bo-ptycho/readme.md

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
2. Download fold_slice
3. Download experimental data

Reconstruction and parameter optimization:

1. Edit 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
   • 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