Diff: SpactrumAnalysisClasses/FFT_Analysis.cpp

Revision:

0:c5b026c2d07e

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/SpactrumAnalysisClasses/FFT_Analysis.cpp	Sun Jul 26 02:48:23 2015 +0000
@@ -0,0 +1,51 @@
+//-------------------------------------------------------
+// Class for spectrum analysis using FFT
+// Copyright (c) 2014 MIKAMI, Naoki,  2014/12/30
+//-------------------------------------------------------
+
+#include "FFT_Analysis.hpp"
+
+namespace Mikami
+{
+    FftAnalyzer::FftAnalyzer(int nData, int nFft)
+            : N_DATA_(nData), N_FFT_(nFft),
+              hm_(nData-1, nFft), fft_(nFft)
+    {
+        pkHolder_ = new PeakHolder[nFft/2+1];
+        for (int n=0; n<=nFft/2; n++)
+            pkHolder_[n].SetCoefs(0.2f);    
+
+        xData = new float[nData];       // Data to be analyzed
+        xFft = new float[nFft];         // Input for FFT
+        yFft = new Complex[nFft/2+1];   // Output of FFT
+        normY = new float[nFft/2+1];    // Powerspectrum
+    }
+   
+    FftAnalyzer::~FftAnalyzer()
+    {
+        delete[] pkHolder_;
+        delete[] xData;
+        delete[] xFft;
+        delete[] yFft;
+        delete[] normY;
+    }
+
+    void FftAnalyzer::Execute(float xn[], float db[])
+    {
+        // Differencing
+        for (int n=0; n<N_DATA_-1; n++)
+            xData[n] = xn[n+1] - xn[n];
+
+        hm_.Execute(xData, xFft);    // Windowing and zero-padding
+        fft_.Execute(xFft, yFft);    // Execute FFT
+
+        // Smoothing
+        for (int n=0; n<=N_FFT_/2; n++)
+            normY[n] = pkHolder_[n].Execute(Sqr(yFft[n].real())
+                     + Sqr(yFft[n].imag()));
+
+        // Translate to dB
+        for (int n=0; n<=N_FFT_/2; n++)
+            db[n] = 10.0f*log10f(normY[n]);
+    }
+}