scientimate.replacespikeenvelope#
xDespiked, Indx = scientimate.replacespikeenvelope(x, lowbound, upbound, nrpeat=1, interpMethod='linear', dispout='no')
Description#
Remove spikes in the time series that are outside a defined envelope
Inputs#
- x
Input data
- lowbound
Lower boundary of the data, all data points should be larger than that
- upbound
Upper boundary of the data, all data points should be smaller than that
- nrpeat=1
Number of time despiking procedure is repeating
- interpMethod=’linear’
- Interpolation method for replacing spike points:Matlab/Octave: ‘linear’, ‘nearest’, ‘next’, ‘previous’, ‘pchip’, ‘cubic’, ‘spline’Python/Scipy : ‘linear’, ‘nearest’, ‘zero’, ‘slinear’, ‘quadratic’, ‘cubic’
- dispout=’no’
Define to display outputs or not (‘yes’: display, ‘no’: not display)
Outputs#
- xDespiked
Dispiked data
- Indx
Index of despiked points
Examples#
import scientimate as sm
import numpy as np
import scipy as sp
from scipy import signal
fs=128
t=np.linspace(0,9.5,10*fs)
x=np.sin(2*np.pi*0.3*t)+0.1*np.sin(2*np.pi*4*t)
x[220:225]=1.5
x=x+5
xDespiked,Indx=sm.replacespikeenvelope(x,3.9,6.1,1,'linear','yes')
fs=2
t=np.linspace(0,1023.5,1024*fs)
x=sp.signal.detrend(0.5*np.cos(2*np.pi*0.2*t)+(-0.1+(0.1-(-0.1)))*np.random.rand(1024*fs))
spikeloc=np.arange(10,len(t),100)
x[np.int64(spikeloc+np.round(2*np.random.randn(len(spikeloc))))]=np.sign(np.random.randn(len(spikeloc)))
xDespiked,Indx=sm.replacespikeenvelope(x,-0.6,0.6,1,'linear','yes')