neuralset.extractors.meta.ExtractorPCA¶
- class neuralset.extractors.meta.ExtractorPCA(*, event_types: str | tuple[str, ...] = 'Event', aggregation: Literal['single', 'sum', 'mean', 'first', 'middle', 'last', 'cat', 'stack', 'trigger'] = 'single', allow_missing: bool = False, frequency: float = 0.0, extractor: BaseExtractor, n_components: int, whiten: bool = True, infra: MapInfra = MapInfra(folder=None, cluster=None, logs='{folder}/logs/{user}/%j', job_name=None, timeout_min=None, nodes=1, tasks_per_node=1, cpus_per_task=None, gpus_per_node=None, mem_gb=None, max_pickle_size_gb=None, slurm_constraint=None, slurm_partition=None, slurm_account=None, slurm_qos=None, slurm_use_srun=False, slurm_additional_parameters=None, conda_env=None, workdir=None, permissions=511, version='0', keep_in_ram=True, max_jobs=128, min_samples_per_job=1, forbid_single_item_computation=False, mode='cached'))[source][source]¶
Applies a PCA to another extractor’s data The underlying extractor is first computed through the prepare method, and then the current extractor applies the PCA on it. Both caches are stored.