Find peaks/valleys of a noisy signal

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.signal import find_peaks, savgol_filter

# Load your data
data = pd.read_csv('path_to_your_data.csv', header=None)
x = data[0]
y = data[1]

# Smooth the data using Savitzky-Golay filter
window_size = 51  # Choose an appropriate window size
poly_order = 3  # Polynomial order
y_smooth = savgol_filter(y, window_size, poly_order)

# Find peaks
peaks, _ = find_peaks(y_smooth, distance=50)  # Adjust 'distance' as needed

# Find valleys (by finding peaks in the inverted signal)
valleys, _ = find_peaks(-y_smooth, distance=50)  # Adjust 'distance' as needed

# Plot the results
plt.figure(figsize=(10, 6))
plt.plot(x, y, label='Original Signal')
plt.plot(x, y_smooth, label='Smoothed Signal')
plt.plot(x[peaks], y_smooth[peaks], 'ro', label='Peaks')
plt.plot(x[valleys], y_smooth[valleys], 'go', label='Valleys')
plt.legend()
plt.xlabel('Time')
plt.ylabel('Signal')
plt.title('Peak and Valley Detection')
plt.show()