mantidimaging.core.parallel.utility module

mantidimaging.core.parallel.utility.calculate_chunksize(cores)[source]
mantidimaging.core.parallel.utility.create_array(shape: Tuple[int, ...], dtype: npt.DTypeLike = <class 'numpy.float32'>) → numpy.ndarray[source]

Create an array, either in a memory file (if name provided), or purely in memory (if name is None)

Parameters

  • shape – Shape of the array

  • dtype – Dtype of the array

  • name – Name of the shared memory array. If None, a non-shared array will be created

  • random_name – Whether to randomise the name. Will discard anything in the name parameter

Returns

The created Numpy array

mantidimaging.core.parallel.utility.enough_memory(shape, dtype)[source]
mantidimaging.core.parallel.utility.execute_impl(img_num: int, partial_func: functools.partial, cores: int, chunksize: int, progress: mantidimaging.core.utility.progress_reporting.progress.Progress, msg: str)[source]
mantidimaging.core.parallel.utility.get_cores()[source]
mantidimaging.core.parallel.utility.multiprocessing_necessary(shape: Union[int, Tuple[int, int, int], List], cores) → bool[source]