num-methods-for-PDEs | Lecture material on numerical methods

by hplgit Python Version: Current License: No License

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kandi X-RAY | num-methods-for-PDEs Summary

num-methods-for-PDEs is a Python library. num-methods-for-PDEs has no bugs, it has no vulnerabilities and it has low support. However num-methods-for-PDEs build file is not available. You can download it from GitHub.

Lecture material on numerical methods for partial differential equations.

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num-methods-for-PDEs has a low active ecosystem.

It has 166 star(s) with 86 fork(s). There are 14 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 209 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of num-methods-for-PDEs is current.

Quality

num-methods-for-PDEs has no bugs reported.

Security

num-methods-for-PDEs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

num-methods-for-PDEs does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

num-methods-for-PDEs releases are not available. You will need to build from source code and install.

num-methods-for-PDEs has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed num-methods-for-PDEs and discovered the below as its top functions. This is intended to give you an instant insight into num-methods-for-PDEs implemented functionality, and help decide if they suit your requirements.

Test the empirical analysis
Calculate the lower and upper and upper bounds
Compute the amplitudes between minima and maxima
Return a numpy array of periods
Plot a basis function
Create a mesh
Plot 3d data
Draw a mesh
Test the plug
R Solve a mesh
Plot the numerical and exact solver
Return a string representation of the network
Test the solver
Run a set of solvers and plot them
Test a potential integer division
Save the plot to file
Shows the current execution
Test the solver for 3 - step 3
R Evaluates the exact discrete solution on a mesh
Plug a profile
Plots the frequency approximations
Plot amplification factors
Plots the evolution of the EDE
R Lagrange polynomials
R Solve the non - physical behavior of a non - physical behavior
Set the bounding box

Get all kandi verified functions for this library.

num-methods-for-PDEs Key Features

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num-methods-for-PDEs Examples and Code Snippets

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Vulnerabilities

No vulnerabilities reported

Install num-methods-for-PDEs

You can download it from GitHub.
You can use num-methods-for-PDEs like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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