mne.preprocessing.eyetracking.Calibration#
- class mne.preprocessing.eyetracking.Calibration(*, onset, model, eye, avg_error, max_error, positions, offsets, gaze, screen_size=None, screen_distance=None, screen_resolution=None)[source]#
Eye-tracking calibration info.
This data structure behaves like a dictionary. It contains information regarding a calibration that was conducted during an eye-tracking recording.
Note
When possible, a Calibration instance should be created with a helper function, such as
read_eyelink_calibration().- Parameters:
- onset
float The onset of the calibration in seconds. If the calibration was performed before the recording started, the the onset can be negative.
- model
str A string, which is the model of the eye-tracking calibration that was applied. For example
'H3'for a horizontal only 3-point calibration, or'HV3'for a horizontal and vertical 3-point calibration.- eye
str The eye that was calibrated. For example,
'left', or'right'.- avg_error
float The average error in degrees between the calibration positions and the actual gaze position.
- max_error
float The maximum error in degrees that occurred between the calibration positions and the actual gaze position.
- positionsarray_like of
float, shape(n_calibration_points, 2) The x and y coordinates of the calibration points.
- offsetsarray_like of
float, shape(n_calibration_points,) The error in degrees between the calibration position and the actual gaze position for each calibration point.
- gazearray_like of
float, shape(n_calibration_points, 2) The x and y coordinates of the actual gaze position for each calibration point.
- screen_sizearray_like of shape
(2,) The width and height (in meters) of the screen that the eyetracking data was collected with. For example
(.531, .298)for a monitor with a display area of 531 x 298 mm.- screen_distance
float The distance (in meters) from the participant’s eyes to the screen.
- screen_resolutionarray_like of shape
(2,) The resolution (in pixels) of the screen that the eyetracking data was collected with. For example,
(1920, 1080)for a 1920x1080 resolution display.
- onset
Methods
__contains__(key, /)True if the dictionary has the specified key, else False.
x.__getitem__(y) <==> x[y]
__iter__(/)Implement iter(self).
__len__(/)Return len(self).
clear()copy()Copy the instance.
fromkeys(iterable[, value])Create a new dictionary with keys from iterable and values set to value.
get(key[, default])Return the value for key if key is in the dictionary, else default.
items()keys()plot([show_offsets, axes, show])Visualize calibration.
pop(key[, default])If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem(/)Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()- __contains__(key, /)#
True if the dictionary has the specified key, else False.
- __getitem__()#
x.__getitem__(y) <==> x[y]
- __iter__(/)#
Implement iter(self).
- __len__(/)#
Return len(self).
- clear() None. Remove all items from D.#
- copy()[source]#
Copy the instance.
- Returns:
- calinstance of
Calibration The copied Calibration.
- calinstance of
- fromkeys(iterable, value=None, /)#
Create a new dictionary with keys from iterable and values set to value.
- get(key, default=None, /)#
Return the value for key if key is in the dictionary, else default.
- items() a set-like object providing a view on D's items#
- keys() a set-like object providing a view on D's keys#
- plot(show_offsets=True, axes=None, show=True)[source]#
Visualize calibration.
- Parameters:
- show_offsetsbool
Whether to display the offset (in visual degrees) of each calibration point or not. Defaults to
True.- axesinstance of
matplotlib.axes.Axes|None Axes to draw the calibration positions to. If
None(default), a new axes will be created.- showbool
Whether to show the figure or not. Defaults to
True.
- Returns:
- figinstance of
matplotlib.figure.Figure The resulting figure object for the calibration plot.
- figinstance of
Examples using
plot:
- pop(key, default=<unrepresentable>, /)#
If the key is not found, return the default if given; otherwise, raise a KeyError.
- popitem(/)#
Remove and return a (key, value) pair as a 2-tuple.
Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.
- setdefault(key, default=None, /)#
Insert key with a value of default if key is not in the dictionary.
Return the value for key if key is in the dictionary, else default.
- update([E, ]**F) None. Update D from dict/iterable E and F.#
If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
- values() an object providing a view on D's values#
