This document describes filtering arbitrary data contained in a .mat file. It loads data from a selected .mat file, defines a 4th order lowpass Butterworth filter centered at 0.05*pi rad/sample, takes the FFT of the data and plots the frequency spectrum, overlays the filter response curve, filters the temperature data, and plots the unfiltered and filtered time series data for comparison.

1. %Matthew Mobley
%Filter arbitrary data contained in a .mat file
%Largely adapted from http://dadorran.wordpress.com search for filtering matlab demo
clear all;
%==============================DEFINITIONS================================%
%load data
[FileName,PathName] = uigetfile('*.mat','Select the .mat-file');
X = importdata(FileName);
%define filter parameters (here a 4th order lowpass butterworth filter
%centered at 0.05*pi rad/sample is the default)
prompt = {'Enter Filter Order:','Enter Filter Frequency:', 'Select Filter Type'};
dlg_title = 'Filter Parameters';
num_lines = 1;
def = {'4','0.05','low'};
answer = inputdlg(prompt,dlg_title,num_lines,def);
FilterOrder = str2double(answer(1));
f0 = str2double(answer(2));
filtertype = char(answer(3));
[b a] = butter(FilterOrder, f0, filtertype);
%=========================================================================%
%============================FFT & FILTER PLOT============================%
%take fft of data
X_mags = abs(fft(X));
num_bins = length(X_mags);
%normalize magnitudes
normX_mags = X_mags./(max(X_mags));
%plot frequency spectrum
plot([0:1/(num_bins/2 -1):1], normX_mags(1:num_bins/2))
xlabel('Normalized Frequency (pi rads/sample)')
ylabel('Normalized Magnitude')
%store filter response curve in H
H = freqz(b,a, floor(num_bins/2));
%plot filter response curve
hold on
plot([0:1/(num_bins/2 -1):1], abs(H),'r');
legend('Normalized Frequency Data', 'Applied Filter Response');
%=========================================================================%
%=======================COMPARATIVE TIME SERIES PLOT======================%
figure(2);
%filter temperature data
Tfiltered = filter(b,a, X);
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2. %plot time series data
subplot(2,1,1), plot(X), title('Unfiltered Data'), xlabel('Sample'), ylabel
('Absolute Magnitude');
subplot(2,1,2), plot(Tfiltered), title('Filtered Data'), xlabel('Sample'), ylabel
('Absolute Magnitude');
%=========================================================================%
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3. Published with MATLAB® R2012b
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