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code/plot_functions.py

@@ -72,14 +72,16 @@ functions_path = r"C:\Users\diana\OneDrive - UT Cloud\Master\GPs\GP1_Grewe\Proje
 sys.path.append(functions_path)
 import useful_functions as u
 import matplotlib.ticker as ticker
+import matplotlib.patches as mpatches
 
 def float_formatter(x, _):
     """Format the y-axis values as floats with a specified precision."""
     return f'{x:.5f}'
 
+
 def plot_highlighted_integrals(ax, frequency, power, points, color_mapping, points_categories, delta=2.5):
     """
-    Highlight integrals on the existing axes of the power spectrum.
+    Highlights integrals on the existing axes of the power spectrum for a given dataset.
 
     Parameters
     ----------
@@ -102,38 +104,40 @@ def plot_highlighted_integrals(ax, frequency, power, points, color_mapping, poin
     -------
     None
     """
-    ax.plot(frequency, power, color = "k")  # Plot power spectrum on the existing axes
+    _, _, AM, df, eodf, nyquist, stim_freq = u.sam_data(sam)
+
+    # Plot the power spectrum on the provided axes
+    ax.plot(frequency, power, color="k")
 
     for point in points:
-        # Calculate the integral and local mean
-        integral, local_mean = u.calculate_integral_2(frequency, power, point)
+        # Identify the category for the current point
+        point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
         
-        # Check if the point is valid
+        # Assign color based on category, or default to grey if unknown
+        color = color_mapping.get(point_category, 'gray')
+        
+        # Calculate the integral and check validity
+        integral, local_mean = u.calculate_integral_2(frequency, power, point)
         valid = u.valid_integrals(integral, local_mean, point)
         
-        if valid:  
-            # Define color based on the category of the point
-            point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
-            color = next((c for cat, c in color_mapping.items() if point in points_categories[cat]), 'gray')
-            
-            # Shade the region around the point where the integral was calculated
+        if valid:
+            # Highlight valid points with a shaded region
             ax.axvspan(point - delta, point + delta, color=color, alpha=0.2, label=f'{point_category}')
 
-            # Text with categories and colors
-            ax.text(1000, 5.8e-5, "AM", fontsize=10, color="green", alpha=0.2)
-            ax.text(1000, 5.6e-5, "Nyquist", fontsize=10, color="blue", alpha=0.2)
-            ax.text(1000, 5.4e-5, "EODf", fontsize=10, color="red", alpha=0.2)
-            ax.text(1000, 5.2e-5, "Stimulus frequency", fontsize=10, color="orange", alpha=0.2)
-            ax.text(1000, 5.0e-5, "EODf of awake fish", fontsize=10, color="purple", alpha=0.2)
-    
+    # Set plot limits and labels
     ax.set_xlim([0, 1200])
     ax.set_ylim([0, 6e-5])
+    ax.axvline(nyquist, color = "k", linestyle = "--")
     ax.set_xlabel('Frequency (Hz)')
     ax.set_ylabel('Power')
-    ax.set_title('Power Spectrum with highlighted Integrals')
+    ax.set_title('Power Spectrum with Highlighted Integrals')
 
     # Apply float formatting to the y-axis
     ax.yaxis.set_major_formatter(ticker.FuncFormatter(float_formatter))
+    ax.legend(loc="upper right")
+
+
+
 
 
 

code/useful_functions.py

@@ -3,40 +3,8 @@ import rlxnix as rlx
 from scipy.signal import welch
 
 def all_coming_together(freq_array, power_array, points_list, categories, num_harmonics_list, colors, delta=2.5, threshold=0.5):
-    """
-    Process a list of points, calculating integrals, checking validity, and preparing harmonics for valid points.
-
-    Parameters
-    ----------
-    freq_array : np.array
-        Array of frequencies corresponding to the power values.
-    power_array : np.array
-        Array of power spectral density values.
-    points_list : list
-        List of harmonic frequency points to process.
-    categories : list
-        List of corresponding categories for each point.
-    num_harmonics_list : list
-        List of the number of harmonics for each point.
-    colors : list
-        List of colors corresponding to each point's category.
-    delta : float, optional
-        Radius of the range for integration around each point (default is 2.5).
-    threshold : float, optional
-        Threshold value to compare integrals with local mean (default is 0.5).
-
-    Returns
-    -------
-    valid_points : list
-        A continuous list of harmonics for all valid points.
-    color_mapping : dict
-        A dictionary mapping categories to corresponding colors.
-    category_harmonics : dict
-        A mapping of categories to their harmonic frequencies.
-    messages : list
-        A list of messages for each point, stating whether it was valid or not.
-    """
-    valid_points = []  # A continuous list of harmonics for valid points
+    # Initialize dictionaries and lists
+    valid_points = []
     color_mapping = {}
     category_harmonics = {}
     messages = []
@@ -46,21 +14,25 @@ def all_coming_together(freq_array, power_array, points_list, categories, num_ha
         num_harmonics = num_harmonics_list[i]
         color = colors[i]
         
-        # Step 1: Calculate the integral for the point
+        # Calculate the integral for the point
         integral, local_mean = calculate_integral_2(freq_array, power_array, point, delta)
         
-        # Step 2: Check if the point is valid
+        # Check if the point is valid
         valid = valid_integrals(integral, local_mean, point, threshold)
         if valid:
-            # Step 3: Prepare harmonics if the point is valid
+            # Prepare harmonics if the point is valid
             harmonics, color_map, category_harm = prepare_harmonic(point, category, num_harmonics, color)
-            valid_points.extend(harmonics)  # Use extend() to append harmonics in a continuous manner
-            color_mapping.update(color_map)
-            category_harmonics.update(category_harm)
+            valid_points.extend(harmonics)
+            color_mapping[category] = color  # Store color for category
+            category_harmonics[category] = harmonics
             messages.append(f"The point {point} is valid.")
         else:
             messages.append(f"The point {point} is not valid.")
-    
+
+    # Debugging print statements
+    print("Color Mapping:", color_mapping)
+    print("Category Harmonics:", category_harmonics)
+
     return valid_points, color_mapping, category_harmonics, messages