# Computing 

## Computing environments

Standard Linux environment:

````
Linux saresc-cons-04.psi.ch 3.10.0-1160.45.1.el7.x86_64 #1 SMP Fri Sep 24 10:17:16 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux

NAME="Red Hat Enterprise Linux Server"
VERSION="7.9 (Maipo)"
````

Some basic commands:
* `module list` : lists currently loaded modules in the environment
* `module avail`: lists available modules
* `module load <modulename>` : loads the given module into the current shell (it is directly active)

## Space
There is a large number of directories, default locations and quotas for the different computing tasks at SwissFEL. 

For large experimental data the allocated space for the respective p-group should be used. E.g. under `/gpfs/photonics/swissfel/res/cristallina-staff/pxxxxx`, here ra.psi.ch does not have write access (regardless of the user) but can read the data. 

To check the currently available space:
`quota -h` and `df -h`. 


## File permsissions
We should all be part of the unx-cristall group. Please make sure permissions are set at least `chmod g+rw,` so that everyone within the group can access and modify documents. Only set more restrictive permissions when necessary. (Alternatively `chmod g=u` to set the permissions equal to user permissions).


## Anaconda
For all python-based applications and analysis scripts we use use virtual environments administrated using conda/mamba. 

### Activate base environment
To bootstrap the base environment as a starting point use `source /sf/cristallina/applications/conda/envs/miniconda/bin/activate`. With a base environment now loaded we can initialize our shell using `conda init` so this environment is available at the next login. 

### Cristallina environments
All conda environments for cristallina are located at `/sf/cristallina/applications/conda/envs`. Their respective descriptions in `/sf/cristallina/applications/conda/env_specs`, which is also tracked in git.psi.ch.

The main environments are: 
 * slic (`/sf/cristallina/applications/conda/envs/slic`)
 * analysis (`/sf/cristallina/applications/conda/envs/analysis`)
 
for instrument control and data analysis. We are trying to track recent upstream packages but please only update if you ensure a working state afterwards and document the changes.

To be able to use the shortcut for activation, e.g. `conda activate slic` the environment directory needs to be added to your `.condarc` file as follows:

````
envs_dirs:
  - /sf/cristallina/applications/conda/envs
````

A backup environment is currently located at: 
````
/gpfs/photonics/swissfel/res/cristallina-staff/p19739/backup/cristallina2
````
if all else fails.

## Getting git
The `git` installed on the cristallina consoles is from 2015, so we can use conda to provide us with an up-to-date version. E.g. with `miniconda` activated simply install using `conda install git`. 

# sf_datafiles directly from github
- pip:
  - "git+https://github.com/paulscherrerinstitute/sf_datafiles@master"

sf_data is installed directly from github (using python ensures that the activated environment site-packages is used):

python -m pip install git+https://github.com/paulscherrerinstitute/sf_datafiles@master

# Remote access (how can users get to RA)
## Through hop.psi.ch (nicer way)
Connect to PSI network for data access
`ssh -L user_name@hop.psi.ch user_name@ra.psi.ch -L5000:jupytera.psi.ch:443`

after that, just open the browser and type:
`https://localhost:5000/hub/login`

## Through NoMachine
see https://gitlab.psi.ch/maloja/docs/-/wikis/python/Getting-started 

# Setting up the cluster:
This is a short summary of the steps to be followed to access the experimental data and the compute resources available for Cristallina users.

#  Copy the bash
Once on ra (ssh user_name@ra.psi.ch as described above), copy the bash file:
`ln -s /sf/cristallina/bin/setting_up_ra.sh`

and run it
`sh setting_up_ra.sh`

This should set up the working python enviroments. For the analysis, please use the 'analysis' enviroment, which is set as a default one.