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Changes dianas plot function

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Diana 2024-10-24 15:45:41 +02:00
parent edc8d832e1
commit a9378771ac
1 changed files with 14 additions and 25 deletions
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39
code/plot_functions.py
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@ -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()