Mailman 3 March 2018 - SciPy-Dev

Mousai 0.3- general purpose Harmonic Balance solver.
by Joseph Slater March 29, 2018

March 29, 2018

Dear colleagues, I've just pushed 0.3 of Mousai, a general purpose numerical Harmonic Balance solver to pypi. There are now two different solution methodologies, one minimizing frequency domain errors the other time domain. Test problems and contributors welcome! Best Regards- Joe https://josephcslater.github.io/mousai/

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welcome Matt and Paul to the core team
by Ralf Gommers March 29, 2018

March 29, 2018

Hi all, On behalf of the SciPy developers I'd like to welcome Matt Haberland and Paul van Mulbregt as members of the core dev team. Matt co-mentored during last years' GSoC, and is the author of the interior-point method that improved optimize.linprog - https://github.com/scipy/scipy/pulls/mdhaber. Paul has been contributing to (mainly) scipy.special for over 6 months - https://github.com/scipy/scipy/pulls/pvanmulbregt. I'm looking forward to their continued contributions! Cheers, Ralf

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Documentation / tutorial for peak finding in scipy.signal
by Lars G. March 29, 2018

March 29, 2018

Hello, recently the 3 user-facing functions `find_peaks`, `peak_prominences` and `peak_widths` were added to extend SciPy's peak finding capabilities. https://scipy.github.io/devdocs/signal.html#peak-finding During that process the idea came up to add a section on peak finding to the "Signal Processing" tutorial. https://scipy.github.io/devdocs/tutorial/signal.html I have tried a few times to come up with a first draft but each time come away with new questions. Therefore I think it might be reasonable to have a small discussion beforehand. Some issues / question I'd like addressed are: - My first impression of the existing tutorial(s) is that only the basic concepts and math are covered with maybe one example or visualizing plot. I think that's a good scope for a tutorial. However I feel that this concept doesn't translate well to the topic at hand. The concepts and math behind the 3 new functions are very simple and are already covered in the relevant docstrings. So I'm not really sure what additional non-duplicate content would be useful here. - The new functions are more like building blocks that would be part of a larger processing chain (filtering, peak finding, peak measurement & classification). My impression is that examples would be the most useful here to demonstrate the workflow but would be to code and plot heavy to fit a tutorial. - To extend on this: one thing that is very well done in Matlab is that it provides examples for the usage of each parameter. A good example is Matlab's version of `find_peaks` itself: https://de.mathworks.com/help/signal/ref/findpeaks.html?requestedDomain=true I think this would be really useful for some of the options of the new functions. E.g. the interplay between `width` and `rel_height` comes to mind. That would require multiple examples which is to much for a docstring. At least that is my impression. - To demonstrate peak finding I would need a signal to analyze. I'm not sure how to generate complex demo-signals in only a few lines of code that don't shift the focus of the reader. The best I could come up with can be seen in `find_peaks` docstring. How is this usually handled? Would it be okay to import this stuff from `misc`? - Should this tutorial cover peak finding with wavelet transformation as well? Reading the roadmap it seems like it's not decided whether wavelet transformation is within the scope of SciPy. So I'd think this topic should be left out until this is decided. Sorry, for the wordy message and I'm in no way an expert in this topic so please take this with a grain of salt. ;) Best regards, Lars

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Thoughts on creating a toolbox for analysis of nonlinear dynamical system analysis
by Sayantan Majumdar March 26, 2018

March 26, 2018

I work with Nonlinear Dynamical Systems and there are no good toolboxes that provide fast and stable tools for the analysis of such systems. there were a lot of good toolboxes in the 80's( I heard ) and there are some packages where those algorithms have been re-implemented and sometimes used, like the PyDSTool package.But its too slow and everything is not stable in it plus some important tools are not there. This can be a good thing to start in this gsoc right? -S

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Re: [SciPy-Dev] Thoughts on creating a toolbox for analysis of nonlinear dynamical system analysis
by Robert Lucente March 26, 2018

March 26, 2018

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how to multiply an instance of ndarray and an object?
by Phillip Feldman March 25, 2018

March 25, 2018

I have a class called `Signal` that handles multiplication by an array on the right by overloading `__mul__`. I tried to implement multiplication by an array on the left by overloading `__rmul__`, but wasn't able to make this work because NumPy thinks that it knows how to handle this, so my `__rmul__` method (below) is never called. The result is an array having dtype `object`. Is there a practical way to modify NumPy to solve this problem Phillip def __rmul__(self, c): S= self.copy() S.phasors*= c return S

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GSOC'18 : Enhance the Randomized Numerical Linear Algebra functionality
by Chaman Agrawal March 25, 2018

March 25, 2018

Hello everyone, Goal of the mail : To understand better about the current status about the project and suggestions/resources to speed up my research for it. I am a second year undergraduate at Indian Institute of Technology Kanpur,India highly interested in Linear Algebra ,Probability Theory and Statistics and algorithms in general. Before sending this I went through the emails archive to avoid asking any redundant question but I was not able to get discussion about this project. Is this project not open or there are already some strong candidates whose discussions I was not able to find? I wanted to ask for a more detailed description about the project compared to what is there in the Ideas page. I had a few doubts like by both Clarkson Woodruff transformation and Johnson–Lindenstrauss lemma we get benefit of dimension reduction so will this project be more focused on dimension reduction techniques or other randomized techniques like subsampled Hadamard Transform Matrix <https://arxiv.org/pdf/1204.0062.pdf> etc. Also if there is a list of desired algorithms to be implemented it would be a great speed booster. Thank you, Chaman Agrawal Indian Institute of Technology Kanpur,India

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ANN: SciPy 1.0.1 released
by Ralf Gommers March 25, 2018

March 25, 2018

On behalf of the SciPy development team I am pleased to announce the availability of Scipy 1.0.1. This is a maintenance release, no new features with respect to 1.0.0. See the release notes below for details. Wheels and sources can be found on PyPI (https://pypi.python.org/pypi/scipy) and on Github (https://github.com/scipy/scipy/releases/tag/v1.0.1). The conda-forge channel will be up to date within a couple of hours. Thanks to everyone who contributed to this release! Cheers, Ralf SciPy 1.0.1 Release Notes ==================== SciPy 1.0.1 is a bug-fix release with no new features compared to 1.0.0. Probably the most important change is a fix for an incompatibility between SciPy 1.0.0 and ``numpy.f2py`` in the NumPy master branch. Authors ======= * Saurabh Agarwal + * Alessandro Pietro Bardelli * Philip DeBoer * Ralf Gommers * Matt Haberland * Eric Larson * Denis Laxalde * Mihai Capotă + * Andrew Nelson * Oleksandr Pavlyk * Ilhan Polat * Anant Prakash + * Pauli Virtanen * Warren Weckesser * @xoviat * Ted Ying + A total of 16 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 1.0.1 ----------------------- - `#7493 <https://github.com/scipy/scipy/issues/7493>`__: `ndimage.morphology` functions are broken with numpy 1.13.0 - `#8118 <https://github.com/scipy/scipy/issues/8118>`__: minimize_cobyla broken if `disp=True` passed - `#8142 <https://github.com/scipy/scipy/issues/8142>`__: scipy-v1.0.0 pdist with metric=`minkowski` raises `ValueError:... - `#8173 <https://github.com/scipy/scipy/issues/8173>`__: `scipy.stats.ortho_group` produces all negative determinants... - `#8207 <https://github.com/scipy/scipy/issues/8207>`__: gaussian_filter seg faults on float16 numpy arrays - `#8234 <https://github.com/scipy/scipy/issues/8234>`__: `scipy.optimize.linprog` `interior-point` presolve bug with trivial... - `#8243 <https://github.com/scipy/scipy/issues/8243>`__: Make csgraph importable again via `from scipy.sparse import*` - `#8320 <https://github.com/scipy/scipy/issues/8320>`__: scipy.root segfaults with optimizer 'lm' Pull requests for 1.0.1 ----------------------- - `#8068 <https://github.com/scipy/scipy/pull/8068>`__: BUG: fix numpy deprecation test failures - `#8082 <https://github.com/scipy/scipy/pull/8082>`__: BUG: fix solve_lyapunov import - `#8144 <https://github.com/scipy/scipy/pull/8144>`__: MRG: Fix for cobyla - `#8150 <https://github.com/scipy/scipy/pull/8150>`__: MAINT: resolve UPDATEIFCOPY deprecation errors - `#8156 <https://github.com/scipy/scipy/pull/8156>`__: BUG: missing check on minkowski w kwarg - `#8187 <https://github.com/scipy/scipy/pull/8187>`__: BUG: Sign of elements in random orthogonal 2D matrices in "ortho_group_gen"... - `#8197 <https://github.com/scipy/scipy/pull/8197>`__: CI: uninstall oclint - `#8215 <https://github.com/scipy/scipy/pull/8215>`__: Fixes Numpy datatype compatibility issues - `#8237 <https://github.com/scipy/scipy/pull/8237>`__: BUG: optimize: fix bug when variables fixed by bounds are inconsistent... - `#8248 <https://github.com/scipy/scipy/pull/8248>`__: BUG: declare "gfk" variable before call of terminate() in newton-cg - `#8280 <https://github.com/scipy/scipy/pull/8280>`__: REV: reintroduce csgraph import in scipy.sparse - `#8322 <https://github.com/scipy/scipy/pull/8322>`__: MAINT: prevent scipy.optimize.root segfault closes #8320 - `#8334 <https://github.com/scipy/scipy/pull/8334>`__: TST: stats: don't use exact equality check for hdmedian test - `#8477 <https://github.com/scipy/scipy/pull/8477>`__: BUG: signal/signaltools: fix wrong refcounting in PyArray_OrderFilterND - `#8530 <https://github.com/scipy/scipy/pull/8530>`__: BUG: linalg: Fixed typo in flapack.pyf.src. - `#8566 <https://github.com/scipy/scipy/pull/8566>`__: CI: Temporarily pin Cython version to 0.27.3 - `#8573 <https://github.com/scipy/scipy/pull/8573>`__: Backports for 1.0.1 - `#8581 <https://github.com/scipy/scipy/pull/8581>`__: Fix Cython 0.28 build break of qhull.pyx

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Feedback to students applying to Rotation Formalism in 3D GSoC project
by Nikolay Mayorov March 24, 2018

March 24, 2018

I decided to give feedback to all the students in one letter. My feedback is proportional to the level of thoroughness of a proposal and I focus on the weakest points. There are strong points as well and we value them, however I don't mention them here (sorry). To Vishal Gupta https://docs.google.com/document/d/1y5OalGAvYkk8UvLtFjQ2-xhRj_NTwq0fV3GvlCB… 1. Quaternion section description is weird. What's this about "Method would accept a 3x1 Axis unit vector and theta which will be used to generate a 4x1 Quaternion (real, i, j ,k). Also add a method to return a 3x3 Rotation Matrix."? 2. I think it's better to dedicate a separate API section rather than putting it into milestones. 3. When you put API section, try to make it more detailed. Discuss fine points and conventions. 4. Add references. To Aditya Bharti https://docs.google.com/document/d/1UriyLABwgjUcYfBofSr4hqAnLzblJ71pkzm7i26… 1. I think that returning Euler angles corresponding to the fixed sequence is not satisfactory. So researching on how to implement that is valuable. I personally don't know much about working with extrinsic rotations, from my experience they are not used that often. Implementing conversion to arbitrary intrinsic rotations (A-B-A or A-B-C) is certainly doable, but challenging. 2. What other important operation similar to composition (in some sense) you can think of. 3. apply method is not discussed enough. Leave the details to figure out to you. 4. slerp, random_sample and Wahba are all inconsiderate. Give a real thought about these algorithms and their APIs. 5. Quaternion class is also inconsiderate. Give a real thought or explanation why you believe is necessary. For example, if you think that quaternion is a superior representation why not to use it in Rotation. 6. I think that you can at least mention other possible algorithms (like if "I have time"). I still believe that "Quaternion spline" is a great algorithm, which will be good to introduce. To Samyak Jain https://docs.google.com/document/d/12cP0LTFa0H3aQqJfb1WAmr5A_KU6bN3qZ17LbKd… 1. It's good that you honestly mentioned your planned vacation, however it certainly doesn't add you any points. I don't know what to advice you here. 2. It's good that you added theoretical descriptions, but they are not quite right at all points. Probably not the most important thing at the moment. 3. API design seems inconsistent and strange. You first mention Rotation class, but then introduce standalone function (looks like) which return 4-tuple "quaternions". It doesn't look very well thought-out. 4. References to MATLAB are not evil by itself, but you should explain what you want from them. It is not an available implementation you can use as a code source. To Anubhav Patel https://docs.google.com/document/d/1ylzugkvVYI7m3IXsWVLD4EkE6zQd8B9YDPKtTno… 1. Fixing the sequence of Euler angles is TOO restrictive, we can't do that. It is applicable to both "from" and "to" conversions. 2. I don't necessary see the benefits of having two possible ways to initialize the class: from __init__ and from "factory methods". Can we do it better? It's not a critical point for sure. 3. In setfrommatrix --- there is a reference listed in your proposal, where a robust and insensitive to non-orthogonality algorithm is proposed, can you spot it and suggest for this? 4. See hint 2 for Aditya Bharti. 5. I feel that rotate discussion is not detailed enough. What exactly Rotation.rotate(v) does? Is there only one way to apply "rotation"? 6. APIs for slerp, qspline and davenportq are not great. Think about how to improve them. 7. In your Timeline: you goes too much in internals of implementing qspline. It is good in one sense, however you should use understandable descriptions, not "_rates", "_slew", etc.. You are not rewriting the code, you implementing the algorithm from scratch. To Sudheer Achary https://docs.google.com/document/d/13U4feVYTJJfGFgSHA37p_JxpexBKZJ2-VSjs4z7… 1. Why __init__ accepts Euler angles? 2. What is the reasoning behind introducing rotate_... and other similar methods? These are some static methods. Wouldn't it be more logical that Rotation itself rotates vectors? 3. I don't see a way to compose rotations. 4. I don't how to put it politely, but overall I don't get your API design. It makes some sense, but it just seems really inconvenient and verbose and hard to grasp. What didn't you like about Rotation being some abstraction that can rotate vectors, be composed with other Rotation and converted from/to common representations? 5. Maybe it would be better if you write method signatures appropriately and not just (). -------------------------- OK, that's it. All proposals and my comments are opened for everybody, so you can learn from them freely. Apologies if I wasn't very attentive to some details, there are many proposals. If any of the students want to ask or say something, I suggest to use this mail thread. Best regards, Nikolay Mayorov

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Fast Walsh–Hadamard transform for SciPy ?
by Chaman Agrawal March 24, 2018

March 24, 2018

Issue #8590 https://github.com/scipy/scipy/issues/8590 Currently there is no implementation of Fast Walsh–Hadamard transform in SciPy. Although it seems that FWHT is not as general as FFT but it is pretty ubiquitous ,it is there is other maths and science softwares like MATLAB etc. .I would like to contribute towards it. Following are the details about it. Fast Walsh–Hadamard transform Hadamard transform is an example of a generalized class of Fourier transforms. It performs an orthogonal, symmetric, involutive, linear operation on 2^(m) numbers. It is equivalent to a multidimensional DFT. Time Complexity: O(nlogn) with Fast Walsh-Hadamard transform (FWHT) Comparison with FFT: FWHT is very useful for reducing bandwidth storage requirements and spread-spectrum analysis. Compared to the FFT, the FWHT requires less storage space and is faster to calculate because it uses only real additions and subtractions, while the FFT requires complex values. The FWHT is able to represent signals with sharp discontinuities more accurately using fewer coefficients than the FFT. Some Usage examples: The Hadamard transform is used in data encryption, as well as many signal processing and data compression algorithms, such as JPEG XR and MPEG-4 AVC. It is also a crucial part of Grover's algorithm and Shor's algorithm in quantum computing. The Hadamard transform is also applied in scientific methods such as NMR, mass spectroscopy and crystallography.

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