Source code for draugr.drawers.mpl_drawers.spectral.fast_fourier_transform
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "Christian Heider Nielsen"
__doc__ = """
Created on 27/04/2019
@author: cnheider
"""
__all__ = ["FastFourierTransformPlot"]
import math
import numpy
from matplotlib import pyplot
from matplotlib.gridspec import GridSpec
from draugr.drawers.mpl_drawers.mpldrawer import MplDrawer
from draugr.tqdm_utilities import progress_bar
FLOAT_EPS = numpy.finfo(float).eps
[docs]class FastFourierTransformPlot(MplDrawer):
"""
Plots last computed fft of data"""
[docs] def __init__(
self,
n_fft: int = 64,
sampling_rate=int(1.0 / 0.0005),
title: str = "",
figure_size=(9, 9),
render: bool = True,
**kwargs
):
"""
:param n_fft:
:type n_fft:
:param sampling_rate:
:type sampling_rate:
:param title:
:type title:
:param placement:
:type placement:
:param fig_size:
:type fig_size:
:param render:
:type render:"""
super().__init__(render=render, figure_size=figure_size, **kwargs)
if not render:
return
self.fig = pyplot.figure(figsize=figure_size)
self.n_fft = n_fft
self.abs_n_fft = (self.n_fft + 1) // 2
self.sampling_rate = sampling_rate
freq_bins = numpy.arange(self.n_fft)
raw_array = numpy.zeros(self.n_fft)
self.zeroes_padding = numpy.zeros((self.abs_n_fft, n_fft))
gs = GridSpec(3, 1)
(self.raw_ax, self.angle_ax, self.mag_ax) = [
pyplot.subplot(gs[i]) for i in range(3)
]
freqs = numpy.fft.fftfreq(self.n_fft, 1 / sampling_rate)
(self.dft_raw_img,) = self.raw_ax.plot(freq_bins, raw_array)
self.raw_ax.set_xlabel("Time (Sec)")
self.raw_ax.set_ylabel("Amplitude")
(self.dft_angle_img,) = self.angle_ax.plot(freq_bins, raw_array)
self.angle_ax.set_xlabel("Phase [Hz]")
self.angle_ax.set_ylabel("Angle (Radians)")
self.angle_ax.set_ylim([-math.pi, math.pi])
# self.angle_ax.set_xticks(freqs)
(self.dft_mag_img,) = self.mag_ax.plot(freq_bins, raw_array)
self.mag_ax.set_xlabel("Frequency [Hz]")
self.mag_ax.set_xlabel("Magnitude (dB)")
# self.mag_ax.set_xticks(freqs)
pyplot.title(title)
pyplot.tight_layout()
def _draw(self, signal_sample: float, delta: float = 1 / 120) -> None:
"""
:param signal_sample:
:param delta: 1 / 60 for 60fps
:return:"""
raw_array = self.dft_raw_img.get_ydata()
raw_array = numpy.hstack((signal_sample, raw_array[:-1]))
self.dft_raw_img.set_ydata(raw_array)
cur_lim = self.raw_ax.get_ylim()
self.raw_ax.set_ylim(
[min(cur_lim[0], signal_sample), max(cur_lim[1], signal_sample)]
)
f_coef = numpy.fft.fft(raw_array, n=self.n_fft)
self.dft_angle_img.set_ydata(numpy.angle(f_coef))
mag = 10 * numpy.log10((numpy.abs(f_coef) ** 2) + FLOAT_EPS)
self.dft_mag_img.set_ydata(mag)
self.mag_ax.set_ylim([min(mag), max(mag)])
if __name__ == "__main__":
def a() -> None:
"""
:rtype: None
"""
duration_sec = 4
mul = 1000
sampling_Hz = 44
sampling_rate = sampling_Hz * mul # Hz
delta = 1 / sampling_rate
n_fft = 64
s = FastFourierTransformPlot(n_fft=n_fft, sampling_rate=sampling_rate)
for t in progress_bar(numpy.arange(0, duration_sec, delta)):
ts = 2 * numpy.pi * t
s1 = numpy.sin(ts * 1 * sampling_Hz / 2**4 * mul)
s2 = numpy.sin(ts * 3 * sampling_Hz / 2**3 * mul + 0.33 * numpy.pi)
s3 = numpy.sin(ts * 5 * sampling_Hz / 2**2 * mul + 0.66 * numpy.pi)
signal = s1 + s2 + s3
signal /= 3
# signal += (numpy.random.random() - 0.5) * 2 * 1 / 2 # Noise
s.draw(signal, delta=delta)
a()