From 2515472d32ec51b9d25fa49f25514afc1ffe4003 Mon Sep 17 00:00:00 2001
From: mbergmann <maximilian.bergmann@student.uni-tuebingen.de>
Date: Mon, 28 Oct 2024 15:11:01 +0100
Subject: [PATCH 1/2] [Animation_ChatGPT] updated
---
code/Animation_ChatGPT.py | 57 ++++++++++++++++++++++++++++++++++-----
1 file changed, 50 insertions(+), 7 deletions(-)
diff --git a/code/Animation_ChatGPT.py b/code/Animation_ChatGPT.py
index 1b84107..abc7604 100644
--- a/code/Animation_ChatGPT.py
+++ b/code/Animation_ChatGPT.py
@@ -9,12 +9,14 @@ import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import welch
from matplotlib.animation import FuncAnimation, PillowWriter
+import useful_functions as f
# Generate distances and corresponding frequencies
-distances = np.arange(-400, 451, 1)
+distances = np.arange(-400, 2000, 1)
f1 = 800
f2 = f1 + distances
+
# Time parameters
dt = 0.00001
t = np.arange(0, 2, dt)
@@ -34,7 +36,7 @@ def plot_powerspectrum(i):
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 = np.sin(2*np.pi*f1*t) + np.sin(2*np.pi*f2[i]*t)
x[x < 0] = 0 # Apply half-wave rectification
# Plot the signal (first 20 ms for clarity)
@@ -42,7 +44,7 @@ def plot_powerspectrum(i):
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)
+ axs[0].set_ylim(-2, 2)
# Compute power spectrum
freq, power = welch(x, fs=1/dt, nperseg=2**16)
@@ -55,9 +57,50 @@ def plot_powerspectrum(i):
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()
+
+ # Generate the signal as a sum of two sine waves
+def plot_powerspectrum_2(i):
+ # Clear the previous plots
+ axs[0].cla()
+ axs[1].cla()
+
+ # Generate the signal as a sum of two sine waves
+ x = np.sin(2 * np.pi * f1 * t) + 0.8 * np.sin(2 * np.pi * f2[i] * t) # Second wave is 20% as strong
+
+
+ # 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(-2, 2)
+
+ x[x < 0] = 0 # Apply half-wave rectification (optional)
+ # Compute power spectrum
+ freq, power = welch(x, fs=1/dt, nperseg=2**16)
+ pref = np.max(power)
+ decibel_power = 10 * np.log10(power/pref)
+ AM = f.find_AM(f1, 0.5 * f1, f2[i])
+ # Plot the power spectrum
+ axs[1].plot(freq, power)
+ axs[1].set_xlim(0, 3000)
+ axs[1].set_title(f'Power Spectrum (f2={f2[i]} Hz)')
+ axs[1].set_xlabel('Frequency [Hz]')
+ axs[1].set_ylabel('Power [1/Hz]')
+ axs[1].set_ylim(0, 0.00007)
+ axs[1].plot(f1, power[np.argmin(np.abs(freq-f1))], 'o')
+ axs[1].plot(f2[i], power[np.argmin(np.abs(freq-f2[i]))], 'd')
+ axs[1].plot(AM, power[np.argmin(np.abs(freq-AM))], '*')
+ axs[1].axvline(AM, alpha = 0.5, color = 'r')
+
# Create the animation
-ani = FuncAnimation(fig, plot_powerspectrum, frames=len(distances), interval=500)
+ani = FuncAnimation(fig, plot_powerspectrum_2, frames=len(distances), interval=500)
-# Display the animation
-ani.save("signal_animation.gif", writer=PillowWriter(fps=30))
-plt.show()
+# Save the animation as a GIF file (optional)
+ani.save("sum_of_sinewaves.gif", writer=PillowWriter(fps=30))
From d2444240f29e790a462cb1f4a9aa6eacceba92bf Mon Sep 17 00:00:00 2001
From: mbergmann <maximilian.bergmann@student.uni-tuebingen.de>
Date: Mon, 28 Oct 2024 15:11:32 +0100
Subject: [PATCH 2/2] [Animation_ChatGPT] updated
---
code/Animation_ChatGPT.py | 35 +----------------------------------
1 file changed, 1 insertion(+), 34 deletions(-)
diff --git a/code/Animation_ChatGPT.py b/code/Animation_ChatGPT.py
index abc7604..7b1017c 100644
--- a/code/Animation_ChatGPT.py
+++ b/code/Animation_ChatGPT.py
@@ -29,40 +29,7 @@ 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) + 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(-2, 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()
# Generate the signal as a sum of two sine waves
def plot_powerspectrum_2(i):
@@ -93,7 +60,7 @@ def plot_powerspectrum_2(i):
axs[1].set_title(f'Power Spectrum (f2={f2[i]} Hz)')
axs[1].set_xlabel('Frequency [Hz]')
axs[1].set_ylabel('Power [1/Hz]')
- axs[1].set_ylim(0, 0.00007)
+ #axs[1].set_ylim(0, 0.00007)
axs[1].plot(f1, power[np.argmin(np.abs(freq-f1))], 'o')
axs[1].plot(f2[i], power[np.argmin(np.abs(freq-f2[i]))], 'd')
axs[1].plot(AM, power[np.argmin(np.abs(freq-AM))], '*')