Chaste Release::3.1
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00001 /* 00002 00003 Copyright (c) 2005-2012, University of Oxford. 00004 All rights reserved. 00005 00006 University of Oxford means the Chancellor, Masters and Scholars of the 00007 University of Oxford, having an administrative office at Wellington 00008 Square, Oxford OX1 2JD, UK. 00009 00010 This file is part of Chaste. 00011 00012 Redistribution and use in source and binary forms, with or without 00013 modification, are permitted provided that the following conditions are met: 00014 * Redistributions of source code must retain the above copyright notice, 00015 this list of conditions and the following disclaimer. 00016 * Redistributions in binary form must reproduce the above copyright notice, 00017 this list of conditions and the following disclaimer in the documentation 00018 and/or other materials provided with the distribution. 00019 * Neither the name of the University of Oxford nor the names of its 00020 contributors may be used to endorse or promote products derived from this 00021 software without specific prior written permission. 00022 00023 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 00024 AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 00025 IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 00026 ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE 00027 LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 00028 CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE 00029 GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) 00030 HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00031 LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT 00032 OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00033 00034 */ 00035 00036 #include "CellwiseDataGradient.hpp" 00037 #include "LinearBasisFunction.hpp" 00038 00039 template<unsigned DIM> 00040 c_vector<double, DIM>& CellwiseDataGradient<DIM>::rGetGradient(unsigned nodeIndex) 00041 { 00042 return mGradients[nodeIndex]; 00043 } 00044 00045 00046 template<unsigned DIM> 00047 void CellwiseDataGradient<DIM>::SetupGradients(AbstractCellPopulation<DIM>& rCellPopulation, const std::string& rItemName) 00048 { 00049 MeshBasedCellPopulation<DIM>* pCellPopulation = static_cast<MeshBasedCellPopulation<DIM>*>(&(rCellPopulation)); 00050 TetrahedralMesh<DIM,DIM>& r_mesh = pCellPopulation->rGetMesh(); 00051 00052 // Initialise gradients size 00053 unsigned num_nodes = pCellPopulation->GetNumNodes(); 00054 mGradients.resize(num_nodes, zero_vector<double>(DIM)); 00055 00056 // The constant gradients at each element 00057 std::vector<c_vector<double, DIM> > gradients_on_elements; 00058 unsigned num_elements = r_mesh.GetNumElements(); 00059 gradients_on_elements.resize(num_elements, zero_vector<double>(DIM)); 00060 00061 // The number of elements containing a given node (excl ghost elements) 00062 std::vector<unsigned> num_real_elems_for_node(num_nodes, 0); 00063 00064 for (unsigned elem_index=0; elem_index<num_elements; elem_index++) 00065 { 00066 Element<DIM,DIM>& r_elem = *(r_mesh.GetElement(elem_index)); 00067 00068 // Calculate the basis functions at any point (eg zero) in the element 00069 c_matrix<double, DIM, DIM> jacobian, inverse_jacobian; 00070 double jacobian_det; 00071 r_mesh.GetInverseJacobianForElement(elem_index, jacobian, jacobian_det, inverse_jacobian); 00072 const ChastePoint<DIM> zero_point; 00073 c_matrix<double, DIM, DIM+1> grad_phi; 00074 LinearBasisFunction<DIM>::ComputeTransformedBasisFunctionDerivatives(zero_point, inverse_jacobian, grad_phi); 00075 00076 bool is_ghost_element = false; 00077 00078 for (unsigned node_index=0; node_index<DIM+1; node_index++) 00079 { 00080 unsigned node_global_index = r_elem.GetNodeGlobalIndex(node_index); 00081 00082 // This code is commented because CellData can't deal with ghost nodes see #1975 00083 assert(pCellPopulation->IsGhostNode(node_global_index) == false); 00085 //if (pCellPopulation->IsGhostNode(node_global_index) == true) 00086 //{ 00087 // is_ghost_element = true; 00088 // break; 00089 //} 00090 00091 // If no ghost element, get PDE solution 00092 CellPtr p_cell = pCellPopulation->GetCellUsingLocationIndex(node_global_index); 00093 double pde_solution = p_cell->GetCellData()->GetItem(rItemName); 00094 00095 // Interpolate gradient 00096 for (unsigned i=0; i<DIM; i++) 00097 { 00098 gradients_on_elements[elem_index](i) += pde_solution* grad_phi(i, node_index); 00099 } 00100 } 00101 00102 // Add gradient at element to gradient at node 00103 if (!is_ghost_element) 00104 { 00105 for (unsigned node_index=0; node_index<DIM+1; node_index++) 00106 { 00107 unsigned node_global_index = r_elem.GetNodeGlobalIndex(node_index); 00108 mGradients[node_global_index] += gradients_on_elements[elem_index]; 00109 num_real_elems_for_node[node_global_index]++; 00110 } 00111 } 00112 } 00113 00114 // Divide to obtain average gradient 00115 for (typename AbstractCellPopulation<DIM>::Iterator cell_iter = pCellPopulation->Begin(); 00116 cell_iter != pCellPopulation->End(); 00117 ++cell_iter) 00118 { 00119 unsigned node_global_index = pCellPopulation->GetLocationIndexUsingCell(*cell_iter); 00120 00121 if (!num_real_elems_for_node[node_global_index] > 0) 00122 { 00123 NEVER_REACHED; 00124 // This code is commented because CellwiseData Can't deal with ghost nodes so won't ever come into this statement see #1975 00127 //Node<DIM>& this_node = *(pCellPopulation->GetNodeCorrespondingToCell(*cell_iter)); 00128 // 00129 //mGradients[node_global_index] = zero_vector<double>(DIM); 00130 //unsigned num_real_adjacent_nodes = 0; 00131 // 00133 //std::set<Node<DIM>*> real_adjacent_nodes; 00134 //real_adjacent_nodes.clear(); 00135 // 00137 //for (typename Node<DIM>::ContainingElementIterator element_iter = this_node.ContainingElementsBegin(); 00138 // element_iter != this_node.ContainingElementsEnd(); 00139 // ++element_iter) 00140 //{ 00141 // // Then loop over nodes therein 00142 // Element<DIM,DIM>& r_adjacent_elem = *(r_mesh.GetElement(*element_iter)); 00143 // for (unsigned local_node_index=0; local_node_index<DIM+1; local_node_index++) 00144 // { 00145 // unsigned adjacent_node_global_index = r_adjacent_elem.GetNodeGlobalIndex(local_node_index); 00146 // 00147 // // If not a ghost node and not the node we started with 00148 // if ( !(pCellPopulation->IsGhostNode(adjacent_node_global_index)) 00149 // && adjacent_node_global_index != node_global_index ) 00150 // { 00151 // 00152 // // Calculate the contribution of gradient from this node 00153 // Node<DIM>& adjacent_node = *(r_mesh.GetNode(adjacent_node_global_index)); 00154 // 00155 // double this_cell_concentration = CellwiseData<DIM>::Instance()->GetValue(*cell_iter, 0); 00156 // CellPtr p_adjacent_cell = pCellPopulation->GetCellUsingLocationIndex(adjacent_node_global_index); 00157 // double adjacent_cell_concentration = CellwiseData<DIM>::Instance()->GetValue(p_adjacent_cell, 0); 00158 // 00159 // c_vector<double, DIM> gradient_contribution = zero_vector<double>(DIM); 00160 // 00161 // if (fabs(this_cell_concentration-adjacent_cell_concentration) > 100*DBL_EPSILON) 00162 // { 00163 // c_vector<double, DIM> edge_vector = r_mesh.GetVectorFromAtoB(this_node.rGetLocation(), adjacent_node.rGetLocation()); 00164 // double norm_edge_vector = norm_2(edge_vector); 00165 // gradient_contribution = edge_vector 00166 // * (adjacent_cell_concentration - this_cell_concentration) 00167 // / (norm_edge_vector * norm_edge_vector); 00168 // } 00169 // 00170 // mGradients[node_global_index] += gradient_contribution; 00171 // num_real_adjacent_nodes++; 00172 // } 00173 // } 00174 //} 00175 //mGradients[node_global_index] /= num_real_adjacent_nodes; 00176 } 00177 else 00178 { 00179 mGradients[node_global_index] /= num_real_elems_for_node[node_global_index]; 00180 } 00181 } 00182 } 00183 00185 // Explicit instantiation 00187 00188 template class CellwiseDataGradient<1>; 00189 template class CellwiseDataGradient<2>; 00190 template class CellwiseDataGradient<3>;