The_Colors_of_Noise.svg
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Summary
| Description |
English:
The colors noise as generated by the colorednoise Python package. The figure shows the color coded relative power spectral density (PSD) for Brown, pink, white, blue, and violet noise normalized at 1kHz. Note the slopes of the PSD are -20, -10, 0, 10, 20 (dB/dec) for each noise spectum respectively.
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| Date | |
| Source | Own work |
| Author | AkanoToE |
| Other versions |
Own work based on: The Colors of Noise.png |
Source Code
import colorednoise as cn
import matplotlib.pyplot as plt
from matplotlib import mlab
betas = [-2, -1, 0, 1, 2]
colors = ['violet', 'blue', 'gray', 'pink', 'darkred']
samples = 100*44100
plt.style.use('default')
plt.rc('font', family='serif', size=14)
plt.rc('text', usetex=True)
fig = plt.figure(dpi=300)
plt.annotate(r'\textit{The Colors of Noise}', (1300, 42), fontsize=16)
nfft=2**21
for beta, color in zip(betas, colors):
y = cn.powerlaw_psd_gaussian(beta, samples)
s, f = mlab.psd(y, NFFT=nfft)
plt.semilogx(2e5*f, 4 + 10*np.log10(s/s[4100:4200].mean())
, color=color, lw=0.5)
plt.xlabel('Frequency (Hz)')
plt.ylabel('Power Spectral Density (dB)')
plt.xlim([1e3, 2e5])
plt.ylim([-70, 56])
plt.tight_layout()
if fig.dpi >= 300:
plt.savefig('../fig/The_Colors_of_Noise.svg')
Licensing
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