diffeqpy | Solving differential equations in Python | Machine Learning library

 by   SciML Python Version: 2.4.1 License: MIT

kandi X-RAY | diffeqpy Summary

kandi X-RAY | diffeqpy Summary

diffeqpy is a Python library typically used in Artificial Intelligence, Machine Learning applications. diffeqpy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install diffeqpy' or download it from GitHub, PyPI.

Python does not allow ! in function names, so this is also a limitation of pyjulia To use functions which on the Julia side have a !, like step!, replace ! by _b, for example:. is valid Python code for using the integrator interface.
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            kandi-support Support

              diffeqpy has a low active ecosystem.
              It has 412 star(s) with 34 fork(s). There are 23 watchers for this library.
              There were 2 major release(s) in the last 12 months.
              There are 32 open issues and 39 have been closed. On average issues are closed in 24 days. There are 3 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of diffeqpy is 2.4.1

            kandi-Quality Quality

              diffeqpy has 0 bugs and 16 code smells.

            kandi-Security Security

              diffeqpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              diffeqpy code analysis shows 0 unresolved vulnerabilities.
              There are 1 security hotspots that need review.

            kandi-License License

              diffeqpy is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              diffeqpy releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              diffeqpy saves you 52 person hours of effort in developing the same functionality from scratch.
              It has 137 lines of code, 15 functions and 8 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed diffeqpy and discovered the below as its top functions. This is intended to give you an instant insight into diffeqpy implemented functionality, and help decide if they suit your requirements.
            • Ensure that julia is installed
            • Installs Java
            • Find the jilli library
            • Return the contents of the README md file
            Get all kandi verified functions for this library.

            diffeqpy Key Features

            No Key Features are available at this moment for diffeqpy.

            diffeqpy Examples and Code Snippets

            No Code Snippets are available at this moment for diffeqpy.

            Community Discussions

            Trending Discussions on diffeqpy

            QUESTION

            Matrix vs. loop for discretization of PDE
            Asked 2021-Mar-27 at 11:20

            I am experimenting with using diffeqpy to solve a PDE by discretization of the spacial dimension, while I treat the time dimension as a set of ordinary differential equations. I managed to solve a very simple problem using a for loop. However, when I try to use matrixes, to scale the problem up, the solver provides incorrect answers.

            The following piece of code works:

            ...

            ANSWER

            Answered 2021-Mar-25 at 13:11

            If you're not doing in-place modification, use the 3-argument form:

            Source https://stackoverflow.com/questions/66743042

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

            Vulnerabilities

            No vulnerabilities reported

            Install diffeqpy

            To install diffeqpy, use pip:.

            Support

            In case you encounter silent failure from tox, try running it with -- -s (e.g., tox -e py36 -- -s) where -s option (--capture=no, i.e., don't capture stdio) is passed to py.test. It may show an error message "error initializing LibGit2 module". In this case, setting environment variable SSL_CERT_FILE may help; e.g., try:.
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            Install
          • PyPI

            pip install diffeqpy

          • CLONE
          • HTTPS

            https://github.com/SciML/diffeqpy.git

          • CLI

            gh repo clone SciML/diffeqpy

          • sshUrl

            git@github.com:SciML/diffeqpy.git

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