jacobi
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HDembinski
Numerical derivatives for Python
Hello Hans, Thank you for this project, we needed something like this for a long time and we had tried to implement it ourselves privately, but given our limited programming...
updates: - [github.com/astral-sh/ruff-pre-commit: v0.3.7 → v0.4.4](https://github.com/astral-sh/ruff-pre-commit/compare/v0.3.7...v0.4.4) - [github.com/psf/black: 24.4.0 → 24.4.2](https://github.com/psf/black/compare/24.4.0...24.4.2) - [github.com/pre-commit/mirrors-mypy: v1.9.0 → v1.10.0](https://github.com/pre-commit/mirrors-mypy/compare/v1.9.0...v1.10.0)
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From discussion with @mdhaber > It looks like step[0] is a relative (to the value of x) initial step size and step[1] is a reduction factor for each iteration. However,...
A challenging test case is the function `y = np.log(1 + a1 * x + a2 * x**2)` with $a1 = 2.0 \pm 0.2$ and $a2 = 1.0 \pm 0.1$...
Test and improve support for Numpy masked arrays. Jacobi raises a ValueError if a numpy.ma.core.MaskedConstant is encountered as an input.
When passing the covariance as numpy array, the `Indexable` type generates linter warnings of the type: ``` Argument of type "NDArray[float64]" cannot be assigned to parameter "cov" of type "float...
