def plot_spectrum(ax1, ax2):
spectrum, spec_extent = spectrum_data.get(), spectrum_data.get_extent()
z = 10. * np.log10(spectrum)
z = np.flipud(z)
ax1.imshow(z, plt.magma(), extent=spec_extent, aspect='auto')
ax1.figure.canvas.draw()
ax2.imshow(z, plt.magma(), extent=spec_extent, aspect='auto')
ax2.plot(time, result, color='g')
ax2.set_ylim(bottom=0, top=512)
ax2.figure.canvas.draw()
def plot_spectrum(spectrum, extent, filename):
z = 10. * np.log10(spectrum)
z = np.flipud(z)
plt.imshow(z, plt.magma(), extent=extent, aspect='auto')
plt.gcf().set_size_inches(15, 5)
plt.savefig(filename, dpi=100)
plt.close()
def ploter(columned_file):
'''
this function will plot 4D dots
'''
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = columned_file[0]
y = columned_file[1]
z = columned_file[2]
c = columned_file[3]
img = ax.scatter(x, y, z, c=c, cmap=plt.magma())
fig.colorbar(img)
plt.show()
#import the plt and wavfile modules
import matplotlib.pyplot as plt
from scipy.io import wavfile
import os
import argparse
# argparser
parser = argparse.ArgumentParser(
description="Plot audio spectrogram for .wav file")
parser.add_argument("audio_file", type=str, help=".wav file path")
args = parser.parse_args()
file_path, file_name = os.path.split(args.audio_file)
file_path = os.path.join(file_path, file_name)
# Read the wav file (mono)
samplingFrequency, signalData = wavfile.read(file_path)
# Plot the signal read from wav file
plt.title(f'Spectrogram of {file_name}')
plt.subplot(111)
plt.specgram(signalData, Fs=samplingFrequency)
plt.magma()
plt.xlabel('Time')
plt.ylabel('Frequency')
plt.show()
