Mailman 3 October 2019 - 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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Discretisation of continuous state space model almost 20 times slower than manual code
by Jonas Bülow Oct. 28, 2019

Oct. 28, 2019

Hi, I'm new to scipy. I implemented a simple state space model where the A and B matrix is specified and C and D is zero. Before I knew about scipy.signal.StateSpace I manually discretised the model using scipy.integrate.quad as shown in the code below. Someone suggested I should use scipy.signal.StateSpace. The code become a lot slower using signal.StateSpace, almost 20 times slower. Any hints on what I'm doing wrong or how I should change my use of signal.StateSpace to get better performance? Or should I just stick to my simplified manual method (variant 1 on the code below)? The code: ----8<-------- import math import numpy as np from scipy import integrate, signal import timeit as ti def cont2disc_1(A, B, sample_time): Ad = math.exp(A * sample_time) def fq(x): return integrate.quad(lambda t: math.exp(A * t) * B[x], 0, sample_time)[0] Bd = np.array([fq(0), fq(1)]) return Ad, Bd def cont2disc_2(A, B, sample_time): ds = signal.StateSpace(A, B, 0, [0, 0]).to_discrete(sample_time) Ad = ds.A[0][0] Bd = ds.B[0] return Ad, Bd if __name__ == "__main__": A,B,h = -0.0004622051395583765, [0.00046221, 0.01629134], 60 print(f'1: {cont2disc_1(A, B, h)}') print(f'2: {cont2disc_2(A, B, h)}') SETUP=f''' from __main__ import cont2disc_1, cont2disc_2 A,B,h = {A}, {B}, {h} ''' t_1 = ti.timeit('cont2disc_1(A, B, h)', SETUP, number=1000) t_2 = ti.timeit('cont2disc_2(A, B, h)', SETUP, number=1000) print(f'Method 1 is {t_2 / t_1} times faster then method 2') ----8<--------

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[ANN] SciPy India 2019
by Prabhu Ramachandran Oct. 20, 2019

Oct. 20, 2019

Hello, [Apologies for the cross-posting!] We are pleased to announce the SciPy India conference 2019. SciPy India is an annual conference on using Python for research and education. The conference is currently in its eleventh year and will be held at IIT Bombay on 29 & 30 November, 2019. The registration and call for papers are open. Please visit http://scipy.in to register and submit your proposals. Please spread the word! Call for Papers ============= We look forward to your submissions on the use of Python for scientific computing and education. This includes development of tools for pedagogy, exploration, modeling, and analysis. We welcome contributions from academia as well as industry. For details on the paper submission please see here: http://scipy.in/ Important Dates ================ - Call for proposals end: 25th October 2019 - List of accepted proposals will be announced: 3rd November. We look forward to seeing you at SciPy India. Regards, Prabhu Ramachandran (For the SciPy organizing team)

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NumPy 1.17 3 released
by Charles R Harris Oct. 17, 2019

Oct. 17, 2019

Hi All, On behalf of the NumPy team I am pleased to announce that NumPy 1.17.3 has been released. This is a bugfix release. The Python versions supported in this release are 3.5-3.8. Downstream developers should use Cython >= 0.29.13 for Python 3.8 support and OpenBLAS >= 3.7 to avoid wrong results on the Skylake architecture. The NumP Wheels for this release can be downloaded from PyPI <https://pypi.org/project/numpy/1.17.3/>, source archives and release notes are available from Github <https://github.com/numpy/numpy/releases/tag/v1.17.3>. *Highlights* - Wheels for Python 3.8 - Boolean matmul fixed to use booleans instead of integers. *Compatibility notes* - The seldom used PyArray_DescrCheck macro has been changed/fixed. *Contributors* A total of 7 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - Allan Haldane - Charles Harris - Kevin Sheppard - Matti Picus - Ralf Gommers - Sebastian Berg - Warren Weckesser *Pull requests merged* A total of 12 pull requests were merged for this release. - gh-14456: MAINT: clean up pocketfft modules inside numpy.fft namespace. - gh-14463: BUG: random.hypergeometic assumes npy_long is npy_int64, hung... - gh-14502: BUG: random: Revert gh-14458 and refix gh-14557. - gh-14504: BUG: add a specialized loop for boolean matmul. - gh-14506: MAINT: Update pytest version for Python 3.8 - gh-14512: DOC: random: fix doc linking, was referencing private submodules. - gh-14513: BUG,MAINT: Some fixes and minor cleanup based on clang analysis - gh-14515: BUG: Fix randint when range is 2**32 - gh-14519: MAINT: remove the entropy c-extension module - gh-14563: DOC: remove note about Pocketfft license file (non-existing here). - gh-14578: BUG: random: Create a legacy implementation of random.binomial. - gh-14687: BUG: properly define PyArray_DescrCheck Cheers, Charles Harris

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Why do SciPy stats return very small but very high precision numbers?
by Vicki Brown Oct. 16, 2019

Oct. 16, 2019

Sometimes, I see results like this: LeveneResult(statistic=1233.9270599281986, pvalue=6.212186164025708e-269) Is it even realistic to claim a value that is this small? (6.212 e-269)? Other times, a function just returns 0.0. Can someone point me to an explanation of how and why the functions decide o return 0 ("fer sure") vs "almost but not exactly 0, but close enough") -- Vicki Vicki Brown cfcl.com/vlb

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Announcement -- scikit-image 0.16." released
by Nelle Varoquaux Oct. 14, 2019

Oct. 14, 2019

Hi All, On behalf of the scikit-image team I am pleased to announce that scikit-image 0.16.1 has been released (0.16.0 was never released due to necessary last minute fixes). This release contains many bugs fixes and new features! Please note that we have dropped support for Python 3.5. Announcement: scikit-image 0.16.1 ================================= We're happy to announce the release of scikit-image v0.16.1! 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: https://scikit-image.org Starting from this release, scikit-image will follow the recently introduced NumPy deprecation policy, `NEP 29 < https://github.com/numpy/numpy/blob/master/doc/neps/nep-0029-deprecation_po… >__`. Accordingly, scikit-image 0.16 drops support for Python 3.5. This release of scikit-image officially supports Python 3.6 and 3.7. Special thanks to Matthias Bussonnier for `Frappuccino <https://github.com/Carreau/frappuccino>`__, which helped us catch all API changes and nail down the APIs for new features. New Features ------------ - New `skimage.evaluate` module containing simple metrics (mse, nrme, psd) and segmentation metrics (adapted rand error, variation of information) (#4025) - n-dimensional TV-L1 optical flow algorithm for registration -- `skimage.registration.optical_flow_tvl1` (#3983) - Draw a line in an n-dimensional array -- `skimage.draw.line_nd` (#2043) - 2D Farid & Simoncelli edge filters - `skimage.filters.farid`, `skimage.filters.farid_h`, and `skimage.filters.farid_v` (#3775) - 2D majority voting filter assigning to each pixel the most commonly occurring value within its neighborhood -- `skimage.filters.majority` (#3836, #3839) - Multi-level threshold "multi-Otsu" method, a thresholding algorithm used to separate the pixels of an input image into several classes by maximizing the variances between classes -- `skimage.filters.threshold_multiotsu` (#3872, #4174) - New example data -- `skimage.data.shepp_logan_phantom`, `skimage.data.colorwheel`, `skimage.data.brick`, `skimage.data.grass`, `skimage.data.roughwall`, `skimage.data.cell` (#3958, #3966) - Compute and format image region properties as a table -- `skimage.measure.regionprops_table` (#3959) - Convert a polygon into a mask -- `skimage.draw.poly2mask` (#3971, #3977) - Visual image comparison helper `skimage.util.compare_images`, that returns an image showing the difference between two input images (#4089) - `skimage.transform.warp_polar` to remap image into polar or log-polar coordinates. (#4097) Improvements ------------ - RANSAC: new option to set initial samples selected for initialization (#2992) - Better repr and str for `skimage.transform.ProjectiveTransform` (#3525, #3967) - Better error messages and data type stability to `skimage.segmentation.relabel_sequential` (#3740) - Improved compatibility with dask arrays in some image thresholding methods (#3823) - `skimage.io.ImageCollection` can now receive lists of patterns (#3928) - Speed up `skimage.feature.peak_local_max` (#3984) - Better error message when incorrect value for keyword argument `kind` in `skimage.color.label2rgb` (#4055) - All functions from `skimage.drawing` now supports multi-channel 2D images (#4134) API Changes ----------- - Deprecated subpackage ``skimage.novice`` has been removed. - Default value of ``multichannel`` parameters has been set to False in `skimage.transform.rescale`, `skimage.transform.pyramid_reduce`, `skimage.transform.pyramid_laplacian`, `skimage.transform.pyramid_gaussian`, and `skimage.transform.pyramid_expand`. Guessing is no longer performed for 3D arrays. - Deprecated argument ``visualise`` has been removed from `skimage.feature.hog`. Use ``visualize`` instead.¨ - `skimage.transform.seam_carve` has been completely removed from the library due to licensing restrictions. - Parameter ``as_grey`` has been removed from `skimage.data.load` and `skimage.io.imread`. Use ``as_gray`` instead. - Parameter ``min_size`` has been removed from `skimage.morphology.remove_small_holes`. Use ``area_threshold`` instead. - Deprecated ``correct_mesh_orientation`` in `skimage.measure` has been removed. - `skimage.measure._regionprops` has been completely switched to using row-column coordinates. Old x-y interface is not longer available. - Default value of ``behavior`` parameter has been set to ``ndimage`` in `skimage.filters.median`. - Parameter ``flatten`` in `skimage.io.imread` has been removed in favor of ``as_gray``. - Parameters ``Hxx, Hxy, Hyy`` have been removed from `skimage.feature.corner.hessian_matrix_eigvals` in favor of ``H_elems``. - Default value of ``order`` parameter has been set to ``rc`` in `skimage.feature.hessian_matrix`. - ``skimage.util.img_as_*`` functions no longer raise precision and/or loss warnings. Bugfixes -------- - Corrected error with scales attribute in ORB.detect_and_extract (#2835) The scales attribute wasn't taking into account the mask, and thus was using an incorrect array size. - Correct for bias in Inverse Randon Transform (`skimage.transform.irandon`) (#3067) Fixed by using the Ramp filter equation in the spatial domain as described in the reference - Fix a rounding issue that caused a rotated image to have a different size than the input (`skimage.transform.rotate`) (#3173) - RANSAC uses random subsets of the original data and not bootstraps. (#3901, #3915) - Canny now produces the same output regardless of dtype (#3919) - Geometry Transforms: avoid division by zero & some degenerate cases (#3926) - Fixed float32 support in denoise_bilateral and denoise_tv_bregman (#3936) - Fixed computation of Meijering filter and avoid ZeroDivisionError (#3957) - Fixed `skimage.filters.threshold_li` to prevent being stuck on stationnary points, and thus at local minima or maxima (#3966) - Edited `skimage.exposure.rescale_intensity` to return input image instead of nans when all 0 (#4015) - Fixed `skimage.morphology.medial_axis`. A wrong indentation in Cython caused the function to not behave as intended. (#4060) - Fixed `skimage.restoration.denoise_bilateral` by correcting the padding in the gaussian filter(#4080) - Fixed `skimage.measure.find_contours` when input image contains NaN. Contours interesting NaN will be left open (#4150) - Fixed `skimage.feature.blob_log` and `skimage.feature.blob_dog` for 3D images and anisotropic data (#4162) - Fixed `skimage.exposure.adjust_gamma`, `skimage.exposure.adjust_log`, and `skimage.exposure.adjust_sigmoid` such that when provided with a 1 by 1 ndarray, it returns 1 by 1 ndarrays and not single number floats (#4169) Deprecations ------------ - Parameter ``neighbors`` in `skimage.measure.convex_hull_object` has been deprecated in favor of ``connectivity`` and will be removed in version 0.18.0. - The following functions are deprecated in favor of the `skimage.metrics` module (#4025): - `skimage.measure.compare_mse` - `skimage.measure.compare_nrmse` - `skimage.measure.compare_psnr` - `skimage.measure.compare_ssim` - The function `skimage.color.guess_spatial_dimensions` is deprecated and will be removed in 0.18 (#4031) - The argument ``bc`` in `skimage.segmentation.active_contour` is deprecated. - The function `skimage.data.load` is deprecated and will be removed in 0.18 (#4061) - The function `skimage.transform.match_histogram` is deprecated in favor of `skimage.exposure.match_histogram` (#4107) - The parameter ``neighbors`` of `skimage.morphology.convex_hull_object` is deprecated. - The `skimage.transform.randon_tranform` function will convert input image of integer type to float by default in 0.18. To preserve current behaviour, set the new argument ``preserve_range`` to True. (#4131) Documentation improvements -------------------------- - DOC: Improve the documentation of transform.resize with respect to the anti_aliasing_sigma parameter (#3911) - Fix URL for stain deconvolution reference (#3862) - Fix doc for denoise guassian (#3869) - DOC: various enhancements (cross links, gallery, ref...), mainly for corner detection (#3996) - [DOC] clarify that the inertia_tensor may be nD in documentation (#4013) - [DOC] How to test and write benchmarks (#4016) - Spellcheck @CONTRIBUTING.txt (#4008) - Spellcheck @doc/examples/segmentation/plot_watershed.py (#4009) - Spellcheck @doc/examples/segmentation/plot_thresholding.py (#4010) - Spellcheck @skimage/morphology/binary.py (#4011) - Spellcheck @skimage/morphology/extrema.py (#4012) - docs update for downscale_local_mean and N-dimensional images (#4079) - Remove fancy language from 0.15 release notes (#3827) - Documentation formatting / compilation fixes (#3838) - Remove duplicated section in INSTALL.txt. (#3876) - ENH: doc of ridge functions (#3933) - Fix docstring for Threshold Niblack (#3917) - adding docs to circle_perimeter_aa (#4155) - Update link to NumPy docstring standard in Contribution Guide (replaces #4191) (#4192) - DOC: Improve downscale_local_mean() docstring (#4180) - DOC: enhance the result display in ransac gallery example (#4109) - Gallery: use fstrings for better readability (#4110) - MNT: Document stacklevel parameter in contribution guide (#4066) - Fix minor typo (#3988) - MIN: docstring improvements in canny functions (#3920) - Minor docstring fixes for #4150 (#4184) - Fix `full` parameter description in compare_ssim (#3860) - State Bradley threshold equivalence in Niblack docstring (#3891) - Add plt.show() to example-code for consistency. (#3908) - CC0 is not equivalent to public domain. Fix the note of the horse image (#3931) - Update the joblib link in tutorial_parallelization.rst (#3943) - Fix plot_edge_filter.py references (#3946) - Add missing argument to docstring of PaintTool (#3970) - Improving documentation and tests for directional filters (#3956) - Added new thorough examples on the inner working of ``skimage.filters.threshold_li`` (#3966) - matplotlib: remove interpolation=nearest, none in our examples (#4002) - fix URL encoding for wikipedia references in filters.rank.entropy and filters.rank.shannon_entropy docstring (#4007) - Fixup integer division in examples (#4032) - Update the links the installation guide (#4118) - Gallery hough line transform (#4124) - Cross-linking between function documentation should now be much improved! (#4188) - Better documentation of the ``num_peaks`` of `skimage.feature.corner_peaks` (#4195) Other Pull Requests ------------------- - Add benchmark suite for exposure module (#3312) - Remove precision and sign loss warnings from ``skimage.util.img_as_`` (#3575) - Propose SKIPs and add mission/vision/values, governance (#3585) - Use user-installed tifffile if available (#3650) - Simplify benchmarks pinnings (#3711) - Add project_urls to setup for PyPI and other services (#3834) - Address deprecations for 0.16 release (#3841) - Followup deprecations for 0.16 (#3851) - Build and test the docs in Azure (#3873) - Pin numpydoc to pre-0.8 to fix dev docs formatting (#3893) - Change all HTTP links to HTTPS (#3896) - Skip extra deps on OSX (#3898) - Add location for Sphinx 2.0.1 search results; clean up templates (#3899) - Fix CSS styling of Sphinx 2.0.1 + numpydoc 0.9 rendered docs (#3900) - Travis CI: The sudo: tag is deprcated in Travis (#4164) - MNT Preparing the 0.16 release (#4204) - FIX generate_release_note when contributor_set contains None (#4205) - Specify that travis should use Ubuntu xenial (14.04) not trusty (16.04) (#4082) - MNT: set stack level accordingly in lab2xyz (#4067) - MNT: fixup stack level for filters ridges (#4068) - MNT: remove unused import `deprecated` from filters.thresholding (#4069) - MNT: Set stacklevel correctly in io matplotlib plugin (#4070) - MNT: set stacklevel accordingly in felzenszwalb_cython (#4071) - MNT: Set stacklevel accordingly in img_as_* (convert) (#4072) - MNT: set stacklevel accordingly in util.shape (#4073) - MNT: remove extreneous matplotlib warning (#4074) - Suppress warnings in tests for viewer (#4017) - Suppress warnings in test suite regarding measure.label (#4018) - Suppress warnings in test_rank due to type conversion (#4019) - Add todo item for imread plugin testing (#3907) - Remove matplotlib agg warning when using the sphinx gallery. (#3897) - Forward-port release notes for 0.14.4 (#4137) - Add tests for pathological arrays in threshold_li (#4143) - setup.py: Fail gracefully when NumPy is not installed (#4181) - Drop Python 3.5 support (#4102) - Force imageio reader to return NumPy arrays (#3837) - Fixing connecting to GitHub with SSH info. (#3875) - Small fix to an error message of `skimage.measure.regionprops` (#3884) - Unify skeletonize and skeletonize 3D APIs (#3904) - Add location for Sphinx 2.0.1 search results; clean up templates (#3910) - Pin numpy version forward (#3925) - Replacing pyfits with Astropy to read FITS (#3930) - Add warning for future dtype kwarg removal (#3932) - MAINT: cleanup regionprop add PYTHONOPTIMIZE=2 to travis array (#3934) - Adding complexity and new tests for filters.threshold_multiotsu (#3935) - Fixup dtype kwarg warning in certain image plugins (#3948) - don't cast integer to float before using it as integer in numpy logspace (#3949) - avoid low contrast image save in a doctest. (#3953) - MAINT: Remove unused _convert_input from filters._gaussian (#4001) - Set minimum version for imread so that it compiles from source on linux in test builds (#3960) - Cleanup plugin utilization in data.load and testsuite (#3961) - Select minimum imageio such that it is compatible with pathlib (#3969) - Remove pytest-faulthandler from test dependencies (#3987) - Fix tifffile and __array_function__ failures in our CI (#3992) - MAINT: Do not use assert in code, raise an exception instead. (#4006) - Enable packagers to disable failures on warnings. (#4021) - Fix numpy 117 rc and dask in thresholding filters (#4022) - silence r,c warnings when property does not depend on r,c (#4027) - remove warning filter, fix doc wrt r,c (#4028) - Import Iterable from collections.abc (#4033) - Import Iterable from collections.abc in vendored tifffile code (#4034) - Correction of typos after #4025 (#4036) - Rename internal function called assert_* -> check_* (#4037) - Improve import time (#4039) - Remove .meeseeksdev.yml (#4045) - Fix mpl deprecation on grid() (#4049) - Fix gallery after deprecation from #4025 (#4050) - fix mpl future deprecation normed -> density (#4053) - Add shape= to circle perimeter in hough_circle example (#4047) - Critical: address internal warnings in test suite related to metrics 4025 (#4063) - Use functools instead of a real function for the internal warn function (#4062) - Test rank capture warnings in threadsafe manner (#4064) - Make use of FFTs more consistent across the library (#4084) - Fixup region props test (#4099) - Turn single backquotes to double backquotes in filters (#4127) - Refactor radon transform module (#4136) - Fix broken import of rgb2gray in benchmark suite (#4176) - Fix doc building issues with SKIPs (#4182) - Remove several __future__ imports (#4198) - Restore deprecated coordinates arg to regionprops (#4144) - Refactor/optimize threshold_multiotsu (#4167) - Remove Python2-specific code (#4170) - `view_as_windows` incorrectly assumes that a contiguous array is needed (#4171) - Handle case in which NamedTemporaryFile fails (#4172) - Fix incorrect resolution date on SKIP1 (#4183) - API updates before 0.16 (#4187) - Fix conversion to float32 dtype (#4193) Contributors to this release ---------------------------- - Abhishek Arya - Alexandre de Siqueira - Alexis Mignon - Anthony Carapetis - Bastian Eichenberger - Bharat Raghunathan - Christian Clauss - Clement Ng - David Breuer - David Haberthür - Dominik Kutra - Dominik Straub - Egor Panfilov - Emmanuelle Gouillart - Etienne Landuré - François Boulogne - Genevieve Buckley - Gregory R. Lee - Hadrien Mary - Hamdi Sahloul - Holly Gibbs - Huang-Wei Chang - i3v (i3v) - Jarrod Millman - Jirka Borovec - Johan Jeppsson - Johannes Schönberger - Jon Crall - Josh Warner - Juan Nunez-Iglesias - Kaligule (Kaligule) - kczimm (kczimm) - Lars Grueter - Shachar Ben Harim - Luis F. de Figueiredo - Mark Harfouche - Mars Huang - Dave Mellert - Nelle Varoquaux - Ollin Boer Bohan - Patrick J Zager - Riadh Fezzani - Ryan Avery - Srinath Kailasa - Stefan van der Walt - Stuart Berg - Uwe Schmidt Reviewers for this release -------------------------- - Alexandre de Siqueira - Anthony Carapetis - Bastian Eichenberger - Clement Ng - David Breuer - Egor Panfilov - Emmanuelle Gouillart - Etienne Landuré - François Boulogne - Genevieve Buckley - Gregory R. Lee - Hadrien Mary - Hamdi Sahloul - Holly Gibbs - Jarrod Millman - Jirka Borovec - Johan Jeppsson - Johannes Schönberger - Jon Crall - Josh Warner - jrmarsha - Juan Nunez-Iglesias - kczimm - Lars Grueter - leGIT-bot - Mark Harfouche - Mars Huang - Dave Mellert - Paul Müller - Phil Starkey - Ralf Gommers - Riadh Fezzani - Ryan Avery - Sebastian Berg - Stefan van der Walt - Uwe Schmidt

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SciPy user documentation survey - please participate
by Ralf Gommers Oct. 12, 2019

Oct. 12, 2019

Hi everyone, Maja, our technical writer for Season of Docs for SciPy, created a survey specifically about how users use the SciPy docs and what they would like to see improved. She sent out the link to scipy-dev before and it was shared on Twitter. We've received some really valuable responses, and would love to get more. If you're a SciPy user, this is a very easy way to help the project! https://docs.google.com/forms/d/e/1FAIpQLSeBAO0UFKDZyKpg2XzRslsLJVHU61ugjc1… Apologies for the cross-post. We do a survey about once a decade and Maja is putting in a lot of work creating and analyzing the survey, so it's worth some more exposure and a couple of minutes of your time! Cheers, Ralf

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request for a volunteer with devops/sysadmin skills, SciPy conda-forge
by Ralf Gommers Oct. 3, 2019

Oct. 3, 2019

Hi all, We have never had a working Windows build on conda-forge for SciPy. This is a bit painful, since it means that pretty much all SciPy/PyData users on Windows can't go "all conda-forge", and mixing the defaults and conda-forge channels is fairly fragile. The solution is now a lot closer, since rather than a Fortran compiler project it's now a devops project: Intel provided permission and a license to use the Intel Fortran compiler, which is the best way to build SciPy on Windows. So "all" that's needed is set that up on a VM somewhere and connect it to conda-forge. This is still nontrivial, it requires some good devops skills. Marius van Niekerk, one of the conda-forge core team members, provided details on status and next steps at https://github.com/conda-forge/scipy-feedstock/issues/80. He could really use a hand. If there's anyone here with the interest and skills to help out here, this would be a really high-impact contribution! Cheers, Ralf

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