Merge branch 'topic/default/maintain' into 'branch/default'

Topic/default/maintain

See merge request fluiddyn/fluidimage!111

.github/workflows/ci-pixi.yml

@@ -17,9 +17,9 @@ jobs:
         shell: bash -l {0}
     steps:
     - uses: actions/checkout@v4
-    - uses: prefix-dev/setup-pixi@v0.4.1
+    - uses: prefix-dev/setup-pixi@v0.8.0
       with:
-        pixi-version: v0.11.1
+        pixi-version: v0.22.0
         cache: false
     - name: Install
       run: |

README.md

@@ -1,5 +1,4 @@
-FluidImage
-==========
+# FluidImage
 
 [![Latest version](https://img.shields.io/pypi/v/fluidimage.svg)](https://pypi.python.org/pypi/fluidimage/)
 ![Supported Python versions](https://img.shields.io/pypi/pyversions/fluidimage.svg)
@@ -9,51 +8,46 @@ FluidImage
 [![Github Actions Linux](https://github.com/fluiddyn/fluidimage/actions/workflows/ci-linux.yml/badge.svg?branch=branch/default)](https://github.com/fluiddyn/fluidimage/actions/workflows/ci-linux.yml)
 [![Github Actions Pixi](https://github.com/fluiddyn/fluidimage/actions/workflows/ci-pixi.yml/badge.svg?branch=branch/default)](https://github.com/fluiddyn/fluidimage/actions/workflows/ci-pixi.yml)
 
-FluidImage is a libre Python framework for scientific processing of
-large series of images.
+FluidImage is a libre Python framework for scientific processing of large series of
+images.
 
 **Documentation:** <http://fluidimage.readthedocs.org>
 
-Image processing for fluid mechanics is highly dominated by proprietary
-tools. Such tools are not ideal when you want to understand and tweak
-the processes and/or to use clusters. With the improvement of the
-open-source tools for scientific computing and collaborative
-development, one can think it is possible to build together a good
-library/toolkit specialized in image processing for fluid mechanics.
-This is our project with FluidImage.
+Image processing for fluid mechanics is highly dominated by proprietary tools. Such tools
+are not ideal when you want to understand and tweak the processes and/or to use clusters.
+With the improvement of the open-source tools for scientific computing and collaborative
+development, one can think it is possible to build together a good library/toolkit
+specialized in image processing for fluid mechanics. This is our project with FluidImage.
 
-This package is young but already good enough to be used "in
-production" to
+This package is young but already good enough to be used "in production" to
 
 - display and pre-process images,
 
-- compute displacement or velocity fields with [Particle Image
-  Velocimetry](https://en.wikipedia.org/wiki/Particle_image_velocimetry%20(PIV))
-  (PIV, i.e. displacements of pattern obtained by correlations of
-  cropped images) and [optical
-  flow](https://en.wikipedia.org/wiki/Optical_flow),
+- compute displacement or velocity fields with
+  [Particle Image Velocimetry](<https://en.wikipedia.org/wiki/Particle_image_velocimetry%20(PIV)>)
+  (PIV, i.e. displacements of pattern obtained by correlations of cropped images) and
+  [optical flow](https://en.wikipedia.org/wiki/Optical_flow),
 
 - analyze and display PIV fields.
 
-We want to make FluidImage easy (useful documentation, easy
-installation, usable with scripts and GUI in Qt), reliable (with good
-[unittests](https://codecov.io/gh/fluiddyn/fluidimage/)) and very
-efficient, in particular when the number of images to process becomes
-large. Thus we want FluidImage to be able to run efficiently and easily
-on a personal computer and on big clusters. The efficiency is achieved
-by using
+We want to make FluidImage easy (useful documentation, easy installation, usable with
+scripts and GUI in Qt), reliable (with good
+[unittests](https://codecov.io/gh/fluiddyn/fluidimage/)) and very efficient, in
+particular when the number of images to process becomes large. Thus we want FluidImage to
+be able to run efficiently and easily on a personal computer and on big clusters. The
+efficiency is achieved by using
 
 - a framework for asynchronous computations (currently, we use
-  [Trio](https://trio.readthedocs.io) + multiprocessing, and in the
-  long term we want to be able to plug FluidImage to distributed
-  computational systems like [Dask](http://dask.pydata.org),
-  [Spark](https://spark.apache.org/) or
+  [Trio](https://trio.readthedocs.io) + multiprocessing, and in the long term we want to
+  be able to plug FluidImage to distributed computational systems like
+  [Dask](http://dask.pydata.org), [Spark](https://spark.apache.org/) or
   [Storm](http://storm.apache.org/)),
 
-- the available cores of the central processing units (CPU) and the
-  available graphics processing units (GPU),
+- the available cores of the central processing units (CPU) and the available graphics
+  processing units (GPU),
 
 - good profiling and efficient and specialized algorithms,
 
 - cutting-edge tools for fast computations with Python (in particular
-  [Pythran](https://pythonhosted.org/pythran/)).
+  [Pythran](https://pythran.readthedocs.io) through
+  [Transonic](https://transonic.readthedocs.io)).