pybie2d | 2D Boundary Integral Equation Tools in Python

by dbstein Python Version: Current License: Apache-2.0

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

kandi X-RAY | pybie2d Summary

pybie2d is a Python library. pybie2d has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

The goal of this project is to provide tools in python for solving the Laplace and Stokes problems in two dimensions, modeled after Alex Barnett's package BIE2D for MATLAB available at:

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Support

pybie2d has a low active ecosystem.

It has 10 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

pybie2d has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pybie2d is current.

Quality

pybie2d has no bugs reported.

Security

pybie2d has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

pybie2d is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

pybie2d releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed pybie2d and discovered the below as its top functions. This is intended to give you an instant insight into pybie2d implemented functionality, and help decide if they suit your requirements.

Compute the closure for the Laplace correction
R Laplace layer form
R Constructs a Stokes layer
Compute the spatial tree
Linear equation for Laplace kernel
Compose Laplace form using the Laplace form
Returns the differentiation matrix
Calculate the Laplace LPD for a given source
R Calculate the compensated Cauchy form
Apply operator
Apply Laplace layer
Modify a Helmholtz layer
Modified Modified Hholtz kernel
Apply the singular transformation to a singularity layer
R Apply a Stokes layer
Performs the Stokes normalization correction on the close panel
Sets up close points for Laplace correction
Modify the modified Helmholtz kernel
Apply a Laplace layer
R Stokes the Stokes kernel
Apply a modified Helmholtz layer
Form the Laplace singular form of a layer
Compress the stochastic equation
R Stokes the Stokes layer
Apply Laplace - Kernel
Prepare the oversampling of the plot
Modified ModifiedHholtz kernel
Compensates the density of a StokesStarts
Apply Stokes Stokes Layer
Computes a linear laplace_apply
Form the singular form of a Stokes layer

Get all kandi verified functions for this library.

pybie2d Key Features

No Key Features are available at this moment for pybie2d.

pybie2d Examples and Code Snippets

No Code Snippets are available at this moment for pybie2d.

Community Discussions

No Community Discussions are available at this moment for pybie2d.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install pybie2d

You can download it from GitHub.
You can use pybie2d 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 .

Find more information at: