plot_bw_fft.py

import numpy as np
import matplotlib.pyplot as plt
import glob

Fs = 32000000 / 16  # sampling rate
Ts = 1.0/Fs # sampling interval

def load(filename):
    y = []
    x = []
    count = 0
    with open(filename) as fh:
        for val in fh.readlines():
            count += 1
            x.append(len(x))
            y.append(int(val))
#            if count == 1000:
#                break

    return x, y

def plot():
    fig = plt.figure()

    # freq plot
    ax = fig.add_subplot(1,1,1)
    ax.grid(True)
    ax.set_xlabel('Freq (Hz)')
    ax.set_ylabel('|Y(freq)|')

    for filename in glob.glob("data-10k*/*csv"):
        print(filename)
        x, y = load(filename)
        ref = 1000                                        # arbitrary ref
        N = len(y)
        win = np.hamming(N)                                                       
        window = y[0:N] * win                             # Take a slice and multiply by a window
        sp = np.fft.rfft(window)                          # Calculate real FFT
        s_mag = np.abs(sp) * 2 / np.sum(win)              # Scale the magnitude of FFT by window and factor of 2,
        freq = np.arange((N / 2) + 1) / (float(N) / Fs)   # Frequency axis
        ax.plot(freq, s_mag)

    plt.show()

if __name__ == '__main__':
    plot()