diff --git a/code/useful_functions.py b/code/useful_functions.py
index 7153e09..c259f2c 100644
--- a/code/useful_functions.py
+++ b/code/useful_functions.py
@@ -32,7 +32,7 @@ def all_coming_together(freq_array, power_array, points_list, categories, num_ha
     Returns
     -------
     valid_points : list
-        A list of valid points with their harmonics.
+        A continuous list of harmonics for all valid points.
     color_mapping : dict
         A dictionary mapping categories to corresponding colors.
     category_harmonics : dict
@@ -40,7 +40,7 @@ def all_coming_together(freq_array, power_array, points_list, categories, num_ha
     messages : list
         A list of messages for each point, stating whether it was valid or not.
     """
-    valid_points = []
+    valid_points = []  # A continuous list of harmonics for valid points
     color_mapping = {}
     category_harmonics = {}
     messages = []
@@ -58,7 +58,7 @@ def all_coming_together(freq_array, power_array, points_list, categories, num_ha
         if valid:
             # Step 3: Prepare harmonics if the point is valid
             harmonics, color_map, category_harm = prepare_harmonic(point, category, num_harmonics, color)
-            valid_points.append((point, harmonics))
+            valid_points.extend(harmonics)  # Use extend() to append harmonics in a continuous manner
             color_mapping.update(color_map)
             category_harmonics.update(category_harm)
             messages.append(f"The point {point} is valid.")
@@ -67,6 +67,8 @@ def all_coming_together(freq_array, power_array, points_list, categories, num_ha
     
     return valid_points, color_mapping, category_harmonics, messages
 
+
+
 def AM(EODf, stimulus):
     """
     Calculates the Amplitude Modulation and Nyquist frequency
@@ -426,7 +428,7 @@ def spike_times(stim):
     return spikes, stim_dur, dt # se changed spike_times to spikes so its not the same as name of function
 
 
-def valid_integrals(integral, local_mean, point, threshold = 0.5):
+def valid_integrals(integral, local_mean, point, threshold = 0.1):
     """
     Check if the integral exceeds the threshold compared to the local mean and 
     provide feedback on whether the given point is valid or not.