# bo-ptycho

This code is a (re)implementation of Bayesian Optimized ptychography in python for use at LEMON lab, used for

- Optimization-based Thickness Estimation and FIB-induced Damage Characterization of TEM Sample via Multislice Electron Ptychography (manuscript)



## Code usage

Prerequisites:
1. Create a python virtual environment with [requirements.txt](./requirements.txt)
2. Download [fold_slice](#)
2. Download [experimental data](#)

Reconstruction and parameter optimization:
1. Edit [config.yaml](./config.yaml)
    - Example configurations can be found under `examples/silicon-fib/`
    - Set io.input_data_path and io.result_dir as needed (WARNING: the result directory will be completely removed)
    - Set ptycho.path to your fold_slice path
2. Edit [job.sub](./job.sub)
    - Set the SBATCH configurations as needed (especially `gres` and `output`)
    - The number of GPUs should match bo.batch in config.yaml
    - Set the virtual environment path
    - Set the config.yaml path
3. Submit the job via SLURM