falscher name

Power spectrum animations for contrast 10% and 20%

code/plot_functions.py

@@ -73,12 +73,12 @@ sys.path.append(functions_path)
 import useful_functions as u
 import matplotlib.ticker as ticker
 import matplotlib.patches as mpatches
+import matplotlib.cm as cm
 
 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, nyquist, true_eodf, color_mapping, points_categories, delta=2.5):
     """
     Highlights integrals on the existing axes of the power spectrum for a given dataset.
@@ -104,9 +104,16 @@ def plot_highlighted_integrals(ax, frequency, power, points, nyquist, true_eodf,
     -------
     None
     """
-    # Plot the power spectrum on the provided axes
-    ax.plot(frequency, power, color="k")
+    # Define color mappings for specific categories
+    category_colors = {
+        "AM": "#ff7f0e",
+        "Nyquist": "#2ca02c",
+        "EODf": "#d62728",
+        "Stimulus": "#9467bd",
+        "EODf (awake fish)": "#8c564b"
+    }
 
+    # Plot the power spectrum on the provided axes
     for point in points:
         # Identify the category for the current point
         point_category = next((cat for cat, pts in points_categories.items() if point in pts), "Unknown")
@@ -120,20 +127,24 @@ def plot_highlighted_integrals(ax, frequency, power, points, nyquist, true_eodf,
         
         if valid:
             # Highlight valid points with a shaded region
-            ax.axvspan(point - delta, point + delta, color=color, alpha=0.2, label=f'{point_category}')
+            ax.axvspan(point - delta, point + delta, color=color, alpha=0.35, label=f'{point_category}')
+    
+    ax.plot(frequency, power, color="#1f77b4", linewidth=1.5)
+    # Use the category colors for 'Nyquist' and 'EODf' lines
+    ax.axvline(nyquist, color=category_colors.get("Nyquist", "#2ca02c"), linestyle="--")
+    ax.axvline(true_eodf, color=category_colors.get("EODf (awake fish)", "#8c564b"), linestyle="--")
 
     # Set plot limits and labels
     ax.set_xlim([0, 1200])
     ax.set_ylim([0, 6e-5])
-    ax.axvline(nyquist, color = "k", linestyle = "--")
-    ax.axvline(true_eodf, color = "k", linestyle = "--")
-    ax.set_xlabel('Frequency (Hz)')
-    ax.set_ylabel('Power')
-    ax.set_title('Power Spectrum with Highlighted Integrals')
+    ax.set_xlabel('Frequency (Hz)', fontsize=12)
+    ax.set_ylabel(r'Power [$\frac{\mathrm{Hz^2}}{\mathrm{Hz}}$]', fontsize=12)
+    #ax.set_title('Power Spectrum with highlighted Integrals', fontsize=14)
 
     # Apply float formatting to the y-axis
     ax.yaxis.set_major_formatter(ticker.FuncFormatter(float_formatter))
-    #ax.legend(loc="upper right")
+
+