From a9378771acfc9ae96096c61de9ed00c3f3f33761 Mon Sep 17 00:00:00 2001
From: Diana <diana.stoll@stundent.uni-tuebingen.de>
Date: Thu, 24 Oct 2024 15:45:41 +0200
Subject: [PATCH] Changes dianas plot function

---
 code/plot_functions.py | 39 ++++++++++++++-------------------------
 1 file changed, 14 insertions(+), 25 deletions(-)

diff --git a/code/plot_functions.py b/code/plot_functions.py
index 5fb4c17..1de4a75 100644
--- a/code/plot_functions.py
+++ b/code/plot_functions.py
@@ -72,12 +72,14 @@ functions_path = r"C:\Users\diana\OneDrive - UT Cloud\Master\GPs\GP1_Grewe\Proje
 sys.path.append(functions_path)
 import useful_functions as u
 
-def plot_highlighted_integrals(frequency, power, points, color_mapping, points_categories, delta=2.5):
+def plot_highlighted_integrals(ax, frequency, power, points, color_mapping, points_categories, delta=2.5):
     """
-    Plot the power spectrum and highlight integrals that exceed the threshold.
+    Highlight integrals on the existing axes of the power spectrum.
 
     Parameters
     ----------
+    ax : matplotlib.axes.Axes
+        The axes on which to plot the highlighted integrals.
     frequency : np.array
         An array of frequencies corresponding to the power values.
     power : np.array
@@ -93,50 +95,37 @@ def plot_highlighted_integrals(frequency, power, points, color_mapping, points_c
 
     Returns
     -------
-    fig : matplotlib.figure.Figure
-        The created figure object with highlighted integrals.
+    None
     """
-    fig, ax = plt.subplots()
-    ax.plot(frequency, power)  # Plot power spectrum
+    ax.plot(frequency, power)  # Plot power spectrum on the existing axes
     
     for point in points:
-        # Use the imported function to calculate the integral and local mean
-        integral, local_mean, _ = u.calculate_integral(frequency, power, point)
+        # Calculate the integral and local mean
+        integral, local_mean = u.calculate_integral_2(frequency, power, point)
         
-        # Use the imported function to check if the point is valid
+        # Check if the point is valid
         valid = u.valid_integrals(integral, local_mean, point)
         
         if valid:  
             # Define color based on the category of the point
             color = next((c for cat, c in color_mapping.items() if point in points_categories[cat]), 'gray')
             
-            # Find the category of the point
-            point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
-            
             # Shade the region around the point where the integral was calculated
             ax.axvspan(point - delta, point + delta, color=color, alpha=0.3, label=f'{point:.2f} Hz')
 
-            # Print out point, category, and color
-            print(f"{point_category}: Integral: {integral:.5e}, Color: {color}")
-            
             # Annotate the plot with the point and its color
             ax.text(point, max(power) * 0.9, f'{point:.2f}', color=color, fontsize=10, ha='center')
 
-            # Define left and right boundaries of adjacent regions
-            left_boundary = frequency[np.where((frequency >= point - 5 * delta) & (frequency < point - delta))[0][0]]
-            right_boundary = frequency[np.where((frequency > point + delta) & (frequency <= point + 5 * delta))[0][-1]]
-
-            # Add vertical dashed lines at the boundaries of the adjacent regions
-            #ax.axvline(x=left_boundary, color="k", linestyle="--")
-            #ax.axvline(x=right_boundary, color="k", linestyle="--")
+            # Print out point, category, and color
+            point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
+            print(f"{point_category}: Integral: {integral:.5e}, Color: {color}")
     
     ax.set_xlim([0, 1200])
     ax.set_xlabel('Frequency (Hz)')
     ax.set_ylabel('Power')
     ax.set_title('Power Spectrum with Highlighted Integrals')
-    ax.legend()
-    
-    return fig, ax
+    #ax.legend()
+