(user.saxs.data_analysis)=
# Data analysis

We can access the online computing resources from the beamline consoles when logged in as the e-account.

## Allocation of nodes

Check available nodes and allocate one:

```bash
sinfo
salloc -A csaxs -p csaxs -w [ra-c-110]
ssh -Y [ra-c-110]
```

Or for a GPU node:

```bash
salloc -A csaxs -p gpu-csaxs --gpus=4 [-w ra-gpu-003]
ssh -Y [ra-gpu-003]
```

(note that we need to ask them to explicitly use one of our GPU nodes there, and this needs a couple of days to set up)

**The home directory is the p group.** To go to the raw directory we need to navigate there:

```bash
cd /sls/x12sa/data/[p22598]/raw
```

## Python tools

### Python package installation

Anaconda is no longer supported. Packages should now be installed directly using `pip`.

For example, `pyFAI` can be installed as follows:

```bash
module load Python/3.11.11
pip install "pyFAI[gui]"
```

To launch the `pyFAI` applications:

```bash
# Detector calibration
python -m pyFAI.app.calib2

# Batch integration
python -m pyFAI.app.integrate
```

### Recommended: using a Python virtual environment

For long-term maintainability and reproducibility, it is recommended to use a dedicated Python virtual environment.

#### Create a virtual environment

```bash
cd /sls/x12sa/data/[p-group]/raw

module load Python/3.11.11
mkdir python-env
cd python-env

# Create a virtual environment named ".venv"
python3 -m venv .venv

# Activate the environment
source .venv/bin/activate

# Install required packages
pip install "pyFAI[gui]"
```

#### Use an existing virtual environment

```bash
cd /sls/x12sa/data/[p-group]/raw/python-env
source .venv/bin/activate
```

### Troubleshooting

If you encounter the following error when launching GUI applications (e.g. `pyFAI-calib2`):

```text
X11 connection rejected
```

reconnect to the analysis node with X11 forwarding enabled:

```bash
ssh -X [ra-c-110]
```

and then reactivate the virtual environment before launching the application.

## Use Jupyter Notebook / Lab

Create a virtual environment following the instructions above, then:

```bash
pip install jupyter
```

To run Jupyter Lab:

```bash
jupyter lab --port 6006 --ip $(hostname) --no-browser
```

## Setup online radial integration on Jungfraujoch

1. **Calibrate the detector using pyFAI.**

   Analyze a calibration scan carefully with `pyFAI` and save the resulting **PONI** file and **pixel mask**. Also determine the beam center position.

   :::{note}
   As of 2026-06-18, Jungfraujoch only accepts `uint32` TIFF mask files. If the mask generated by `pyFAI` is stored as `uint8`, it needs to be converted to the required format before uploading.
   To do this (from the home directory `/sls/x12sa/data/[p-group]/raw/`):

   - Activate the python environment: `source mask/.mask/bin/activate`
   - Run `python convert_mask_format.py -i <input .tif file path> -o <output .tiff file path>`
   :::

2. **Update the BEC configuration.**

   Update the detector distance and beam center coordinates in the BEC configuration files using the calibration results.

3. **Configure Jungfraujoch.**

   Open the **Jungfraujoch Expert Configuration** panel in the frontend interface, for example:

   ```text
   http://sls-jfjoch-001:8080/frontend
   ```

   - Upload the pixel mask under **Pixel Mask**.
   - Fill in the required parameters under **Azimuthal Integration Settings**.
   - Make sure to enable **Force CPU calculation in FPGA workflow**.
   - After uploading a new configuration, do not press "initialize", as this will remove all the previously uploaded configuration.

4. **Detector rotation (if required).**

   :::{note}
   Adding rotation of the detector still needs to be documented (likely configured in the BEC configuration).
   :::