added README and license

readme.md

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+# 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