PreprocessingModulesExamples/DoubleMovingAverageFilterExample/DoubleMovingAverageFilterExample.cpp

/*
 GRT MIT License
 Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>
 
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/*
 GRT DoubleMovingAverageFilter Example
 This example demonstrates how to create and use the GRT DoubleMovingAverageFilter PreProcessing Module.
 
 The DoubleMovingAverageFilter implements a low pass double moving average filter. 
 
 In this example we create an instance of a DoubleMovingAverageFilter and use this to filter some
 dummy data, generated from a sine wave + random noise. The test signal and filtered signals are 
 then printed to std::cout.
 
 This example shows you how to:
 - Create a new DoubleMovingAverageFilter instance with a specific window size for a 1 dimensional signal
 - Filter some data using the DoubleMovingAverageFilter
 - Save the DoubleMovingAverageFilter settings to a file
 - Load the DoubleMovingAverageFilter settings from a file
*/

//You might need to set the specific path of the GRT header relative to your project
#include <GRT/GRT.h>
using namespace GRT;
using namespace std;

int main (int argc, const char * argv[])
{
 //Create a new instance of a double moving average filter with a window size of 5 for a 1 dimensional signal
 DoubleMovingAverageFilter filter( 5, 1 );
 
 //Generate some data (sine wave + noise) and filter it
 double x = 0;
 const UINT M = 1000;
 Random random;
 for(UINT i=0; i<M; i++){
 double signal = sin( x ) + random.getRandomNumberUniform(-0.2,0.2);
 
 double filteredValue = filter.filter( signal );
 
 cout << signal << "\t" << filteredValue << endl;
 
 x += TWO_PI/double(M)*10;
 }
 
 //Save the filter settings to a file
 filter.save("DoubleMovingAverageFilterSettings.grt");
 
 //We can then load the settings later if needed
 filter.load("DoubleMovingAverageFilterSettings.grt");
 
 return EXIT_SUCCESS;
}