scientimate.periodogrampsd#

f, Sxx = scientimate.periodogrampsd(x, fs=2, WindowName='none', OutputSmoothSize=0, dispout='no')

Description#

Calculate power spectral density using periodogram method

Inputs#

x

Input data

fs=2

Sampling frequency that data collected at in (Hz)

WindowName=’none’
Window name, define if multiplying input data by window function or not (‘none’: not multiplying)
‘none’,’rectangular’,’triangular’,’welch’,’hanning’,’hamming’,’gaussian’,’blackman’,’nuttall’,’blackmanharris’
OutputSmoothSize=0
Window size for smoothing calculated spectrum (0, 1 or 2: not smoothing, reports original periodogram)
if WindowName=’none’ and OutputSmoothSize>2, then WindowName=’hamming’
dispout=’no’

Define to display outputs or not (‘yes’: display, ‘no’: not display)

Outputs#

f

Frequency in (Hz)

Sxx

Power spectral density using periodogram method (m^2/Hz)

Examples#

import scientimate as sm
import numpy as np
import scipy as sp
from scipy import signal

x=sp.signal.detrend(0.5*np.cos(2*np.pi*0.2*np.arange(0,1024,1/2))+(-0.1+(0.1-(-0.1)))*np.random.rand(1024*2))
f,Sxx=sm.periodogrampsd(x,2,'none',0,'yes')

References#