Version 1.1.0

Updated default settings to larger model architecture, modified positional encoding, and accelerated training:

• Mixed precision training is now turned on by default (Use --no-amp to revert to single precision training)
• Encoder/decoder architecture is now 1024x3 by default (Use --enc-dim 256 and --dec-dim 256 to revert)
• Gaussian Fourier featurization for faster training and higher resolution density maps (Use --pe-type geom_lowf to revert)

Version 1.0.0

Release for version 1.0.0

NEW: cryodrgn analyze_landscape for automatic classification and energy landscape inference
NEW: Faster training and higher resolution model with Gaussian Fourier featurization (Use --pe-type gaussian)
NEW: cryodrgn_utils <command> -h for standalone utility scripts
NEW: cryodrgn_utils write_star for converting cryoDRGN particle selections to .star files
Add pytorch native mixed precision training and fix support for pytorch 1.9+

Version 0.3.4

Updates to auxiliary scripts

• FIX: Bug in write_starfile.py when provided particle stack is chunked (.txt file)
• Support micrograph coordinates and additional column headers to write_starfile.py
• New helper scripts: analyze_convergence.py (in beta testing) contributed by Barrett Powell (thanks!) and make_train_test.py for splitting up particle stacks for training

Version 0.3.3

cryoDRGN version 0.3.3b

• Faster image preprocessing and smaller memory footprint
• New: cryodrgn preprocess for large datasets (in beta testing - see here for details)
• Known issue with PyTorch version 1.9+

(Version 0.3.3b patches a minor argument naming bug for --lazy)

Version 0.3.2

Minor updates to 0.3.1 software

• New: Additional Jupyter notebook for particles filtering, cryoDRGN_filtering.ipynb
• New: cryodrgn view_config
• Fix: Compatibility and deprecation fixes with pytorch 1.7 (#29), scipy (#39), and seaborn (3111efd)
• Updated: More functionality for converting to starfiles with write_starfile.py (#44)
• Performance improvements to cryodrgn eval_vol and a minor fix for a corner case (#33)
• Note: The logged KL divergence in stdout is no longer scaled by beta, however the default objective is identical

Version 0.3.1

Minor update to v0.3 software:

• New script write_starfile.py to save selected particles as a .star file for use in other tools
• Improvements to cryodrgn analyze

Version 0.3.0

• New: GPU parallelization with flag --multigpu
• New: Mode for accelerated mixed precision training with flag --amp, available for NVIDIA tensor core GPUs
• Interface update:
  • Renamed encoder arguments --qdim and --qlayers to --enc-dim and --enc-layers
  • Renamed decoder arguments --pdim and --players to --dec-dim and --dec-layers
• Argument default changes:
  • Flipped the default for --invert-data to True by default
  • Flipped the default for --window to True by default
• Updated training recommendations in below quick start guide
• Updates to cryodrgn analyze
  • More visualizations
  • Order kmeans volumes according to distances in latent space (previously random)
  • More features for particle selection and filtering in the Jupiter notebook