CODEWITHSUNDEEP
filteringfft
user2288393
user2288393

Reputation: 13

How to filter the fft output to remove 0 Hz components

I tried to calculate the fourier transform of the set of experimental data. I ended up looking at data where 0 Hz component is higher. Any idea on how to remove this? What does the 0 Hz component actually represent?

#Program for Fourier Transformation
# last update 131003, aj
import numpy as np
import numpy.fft as fft
import matplotlib.pyplot as plt

def readdat( filename ):
    """
        Reads experimental data from the file
    """

    # read all lines of input files
    fp = open( filename, 'r')
    lines = fp.readlines() # to read the tabulated data
    fp.close()

    # Processing the file data
    time = []
    ampl = []
    for line in lines:
        if line[0:1] == '#':
            continue # ignore comments in the file
        try:
            time.append(float(line.split()[0]))
            #first column is time
            ampl.append(float(line.split()[1]))
            # second column is corresponding amplitude
        except:
            # if the data interpretation fails..
            continue
    return np.asarray(time), np.asarray(ampl)

if __name__ == '__main__':

    time, ampl = readdat( 'VM.dat')
    print time
    print ampl

    spectrum = fft.fft(ampl)
    # assume samples at regular intervals
    timestep = time[1]-time[0] 
    freq = fft.fftfreq(len(spectrum),d=timestep)
    freq=fft.fftshift(freq)
    spectrum = fft.fftshift(spectrum)
    plt.figure(figsize=(5.0*1.21,5.0))
    plt.plot(freq,spectrum.real)
    plt.title("Measured Voltage")
    plt.xlabel("frequency(rad/s)")
    plt.ylabel("Spectrum")
    plt.xlim(0.,5.)
    plt.ylim(ymin=0.)
    plt.grid()
    plt.savefig("VM_figure.png")

Upvotes: 1

Views: 7018

Answers (2)

chip_wrangler
chip_wrangler

Reputation: 145

If the average of the data set before processing is made to be zero then the 0Hz component should be negligible. This would be equivalent to detrending {scipy detrend} the data with option 'constant'.

This is sometimes used as a preconditioning step in low precision systems as finite precision numerical processing of data with large DC offsets will generate related numerical errors.

Upvotes: 1

pcarranzav
pcarranzav

Reputation: 215

The 0 Hz component represents the DC offset of your signal.

You can remove it with any high-pass filter, just put the cutoff frequency as low as possible (the filter could be digital or analogue, I don't know what your experimental setup is).

A simple possibility is just to force that value to 0 (modifying the FFT in this way is equivalent to applying a high pass FIR filter).

Upvotes: 0

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