rectangular_generalized#
You can find an interactive version of this example here
- stimupy.stimuli.bullseyes.rectangular_generalized(visual_size=None, ppd=None, shape=None, radii=None, rotation=0.0, intensity_frames=(0.0, 1.0), intensity_background=0.5, intensity_target=0.5, origin='mean')#
Draw sequential set of square frames with specified radii with central target
- Parameters:
frame_radii (Sequence[Number]) – radii of each frame, in degrees visual angle
visual_size (Sequence[Number, Number], Number, or None (default)) – visual size [height, width] of image, in degrees
ppd (Sequence[Number, Number], Number, or None (default)) – pixels per degree [vertical, horizontal]
shape (Sequence[Number, Number], Number, or None (default)) – shape [height, width] of image, in pixels
radii (Sequence[Number] or None (default)) – radii of each frame, in degrees visual angle
rotation (float, optional) – rotation (in degrees), counterclockwise, by default 0.0 (horizontal)
intensity_frames (Sequence[float, float]) – min and max intensity of square-wave, by default (0.0, 1.0)
intensity_background (float (optional)) – intensity value of background, by default 0.5
intensity_target (float, or Sequence[float, ...], optional) – intensity value for each target, by default 0.5. Can specify as many intensities as number of target_indices; If fewer intensities are passed than target_indices, cycles through intensities
origin ("corner", "mean" or "center") – if “corner”: set origin to upper left corner if “mean”: set origin to hypothetical image center (default) if “center”: set origin to real center (closest existing value to mean)
- Returns:
dict with the stimulus (key: “img”), mask with integer index for each frame (key: “target_mask”), and additional keys containing stimulus parameters
- Return type: