copy incoming array by default: normalize, scale

modules/util/util.py

@@ -435,7 +435,9 @@ def make_histogram(values, edges):
     return h
 
 
-def normalize(data, param, mean_std_dict, add_noise=False, noise_scale=0.01, seed=None):
+def normalize(data, param, mean_std_dict, add_noise=False, noise_scale=0.01, seed=None, copy=True):
+    if copy:
+        data = data.copy()
 
     if mean_std_dict.get(param) is None:
         return data
@@ -462,7 +464,9 @@ def normalize(data, param, mean_std_dict, add_noise=False, noise_scale=0.01, see
     return data
 
 
-def denormalize(data, param, mean_std_dict):
+def denormalize(data, param, mean_std_dict, copy=True):
+    if copy:
+        data = data.copy()
 
     if mean_std_dict.get(param) is None:
         return data
@@ -479,7 +483,9 @@ def denormalize(data, param, mean_std_dict):
     return data
 
 
-def scale(data, param, mean_std_dict):
+def scale(data, param, mean_std_dict, copy=True):
+    if copy:
+        data = data.copy()
 
     if mean_std_dict.get(param) is None:
         return data
@@ -487,10 +493,6 @@ def scale(data, param, mean_std_dict):
     shape = data.shape
     data = data.flatten()
 
-    if mean_std_dict is None:
-        lo = np.nanmin(data)
-        hi = np.nanmax(data)
-
     _, _, lo, hi = mean_std_dict.get(param)
 
     data -= lo