Sensor Simulation#

SS#

sensor_simulation.py Module for simulating synthetic brain activity data for sensor-level measurements.

class calibrain.sensor_simulation.SensorSimulator(logger=None)[source]#

Bases: object

Simulates synthetic brain activity data for sensor-level measurements.

__init__(logger=None)[source]#

Initialize the SensorSimulator. :type logger: Optional[Logger] :param logger: Logger instance for logging messages. If None, a default logger will be created. :type logger: Optional[logging.Logger]

simulate(x_trials, L, orientation_type='fixed', alpha_SNR=0.5, n_trials=1, global_seed=42)[source]#

Simulate sensor trials by projecting source data to sensor space and adding noise to the clean sensor data.

Parameters:

  • x_trials (List[np.ndarray]) – List of source time courses for each trial. Each element should be an array of shape (n_sources, n_times) for fixed orientation or (n_sources, 3, n_times) for free orientation.

  • L (np.ndarray) – Leadfield matrix (µV / nAm for EEG or fT / nAm for MEG). - ‘fixed’: Shape (n_sensors, n_sources). - ‘free’: Shape (n_sensors, 3, n_sources).

  • orientation_type (str) – Orientation type of the sources (‘fixed’ or ‘free’).

  • alpha_SNR (float) – Desired signal-to-noise ratio between 0 and 1. - 0.0 means full noise, no signal. - 1.0 means no noise, only signal.

  • n_trials (int) – Number of trials to simulate. Default is 1.

  • global_seed (int) – Global seed for random number generation to ensure reproducibility across trials.

Returns:

  • y_clean_all_trialsnp.ndarray

    Clean sensor data for all trials. Shape: (n_trials, n_sensors, n_times).

  • y_noisy_all_trialsnp.ndarray

    Noisy sensor data for all trials. Shape: (n_trials, n_sensors, n_times).

  • noise_all_trialsnp.ndarray

    Noise added to the clean sensor data for all trials. Shape: (n_trials, n_sensors, n_times).

  • noise_var_all_trialsnp.ndarray

    Noise variance for each trial. Shape: (n_trials,).

Return type:

Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]

calibrain.sensor_simulation.main()[source]#