Clean up RHS2007 plotting code a bit

stimuli/papers/RHS2007.py

@@ -161,53 +161,31 @@ def bullseye_thick():
 
 if __name__ == "__main__":
     import matplotlib.pyplot as plt
-    plot_all = True
-    if plot_all:
-        stims = {
-            "WE_thick": WE_thick,
-            "WE_thin_wide": WE_thin_wide,
-            "WE_dual": WE_dual,
-            "WE_anderson": WE_anderson,
-            "WE_howe": WE_howe,
-            "WE_radial_thick_small": WE_radial_thick_small,
-            "WE_radial_thick": WE_radial_thick,
-            "WE_radial_thin_small": WE_radial_thin_small,
-            "WE_radial_thin": WE_radial_thin,
-            "WE_circular1": WE_circular1,
-            "WE_circular05": WE_circular05,
-            "WE_circular025": WE_circular025,
-            "grating_induction": grating_induction,
-            "sbc_large": sbc_large,
-            "sbc_small": sbc_small,
-            "todorovic_equal": todorovic_equal,
-            "todorovic_in_large": todorovic_in_large,
-            "todorovic_in_small": todorovic_in_small,
-            "checkerboard_0.16": checkerboard_016,
-            "checkerboard_0.938": checkerboard_0938,
-            "checherboard_2.09": checkerboard209
-        }
-
-        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+"")
-            st = stim()
-            img, mask = st["img"], st["mask"]
-            img = np.dstack([img, img, img])
-
-            mask = np.insert(np.expand_dims(mask, 2), 1, 0, axis=2)
-            mask = np.insert(mask, 2, 0, axis=2)
-            final = mask + img
-            final /= np.max(final)
-
-            plt.subplot(a, a, i + 1)
-            plt.title(stim_name + " - img")
-            plt.imshow(final)
-
-        plt.tight_layout()
-
-    else:
-        plt.imshow(img, cmap='gray')
-
-    plt.savefig("overview_RHS2007.png")
+
+    stims = {}
+    for stimname in __all__:
+        print("Generating " + stimname)
+        try:
+            stims[stimname] = globals()[stimname]()
+        except NotImplementedError:
+            print("-- not implemented")
+
+    # Plot each stimulus+mask
+    n_stim = math.ceil(math.sqrt(len(stims)))
+    plt.figure(figsize=(n_stim * 3, n_stim * 3))
+    for i, (stim_name, stim) in enumerate(stims.items()):
+        img, mask = stim["img"], stim["mask"]
+        img = np.dstack([img, img, img])
+
+        mask = np.insert(np.expand_dims(mask, 2), 1, 0, axis=2)
+        mask = np.insert(mask, 2, 0, axis=2)
+        final = mask + img
+        final /= np.max(final)
+
+        plt.subplot(n_stim, n_stim, i + 1)
+        plt.title(stim_name)
+        plt.imshow(final)
+
+    plt.tight_layout()
+
     plt.show()