Source code for mantidimaging.core.operation_history.operations

# Copyright (C) 2024 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
from __future__ import annotations

from functools import partial
from logging import getLogger
from typing import Any
from import Callable, Iterable

import numpy as np

from mantidimaging.core.operations.loader import load_filter_packages
from . import const

MODULE_NOT_FOUND = "Could not find module with name '{}'"

[docs] class ImageOperation: """ A deserialized representation of an item in a stack's operation_history """ def __init__(self, filter_name: str, filter_kwargs: dict[str, Any], display_name: str): self.filter_name = filter_name self.filter_kwargs = filter_kwargs self.display_name = display_name
[docs] def to_partial(self, filter_funcs: dict[str, Callable]) -> partial: try: fn = filter_funcs[self.filter_name] return partial(fn, **self.filter_kwargs) except KeyError as exc: msg = MODULE_NOT_FOUND.format(self.filter_name) getLogger(__name__).error(msg) raise KeyError(msg) from exc
[docs] @staticmethod def from_serialized(metadata_entry: dict[str, Any]) -> ImageOperation: return ImageOperation(filter_name=metadata_entry[const.OPERATION_NAME], filter_kwargs=metadata_entry[const.OPERATION_KEYWORD_ARGS], display_name=metadata_entry[const.OPERATION_DISPLAY_NAME])
[docs] def serialize(self) -> dict[str, Any]: return { const.OPERATION_NAME: self.filter_name, const.OPERATION_KEYWORD_ARGS: self.filter_kwargs, const.OPERATION_DISPLAY_NAME: self.display_name, }
def __str__(self): return f"{self.display_name if self.display_name else self.filter_name}, " \ f"kwargs: {self.filter_kwargs}"
[docs] def deserialize_metadata(metadata: dict[str, Any]) -> list[ImageOperation]: return [ImageOperation.from_serialized(entry) for entry in metadata[const.OPERATION_HISTORY]] \ if const.OPERATION_HISTORY in metadata else []
[docs] def ops_to_partials(filter_ops: Iterable[ImageOperation]) -> Iterable[partial]: filter_funcs: dict[str, Callable] = {f.__name__: f.filter_func for f in load_filter_packages()} fixed_funcs = { const.OPERATION_NAME_AXES_SWAP: lambda img, **_: np.swapaxes(img, 0, 1), # const.OPERATION_NAME_TOMOPY_RECON: lambda img, **kwargs: TomopyReconWindowModel.do_recon(img, **kwargs), } filter_funcs.update(fixed_funcs) return (op.to_partial(filter_funcs) for op in filter_ops)