meshzoo | : tiger : : cow : : panda_face : A collection of meshes | Service Mesh library

by nschloe Python Version: v0.9.4 License: GPL-3.0

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

kandi X-RAY | meshzoo Summary

meshzoo is a Python library typically used in Architecture, Service Mesh applications. meshzoo has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However meshzoo build file is not available. You can install using 'pip install meshzoo' or download it from GitHub, PyPI.

When generating meshes for FEM/FVM computations, sometimes your geometry is so simple that you don't need a complex mesh generator (like pygmsh, MeshPy, mshr, pygalmesh, dmsh), but something simple and fast that makes use of the structure of the domain. Enter meshzoo.

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Support

meshzoo has a low active ecosystem.

It has 245 star(s) with 31 fork(s). There are 11 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 15 have been closed. On average issues are closed in 7 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of meshzoo is v0.9.4

Quality

meshzoo has 0 bugs and 0 code smells.

Security

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

meshzoo code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

meshzoo is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

meshzoo releases are available to install and integrate.

Deployable package is available in PyPI.

meshzoo has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

meshzoo saves you 584 person hours of effort in developing the same functionality from scratch.

It has 1362 lines of code, 70 functions and 36 files.

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

Top functions reviewed by kandi - BETA

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

Given a set of corners and a list of corners compose them .
Creates a quadratic rectangle .
Generate a spherical sphere .
Create a cube triangulation .
Generate a uv - v sphere .
Generate a MOBius .
Create a triangular triangle .
Insert the endpoints of a cell .
Create an icosahed sphere .
Create a cube of the x y - axis .

Get all kandi verified functions for this library.

meshzoo Key Features

No Key Features are available at this moment for meshzoo.

meshzoo Examples and Code Snippets

Efficiently construct FEM/FVM matrix

Python

Lines of Code : 9

License : Strong Copyleft (CC BY-SA 4.0)

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Community Discussions

Trending Discussions on meshzoo

Efficiently construct FEM/FVM matrix

QUESTION

Efficiently construct FEM/FVM matrix

Asked 2017-Feb-22 at 07:56

This is a typical use case for FEM/FVM equation systems, so is perhaps of broader interest. From a triangular mesh à la

I would like to create a scipy.sparse.csr_matrix. The matrix rows/columns represent values at the nodes of the mesh. The matrix has entries on the main diagonal and wherever two nodes are connected by an edge.

Here's an MWE that first builds a node->edge->cells relationship and then builds the matrix:

...

ANSWER

Answered 2017-Feb-20 at 22:13

I would try creating the csr structure directly, especially if you are resorting to np.unique since this gives you sorted keys, which is half the job done.

I'm assuming you are at the point where you have i, j sorted lexicographically and overlapping v summed using np.add.at on the optional inverse output of np.unique.

Then v and j are already in csr format. All that's left to do is creating the indptr which you simply get by np.searchsorted(i, np.arange(M+1)) where M is the column length. You can pass these directly to the sparse.csr_matrix constructor.

Ok, let code speak:

Source https://stackoverflow.com/questions/42349191

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

Vulnerabilities

No vulnerabilities reported

Install meshzoo

meshzoo is available from the Python Package Index, so simply do.

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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