# Changelog

All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [0.1.0b12] - 2025-09-30
### Added
- Add `pos_recenter` constraint to remove potential global offset from cropping positions. This will help keeping probe, position, and object relatively in place.
- Add `get_error_distribution.ipynb`, `read_ptyrad_output_hdf5.ipynb`, and `get_local_obj_tilts.ipynb` (issue #15) to `demo/scripts/analysis/`
### Changed
- Refactor `plot_probe_modes` so it can take either 1 or 2 input probes for easier visualization
- Fix incorrect probe shifting direction in `obj_z_recenter` so it can shift the object and probe correctly
- Explictly assign device for `near_field_evolution_torch` in `obj_z_recneter` constraint so it can correctly work on multi-GPU machines when assigned device != 'cuda'
- Improve `obj_z_recenter` constraint by approximating `torch.quantile` so it can operate on large tensors with more than 16.7M elements; Add `approx_torch_quantile` to `ptyrad.utils.math_ops`.
- Fix missing cache initialization in `init_cache` for `init_obj_tilts` as mentioned in issue #24 by @yifengh3
- Rename `probe_add_df` into `probe_z_shift` for clarity as mentioned in issue #18. Positive value means propagate the probe forward (increasing z depth).
- Fix a torch.compile edge case in `get_probe`s when position learning rate = 0. len(indices) would be treated incorrectly as a FakeTensor despite it should just be an int from len(np.ndarray).
- Remove a pair of fftshifts in `imshift_batch` and adjust the k-space grid accordingly in `create_grids`. This improves the forward pass efficiency without affecting the reconstruction.
- Allow `pruner_params` to be null during pydantic validation as mentioned in issue #20 by @GeriTopore

## [0.1.0b11] - 2025-08-21
### Added
- Add `obj_z_resample` preprocessing to `init_params` so we can reslice the object along depth dimension to adjust the slice thickness without changing total thickness. This is useful for refining an existing multislice restruction with finer slices as mentioned in issue #5, or to convert between single <-> multislice object
- Add `obj_z_pad` preprocessing to `init_params` so we can pad more depth slices with 'vacuum', 'mean', or 'edge' options. This is useful for re-centering or expanding the loaded/initialized object along depth as mentioned in issue #5, or to quickly experiment the total thickness.
- Add `obj_z_crop` preprocessing to `init_params` so we can remove unwanted depth slices. This is useful for re-centering the loaded/initialized object along depth as mentioned in issue #5
- Add `obj_z_recenter` constraint to keep the multislice object centered within depth by measuring object CoM and adjusting probe defocus accordingly. This is useful when there're vacuum region around the object. This is in response to issue #5 suggested by @HanHsuanWu.
- Add `probe_add_df` to `init_params` so we can adjust defocus of loaded probe, which could help the multislice object z-recentering; Add `add_df` as new hypertunable params to sweep additional defocus of loaded probe; Add `probe_add_df` to the illumination preset of `recon_dir_affixes` for folder name
- Enable `probe_pmode_max` and `obj_omode_max` to automatically pad the mixed states if the loaded probe/object has fewer modes than the specified number of modes as suggested by @Xinyan-Li; Add numpy version of `orthogonalize_modes_vec_np` and `sort_by_mode_int_np` to utils; improve `check_modes_ortho` with automatic np.ndarray-to-torch.tensor casting
- Enable `start_iter`, `step`, and `end_iter` for more flexible control of iter-wise constraints. This change is backward compatible. Original key of `freq` is still supported but is deprecated and will be removed in future
- Improve reproducibility by adding `--seed` to CLI argument and `init_params.random_seed` to params file. Randomness includes object and position initialization, measurements Poisson noise, batches, and shuffling, etc. The seed is automatically set to 42 if not specified in multiGPU optimization, where we need exact same initialzation across devices.
- Enable `start_iter` for torch.compile and multiGPU in response to issue #13 via manual recompilation; Add `end_iter` to `update_params` to further control grads for optimizable tensors
### Changed
- Change the appended digit of scan affines for clearer display. scale and asymmetry has been changed from `.2g` to `.2f`, while rotation and shear are changed from `.2g` to `.1f` so 3-digits angle like 179.5 degree can be displayed properly.
- Improve `init_calibration` logging clarity by displaying the final RBF, Npix, and suggested probe_mask_k radius after meas_resample despite resampling won't change the ratio

## [0.1.0b10] - 2025-07-23
### Added
- Add `compiler_configs` to `recon_params` to allow optional PyTorch JIT compilation for significant speedup (1.9x faster on PSO tested on A100 20gb MIG). Special thanks to @dy327 and @guanxing.li for helping me testing on macOS and Windows machines! Currently the `torch.compile` works for Windows, macOS, and Linux, although it has a bit more hardware/firmware requirements including:
  - Windows users would need to install `triton-windows` 
  - NVIDIA GPU needs to have Compute Capability >7.0 (Volta architecture or newer).
  - NVIDIA GPU needs to get a more modern driver version, 520.61.05 is known to be not working.
### Changed
- Add CUDA Compute Capability and `torch.compile` Triton info to `print_gpu_info`
- Improve `print_system_info` by adding `platform.platform()` to show user-facing macOS version string
- Fix incorrect MPS device count for macOS in `set_accelerator` so the CLI command of `ptyrad run` can pass the accelerator initialization
- Add CPU fallback to `orthogonalize_modes_vec` since MPS doesn't seem to have implemented `torch.linalg.eig` yet as pointed out by @dy327
- Fix incorrect type check for `init_tilts` to allow float values of initial tilts as pointed out by @dy327

## [0.1.0b9] - 2025-07-10
### Changed
- Update README with new installation guide and references to docs, youtube, and other links
- Change the output shape of propagated probe amplitude from a binned 2D tableau into a 3D stack
- Fix incorrect caching of H for an edge case of fixed but non-zero pos-dependent tilts; Fix incorrect indexing for `model.get_propagated_probe` of pos-dependent tilts; Refactor and improve `model.get_propagators` by unifying grid usage; Remove unused propagator-related functions from `utils.physics.py`
- Allow `plot_obj_tilts` and `plot_slice_thickness` to savie figures even for fixed tilts and thickness by appending results to model regardless; Add a safety guard to skip quiver plot of effective 0 tilt; Update demo params files comments regarding available selected_figs; Update recon_params to add the missing figure options
- Update `FilePathWithKey` in `init_params.py` so we can load '.raw' file with arbitrary shape, offset, and gap
- Fix incorrect modes orthogonalization (missing .conj()) in `orthogonalize_modes_vec` in response to issue #11 as pointed out by @dong-zehao. This error doesn't negatively impact results but just produce probe modes that aren't really orthognal with each other; Update check_modes_ortho in utils.dev_tools.py so it can check complex modes as well

## [0.1.0b8] - 2025-07-02
### Added
- **Add `params/` module to enable params default filling, type check, and validation via pydantic**. This adds a new dependency (`pydantic`) but greatly enhances the robustness of PtyRAD and promotes "fail early" philosophy reggarding params configuration. Default filling makes it possible to create a minimal params file with ~ 15 fields. The validation would check for variable types, option availability, and file existence, etc.
- Add demo `tBL_WSe2_reconstruct_minimal.yml` params file for demonstration
- Allow `tilt_source` to take `file` option so we can load object tilts from file. This is suggested by @zb87
- Add `meas_normalization` option to demo params files
- Add 'force' boolean option to `meas_remove_neg_values` so that we can subtract values from measurements without negative values
- Add versioning strings to demo params/notebooks for calrity
- Allow fine-grained control of output folder name by adding high-level presets including 'minimal', 'default', and 'all' to `recon_dir_affixes` in `recon_params` while supporting 16 individual control options as well. **High-level presets would introduce a breaking change for previous params files.** 
### Changed
- Update `load_params` to include the validation logic and option
- Update CLI `run` to include optional validation (--skip_validate)
- Update CLI `validate-param`s command so we can simplify validate the params files in command line
- Simplify `_process_meas` by removing unnecessary neg correction and normalization
- Improve `_meas_add_poisson_noise` by adding built-in negative values check and switching to global normalization to maintain relative intensity between each pattern
- Move Slurm scripts to demo/scripts for simplicity
- Change `prefix_date` option in `recon_params` into `prefix_time` to enable more control of the time format prepended to the output folder name. Default time format is 'date' for output folder, and 'datetime' for the output log file. **This introduces a breaking change for previous params files.** 
- Fix `_tilt` recon folder name appending when 'tilt_type' : 'each' otherwise it was appending all (N,2) values

## [0.1.0b7] - 2025-05-30
### Added
- Add CLI command `ptyrad export-meas-init` to allow quick exporting initialized measurement arrays to disk with specified file types (.mat, .hdf5, .tif, .npy)
- Add utils functions `get_nested` and `list_nested_keys` to better handle nested dicts / HDF5 files
- Add `meas_export` to `init_params` so we can export the PtyRAD initialized diffraction patterns for further processing, analysis, or visulaization if needed. Currently supporting hdf5, tif, and npy that can be directly ported into `py4D-browser`.
- Add `is_mig_enabled` util function and improve the overall error message related to multiGPU
- Add `Nlayer` to hypertune optimizable params as suggested by @zb87
### Changed
- **Switch the PtyRAD model output from .pt to .hdf5 for better interoperability.** Previous .pt files are still supported via the wrapper function `load_ptyrad`. The full (de)serialization process is handled by `save_dict_to_hdf5`, `tensors_to_ndarrays`, `handle_hdf5_types`, and `ndarrays_to_tensor` specifically for optimizer state dicts
- Significantly refactor and enhance `load_hdf5` and `load_mat` to handle different file version, list of keys and specified delimiter for nested keys
- Allow key-less data loading for .mat and .hdf5, so users don't necessarily need to specify a key when loading diffraction patterns. Add a general purpose `load_measurements` function in `load.py` to automatically detect file extension and dispatch. This change is inspired by [py4D-browser](https://github.com/py4dstem/py4D-browser).
- Internal clean up of the `model.forward` method to only return diffraction patterns. The object patches are cached in `model._current_object_patches`. An intermediate wrapper function `model.get_forward_meas` is added
- Fix incorrect `dz` intermediate output folder name in hypertune mode from [issue 4](https://github.com/chiahao3/ptyrad/issues/4) pointed out by @HanHsuanWu

## [0.1.0b6] - 2025-05-24
### Added
- Add `__main__.py` to allow `python -m ptyrad`. Now we can execute `ptyrad` package as a module/script for `accelerate launch`.
- Add `.github/workflows/publish_pypi.yml` for automation. Future release will automatically be published to PyPI. 
### Changed
- Fix `set_gpu_device` so we can properly return `device=None` to allow `accelerate` setting devices for multiGPU. The `--gpuid` argument can now take `'acc'`, `'cpu'`, and integers for GPU ID, which is still backward compatible. This hotfix is motivated by the question of multiGPU raised by @ccs1019.
- Update `slurm_run_ptyrad.sub` with clearer comments about the normal and accelerate (multiGPU) modes.
- Update `pyproject.toml` for the PyPI (pip) publishing. The dependencies are moved to the core list so `pip install -e . --no-deps` is now preferred to prevent `pip` from pulling packages.
### Removed
- Remove `scripts/run_ptyrad.py` script because it's completely covered by the `ptyrad run` CLI command for reconstruction, hypertune, and accelerate (multiGPU) modes.

## [0.1.0b5] - 2025-05-20
### Added
- Add `meas_calibration` option into the params yml file to enable calibration using 7 different units, or to directly fit the experimental data. This change is strongly advised by @noahschnitzer, @ecchung, and @shaqekar!
- Add `dx` as a hypertunable parameter, although technically one should do the kMax calibration and fix the dx value for each collection angle, and use hypertune for scan affine transformation
- Add `append_params` boolean flag to `hypertune_params` so we can optionally append the hypertune params to the collate results. This is advised by @shaqekar and @YinChen!
- Add the Command Line Interface (CLI) tools as `cli.py` module. We can call `ptyrad run --params_path <PARAMS_PATH> --gpuid 0` from anywhere, or call `ptyrad check-gpu` to quickly check whether GPU-supported PyTorch is installed or not. This is suggested by @sezelt!
- Add `envs/` to keep CUDA-specific environment.yml files. Set suggested versions to CUDA 11.8, Python>=3.10, <3.13. and pytorch>=2.0, <2.7 for maximal compatibility. This is motivated by @dasol-yoon!
### Changed
- Fix the potential mismatch from rounding Npix during `meas_resample`. This was first pointed out by @ecchung!
- Improve `init_initialization` process significatly, especially the `init_calibration` logic with `init_measurements`.
- Add `safe_filename` to `utils/common/` so we can correct illegal filenames (total length and component length) across different platforms, extra str except file extension would be clipped, this should completely prevent the file name too long error especially on Windows.
- Enable proper pip install via `pip install .` by modifying the `pyproject.toml` Thanks @ercius for pointing this out!
- Split `print_gpu_info` and `print_packages_info` out of `print_system_info` for clarity and allow easier check via CLI. Also improve the printed message and format a bit.
- Enhance error messages about missing fields and shape mismatch of `load_meas` and `_process_meas` of `init_measurements`. This is motivated by @PhysX.
### Removed
- Remove `probe_dx` option from params yml and incorporate it into `meas_calibration`. Note that `dx` is still used internally by PtyRAD as the only calibration metric.

## [0.1.0b4] - 2025-05-12 (soft public release)
### Added
- Add `demo/` folder to organize demo-specific data, params, and notebooks
- Add `LICENSE`, `CONTRIBUTING`, and `WISHLIST.md`
- Add `load_toml` for supporting .toml params file
- Add `environment_ptyrad.yml` for ease of creating Python environment
### Changed
- Slight restructure of the params file format of `init_params`, this will cause BREAKING CHANGES so all users need to update their current params files
- Major refactoring of the `initialization.py` module internally for clarity and future extensibility
- Change the repo to `src/` layout for more install and import robustness
- Change the `utils.py` into a `utils/` module for better organization, split off the `save.py` module
- Change the `data_io.py` into `load.py`
- Split `optimizaiton.py` module into `losses.py` and `constraints.py`
- Refine `README.md` for more comprehensive step-by-step guide
### Removed
- Remove `notes/` and `scripts/analysis/` for clarity in the soft public release
- Remove paper related figure notebooks as they'll be included in final Zenodo record and another repo

## [0.1.0b3.dev3] - 2025-04-26
### Added
- Add `Git_workflow.md`, `CONTRIBUTING.md`, and `WISHLIST.md` drafts
### Changed
- Modify `set_gpu_device` to add automatic support for Apple Silicon (MPS) GPUs.
- Fix `UnicodeDecodeError` by specifying UTF-8 encoding when loading YAML / JSON params files on non-UTF8 terminals
- Add paper figure saving as pdf and png with 600 DPI
- Fix hypertune when no pruner. The final optuna_error should only be calculated when pruner = None. Thanks to @noahschnitzer
- Update `pyproject.toml` with the PEP 440 valid versioning and installation setup for `pip install -e .`
- Change the versioning `v0.1.0-beta3.3` -> `0.1.0b3.dev3` to get `pyproject.toml` install working. 

## [v0.1.0-beta3.2] - 2025-04-11
### Added
- Add `simulate_tBL_WSe2_4dstem` and `preprocess_simulated_4dstem` notebooks and script to `scripts/paper` to generate simulated data with abTEM
- Add `meas_pad` to `exp_parmas` with both 'precompute' and 'on_the_fly' mode. The 'padding_type' can be 'constant', 'edge', 'linear_ramp', 'exp', and 'power'. This allows flexible diffraction padding to conveniently change the real-space object pixel sampling.
- Add options to `objp_postiv` constraint, including 'mode': 'subtract_min' and 'clip_neg'. The default is 'clip_neg' because it performs much better than 'subtract_min'. The 'subtract_min' option is added mostly for completeness.
- Add `padding_with_fitted_background` notebook to `scripts/analysis/` to show the fitting process
- Add `figure_kz_series` notebook to `scripts/paper/`
- Add `mfft2` (the P+S decomposition) and `center_crop` to `utils` for cleaner figure notebooks
### Changed
- Fix the incorrect unit conversion of `meas_add_source_size` for partial spatial coherence. It was applying source size effect incorrectly as ang / scan_step_size. This would make an intended 0.34 Ang std with 0.4 Ang scan step size becomes effectively 0.34 scan step size, so 0.136 Ang std.
- Fix `model.probe_int_sum` so it takes the padded background into account during 'on-the-fly' padding mode.
- Modify the `get_loss_pacbed` so it's normalized by data_mean as well just like other losses.

## [v0.1.0-beta3.1] - 2025-02-13
### Added
- Add `create_optuna_sampler` and `create_optuna_pruner` to allow flexible hyperameter tuning algorithm cofigurations in Optuna. The chosen sampler/pruner names will be affixed to the hypertune result folder.
- Add new hypertunable parameters including PyTorch optimizers, learning rates, batch sizes, and number of probe modes.
- Add `params/paper` to keep the params files used in the paper
- Add `docs/20241202_packages_iter_times/` for the package iteration time benchmarking
- Add `docs/20241215_multiGPU/` for multiGPU benchmarking
- Add `docs/20241219_GPU_comparison/` for GPU performance comparison
- Add `scripts/paper/` to keep the scripts used in the paper
- Add `meas_remove_neg_values` option so that we can choose whether to clip the negative values or subtract the minimum. Original default behavior is subtracting the minimum value, while clipping negative values behaves better for low dose data. NOTE that the default behavior of PtyRAD has changed from `subtract_min` to `clip_neg` to support better convergence.
- Add `timeout` to `hypertune_params` so that we can limit the overall time for a hypertune study
- Add `optim_state` as a new saving option to `save_result`. This changes the default saving behavior of `model` so if `optim_state` is not specified, the saved `model.pt` is roughly 40% of the file size comparing to the model with an Adam state dict using the default history setting.
- Add `tilt_avg` to `selected_figs` in `recon_params` so we can visualize how averaged tilt_y, tilt_x evolve with iterations when optimized with AD.
- Add a new unit in `meas_add_poisson_noise` so we can apply Poisson noise with either `total_e_per_pattern` or `e_per_Ang2`
- Add `complex_ratio` and `mirrored_amp` into `constraint_params` as initial attempts to constrain object amplitude based on object phase, which should help the doughnut issues in thick samples or samples with heavy atoms
### Changed
- Reformat the `'tune_params'` for hypertune mode so users can freely set the Optuna suggesting int, float, or categorical values and pass whatever keyword arguments (`kwargs`) for maximal flexibility and future compatibility. This allows users to use smart samplers to navigate a discrete search space defined arbitrarily if the users specify the 'choices' when using `'suggest': 'cat'` for categorical values. The alternative approach for discrete search space would be to use `GridSampler` but it's as inefficient as `BruteForceSampler`
- Refine `optuna_objective` to take the updated `'tune_params'` format
- Update the `hypertune_params` for demo params files
- Simplify `load_fields_from_mat` by calling the updated `load_hdf5` so matlab file version 7.3 can be loaded in a unified way with normal hdf5
- Update `initialization.py` so `PtyShv` can be loaded correctly with either matlab file version 7.3 or older versions. Special handling is necessary because matlab file version 7.3 will be loaded by `load_hdf5` using  `h5py` and the array would be loaded using C-order, which is reversed from the normal matlab F-order. Complex array would also be loaded as nested array hence special casting is needed.
- Refine `load_raw` by adding a file size check. If the specified shape gives a file size different from the actual file size, it will raise an error immediately
- Improve information logging in hypertune mode by printing relevant configurations
- Improve information logging of `init_measurements` in the Poisson noise simulation and normalization parts
- Improve information logging of `loss_params` and `constraint_params` by printing relevant configurations

## [v0.1.0-beta3.0] - 2024-11-26
### Added
- Add `LBFGS` as available optimizer option. LBFGS is a Quasi-Newton 2nd order optimizer that was designed for full-batch update scheme and converges very fast on certain convex problems. While generally it requires full-batch update and ideally noiseless gradients, it's included for completeness and certain special cases.
- Add `.json` as supported params file type in hope of better support for LLM-related interfaces
- Add `slice_thickness` as an AD-optimizable parameter and rename most `z_distance` into `slice_thickness` for clarity.
- Add `plot_slice_thickness` for visualization
- Add `npy` as the new measurements data type into `data_io.py` and `initialization.py`
### Changed
- Refine `near_field_evolution` (Fresnel propagator) for performance and simplify the function signature.
- Refactor `recon_step` and `recon_loop` a bit by moving `iter_times`, `loss_iters`, and `dz_iters` all inside `recon_step` since they'll be stored in `model` for every iteration
- Simplify the function signature of `save_results`, `make_save_dict`, and `plot_summary` by moving the iter-result-lists inside `model`
- Fix the `model_instance` usage in `recon_step` for multiGPU mode (`model.module` is required due to DDP wrapping). Note that `start_iter` currently doesn't work properly in DDP mode (multiGPU).

## [v0.1.0-beta2.10] - 2024-11-06
### Added
- Add `CustomLogger` to notebooks/scripts to log the Python terminal stdout specifically to a log file under the reconstructed folder. If `SAVE_ITERS = None` and no output directory is generated, the log would be saved to `logs`.
### Changed
- Fix the printing error when using `GROUP_MODE = 'sparse'` by making `sparse_batches` a list of arrays so we can do `batch.tolist()` for cleaner printing of the batch_t
- Change the default update step size for `py4dstem` scripts to 0.1 for numerical stability, otherwise the default 0.5 would easily give NaNs on my tBL-WSe2 dataset. Thanks the input from @sezelt
- Simplify `run_py4dstem.py` and `run_py4dstem_detailed_walkthrough.ipynb` by calling the v0.0.2 version of locally modified py4DSTEM repo 
- Move `scikit-learn` as optional dependency because it's only used for compact/sparse grouping
- Add `self.optimizer` to PtychoAD object so we can retrieve optimizer after the reconstruction

## [v0.1.0-beta2.9] - 2024-10-17
### Added
- Add `py4DTEM` as a new source for object, probe, and positions in params file with inputs from @dsmagiya
- Refine `run_py4dstem.py`, `slurm_run_py4dstem.sub`, and `run_py4dstem_detailed_walkthrough.ipynb`
- Add `probe_prop` as a new option for `save_result` list. It'll save a 2D montage of (Nz x Ny, pmode x Nx) to show how the probe modes propagate through the object
### Changed
- Modify `load_hdf5` so that it can return the entire dict if `dataset_key = None`
- Add a `with torch.no_grad()` block for the saving/plotting block to locally disable autograd
- Move the `init_accelerator` from `PtyRADSolver` class to `utils` to reduce duplicated printing because DDP is only initialized after initializing `accelerate`
- Change the interpolation mode for on-the-fly resampling (torch.nn.functional.interpolate) from 'area' to 'bilinear' to avoid the edge artifact in reconstructed probe 

## [v0.1.0-beta2.8] - 2024-10-14
### Added
- Add x-ray ptychography capability to PtyRAD with the help from @ameyluktuke, @xyin-anl, and @yijiang1
- Add `simu_xray_ptycho.yml` and demo data for x-ray ptychography
- Add `make_fzp_probe` to `utils.py` to simulate x-ray probe generated by Fresnel zone plates
- Add `foldslice_hdf5` as a new position source for most APS instruments that generate hdf5 position files. The hdf5 files are commonly handled in `fold_slice` using `p.src_positions = 'hdf5_pos';`
### Changed
- `illumination_type` is now a required field in the `exp_params` dict inside the yml param files
- Modify `initialization.py` to be compatible with x-ray ptycho including `init_exp_params`, `init_measurments`, `init_probe`, `init_pos`, `init_obj`, and `init_H`

## [v0.1.0-beta2.7] - 2024-10-05
### Added
- Add on-the-fly measurements resampling into `meas_resample` to reduce GPU VRAM usage with negligible performace impairment
- Add `20241005_effect_of_cpu_cores/` under `docs/`
### Changed
- Update `time_sync` by replacing `time.time()` with `time.perf_counter()` so that it can better measure events that are shorter than 1 ms.
- Let `PtyRADSolver.reconstruct()` create an attribute of reconstructed `PtychoAD` model called `PtyRADSolver.reconstruct_results` so that we can do some further work if needed
- Modify `accelerate` branch so that the HuggingFace `accelerate` package becomes optional and can work on environments without `accelerate` installed. This makes it possible to merge `accelerate` branch into `main` and allow Windows users to at least run `PtyRAD` on a single GPU using the exact same codebase.
- Modify `imshift_batch` so that PtyRAD is compatible with older Python version < 3.11 as well
- Simplify the output message of `set_gpu_device()`
- Merge `accelerate` branch into `main` so that it's easier to maintain. Windows users without NCCL do not need to install `accelerate` package, and they can still use a conda environment without `accelerate` to execute PtyRAD from `main` branch

## [v0.1.0-beta2.6] - 2024-09-30
### Added
- Add `--gpuid` as a command line argument for `run_ptyrad.py` @sezelt
- Add `set_gpu_device` to `utils` for cleaner `run_ptyrad.py` script
- Add `c5` explicitly under `exp_params` so we have more control on simulated initial probe
- Add `c3` and `c5` into hypertunable params @sezelt
- Enable `'step': null` inside `'tune_params'` for continuous parameter space in hypertune mode @sezelt
- Add multi-GPU and mixed-precision capabilities via HuggingFace `accelerate` package. This is implemented in a separate branch `accelerate` and would require a different environment.
### Changed
- Update `get_default_probe_simu_params` to take in 'c5' from `exp_params` as well
- Update `make_output_folder` to include c3, c5 values under the `init` condition inside `recon_dir_affixes`
- Update `make_stem_probe` with more robust param parsing @sezelt
- Update `run_ptyrad` script and notebooks, and `slurm_run_ptyrad.sub` accordingly

## [v0.1.0-beta2.5] - 2024-09-19
### Added
- Add `optimizer_params` dict under `model_params` in the .yml params file to support more PyTorch available optimizers with configurations and allow loading the optimizer state
- Add `create_optimizer` function under `optimization.py` for arbitrary PyTorch optimizer creation with configurations
- Add `grad_accumulation` into `BATCH_SIZE` so we can approximate large batch size that doesn't fit into memory by accumulating gradients from many sub-batches. This is essentially a "memory-save" mode for PtyRAD
### Changed
- Refine the `plot_forward_pass` default indices generation method so it works better for different INDICES_MODE
- Update `make_output_folder` so the optimizer name can be optionally affixed
- Change `make_save_dict` and `save_results` so that it saves the optimizer state into `model.pt` as well
- Rename `model.set_optimizer_params` into `model.create_optimizable_params_dict` for clarity
- Move some jupyter notebooks into `scripts/analysis/` for clarity
- Move `spec-file_ptyrad.txt` to new folder `envs/` for clarity

## [v0.1.0-beta2.4] - 2024-09-17
### Added
- Add an `'obja'` option to the `save_results` to allow saving the object amplitude. 
### Changed
- Change the `plot_forward_pass` default behavior in `plot_summary` from random indices to fixed indices so the reconstruction progress can be better observed by visualizing the same region throughout the run.
- Fix normalization error of `'bit: ['raw']` in `'result_modes'` since beta2.2 (2024-09-03). It was incorrectly normalizing the tif outputs from 0 to 1 when it should be outputting the original range. The output figure like `forward` and saved optimized tensors in `model.pt` were not affected by this error.

## [v0.1.0-beta2.3] - 2024-09-13
### Added
- Add a simple notebook `check_sqlite.ipynb` to check duplicated params in sqlite database for hypertune mode, though the duplicatation is an expected behavior for BO algorithm
- Add `raw` as new measurement data source to handle EMPAD and pre-processed EMPAD2 4D-STEM datasets
- Add `power_thresh` to `probe_mask_k` constraint so we can select how much probe modes should be masked in k-space
### Changed
- Specify the file_path in all loading functions in `data_io` when there's a `FileNotFoundError`
- Add `indices` into the argument of `make_save_dict` so that the selected probe position indices are saved into `model.pt` as well. This enables more convenient custom object cropping.
- `lr_params` is merged with `start_iter` and renamed to `update_params` under `model_params` to add extra control over when to start optimizing the optimizable tensors
- modify `make_output_dir` to affix non-zero `start_iter`, also change the `lr` affix to non-zero learning rates only

## [v0.1.0-beta2.2] - 2024-09-03
### Added
- Add a default `/data` folder with txt instruction
- Add `demo` under `params` with a couple tBL_WSe2 examples
- Add `run_PtyShv.m` and `slurm_run_PtyShv.sub` for direct comparison with PtychoShelves
- Add `copy_params` boolean to `recon_params` to copy the params files to the output directories for better record keeping
- Add `save_results` list to `recon_params` to specify which result (obj, probe) to save
- Add `result_modes` dict to `recon_params` to specify the dimension of output object and whether to postprocess (crop, bit depth) the result before saving
- Add `collate_results` boolean to `hypertune_params` to specify whether to collect hypertune results under `output_dir`
- Add `parse_sec_to_time_str` to `utils` to display the solver time and iteration time in flexible time string from days, hours, mins, to secs
- Add full description to every entry in the params file
### Changed
- Move `subscan_slow` and `subscan_fast` under `INDICES_MODE` for (hopefully) clarity
- Let `load_params` add additional entry of `params_path` to the params dict before return for easier usage of `copy_params`
- Absorb `--hypertune` and `--quiet` into the params file, simplifying the scripts and letting the entire recontstruction behavior controlled by params file
- Drop the `_optuna` suffix in `README.md` and `spec-file.txt` for simplicity
- Simplify the installation guide in `README.md`
- Rename `fig_list` to `selected_figs` for clarity
- Rename `dir_affixes` to `recon_dir_affixes` for clarity
### Removed
- Remove `probe_simu_params` from `exp_params` because it's duplicated with `probe_params` in `source_params`

## [v0.1.0-beta2.1] - 2024-08-28
### Added
- Add `get_scan_affine.ipynb` to quickly estimate the scan affine transformation for known crystal structure
- Add `decompose_affine_matrix` to `utils` to decompose an affine matrix into the 4 components
- Add `subscan_slow` and `subscan_fast` into `recon_params` for finer control of `INDICES_MODE` like `center` and `sub`
- Add `dir_affixes` to `recon_params` to enable flexible control of the output folder name with `make_output_folder`
- Add `defocus` and `conv_angle` to Optuna optimizable params in `hypertune_params` 
### Changed
- Fix `optuna_objective` so that the 4 components of `scan_affine` can be optimized independently
- Move `inputs` out of `ptyrad` core package and rename it as `params` for simplicity
- Rename the `full_params_xxx.yml` into `xxx.yml` for simplicity
- Modify `LoopSubmit.sh` so the 1st loop would wait 10 sec before the 2nd one to finish the database creation, which prevents the sqlite3 "table already exists error"
- Fix `make_mixed_probe` arguments with optional verbose

## [v0.1.0-beta2.0] - 2024-08-18
### Added
- Add hyperparameter tuning (Bayesian optimization and others) capability for `z_distance`, `scan_affine`, and `obj_tilts` with Optuna
- Add `reconstruction` module and `PtyRADSolver` wrapper class for a more compact workflow and streamlined interface
- Add `load_params` into `data_io`
- Add `.yml` as a new params file type. The original `.py` is still working but deprecated, might be removed before public release
- Add `vprint` as verbose print to `utils` to better control the verbosity of printed information (especially for hyperparamter tuning)
- Add a rough version of doc string for major classes and functions
### Changed
- Simplify the arguments for `save_results` and `make_save_dict`
- Rearrange the argument order of `plot_summary` and add default value to `fig_list`
- Refactor the `run_ptyrad` scripts and notebooks and move them into `scripts` 
- Move previous params.py files to `ptyrad/inputs/archive` and stop updating them
- Fix `make_output_folder` so that dz will only print 3 significant figures after rounded to 2 decimal points. So dz = 12.8 would be printed as 12.8 instead of 12.800000190734863.
- Add the `eps=1e-10` back to `multislice_forward_model_vec_all` in `forward` so that the `dp.pow()` is more numerically stable, especially for large collection angles with intensities near 0
### Removed
- Remove `rbf` from `exp_params` and `make_stem_probe`. This is to encourage/enforce users to calibrated their dk for each camera length to get `dx_spec`.
- Remove `make_recon_params_dict` from `utils`
- Remove `load_empad_as_4d` and `save_4D_as_hdf5` and other archived from `data_io` because we're not using it at the moment

## [v0.1.0-beta1.3] - 2024-07-10
### Added
- Add 4D-STEM preprocessing methods including `meas_crop`, `meas_resample`, `meas_add_source_size`, `meas_add_detector_blur`, `meas_add_poisson_noise` to `initialization` for better handling of input simulated 4D-STEM data. With these new methods, users can easily reconstruct with different 4D-STEM data conditions without manually generating and saving each 4D-STEM variants. We may create 4D-STEM datasets with different collection angles, k-space sampling, partial spatial coherence, detector blur, and noise level from a single dataset right before the reconstruction.
- Add `obj_preblur_std` to `model` for an effective real space deconvolution with a 2D Gaussian kernel. By pre-convolving the obj with a 2D Gaussian before simulating the diffraction pattern, the reconstructed obj is essentially the deconvolution version of the transmission function.
### Changed
- Rename `cbeds` variables/keys into `meas` or `DP` for generalizability. Changes are primarily made inside `initialization`, `optimization`, and `visualization` but you will need to modify the params files.
- Modify `make_output_folder` to include `obj_preblur_std` values
- Modify the gaussian_blur implementation in `loss_simlar` from a stack/list comp version to a reshape version and gets a 25% speed up (45 sec vs. 1min /iter)!
### Removed
- Remove `recenter_cbeds` in `model_params` because sub-px shifting noisy CBEDs is really not a good idea and leaves quite some artifact as well. We should directly handle the obj linear phase ramp from the off-centered CBEDs.
- Remove `run_ptyrad_local.py` for simplicity as I don't expect a lot of users would need it anymore. One can modify the atlas script by changing the path of `ptyrad` package.

## [v0.1.0-beta1.2] - 2024-06-05
### Added
- Add `obj_zblur` to `optimization` for a real-space substitution of `kz_filter`. By convolving a 1D Gaussian filter along z-direciton, we could remove the wrap-around while maintaining the z-regularization behavior. Note that there's no free lunch so instead of the wrap-around from `kz_filter`, the `obj_zblur` would still introduce edge effect due to the convolution. The default is "same" padding with "replicate" padding mode, so the object is padded with edge elements like abc|ccc, where | stands for the object edge 
- Add `get_decomposed_affine_matrix` to `utils` to quickly estimate the needed scan affine transformation components if we already have a reconstructed object and we know the ideal lattice constant and the angle between lattice vectors
### Changed
- Move `obj_tilts` to `source_params` so that we can decouple it with the `init_cache` and use it freely from scratch (e.g. start from random object, probe, pos but with known local tilts from previous reconstructions)
- Change the `measurements_params` for `'mat'` and `'hdf5'` from a `list` to a `dict` for better clarity, i.e. [path, 'cbed'] -> {'path':<path>, 'key':'cbed'}
- Modify `make_output_folder` to include `obja_thresh` values in accordance with the added `obj_zblur` feature. Because the `kz_filter` automatically contains a soft thresholding for obja so in order to fully replace it with `obj_zblur`, we'll need to additionally specify `obja_thresh` as well
- Decouple the obj tilts from `plot_scan_pos` by adding `plot_obj_tilts` to `visualization`

## [v0.1.0-beta1.1] - 2024-05-31
### Added
- Add `scan_rand_std` option to `initialization` for Guassian displacements of scan positions to reduce the raster grid pathology
- Add `loss_poissn` to `optimization` for loss calculation with Poisson noise statistics. This should be helpful for low dose data.
### Changed
- Add the `show_fig` flag and `plt.ioff` to `plot_pos_grouping` so that it's consistent with other plotting functions
- Remove the `os.environ["OMP_NUM_THREADS"] = "4"` in  `utils` since I somehow don't get the warning from `MiniBatchKMeans` anymore
- Add the description about reading py4dstem-processed .hdf5 with data key `'/datacube_root/datacube/data'` found by Desheng to `params_description.md`
- Rearrange output strings in `make_output_folder` and add keywords (`show_lr`, `show_constraint`, `show_model`, `show_loss`)to disable optional info like learning rates, constraints, detector blur, and losses

## [v0.1.0-beta1.0] - 2024-05-23
### Added
- Add `blur_std` option for `loss_simlar` so we could compare the std between Gaussian blurred object modes
- Add `kr_filter` as additional obj constraint to `optimization` so we could set our desirable maximum kr that contributes to the object image. Note that the positivity clipping could be doubling the apparent spatial frequencies
- Add `run_ptyrad_altas.py`, `run_ptyrad_local.py`, and `slurm_run_ptyrad.sub` as demo scripts
- Add `docs/` and `params_description.md` for some more explanation
### Changed
- Rename the `kz_filter` output folder string in `make_output_folder` from `kzreg` into `kzf` for simplicity, and to be consistent with `krf` for `kr_filter` 
- Change the `shift_cbeds` in `models` from `.abs()` to `.real.clamp(min=0)` because it seems that taking the real part of the complex Fourier filtered output from a real-valued input is a more correct approach
- Use the `plt.show(block=False)` flag for `plot_pos_grouping` so that the non-interactive python execution wouldn't be block by the `plt.show()` when executed from script
- Update `README.md` with the new conda install commands for local and altas usage

## [v0.1.0-alpha3.10] - 2024-05-20
### Added
- Add `load_PtyRAD` option for `obj_tilts` initialization in `exp_params` so we can reconstuct from previous PtyRAD runs with `opt_obj_tilts`
- Add `get_local_obj_tilts` estimation function into `utils`
- Add `get_local_obj_tilts.ipynb` notebooks to `scripts/` for interactive demonstration
- Update `CHANGELOG.md` and fill in previous record information for record keeping
### Changed
- Rename `source_params` keyword in `initialization` from `pt` to `PtyRAD` for clarity
- Change the comments in params files to hint the expected keywords for `obj_tilts`
### Removed
- Remove `z_pad` argument from `kz_filter` because it's not as helpful. The obj still shows artificial intensity decay for top and bottom layers for z_pad = 2 and 8 and can not fix the multislice obj wrap-around artifact
- Remove `pphase_smooth` constraint because it's not as helpful. Naively modifying (smoothing or scaling) the Fourier probe phase has a rough effect of focusing the real space probe and doesn't really stabilize the Fourer probe phase nor fixing the corner intensity problem

## [v0.1.0-alpha3.9] - 2024-05-16
### Added
- Add selective figure saving with `fig_list` to `plot_summary`
- Add `pphase_smooth` smooth with Fourier probe phase unwrapping and Gaussian smooth in hope of stabilizing the Fourier probe phase during optimization (doesn't help, will be removed by the next commit)
- Add an image overlay argument and dashed lines to `plot_sigmoid_mask` for better visualization
### Changed
- Rename `scan_flip` field in `exp_params` to `scan_flipT` to be consistent with `cbed_flipT` and the PtychoShelves convention of [flipup, fliplr, transpose]
- Update all params files to be consistent with the new `scan_flipT` field
### Removed
- Remove `fix_probe_phi` constraint for simplicity because it's only for visualization purpose (setting phase at k(0,0) as 0) without actual funcitonality

## [v0.1.0-alpha3.8] - 2024-05-10
### Added
= Add `loss_simlar` for omode similarity regularization
### Changed
- Update params files with the new `obj_tilts` field
- Move `omode_occu` from `source_params` to `exp_params` for params files because `omode_occu` is no longer planned to be an optimizable/loadable variable

## [v0.1.0-alpha3.7] - 2024-05-09
### Added
- Add `get_date` and `prefix` to `make_output_folder`
### Changed
- Add new fields like `tilt_obj`, `dk`, and `dx` to `make_save_dict`
- Fix the condition statements for `self.tilt_obj` in `models` so it behaves correctly when the initialized `obj_tilts` is [0,0] so no need for tilt propagator
- Fix `kz_filter` to use `torch.real()` for the Fourier filtered obj to respect possible negative values
- Delete the just-added fftshift/ifftshift in `forward` as they don't seem to matter and the forward pass is 50% slower with additional fftshifts
### Removed
- Remove `fix_probe_com` constraints because constantly shifting global probe would cause instability of the obj. Once the obj is fairly reconstructed, shifting the global probe would require shifting the already reconstructed object (or equivalently the entire (N,2) `probe_pos_shifts`) 
- Remove `probe_mask_r` constraints because it's just not physical and I can't justify myself clipping so much real-space probe tails
- Remove `obj_chgflip` constraints because the performance is rather poor
- Remove `obj_same` constraints because the usecase is rather limited and could probably be replaced with `kz_filter`. Optimizing the broadcasted averaged slice wouldn't be computationally faster. Besides, the "rough" result cann't be used to estimate obj tilts so is less usefull than the obj regularized by `kz_filter`

## [v0.1.0-alpha3.6] - 2024-05-07
### Added
- Add `opt_obj_tilts` for global (1,2) or local/adaptive (N,2) crystal tilt correction during ptycho reconstruction
- Add `obj_tilts` fields into `exp_params` for params files
- Add `test_constraint_fn` to roughly demonstrate the `constraint_fn`
- Extend `plot_scan_pos` with an `tilts` argument so we can temporarily borrow the `plot_scan_pos` to plot out obj tilt vectors (We should decouple this in the future)
- Add `get_rbf` to roughly estimate the radius of bright-field disk of the CBEDs for `probe_k_mask`
### Changed
- Move `omode_occu` to from `source_params` to `exp_params` in `initialization` for consistency with the obj tilts as they're specific for PtyRAD and behaves differently than obj, probe, or pos

## [v0.1.0-alpha3.5] - 2024-05-06
### Added
- Add `fix_probe_phi` for Fourier probe phase constraint. This is mostly for visualizaiton purpose, not sure if it stabilize the probe update for corner intensity artifact or not
- Add `fftshift2` and `ifftshift2` to `utils` as alias functions to remove the annoying `dim=(-2,-1)` argument for most fft, ifft calls
### Changed
- Global check for the fft/ifft/fftshift/ifftshift consistency. fft is for real->k, while fftshift is for corner->center. Do ifftshift to preshift before fft. All functions except the `imshift_batch` and `imshift_single` follow this pattern
- Simplify `near_field_evolution` by removing the unused far-field propagation and unused variables

## [v0.1.0-alpha3.4] - 2024-05-04
### Added
- Add `recenter_cbeds` field into the `models` so we may shift the CBEDs based on their CoM
### Changed
- Extend `get_center_of_mass` for 3D input (N,Ny,Nx)
- Rename `imshift` into `imshift_single` and modify it in accordance with `get_center_of_mass` 

## [v0.1.0-alpha3.3] - 2024-05-04
### Added
- Add probe constraints `fix_probe_com`, `probe_mask_r`, `probe_mask_k`  in hope of fixing the probe artifact
- Add corresponding visualization function `plot_sigmoid_mask`
### Changed
- Modify the `make_output_folder` accordingly for the probe mask constraints

## [v0.1.0-alpha3.2] - 2024-05-03
### Added
- Add a simple charge-flipping constraint `obj_chgflp` for fun and hoping it might fix the "black hole atom" artifact but it does not

## [v0.1.0-alpha3.1] - 2024-05-02
### Changed
- Delete the redundant intermediate wrapper function `batch_update` as it's probably unnecessarily complicated
### Removed
- Refactor `optimization` by removing redundant losses like `loss_tv`, `loss_postiv`, and `loss_obja1`. `loss_tv` is introducing very strong mosaic-style artifact. `loss_postiv` is overlapping with the `objp_positv` constraint and we can make the constraint soft by the mixing param so there's no need for `loss_postiv`. Same reason applies to `loss_obja1` as we already have the constraint version as `obja_thresh`
- Remove the placeholder `ortho_omode` function because I don't think orthogonalizing omode is the right thing to do. The omode are not necessarily orthogonal with each other and we should probably do the decomposition in the post-processing stage, not during the reconstruction
- Remove the for-loop implementation of `orthogonalize_modes_loop` because it's no longer needed, the vectorized version is much faster

## [v0.1.0-alpha3.0] - 2024-05-01
### Added
- Add amplitude options for obj specific constraints `kz_filter` and `obj_blur` so that we have finer control
- Add obja-related loss and constraints for completeness including `loss_obja1`, `obja_thresh`, and `obj_same`
### Changed
- Major refactor of the `optimization` by encapsulating each section of losses and constraints into individual functions for clarity 
- Combine `loss_l1`, `loss_l2` into `loss_sparse` for simplicity, while I think the LN-norm with N > 1 isn't really sparse so could be useless
- Extend `plot_forward_pass` to plot the obja(zprod) as well
- Update `make_output_folder` with oalr, obj_blur, and the kz_str
- Refine visualization functions including the "last N iters" to `plot_loss_iters` for the convergence, adding "iter" to figure title, fixing the displayed scan_pos range, and the probe power to `plot_probe_modes`

## [v0.1.0-alpha2.7] - 2024-04-28
### Added
- Extend `kz_filter` to `obja`, which turns out to be critical for thick samples like Si and now the `kz_filter` is fully recovering the `multilayer_regulation` operation in PtychoShelves
- Add Fourier probe modes saving to `plot_summary`
- Add version printing in `__init__` for clarity
### Changed
- Fix the incorrect scan position plotting when it's called in `plot_summary`
- Fix the checkerboard phase artifact in k-space for `plot_probe_modes` by adding the necessary fftshift
- Add an amplitude scaling to the displayed phase for better visualization
- Refactor `imshift_batch` so that it can handle tensors with arbitrary leading dimensions (..., Ny, Nx), which is in preparation for possible need of shifting the object (omode, Nz, Ny, Nx) for global scan affine transformation
- Rename and clarify the variables associated with `create_grids` in `models`

## [v0.1.0-alpha2.6] - 2024-04-23
### Added
- `Add plot_pos_grouping` to visualize the spatial distribution for different grouping
### Changed
- Fix the incorrect sparse batch generation due to duplicated indices in the `make_batch` function
- Fix the incorrect `imshift_batch` due to a missing ")" so the shifts were not applied correctly. It has very little effect when the sub-px shifts are <<1, but it could've been limiting the capability of pos correction

## [v0.1.0-alpha2.5] - 2024-04-21
### Added
- Add `plot_scan_positions` to `plot_summary`
- Add `init_pos` argument into `plot_scan_positions` 
### Changed
- Extend `plot_probe_modes` with real/reciprocal/amp/phase options
- Refine `plot_forward_modes` with weighted sum of omode for more correct objp visualization
- Rename all occurence of `iter` into `niter` to avoid name clashing with native python build-in iterator
- Fix `make_mixed_probe` error when pmode=1 by expanding the initial probe dim into (1,Ny,Nx) and passing only the probe[0] into `make_mixed_probe` to avoid changes inside the function

## [v0.1.0-alpha2.4] - 2024-04-21
### Added
- Add `plot_summary` to show and save reconstruction summary figures
### Changed
- Refine `plot_forward_pass` to add probe and remove redundant obj panels

## [v0.1.0-alpha2.3] - 2024-04-20
### Changed
- Rename `cbeds_flip` into `cbeds_flipsT` and make it comply with PtychoShelves format (flipup,fluplr,transpose)

## [v0.1.0-alpha2.2] - 2024-04-20
### Added
- Add `objp_blur` as a new obj constraint
- Add lr format into `make_output_folder` to save learning rate into the folder name
### Changed
- Add an if block for `make_mixed_probe` so only pmode>1 would initiate the function
- Fix the incorrect pos centering inside the affine transformation block in `init_pos` in `initializaiton`

## [v0.1.0-alpha2.1] - 2024-04-19
### Added
- Add `/scripts` for .py usage
- Add a quick CoM routine `center_of_mass` in `utils` for future CBED centering purpose
### Changed
- Move `init_variables` out of `model_params` for cleaner params file setup

## [v0.1.0-alpha2.0] - 2024-04-17
### Added
- Refactor the path generation and saving by adding `make_output_folder` and `save_results`
### Changed
- Unify grouping indices selection with `select_scan_indices`, 3 modes are available ("sparse", "compact", and "random")
- Refactor the indicies and batch making functions by removing `shuffle_batches` and `select_center_rectangle`

## [v0.1.0-alpha1.0] - 2024-04-16
### Added
- Add `init_check` into `initialization`
- Add `/inputs` to store the experimental data params
- Add position initialization with global affine transformation and flip into `initialization`
- Add `README` and `CHANGELOG`
### Removed
- Remove `/archive`

## [Initial development]
### 2024-04-14
- Add `detector_blur_std` for `models`
- Add `plot_scan_positions` and `plot_affine_transformation` to `visualization`

### 2024-04-13
- Add `fix_probe_int` constraint for `optimization` 
- Fix incorrect model saving and loading from .pt
- Modify `orthogonalize_modes_vec` for probe_int sorting and printing
- Modify `obj_ROI_grid` to on-the-fly generation to reduce memory consumption for large 4D dataset
- Add `init_cache` to reduce file loading time, especially for large .mat from PtychoShelves

### 2024-04-10
- Add `CombinedConstraint` class for iter-wise constraints including orthogonalization of pmode/omode, hard positivity clamp, and kz_filter for MS-ptycho
- Modify `orthogonalize_modes_vec` to take both 3/4D input and float/complex dtype
- Modify `make_save_dict` to accomodate constraint_params
- Add `shuffle_batches` to enhance randomness of mini-batch updates

### 2024-04-06
- Add `select_center_rectangle_indices` for partial reconstructions
- Unify batch generation funciton with "random", "compact", and "sparse"
- Modify iter/batch printing indices to start at 1

### 2024-04-04
- Reorganization of package directories
- Reformat params dicts
- Refine `initialization` class
- Move probe-related functions from `initializaiton` to `utils`

### 2024-04-02
- Major refactoring of the `initialization` class
- Add epsilon to forward model for numerical stability
- Add `make_stem_probe`, `make_mixed_probe`, and `orthogonalize_mode` functions for full reconstruction capability from simulated mixed-state probe

### 2024-03-30
- Implement the `initializaiton` class

### 2024-03-29
- Add 'ortho' kw for FFT intensity normalization
- Add `Fresnel_propagator` to move probe defocus
- Modify loss function to regularize on each object mode separately

### 2024-03-23
- Clean up archived versions class/functions, rename for clarity
- Add `set_optimizer` method into `models` so we may change the list of optimizable tensors or change their learning rates
- Split `opt_obj` into `obja` and `objp`, return opt_patches, calculate loss on obj_patches
- Implement `omode_occu` for mixed object reconstruction

### 2024-03-21
- Vectorzied object cropping and Fourier shift porbes. Got probably a 10x speed up

### 2024-03-20
- Implement the `imshift` with Fourier shift

### 2024-03-18
- Initialize the GitHub repo for PtyRAD

### 2024-03-16
- Implement a probe shift with `torchviosn.transformation.affine` but it seems to introduce artifacts to the probe

### 2024-03-14
- Implement the probe position with STN (spatial transformation network) on object
- Implement object losses including obj phase L1, obj phase positivity, obj phase TV

### 2024-03-11
- Implement the mixed object reconstruciton with unified dimension (omode,Nz,Ny,Nx)

### 2024-03-10
- Implement mixed probe reconstruction with 2D/3D object

### 2024-03-08
- Start working on the PtyRAD package