/*========================================================================= * * Copyright NumFOCUS * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * https://www.apache.org/licenses/LICENSE-2.0.txt * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * *=========================================================================*/ #ifndef itkEuclideanDistanceMetric_hxx #define itkEuclideanDistanceMetric_hxx namespace itk { namespace Statistics { template inline double EuclideanDistanceMetric::Evaluate(const MeasurementVectorType & x) const { MeasurementVectorSizeType measurementVectorSize = this->GetMeasurementVectorSize(); if (measurementVectorSize == 0) { itkExceptionMacro("Please set the MeasurementVectorSize first"); } MeasurementVectorTraits::Assert(this->GetOrigin(), measurementVectorSize, "EuclideanDistanceMetric::Evaluate Origin and input vector have different lengths"); double sumOfSquares = 0.0; for (unsigned int i = 0; i < measurementVectorSize; ++i) { const double temp = this->GetOrigin()[i] - x[i]; sumOfSquares += temp * temp; } const double distance = std::sqrt(sumOfSquares); return distance; } template inline double EuclideanDistanceMetric::Evaluate(const MeasurementVectorType & x1, const MeasurementVectorType & x2) const { MeasurementVectorSizeType measurementVectorSize = NumericTraits::GetLength(x1); if (measurementVectorSize != NumericTraits::GetLength(x2)) { itkExceptionMacro("The two measurement vectors have unequal size (" << NumericTraits::GetLength(x1) << " and " << NumericTraits::GetLength(x2) << ')'); } double sumOfSquares = 0.0; for (unsigned int i = 0; i < measurementVectorSize; ++i) { const double temp = x1[i] - x2[i]; sumOfSquares += temp * temp; } const double distance = std::sqrt(sumOfSquares); return distance; } template inline double EuclideanDistanceMetric::Evaluate(const ValueType & a, const ValueType & b) const { const double temp = a - b; return itk::Math::abs(temp); } } // end of namespace Statistics } // end of namespace itk #endif