mantidimaging.core.io.loader.loader module

class mantidimaging.core.io.loader.loader.FileInformation(filenames: List[str], shape: Tuple[int, int, int], sinograms: bool)[source]

Bases: object

filenames: List[str]
shape: Tuple[int, int, int]
sinograms: bool
mantidimaging.core.io.loader.loader.create_loading_parameters_for_file_path(file_path: str, logger: Logger | None = None) → LoadingParameters | None[source]
mantidimaging.core.io.loader.loader.find_and_verify_sample_log(sample_directory: str, image_filenames: List[str]) → str[source]
mantidimaging.core.io.loader.loader.load(input_path: str | None = None, input_path_flat_before: str | None = None, input_path_flat_after: str | None = None, input_path_dark_before: str | None = None, input_path_dark_after: str | None = None, in_prefix: str = '', in_format: str = 'tif', dtype: npt.DTypeLike = <class 'numpy.float32'>, file_names: ~typing.List[str] | None = None, indices: ~typing.List[int] | ~mantidimaging.core.utility.data_containers.Indices | None = None, progress: ~mantidimaging.core.utility.progress_reporting.progress.Progress | None = None) → StrictDataset[source]

Loads a stack, including sample, white and dark images.

Parameters:

  • input_path – Path for the input data folder

  • input_path_flat_before – Optional: Path for the input Flat Before images folder

  • input_path_flat_after – Optional: Path for the input Flat After images folder

  • input_path_dark_before – Optional: Path for the input Dark Before images folder

  • input_path_dark_after – Optional: Path for the input Dark After images folder

  • in_prefix – Optional: Prefix for loaded files

  • in_format – Default:’tiff’, format for the input images

  • dtype – Default:np.float32, data type for the input images

  • file_names – Use provided file names for loading

  • indices – Specify which indices are loaded from the found files. This DOES NOT check for the number in the image filename, but removes all indices from the filenames list that are not selected

  • progress – The progress reporting instance

Returns:

a tuple with shape 3: (sample, flat, dark), if no flat and dark were loaded, they will be None

mantidimaging.core.io.loader.loader.load_log(log_file: str) → IMATLogFile[source]
mantidimaging.core.io.loader.loader.load_p(parameters: ImageParameters, dtype: npt.DTypeLike, progress: Progress) → Images[source]
mantidimaging.core.io.loader.loader.load_stack(file_path: str, progress: Progress | None = None) → Images[source]
mantidimaging.core.io.loader.loader.read_in_file_information(input_path: str, in_prefix: str = '', in_format: str = 'tif', data_dtype: npt.DTypeLike = <class 'numpy.float32'>) → FileInformation[source]
mantidimaging.core.io.loader.loader.supported_formats() → List[str][source]