From df2f0b1538e426eb1290c550a179741f80240e39 Mon Sep 17 00:00:00 2001 From: paugier Date: Thu, 30 May 2024 12:55:55 +0200 Subject: [PATCH] Improve README --- README.md | 20 ++++++++++---------- doc/install.md | 4 ++-- 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index 8cc6c36..e7b98cc 100644 --- a/README.md +++ b/README.md @@ -23,24 +23,24 @@ Matlab, which is itself proprietary. With the improvement of the Python numerical ecosystem and of tools for collaborative development, one can think it is possible to build together a good community-driven library/toolkit specialized in image processing for fluid mechanics. This is our project -with FluidImage. Fluidimage can be thought as a partial rewrite in Python of [UVmat] with -a focus on performance and usability. Moreover, we try to integrate good ideas taken from -[OpenPIV], [PIVlab] and [PIVmat]. +with FluidImage. -This package is quite young but can be used to +Fluidimage has now grown into a clean software reimplementing in modern Python algorithms +and ideas taken from [UVmat], [OpenPIV], [PIVlab] and [PIVmat] with a focus on +performance, usability and maintanability. However, Fluidimage is not restricted to +Particle Image Velocimetry computations ([PIV], i.e. displacements of pattern obtained by +correlations of cropped images) and can be used to - display and pre-process images, -- compute displacement or velocity fields with Particle Image Velocimetry ([PIV], i.e. - displacements of pattern obtained by correlations of cropped images), - Background-Oriented Schlieren +- compute displacement or velocity fields with PIV, Background-Oriented Schlieren ([BOS](https://en.wikipedia.org/wiki/Background-oriented_schlieren_technique)) and [optical flow](https://en.wikipedia.org/wiki/Optical_flow), -- analyze and display PIV fields. +- analyze and display vector and scalar fields. -We want to make FluidImage easy (useful documentation, easy installation, good API, -usable with simple scripts and simple graphical user interfaces), reliable (with good +We want to make FluidImage easy (useful documentation, easy installation, nice API, +usable with simple scripts and few simple graphical user interfaces), reliable (with good [unittests](https://codecov.io/gh/fluiddyn/fluidimage/)) and very efficient, in particular when the number of images is large. Thus we want FluidImage to be able to run efficiently and easily on a personal computer and on big clusters. The efficiency is diff --git a/doc/install.md b/doc/install.md index 79273bd..08d8e5d 100644 --- a/doc/install.md +++ b/doc/install.md @@ -37,8 +37,8 @@ Fluidimage has 2 sets of optional dependencies, which can be installed with comm ## Install the conda-forge package with conda or mamba We recommend installing `conda` and `mamba` with the -[miniforge installer](https://github.com/conda-forge/miniforge) so that the installed -packages will be uploaded from the [conda-forge] channel. Then, one can run: +[miniforge installer](https://github.com/conda-forge/miniforge) so that the packages will +be uploaded from the [conda-forge] channel. Then, one can run: ```sh mamba install fluidimage