added Stimulus class and made all functions return a stimulus object

stimuli/Stimulus.py

@@ -0,0 +1,5 @@
+class Stimulus():
+    def __init__(self):
+        target_mask = None
+        img = None
+

stimuli/illusions/benary_cross.py

@@ -1,6 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
-
+from stimuli.Stimulus import Stimulus
 
 def benarys_cross(ppd=10, cross_size=(8,8,8,8), cross_thickness=5, padding=(1,1,1,1), target_size=2, back=1., cross=0., target=.5):
     """
@@ -51,13 +51,16 @@ def benarys_cross(ppd=10, cross_size=(8,8,8,8), cross_thickness=5, padding=(1,1,
     img = pad_img(img, padding, ppd, back)
     mask = pad_img(mask, padding, ppd, 0)
 
-    return (img, mask)
+    stim = Stimulus()
+    stim.target_mask = mask
+    stim.img = img
+    return stim
 
 def domijan2015():
     return benarys_cross(ppd=10, cross_size=(3,3,3,3), cross_thickness=2.1, padding=(.9,1.0,.9,1.0),target_size=1.1,  back=9., cross=1., target=5.)
 
 if __name__ == '__main__':
     import matplotlib.pyplot as plt
-    img, mask = benarys_cross()
-    plt.imshow(img, cmap='gray')
+    stim = benarys_cross()
+    plt.imshow(stim.img, cmap='gray')
     plt.show()

stimuli/illusions/bullseye.py

@@ -1,6 +1,7 @@
 import numpy as np
 from stimuli.illusions.rings import ring_pattern
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 def bullseye_illusion(ppd=10, n_rings=8, ring_width=.5, target_pos_l=0, target_pos_r=0, padding=(1.0,1.0,1.0,1.0), back=0., rings=1., target=.5):
     """
@@ -20,12 +21,19 @@ def bullseye_illusion(ppd=10, n_rings=8, ring_width=.5, target_pos_l=0, target_p
     -------
     2D numpy array
     """
-    img1, mask1 = ring_pattern(n_rings=n_rings, target_pos_l=target_pos_l, ring_width=ring_width, padding=padding,
+    stim1 = ring_pattern(n_rings=n_rings, target_pos_l=target_pos_l, ring_width=ring_width, padding=padding,
                         back=back, rings=rings, target=target, invert_rings=False, double=False)
-    img2, mask2 = ring_pattern(n_rings=n_rings, target_pos_l=target_pos_r, ring_width=ring_width, padding=padding,
+    stim2 = ring_pattern(n_rings=n_rings, target_pos_l=target_pos_r, ring_width=ring_width, padding=padding,
                         back=back, rings=rings, target=target, invert_rings=True, double=False)
 
-    return (np.hstack((img1, img2)), np.hstack((mask1, mask2)))
+    img = np.hstack((stim1.img, stim2.img))
+    mask = np.hstack((stim1.target_mask, stim2.target_mask))
+
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 def domijan2015():
     img =  bullseye_illusion(n_rings=8, ring_width=.5, target_pos_l=0, target_pos_r=0, padding=(.9,1.0,.9,1.0), back=1., rings=9., target=5.)
@@ -39,6 +47,6 @@ def RHS2007_bullseye_thick():
 
 if __name__ == '__main__':
     import matplotlib.pyplot as plt
-    img, mask = bullseye_illusion()
-    plt.imshow(img, cmap='gray')
+    stim = bullseye_illusion()
+    plt.imshow(stim.img, cmap='gray')
     plt.show()

stimuli/illusions/checkerboard_contrast_contrast.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 
 def checkerboard_contrast_contrast_effect(ppd=10, n_checks=8, check_size=1.0, target_length=4, padding=(1.0,1.0,1.0,1.0), check1=0., check2=2.,
@@ -53,7 +54,13 @@ def checkerboard_contrast_contrast_effect(ppd=10, n_checks=8, check_size=1.0, ta
     mask2 = np.repeat(np.repeat(mask_arr2, check_size_px, axis=0), check_size_px, axis=1)
     mask2 = pad_img(mask2, padding, ppd, 0)
 
-    return (np.hstack([img1, img2]), np.hstack([mask1, mask2]))
+    img = np.hstack([img1, img2])
+    mask =  np.hstack([mask1, mask2])
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 
 

stimuli/illusions/checkerboard_sbc.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 def checkerboard_contrast(ppd=10, n_checks=8, check_size=1.0, target1_coords=(3, 2), target2_coords=(5, 5), extend_targets=False,
                           padding=(1.0,1.0,1.0,1.0), check1=0., check2=1., target=.5):
@@ -51,7 +52,11 @@ def checkerboard_contrast(ppd=10, n_checks=8, check_size=1.0, target1_coords=(3,
     img = pad_img(img, padding, ppd, (check1+check2)/2)
     mask = pad_img(mask, padding, ppd, 0)
 
-    return (img, mask)
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 
 def domijan2015():

stimuli/illusions/cornsweet.py

@@ -1,4 +1,5 @@
 import numpy as np
+from stimuli.Stimulus import Stimulus
 
 def cornsweet(size=(10,10), ppd=10, contrast=0.5, ramp_width=2, exponent=2.75,
               mean_lum=.5):
@@ -55,7 +56,12 @@ def cornsweet(size=(10,10), ppd=10, contrast=0.5, ramp_width=2, exponent=2.75,
     stim[:, :size[1] // 2] += profile[::-1]
     stim[:, size[1] // 2:] -= profile
     mask = None
-    return (stim, mask)
+
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 
 if __name__ == '__main__':

stimuli/illusions/cube.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 
 def cube_illusion(ppd=10, n_cells=4, target_length=1, cell_long=1.5, cell_short=1.0, corner_cell_width=1.8, corner_cell_height=1.8,
@@ -109,11 +110,16 @@ def cube_illusion(ppd=10, n_cells=4, target_length=1, cell_long=1.5, cell_short=
     mask = pad_img(mask, padding, ppd, 0)
 
     if double:
-        img2, mask2 = cube_illusion(ppd=ppd, n_cells=n_cells, target_length=target_length, cell_long=cell_long, cell_short=cell_short, corner_cell_width=corner_cell_width, corner_cell_height=corner_cell_height,
+        stim2 = cube_illusion(ppd=ppd, n_cells=n_cells, target_length=target_length, cell_long=cell_long, cell_short=cell_short, corner_cell_width=corner_cell_width, corner_cell_height=corner_cell_height,
                              cell_spacing=cell_spacing, padding=padding, occlusion_overlap=occlusion_overlap, back=grid, grid=back, target=target, double=False)
-        return (np.hstack([img, img2]), np.hstack([mask, mask2]))
-    else:
-        return (img, mask)
+        img = np.hstack([img, stim2.img])
+        mask = np.hstack([mask, stim2.target_mask])
+
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 
 def domijan2015():

stimuli/illusions/disc_and_ring.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils.utils import degrees_to_pixels, resize_array
+from stimuli.Stimulus import Stimulus
 
 
 def disc_and_ring(shape=(10,10), radii=(9,5), values=(200, 100), bg=0, ppd=30, ssf=5):
@@ -48,7 +49,11 @@ def disc_and_ring(shape=(10,10), radii=(9,5), values=(200, 100), bg=0, ppd=30, s
 
     mask = None
 
-    return (np.dot(sampler, np.dot(stim, sampler.T)) / ssf ** 2, mask)
+    stim = Stimulus()
+    stim.img = np.dot(sampler, np.dot(stim, sampler.T)) / ssf ** 2
+    stim.target_mask = mask
+
+    return stim
 
 
 if __name__ == '__main__':

stimuli/illusions/dungeon.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 
 def dungeon_illusion(ppd=10, n_cells=5, target_radius=1, cell_size=1.0, padding=(1.0,1.0,1.0,1.0), back=0., grid=1., target=0.5, double=True):
@@ -51,10 +52,15 @@ def dungeon_illusion(ppd=10, n_cells=5, target_radius=1, cell_size=1.0, padding=
     mask = pad_img(mask, padding, ppd, False)
 
     if double:
-        img2, mask2 = dungeon_illusion(ppd=ppd, n_cells=n_cells, target_radius=target_radius, cell_size=cell_size, padding=padding,  back=grid, grid=back, target=target, double=False)
-        return (np.hstack([img, img2]), np.hstack([mask, mask2]))
-    else:
-        return (img, mask)
+        stim2 = dungeon_illusion(ppd=ppd, n_cells=n_cells, target_radius=target_radius, cell_size=cell_size, padding=padding,  back=grid, grid=back, target=target, double=False)
+        img = np.hstack([img, stim2.img])
+        mask = np.hstack([mask, stim2.target_mask])
+
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 def domijan2015():
     return dungeon_illusion(ppd=10, n_cells=5, target_radius=1,cell_size=1.0, padding=(.9,1.1,.9,1.1), back=1.0, grid=9.0, target=5.0, double=True)

stimuli/illusions/grating.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 
 def grating_illusion(ppd=10, n_bars=5, target_length=1, bar_width=1.0, bar_height=8.0, padding=(1.0,1.0,1.0,1.0), back=0., grid=1., target=0.5, double=True):
@@ -50,11 +51,16 @@ def grating_illusion(ppd=10, n_bars=5, target_length=1, bar_width=1.0, bar_heigh
 
 
     if double:
-        img2, mask2 = grating_illusion(ppd=ppd, n_bars=n_bars, target_length=target_length, bar_width=bar_width, bar_height=bar_height,
+        stim2 = grating_illusion(ppd=ppd, n_bars=n_bars, target_length=target_length, bar_width=bar_width, bar_height=bar_height,
                                 padding=padding, back=grid, grid=back, target=target, double=False)
-        return (np.hstack([img, img2]), np.hstack([mask, mask2]))
-    else:
-        return (img, mask)
+        img = np.hstack([img, stim2.img])
+        mask = np.hstack([mask, stim2.target_mask])
+
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 def domijan2015():
     return grating_illusion(ppd=10, n_bars=5, target_length=1, bar_width=1.0, bar_height=8.1, padding=(.9,1.0,.9,1.1), back=1, grid=9, target=5, double=True)

stimuli/illusions/grating_induction.py

@@ -1,6 +1,7 @@
 import numpy as np
 from scipy.ndimage.filters import gaussian_filter
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 import stimuli
 
@@ -26,7 +27,11 @@ def grating_illusion(shape=(10,10), ppd=40, frequency=0.5, target_height=0.5, bl
     img = pad_img(img, padding, ppd, target)
     mask = pad_img(mask, padding, ppd, 0)
 
-    return (img, mask)
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 def RHS2007_grating_induction():
     total_height, total_width, ppd = (32,)*3

stimuli/illusions/rings.py

@@ -1,5 +1,6 @@
 import numpy as np
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 def ring_pattern(ppd=10, n_rings=8, target_pos_l=4, target_pos_r=3, ring_width=.5, padding=(1.0,1.0,1.0,1.0,), back=0., rings=1., target=.5, invert_rings=False, double=True, ):
     """
@@ -63,11 +64,16 @@ def ring_pattern(ppd=10, n_rings=8, target_pos_l=4, target_pos_r=3, ring_width=.
 
     # create right half of stimulus
     if double:
-        img2, mask2 = ring_pattern(ppd=ppd, n_rings=n_rings, target_pos_l=target_pos_r, target_pos_r=0, ring_width=ring_width,
+        stim2 = ring_pattern(ppd=ppd, n_rings=n_rings, target_pos_l=target_pos_r, target_pos_r=0, ring_width=ring_width,
                             padding=padding, back=back, rings=rings, target=target, invert_rings=invert_rings, double=False)
-        return (np.hstack([img, img2]), np.hstack([mask, mask2]))
-    else:
-        return (img, mask)
+        img = np.hstack([img, stim2.img])
+        mask = np.hstack([mask, stim2.target_mask])
+
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 def domijan2015():
     img = ring_pattern(ppd=10, n_rings=8, target_pos_l=4, target_pos_r=3, ring_width=.5, padding=(.9,1.0,.9,1.0), back=1., rings=9., target=5., invert_rings=False, double=True)

stimuli/illusions/sbc.py

@@ -1,6 +1,7 @@
 import numpy as np
 import stimuli
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 
 def simultaneous_brightness_contrast(ppd=10, target_shape=(5,5), padding=(2,2,2,2), inner_padding=(3,3,3,3), left=1., right=0., target=.5):
@@ -39,7 +40,11 @@ def simultaneous_brightness_contrast(ppd=10, target_shape=(5,5), padding=(2,2,2,
     img = pad_img(img, padding, ppd, target)
     mask = pad_img(mask, padding, ppd, 0)
 
-    return (img, mask)
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
+
+    return stim
 
 
 def domijan2015():

stimuli/illusions/todorovic.py

@@ -3,6 +3,7 @@
 import math
 
 from stimuli.utils import degrees_to_pixels, pad_img
+from stimuli.Stimulus import Stimulus
 
 
 def todorovic_illusion(target_shape=(4,4), ppd=10, covers_shape=(2.5, 2.5), spacing=(1.5,1.5,1.5,1.5), inner_padding=(3,3,3,3), padding=(2,2,2,2), back=0., grid=1., target=.5, double=True):
@@ -72,16 +73,19 @@ def todorovic_illusion(target_shape=(4,4), ppd=10, covers_shape=(2.5, 2.5), spac
 
     # create right half of stimulus
     if double:
-        img2, mask2 = todorovic_illusion(target_shape=target_shape, ppd=ppd, covers_shape=covers_shape, spacing=spacing,
+        stim2 = todorovic_illusion(target_shape=target_shape, ppd=ppd, covers_shape=covers_shape, spacing=spacing,
                                   padding=(0,0,0,0), inner_padding=inner_padding, back=grid, grid=back, target=target, double=False)
-        img = np.hstack([img, img2])
-        mask = np.hstack([mask, mask2])
+        img = np.hstack([img, stim2.img])
+        mask = np.hstack([mask, stim2.target_mask])
 
     img = pad_img(img, padding, ppd, target)
     mask = pad_img(mask, padding, ppd, target)
 
-    return (img, mask)
+    stim = Stimulus()
+    stim.img = img
+    stim.target_mask = mask
 
+    return stim
 
 def domijan2015():
     return todorovic_illusion(target_shape=(4.1, 4.1), ppd=10, covers_shape=(3.1, 3.1), spacing=(1.5, 1.5, 1.5, 1.5), inner_padding=(2.9,3.0, 2.9,3.0 ),