pymovements.gaze

Provides gaze related functionality.

Classes

Experiment([screen_width_px, ...])	Experiment class for holding experiment properties.
EyeTracker([sampling_rate, left, right, ...])	EyeTracker class for holding eyetracker properties.
Screen([width_px, height_px, width_cm, ...])	Screen class for holding screen properties.
GazeDataFrame([data, experiment, events, ...])	A DataFrame for gaze time series data.

Transformations

transforms.center_origin(*, ...[, origin, ...])	Center pixel data.
transforms.downsample(*, factor)	Downsample gaze data by an integer factor.
transforms.norm(*, columns)	Take the norm of a 2D series.
transforms.pix2deg(*, screen_resolution, ...)	Convert pixel screen coordinates to degrees of visual angle.
transforms.deg2pix(*, screen_resolution, ...)	Convert degrees of visual angle to pixel screen coordinates.
transforms.pos2acc(*, sampling_rate, ...[, ...])	Compute acceleration data from positional data.
transforms.pos2vel(*, sampling_rate, method, ...)	Compute velocitiy data from positional data.
transforms.savitzky_golay(*, window_length, ...)	Apply a 1-D Savitzky-Golay filter to a column|_|:cite:p:SavitzkyGolay1964.

Input / Output

from_asc(file, *[, patterns, ...])	Initialize a pymovements.gaze.GazeDataFrame.
from_csv(file[, experiment, trial_columns, ...])	Initialize a pymovements.gaze.GazeDataFrame.
from_ipc(file[, experiment, trial_columns, ...])	Initialize a pymovements.gaze.GazeDataFrame.

Integration

from_numpy([data, experiment, events, ...])	Get a GazeDataFrame from a numpy array.
from_pandas(data[, experiment, events, ...])	Get a GazeDataFrame from a pandas DataFrame.

Numpy Transformations

transforms_numpy.pix2deg(arr, screen_px, ...)	Convert pixel screen coordinates to degrees of visual angle.
transforms_numpy.pos2acc(arr, sampling_rate)	Compute velocity time series from 2-dimensional position time series.
transforms_numpy.pos2vel(arr[, ...])	Compute velocity time series from 2-dimensional position time series.
transforms_numpy.norm(arr[, axis])	Take the norm of an array.
transforms_numpy.split(arr, window_size[, ...])	Split sequence into subsequences of equal length.
transforms_numpy.downsample(arr, factor)	Downsamples array by integer factor.
transforms_numpy.consecutive(arr)	Split array into groups of consecutive numbers.