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27 lines
1.0 KiB
Markdown
27 lines
1.0 KiB
Markdown
# bo-ptycho
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This code is a (re)implementation of Bayesian Optimized ptychography in python for use at LEMON lab, used for
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- Optimization-based Thickness Estimation and FIB-induced Damage Characterization of TEM Sample via Multislice Electron Ptychography (manuscript)
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## Code usage
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Prerequisites:
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1. Create a python virtual environment with [requirements.txt](./requirements.txt)
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2. Download [fold_slice](#)
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2. Download [experimental data](#)
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Reconstruction and parameter optimization:
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1. Edit [config.yaml](./config.yaml)
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- Example configurations can be found under `examples/silicon-fib/`
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- Set io.input_data_path and io.result_dir as needed (WARNING: the result directory will be completely removed)
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- Set ptycho.path to your fold_slice path
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2. Edit [job.sub](./job.sub)
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- Set the SBATCH configurations as needed (especially `gres` and `output`)
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- The number of GPUs should match bo.batch in config.yaml
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- Set the virtual environment path
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- Set the config.yaml path
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3. Submit the job via SLURM
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