eegunity package

Subpackages

• eegunity.module_eeg_batch package
  • Submodules
  • eegunity.module_eeg_batch.eeg_batch module
    • EEGBatch
      • EEGBatch.align_channel()
      • EEGBatch.auto_domain()
      • EEGBatch.batch_process()
      • EEGBatch.epoch_by_event()
      • EEGBatch.epoch_for_pretraining()
      • EEGBatch.export_h5Dataset()
      • EEGBatch.filter()
      • EEGBatch.format_channel_names()
      • EEGBatch.get_events()
      • EEGBatch.get_quality()
      • EEGBatch.ica()
      • EEGBatch.infer_units()
      • EEGBatch.normalize()
      • EEGBatch.process_mean_std()
      • EEGBatch.replace_paths()
      • EEGBatch.resample()
      • EEGBatch.sample_filter()
      • EEGBatch.save_as_other()
      • EEGBatch.set_column()
  • eegunity.module_eeg_batch.eeg_scores module
    • butter_bandpass()
    • butter_bandpass_filter()
    • calculate_beta_amplitude_score()
    • calculate_beta_sinusoidal_score()
    • calculate_dominant_frequency()
    • calculate_eeg_quality_scores()
    • calculate_general_amplitude_score()
    • calculate_highest_amplitude_score()
    • calculate_symmetry_score()
    • calculate_theta_amplitude_score()
    • classify_channels()
    • plot_radar_chart()
  • Module contents
• eegunity.module_eeg_correction package
  • Submodules
  • eegunity.module_eeg_correction.eeg_correction module
    • EEGCorrection
      • EEGCorrection.report()
      • EEGCorrection.visualization_channels_corr()
      • EEGCorrection.visualization_frequency()
  • Module contents
• eegunity.module_eeg_llm_booster package
  • Submodules
  • eegunity.module_eeg_llm_booster.eeg_llm_booster module
    • EEGLLMBooster
  • eegunity.module_eeg_llm_booster.eeg_llm_des_parser module
    • llm_description_file_parser()
  • eegunity.module_eeg_llm_booster.eeg_llm_file_parser module
    • llm_boost_parser()
  • Module contents
• eegunity.module_eeg_parser package
  • Submodules
  • eegunity.module_eeg_parser.eeg_parser module
    • EEGParser
      • EEGParser.check_locator()
      • EEGParser.get_data()
    • channel_name_parser()
    • convert_unit()
    • create_montage_from_json()
    • extract_events()
    • get_data_row()
    • handle_nonstandard_data()
    • infer_channel_unit()
    • normalize_data()
    • process_mne_files()
    • set_channel_type()
    • set_infer_unit()
    • set_montage_any()
  • eegunity.module_eeg_parser.eeg_parser_config module
  • eegunity.module_eeg_parser.eeg_parser_csv module
    • calculate_interval()
    • identify_time_columns()
    • is_datetime_format()
    • process_csv_files()
  • eegunity.module_eeg_parser.eeg_parser_mat module
    • process_mat_files()
  • Module contents
• eegunity.utils package
  • Submodules
  • eegunity.utils.con_udatasets module
    • con_udatasets()
  • eegunity.utils.h5 module
    • h5Dataset
      • h5Dataset.addAttributes()
      • h5Dataset.addDataset()
      • h5Dataset.addGroup()
      • h5Dataset.name
      • h5Dataset.save()
  • eegunity.utils.normalize module
    • normalize_mne()
  • eegunity.utils.pipeline module
    • Pipeline
      • Pipeline.functions
      • Pipeline.forward()
  • Module contents

Submodules

eegunity.share_attributes module

class eegunity.share_attributes.UDatasetSharedAttributes

Bases: object

get_shared_attr()

set_shared_attr(value)

eegunity.unifieddataset module

class eegunity.unifieddataset.UnifiedDataset(domain_tag: str | None = None, dataset_path: str | None = None, locator_path: str | None = None, is_unzip: bool = True, verbose: str = 'CRITICAL')

Bases: UDatasetSharedAttributes

This is the kernel class to manage mutiple EEG datasets and associated processing tools.

Attributes:

dataset_pathstr, optional

Path to the dataset (folder). Should not be provided alongside locator_path.

locator_pathstr, optional

Path to the locator. Should not be provided alongside dataset_path.

is_unzipbool, optional

If set to True, any Zip files in the specified dataset will be unzipped. Be aware that unzipping may modify the dataset.

domain_tagstr, optional

The domain tag identifies the dataset name and is required if you specify a dataset path.

verbosestr, optional

Level of verbosity for logging (default is ‘CRITICAL’).

eeg_parserEEGParser

EEGParser module

eeg_batchEEGBatch

EEGBatch module

eeg_correctionEEGCorrection

EEGCorrection module

module_eeg_llm_boosterEEGLLMBooster

EEGLLMBooster module

copy()

Create a deep copy of the UnifiedDataset instance.

Returns:

UnifiedDataset

A deep copy of the current UnifiedDataset instance.

get_locator()

Return the locator in DataFrame.

Returns:

pandas.DataFrame

The locator DataFrame associated with the dataset.

save_locator(path)

Save the locator of this UnifiedDataset to a CSV file at the specified path. This file is helpful for checking the current status and metadata after data processing. You can also reload the UnifiedDataset later by using this locator file, for example: unified_dataset = UnifiedDataset(locator_path=”your_locator_path”)

Parameters:

pathstr

The file path where the locator should be saved.

set_locator(new_locator)

Set a new locator for this UnifiedDataset instance. This allows you to update the metadata for the entire dataset without altering the original raw file.

Parameters:

new_locatorpandas.DataFrame

The new locator DataFrame to associate with the dataset.

Module contents