snapshot...

modules/deeplearning/cloud_fraction_fcn.py

@@ -68,23 +68,24 @@ print('label_param: ', label_param)
 
 KERNEL_SIZE = 3  # target size: (128, 128)
 N_X = N_Y = 1
+X_LEN = Y_LEN = 128
 
 if KERNEL_SIZE == 3:
-    slc_x = slice(1, int((N_X*128)/2) + 3)
-    slc_y = slice(1, int((N_Y*128)/2) + 3)
-    x_128 = slice(4, N_X*128 + 4)
-    y_128 = slice(4, N_Y*128 + 4)
-elif KERNEL_SIZE == 5:
-    slc_x = slice(3, 135)
-    slc_y = slice(3, 135)
-    slc_x_2 = slice(2, 137, 2)
-    slc_y_2 = slice(2, 137, 2)
-    x_128 = slice(5, 133)
-    y_128 = slice(5, 133)
-    t = np.arange(1, 67, 0.5)
-    s = np.arange(1, 67, 0.5)
-    x_2 = np.arange(68)
-    y_2 = np.arange(68)
+    slc_x = slice(1, int((N_X*X_LEN)/2) + 3)
+    slc_y = slice(1, int((N_Y*Y_LEN)/2) + 3)
+    x_128 = slice(4, N_X*X_LEN + 4)
+    y_128 = slice(4, N_Y*Y_LEN + 4)
+# elif KERNEL_SIZE == 5: These no longer apply here
+#     slc_x = slice(3, 135)
+#     slc_y = slice(3, 135)
+#     slc_x_2 = slice(2, 137, 2)
+#     slc_y_2 = slice(2, 137, 2)
+#     x_128 = slice(5, 133)
+#     y_128 = slice(5, 133)
+#     t = np.arange(1, 67, 0.5)
+#     s = np.arange(1, 67, 0.5)
+#     x_2 = np.arange(68)
+#     y_2 = np.arange(68)
 # ----------------------------------------