51 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
52 CubatureTensorSorted<Scalar,ArrayPoint,ArrayWeight>::CubatureTensorSorted(
53 int numPoints,
int dimension) {
58 points_.clear(); weights_.clear();
59 numPoints_ = numPoints;
60 dimension_ = dimension;
63 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
75 std::vector<Scalar> node(1,0.0);
76 typename std::map<Scalar,int>::iterator it;
77 points_.clear(); weights_.clear();
78 for (it = cubLine.
begin(); it != cubLine.
end(); it++) {
80 points_.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
81 weights_.push_back(cubLine.
getWeight(it->second));
86 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
88 int dimension, std::vector<int> numPoints1D,
89 std::vector<EIntrepidBurkardt> rule1D,
bool isNormalized) {
93 TEUCHOS_TEST_FOR_EXCEPTION((dimension!=(
int)numPoints1D.size()||
94 dimension!=(int)rule1D.size()),std::out_of_range,
95 ">>> ERROR (CubatureTensorSorted): Dimension mismatch for inputs.");
97 dimension_ = dimension;
98 degree_.resize(dimension);
99 std::vector<int> degree(1,0);
101 for (
int i=0; i<dimension; i++) {
105 degree_[i] = degree[0];
107 newRule = kron_prod<Scalar>(newRule,rule1);
110 typename std::map<std::vector<Scalar>,
int>::iterator it;
111 points_.clear(); weights_.clear();
113 std::vector<Scalar> node(dimension_,0.0);
114 for (it=newRule.
begin(); it!=newRule.
end(); it++) {
116 points_.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
117 weights_.push_back(newRule.
getWeight(node));
122 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
124 int dimension, std::vector<int> numPoints1D,
125 std::vector<EIntrepidBurkardt> rule1D,
126 std::vector<EIntrepidGrowth> growth1D,
131 TEUCHOS_TEST_FOR_EXCEPTION((dimension!=(
int)numPoints1D.size()||
132 dimension!=(int)rule1D.size()||
133 dimension!=(int)growth1D.size()),std::out_of_range,
134 ">>> ERROR (CubatureTensorSorted): Dimension mismatch for inputs.");
135 dimension_ = dimension;
136 degree_.resize(dimension);
137 std::vector<int> degree(1);
139 for (
int i=0; i<dimension; i++) {
141 int numPoints = growthRule1D(numPoints1D[i],growth1D[i],rule1D[i]);
144 degree_[i] = degree[0];
146 newRule = kron_prod<Scalar>(newRule,rule1);
150 typename std::map<std::vector<Scalar>,
int>::iterator it;
151 points_.clear(); weights_.clear();
153 std::vector<Scalar> node;
154 for (it=newRule.
begin(); it!=newRule.
end(); it++) {
156 points_.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
157 weights_.push_back(newRule.
getWeight(node));
162 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
164 int dimension,
int maxNumPoints,
165 std::vector<EIntrepidBurkardt> rule1D,
166 std::vector<EIntrepidGrowth> growth1D,
171 TEUCHOS_TEST_FOR_EXCEPTION((dimension!=(
int)rule1D.size()||
172 dimension!=(int)growth1D.size()),std::out_of_range,
173 ">>> ERROR (CubatureTensorSorted): Dimension mismatch for inputs.");
174 dimension_ = dimension;
175 degree_.resize(dimension);
176 std::vector<int> degree(1);
178 for (
int i=0; i<dimension; i++) {
180 int numPoints = growthRule1D(maxNumPoints,growth1D[i],rule1D[i]);
183 degree_[i] = degree[0];
185 newRule = kron_prod<Scalar>(newRule,rule1);
189 typename std::map<std::vector<Scalar>,
int>::iterator it;
190 points_.clear(); weights_.clear();
192 std::vector<Scalar> node;
193 for (it=newRule.
begin(); it!=newRule.
end(); it++) {
195 points_.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
196 weights_.push_back(newRule.
getWeight(node));
204 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
209 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
211 std::vector<int> & accuracy)
const {
215 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
217 ArrayPoint & cubPoints, ArrayWeight & cubWeights)
const {
219 typename std::map<std::vector<Scalar>,
int>::const_iterator it;
220 for (it=points_.begin(); it!=points_.end();it++) {
221 for (
int j=0; j<dimension_; j++) {
222 cubPoints(it->second,j) = it->first[j];
224 cubWeights(it->second) = weights_[it->second];
240 template<
class Scalar,
class ArrayPo
int,
class ArrayWeight>
242 ArrayWeight& cubWeights,
243 ArrayPoint& cellCoords)
const
245 TEUCHOS_TEST_FOR_EXCEPTION( (
true), std::logic_error,
246 ">>> ERROR (CubatureTensorSorted): Cubature defined in reference space calling method for physical space cubature.");
249 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
254 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
256 return points_.begin();
259 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
261 return points_.end();
264 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
266 typename std::map<std::vector<Scalar>,
int>::iterator it,
267 std::vector<Scalar> point,
269 points_.insert(it,std::pair<std::vector<Scalar>,
int>(point,
270 (
int)points_.size()));
271 weights_.push_back(weight);
276 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
284 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
290 return weights_[node];
293 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
295 std::vector<Scalar> point) {
299 return weights_[points_[point]];
302 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
309 typename std::map<std::vector<Scalar>,
int>::iterator it;
312 typename std::map<std::vector<Scalar>,
int> newPoints;
313 std::vector<Scalar> newWeights(0,0.0);
314 std::vector<Scalar> node(dimension_,0.0);
318 typename std::map<std::vector<Scalar>,
int> inter;
319 std::set_intersection(points_.begin(),points_.end(),
321 inserter(inter,inter.begin()),inter.value_comp());
322 for (it=inter.begin(); it!=inter.end(); it++) {
324 newWeights.push_back( alpha1*weights_[it->second]
326 newPoints.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
330 int isize = inter.size();
333 int size = points_.size();
335 typename std::map<std::vector<Scalar>,
int> diff1;
336 std::set_difference(points_.begin(),points_.end(),
338 inserter(diff1,diff1.begin()),diff1.value_comp());
339 for (it=diff1.begin(); it!=diff1.end(); it++) {
341 newWeights.push_back(alpha1*weights_[it->second]);
342 newPoints.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
350 typename std::map<std::vector<Scalar>,
int> diff2;
351 std::set_difference(cubRule2.
begin(),cubRule2.
end(),
352 points_.begin(),points_.end(),
353 inserter(diff2,diff2.begin()),diff2.value_comp());
354 for (it=diff2.begin(); it!=diff2.end(); it++) {
356 newWeights.push_back(alpha2*cubRule2.
getWeight(it->second));
357 newPoints.insert(std::pair<std::vector<Scalar>,
int>(node,loc));
362 points_.clear(); points_.insert(newPoints.begin(),newPoints.end());
363 weights_.clear(); weights_.assign(newWeights.begin(),newWeights.end());
364 numPoints_ = (int)points_.size();
367 template <
class Scalar,
class ArrayPo
int,
class ArrayWeight>
371 typename std::vector<Scalar>::iterator it;
372 for (it=weights_.begin(); it!=weights_.end(); it++)
375 for (it=weights_.begin(); it!=weights_.end(); it++)
383 template <
class Scalar>
399 CubatureTensorSorted<Scalar> TPrule(0,Ndim+1);
406 typename std::map<std::vector<Scalar>,
int>::iterator it = TPrule.begin();
407 typename std::map<std::vector<Scalar>,
int>::iterator it_i;
408 typename std::map<Scalar,int>::iterator it_j;
409 for (it_i=rule1.
begin(); it_i!=rule1.
end(); it_i++) {
410 for (it_j=rule2.
begin(); it_j!=rule2.
end(); it_j++) {
411 std::vector<Scalar> node = rule1.
getNode(it_i);
414 node.push_back(node2);
415 TPrule.insert(it,node,weight);
424 #if defined(Intrepid_SHOW_DEPRECATED_WARNINGS)
426 #warning "The Intrepid package is deprecated"
int getNumPoints() const
Returns the number of cubature points.
void normalize()
Normalize CubatureLineSorted weights.
std::map< std::vector< Scalar >, int >::iterator begin()
Initiate iterator at the beginning of data.
Utilizes cubature (integration) rules contained in the library sandia_rules (John Burkardt...
std::map< Scalar, int >::iterator begin(void)
Initiate iterator at the beginning of data.
Scalar getWeight(int node)
Get a specific weight described by the integer location.
std::vector< Scalar > getNode(typename std::map< std::vector< Scalar >, int >::iterator it)
Get a specific node described by the iterator location.
void getAccuracy(std::vector< int > &accuracy) const
Returns max. degree of polynomials that are integrated exactly. The return vector has size 1...
void update(Scalar alpha2, CubatureTensorSorted< Scalar > &cubRule2, Scalar alpha1)
Replace CubatureLineSorted values with "this = alpha1*this+alpha2*cubRule2".
int getNumPoints() const
Returns the number of cubature points.
void insert(typename std::map< std::vector< Scalar >, int >::iterator it, std::vector< Scalar > point, Scalar weight)
Insert a node and weight into data near the iterator position.
int getDimension() const
Returns dimension of domain of integration.
Scalar getNode(typename std::map< Scalar, int >::iterator it)
Get a specific node described by the iterator location.
void getAccuracy(std::vector< int > &accuracy) const
Returns max. degree of polynomials that are integrated exactly. The return vector has size 1...
Utilizes 1D cubature (integration) rules contained in the library sandia_rules (John Burkardt...
void getCubature(ArrayPoint &cubPoints, ArrayWeight &cubWeights) const
Returns cubature points and weights (return arrays must be pre-sized/pre-allocated).
Scalar getWeight(int weight)
Get a specific weight described by the integer location.
std::map< std::vector< Scalar >, int >::iterator end()
Initiate iterator at the end of data.
std::map< Scalar, int >::iterator end(void)
Initiate iterator at the end of data.