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parallel::mclapply)set_parallel_plan()R/parallel_config.R:
set_parallel_plan(): Configure parallel strategy
(sequential, multisession, multicore, cluster)is_parallel_enabled(): Check parallel statusshould_parallelize(): Auto-detect when to parallelize
based on thresholdget_n_workers(): Query number of parallel workersreset_parallel_plan(): Reset to sequential modeR/progress_utils.R:
with_progress(): Execute expressions with progress
reportingcreate_progressor(): Create progress reporters for
loopsconfigure_progress(): Configure progress handlersis_progress_available(): Check progressr
availabilityR/tangent_handler.R):
compute_tangents(): Parallel tangent space
projectionscompute_vecs(): Parallel vectorizationcompute_conns(): Parallel exponential mapsset_reference_point(): Parallel tangent relocationprogress parameterR/parquet_backend.R):
get_all_matrices(): Parallel matrix loading from
Parquet filesget_matrices_parallel(): New method for batch parallel
loadingR/other_utils.R):
relocate(): Now uses furrr::future_map()
instead of parallel::mclapply (cross-platform!)compute_frechet_mean(): Parallel processing support
with progress parameterprogress parameterR/sample.R):
compute_tangents(): Pass-through progress supportcompute_vecs(): Pass-through progress supportcompute_unvecs(): Parallel unvectorizati with
progresscompute_conns(): Pass-through progress supportcompute_fmean(): Pass-through progress supportchange_ref_pt(): Pass-through progress supportload_connectomes_batched(): NEW -
Batch loading with memory management for large Parquet datasetsrelocate() function signature changed: added optional
progress parameter (default: FALSE)
compute_frechet_mean() function signature changed:
added optional progress parameter
future to Imports (cross-platform parallel
backend)furrr to Imports (future-based parallel map
functions)progressr to Suggests (optional progress
reporting)parallel::mclapply
(platform-specific, Windows incompatible)DataBackend,
ListBackend, ParquetBackend) to decouple
storage from business logicListBackend: Wraps existing list-based storage for
backwards compatibilityParquetBackend: Lazy-loads matrices from Parquet files
with LRU caching (default cache size: 10 matrices)write_connectomes_to_parquet(): Export matrices to
Parquet format with metadatavalidate_parquet_directory(): Validate Parquet
directory structurecreate_parquet_backend(): Convenience function to
create ParquetBackendCSample now accepts backend parameter for
flexible storage optionsvalidate_backend(): Validates backend
objectsvalidate_parquet_dir(): Validates Parquet
directory structureCSample to use backend abstraction
internallyCSample$connectomes active binding to support
lazy loadingCSuperSample works transparently with all backend
typesarrow to Imports for Parquet supportsuper_sample.R, introducing the
CSuperSample class for handling and analyzing collections
of CSample objects.CSuperSample in
test-csupersample.R.Matrix package from Depends to
Imports in the DESCRIPTION file.roxygen2.LICENSE file with the MIT license.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.