API Reference

This page indexes the full pyavs top-level API (everything importable as pyavs.<name>). For richer, docstring-heavy documentation organized by topic, see the per-submodule pages below. AVSComposer, EyeTrackingPlotter, AVSRemote and open_remote are documented in full on their dedicated pages (Preprocessing (pyavs.preprocessing), Visualization (pyavs.visualization), Remote Access (pyavs.remote)) rather than duplicated below.

Top-Level API

pyavs.set_data_path
pyavs.get_data_path
pyavs.setup_data_directory
pyavs.configure	Configure pyavs data directory once per machine/environment.
pyavs.check_data_availability	Check if data is available for a subject/session.
pyavs.load_eye_events	Load eye tracking events and messages for a subject/session.
pyavs.load_experiment_log	Load experiment log for a subject/session.
pyavs.load_anatomical	Load anatomical data path for a subject.
pyavs.load_scenes	Load scene image paths, fetching from COCO on demand if not shipped locally.
pyavs.load_and_enrich_eye_events	Load and enrich eye tracking events for multiple subjects/sessions.
pyavs.add_fixation_sequence_position	Add fixation sequence positions to events dataframe.
pyavs.add_cross_event_information	Add cross-event information (saccade-fixation relationships).
pyavs.load_and_preprocess_eye_tracking	Load and preprocess eye-tracking data for multiple subjects/sessions.
pyavs.load_meg_raw	Load raw MEG data for a specific subject/session/run.
pyavs.load_meg_preprocessed	Load preprocessed MEG data for a specific subject/session/run.
pyavs.load_meg_session	Load MEG data for all runs in a session.
pyavs.load_and_preprocess_meg_run	Load and preprocess MEG data for a single run.
pyavs.get_fixated_objects	Add object labels to fixation events using transformed AVS scene annotations.
pyavs.preprocess_eye_events	Preprocess eye tracking events by removing artifacts and outliers.
pyavs.apply_maxwell_filter	Apply Maxwell filtering (tSSS) to MEG data.
pyavs.filter_meg	Apply bandpass filtering to MEG data.
pyavs.resample_meg	Resample MEG data to a new sampling frequency.
pyavs.preprocess_meg_block	Complete preprocessing pipeline for a single MEG block.
pyavs.apply_precomputed_ica	Apply precomputed ICA solution to MEG data.
pyavs.compute_ica	Compute ICA decomposition on MEG data.
pyavs.apply_ica	Apply ICA to remove specified components.
pyavs.find_cardiac_components	Find ICA components related to cardiac artifacts.
pyavs.find_eye_components_xy_correlation	Find ICA components correlated with per-scene XY gaze position.
pyavs.run_ica_et_pipeline	Full ICA pipeline with eye tracking XY correlation for one subject/session.
pyavs.build_et_raw_from_samples	Wrap eye tracking samples from a CSV DataFrame into an MNE RawArray.
pyavs.align_et_to_meg	Align ET RawArray to MEG Raw using shared scene onset events.
pyavs.create_et_event_epochs	Create MEG epochs based on eye tracking events using the AVS composer approach.
pyavs.get_meg_trigger_mapping	Get mapping of MEG trigger names to codes.
pyavs.repair_meg_trigger_events	Repair corrupted MEG trigger events.
pyavs.get_meg_trigger_dict	Here we define a dictionary to map the event codes to the event names.
pyavs.get_avs_blocks	Returns a list of all avs blocks in the requested session.
pyavs.get_meg_timestamp	Returns the timestamp of the scene onset in the MEG data.
pyavs.add_fix_event_trigger	Adds eye movement based event triggers (fixation, saccade) to the raw neuro data.
pyavs.attach_scene_ids_to_samples	Attach scene IDs and trial information to eye tracking samples using pyAVS conventions.
pyavs.load_samples_with_scenes	Convenience function to load samples file and attach scene information.
pyavs.validate_samples_scene_assignment	Validate the scene ID assignment results for samples.
pyavs.create_forward_model	Create forward model for source reconstruction.
pyavs.create_bem_model	Create BEM (Boundary Element Method) model for source reconstruction.
pyavs.setup_coregistration	Set up coregistration between MEG and MRI coordinate systems.
pyavs.load_forward_model	Load a forward model from the dataset.
pyavs.apply_source_reconstruction	Apply source reconstruction to epoched data.
pyavs.compute_beamformer_filters	Compute LCMV beamformer filters.
pyavs.compute_population_codes	Compute population codes for different experimental conditions.
pyavs.extract_roi_data	Extract data from regions of interest.
pyavs.save_source_data	Save source space data in HDF5 format.
pyavs.save_annotated_raw	Save annotated Raw data in HDF5 format.
pyavs.save_population_codes_h5	Save population codes to HDF5 file in standardized format.
pyavs.find_population_codes_files	Find population codes files for a subject with optional parameter filtering.
pyavs.list_available_parameter_sets	List all available parameter sets in the population codes storage.
pyavs.load_source_data	Load data from HDF5 files.
pyavs.create_source_space	Create cortical source space.
pyavs.get_roi_labels	Get ROI labels from FreeSurfer parcellation.
pyavs.get_glasser_roi_labels	Get Glasser atlas ROI names.
pyavs.plot_evoked_joint	Create a joint plot of evoked MEG data: topomaps above, butterfly + GFP below.
pyavs.plot_median_erf	Plot median ERF (Event-Related Field) for MEG sensor space data.
pyavs.plot_sensor_space_overview	Create an overview plot of sensor space MEG data.
pyavs.load_pilot_events	Combine fixation events from all pilot subjects into one enriched DataFrame.
pyavs.load_pilot_samples	Combine enriched gaze samples from all pilot subjects into one DataFrame.
pyavs.add_sample_scene_coordinates	Add scene-centred and normalised gaze coordinates to raw samples.
pyavs.load_and_preprocess	Load and preprocess MEG + eye-tracking data for a subject/session.
pyavs.get_epochs	Extract epochs from preprocessed subject data.

Browse by Topic

• Data Loading (pyavs.dataloader)
• Preprocessing (pyavs.preprocessing)
• Source Reconstruction (pyavs.source)
• Scene Analysis (pyavs.scenes)
• Captions (pyavs.captions)
• Utilities (pyavs.utils)
• Configuration (pyavs.config)
• Visualization (pyavs.visualization)
• I/O (pyavs.io)
• Pilot Data (pyavs.pilot)
• Remote Access (pyavs.remote)
• Command Line Interface (pyavs.cli)

AVSComposer (pyavs.preprocessing.composer.AVSComposer, documented in full on Preprocessing (pyavs.preprocessing)) is the recommended high-level entry point for most analyses; see AVSComposer Guide for a guided walkthrough. pyavs.MEGETComposer is a backward-compatibility alias for the same class.

AVSRemote (pyavs.remote.client.AVSRemote, opened via pyavs.open_remote(), documented in full on Remote Access (pyavs.remote)) loads data on demand from the public AWS release bucket instead of a local data_path – see Data Access for details.