pycvodes | Python wrapper around cvodes

by bjodah C++ Version: 0.14.5 License: BSD-2-Clause

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pycvodes Summary

pycvodes is a C++ library. pycvodes has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Python wrapper around cvodes (from the sundials library)

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pycvodes has a low active ecosystem.

It has 24 star(s) with 4 fork(s). There are 3 watchers for this library.

There were 3 major release(s) in the last 12 months.

There are 5 open issues and 4 have been closed. On average issues are closed in 191 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pycvodes is 0.14.5

Quality

pycvodes has 0 bugs and 0 code smells.

Security

pycvodes has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pycvodes code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pycvodes is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

pycvodes releases are available to install and integrate.

It has 1059 lines of code, 93 functions and 14 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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pycvodes Key Features

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pycvodes Examples and Code Snippets

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Community Discussions

Trending Discussions on pycvodes

How to perform adjoint sensitivity in Python (preferably through CVODE)

QUESTION

How to perform adjoint sensitivity in Python (preferably through CVODE)

Asked 2020-Dec-15 at 12:08

I want to implement the adjoint sensitivity analysis in python, in order to determine the gradient of my objective function with respect to some parameters. In specific the objective function depends on the solution of a differential equation which in turn depends on said parameters which I am looking to find the optimum of.

To perform this there are numerous good packages both in Julia (see here), as well as CVODES from SUNDIALS, however the latter which does apparently have a wrapper made for python, does not include sensitivity analysis capabilities according to this link. Furthermore, I have looked into SALib for sensitivity analysis, but as far as I understand this refers to some other type of 'sensitivity analysis' and therefore adjoint or even forward sensitivity analysis is not included (correct me if I am wrong on this one).

Thus my question is, does a version of CVODES exist in python with sensitivity analysis capabilities, or is there there any other package where one can use in order to perform adjoint sensitivity analys?

...

ANSWER

Answered 2020-Dec-15 at 12:08

You can easily call Julia code / packages from Python with pyjulia. https://github.com/JuliaPy/pyjulia

Source https://stackoverflow.com/questions/65302689

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

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Install pycvodes

You can download it from GitHub.

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