I have two lists of float values, one for time and other for voltage values taken from an oscilloscope (I assume). I have to draw an amplitude spectrum plot, but i'm not exactly sure what function I need to use and what parameters I need to give it, I tried fft(u), but it didn't work.
Any help is appreciated, let me know if you need more info.
Use numpy.
As an example, let me show how I analysed the frequencies in a stereo WAV file;
First I read the data and separated it in the left and right channels;
import wave
import numpy as np
wr = wave.open('input.wav', 'r')
sz = 44100 # Read and process 1 second at a time.
da = np.fromstring(wr.readframes(sz), dtype=np.int16)
left, right = da[0::2], da[1::2]
Next I run a discrete fourier transform on it;
lf, rf = abs(np.fft.rfft(left)), abs(np.fft.rfft(right))
And we plot the left channel with mathplotlib;
import matplotlib.pyplot as plt
plt.figure(1)
a = plt.subplot(211)
r = 2**16/2
a.set_ylim([-r, r])
a.set_xlabel('time [s]')
a.set_ylabel('sample value [-]')
x = np.arange(44100)/44100
plt.plot(x, left)
b = plt.subplot(212)
b.set_xscale('log')
b.set_xlabel('frequency [Hz]')
b.set_ylabel('|amplitude|')
plt.plot(lf)
plt.savefig('sample-graph.png')
The graph looks something like this;
Here is the Frequency-Time spectrum of the signal, stored in the wave file
import wave
import numpy as np
from scipy import signal
import matplotlib.pyplot as plt
signal_wave = wave.open('voice.wav', 'r')
sample_frequency = 16000
data = np.fromstring(signal_wave.readframes(sample_frequency), dtype=np.int16)
sig = signal_wave.readframes(-1)
sig = np.fromstring(sig, 'Int16')
For the wave file
sig = sig[:]
For some segment of the wave file
sig = sig[25000:32000]
To plot spectrum of the signal wave file
plt.figure(1)
c = plt.subplot(211)
Pxx, freqs, bins, im = c.specgram(sig, NFFT=1024, Fs=16000, noverlap=900)
c.set_xlabel('Time')
c.set_ylabel('Frequency')
plt.show()
Related
I've been trying to get the fourier transform of the data in file S1L1E here https://github.com/gergobes/data-for-fft/blob/c0b664379c0eeab04abdc541e34d6e636e841eb0/S1L1E. First column is time, 2nd column is amplitude of first wave and 3rd column is the amplitude of another wave. The code I tried is;
import matplotlib.pyplot as plt
import numpy as np
from scipy.fft import fft, fftfreq
data = np.loadtxt("S1L1E")
time = data[:,0]
amp_left = data[:,1]
amp_right = data[:,2]
plt.plot(time, amp_left)
plt.plot(time, amp_right)
plt.show()
# fft attempt
samplerate = 5000
duration = time[-1]
N = int(samplerate * duration)
x = time
y = amp_left
yf = fft(y)
xf = fftfreq(len(y))
plt.plot(xf, abs(yf))
plt.show()
I tried for the first wave but got only a spike at 0. What am I doing wrong? It's my first time trying a fft so I'm kinda lost here. I would appreciate any help.
I want to plot a power spectrum from my data set (array of about 2000 values, the data is recorded every minute).
I've gotten so far as:
y= np.fft.fft(data)
abs = np.abs(y) #absolute value
p = np.square(abs) #power
but am confused about setting the frequency.
I've tried using freqs = np.fft.fftfreq(len(y)), but when I plot the result it looks like, which can't be right.
What am I doing wrong?
Here is an example to plot the power spectrum:
import matplotlib.pyplot as plt
import numpy as np
t = np.linspace(0,2000,200)
data = 2 * np.sin(2*np.pi *60*t) + 2 * np.sin(2*np.pi *42*t)
spectrum = np.fft.fft(data)
power_spectrum = np.square(np.abs(spectrum))
fig, ax = plt.subplots()
ax.plot(np.arange(len(power_spectrum)), power_spectrum)
plt.show()
I'm creating a sine wave of 100Hz and trying to plot it's stft :
import scipy.io
import numpy as np
import librosa
import librosa.display
#%matplotlib notebook
import matplotlib.pyplot as plt
A = 1 # Amplitude
f0 = 100 # frequency
Fs = f0 * 800 # Sampling frequency
t = np.arange(Fs) / float(Fs)
X = np.sin(2*np.pi*t*f0)
plt.plot(t, X)
plt.xlabel("Time")
plt.ylabel("Amplitude")
plt.show()
D = np.abs(librosa.stft(X))
librosa.display.specshow(librosa.amplitude_to_db(D,ref=np.max),y_axis='log', x_axis='time')
I was expecting a single line at 100Hz instead.
Also, how can I plot Frequency(X-axis) vs Amplitude(Y-axis) graph to see a peak at 100Hz?
You need to pass the sample rate to specshow, using the sr keyword argument. Otherwise it will default to 22kHz, which will give wrong results.
D = np.abs(librosa.stft(X))
db = librosa.amplitude_to_db(D,ref=np.max)
librosa.display.specshow(db, sr=Fs, y_axis='log', x_axis='time')
I am trying to do an FFT on a .wav file that contains only a 1 kHz sin wave. When I plot the result, I expect the peak to be at the fundamental (1 kHz) but instead, I see the peak at what seems to be the 3rd harmonic (3 kHz). I have tried 2 other .wav files at 440 Hz and 2 kHz with the same result. I used a frequency counter to verify the .wav files contain the frequencies I expect.
For comparison, I use the commented code below to generate and plot a sin function which displays correctly.
import matplotlib.pyplot as plt
import numpy as np
import wave, struct
sound_file = wave.open('c:\downloads\SineWave_1000Hz.wav', 'r')
file_length = sound_file.getnframes()
data = sound_file.readframes(file_length)
data = struct.unpack('{n}h'.format(n=file_length), data)
data = np.array(data)
sound_file.close()
#x = np.linspace(0.0, 1, 600)
#y = np.sin(50.0 * 2.0*np.pi*x)
#yf = fft(y)
yf = fft(data)
plt.xlim(0, 4000)
plt.plot( np.abs(yf))
plt.grid()
plt.show()
I wrote this code where I read a wav file and then It identifies where is the larger sample, but this only give me the possition of the max sample, but not the value of it, so what can I do to know which is its value? And when I plot it, why it doesn't fit on thw y-scale. For example, it says that the value is 6920, but when I plot, it only reaches 5535.
Thank you!
import matplotlib.pyplot as plt
import numpy as np
import wave
import sys
spf1 = wave.open('C:/Users/Martinez/Documents/Diego/Facultad/Proyecto Final/Mediciones Cubo/5 sentado/Lado 1_5 sentado.wav','r')
#Extract Raw Audio from Wav File
signal1 = spf1.readframes(-1)
signal1 = np.fromstring(signal1, 'Int16')
fs1 = spf1.getframerate()
#If Stereo
if spf1.getnchannels() == 2:
print 'Just mono files'
sys.exit(0)
print np.arange(signal1)
m = abs(signal1).max()
print m
Time=np.linspace(0, len(signal1)/float(fs), num=len(signal1))
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.vlines(Time[m:], [0], abs(signal1)[m:] )
ax1.grid(True)
ax1.axhline(color='black', lw=2)
plt.show()
won't abs(signal1).max() do the trick?