diff --git a/pyzebra/ccl_findpeaks.py b/pyzebra/ccl_findpeaks.py
index 6e5ba56..fc52425 100644
--- a/pyzebra/ccl_findpeaks.py
+++ b/pyzebra/ccl_findpeaks.py
@@ -15,54 +15,49 @@ def ccl_findpeaks(
                         i.e. will only detect peaks above 75% of max intensity
 
             prominence - defines a drop of values that must be between two peaks, must be positive number
-                        i.e. if promimence is 20, it will detect two neigbouring peaks of 300 and 310 intesities, 
+                        i.e. if promimence is 20, it will detect two neigbouring peaks of 300 and 310 intesities,
                         if none of the itermediate values are lower that 290
 
             smooth  - if true, smooths data by savitzky golay filter, if false - no smoothing
 
             window_size - window size for savgol filter, must be odd positive integer
 
-            poly_order =  order of the polynomial used in savgol filter, must be positive integer smaller than 
+            poly_order =  order of the polynomial used in savgol filter, must be positive integer smaller than
             window_size returns: dictionary with following structure:
                                 D{M34{  'num_of_peaks': 1,              #num of peaks
                                         'peak_indexes': [20],           # index of peaks in omega array
-                                        'peak_heights': [90.],          # height of the peaks (if data vere smoothed 
+                                        'peak_heights': [90.],          # height of the peaks (if data vere smoothed
                                                                         its the heigh of the peaks in smoothed data)
     """
 
     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: