Murray2020 demo script to plot stimuli and masks

stimuli/papers/murray2020_script.py

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+import numpy as np
+import math
+import matplotlib.pyplot as plt
+import stimuli
+
+
+def argyle_illusion():
+    return stimuli.illusions.argyle_illusion()
+
+def argyle_control_illusion():
+    return stimuli.illusions.argyle_control_illusion()
+
+def argyle_long_illusion():
+    return stimuli.illusions.argyle_long_illusion()
+
+def snake_illusion():
+    return stimuli.illusions.snake_illusion()
+
+def snake_control_illusion():
+    return stimuli.illusions.snake_control_illusion()
+
+def koffka_adelson_illusion():
+    return stimuli.illusions.koffka_adelson_illusion()
+
+def koffka_broken_illusion():
+    return stimuli.illusions.koffka_broken_illusion()
+
+def koffka_connected_illusion():
+    return stimuli.illusions.koffka_connected_illusion()
+
+def checkassim_illusion():
+    return stimuli.illusions.checkassim_illusion()
+
+def simcon_illusion():
+    return stimuli.illusions.simcon_illusion()
+
+def simcon_articulated_illusion():
+    return stimuli.illusions.simcon_articulated_illusion()
+
+def white_illusion():
+    return stimuli.illusions.white_illusion()
+
+
+if __name__ == '__main__':
+
+    ppd = 16
+
+    plot_all = True
+    if plot_all:
+        stims = {"argyle_illusion": argyle_illusion(), 
+                 "argyle_control_illusion": argyle_control_illusion(),
+                 #"argyle_long_illusion": argyle_long_illusion(),
+                 "snake_illusion": snake_illusion(),
+                 "snake_control_illusion": snake_control_illusion(),
+                 "koffka_adelson_illusion": koffka_adelson_illusion(),
+                 "koffka_broken_illusion": koffka_broken_illusion(),
+                 "koffka_connected_illusion": koffka_connected_illusion(),
+                 "checkassim_illusion": checkassim_illusion(),
+                 "simcon_illusion": simcon_illusion(),
+                 "simcon_articulated_illusion": simcon_articulated_illusion(),
+                 "white_illusion": white_illusion()          
+                 }
+
+        a = math.ceil(math.sqrt(len(stims)))
+        plt.figure(figsize=(a*3, a*3))
+        for i, (stim_name, stim) in enumerate(stims.items()):
+            print("Generating", stim_name+"")
+
+            mask = stim['mask']*100
+            final = (stim['img']+mask)/np.max(stim['img']+stim['mask'])
+
+            plt.subplot(a, a, i + 1)
+            plt.title(stim_name + " - img")
+            plt.imshow(final)
+
+        plt.tight_layout()
+
+    else:
+        plt.imshow(stim['img'], cmap='gray')
+
+    plt.savefig("overview_murray2020.png")
+    plt.show()
+