Real-time Plot

import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from matplotlib.widgets import Slider
import numpy as np
import sounddevice as sd
import sys, queue

# Parameters for the audio signal stream
SAMPLERATE = 44100
WINDOW = 200

# Audio buffer setup
mapping = [0]
q = queue.Queue()
length = int(WINDOW * SAMPLERATE/1000)
ydata_time = np.zeros((length, 1))

# This is called (from a separate thread) for each audio block
def audio_callback(indata, frames, time, status):
    if status:
        print(status, file=sys.stderr)
    q.put(indata[::1, mapping])

# This is called by matplotlib for each plot update
def update_plot(frame):
    global ydata_time
    # Update y data with new audio chunk
    while True:
        try:
            data = q.get_nowait()
        except queue.Empty:
            break
        shift = len(data)
        ydata_time = np.roll(ydata_time, -shift, axis=0)
        ydata_time[-shift:, :] = data
    
    # Update time-domain plot
    for column, line in enumerate(lines_time):
        line.set_ydata(ydata_time[:, column])
    
    # Compute FFT for the last chunk of data
    fft_data = np.fft.fft(ydata_time[:, 0])
    fft_data = np.abs(fft_data[:len(fft_data)//2])
    ydata_freq = np.fft.fftfreq(len(ydata_time), 1/SAMPLERATE)[:len(fft_data)]
    
    # Update the frequency-domain plot
    lines_freq.set_data(ydata_freq, fft_data)
    ax2.set_ylim(0, np.max(fft_data) * 1.1)
    
    return lines_time + [lines_freq]

# Slider callback
def update_xlim(val):
    ax2.set_xlim(0, slider.val)
    plt.draw()

# Create a figure and axis for the plot
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 6))

# Time-domain plot
ax1.set_title('Time-domain Signal')
ax1.set_xlabel('Time (s)')
time_axis = np.linspace(0, length/SAMPLERATE, length) 
lines_time = ax1.plot(time_axis, ydata_time)
# ax1.set_yticks([0])
ax1.axis((0, time_axis[-1], -1, 1))
ax1.grid(color='gray', linestyle='--', linewidth=0.5)

# Frequency-domain plot (FFT)
ax2.set_title('FFT of the Signal')
ax2.set_xlabel('Frequency (Hz)')
lines_freq, = ax2.plot([], [], 'r')
ax2.set_xlim(0, SAMPLERATE//2)
ax2.grid(color='gray', linestyle='--', linewidth=0.5)

# Layout adjustment
fig.tight_layout()
fig.subplots_adjust(bottom=0.15)

# Add a slider for controlling the xlimit of the frequency-domain plot
slider_ax = plt.axes([0.2, 0.02, 0.65, 0.03])
slider = Slider(slider_ax, 'Frequency Limit', valmin=1000, valmax=SAMPLERATE//2, valinit=SAMPLERATE//2, valstep=100)
slider.on_changed(update_xlim)


# Audio Stream and Plot Animation - device = None: Default
stream = sd.InputStream(device=None, channels=1, samplerate=SAMPLERATE, callback=audio_callback)
ani = FuncAnimation(fig, update_plot, interval=30, blit=True)

with stream:
    plt.show()