https://github.com/clatlan/gwaihir

Repository regarding the Gwaihir GUI used for Bragg Coherent Coherent Diffraction (BCDI) data analysis

https://github.com/clatlan/gwaihir

Repository

Repository regarding the Gwaihir GUI used for Bragg Coherent Coherent Diffraction (BCDI) data analysis

https://github.com/clatlan/gwaihir/blob/master/

# Welcome 

## This github is focused on the scripts that will be used during my thesis

Contact : david.simonne@universite-paris-saclay.fr

You can install gwaihir via the setup.py script, so that you can use via a package after in python, see below

The bcdi subfolder gives some guidelines into how to process BCDI data

Gwaihir is also avaible on pypi.org, each new version from the master branch is uploaded: `https://pypi.org/project/gwaihir/`
On the contrary, if you follow the github changes on the dev branchm you will have the latest version

# Installing different packages

First, I advise you to create a Packages directory to keep these.
Secondly, I advise you to create a virtual environment to jelp with debogging, and so that once everything works, you don't update a package by mistake. To do so please follow the following steps:

## Create a virtual environment

* `mkdir py38-env`
* `cd py38-env/`
* `python3.8 -m venv .`
* `source bin/activate` # To activate the environment

Then you should create an alias such as: `alias source_p9="source /data/id01/inhouse/david/py38-env/bin/activate"`

## Install gwaihir
* `cd /Packages`
* `git clone https://github.com/DSimonne/gwaihir.git`
* `cd gwaihir`
* `source_p9`
* `pip install .`

## Install PyNX
* Send a thank you email to Vincent Favre-Nicolin =D
* `cd /Packages`
* `mkdir PyNX_install`
* `cd PyNX_install/`
* `curl -O http://ftp.esrf.fr/pub/scisoft/PyNX/pynx-devel-nightly.tar.bz2`      # Installation details within install-pynx-venv.sh
* `source_p9`
* `pip install pynx-devel-nightly.tar.bz2[cuda,gui,mpi]`                        # Install avec les extras cuda, mpi, cdi
* cite `PyNX: high-performance computing toolkit for coherent X-ray imaging based on operators is out: J. Appl. Cryst. 53 (2020), 1404`, also available as `arXiv:2008.11511`

Please use the commit from the data: Wednesday, August 18, 17:36:37, 2021 +0200, commit number: `2c822d3f`

## Install bcdi
* Send a thank you email to Jerome Carnis =D
* `cd /Packages`
* `git clone https://github.com/carnisj/bcdi.git`
* `cd bcdi`
* `source_p9`
* `pip install .`
* cite `DOI: 10.5281/zenodo.3257616`

For now it is mandatory to use the version 0.1.5 of bcdi

## Install facet-analyser (Debian 11 only)
* Send a thank you email to Fred Picca =D
* `cd /Packages`
* `git clone https://salsa.debian.org/science-team/facet-analyser.git`
* `cd facet-analyser`
* `git checkout`
* `sudo mk-build-deps -i`
* `debuild -b`
* `sudo debi`
* The package is now installed. You can check the locations of its files with the command `dpkg -L facet-analyser`
* You should see a file named `/usr/lib/x86_64-linux-gnu/paraview-5.9/plugins/FacetAnalyser/FacetAnalyser.so`
* Now launch `/usr/bin/paraview` (if not installed yet, good luck, refer to `https://www.paraview.org/Wiki/ParaView:Build_And_Install#Installing`)
* In paraview, go to Tools > Manage Plugins > Load New
* Here type the path to the plugin that was printed with the `dpkg -L facet-analyser` command.
* Feel free to add it to `/usr/bin/plugin` so that it is loaded automatically.
* cite `Grothausmann, R. (2015). Facet Analyser : ParaView plugin for automated facet detection and measurement of interplanar angles of tomographic objects. March.`

# Clusters at ESRF

## slurm
`ssh -X @slurm-nice-devel`

Demande GPU

`srun -N 1 --partition=p9gpu --gres=gpu:1 --time=01:00:00 --pty bash`

### Environments on slurm
* python3: your personal environemnt
* p9_3.8_dev : optimised for BCDI, gwaihir and PyNX, development version
* p9_3.8_stable : optimised for BCDI, gwaihir and PyNX, stable version
* p9.pynx-devel : fonctionne pour pynx, frequently updated : `source /sware/exp/pynx/devel.p9/bin/activate`
* p9.pynx-gap : ?

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