import numpy as np
from stimupy.components.edges import cornsweet as cornsweet_edge
__all__ = [
"cornsweet",
]
[docs]def cornsweet(
visual_size=None,
ppd=None,
shape=None,
ramp_width=None,
rotation=0.0,
intensity_edges=(0.0, 1.0),
intensity_plateau=0.5,
exponent=2.75,
):
"""Draw rectangular Cornsweet edge stimulus.
The 2D luminance profile of the stimulus is defined as
Left side:
v = vtarget + (1 - X / w) ** a * (intensity_max-vtarget) for the ramp and v = vtarget beyond.
Right side:
v = vtarget - (1 - X / w) ** a * (intensity_min-vtarget) for the ramp and v = vtarget beyond.
X is the distance to the edge, w is the width of the ramp, a is a variable
determining the steepness of the ramp, vtarget is the luminance of the targets and
intensity_max/intensity_min are the max/min luminances.
Parameters
----------
visual_size : Sequence[Number, Number], Number, or None (default)
visual size [height, width] of grating, 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 grating, in pixels
ramp_width : float
width of luminance ramp in degrees of visual angle
rotation : float, optional
rotation (in degrees), counterclockwise, by default 0.0 (horizontal)
intensity_edges : (float, float)
intensity of edges
intensity_plateau : float
intensity value of plateau
exponent : float
determines steepness of ramp (default is 2.75. 1 would be linear)
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img"),
mask with integer index for each target (key: "target_mask"),
and additional keys containing stimulus parameters
References
----------
Boyaci, H., Fang, F., Murray, S.O., Kersten, D. (2007).
Responses to lightness variations in early human visual cortex.
Current Biology 17, 989-993.
https://doi.org/10.1016/j.cub.2007.05.005
Cornsweet, T. (1970).
Visual perception. Academic press.
https://doi.org/10.1016/B978-0-12-189750-5.X5001-5
"""
stim = cornsweet_edge(
visual_size=visual_size,
ppd=ppd,
shape=shape,
ramp_width=ramp_width,
rotation=rotation,
intensity_edges=intensity_edges,
intensity_plateau=intensity_plateau,
exponent=exponent,
)
# Generate the target mask
mask = np.where(stim["d1"] == 1, stim["edge_mask"], 0) + np.where(
stim["d2"] == 1, stim["edge_mask"], 0
)
stim["target_mask"] = mask.astype(int)
return stim
def overview(**kwargs):
"""Generate example stimuli from this module
Returns
-------
stims : dict
dict with all stimuli containing individual stimulus dicts.
"""
default_params = {"visual_size": 15, "ppd": 30}
default_params.update(kwargs)
# fmt: off
stimuli = {
"cornsweet": cornsweet(**default_params, ramp_width=3)
}
# fmt: on
return stimuli
if __name__ == "__main__":
from stimupy.utils import plot_stimuli
stims = overview()
plot_stimuli(stims, mask=False, save=None)
