MatchingData.computation_schedule#

MatchingData.computation_schedule(matching_method='FLCSphericalMask', max_cores=1, use_gpu=False, pad_fourier=False, pad_target_edges=False, analyzer_method=None, available_memory=None, max_splits=256)[source]#

Computes a parallelization schedule for a given template matching operation.

Parameters:
matching_methodstr

Matching method to use, default “FLCSphericalMask”.

max_coresint, optional

Maximum number of CPU cores to use, default 1.

use_gpubool, optional

Whether to utilize GPU acceleration, default False.

pad_fourierbool, optional

Apply Fourier padding, default False.

pad_target_edgesbool, optional

Apply padding to target edges, default False.

analyzer_methodstr, optional

Method used for score analysis, default None.

available_memoryint, optional

Available memory in bytes. If None, uses all available system memory.

max_splitsint, optional

Maximum number of splits to consider, default 256.

Returns:
target_splitsdict

Optimal splits for each axis of the target tensor

scheduletuple

(n_outer_jobs, n_inner_jobs_per_outer) defining the parallelization schedule