Deep Reinforcement Learning for Data-Driven Adaptive Scanning in Ptychography

These are the data sets used for the publication https://arxiv.org/abs/2203.15413.

In more detail, the DataFile.pkl files in the training_data and testing_data folders are the actual data, including diffraction patterns, the corresponding reconstructions and the used illumination probe. The folders dwcnt_training_data and dwcnt_testing_data include the data sets of the simulated double-walled carbon nanotube.

The reconstruction folder includes the source code of the reconstruction algorithm ROP and the used parameter files.

The results folder includes the updated weights of the network model and the reconstructed potentials for the 25 test data sets used in the comparison of the publication.

The sequence_grid.npy file stores the sparse grid scanning sequence used for initialization and comparison as described in the publication. The dwcnt_sequence_grid.npy file is the corresponding file for the double-walled carbon nanotube data.

If you want more information, please contact the corresponding author of the publication, at schlozma@hu-berlin.de.