first try at histograms

compress_start.py

@@ -66,28 +66,35 @@ if __name__ == '__main__':
                 tiff2.append(os.path.join(scene, s))
             elif s[-6] == '3':
                 tiff3.append(os.path.join(scene, s))
- 
+    
+    cameras = [tiff0, tiff1, tiff2, tiff3]
     diff = []
-    for ii in range(len(tiff1)):
-        image = Image.open(tiff1[ii])    #Open the image and read it as an Image object
-        image = np.array(image)[1:,:]    #Convert to an array, leaving out the first row because the first row is just housekeeping data
-        ar1, ar2 = image.shape
-       
-        ind1, ind2 = np.random.randint(1,ar1-1), np.random.randint(1,ar2-1) #ind1 randomly selects a row, ind2 randomly selects a column, 
-                                                                        #this is now a random pixel selection within the image
+    i = 0
+    for cam in cameras:
+        for ii in range(len(cam)):
+            image = Image.open(cam[ii])    #Open the image and read it as an Image object
+            image = np.array(image)[1:,:]    #Convert to an array, leaving out the first row because the first row is just housekeeping data
+            ar1, ar2 = image.shape
+           
+            ind1, ind2 = np.random.randint(1,ar1-1), np.random.randint(1,ar2-1) #ind1 randomly selects a row, ind2 randomly selects a column, 
+                                                                            #this is now a random pixel selection within the image
+            
+            surrounding = []                                                #initialize a list to be filled the 8 surrounding pixels
+            for i,j in product(np.arange(-1,2), repeat=2):                  #Iterate through the combinations of surrounding pixel indices
+                if i == 0 and j == 0:                                       #Avoid the target pixel
+                    continue
+                else:
+                    surrounding.append(image[ind1+i, ind1+j])               #Add the other 8 pixels to the list
+            diff.append(np.max(surrounding)-np.min(surrounding))
+        plt.subplot(2,2,i+1)
+        plt.hist(diff)
+        i += 1
+    plt.tight_layout()
+    plt.show()
+    
         
-        surrounding = []                                                #initialize a list to be filled the 8 surrounding pixels
-        for i,j in product(np.arange(-1,2), repeat=2):                  #Iterate through the combinations of surrounding pixel indices
-            if i == 0 and j == 0:                                       #Avoid the target pixel
-                continue
-            else:
-                surrounding.append(image[ind1+i, ind1+j])               #Add the other 8 pixels to the list
-        diff.append(np.max(surrounding)-np.min(surrounding))
         
     
-
-    
-    
     
     
     """scene_names = file_extractor("images")