replacemissing1d

[xReplaced, NaN_Indx] = replacemissing1d(x, what2replace, interpMethod, dispout)

Description

Replace missing data points in 1d data such as time series

Inputs

x

Input data

what2replace=’both’;

What needs to be replaced

‘NaN’: replacing NaN data points

‘Inf’: replacing Inf data points

‘both’: replacing NaN and Inf data points

Number: replacing data points equal to Number

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

xReplaced

Replaced data

NaN_Indx

Logical index of replaced points

Examples

fs=128;
t(:,1)=linspace(0,9.5,10*fs);
x(:,1)=sin(2*pi*0.3*t)+0.1*sin(2*pi*4*t);
spikeloc(:,1)=[10:100:length(t(:,1))];
x(spikeloc+round(2*randn(length(spikeloc(:,1)),1)),1)=NaN;
x=x+5;
x(220:225,1)=NaN;
[xReplaced,NaN_Indx]=replacemissing1d(x,'NaN','linear','yes');

fs=2;
t(:,1)=linspace(0,1023.5,1024*fs);
x(:,1)=detrend(0.5.*cos(2*pi*0.2*t)+(-0.1+(0.1-(-0.1))).*rand(1024*fs,1));
spikeloc(:,1)=[10:100:length(t(:,1))];
x=x+1;
x(spikeloc+round(2*randn(length(spikeloc(:,1)),1)),1)=0;
[xReplaced,NaN_Indx]=replacemissing1d(x,0,'linear','yes');

References