculation in skimage.feature.match_template (#1980) - Add nD support to clear_border (#2087) - Add uint16 images support for co-occurrence matrix (#2095) - Add default parameters for Gaussian and median filters (#2151) - try_all to choose the best threshold algorithm (#2110) - Add support for multichannel in Felzenszwalb segmentation (#2134) - Improved SimilarityTransform, new EuclideanTransform class (#2044) - ENH: Speed up Hessian matrix computation (#2194) - add n-dimensional support to denoise_wavelet (#2242) - Speedup ``inpaint_biharmonic`` (#2234) - Update hessian matrix code to include order kwarg (#2327) - Handle cases for label2rgb where input labels are negative and/or nonconsecutive (#2370) - Added watershed_line parameter (#2393) API Changes ----------- - Remove deprecated ``filter`` module. Use ``filters`` instead. (#2023) - Remove ``skimage.filters.canny`` links. Use ``feature.canny`` instead. (#2024) - Removed Python 2.6 support and related checks (#2033) - Remove deprecated {h/v}sobel, {h/v}prewitt, {h/v}scharr, roberts_{positive/negative} filters (#2159) - Remove deprecated ``_mode_deprecations`` (#2156) - Remove deprecated None defaults in ``rescale_intensity`` (#2161) - Parameters ``ntiles_x`` and ``ntiles_y`` have been removed from ``exposure.equalize_adapthist`` - The minimum NumPy version is now 1.11, and the minimum SciPy version is now 0.17 Deprecations ------------ - clip_negative will be set to false by default in version 0.15 (func: dtype_limits) (#2228) - Deprecate "dynamic_range" in favor of "data_range" (#2384) - The default value of the ``circle`` argument to ``radon`` and ``iradon`` transforms will be ``True`` in 0.15 (#2235) - The default value of ``multichannel`` for ``denoise_bilateral`` and ``denoise_nl_means`` will be ``False`` in 0.15 - The default value of ``block_norm`` in ``feature.hog`` will be L2-Hysteresis in 0.15. - The ``threshold_adaptive`` function is deprecated. Use ``threshold_local`` instead. - The default value of ``mode`` in ``transform.swirl``, ``resize``, and ``rescale`` will be "reflect" in 0.15. For a complete list of contributors and pull requests merged in this release, please see our release notes online: https://github.com/scikit-image/scikit-image/blob/master/doc/release/releas… Please spread the word, including on Twitter <https://twitter.com/jnuneziglesias/status/847145183250665472>! Enjoy! Juan.

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Announcement: scikit-image 0.13.0
by Juan Nunez-Iglesias March 29, 2017

March 29, 2017

We're happy to (finally) announce the release of scikit-image v0.13.0! Special thanks to all our contributors who made this possible. Linux and macOS wheels are available now on PyPI, as well as a source distribution. A conda-forge package, Windows wheels, and Debian packages should arrive in the coming days. scikit-image is an image processing toolbox for SciPy that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. For more information, examples, and documentation, please visit our website: http://scikit-image.org and our gallery of examples http://scikit-image.org/docs/dev/auto_examples/ Highlights ---------- This release is the result of a year of work, with over 200 pull requests by 82 contributors. Highlights include: - Improved n-dimensional image support. This release adds nD support to: * ``regionprops`` computation for centroids (#2083) * ``segmentation.clear_border`` (#2087) * Hessian matrix (#2194, #2327) - In addition, the following new functions support nD images: * new wavelet denoising function, ``restoration.denoise_wavelet`` (#1833, #2190, #2238, #2240, #2241, #2242, #2462) * new thresholding functions, ``filters.threshold_sauvola`` and ``filters.threshold_niblack`` (#2266, #2441) * new local maximum, local minimum, hmaxima, hminima functions (#2449) - Grey level co-occurrence matrix (GLCM) now works with uint16 images - ``filters.try_all_threshold`` to rapidly see output of various thresholding methods - Frangi and Hessian filters (2D only) (#2153) - New *compact watershed* algorithm in ``segmentation.watershed`` (#2211) - New *shape index* algorithm in ``feature.shape_index`` (#2312) New functions and features -------------------------- - Add threshold minimum algorithm (#2104) - Implement mean and triangle thresholding (#2126) - Add Frangi and Hessian filters (#2153) - add bbox_area to region properties (#2187) - colorconv: Add rgba2rgb() (#2181) - Lewiner marching cubes algorithm (#2052) - image inversion (#2199) - wavelet denoising (from #1833) (#2190) - routine to estimate the noise standard deviation from an image (#1837) - Add compact watershed and clean up existing watershed (#2211) - Added the missing 'grey2rgb' function. (#2316) - Shape index (#2312) - Fundamental and essential matrix 8-point algorithm (#1357) - Add YUV, YIQ, YPbPr, YCbCr colorspaces - Detection of local extrema from morphology (#2449) - shannon entropy (#2416) Documentation improvements -------------------------- - add details about github SSH keys in contributing page (#2073) - Add example for felzenszwalb image segmentation (#2096) - Sphinx gallery for example gallery (#2078) - Improved region boundary RAG docs (#2106) - Add gallery Lucy-Richardson deconvolution algorithm (#2376) - Gallery: Use Horse to illustrate Convex Hull (#2431) - Add working with OpenCV in user guide (#2519) Code improvements ----------------- - Remove lena image from test suite (#1985) - Remove duplicate mean calculation in skimage.feature.match_template (#1980) - Add nD support to clear_border (#2087) - Add uint16 images support for co-occurrence matrix (#2095) - Add default parameters for Gaussian and median filters (#2151) - try_all to choose the best threshold algorithm (#2110) - Add support for multichannel in Felzenszwalb segmentation (#2134) - Improved SimilarityTransform, new EuclideanTransform class (#2044) - ENH: Speed up Hessian matrix computation (#2194) - add n-dimensional support to denoise_wavelet (#2242) - Speedup ``inpaint_biharmonic`` (#2234) - Update hessian matrix code to include order kwarg (#2327) - Handle cases for label2rgb where input labels are negative and/or nonconsecutive (#2370) - Added watershed_line parameter (#2393) API Changes ----------- - Remove deprecated ``filter`` module. Use ``filters`` instead. (#2023) - Remove ``skimage.filters.canny`` links. Use ``feature.canny`` instead. (#2024) - Removed Python 2.6 support and related checks (#2033) - Remove deprecated {h/v}sobel, {h/v}prewitt, {h/v}scharr, roberts_{positive/negative} filters (#2159) - Remove deprecated ``_mode_deprecations`` (#2156) - Remove deprecated None defaults in ``rescale_intensity`` (#2161) - Parameters ``ntiles_x`` and ``ntiles_y`` have been removed from ``exposure.equalize_adapthist`` - The minimum NumPy version is now 1.11, and the minimum SciPy version is now 0.17 Deprecations ------------ - clip_negative will be set to false by default in version 0.15 (func: dtype_limits) (#2228) - Deprecate "dynamic_range" in favor of "data_range" (#2384) - The default value of the ``circle`` argument to ``radon`` and ``iradon`` transforms will be ``True`` in 0.15 (#2235) - The default value of ``multichannel`` for ``denoise_bilateral`` and ``denoise_nl_means`` will be ``False`` in 0.15 - The default value of ``block_norm`` in ``feature.hog`` will be L2-Hysteresis in 0.15. - The ``threshold_adaptive`` function is deprecated. Use ``threshold_local`` instead. - The default value of ``mode`` in ``transform.swirl``, ``resize``, and ``rescale`` will be "reflect" in 0.15. For a complete list of contributors to this release, and PRs merged, please see the online release notes: https://github.com/scikit-image/scikit-image/blob/master/doc/release/releas… Enjoy!

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Is a worked paper example appropriate for documentation?
by Edward Richards March 24, 2017

March 24, 2017

I am wondering if simple recipes for recreating paper figures are appropriate for documentation, and if so, where should they be put? I have code to recreate figure 1 from E T Y Lee's paper "Choosing nodes in parametric curve interpolation" (doi: 0010448589900031). I know very little about interpolation, but I worked this example because of the response to mathematica SE question # 10273. It seems to me like a good exploration of some of the more esoteric features of interpolation, and it spans a number of separate scipy.interpolate functions. Would adding code like this help or clutter existing documentation? As a side note I feel that I am late to the party for missing by Docathon a week. Thanks, Ned import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import splprep, splev, CubicSpline p = np.array([[0, 26, 28, 54], [0, 24, 24, 0]]) dp = np.diff(p, axis=-1) def parametic_nodes(escale): """Compute parametric knots location""" t = np.hstack((0, np.cumsum(np.linalg.norm(dp, axis=0) ** escale))) return t / np.max(t) us = np.arange(201) / 200 fig, ax = plt.subplots(2,2) ax[0, 0].plot(*splev(us, splprep(p, u=np.arange(4) / 3, s=0)[0])) ax[0, 0].plot(*splev(us, splprep(p, u=p[0, :] / 54, s=0)[0])) ax[0, 0].plot(*splev(us, splprep(p, u=parametic_nodes(1), s=0)[0])) ax[0, 1].plot(*splev(us, splprep(p, u=parametic_nodes(0), s=0)[0])) ax[0, 1].plot(*splev(us, splprep(p, u=parametic_nodes(0.5), s=0)[0])) ax[0, 1].plot(*splev(us, splprep(p, u=parametic_nodes(1), s=0)[0])) ax[1, 0].plot(*splev(us, splprep(p, u=parametic_nodes(0.35), s=0)[0])) ax[1, 0].plot(*splev(us, splprep(p, u=parametic_nodes(0.5), s=0)[0])) ax[1, 0].plot(*splev(us, splprep(p, u=parametic_nodes(0.65), s=0)[0])) ax[1, 1].plot(*CubicSpline(np.arange(4) / 3, p.T, bc_type='natural')(us).T) ax[1, 1].plot(*CubicSpline(parametic_nodes(0.5), p.T, bc_type='natural')(us).T) ax[1, 1].plot(*CubicSpline(parametic_nodes(1), p.T, bc_type='natural')(us).T) plt.show(block=False)

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Re: [SciPy-User] migration of all scipy.org
by Propadovic Nenad March 23, 2017

March 23, 2017

Hello Ralf, thanks for the answer. Where did you find that outdated link, and does it still need fixing? Our > own page on that is https://scipy.org/scipylib/mailing-lists.html, which > was updated on 15 Nov last year from the scipy-user move. > Well I'm pretty sure I had seen that link somewhere at https://scipy.org/scipylib/mailing-lists.html , all right, and that was some time end of January or beginning of February. I do not see any incongruent links there any more. I had revisited the same page maybe two weeks later, and then found that one of the last posts (maybe the last post) in the archive announced the migration. Maybe I clicked an old link google gave me from its cache? I really don't know. Two things have not changed, however. The 'Read/Search'-links (pointing to gmane) for all lists give me blank pages. Might be more an issue of gmane (?), but still confusing for an unsuspecting new user. And the archive of scipy-svn has its last entries in May 2016, which I'd probably understand if I cared to think about it. Not sure I was able to help, cheers, Nenad

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Re: [SciPy-User] migration of all scipy.org
by Propadovic Nenad March 23, 2017

March 23, 2017

Hello, I'd just like to add that it's important to point to the new lists from scipy.org as soon as possible. When I searched the scipy mailing list some two months ago, I was pointed to the one at scipy.org and found myself wondering how comes that the last message is from November last year. It took some time to realize that the last message announces the migration to the new list... Besides: "explicit is better than implicit" ... Cheers, Nenad

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migration of all scipy.org mailing lists
by Ralf Gommers March 22, 2017

March 22, 2017

Hi all, The server for the scipy.org mailing list is in very bad shape, so we (led by Didrik Pinte) are planning to complete the migration of active mailing lists to the python.org infrastructure and to decommission the lists than seem dormant/obsolete. The scipy-user mailing list was already moved to python.org a month or two ago, and that migration went smoothly. These are the lists we plan to migrate: astropy ipython-dev ipython-user numpy-discussion numpy-svn scipy-dev scipy-organizers scipy-svn And these we plan to retire: Announce APUG Ipython-tickets Mailman numpy-refactor numpy-refactor-git numpy-tickets Pyxg scipy-tickets NiPy-devel There will be a short period (<24 hours) where messages to the list may be refused, with an informative message as to why. The mailing list address will change from listname(a)scipy.org to listname(a)python.org This will happen asap, likely within a day or two. So two requests: 1. If you see any issue with this plan, please reply and keep Didrik and myself on Cc (we are not subscribed to all lists). 2. If you see this message on a numpy/scipy list, but not on another list (could be due to a moderation queue) then please forward this message again to that other list. Thanks, Ralf

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