diff --git a/modules/deeplearning/srcnn_cld_frac.py b/modules/deeplearning/srcnn_cld_frac.py
index c45a69d8fbf56f30ae9a7f2fcd3e73471956fee3..5ea3e60d9fbeab8fd5a4c04a11318992f38b66e2 100644
--- a/modules/deeplearning/srcnn_cld_frac.py
+++ b/modules/deeplearning/srcnn_cld_frac.py
@@ -938,21 +938,21 @@ def analyze(file='/Users/tomrink/cld_opd_frac.npy'):
     true_no_1_2 = (lbls_1_2 == 1) & (pred_1_2 == 1)
     false_no_1_2 = (lbls_1_2 == 0) & (pred_1_2 == 1)
 
-    tp_0 = np.sum(true_0_1)
-    tp_1 = np.sum(true_1_2)
-    tp_2 = np.sum(true_0_2)
+    tp_0 = np.sum(true_0_1).astype(np.float64)
+    tp_1 = np.sum(true_1_2).astype(np.float64)
+    tp_2 = np.sum(true_0_2).astype(np.float64)
 
-    tn_0 = np.sum(true_no_0_1)
-    tn_1 = np.sum(true_no_1_2)
-    tn_2 = np.sum(true_no_0_2)
+    tn_0 = np.sum(true_no_0_1).astype(np.float64)
+    tn_1 = np.sum(true_no_1_2).astype(np.float64)
+    tn_2 = np.sum(true_no_0_2).astype(np.float64)
 
-    fp_0 = np.sum(false_0_1)
-    fp_1 = np.sum(false_1_2)
-    fp_2 = np.sum(false_0_2)
+    fp_0 = np.sum(false_0_1).astype(np.float64)
+    fp_1 = np.sum(false_1_2).astype(np.float64)
+    fp_2 = np.sum(false_0_2).astype(np.float64)
 
-    fn_0 = np.sum(false_no_0_1)
-    fn_1 = np.sum(false_no_1_2)
-    fn_2 = np.sum(false_no_0_2)
+    fn_0 = np.sum(false_no_0_1).astype(np.float64)
+    fn_1 = np.sum(false_no_1_2).astype(np.float64)
+    fn_2 = np.sum(false_no_0_2).astype(np.float64)
 
     recall_0 = tp_0 / (tp_0 + fn_0)
     recall_1 = tp_1 / (tp_1 + fn_1)