Clear main

src/main.cxx

@@ -6,99 +6,11 @@
 
 #include <complex>
 
-#include "Matrix.h"
+#include "common/ceMatchedFilterHandling.h"
-#include "Function.h"
-#include "Function1D.h"
-#include "Function2D.h"
-#include "Function3D.h"
 #include "MatlabReader.h"
 
 int main()
 {
-    MatlabReader m;
-    Input i;
-    MatchedFilter o;
-
-    m.read(&i, &o, "/home/krad/TestData/testCreateMatchedFilter.mat");
-    bool measuredCEused = true, findDefects = i.mParams->mFindDefects, removeOutliers = i.mRemoveOutliersFromCEMeasured;
-
-    Aurora::Matrix mFTime = Aurora::Matrix::fromRawData(i.mCe, 4000, 2304);
-    if (removeOutliers)
-    {
-        auto normSTD = Aurora::std(Aurora::abs(mFTime));
-        Aurora::nantoval(normSTD, 0.0);
-        auto sortSTD = Aurora::sort(normSTD);
-        int t = (int)std::round(0.4 * mFTime.getDimSize(1)) - 1;
-        t = t <= 0 ? 1.0 : t;
-        auto absFTime = abs(mFTime);
-        auto maxAbsFTime = max(absFTime);
-        auto maxFlag = maxAbsFTime < (0.1 * max(maxAbsFTime));
-        auto lessFlag = normSTD < sortSTD(0, t).toMatrix();
-        long maxCol, maxRow;
-        max(normSTD, Aurora::Column, maxRow, maxCol);
-        for (int j = 0; j < mFTime.getDimSize(1); ++j)
-        {
-            if ((bool)(lessFlag.getData()[j]) || (bool)(maxFlag.getData()[j]))
-            {
-                mFTime(Aurora::$, j) = mFTime(Aurora::$, maxCol);
-            }
-        }
-    }
-    auto matchedFilter = fft(mFTime);
-    auto sumDiff = Aurora::zeros(1, matchedFilter.getDimSize(1));
-    long minCol = 998, row;
-
-    auto absMatchedFilter = abs(matchedFilter);
-    auto highNoiseScore = mean(absMatchedFilter) * Aurora::std(absMatchedFilter);
-    // auto highNoiseScore = mean( abs(matchedFilter)) * Aurora::std(absMatchedFilter);
-    printf("highNoiseScore[998]: %f4, highNoiseScore[2053]:%f4\r\n", highNoiseScore.getData()[998], highNoiseScore.getData()[2053]);
-    auto medianNoise = median(highNoiseScore);
-    printf("median: %f , should be: 1724817516.8468074\r\n", medianNoise.getScalar());
-
-    min(abs(highNoiseScore - median(highNoiseScore)), Aurora::Column, row, minCol);
-    //
-    // minCol = 998;
-
-    auto maxMatchFilter = matchedFilter(Aurora::$, minCol).toMatrix();
-    for (int k = 0; k < matchedFilter.getDimSize(1); ++k)
-    {
-        sumDiff.getData()[k] = sum(abs(matchedFilter(Aurora::$, k).toMatrix() - maxMatchFilter)).getData()[0];
-    }
-
-    // printf("meanSumDiff\r\n");
-    // auto meanSumDiff = mean(sumDiff);
-    // printf("meanSumDiff finish\r\n");
-    {
-        double meansumDiff = mean(sumDiff).getScalar() ;
-        double stdSumDiff =  Aurora::std(sumDiff).getScalar();
-        double sumDiffJ =meansumDiff + 2.596 * stdSumDiff;
-        // auto indexe = sumDiff > sumDiffJ;
-        printf("indexe finish\r\n");
-
-        for (int l = 0; l < sumDiff.getDataSize(); ++l)
-        {
-            
-            if (sumDiff.getData()[l]> sumDiffJ)
-            {
-                matchedFilter(Aurora::$, l) = matchedFilter(Aurora::$, minCol);
-            }
-        }
-        printf("\r\n");
-    }
-    
-
-    if (measuredCEused)
-    {
-        auto mFTime2 = real(ifft(-matchedFilter));
-        mFTime2 = mFTime2 / repmat(max(Aurora::abs(mFTime2)), mFTime2.getDimSize(0), 1);
-        mFTime2 = mFTime2 / repmat(sum(Aurora::abs(mFTime2)), mFTime2.getDimSize(0), 1);
-        matchedFilter = fft(mFTime2);
-    }
-    for (size_t i = 0; i < 10000; i += 500)
-    {
-        printf("index :%d,origin output:%f4,%f4, output:%f4,%f4\r\n",
-               i, o.mReal[i], o.mImag[i], matchedFilter.getData()[i * 2], matchedFilter.getData()[i * 2 + 1]);
-    }
 
     return 0;
 }