pyzebra/ccl_findpeaks.py

@@ -33,36 +33,31 @@ def ccl_findpeaks(
     if type(data) is not dict and data["file_type"] != "ccl":
         print("Data is not a dictionary or was not made from ccl file")
 
-    if 0 <= int_threshold <= 1:
-        pass
-    else:
-        int_threshold = 0.75
+    if not 0 <= int_threshold <= 1:
+        int_threshold = 0.8
         print(
             "Invalid value for int_threshold, select value between 0 and 1, new value set to:",
             int_threshold,
         )
-    if isinstance(window_size, int) is True and (window_size % 2) != 0 and window_size >= 1:
-        pass
-    else:
+
+    if isinstance(window_size, int) is False or (window_size % 2) == 0 or window_size <= 1:
         window_size = 7
         print(
-            "Invalid value for window_size, select positive odd integer, new value set to:",
-            window_size,
-        )
-    if isinstance(poly_order, int) is True and window_size > poly_order >= 1:
-        pass
-    else:
+            "Invalid value for window_size, select positive odd integer, new value set to!:",
+            window_size)
+
+    if isinstance(poly_order, int) is False or window_size < poly_order:
         poly_order = 3
         print(
             "Invalid value for poly_order, select positive integer smaller than window_size, new value set to:",
             poly_order,
         )
-    if isinstance(prominence, (int, float)) is True and prominence > 0:
-        pass
-    else:
+
+    if isinstance(prominence, (int, float)) is False and prominence < 0:
         prominence = 50
         print("Invalid value for prominence, select positive number, new value set to:", prominence)
 
+
     omega = data["Measurements"][str(keys)]["omega"]
     counts = np.array(data["Measurements"][str(keys)]["counts"])
     if smooth is True: