Mailman 3 March 2022 - 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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ANN: SfePy 2022.1
by Robert Cimrman April 12, 2022

April 12, 2022

I am pleased to announce the release of SfePy 2022.1. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by finite element methods. It is distributed under the new BSD license. Home page: https://sfepy.org Mailing list: https://mail.python.org/mm3/mailman3/lists/sfepy.python.org/ Git (source) repository, issue tracker: https://github.com/sfepy/sfepy Highlights of this release -------------------------- - new handling of state variables data and State class removal - many new sensitivity analysis terms based on multi-linear term implementation For full release notes see [1]. Cheers, Robert Cimrman [1] http://docs.sfepy.org/doc/release_notes.html#id1 --- Contributors to this release in alphabetical order: Robert Cimrman Robert T. McGibbon Vladimir Lukes

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Best practices regarding partial import of hand-selected functions into global namespace
by battaglia01＠gmail.com March 22, 2022

March 22, 2022

Hi all, I have a question regarding best practices for imports when using scipy. I understand that doing things like `from numpy import *` is discouraged and that it is best to keep the global namespace clean. On the other hand, it can also be useful to hand-select some functions from numpy or scipy and import them into the global namespace. Virtually all of the scipy examples use this code style. For instance from https://docs.scipy.org/doc/scipy/reference/sparse.html (combining some things for brevity): ``` from scipy.sparse import csr_matrix from scipy.sparse import lil_matrix from scipy.sparse.linalg import spsolve from numpy.linalg import solve, norm ... ``` etc. Is this considered acceptable practice, then, as long as you aren't shadowing built-ins and the like? I ask because for any reasonable program you will of course never just use three or four functions, but as you keep developing will quickly get to 20-30 or 50 or more. Is that alright then? Are there any guidelines or best practices regarding this usage, particularly if you have a package with several submodules and etc?

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Success criteria for trust-constr
by thegreatjules＠hotmail.com March 21, 2022

March 21, 2022

The `trust-constr` algorithm from `scipy.optimize.minimize` defines 4 stop criteria: Termination status: 0 : The maximum number of function evaluations is exceeded. 1 : gtol termination condition is satisfied. 2 : xtol termination condition is satisfied. 3 : callback function requested termination. From http://scipy.github.io/devdocs/reference/optimize.minimize-trustconstr.html… The `OptimizeResult` object returned also contains a field `success`, which is filled in as follows: # Status 3 occurs when the callback function requests termination, # this is assumed to not be a success. result.success = True if result.status in (1, 2) else False From https://github.com/scipy/scipy/blob/a06cc0da56df9741105eedcd160b77f6f08236e… I understand why status 1 is considered success (infinity norm of Lagrangian gradient and the constraint violation are smaller than `gtol`), but why is status 2 also considered success? The `xtol` criterium is satisfied when the trust region radius drops below `xtol`, 1e-8 by default, but it doesn't check the Lagrangian gradient to see if an extremum was reached or the constraint violation to see if the constraints are satisfied. It seems this criterium stops the algorithm because it doesn't make sense to iterate further, not because it reached a solution. What am I missing?

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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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SciPy Griddata 2d interpolation
by huangqinuo＠outlook.com March 8, 2022

March 8, 2022

Dear, I am doing 2-dimensional interpolation (time and altitude) using griddata. I am wondering how the default 2d interpolation method, say 'linear' works when dealing with my case. I changed the time difference (minus my reference) time to seconds/hours, but found that the interpolated outcome different. This is aimed to find out the how time difference and height difference between the data and interpolated point influence data selected to interpolate. So my question is for example, I want an interpolated point at 02 LST, 01 Jan 2001, at 200 metres, using data 1.5 h +- 02 LST, 01 Jan 2001, 100 m +- 200 metres (this is my ideal idea), how could I set the data used to interpolate at the aimed point. The reason why I am asking this is that I found when I got missing data along time axis and/or altitude axis, the data used to interpolate will be strange. For example, still the same aimed interpolated point, when I do not have data around 200 metres at 2 or 3 LST, but have 100, 500 metres data at 2 LST and 200 metres data at 5 LST. How can I use the data at different altitudes at 2 LST to interpolated instead of using data at 200 metres at 5 LST. I also use a simple example, using 3 points data (a triangle) to interpolate another point in the triangle. But I cannot calculate the interpolated value. Anyways, hope that I have expressed my question clearly. Just wanna know the mechanism of 2d interpolation using grid data. Many thanks in advance, Qinuo

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NumPy 1.22.3 released
by Charles R Harris March 7, 2022

March 7, 2022

Hi All, On behalf of the NumPy team, I'm pleased to announce the release of NumPy 1.22.3. NumPy 1.22.3 is a maintenance release that fixes bugs discovered after the 1.22.2 release. The most noticeable fixes may be those for DLPack. One that may cause some problems is disallowing strings as inputs to logical ufuncs. It is still undecided how strings should be treated in those functions and it was thought best to simply disallow them until a decision was reached. That should not cause problems with older code. The Python versions supported in this release are 3.8-3.10. Wheels can be downloaded from PyPI <https://pypi.org/project/numpy/1.22.3>; source archives, release notes, and wheel hashes are available on Github <https://github.com/numpy/numpy/releases/tag/v1.22.3>. Note that the Mac wheels are now based on OS X 10.14 rather than 10.9 that was used in previous NumPy release cycles. 10.14 is the oldest release supported by Apple. Linux users will need pip >= 0.19.3 in order to install the manylinux2014 wheels. A recent version of pip is needed to install the universal2 macos wheels. *Contributors* A total of 9 people contributed to this release. People with a "+" by their names contributed a patch for the first time. - @GalaxySnail + - Alexandre de Siqueira - Bas van Beek - Charles Harris - Melissa Weber Mendonça - Ross Barnowski - Sebastian Berg - Tirth Patel - Matthieu Darbois *Pull requests merged* A total of 10 pull requests were merged for this release. - #21048: MAINT: Use "3.10" instead of "3.10-dev" on travis. - #21106: TYP,MAINT: Explicitly allow sequences of array-likes in ``np.concatenate`` - #21137: BLD,DOC: skip broken ipython 8.1.0 - #21138: BUG, ENH: np._from_dlpack: export correct device information - #21139: BUG: Fix numba DUFuncs added loops getting picked up - #21140: BUG: Fix unpickling an empty ndarray with a non-zero dimension... - #21141: BUG: use ThreadPoolExecutor instead of ThreadPool - #21142: API: Disallow strings in logical ufuncs - #21143: MAINT, DOC: Fix SciPy intersphinx link - #21148: BUG,ENH: np._from_dlpack: export arrays with any strided size-1... Cheers, Charles Harris

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