"""Modelfest dataset from Carney et al (1999) https://doi.org/10.1117/12.348473
This module reproduces all of the stimuli from the Modelfest dataset
prior to the spatiotemporal extension as described in Carney et al (1999)
but normalized between 0 and 1.
More information on Modelfest can be found here:
https://www.visionscience.com/data/modelfest/
Each stimulus is provided by a separate function,
a full list can be found as stimupy.papers.modelfest.__all__
The output of each of these functions is a stimulus dictionary.
For a visual representation of all the stimuli and their mask,
simply run this module as a script:
$ python stimuli/papers/modelfest.py
Attributes
----------
__all__ (list of str): list of all stimulus-functions
that are exported by this module when executing
>>> from stimupy.papers.modelfest import *
References
-----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
from pathlib import Path
import numpy as np
import pandas as pd
from stimupy import checkerboards
from stimupy.components import gaussians, lines, shapes
from stimupy.components.edges import gaussian as gaussian_edge
from stimupy.components.waves import bessel
from stimupy.noises.binaries import binary as binary_noise
from stimupy.stimuli.gabors import gabor
from stimupy.stimuli.plaids import gabors as plaid
from stimupy.utils import pad_dict_to_shape, resize_dict, resolution, roll_dict, stack_dicts
__all__ = [
"GaborPatch1",
"GaborPatch2",
"GaborPatch3",
"GaborPatch4",
"GaborPatch5",
"GaborPatch6",
"GaborPatch7",
"GaborPatch8",
"GaborPatch9",
"GaborPatch10",
"GaborPatch11",
"GaborPatch12",
"GaborPatch13",
"GaborPatch14",
"ElongatedGabor15",
"ElongatedGabor16",
"ElongatedGabor17",
"Baguette18",
"Baguette19",
"Baguette20",
"Baguette21",
"Subthreshold22",
"Subthreshold23",
"Subthreshold24",
"Subthreshold25",
"Gaussians26",
"Gaussians27",
"Gaussians28",
"Gaussians29",
"Edge30",
"Line31",
"Dipole32",
"GaborString33",
"GaborString34",
"Noise35",
"Orientation36",
"Orientation37",
"Plaids38",
"Plaids39",
"Disk40",
"Bessel41",
"Checkerboard42",
"NaturalScene43",
]
# Default values:
PPD = 120 # pixel size of 0.5 arcmin
PPD2 = 60 # pixel size of 1 arcmin (pixel replication)
VISUAL_SIZE = resolution.visual_size_from_shape_ppd(shape=256, ppd=PPD)
mean_lum = 0.5
df = pd.read_csv(Path(__file__).parents[0] / "modelfest_data.csv", header=None)
participants = df[0]
def gen_all(ppd=PPD, skip=False):
stims = {} # save the stimulus-dicts in a larger dict, with name as key
for stim_name in __all__:
print(f"Generating modelfest.{stim_name}")
# Get a reference to the actual function
func = globals()[stim_name]
try:
stim = func(ppd=ppd)
# Accumulate
stims[stim_name] = stim
except NotImplementedError as e:
if not skip:
raise e
# Skip stimuli that aren't implemented
print("-- not implemented")
pass
return stims
[docs]def GaborPatch1(ppd=PPD):
"""GaborPatch1 with fixed size in degrees, Carney et al (1999)
Frequency: 1.12 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 1.12,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 1
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch2(ppd=PPD):
"""GaborPatch2 with fixed size in degrees, Carney et al (1999)
Frequency: 2 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 2,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 5
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch3(ppd=PPD):
"""GaborPatch3 with fixed size in degrees, Carney et al (1999)
Frequency: 2.83 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 2.83,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 9
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch4(ppd=PPD):
"""GaborPatch4 with fixed size in degrees, Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 13
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch5(ppd=PPD):
"""GaborPatch5 with fixed size in degrees, Carney et al (1999)
Frequency: 5.66 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 5.66,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 17
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch6(ppd=PPD):
"""GaborPatch6 with fixed size in degrees, Carney et al (1999)
Frequency: 8 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 8,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 21
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch7(ppd=PPD):
"""GaborPatch7 with fixed size in degrees, Carney et al (1999)
Frequency: 11.3 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 11.3,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 25
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch8(ppd=PPD):
"""GaborPatch8 with fixed size in degrees, Carney et al (1999)
Frequency: 16 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 16,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 29
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch9(ppd=PPD):
"""GaborPatch9 with fixed size in degrees, Carney et al (1999)
Frequency: 22.6 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 22.6,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 33
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch10(ppd=PPD):
"""GaborPatch10 with fixed size in degrees, Carney et al (1999)
Frequency: 30 cpd
Gaussian window: sx=sy=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 30,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 37
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch11(ppd=PPD):
"""GaborPatch11 with fixed size in cycles (~1 octave), Carney et al (1999)
Frequency: 2 cpd
Gaussian window: sx=sy=0.28 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 2,
"sigma": 0.28,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 41
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch12(ppd=PPD):
"""GaborPatch12 with fixed size in cycles (~1 octave), Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sx=sy=0.14 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": 0.14,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 45
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch13(ppd=PPD):
"""GaborPatch13 with fixed size in cycles (~1 octave), Carney et al (1999)
Frequency: 8 cpd
Gaussian window: sx=sy=0.07 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 8,
"sigma": 0.07,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 49
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborPatch14(ppd=PPD):
"""GaborPatch14 with fixed size in cycles (~1 octave), Carney et al (1999)
Frequency: 16 cpd
Gaussian window: sx=sy=0.035 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 16,
"sigma": 0.035,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 53
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def ElongatedGabor15(ppd=PPD):
"""ElongatedGabor15, Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sy=0.28 (~0.5octave); sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": (0.28, 0.5),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 57
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def ElongatedGabor16(ppd=PPD):
"""ElongatedGabor16, Carney et al (1999)
Frequency: 8 cpd
Gaussian window: sy=0.14 (~0.5octave); sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 8,
"sigma": (0.14, 0.5),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 61
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def ElongatedGabor17(ppd=PPD):
"""ElongatedGabor17, Carney et al (1999)
Frequency: 16 cpd
Gaussian window: sy=0.07 (~0.5octave); sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 16,
"sigma": (0.07, 0.5),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 65
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Baguette18(ppd=PPD):
"""Baguette18 (elongated Gabors; varying aspect ratios), Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sy=0.14 (~1octave); sx=0.28 deg (~2octaves)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": (0.14, 0.28),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 69
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Baguette19(ppd=PPD):
"""Baguette19 (elongated Gabors; varying aspect ratios), Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sy=0.14 (~1octave); sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": (0.14, 0.5),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 73
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Baguette20(ppd=PPD):
"""Baguette20 (elongated Gabors; varying aspect ratios), Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sy=0.28 (~2octave); sx=0.14 deg (~1octave)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": (0.28, 0.14),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 77
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Baguette21(ppd=PPD):
"""Baguette20 (elongated Gabors; varying aspect ratios), Carney et al (1999)
Frequency: 4 cpd
Gaussian window: sy=0.5 deg; sx=0.14 deg (~1octave)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": (0.5, 0.14),
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 81
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Subthreshold22(ppd=PPD):
"""Subthreshold22 (compound Gabor), Carney et al (1999)
Frequencies: 2 cpd & 2*sqrt(2) cpd
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim1 = gabor(**params, frequency=2)
stim2 = gabor(**params, frequency=2 * np.sqrt(2))
stim1["img"] = stim1["img"] / 2 + stim2["img"] / 2
stim1["grating_mask2"] = stim2["grating_mask"]
stim1["frequency2"] = stim2["frequency"]
stim1["phase_width2"] = stim2["phase_width"]
stim1["n_phases2"] = stim2["n_phases"]
v = 85
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim1, "experimental_data": experimental_data}
[docs]def Subthreshold23(ppd=PPD):
"""Subthreshold23 (compound Gabor), Carney et al (1999)
Frequencies: 2 cpd & 4 cpd
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim1 = gabor(**params, frequency=2)
stim2 = gabor(**params, frequency=4)
stim1["img"] = stim1["img"] / 2 + stim2["img"] / 2
stim1["grating_mask2"] = stim2["grating_mask"]
stim1["frequency2"] = stim2["frequency"]
stim1["phase_width2"] = stim2["phase_width"]
stim1["n_phases2"] = stim2["n_phases"]
v = 89
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim1, "experimental_data": experimental_data}
[docs]def Subthreshold24(ppd=PPD):
"""Subthreshold24 (compound Gabor), Carney et al (1999)
Frequencies: 4 cpd & 4*sqrt(2) cpd
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim1 = gabor(**params, frequency=4)
stim2 = gabor(**params, frequency=4 * np.sqrt(2))
stim1["img"] = stim1["img"] / 2 + stim2["img"] / 2
stim1["grating_mask2"] = stim2["grating_mask"]
stim1["frequency2"] = stim2["frequency"]
stim1["phase_width2"] = stim2["phase_width"]
stim1["n_phases2"] = stim2["n_phases"]
v = 93
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim1, "experimental_data": experimental_data}
[docs]def Subthreshold25(ppd=PPD):
"""Subthreshold24 (compound Gabor), Carney et al (1999)
Frequencies: 4 cpd & 8 cpd
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 0.5,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim1 = gabor(**params, frequency=4)
stim2 = gabor(**params, frequency=8)
stim1["img"] = stim1["img"] / 2 + stim2["img"] / 2
stim1["grating_mask2"] = stim2["grating_mask"]
stim1["frequency2"] = stim2["frequency"]
stim1["phase_width2"] = stim2["phase_width"]
stim1["n_phases2"] = stim2["n_phases"]
v = 97
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim1, "experimental_data": experimental_data}
[docs]def Gaussians26(ppd=PPD):
"""Gaussians26, Carney et al (1999)
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 0.5,
"intensity_max": 1,
"origin": "center",
}
stim = gaussians.gaussian(**params)
stim["img"] = stim["img"] / 2 + 0.5
v = 101
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Gaussians27(ppd=PPD):
"""Gaussians27, Carney et al (1999)
Gaussian window: sy=sx=8.43 arcmin
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 8.43 / 60,
"intensity_max": 1,
"origin": "center",
}
stim = gaussians.gaussian(**params)
stim["img"] = stim["img"] / 2 + 0.5
v = 105
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Gaussians28(ppd=PPD):
"""Gaussians28, Carney et al (1999)
Gaussian window: sy=sx=2.106 arcmin
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 2.106 / 60,
"intensity_max": 1,
"origin": "center",
}
stim = gaussians.gaussian(**params)
stim["img"] = stim["img"] / 2 + 0.5
v = 109
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Gaussians29(ppd=PPD):
"""Gaussians29, Carney et al (1999)
Gaussian window: sy=sx=1.05 arcmin
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"sigma": 1.05 / 60,
"intensity_max": 1,
"origin": "center",
}
stim = gaussians.gaussian(**params)
stim["img"] = stim["img"] / 2 + 0.5
v = 113
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Edge30(ppd=PPD):
"""Edge30, Carney et al (1999)
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
stim = gaussian_edge(visual_size=VISUAL_SIZE, ppd=ppd, rotation=-90, sigma=0.5)
v = 117
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Line31(ppd=PPD):
"""Line31: line x Gaussian, Carney et al (1999)
Line width: 0.5 arcmin
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
stim = lines.line(
visual_size=VISUAL_SIZE,
ppd=ppd,
line_length=VISUAL_SIZE.width,
line_width=resolution.visual_angle_from_length_ppd(length=0.5, ppd=PPD2),
rotation=90,
intensity_background=0.5,
)
window = gaussians.gaussian(visual_size=VISUAL_SIZE, ppd=ppd, sigma=0.5)
img = (stim["img"] - 0.5) * window["img"] + 0.5
stim["img"] = img
stim["sigma"] = window["sigma"]
v = 121
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Dipole32(ppd=PPD):
"""Dipole32: lines x Gaussian, Carney et al (1999)
Line width: 3 px =
Separation: 1 px =
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
stim = lines.dipole(
visual_size=VISUAL_SIZE,
ppd=ppd,
line_length=VISUAL_SIZE.width,
line_width=resolution.visual_angle_from_length_ppd(length=1, ppd=PPD),
line_gap=resolution.visual_angle_from_length_ppd(length=2, ppd=PPD),
rotation=270,
)
stim = roll_dict(stim, -1, axes=0)
window = gaussians.gaussian(visual_size=VISUAL_SIZE, ppd=ppd, sigma=0.5)
img = (stim["img"] - 0.5) * window["img"] + 0.5
stim["img"] = img
stim["sigma"] = window["sigma"]
v = 125
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborString33(ppd=PPD):
"""GaborString33 - 5 collinear in-phase Gabors, Carney et al (1999)
Frequency: 8 cpd
Gaussian window of individual Gabors: sx=sy=0.07 deg (~1octave)
Separation: 5sx
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE.width / 6,
"ppd": ppd,
"frequency": 8,
"sigma": 0.07,
"rotation": -90,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
# Stack collinear Gabors horizontally and pad
stimc = stack_dicts(stim, stim)
stimc = stack_dicts(stimc, stimc)
stimc = stack_dicts(stimc, stim)
stimc = pad_dict_to_shape(stimc, (256, 256), pad_value=0.5)
stim["img"] = stimc["img"]
stim["grating_mask"] = stimc["grating_mask"]
stim["visual_size"] = stimc["visual_size"]
stim["shape"] = stimc["shape"]
stim = roll_dict(stim, (-1, -1), axes=(0, 1))
v = 129
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def GaborString34(ppd=PPD):
"""GaborString33 - 5 collinear out-of-phase Gabors, Carney et al (1999)
Frequency: 8 cpd
Gaussian window of individual Gabors: sx=sy= deg (~1octave)
Separation: 5sx
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE.width / 6,
"ppd": ppd,
"frequency": 8,
"sigma": 0.07,
"rotation": -90,
"origin": "center",
}
stim1 = gabor(**params, phase_shift=-90)
stim2 = gabor(**params, phase_shift=90)
# Stack collinear Gabors horizontally and pad
stimc = stack_dicts(stim2, stim1)
stimc = stack_dicts(stimc, stim2)
stimc = stack_dicts(stimc, stim1)
stimc = stack_dicts(stimc, stim2)
stimc = pad_dict_to_shape(stimc, (256, 256), pad_value=0.5)
stim1["img"] = stimc["img"]
stim1["grating_mask"] = stimc["grating_mask"]
stim1["visual_size"] = stimc["visual_size"]
stim1["shape"] = stimc["shape"]
stim1["phase_shift2"] = stim2["phase_shift"]
stim1 = roll_dict(stim1, (-1, -1), axes=(0, 1))
v = 133
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim1, "experimental_data": experimental_data}
def Noise35_random(ppd=PPD):
"""Noise35 - binary noise x Gaussian, Carney et al (1999)
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
stim = binary_noise(visual_size=VISUAL_SIZE, ppd=ppd / 2, rms_contrast=1)
stim = resize_dict(stim, (2, 2))
window = gaussians.gaussian(visual_size=VISUAL_SIZE, ppd=ppd, sigma=0.5)
img = stim["img"] * window["img"]
stim["img"] = img / 2 + 0.5
stim["mask"] = np.zeros(img.shape).astype(int)
return stim
[docs]def Noise35(ppd=PPD):
"""Noise35 - binary noise x Gaussian, Carney et al (1999)
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
# Read natural image from Modelfest
img = read_tif(Path(__file__).parents[0] / "modelfest_noise.tif")
img = img / 255
stim = {
"img": img,
"visual_size": VISUAL_SIZE,
"shape": img.shape,
"ppd": PPD,
"intensity_range": (img.min(), img.max()),
}
v = 169
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
mask = np.zeros(img.shape).astype(int)
return {**stim, "mask": mask, "experimental_data": experimental_data}
[docs]def Orientation36(ppd=PPD):
"""Orientation36 - oriented Gabor, Carney et al (1999)
Frequency: 4 cpd
Rotation: 45 deg
Gaussian window: sx=sy=0.14 deg (~1octave)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": 0.14,
"rotation": -45,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 141
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Orientation37(ppd=PPD):
"""Orientation37 - oriented Gabor, Carney et al (1999)
Frequency: 4 cpd
Rotation: 0 deg
Gaussian window: sx=sy=0.14 deg (~1octave)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": 0.14,
"rotation": 0,
"phase_shift": 90,
"origin": "center",
}
stim = gabor(**params)
v = 145
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Plaids38(ppd=PPD):
"""Plaids38 - compound Gabors, Carney et al (1999)
Frequency: 4 cpd
Rotation: 0 & 90 deg
Gaussian window: sx=sy=0.14 deg (~1octave)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": 0.14,
"phase_shift": 90,
"origin": "center",
"round_phase_width": False,
}
stim = plaid(
gabor_parameters1={**params, "rotation": 0},
gabor_parameters2={**params, "rotation": -90},
)
v = 149
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Plaids39(ppd=PPD):
"""Plaids39 - compound Gabors, Carney et al (1999)
Frequency: 4 cpd
Rotation: 45 & 90 deg
Gaussian window: sx=sy=0.14 deg (~1octave)
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 4,
"sigma": 0.14,
"phase_shift": 90,
"origin": "center",
}
stim = plaid(
gabor_parameters1={**params, "rotation": -45},
gabor_parameters2={**params, "rotation": -90},
)
v = 153
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Disk40(ppd=PPD):
"""Disk40 - Carney et al (1999)
Diameter: 0.25 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
stim = shapes.disc(
visual_size=VISUAL_SIZE, ppd=ppd, radius=0.1249, origin="center", intensity_background=0.5
)
stim = roll_dict(stim, (-2, -2), axes=(0, 1))
v = 157
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Bessel41(ppd=PPD):
"""Bessel41 - Bessel x Gaussian, Carney et al (1999)
Frequency: 4cpd
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
stim = bessel(visual_size=VISUAL_SIZE, ppd=ppd, frequency=4, origin="center")
window = gaussians.gaussian(visual_size=VISUAL_SIZE, ppd=ppd, sigma=0.5)
stim["sigma"] = window["sigma"]
# Apply Gaussian windows to Bessel
stim["img"] = (stim["img"] - stim["img"].mean()) * window["img"]
# Set "background" intensity to 0.5 and make sure that max intensity = 1
stim["img"] = stim["img"] / stim["img"].max() / 2 + 0.5
v = 161
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def Checkerboard42(ppd=PPD):
"""Checkerboard42 - Checkerboard x Gaussian, Carney et al (1999)
Frequency: 4cpd fundamental
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
params = {
"visual_size": VISUAL_SIZE,
"ppd": ppd,
"frequency": 2.81,
"rotation": -45,
"round_phase_width": False,
"intensity_checks": (1.0, 0.0),
}
stim = checkerboards.checkerboard(**params)
window = gaussians.gaussian(visual_size=VISUAL_SIZE, ppd=ppd, sigma=0.5)
img = (stim["img"] - 0.5) * window["img"] + 0.5
stim["img"] = img
stim["sigma"] = window["sigma"]
v = 165
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
return {**stim, "experimental_data": experimental_data}
[docs]def NaturalScene43(ppd=PPD):
"""NaturalScene43 - Natural image x Gaussian, Carney et al (1999)
Gaussian window: sy=sx=0.5 deg
Parameters
----------
ppd : Sequence[Number, Number], Number, or None
pixels per degree [vertical, horizontal]
Returns
-------
dict[str, Any]
dict with the stimulus (key: "img") and additional keys containing
stimulus parameters
References
----------
Carney, T., Klein, S. A., Tyler, C. W., Silverstein, A. D., Beutter, B., Levi, D.,
... & Eckstein, M. P. (1999).
Development of an image/threshold database
for designing and testing human vision models.
Proceedings of SPIE, 3644, 542-551.
https://doi.org/10.1117/12.348473
"""
# Read natural image from Modelfest
img = read_tif(Path(__file__).parents[0] / "modelfest_natural_scene.tif")
img /= 255
stim = {
"img": img,
"visual_size": VISUAL_SIZE,
"shape": img.shape,
"ppd": PPD,
"intensity_range": (img.min(), img.max()),
}
v = 169
experimental_data = {
"participants": participants,
"thresholds1": df[v],
"thresholds2": df[v + 1],
"thresholds3": df[v + 2],
"thresholds4": df[v + 3],
}
mask = np.zeros(img.shape).astype(int)
return {**stim, "mask": mask, "experimental_data": experimental_data}
def read_tif(filename):
from PIL import Image
img = np.array(Image.open(filename)).astype(float)
return img
if __name__ == "__main__":
from stimupy.utils import plot_stimuli
stims = gen_all(skip=True)
plot_stimuli(stims, mask=False, units="visual_size")
