Haskels/ptycho fm backend - #131
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Mirrors the ptychopinn_torch subprocess-isolation pattern for the ptycho-vit foundation model. Parent-side factory produces a SubprocessReconstructor whose child entry points (run_reconstruct / run_train) are the only ptychodus modules that import torch or ptycho_vit. The parent hands the child a pre-built nested config dict (no framework types cross the pickle boundary) plus the raw payload. Inference batches diffraction amplitudes through PtychoViT, applies a central crop to each patch, and stitches phase + amplitude back onto the object grid via place_patches_fourier_shift, folding the result into layer 0 as amp*exp(1j*ph). Training runs a minimal single-device loop (no DDP, no mlflow, no wandb) with random_split train/val and saves the best-val checkpoint to output_path/best.pth. Registers Unsupervised + Supervised modes via the reconstructor library and wires a PyQt controller with Data/Model/Training/Inference groups. When ptycho_vit is absent, developer mode falls back to NullReconstructor so the GUI still boots. Optional dep ptycho-fm = ["ptycho-vit"] added to pyproject.toml; the test_parent_config_builders discipline gate covers ptycho_fm too.
CI on webservice runs `ruff format --check .` over the whole tree, including Python fenced blocks in docs/source/. Two pages had drifted (double quotes, unpacked multi-line call arguments) and were failing the check for every open PR. Running `ruff format .` reformats them in place with no logic changes.
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@stevehenke could you please merge this branch to webservice? I do not have write access so I am unable to merge. |
Replaces the NPZ writer with a two-HDF5 exporter matching what ptycho_vit.CombinedDataset actually reads: <stem>_dp.hdf5 with a 'dp' dataset of diffraction patterns, and <stem>_para.hdf5 with 'object', 'probe', 'probe_position_x_m', and 'probe_position_y_m' plus a 'pixel_height_m' attr on 'object'. file_path is treated as a stem (the picked filename itself is not created).
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