How to convert x-axis from samples into time (s) and frequency (Hz) with python?
Question:
here I have plotted an ecg signal in time-domain and frequency-domain with fft():
time-domain
but as you can see, the x-axis of both images are still in samples.
I have searched some references how to convert samples into time (s) and frequency (Hz), but it fails, not only the x-axis changes but also the plot shape.
Can you help me to solve this problem? Thank you.
Answers:
The Code can look like this:
signal, sample_rate = librosa.load(blues_1)
max_time = signal.size/sample_rate
time_steps = np.linspace(0, max_time, signal.size)
plt.figure()
plt.plot(time_steps, signal)
plt.xlabel("Time [s]")
plt.ylabel("Amplitude")
f = np.abs(np.fft.fft(signal))
freq_steps = np.fft.fftfreq(signal.size, d=1/sample_rate)
plt.figure()
plt.plot(freq_steps, f)
plt.xlabel("Frequency [Hz]")
plt.ylabel("Amplitude")
Understandably you can also plot only half of the values in frequency domain.
A variation with Scipy
sample_rate, signal = scipy.io.wavfile.read( pathname1+file)
max_time = signal.size/sample_rate
time_steps = np.linspace(0, max_time, signal.size)
plt.plot(time_steps,signal)
here I have plotted an ecg signal in time-domain and frequency-domain with fft():
time-domain
but as you can see, the x-axis of both images are still in samples.
I have searched some references how to convert samples into time (s) and frequency (Hz), but it fails, not only the x-axis changes but also the plot shape.
Can you help me to solve this problem? Thank you.
The Code can look like this:
signal, sample_rate = librosa.load(blues_1)
max_time = signal.size/sample_rate
time_steps = np.linspace(0, max_time, signal.size)
plt.figure()
plt.plot(time_steps, signal)
plt.xlabel("Time [s]")
plt.ylabel("Amplitude")
f = np.abs(np.fft.fft(signal))
freq_steps = np.fft.fftfreq(signal.size, d=1/sample_rate)
plt.figure()
plt.plot(freq_steps, f)
plt.xlabel("Frequency [Hz]")
plt.ylabel("Amplitude")
Understandably you can also plot only half of the values in frequency domain.
A variation with Scipy
sample_rate, signal = scipy.io.wavfile.read( pathname1+file)
max_time = signal.size/sample_rate
time_steps = np.linspace(0, max_time, signal.size)
plt.plot(time_steps,signal)