From af4e888db03969918405621bd6c0f75a67d04647 Mon Sep 17 00:00:00 2001
From: mbergmann <maximilian.bergmann@student.uni-tuebingen.de>
Date: Tue, 22 Oct 2024 15:44:54 +0200
Subject: [PATCH] [Animation_ChatGPT.py added

---
 code/Animation_ChatGPT.py | 63 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 63 insertions(+)
 create mode 100644 code/Animation_ChatGPT.py

diff --git a/code/Animation_ChatGPT.py b/code/Animation_ChatGPT.py
new file mode 100644
index 0000000..1b84107
--- /dev/null
+++ b/code/Animation_ChatGPT.py
@@ -0,0 +1,63 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Oct 15 16:46:07 2024
+
+@author: ernesto311
+"""
+
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.signal import welch
+from matplotlib.animation import FuncAnimation, PillowWriter
+
+# Generate distances and corresponding frequencies
+distances = np.arange(-400, 451, 1)
+f1 = 800
+f2 = f1 + distances
+
+# Time parameters
+dt = 0.00001
+t = np.arange(0, 2, dt)
+
+# Set up the figure and axis for the animation
+fig, axs = plt.subplots(1, 2, layout='constrained')
+axs[0].set_xlabel('Time [s]')
+axs[0].set_ylabel('Amplitude')
+axs[1].set_xlabel('Frequency [Hz]')
+axs[1].set_ylabel('Power [1/Hz]')
+axs[1].set_xlim(0, 1500)
+
+# Function to compute and plot the power spectrum
+def plot_powerspectrum(i):
+    # Clear the previous plots
+    axs[0].cla()
+    axs[1].cla()
+    
+    # Generate the signal
+    x = np.sin(2*np.pi*f1*t) + 0.2 * np.sin(2*np.pi*f2[i]*t)
+    x[x < 0] = 0  # Apply half-wave rectification
+
+    # Plot the signal (first 20 ms for clarity)
+    axs[0].plot(t[t < 0.02], x[t < 0.02])
+    axs[0].set_title(f"Signal (f2={f2[i]} Hz)")
+    axs[0].set_xlabel('Time [s]')
+    axs[0].set_ylabel('Amplitude')
+    axs[0].set_ylim(0, 1.2)
+
+    # Compute power spectrum
+    freq, power = welch(x, fs=1/dt, nperseg=2**16)
+
+    # Plot the power spectrum
+    axs[1].plot(freq, power)
+    axs[1].set_xlim(0, 1500)
+    axs[1].set_ylim(0, 0.05)
+    axs[1].set_title(f'Power Spectrum (f2={f2[i]} Hz)')
+    axs[1].set_xlabel('Frequency [Hz]')
+    axs[1].set_ylabel('Power [1/Hz]')
+
+# Create the animation
+ani = FuncAnimation(fig, plot_powerspectrum, frames=len(distances), interval=500)
+
+# Display the animation
+ani.save("signal_animation.gif", writer=PillowWriter(fps=30))
+plt.show()