numdifftools
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pbrod
Solve automatic numerical differentiation problems in one or more variables.
I'm not on the bleeding edge version but I'm getting this error when trying to calculate the Hessian of a function that returns a 1D array: ``` TypeError: only size-1...
Similar to issue #20 , I would be willing to implement parallelizing the function evaluations for the derivative with the multiprocessing module. I have it working in my own implementation,...
Some people like myself are not interested in the API that requires scipy or algopy. Please make these dependencies optional.
I tried to compare the values obtained from computing the jacobian of a complex valued function using numdifftools and found that it differed from that computed using autograd only for...
Hi, the results of Gradient and Hessian are NaN. I believe, I get NaN as a result because the values of Gradient and Hessian are too small. However, I need...
The original docs of the matlab version can be found here: https://convexoptimization.com/TOOLS/DERIVEST.pdf The docs give credit to d'Errico, but without explicit permission from the original author, this is still a...
Assume `f` is a function that consumes numpy arrays of shape `N x d` and returns arrays of the form `N` (i.e., it is a map from R^d to R...
I use the Hessian tool to calculate the covariance matrix of a cost function (NLL). The NLL is calculated for multiple categories of data and then combined in a single...
Hi, the how-to guide seems to be broken: https://numdifftools.readthedocs.io/en/stable/how-to/index.html
In the module "numdifftools/src/numdifftools/limits.py", the function "_add_error_to_outliers" is used to get the best estimate. Do you have a reference for this method? Thanks in advance, Robbert
