rparini / cxroots Goto Github PK

Tracking issue for:

• https://github.com/rparini/cxroots/security/code-scanning/4

Biggest change is to rename variables to snake_case. Huge breaking change, will require a major version bump.

1. There is a certain amount of repetition in the stopping criteria for newton, secant and muller, these could probably be centralised to reduce repetition, perhaps in some stop_iteration function.
2. Would be nice to use some more battle-tested implementaions for these standard methods, rather than my own.
   • I think I originally passed on scipy.optimize.newton before because of scipy/scipy#10103 but it has now been pointed out that casting x0 to np.complex128 works around that. I also make use of callbacks during the iteration in my cuurent implemention but could probably get the same effect by wrapping the target func passed to scipy.optimize.newton.
   • Or maybe threre`s some other capability in mpmath or numdifftools that could be used more easily.

Would be helpful for Pylance to have type hints on functions. Could also run mypy/pyright/pytype in a github action to verify types

Will probably go with Pyright because I use that at work and it has good integration with VSCode via pylance.

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The current method of building wheels is python setup.py sdist bdist_wheel but gives

/opt/hostedtoolcache/Python/3.10.6/x64/lib/python3.10/site-packages/setuptools/installer.py:27: SetuptoolsDeprecationWarning: setuptools.installer is deprecated. Requirements should be satisfied by a PEP 517 installer.

and

/opt/hostedtoolcache/Python/3.10.6/x64/lib/python3.10/site-packages/setuptools/command/install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.

Hi,
I’m using cxroots to find all the roots of a complex function f(z). When I choose a rectangle of size real(-5000,5000), imag(-5000,5000), it gives me 14 roots, each with multiplicity 1. The roots are symmetric about the imaginary axis. That is it has 7 roots of the form x+iy and other 7 roots of the form -x+iy.
So, when I choose a rectangle of size real(0,5000), imag(-5000,5000), it gives me only 5 roots (two roots with a multiplicity of 2). Which implies, it did not detect two roots compared to the former case. The interesting thing is, if I specify a circle (2500,2500) instead of a rectangle, it gives me all the seven roots. Why is this happening?

Thanks.

https://github.blog/changelog/2022-05-19-render-mathematical-expressions-in-markdown/

Setting version.py in the release action and then exec-ing it in setup.py and the Sphinx config.py feels a bit janky and fragile.

Maybe setuptools-scm would help?

Hello,

We've tried to activate or update your repository on Depfu and couldn't find any supported dependency files. If we were to guess, we would say that this is not actually a project Depfu supports and has probably been activated by error.

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Add an Actions job to verify Black formatting

We have some files like AnnulusSector.py and others like test_rootfinding_contours.py. We should have a consistnet naming convention

Since we changed this test in #173 we would need to change the docs too. Or perhaps change the default values?

Will sort imports automatically

Several boolean args that lead to some complex if/else that make this function hard to read

Tracking issue for:

• https://github.com/rparini/cxroots/security/code-scanning/6

Not great to be installing things globally, make a package.json and install that (then Renovate should also update it as well)

Currently using coveralls but would be good to centralise on SonarCloud

A "What's new" section to highlight changes

At the moment its "Development Status :: 4 - Beta"

We currently have:

• CodeQL
• Bandit
• Black
• Flake8
• isort
• pyright

What can be removed or linked with SonarCloud?

Black provides consistent formatting

Improving derivative-free case

When df is not provided we currently approximate it using a finite difference method

Is there a better way of doing this? I feel like knowing f is complex analytic should let us do something more clever but not sure what. I've seen literature involving contour integrations to do this (and I implemented an approach in the cxroots.derivative.cx_derivative function) but integration can involve a lot of function evaluations. Possibly relevant reading:

• Numerical Differentiation of Analytic Functions, Fornberg 1981

Alternatively, perhaps we could take a different approach to rootfinding that avoids approximating df when it is not provided. Possibly relevant reading:

• Computing zeros of analytic functions in the complex plane without using derivatives, 2006
• A Derivative-Free Algorithm for Computing Zeros of Analytic Functions
  
• A Numerical Method for Locating the Zeros of an Analytic Function suggests evaluating ln(f(z))

Cluster handling

Can we improve how we handle clusters of roots?

• On Locating Clusters of Zeros of Analytic Functions

Currently blocked by pbrod/numdifftools#72

There are quite a lot of warnings raised when running the pytest test suite. What can we address?

A progress bar with "N/M roots found" would be a good middle ground between printing nothing (currently verbose=False) and printing a huge amount of debugging output (currently verbose=True). Not sure if this should be toggled by a new parameter or a new verbose level (verbose=1,2 or 3 instead of True/False).

scipy.integrate.quad added a complex_func argument in v1.10.0 which should let us get rid of the cxroots integrate_quad_complex. Should set scipy range in setup.py

For small contours (diameter < 1e-3), the arrows drawn by contour.show() becomes huge and eventually fills the whole figure.
To reproduce:

c = cxroots.Rectangle((-1e-4, 1e-4),(-1e-4, 1e-4))
c.show()

For some stupid reason, the width parameter of pyplot.arrow defaults to 1e-3, see https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.arrow.html

Suggested fix: set width instead of head_width and head_length here. The head dimensions are set relative to the width parameter.

Alternative: Use annotate instead of arrow as suggested at the very bottom of https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.arrow.html.

• Currently using PyUp but it somehow missed its dependency update for December and is quite limited anyway (only Python so will not help with other projects)
• Snyk has a lot of features (eg. code scanning) but can't get it to make dependency updates other than for security (despite turning on "automatic dependecy update pull requests")
• GitHub's built-in Dependabot might be good, nice to have everything in GitHub, though maybe not as fully featured as Snyk.
  • Seems like Dependabot can't group updates together which creates a lot of noise dependabot/dependabot-core#1190
• Renovate needs some config but I use it for work, probably about the same features as Dependabot #111
  • But it can't support environment markers in the requirements.txt which we currently need to test against Python2: renovatebot/renovate#12727

At the moment the create_docs has npm install -g terminalizer which is messy, should be in a package.json that then Renovate can update in a managed way

count_roots is there but the parameters aren't documented. .roots(...) seems to be entirely missing

attempt_best is passed to the newton and muller functions but then it only returns the root if

Perhaps newton and muller could return dx0 so that we could return the root if abs(dx0) < step_tol. Maybe worth evaluating if the attempt_best functionality is useful first.

Also an opportunity to resolve

• https://github.com/rparini/cxroots/security/code-scanning/5

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How to automatically set versions?

Look into getting a DOI for cxroots, probably following these docs

Eg, what scipy has:

Will be important if/when breaking changes are introduced that people can still look at older versions

It's a very long generator with several functions defined within it so hard to read. Might want to be a class with methods instead.

There are also some special cases and adaptive adjustments in the code that are not tested