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‎Amplitude-Frequency-Visualizer.py

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import PySimpleGUI as sg
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import pyaudio
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import numpy as np
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import scipy.fft
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import matplotlib.pyplot as plt
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
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""" RealTime Audio Frequency plot """
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# VARS CONSTS:
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_VARS = {"window": False, "stream": False, "audioData": np.array([])}
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# pysimpleGUI INIT:
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AppFont = "Any 16"
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sg.theme("DarkBlue3")
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layout = [
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[
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sg.Graph(
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canvas_size=(500, 500),
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graph_bottom_left=(-2, -2),
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graph_top_right=(102, 102),
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background_color="#809AB6",
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key="graph",
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)
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],
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[sg.ProgressBar(4000, orientation="h", size=(20, 20), key="-PROG-")],
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[
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sg.Button("Listen", font=AppFont),
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sg.Button("Stop", font=AppFont, disabled=True),
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sg.Button("Exit", font=AppFont),
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],
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]
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_VARS["window"] = sg.Window("Mic to frequency plot + Max Level", layout, finalize=True)
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graph = _VARS["window"]["graph"]
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# INIT vars:
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CHUNK = 1024 # Samples: 1024, 512, 256, 128
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RATE = 44100 # Equivalent to Human Hearing at 40 kHz
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INTERVAL = 1 # Sampling Interval in Seconds -> Interval to listen
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TIMEOUT = 10 # In ms for the event loop
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pAud = pyaudio.PyAudio()
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# FUNCTIONS:
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# PySimpleGUI plots:
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def draw_figure(canvas, figure):
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figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
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figure_canvas_agg.draw()
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figure_canvas_agg.get_tk_widget().pack(side="top", fill="both", expand=1)
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return figure_canvas_agg
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# pyaudio stream:
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def stop():
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if _VARS["stream"]:
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_VARS["stream"].stop_stream()
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_VARS["stream"].close()
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_VARS["window"]["-PROG-"].update(0)
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_VARS["window"]["Stop"].Update(disabled=True)
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_VARS["window"]["Listen"].Update(disabled=False)
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# callback:
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def callback(in_data, frame_count, time_info, status):
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_VARS["audioData"] = np.frombuffer(in_data, dtype=np.int16)
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return (in_data, pyaudio.paContinue)
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def listen():
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_VARS["window"]["Stop"].Update(disabled=False)
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_VARS["window"]["Listen"].Update(disabled=True)
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_VARS["stream"] = pAud.open(
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format=pyaudio.paInt16,
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channels=1,
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rate=RATE,
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input=True,
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frames_per_buffer=CHUNK,
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stream_callback=callback,
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)
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_VARS["stream"].start_stream()
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# INIT:
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fig, ax = plt.subplots() # create a figure and an axis object
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fig_agg = draw_figure(graph.TKCanvas, fig) # draw the figure on the graph
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# MAIN LOOP
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while True:
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event, values = _VARS["window"].read(timeout=TIMEOUT)
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if event == sg.WIN_CLOSED or event == "Exit":
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stop()
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pAud.terminate()
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break
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if event == "Listen":
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listen()
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if event == "Stop":
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stop()
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# Along with the global audioData variable, this
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# bit updates the frequency plot
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elif _VARS["audioData"].size != 0:
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# Update volume meter
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_VARS["window"]["-PROG-"].update(np.amax(_VARS["audioData"]))
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# Compute frequency spectrum
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yf = scipy.fft.fft(_VARS["audioData"]) # compute the discrete Fourier transform
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xf = np.linspace(0.0, RATE / 2, CHUNK // 2) # create the frequency axis
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# Plot frequency spectrum
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ax.clear() # clear the previous plot
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ax.plot(
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xf, 2.0 / CHUNK * np.abs(yf[: CHUNK // 2])
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) # plot the frequency spectrum as a line graph
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ax.set_ylabel("Amplitude") # set the y-axis label
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ax.set_xlabel("Frequency [Hz]") # set the x-axis label
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fig_agg.draw() # redraw the figure

‎Spectogram.py

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import PySimpleGUI as sg
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import pyaudio
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import numpy as np
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import scipy.signal
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import matplotlib.pyplot as plt
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
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""" RealTime Audio Time-Frequency plot """
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# VARS CONSTS:
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_VARS = {"window": False, "stream": False, "audioData": np.array([])}
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# pysimpleGUI INIT:
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AppFont = "Any 16"
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sg.theme("DarkBlue3")
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layout = [
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[
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sg.Graph(
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canvas_size=(500, 500),
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graph_bottom_left=(-2, -2),
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graph_top_right=(102, 102),
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background_color="#809AB6",
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key="graph",
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)
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],
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[sg.ProgressBar(4000, orientation="h", size=(20, 20), key="-PROG-")],
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[
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sg.Button("Listen", font=AppFont),
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sg.Button("Stop", font=AppFont, disabled=True),
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sg.Button("Exit", font=AppFont),
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],
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]
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_VARS["window"] = sg.Window(
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"Mic to time-frequency plot + Max Level", layout, finalize=True
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)
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graph = _VARS["window"]["graph"]
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# INIT vars:
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CHUNK = 1024 # Samples: 1024, 512, 256, 128
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RATE = 44100 # Equivalent to Human Hearing at 40 kHz
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INTERVAL = 1 # Sampling Interval in Seconds -> Interval to listen
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TIMEOUT = 10 # In ms for the event loop
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pAud = pyaudio.PyAudio()
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# FUNCTIONS:
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# PySimpleGUI plots:
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def draw_figure(canvas, figure):
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figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
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figure_canvas_agg.draw()
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figure_canvas_agg.get_tk_widget().pack(side="top", fill="both", expand=1)
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return figure_canvas_agg
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# pyaudio stream:
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def stop():
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if _VARS["stream"]:
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_VARS["stream"].stop_stream()
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_VARS["stream"].close()
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_VARS["window"]["-PROG-"].update(0)
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_VARS["window"]["Stop"].Update(disabled=True)
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_VARS["window"]["Listen"].Update(disabled=False)
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# callback:
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def callback(in_data, frame_count, time_info, status):
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_VARS["audioData"] = np.frombuffer(in_data, dtype=np.int16)
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return (in_data, pyaudio.paContinue)
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def listen():
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_VARS["window"]["Stop"].Update(disabled=False)
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_VARS["window"]["Listen"].Update(disabled=True)
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_VARS["stream"] = pAud.open(
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format=pyaudio.paInt16,
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channels=1,
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rate=RATE,
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input=True,
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frames_per_buffer=CHUNK,
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stream_callback=callback,
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)
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_VARS["stream"].start_stream()
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# INIT:
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fig, ax = plt.subplots() # create a figure and an axis object
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fig_agg = draw_figure(graph.TKCanvas, fig) # draw the figure on the graph
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# MAIN LOOP
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while True:
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event, values = _VARS["window"].read(timeout=TIMEOUT)
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if event == sg.WIN_CLOSED or event == "Exit":
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stop()
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pAud.terminate()
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break
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if event == "Listen":
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listen()
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if event == "Stop":
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stop()
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# Along with the global audioData variable, this
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# bit updates the time-frequency plot
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elif _VARS["audioData"].size != 0:
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# Update volume meter
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_VARS["window"]["-PROG-"].update(np.amax(_VARS["audioData"]))
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# Compute time-frequency spectrum
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f, Pxx = scipy.signal.periodogram(
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_VARS["audioData"], fs=RATE
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) # compute the power spectral density
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t = np.arange(len(_VARS["audioData"])) / RATE # create the time axis
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# Plot time-frequency spectrum
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ax.clear() # clear the previous plot
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# Resize the frequency array to match the length of the time array
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f = np.resize(f, t.shape)
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# Plot the time-frequency spectrum as a line graph
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ax.plot(t, f)
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ax.set_ylabel("Frequency [Hz]") # set the y-axis label
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ax.set_xlabel("Time [sec]") # set the x-axis label
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fig_agg.draw() # redraw the figure

‎Waveform.py

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import PySimpleGUI as sg
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import pyaudio
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import numpy as np
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""" RealTime Audio Waveform plot """
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# VARS CONSTS:
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_VARS = {"window": False, "stream": False, "audioData": np.array([])}
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# pysimpleGUI INIT:
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AppFont = "Any 16"
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sg.theme("DarkBlue3")
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layout = [
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[
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sg.Graph(
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canvas_size=(500, 500),
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graph_bottom_left=(-2, -2),
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graph_top_right=(102, 102),
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background_color="#809AB6",
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key="graph",
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)
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],
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[sg.ProgressBar(4000, orientation="h", size=(20, 20), key="-PROG-")],
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[
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sg.Button("Listen", font=AppFont),
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sg.Button("Stop", font=AppFont, disabled=True),
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sg.Button("Exit", font=AppFont),
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],
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]
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_VARS["window"] = sg.Window("Mic to waveform plot + Max Level", layout, finalize=True)
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graph = _VARS["window"]["graph"]
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# INIT vars:
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CHUNK = 1024 # Samples: 1024, 512, 256, 128
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RATE = 44100 # Equivalent to Human Hearing at 40 kHz
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INTERVAL = 1 # Sampling Interval in Seconds -> Interval to listen
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TIMEOUT = 10 # In ms for the event loop
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pAud = pyaudio.PyAudio()
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# FUNCTIONS:
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# PySimpleGUI plots:
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def drawAxis(dataRangeMin=0, dataRangeMax=100):
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# Y Axis
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graph.DrawLine((0, 50), (100, 50))
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# X Axis
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graph.DrawLine((0, dataRangeMin), (0, dataRangeMax))
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# pyaudio stream:
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def stop():
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if _VARS["stream"]:
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_VARS["stream"].stop_stream()
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_VARS["stream"].close()
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_VARS["window"]["-PROG-"].update(0)
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_VARS["window"]["Stop"].Update(disabled=True)
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_VARS["window"]["Listen"].Update(disabled=False)
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# callback:
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def callback(in_data, frame_count, time_info, status):
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_VARS["audioData"] = np.frombuffer(in_data, dtype=np.int16)
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return (in_data, pyaudio.paContinue)
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def listen():
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_VARS["window"]["Stop"].Update(disabled=False)
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_VARS["window"]["Listen"].Update(disabled=True)
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_VARS["stream"] = pAud.open(
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format=pyaudio.paInt16,
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channels=1,
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rate=RATE,
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input=True,
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frames_per_buffer=CHUNK,
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stream_callback=callback,
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)
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_VARS["stream"].start_stream()
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# INIT:
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drawAxis()
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# MAIN LOOP
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while True:
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event, values = _VARS["window"].read(timeout=TIMEOUT)
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if event == sg.WIN_CLOSED or event == "Exit":
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stop()
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pAud.terminate()
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break
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if event == "Listen":
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listen()
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if event == "Stop":
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stop()
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# Along with the global audioData variable, this
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# bit updates the waveform plot
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elif _VARS["audioData"].size != 0:
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# Uodate volumne meter
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_VARS["window"]["-PROG-"].update(np.amax(_VARS["audioData"]))
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# Redraw plot
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graph.erase()
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drawAxis()
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# Here we go through the points in the audioData object and draw them
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# Note that we are rescaling ( dividing by 100 ) and centering (+50)
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# try different values to get a feel for what they do.
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for x in range(CHUNK):
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graph.DrawCircle(
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(x, (_VARS["audioData"][x] / 100) + 50),
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0.4,
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line_color="blue",
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fill_color="blue",
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)
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_VARS["window"].close()

‎requirements.txt

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cffi==1.16.0
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contourpy==1.1.1
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cycler==0.12.1
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fonttools==4.47.2
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importlib-resources==6.1.1
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kiwisolver==1.4.5
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matplotlib==3.7.4
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mkl-fft @ file:///C:/b/abs_19i1y8ykas/croot/mkl_fft_1695058226480/work
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mkl-random @ file:///C:/b/abs_edwkj1_o69/croot/mkl_random_1695059866750/work
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mkl-service==2.4.0
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numpy @ file:///C:/Users/dev-admin/mkl/numpy_and_numpy_base_1682982345978/work
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packaging==23.2
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pillow==10.2.0
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PyAudio==0.2.14
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pycparser==2.21
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pyparsing==3.1.1
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PySimpleGUI==4.60.5
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python-dateutil==2.8.2
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scipy==1.10.1
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six==1.16.0
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sounddevice==0.4.6
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zipp==3.17.0

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