diff --git a/modules/deeplearning/cnn_cld_frac.py b/modules/deeplearning/cnn_cld_frac.py
index 7c2824a6e08e5f9bd203d321d5f4cf1f31c97f6e..2e78ba0e21fdd42940659af47ad3a3af63d2e3d6 100644
--- a/modules/deeplearning/cnn_cld_frac.py
+++ b/modules/deeplearning/cnn_cld_frac.py
@@ -1048,28 +1048,6 @@ def analyze2(nda_m, nda_i):
                 sub_4x4 = nda_i[k, j*2-1:j*2+3, i*2-1:i*2+3]
                 cf_i[k, j-1, i-1] = np.sum(sub_4x4)
 
-    # cat_0 = cf_m == 0
-    # cat_1 = (cf_m >= 0.1) & (cf_m < 0.13)
-    # cat_2 = (cf_m >= 0.2) & (cf_m < 0.23)
-    # cat_3 = (cf_m >= 0.3) & (cf_m < 0.34)
-    # cat_4 = (cf_m >= 0.4) & (cf_m < 0.45)
-    # cat_5 = (cf_m >= 0.5) & (cf_m < 0.56)
-    # cat_6 = (cf_m >= 0.6) & (cf_m < 0.67)
-    # cat_7 = (cf_m >= 0.7) & (cf_m < 0.78)
-    # cat_8 = (cf_m >= 0.8) & (cf_m < 0.89)
-    # cat_9 = cf_m == 1.0
-    #
-    # cf_m[cat_0] = 0
-    # cf_m[cat_1] = 1
-    # cf_m[cat_2] = 2
-    # cf_m[cat_3] = 3
-    # cf_m[cat_4] = 4
-    # cf_m[cat_5] = 5
-    # cf_m[cat_6] = 6
-    # cf_m[cat_7] = 7
-    # cf_m[cat_8] = 8
-    # cf_m[cat_9] = 9
-
     for k in range(n_imgs):
         cat_0 = (cf_m[k, ] == 0)
         cat_1 = (cf_m[k, ] > 0) & (cf_m[k, ] < 9)