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backport 963931: fix linearRegression
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@@ -62,6 +62,20 @@ void makeNoisyCohyperplanarPoints(int numPoints,
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*(points[i]) += noiseAmplitude * VectorType::Random(size);
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}
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template<typename VectorType>
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void check_linearRegression(int numPoints,
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VectorType **points,
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const VectorType& original,
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typename VectorType::Scalar tolerance)
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{
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int size = points[0]->size();
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assert(size==2);
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VectorType result(size);
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linearRegression(numPoints, points, &result, 1);
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typename VectorType::Scalar error = (result - original).norm() / original.norm();
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VERIFY(ei_abs(error) < ei_abs(tolerance));
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}
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template<typename VectorType,
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typename HyperplaneType>
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void check_fitHyperplane(int numPoints,
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@@ -81,6 +95,20 @@ void test_regression()
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{
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for(int i = 0; i < g_repeat; i++)
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{
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{
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Vector2f points2f [1000];
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Vector2f *points2f_ptrs [1000];
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for(int i = 0; i < 1000; i++) points2f_ptrs[i] = &(points2f[i]);
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Vector2f coeffs2f;
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Hyperplane<float,2> coeffs3f;
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makeNoisyCohyperplanarPoints(1000, points2f_ptrs, &coeffs3f, 0.01f);
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coeffs2f[0] = -coeffs3f.coeffs()[0]/coeffs3f.coeffs()[1];
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coeffs2f[1] = -coeffs3f.coeffs()[2]/coeffs3f.coeffs()[1];
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CALL_SUBTEST(check_linearRegression(10, points2f_ptrs, coeffs2f, 0.05f));
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CALL_SUBTEST(check_linearRegression(100, points2f_ptrs, coeffs2f, 0.01f));
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CALL_SUBTEST(check_linearRegression(1000, points2f_ptrs, coeffs2f, 0.002f));
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}
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{
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Vector2f points2f [1000];
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Vector2f *points2f_ptrs [1000];
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