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Eigen_demo: Added FFT demo

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git-svn-id: svn://ultimatepp.org/upp/trunk@9470 f0d560ea-af0d-0410-9eb7-867de7ffcac7
This commit is contained in:
koldo 2016-02-12 22:24:24 +00:00
parent bb5315c1ae
commit db2d4333ef
3 changed files with 96 additions and 1 deletions
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3
reference/Eigen_demo/Eigen_demo.upp
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@ -6,7 +6,8 @@ uses
file
eigen_demo.cpp,
non-linear.cpp;
non-linear.cpp,
fft.cpp;
mainconfig
"" = "";

10
reference/Eigen_demo/eigen_demo.cpp
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@ -7,6 +7,7 @@ using namespace Upp;
using namespace Eigen;
void NonLinearTests();
void FFTTests();
struct SerialTest {
MatrixXd m;
@ -30,6 +31,10 @@ struct SerialTest {
CONSOLE_APP_MAIN
{
FFTTests();
Cout() << "\nFin";
getchar();
// http://eigen.tuxfamily.org/dox/TutorialMatrixClass.html
Cout() << "\n\nTutorial page 1 - The Matrix class";
@ -695,6 +700,11 @@ CONSOLE_APP_MAIN
NonLinearTests();
Cout() << "\nPress enter to continue\n";
ReadStdIn();
FFTTests();
Cout() << "\nPress enter to end";
ReadStdIn();
}

84
reference/Eigen_demo/fft.cpp Normal file
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@ -0,0 +1,84 @@
#include <Core/Core.h>
using namespace Upp;
#include <plugin/Eigen/Eigen.h>
#ifdef USE_FFTW
#include <fftw3.h>
#endif
using namespace Eigen;
void FFTTests()
{
Cout() << "\n\nFFT sample\nGets the FFT of equation"
"\n f(t) = 2*sin(2*PI*t/50 - PI/3) + 5*sin(2*PI*t/30 - PI/2) + 30*sin(2*PI*t/10 - PI/5)"
"\nsampled with a frequency of 14 samples/second";
int numData = 8000;
double samplingFrecuency = 14;
String csvSep = ";";
// Filling the data series
VectorXd timebuf(numData);
{
double t = 0;
for (int i = 0; i < numData; ++i, t = i*1/samplingFrecuency)
timebuf[i] = 2*sin(2*M_PI*t/50 - M_PI/3) + 5*sin(2*M_PI*t/30 - M_PI/2) + 30*sin(2*M_PI*t/10 - M_PI/5);
}
// FFT
VectorXcd freqbuf;
FFT<double> fft;
fft.SetFlag(fft.HalfSpectrum);
fft.fwd(freqbuf, timebuf);
// Filter the FFT. Frequemcies between 1/25 and 1/35 Hz are removed
// Original FFT is not changed for saving it later
VectorXcd freqbuf2(freqbuf.size());
{
for (int i = 0; i < freqbuf.size(); ++i) {
double freq = i*samplingFrecuency/numData;
double T = 1/freq;
if (T > 25 && T < 35)
freqbuf2[i] = 0;
else
freqbuf2[i] = freqbuf[i];
}
}
// Inverse filtered FFT to get filtered series
VectorXd timebuf2(numData);
fft.inv(timebuf2, freqbuf2);
// Saving original and filtered FFT
{
String str;
str << "Frec" << csvSep << "T" << csvSep << "fft" << csvSep << "Filtered fft";
for (int i = 0; i < freqbuf.size(); ++i) {
double freq = i*samplingFrecuency/numData;
double T = 1/freq;
str << "\n" << freq << csvSep << (freq > 0 ? FormatDouble(T) : "") << csvSep
<< 2*std::abs(freqbuf[i])/numData << csvSep
<< 2*std::abs(freqbuf2[i])/numData;;
}
String fftFileName = AppendFileName(GetDesktopFolder(), "fft.csv");
Cout() << "\nFFT saved in '" << fftFileName << "'";
SaveFile(fftFileName, str);
}
// Saving original and filtered series
{
String str;
str << "Time" << csvSep << "Data" << csvSep << "Filtered data";
double t = 0;
for (int i = 0; i < numData; ++i, t = i*1/samplingFrecuency)
str << "\n" << t << csvSep << timebuf[i] << csvSep << timebuf2[i];;
String dataFileName = AppendFileName(GetDesktopFolder(), "data.csv");
Cout() << "\nSource data saved in '" << dataFileName << "'";
SaveFile(dataFileName, str);
}
}