LaPy | Differential Geometry on Triangle and Tetrahedra Meshes | Service Mesh library

by Deep-MI Python Version: 1.0.1 License: MIT

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kandi X-RAY | LaPy Summary

LaPy is a Python library typically used in Architecture, Service Mesh applications. LaPy 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 LaPy' or download it from GitHub, PyPI.

LaPy is a package to compute spectral features (Laplace-Beltrami operator) on tetrahedral and triangle meshes. It is written purely in python 3 without sacrificing speed as almost all loops are vectorized, drawing upon efficient and sparse mesh data structures. It is a basically a port of the C++ ShapeDNA project with extended differential geometry capabilities.

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Support

LaPy has a low active ecosystem.

It has 30 star(s) with 9 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 10 have been closed. On average issues are closed in 113 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of LaPy is 1.0.1

Quality

LaPy has 0 bugs and 0 code smells.

Security

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

LaPy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

LaPy is licensed under the MIT License. This license is Permissive.

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

Reuse

LaPy 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 are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Compute the spherical parameterization of a mesh
Linear Boundrami solver
Calculates the coefficient of the packingrami coefficient
Computes the inverse of the transformation from a plane
Project a mesh onto a sphere
Normalize the vector
Computes the fractional mass of a triangle
Calculate mean curvature flow
Imports a GMSH file into a dictionary
Returns the contents of the file relative to the given relative path
Compute the shape of a shape matrix
Map a tfunc to a vfunc
Compute the Geodesic F
Compute the geodesic f
Compute the rotation of a geometry
Imports a TM mesh from a file
Smooth the model
Offset the surface of the mesh
Get the version string
Return a list of lists of boundary loops
Import an EVL file
Orient the mesh
R Function to plot a mesh
Compute the mobius area correction for a sphere
Normalize evals
Calculate the curvature of the triangle

Get all kandi verified functions for this library.

LaPy Key Features

No Key Features are available at this moment for LaPy.

LaPy Examples and Code Snippets

No Code Snippets are available at this moment for LaPy.

Community Discussions

Trending Discussions on LaPy

Fastest way to modify columns value iterating on pandas dataframe

QUESTION

Fastest way to modify columns value iterating on pandas dataframe

Asked 2021-Jul-07 at 23:05

Im using a csv file that has the lap number on a column, where each row contain data about that lap (last number is the lap), like this: value1, value2, 1 value3, value4, 1 ... valueN, valuex, 99

I have a subset of this data, so i have a range from lapX to lapY, and i want to rearrange it, where lapX is 1 and each time a new lap appears add 1 to the actual lap. I write this code that do what i want:

...

ANSWER

Answered 2021-Jul-07 at 20:46

Based on the expected dataframe, it looks like you just want to re-number the laps incrementally, even if they are not consecutive laps. So 5, 6, 9 becomes 1, 2, 3.

For that, take the unique values of Lap and sort them. Then zip it with a itertools.count() which just counts up. Make a dictionary from that and then map the old Lap values to new Lap values:

Source https://stackoverflow.com/questions/68292347

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

Vulnerabilities

No vulnerabilities reported

Install LaPy

You can install using 'pip install LaPy' or download it from GitHub, PyPI.
You can use LaPy 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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