Skip to main content


NMesh

Modules • Installing the application • Makefile commands • Environments • Running the application Ressources

NMesh is a Python package that provides two high-level features:

  • A simple Mesh processor
  • A list of tool to convert mesh files into point cloud

You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend ZakuroCache integration.

Modules

At a granular level, NMesh is a library that consists of the following components:

Component Description
nmesh Contains the implementation of NMesh
nmesh.core Contain the functions executed by the library.
nmesh.pc Processor for the point cloud
nmesh.tests Unit tests

Installing the application

To clone and run this application, you'll need the following installed on your computer:

Install the package:

# Clone this repository and install the code
git clone https://github.com/JeanMaximilienCadic/nmesh

# Go into the repository
cd nmesh

Makefile commands

Exhaustive list of make commands:

install_wheels
sandbox_cpu
sandbox_gpu
build_sandbox
push_environment
push_container_sandbox
push_container_vanilla
pull_container_vanilla
pull_container_sandbox
build_vanilla
build_wheels
auto_branch 

Environments

Docker

Note

Running this application by using Docker is recommended.

To build and run the docker image

make build
make sandbox

PythonEnv

Warning

Running this application by using PythonEnv is possible but not recommended.

make install_wheels

Running the application

from nmesh import NMesh, cfg
m = NMesh(cfg.drive.bull)
m.show()

Ressources

Metadata

Release files for nmesh 0.1.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for nmesh 0.1.4
File Interpreter ABI Platform
nmesh-0.1.4-py3-none-any.whl Python 3 none any Details

Release files / nmesh-0.1.4-py3-none-any.whl

Download URL nmesh-0.1.4-py3-none-any.whl
Size 16.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
bdc39d916651f442f9c7ac60426f32833f0b2df8604b1e6a46b17958f33583ed
BLAKE2b-256 checksum
How to use checksums
e0ac22ddd0b5e15394a69a2b0e489b7380777e49b8ba7d3b9f9a3af25bebefe7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.8.0 colorama/0.4.4 importlib-metadata/4.6.4 keyring/23.5.0 pkginfo/1.8.2 readme-renderer/34.0 requests-toolbelt/0.9.1 requests/2.25.1 rfc3986/1.5.0 tqdm/4.57.0 urllib3/1.26.5 CPython/3.10.6
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page