Toolkit documentation¶

chunk_length_samples: int = 30000

max_spikes_per_second: int = 16384

cd_iter: int = 0

coarse_cd: bool = True

threshold: float | Literal['fp_control'] = 8.0

template_svd_compression_rank: int = 5

up_factor: int = 4

upsampling_radius: int = 8

template_min_channel_amplitude: float = 1.0

refractory_radius_frames: int = 0

amplitude_scaling_variance: float = 0.01 ** 2

amplitude_scaling_boundary: float = 1.0 / 3.0

max_iter: int = 100

conv_ignore_threshold: float = 0.0

coarse_approx_error_threshold: float = 0.0

coarse_objective: bool = True

channel_selection: Literal['template', 'amplitude'] = 'template'

channel_selection_radius: float | None = None

template_type: Literal['individual_compressed_upsampled', 'drifty', 'debug'] = 'drifty'

up_method: Literal['interpolation', 'keys3', 'keys4', 'direct'] = 'keys4'

drift_interp_params: InterpolationParams = tps_interp_clampna_extrap_params

upsampling_compression_map: Literal['yass', 'none'] = 'yass'

whitening: WhiteningConfig = WhiteningConfig(strategy='prewhiten_postapply')

whiten_features: bool = False

margin_factor: int = 2

max_fp_per_input_spike: float = 2.5

min_template_ptp: float = 1.0

always_keep_ptp: float = 10.0

min_template_snr: float = 0.0

min_template_count: int = 20

max_cc_flag_rate: float = 0.4

cc_flag_entropy_cutoff: float = 2.0

depth_order: bool = True

template_merge_cfg: TemplateMergeConfig | None = TemplateMergeConfig()

template_realignment_cfg: TemplateRealignmentConfig = TemplateRealignmentConfig()

precomputed_templates_npz: str | None = None

delete_pconv: bool = True

chunk_length_samples: int = 30000

fit_only: bool = False

detection_threshold: float = 3.0

peak_sign: PeakSign = 'both'

realign_to_denoiser: bool = True

denoiser_realignment_channel: Literal['detection', 'denoised'] = 'detection'

denoiser_realignment_shift: int = 5

relative_peak_radius_samples: int = 5

relative_peak_radius_um: float | None = 35.0

spatial_dedup_radius_um: float | None = 50.0

temporal_dedup_radius_samples: int = 11

remove_exact_duplicates: bool = True

positive_temporal_dedup_radius_samples: int = 41

subtract_radius_um: float = 200.0

residnorm_decrease_threshold: float = 10.0

decrease_objective: Literal['norm', 'normsq', 'deconv'] = 'deconv'

growth_tolerance: float | None = None

trough_priority: float | None = 2.0

cumulant_order: int | None = None

convexity_threshold: float | None = None

convexity_radius: int = 7

max_iter: int = 100

subtraction_denoising_cfg: FeaturizationConfig = FeaturizationConfig(denoise_only=True, do_nn_denoise=True, extract_radius=200.0, input_waveforms_name='raw', output_waveforms_name='subtracted')

first_denoiser_max_waveforms_fit: int = 250000

first_denoiser_noise_snips: int = 100 * 128

first_denoiser_noise_snip_length_mul: float = 2.5

first_denoiser_noise_density: float = 0.5

first_denoiser_thinning: float = 0.0

first_denoiser_temporal_jitter: int = 3

first_denoiser_spatial_jitter: float = 35.0

first_denoiser_spatial_dedup_radius: float = 100.0

save_iteration: bool = False

save_residnorm_decrease: bool = False

chunk_length_samples: int = 30000

detection_threshold: float = 4.0

max_spikes_per_chunk: int | None = None

peak_sign: Literal['pos', 'neg', 'both'] = 'both'

spatial_dedup_radius_um: float = 150.0

relative_peak_radius_um: float | None = 35.0

relative_peak_radius_samples: int = 5

temporal_dedup_radius_samples: int = 11

remove_exact_duplicates: bool = True

cumulant_order: int | None = None

convexity_threshold: float | None = None

convexity_radius: int = 7

thinning: float = 0.0

time_jitter: int = 0

spatial_jitter_radius: float = 0.0

trough_priority: float | None = 2.0

shave_score: float = 10.0

skip: bool = False

extract_radius: float = 100.0

do_nn_denoise: bool = False

do_tpca_denoise: bool = True

do_enforce_decrease: bool | Literal['loc_only'] = 'loc_only'

denoise_only: bool = False

save_input_voltages: bool = True

save_input_waveforms: bool = False

save_input_tpca_projs: bool = True

compute_input_tpca_projs_regardless: bool = False

save_output_waveforms: bool = False

save_output_tpca_projs: bool = False

save_collidedness: bool = False

save_amplitudes: bool = True

save_all_amplitudes: bool = False

do_localization: bool = True

localization_radius: float = 100.0

localization_amplitude_type: Literal['peak', 'ptp'] = 'peak'

localization_decay_power: int = 1

localization_model: Literal['pointsource', 'dipole'] = 'pointsource'

nn_localization: bool = True

additional_com_localization: bool = False

nn_denoiser_class_name: str = 'Decollider'

nn_denoiser_pretrained_path: str | None = None

nn_denoiser_train_epochs: int = 100

nn_denoiser_epoch_size: int = 200 * 256

nn_denoiser_extra_kwargs: dict | None = argfield(None, cli=False)

tpca_fit_radius: float = 75.0

tpca_rank: int = 8

tpca_centered: bool = False

learn_cleaned_tpca_basis: bool = False

input_tpca_waveform_cfg: WaveformConfig | None = WaveformConfig(ms_before=0.75, ms_after=1.25)

tpca_max_waveforms: int = 40000

tpca_from_templates: bool = True

use_gmm_classifier: bool = False

pre_gmm_clustering_cfg: ClusteringConfig | None = None

pre_gmm_refinement_cfgs: Sequence[RefinementConfig | None] | None = None

gmm_refinement_cfg: RefinementConfig | None = None

gmm_clustering_features_cfg: ClusteringFeaturesConfig | None = None

input_waveforms_name: str = 'collisioncleaned'

output_waveforms_name: str = 'denoised'

use_x: bool = True

use_z: bool = True

motion_aware: bool = True

use_amplitude: bool = False

use_signed_amplitude: bool = True

log_transform_amplitude: bool = True

amp_log_c: float = 5.0

amp_scale: float = 3.0

x_scale: float = 1.0

n_main_channel_pcs: int = 5

pc_scale: float = 2.0

pc_transform: Literal['log', 'sqrt', 'none'] | None = 'none'

pc_pre_transform_scale: float = 0.5

adaptive_feature_scales: bool = False

feature_rank: int = 8

interp_params: InterpolationParams = tps_interp_params

motion_depth_mode: Literal['channel', 'localization'] = 'channel'

amplitudes_dataset_name: str = 'denoised_ptp_amplitudes'

voltages_dataset_name: str = 'collisioncleaned_voltages'

amplitude_vectors_dataset_name: str = 'denoised_ptp_amplitude_vectors'

localizations_dataset_name: str = 'point_source_localizations'

pca_dataset_name: str = 'collisioncleaned_tpca_features'

cluster_strategy: str = 'dpc'

sampling_cfg: FitSamplingConfig = default_clustering_fit_sampling_cfg

random_seed: int = 0

min_cluster_size: int = 25

knn_k: int | None = None

sigma_local: float = 5.0

sigma_regional: float | None = 25.0

n_neighbors_search: int = 50

radius_search: float = 25.0

noise_density: float = 0.0

outlier_radius: float = 25.0

outlier_neighbor_count: int = 10

kmeanspp_initializations: int = 10

kmeans_iter: int = 100

components_per_channel: int = 20

component_overlap: float = 0.95

hellinger_strong: float = 0.0

hellinger_weak: float = 0.0

use_hellinger: bool = True

gmmdpc_max_sigma: float = 5.0

mop: bool = True

min_samples: int = 25

cluster_selection_epsilon: int = 1

recursive: bool = False

grid_dx: float = 15.0

grid_dz: float = 15.0

sklearn_class_name: str = 'DBSCAN'

sklearn_kwargs: dict | None = None

refinement_strategy: str = 'tmm'

sampling_cfg: FitSamplingConfig = default_clustering_fit_sampling_cfg

pc_merge_threshold: float = 0.1

pc_merge_metric: str = 'normeuc'

pc_merge_spikes_per_unit: int = 4096

pc_merge_linkage: str = 'complete'

pc_merge_rank: int = 5

pc_merge_min_iou: float = 0.95

cov_kind: str = 'factorizednoise'

glasso_alpha: float | int | None = None

neighb_overlap: float = 0.75

explore_neighb_steps: int = 0

min_count: int = 25

split_min_count: int = 8

channels_count_min: int = 1

signal_rank: int = 3

initialize_at_rank_0: bool = False

cl_alpha: float = 0.05

cl_split_only: bool = True

latent_prior_std: float = 1.0

initial_basis_shrinkage: float = 1.0

n_spikes_fit: int = 4096

distance_metric: ComponentDistanceMetric = 'scaled_normeuc'

n_candidates: int = 5

merge_group_size: int = 5

n_search: int | None = 3

n_explore: int | None = None

train_batch_size: int = 512

eval_batch_size: int = 512

split_friend_distance: float = 0.8

split_distance_threshold: float = 1.5

merge_distance_threshold: float = 1.5

criterion_em_iters: int = 3

hold_out_criterion: bool = True

n_em_iters: int = 250

em_converged_atol: float = 0.005

n_total_iters: int = 1

mixture_steps: Sequence[MixtureStep] = ('split', 'merge', 'demolish')

prior_pseudocount: float = 0.0

kmeansk: int = 4

kmeans_tries: int = 5

kmeanspp_tries: int = 5

full_proposal_every: int = 10

main_min_iters: int = 20

search_adj: Literal['top', 'explore'] = 'top'

robust_strategy: Literal['none', 'fixed'] = 'none'

robust_fixed_std_dataset: str = 'collidedness'

robust_fixed_power: float = 40.0

robust_df: float = 4.0

demolition_min_resp_ratio: float = 1.1

demolish_during_selection: bool = False

em_after_demolish: bool = False

whiten_split: bool = True

scale_dist_args: tuple[float, float, float] = (0.01, 3.0 / 4.0, 4.0 / 3.0)

whiten_dist: bool = True

template_merge_cfg: TemplateMergeConfig = TemplateMergeConfig(linkage='single')

glom_max_firing_corr: float | None = -0.1

glom_firing_corr_dt: float = 0.5

glom_firing_corr_method: Literal['binsqrt'] = 'binsqrt'

qda_link: Literal['single', 'complete'] = 'single'

qda_uni_score: float = 0.95

qda_threshold: float = 0.35

qda_min_ratio: float = 0.1

qda_min_coverage: float = 0.35

qda_min_iou: float = 0.5

qda_force_merge_for_temp_dist_below: float = 0.3

chunk_size_s: float = 300.0

log_c: float = 5.0

feature_scales: tuple[float, float, float] = (1.0, 1.0, 50.0)

adaptive_feature_scales: bool = False

cov_radius: float = 200.0

val_proportion: float = 0.5

impute_kind: Literal['interp', 'impute'] = 'impute'

noise_interp_params: InterpolationParams = tps_interp_clampna_extrap_params

templates: ndarray

unit_ids: ndarray

spike_counts: ndarray

spike_counts_by_channel: ndarray | None = None

raw_std_dev: ndarray | None = None

registered_geom: ndarray | None = None

trough_offset_samples: int

sampling_frequency: float

properties: dict[str, ndarray] | None = None

tsvd: TruncatedSVD | PCA | None = None

whitener: ndarray | None = None

whiten_strategy: WhiteningStrategy = 'none'

featurization_basis: ndarray | None = None

spike_length_samples