Changeset 1120
- Timestamp:
- Feb 22, 2008, 12:18:41 AM (16 years ago)
- Location:
- trunk
- Files:
-
- 50 edited
- 2 moved
Legend:
- Unmodified
- Added
- Removed
-
trunk/test/averager_test.cc
r1043 r1120 28 28 #include "yat/statistics/AveragerPairWeighted.h" 29 29 #include "yat/statistics/AveragerWeighted.h" 30 #include "yat/utility/ vector.h"30 #include "yat/utility/Vector.h" 31 31 32 32 #include <cmath> … … 123 123 *error << "variance(mean) " << a.variance(a.mean()) << std::endl; 124 124 } 125 theplu::yat::utility:: vector* tmp_vec = new theplu::yat::utility::vector(10);125 theplu::yat::utility::Vector* tmp_vec = new theplu::yat::utility::Vector(10); 126 126 add(a, tmp_vec->begin(), tmp_vec->end()); 127 127 delete tmp_vec; … … 135 135 // Testing AveragerWeighted 136 136 *error << "testing AveragerWeighted" << std::endl; 137 theplu::yat::utility:: vector x(3,0);137 theplu::yat::utility::Vector x(3,0); 138 138 x(0)=0; 139 139 x(1)=1; 140 140 x(2)=2; 141 theplu::yat::utility:: vector w(3,1);141 theplu::yat::utility::Vector w(3,1); 142 142 theplu::yat::statistics::AveragerWeighted aw; 143 143 add(aw, x.begin(), x.end(), w.begin()); … … 174 174 delete aw2; 175 175 { 176 theplu::yat::utility:: vector tmp(10);176 theplu::yat::utility::Vector tmp(10); 177 177 add(aw, tmp.begin(), tmp.end()); 178 178 } … … 206 206 AveragerPairWeighted apw; 207 207 x(0)=0; x(1)=1; x(2)=2; 208 theplu::yat::utility:: vector y(3,0);208 theplu::yat::utility::Vector y(3,0); 209 209 x(0)=0; x(1)=0; x(2)=2; 210 210 add(apw, x.begin(), x.end(), y.begin(), w.begin(), w.begin()); -
trunk/test/data_lookup_1d_test.cc
r1000 r1120 130 130 my_out.close(); 131 131 std::ifstream is("data/tmp_test_datalookup1D.txt"); 132 utility:: vector v5(is);132 utility::Vector v5(is); 133 133 is.close(); 134 134 if (v5.size()!=v1.size() || v5(0)!=v1(0) || v5(1)!=v1(1) || … … 148 148 my_out.close(); 149 149 is.open("data/tmp_test_datalookup1D.txt"); 150 utility:: vector v7(is,'\t');150 utility::Vector v7(is,'\t'); 151 151 is.close(); 152 152 if (v7.size()!=v6.size() || !std::isnan(v7(1))) { … … 161 161 162 162 DataLookup1D dl(v5); 163 utility:: vector v8;163 utility::Vector v8; 164 164 classifier::convert(dl, v8); 165 165 if (!v5.equal(v8,0.0)) { -
trunk/test/distance_test.cc
r1053 r1120 27 27 #include "yat/statistics/PearsonDistance.h" 28 28 #include "yat/utility/matrix.h" 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 #include <cassert> … … 52 52 bool ok = true; 53 53 54 utility:: vector a(3,1);54 utility::Vector a(3,1); 55 55 a(1) = 2; 56 utility:: vector b(3,0);56 utility::Vector b(3,0); 57 57 b(2) = 1; 58 58 -
trunk/test/iterator_test.cc
r1111 r1120 28 28 #include "yat/utility/Container2DIterator.h" 29 29 #include "yat/utility/matrix.h" 30 #include "yat/utility/ vector.h"30 #include "yat/utility/Vector.h" 31 31 32 32 #include <algorithm> … … 49 49 50 50 *message << "testing utility::vector::iterator" << std::endl; 51 utility:: vector vec(12);51 utility::Vector vec(12); 52 52 classifier::DataLookup1D lookup(vec); 53 utility:: vector::iterator begin=vec.begin();53 utility::Vector::iterator begin=vec.begin(); 54 54 // test iterator to const_iterator conversion 55 utility:: vector::const_iterator ci = vec.begin();55 utility::Vector::const_iterator ci = vec.begin(); 56 56 ci = begin; 57 57 if (begin!=ci) 58 58 ok = false; 59 59 60 utility:: vector::iterator end=vec.end();60 utility::Vector::iterator end=vec.end(); 61 61 std::sort(begin, end); 62 62 -
trunk/test/matrix_test.cc
r1098 r1120 170 170 // Checking that a view is not inherited through the copy 171 171 // contructor. 172 utility:: vector v6(v5subrow);172 utility::Vector v6(v5subrow); 173 173 v6.all(2); 174 174 double v5subrow_sum3=0; -
trunk/test/regression_test.cc
r1000 r1120 31 31 #include "yat/regression/PolynomialWeighted.h" 32 32 #include "yat/utility/matrix.h" 33 #include "yat/utility/ vector.h"33 #include "yat/utility/Vector.h" 34 34 35 35 #include <cmath> … … 48 48 bool unity_weights(regression::OneDimensional&, 49 49 regression::OneDimensionalWeighted&, 50 const utility:: vector&, const utility::vector&,50 const utility::Vector&, const utility::Vector&, 51 51 std::ostream*); 52 52 53 53 bool rescale_weights(regression::OneDimensionalWeighted&, 54 const utility:: vector&, const utility::vector&,54 const utility::Vector&, const utility::Vector&, 55 55 std::ostream*); 56 56 57 57 bool zero_weights(regression::OneDimensionalWeighted&, 58 const utility:: vector&, const utility::vector&,58 const utility::Vector&, const utility::Vector&, 59 59 std::ostream*); 60 60 … … 77 77 78 78 // test data for Linear and Naive (Weighted and non-weighted) 79 utility:: vector x(4); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000;80 utility:: vector y(4); y(0)=12; y(1)=11; y(2)=14; y(3)=13;81 utility:: vector w(4); w(0)=0.1; w(1)=0.2; w(2)=0.3; w(3)=0.4;79 utility::Vector x(4); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000; 80 utility::Vector y(4); y(0)=12; y(1)=11; y(2)=14; y(3)=13; 81 utility::Vector w(4); w(0)=0.1; w(1)=0.2; w(2)=0.3; w(3)=0.4; 82 82 83 83 // Comparing linear and polynomial(1) … … 208 208 std::ifstream s("data/regression_gauss.data"); 209 209 utility::matrix data(s); 210 utility:: vector x(data.rows());211 utility:: vector ln_y(data.rows());210 utility::Vector x(data.rows()); 211 utility::Vector ln_y(data.rows()); 212 212 for (size_t i=0; i<data.rows(); ++i) { 213 213 x(i)=data(i,0); … … 217 217 regression::Polynomial polynomialfit(2); 218 218 polynomialfit.fit(x,ln_y); 219 utility:: vector fit=polynomialfit.fit_parameters();219 utility::Vector fit=polynomialfit.fit_parameters(); 220 220 if (fabs(fit[0]-1.012229646706 + fit[1]-0.012561322528 + 221 221 fit[2]+1.159674470130)>1e-11) { … … 247 247 { 248 248 bool ok=true; 249 utility:: vector x(5); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000; x(4)=2010;250 utility:: vector y(5); y(0)=12; y(1)=11; y(2)=14; y(3)=13; y(4)=15;249 utility::Vector x(5); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000; x(4)=2010; 250 utility::Vector y(5); y(0)=12; y(1)=11; y(2)=14; y(3)=13; y(4)=15; 251 251 252 252 ok = unity_weights(r, wr, x, y, error) && ok; … … 259 259 bool unity_weights(regression::OneDimensional& r, 260 260 regression::OneDimensionalWeighted& rw, 261 const utility:: vector& x, const utility::vector& y,261 const utility::Vector& x, const utility::Vector& y, 262 262 std::ostream* error) 263 263 { 264 264 *error << " testing unity weights equal to non-weighted version.\n"; 265 265 bool ok=true; 266 utility:: vector w(x.size(), 1.0);266 utility::Vector w(x.size(), 1.0); 267 267 r.fit(x,y); 268 268 rw.fit(x,y,w); … … 303 303 304 304 bool rescale_weights(regression::OneDimensionalWeighted& wr, 305 const utility:: vector& x, const utility::vector& y,305 const utility::Vector& x, const utility::Vector& y, 306 306 std::ostream* error) 307 307 { 308 308 *error << " testing rescaling weights.\n"; 309 309 bool ok = true; 310 utility:: vector w(5); w(0)=1.0; w(1)=1.0; w(2)=0.5; w(3)=0.2; w(4)=0.2;310 utility::Vector w(5); w(0)=1.0; w(1)=1.0; w(2)=0.5; w(3)=0.2; w(4)=0.2; 311 311 wr.fit(x,y,w); 312 312 double predict = wr.predict(2000); … … 359 359 360 360 bool zero_weights(regression::OneDimensionalWeighted& wr, 361 const utility:: vector& x, const utility::vector& y,361 const utility::Vector& x, const utility::Vector& y, 362 362 std::ostream* error) 363 363 { 364 364 *error << " testing zero weights equal to missing value.\n"; 365 365 bool ok = true; 366 utility:: vector w(5); w(0)=1.0; w(1)=1.0; w(2)=0.5; w(3)=0.2; w(4)=0;366 utility::Vector w(5); w(0)=1.0; w(1)=1.0; w(2)=0.5; w(3)=0.2; w(4)=0; 367 367 wr.fit(x,y,w); 368 368 double predict = wr.predict(2000); … … 372 372 double standard_error2 = wr.standard_error2(2000); 373 373 374 utility:: vector x2(4);375 utility:: vector y2(4);376 utility:: vector w2(4);374 utility::Vector x2(4); 375 utility::Vector y2(4); 376 utility::Vector w2(4); 377 377 for (size_t i=0; i<4; ++i){ 378 378 x2(i) = x(i); … … 412 412 bool ok = true; 413 413 *error << " testing regression::MultiDimensionalWeighted" << std::endl; 414 utility:: vector x(5); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000; x(4)=2010;415 utility:: vector y(5); y(0)=12; y(1)=11; y(2)=14; y(3)=13; y(4)=15;416 utility:: vector w(5,1.0);414 utility::Vector x(5); x(0)=1970; x(1)=1980; x(2)=1990; x(3)=2000; x(4)=2010; 415 utility::Vector y(5); y(0)=12; y(1)=11; y(2)=14; y(3)=13; y(4)=15; 416 utility::Vector w(5,1.0); 417 417 418 418 utility::matrix data(5,3); … … 426 426 regression::MultiDimensionalWeighted mdw; 427 427 mdw.fit(data,y,w); 428 utility:: vector z(3,1);428 utility::Vector z(3,1); 429 429 z(1)=2000; 430 430 z(2)=2000*2000; … … 502 502 rl.fit(10, 100); 503 503 504 utility:: vector y(rl.y_predicted());504 utility::Vector y(rl.y_predicted()); 505 505 for (size_t i=0; i<y.size(); i++) 506 506 if (y(i)!=10.0){ -
trunk/test/roc_test.cc
r1000 r1120 27 27 #include "yat/statistics/utility.h" 28 28 #include "yat/utility/matrix.h" 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 #include <cmath> … … 49 49 50 50 *error << "testing ROC" << std::endl; 51 utility:: vector value(31);51 utility::Vector value(31); 52 52 std::vector<std::string> label(31,"negative"); 53 53 for (size_t i=0; i<16; i++) -
trunk/test/score_test.cc
r1028 r1120 31 31 #include "yat/statistics/WilcoxonFoldChange.h" 32 32 #include "yat/utility/matrix.h" 33 #include "yat/utility/ vector.h"33 #include "yat/utility/Vector.h" 34 34 #include "yat/utility/VectorView.h" 35 35 … … 55 55 56 56 *error << "testing AUC" << std::endl; 57 utility:: vector value(31);57 utility::Vector value(31); 58 58 std::vector<std::string> label(31,"negative"); 59 59 for (size_t i=0; i<16; i++) … … 86 86 is.close(); 87 87 88 utility:: vector correct_area(3);88 utility::Vector correct_area(3); 89 89 correct_area(0)=1.0/9.0; 90 90 correct_area(1)=3.0/9.0; … … 107 107 } 108 108 109 utility:: vector weight(target2.size(),1);109 utility::Vector weight(target2.size(),1); 110 110 for (size_t i=0; i<data.rows(); i++){ 111 111 utility::VectorView vec = data.row_view(i); -
trunk/test/statistics_test.cc
r1039 r1120 25 25 26 26 #include "yat/statistics/utility.h" 27 #include "yat/utility/ vector.h"27 #include "yat/utility/Vector.h" 28 28 29 29 #include <vector> … … 35 35 { 36 36 using namespace theplu::yat; 37 utility:: vector gsl_vec(10);37 utility::Vector gsl_vec(10); 38 38 std::vector<double> data; 39 39 for (unsigned int i=0; i<10; i++){ -
trunk/test/svd_test.cc
r1000 r1120 28 28 #include "yat/utility/matrix.h" 29 29 #include "yat/utility/SVD.h" 30 #include "yat/utility/ vector.h"30 #include "yat/utility/Vector.h" 31 31 32 32 using namespace theplu::yat; … … 56 56 utility::SVD svd(A); 57 57 svd.decompose(algo); 58 theplu::yat::utility:: vector s(svd.s());58 theplu::yat::utility::Vector s(svd.s()); 59 59 utility::matrix S(s.size(),s.size()); 60 60 for (size_t i=0; i<s.size(); ++i) -
trunk/test/svm_test.cc
r1100 r1120 32 32 #include "yat/classifier/Target.h" 33 33 #include "yat/utility/matrix.h" 34 #include "yat/utility/ vector.h"34 #include "yat/utility/Vector.h" 35 35 36 36 #include <cassert> … … 126 126 127 127 is.open("data/nm_alpha_linear_matlab.txt"); 128 theplu::yat::utility:: vector alpha_matlab(is);128 theplu::yat::utility::Vector alpha_matlab(is); 129 129 is.close(); 130 130 … … 133 133 svm.train(kv, target); 134 134 135 theplu::yat::utility:: vector alpha = svm.alpha();135 theplu::yat::utility::Vector alpha = svm.alpha(); 136 136 137 137 // Comparing alpha to alpha_matlab 138 theplu::yat::utility:: vector diff_alpha(alpha);138 theplu::yat::utility::Vector diff_alpha(alpha); 139 139 diff_alpha-=alpha_matlab; 140 140 if (diff_alpha*diff_alpha> 1e-10 ){ … … 144 144 145 145 // Comparing output to target 146 theplu::yat::utility:: vector output(svm.output());146 theplu::yat::utility::Vector output(svm.output()); 147 147 double slack = 0; 148 148 for (unsigned int i=0; i<target.size(); i++){ -
trunk/test/ttest_test.cc
r1000 r1120 25 25 #include "yat/statistics/tTest.h" 26 26 #include "yat/statistics/utility.h" 27 #include "yat/utility/ vector.h"27 #include "yat/utility/Vector.h" 28 28 29 29 #include <cmath> … … 47 47 48 48 *error << "testing ttest" << std::endl; 49 utility:: vector value(31);49 utility::Vector value(31); 50 50 std::vector<std::string> label(31,"positive"); 51 51 for (size_t i=0; i<16; i++) -
trunk/test/vector_test.cc
r1056 r1120 28 28 #include "yat/utility/FileUtil.h" 29 29 #include "yat/utility/utility.h" 30 #include "yat/utility/ vector.h"30 #include "yat/utility/Vector.h" 31 31 #include "yat/utility/VectorConstView.h" 32 32 #include "yat/utility/VectorView.h" … … 59 59 bool ok = true; 60 60 61 utility:: vector vec(12);61 utility::Vector vec(12); 62 62 for (size_t i=0; i<vec.size(); i++) 63 63 vec(i)=i; … … 91 91 { 92 92 *message << "const view implementation" << std::endl; 93 const utility:: vector vv(10,3.0);93 const utility::Vector vv(10,3.0); 94 94 utility::VectorConstView vview(vv,0,5,1); 95 // const utility:: vector vview(vv,0,5,1); // this is the proper line96 utility:: vector vv2(5,2.0);95 // const utility::Vector vview(vv,0,5,1); // this is the proper line 96 utility::Vector vv2(5,2.0); 97 97 vv2.mul(vview); // should work even without const since const arg passing 98 98 vv2.div(vview); // should work even without const since const arg passing … … 104 104 { 105 105 *message << "copy constructor" << std::endl; 106 utility:: vector vec2(vec);106 utility::Vector vec2(vec); 107 107 ok &= (vec.size()==vec2.size()); 108 108 ok &= (vec2==vec); … … 115 115 { 116 116 *message << "copy contructor on view" << std::endl; 117 utility:: vector vec3(vec_view);117 utility::Vector vec3(vec_view); 118 118 ok &= (vec_view.size()==vec3.size()); 119 119 ok &= (vec3 == vec_view); … … 132 132 bool exception_happens=false; 133 133 try { 134 utility:: vector v(vec_view.size()+1,0.0);134 utility::Vector v(vec_view.size()+1,0.0); 135 135 vec_view=v; 136 136 } catch (utility::GSL_error& err) { … … 151 151 vec[3]=vec[4]=vec[5]=13; 152 152 utility::VectorView vec_view(vec,3,3,1); 153 utility:: vector vec2(3,123.0);153 utility::Vector vec2(3,123.0); 154 154 vec_view=vec2; 155 155 if (vec[3]!=vec_view[0] || vec[4]!=vec_view[1] || vec[5]!=vec_view[2]){ … … 164 164 bool this_ok=true; 165 165 *message << "\tcloning normal vector" << std::endl; 166 utility:: vector vec2(3,123.0);166 utility::Vector vec2(3,123.0); 167 167 vec2 = vec; 168 168 if (vec.size()!=vec2.size()) … … 211 211 std::ifstream data_stream3(data3.c_str()); 212 212 std::ifstream data_stream4(data4.c_str()); 213 utility:: vector vec1(data_stream1);213 utility::Vector vec1(data_stream1); 214 214 ok &= (vec1.size()==9); 215 vec1=utility:: vector(data_stream2);215 vec1=utility::Vector(data_stream2); 216 216 ok &= (vec1.size()==9); 217 utility:: vector vec2(data_stream3);217 utility::Vector vec2(data_stream3); 218 218 ok &= (vec2.size()==12); 219 vec2=utility:: vector(data_stream4);219 vec2=utility::Vector(data_stream4); 220 220 ok &= (vec2.size()==12); 221 221 } catch (utility::IO_error& err) { … … 231 231 std::stringstream s; 232 232 s << vec; 233 utility:: vector vec2(s);233 utility::Vector vec2(s); 234 234 ok &= (vec==vec2); 235 235 } … … 244 244 check_file_access(data5); 245 245 std::ifstream data_stream5(data5.c_str()); 246 utility:: vector dummy(data_stream5); // this will give an exception246 utility::Vector dummy(data_stream5); // this will give an exception 247 247 } catch (utility::IO_error& err) { 248 248 *message << err.what() << std::endl; … … 253 253 check_file_access(data); 254 254 std::ifstream data_stream(data.c_str()); 255 utility:: vector dummy(data_stream); // this will give an exception255 utility::Vector dummy(data_stream); // this will give an exception 256 256 } catch (utility::IO_error& err) { 257 257 *message << err.what() << std::endl; … … 265 265 check_file_access(data); 266 266 std::ifstream data_stream(data.c_str()); 267 vec=utility:: vector(data_stream); // this will give an exception267 vec=utility::Vector(data_stream); // this will give an exception 268 268 } catch (utility::IO_error& err) { 269 269 *message << err.what() << std::endl; … … 277 277 std::string data3("data/vector3.data"); 278 278 std::ifstream data_stream3(data3.c_str()); 279 utility:: vector vec3(data_stream3);279 utility::Vector vec3(data_stream3); 280 280 std::vector<size_t> dummy; 281 281 dummy.push_back(100); // To make sure it works starting with a non-empty vector … … 316 316 // test for ticket:285 317 317 { 318 theplu::yat::utility:: vector vec(10);319 theplu::yat::utility:: vector vec2;318 theplu::yat::utility::Vector vec(10); 319 theplu::yat::utility::Vector vec2; 320 320 vec2 = vec; 321 321 } -
trunk/yat/classifier/DataLookup1D.cc
r1080 r1120 29 29 30 30 #include "yat/utility/matrix.h" 31 #include "yat/utility/ vector.h"31 #include "yat/utility/Vector.h" 32 32 33 33 #include <cassert> -
trunk/yat/classifier/IGP.h
r1050 r1120 28 28 #include "MatrixLookup.h" 29 29 #include "Target.h" 30 #include "yat/utility/ vector.h"30 #include "yat/utility/Vector.h" 31 31 #include "yat/utility/yat_assert.h" 32 32 … … 65 65 /// @return the IGP score for each class as elements in a vector. 66 66 /// 67 const utility:: vector& score(void) const;67 const utility::Vector& score(void) const; 68 68 69 69 70 70 private: 71 utility:: vector igp_;71 utility::Vector igp_; 72 72 Distance distance_; 73 73 … … 86 86 87 87 // Calculate IGP for each class 88 igp_ = utility:: vector(target_.nof_classes());88 igp_ = utility::Vector(target_.nof_classes()); 89 89 90 90 for(u_int i=0; i<target_.size(); i++) { … … 116 116 117 117 template <typename Distance> 118 const utility:: vector& IGP<Distance>::score(void) const118 const utility::Vector& IGP<Distance>::score(void) const 119 119 { 120 120 return igp_; -
trunk/yat/classifier/NBC.cc
r1042 r1120 101 101 assert(i<centroids_.rows()); 102 102 assert(j<centroids_.columns()); 103 centroids_(i,j) = aver[j].mean();104 103 assert(i<sigma2_.rows()); 105 104 assert(j<sigma2_.columns()); 106 if (aver[j].n()>1) 105 if (aver[j].n()>1){ 107 106 sigma2_(i,j) = aver[j].variance(); 108 else 107 centroids_(i,j) = aver[j].mean(); 108 } 109 else { 109 110 sigma2_(i,j) = std::numeric_limits<double>::quiet_NaN(); 111 centroids_(i,j) = std::numeric_limits<double>::quiet_NaN(); 112 } 110 113 } 111 114 } … … 125 128 assert(i<sigma2_.rows()); 126 129 assert(j<sigma2_.columns()); 127 if (aver[j].n()>1) 130 if (aver[j].n()>1){ 128 131 sigma2_(i,j) = aver[j].variance(); 129 else 132 centroids_(i,j) = aver[j].mean(); 133 } 134 else { 130 135 sigma2_(i,j) = std::numeric_limits<double>::quiet_NaN(); 136 centroids_(i,j) = std::numeric_limits<double>::quiet_NaN(); 137 } 131 138 } 132 139 } … … 142 149 assert(x.rows()==sigma2_.rows()); 143 150 assert(x.rows()==centroids_.rows()); 144 145 151 146 152 … … 192 198 // problems when calculating P = exp(- -lnP), we centralize matrix 193 199 // by adding a constant. 194 double m=0; 195 for (size_t i=0; i<prediction.rows(); ++i) 196 for (size_t j=0; j<prediction.columns(); ++j) 197 m+=prediction(i,j); 198 prediction -= m/prediction.rows()/prediction.columns(); 200 statistics::Averager a; 201 add(a, prediction.begin(), prediction.end()); 202 prediction -= a.mean(); 199 203 200 204 // exponentiate -
trunk/yat/classifier/NCC.h
r1115 r1120 38 38 #include "yat/statistics/AveragerWeighted.h" 39 39 #include "yat/utility/matrix.h" 40 #include "yat/utility/ vector.h"40 #include "yat/utility/Vector.h" 41 41 #include "yat/utility/stl_utility.h" 42 42 #include "yat/utility/yat_assert.h" -
trunk/yat/classifier/SVM.cc
r1108 r1120 30 30 #include "yat/statistics/Averager.h" 31 31 #include "yat/utility/matrix.h" 32 #include "yat/utility/ vector.h"32 #include "yat/utility/Vector.h" 33 33 34 34 #include <algorithm> … … 76 76 77 77 78 const utility:: vector& SVM::alpha(void) const78 const utility::Vector& SVM::alpha(void) const 79 79 { 80 80 return alpha_; … … 134 134 135 135 136 const theplu::yat::utility::vector& SVM::output(void) const136 const utility::Vector& SVM::output(void) const 137 137 { 138 138 return output_; … … 186 186 target_ = targ; 187 187 188 alpha_ = utility:: vector(targ.size(), 0.0);189 output_ = utility:: vector(targ.size(), 0.0);188 alpha_ = utility::Vector(targ.size(), 0.0); 189 output_ = utility::Vector(targ.size(), 0.0); 190 190 // initializing variables for optimization 191 191 assert(target_.size()==kernel_->rows()); … … 193 193 194 194 sample_.init(alpha_,tolerance_); 195 utility:: vector E(target_.size(),0);195 utility::Vector E(target_.size(),0); 196 196 for (size_t i=0; i<E.size(); i++) { 197 197 for (size_t j=0; j<E.size(); j++) … … 273 273 274 274 275 bool SVM::choose(const theplu::yat::utility:: vector& E)275 bool SVM::choose(const theplu::yat::utility::Vector& E) 276 276 { 277 277 // First check for violation among SVs -
trunk/yat/classifier/SVM.h
r1108 r1120 29 29 #include "SVindex.h" 30 30 #include "Target.h" 31 #include "yat/utility/ vector.h"31 #include "yat/utility/Vector.h" 32 32 33 33 #include <utility> … … 81 81 /// @return \f$ \alpha \f$ 82 82 /// 83 const utility:: vector& alpha(void) const;83 const utility::Vector& alpha(void) const; 84 84 85 85 /// … … 117 117 @return output 118 118 */ 119 const theplu::yat::utility:: vector& output(void) const;119 const theplu::yat::utility::Vector& output(void) const; 120 120 121 121 /** … … 215 215 /// can be found 216 216 /// 217 bool choose(const theplu::yat::utility:: vector&);217 bool choose(const theplu::yat::utility::Vector&); 218 218 219 219 /// … … 227 227 int target(size_t i) const; 228 228 229 utility:: vector alpha_;229 utility::Vector alpha_; 230 230 double bias_; 231 231 double C_inverse_; … … 233 233 double margin_; 234 234 unsigned long int max_epochs_; 235 utility:: vector output_;235 utility::Vector output_; 236 236 SVindex sample_; 237 237 Target target_; -
trunk/yat/classifier/SVindex.cc
r1100 r1120 27 27 #include "yat/statistics/Averager.h" 28 28 #include "yat/utility/matrix.h" 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 #include <algorithm> … … 65 65 } 66 66 67 void SVindex::init(const utility:: vector& alpha, const double tol)67 void SVindex::init(const utility::Vector& alpha, const double tol) 68 68 { 69 69 nof_sv_=0; -
trunk/yat/classifier/SVindex.h
r1000 r1120 32 32 33 33 namespace utility { 34 class vector;34 class Vector; 35 35 } 36 36 … … 59 59 60 60 /// synch the object against alpha 61 void init(const utility:: vector& alpha, const double);61 void init(const utility::Vector& alpha, const double); 62 62 63 63 /// @return nof support vectors -
trunk/yat/classifier/utility.cc
r1009 r1120 26 26 #include "DataLookup1D.h" 27 27 #include "DataLookupWeighted1D.h" 28 #include "yat/utility/ vector.h"28 #include "yat/utility/Vector.h" 29 29 30 30 … … 33 33 namespace classifier { 34 34 35 void convert(const DataLookup1D& lookup, utility:: vector& vector)35 void convert(const DataLookup1D& lookup, utility::Vector& vector) 36 36 { 37 vector = utility:: vector(lookup.size());37 vector = utility::Vector(lookup.size()); 38 38 for(u_int i=0; i<lookup.size(); i++) 39 39 vector(i)=lookup(i); 40 40 } 41 41 42 void convert(const DataLookupWeighted1D& lookup, utility:: vector& value,43 utility:: vector& weight)42 void convert(const DataLookupWeighted1D& lookup, utility::Vector& value, 43 utility::Vector& weight) 44 44 { 45 45 46 value = utility:: vector(lookup.size());47 weight = utility:: vector(lookup.size());46 value = utility::Vector(lookup.size()); 47 weight = utility::Vector(lookup.size()); 48 48 for(u_int i=0; i<lookup.size(); i++){ 49 49 value(i)=lookup.data(i); -
trunk/yat/classifier/utility.h
r1000 r1120 30 30 31 31 namespace utility { 32 class vector;32 class Vector; 33 33 } 34 34 … … 41 41 /// Converts a DataLookup1D to a utility::vector 42 42 /// 43 void convert(const DataLookup1D&, utility:: vector&);43 void convert(const DataLookup1D&, utility::Vector&); 44 44 45 45 /// 46 46 /// Converts a DataLookupWeighted1D to two utility::vector 47 47 /// 48 void convert(const DataLookupWeighted1D&, utility:: vector& value,49 utility:: vector& weight);48 void convert(const DataLookupWeighted1D&, utility::Vector& value, 49 utility::Vector& weight); 50 50 51 51 }}} // of namespace classifier, yat, and theplu -
trunk/yat/regression/LinearWeighted.cc
r1043 r1120 26 26 #include "LinearWeighted.h" 27 27 #include "yat/statistics/AveragerPairWeighted.h" 28 #include "yat/utility/ vector.h"28 #include "yat/utility/Vector.h" 29 29 30 30 #include <cassert> … … 75 75 // want. 76 76 ap_.reset(); 77 yat::utility:: vector dummy(x.size(), 1.0);77 yat::utility::Vector dummy(x.size(), 1.0); 78 78 add(ap_, x.begin(), x.end(), y.begin(),dummy.begin(),w.begin()); 79 79 -
trunk/yat/regression/Local.cc
r1049 r1120 26 26 #include "Kernel.h" 27 27 #include "OneDimensionalWeighted.h" 28 #include "yat/utility/ vector.h"28 #include "yat/utility/Vector.h" 29 29 #include "yat/utility/VectorView.h" 30 30 … … 68 68 69 69 size_t nof_fits=data_.size()/step_size; 70 x_ = utility:: vector(nof_fits);71 y_predicted_ = utility:: vector(x_.size());72 y_err_ = utility:: vector(x_.size());70 x_ = utility::Vector(nof_fits); 71 y_predicted_ = utility::Vector(x_.size()); 72 y_err_ = utility::Vector(x_.size()); 73 73 sort(data_.begin(), data_.end()); 74 74 75 75 // coying data to 2 utility vectors ONCE to use views from 76 utility:: vector x(data_.size());77 utility:: vector y(data_.size());76 utility::Vector x(data_.size()); 77 utility::Vector y(data_.size()); 78 78 for (size_t j=0; j<x.size(); j++){ 79 79 x(j)=data_[j].first; … … 115 115 116 116 // calculating weights 117 utility:: vector w(max_index-min_index+1);117 utility::Vector w(max_index-min_index+1); 118 118 for (size_t j=0; j<w.size(); j++) 119 119 w(j) = (*kernel_)( (x_local(j)- x_mid)/width ); … … 128 128 } 129 129 130 const utility:: vector& Local::x(void) const130 const utility::Vector& Local::x(void) const 131 131 { 132 132 return x_; 133 133 } 134 134 135 const utility:: vector& Local::y_predicted(void) const135 const utility::Vector& Local::y_predicted(void) const 136 136 { 137 137 return y_predicted_; 138 138 } 139 139 140 const utility:: vector& Local::y_err(void) const140 const utility::Vector& Local::y_err(void) const 141 141 { 142 142 return y_err_; -
trunk/yat/regression/Local.h
r1000 r1120 27 27 */ 28 28 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 #include <iostream> … … 78 78 /// @return x-values where fitting was performed. 79 79 /// 80 const utility:: vector& x(void) const;80 const utility::Vector& x(void) const; 81 81 82 82 /// 83 83 /// Function returning predicted values 84 84 /// 85 const utility:: vector& y_predicted(void) const;85 const utility::Vector& y_predicted(void) const; 86 86 87 87 /// 88 88 /// Function returning error of predictions 89 89 /// 90 const utility:: vector& y_err(void) const;90 const utility::Vector& y_err(void) const; 91 91 92 92 private: … … 99 99 Kernel* kernel_; 100 100 OneDimensionalWeighted* regressor_; 101 utility:: vector x_;102 utility:: vector y_predicted_;103 utility:: vector y_err_;101 utility::Vector x_; 102 utility::Vector y_predicted_; 103 utility::Vector y_err_; 104 104 }; 105 105 -
trunk/yat/regression/MultiDimensional.cc
r1098 r1120 27 27 #include "yat/utility/matrix.h" 28 28 #include "yat/utility/VectorBase.h" 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 #include <cassert> … … 60 60 assert(x.rows()==y.size()); 61 61 covariance_.resize(x.columns(),x.columns()); 62 fit_parameters_ = utility:: vector(x.columns());62 fit_parameters_ = utility::Vector(x.columns()); 63 63 if (work_) 64 64 gsl_multifit_linear_free(work_); … … 76 76 } 77 77 78 const utility:: vector& MultiDimensional::fit_parameters(void) const78 const utility::Vector& MultiDimensional::fit_parameters(void) const 79 79 { 80 80 return fit_parameters_; -
trunk/yat/regression/MultiDimensional.h
r1021 r1120 69 69 /// @return parameters of the model 70 70 /// 71 const utility:: vector& fit_parameters(void) const;71 const utility::Vector& fit_parameters(void) const; 72 72 73 73 /** … … 96 96 double s2_; 97 97 utility::matrix covariance_; 98 utility:: vector fit_parameters_;98 utility::Vector fit_parameters_; 99 99 gsl_multifit_linear_workspace* work_; 100 100 -
trunk/yat/regression/MultiDimensionalWeighted.cc
r1098 r1120 25 25 #include "yat/statistics/AveragerWeighted.h" 26 26 #include "yat/utility/matrix.h" 27 #include "yat/utility/ vector.h"27 #include "yat/utility/Vector.h" 28 28 29 29 #include <cassert> … … 59 59 60 60 covariance_.resize(x.columns(),x.columns()); 61 fit_parameters_ = utility:: vector(x.columns());61 fit_parameters_ = utility::Vector(x.columns()); 62 62 if (work_) 63 63 gsl_multifit_linear_free(work_); … … 80 80 81 81 82 const utility:: vector& MultiDimensionalWeighted::fit_parameters(void) const82 const utility::Vector& MultiDimensionalWeighted::fit_parameters(void) const 83 83 { 84 84 return fit_parameters_; -
trunk/yat/regression/MultiDimensionalWeighted.h
r1022 r1120 26 26 27 27 #include "yat/utility/matrix.h" 28 #include "yat/utility/ vector.h"28 #include "yat/utility/Vector.h" 29 29 30 30 #include <gsl/gsl_multifit.h> … … 85 85 /// @return parameters of fitted model 86 86 /// 87 const utility:: vector& fit_parameters(void) const;87 const utility::Vector& fit_parameters(void) const; 88 88 89 89 /// … … 95 95 double chisquare_; 96 96 utility::matrix covariance_; 97 utility:: vector fit_parameters_;97 utility::Vector fit_parameters_; 98 98 double s2_; 99 99 gsl_multifit_linear_workspace* work_; -
trunk/yat/regression/NaiveWeighted.cc
r1043 r1120 27 27 #include "OneDimensional.h" 28 28 #include "yat/statistics/AveragerWeighted.h" 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 #include <cassert> … … 51 51 assert(y.size()==w.size()); 52 52 ap_.reset(); 53 utility:: vector dummy(x.size(),1.0);53 utility::Vector dummy(x.size(),1.0); 54 54 add(ap_, x.begin(), x.end(), y.begin(),dummy.begin(), w.begin()); 55 55 chisq_ = ap_.y_averager().sum_xx_centered(); -
trunk/yat/regression/Polynomial.cc
r1043 r1120 62 62 63 63 64 const utility:: vector& Polynomial::fit_parameters(void) const64 const utility::Vector& Polynomial::fit_parameters(void) const 65 65 { 66 66 return md_.fit_parameters(); … … 70 70 double Polynomial::predict(const double x) const 71 71 { 72 utility:: vector vec(power_+1,1);72 utility::Vector vec(power_+1,1); 73 73 for (size_t i=1; i<=power_; ++i) 74 74 vec(i) = vec(i-1)*x; … … 85 85 double Polynomial::standard_error2(const double x) const 86 86 { 87 utility:: vector vec(power_+1,1);87 utility::Vector vec(power_+1,1); 88 88 for (size_t i=1; i<=power_; ++i) 89 89 vec(i) = vec(i-1)*x; -
trunk/yat/regression/Polynomial.h
r1019 r1120 72 72 /// @see MultiDimensional 73 73 /// 74 const utility:: vector& fit_parameters(void) const;74 const utility::Vector& fit_parameters(void) const; 75 75 76 76 /// -
trunk/yat/regression/PolynomialWeighted.cc
r1043 r1120 25 25 #include "PolynomialWeighted.h" 26 26 #include "yat/utility/matrix.h" 27 #include "yat/utility/ vector.h"27 #include "yat/utility/Vector.h" 28 28 29 29 #include <cassert> … … 52 52 // product wx*wy, so we can send in w and a dummie to get what we 53 53 // want. 54 utility:: vector dummy(x.size(), 1.0);54 utility::Vector dummy(x.size(), 1.0); 55 55 add(ap_,x.begin(), x.end(),y.begin(),dummy.begin(),w.begin()); 56 56 utility::matrix X=utility::matrix(x.size(),power_+1,1); … … 63 63 64 64 65 const utility:: vector& PolynomialWeighted::fit_parameters(void) const65 const utility::Vector& PolynomialWeighted::fit_parameters(void) const 66 66 { 67 67 return md_.fit_parameters(); … … 76 76 double PolynomialWeighted::predict(const double x) const 77 77 { 78 utility:: vector vec(power_+1,1);78 utility::Vector vec(power_+1,1); 79 79 for (size_t i=1; i<=power_; ++i) 80 80 vec(i) = vec(i-1)*x; … … 84 84 double PolynomialWeighted::standard_error2(const double x) const 85 85 { 86 utility:: vector vec(power_+1,1);86 utility::Vector vec(power_+1,1); 87 87 for (size_t i=1; i<=power_; ++i) 88 88 vec(i) = vec(i-1)*x; -
trunk/yat/regression/PolynomialWeighted.h
r1020 r1120 27 27 #include "OneDimensionalWeighted.h" 28 28 #include "MultiDimensionalWeighted.h" 29 #include "yat/utility/ vector.h"29 #include "yat/utility/Vector.h" 30 30 31 31 namespace theplu { … … 65 65 /// @see MultiDimensional 66 66 /// 67 const utility:: vector& fit_parameters(void) const;67 const utility::Vector& fit_parameters(void) const; 68 68 69 69 /// -
trunk/yat/statistics/FoldChange.cc
r1023 r1120 30 30 #include "yat/classifier/DataLookupWeighted1D.h" 31 31 #include "yat/classifier/Target.h" 32 #include "yat/utility/ vector.h"32 #include "yat/utility/VectorBase.h" 33 33 34 34 namespace theplu { -
trunk/yat/statistics/ROC.cc
r1000 r1120 29 29 #include "yat/classifier/Target.h" 30 30 #include "yat/utility/stl_utility.h" 31 #include "yat/utility/ vector.h"31 #include "yat/utility/VectorBase.h" 32 32 33 33 #include <gsl/gsl_cdf.h> -
trunk/yat/statistics/Score.cc
r1000 r1120 30 30 #include "yat/classifier/Target.h" 31 31 #include "yat/classifier/utility.h" 32 #include "yat/utility/ vector.h"32 #include "yat/utility/Vector.h" 33 33 34 34 #include <cassert> … … 56 56 { 57 57 assert(target.size()==value.size()); 58 utility:: vector a(value.size());58 utility::Vector a(value.size()); 59 59 classifier::convert(value,a); 60 60 return score(target,a); … … 66 66 { 67 67 assert(target.size()==value.size()); 68 utility:: vector a(value.size());69 utility:: vector b(value.size());68 utility::Vector a(value.size()); 69 utility::Vector b(value.size()); 70 70 classifier::convert(value,a,b); 71 71 return score(target,a,b); … … 77 77 const classifier::DataLookup1D& weight) const 78 78 { 79 utility:: vector a(value.size());79 utility::Vector a(value.size()); 80 80 classifier::convert(value,a); 81 utility:: vector b(value.size());81 utility::Vector b(value.size()); 82 82 classifier::convert(weight,a); 83 83 return score(target,a,b); -
trunk/yat/utility/Alignment.cc
r1000 r1120 26 26 #include "Alignment.h" 27 27 #include "matrix.h" 28 #include " yat/utility/stl_utility.h"28 #include "stl_utility.h" 29 29 30 30 #include <algorithm> -
trunk/yat/utility/Makefile.am
r1110 r1120 29 29 matrix.cc NNI.cc Option.cc OptionFile.cc OptionInFile.cc OptionOutFile.cc \ 30 30 OptionHelp.cc OptionSwitch.cc \ 31 PCA.cc stl_utility.cc SVD.cc TypeInfo.cc utility.cc vector.cc \31 PCA.cc stl_utility.cc SVD.cc TypeInfo.cc utility.cc Vector.cc \ 32 32 VectorBase.cc VectorConstView.cc VectorMutable.cc VectorView.cc WeNNI.cc 33 33 … … 42 42 OptionHelp.h OptionSwitch.h \ 43 43 PCA.h SmartPtr.h stl_utility.h StrideIterator.h \ 44 SVD.h TypeInfo.h utility.h vector.h \44 SVD.h TypeInfo.h utility.h Vector.h \ 45 45 VectorBase.h VectorConstView.h VectorMutable.h VectorView.h \ 46 46 WeNNI.h yat_assert.h -
trunk/yat/utility/PCA.cc
r1098 r1120 47 47 48 48 49 const utility:: vector& PCA::eigenvalues(void) const49 const utility::Vector& PCA::eigenvalues(void) const 50 50 { 51 51 return eigenvalues_; … … 147 147 utility::matrix projs( Ncol, Ncol ); 148 148 149 utility:: vector temp(samples.rows());149 utility::Vector temp(samples.rows()); 150 150 for( size_t j = 0; j < Ncol; ++j ) { 151 151 for (size_t i=0; i<Ncol; ++i ) 152 152 temp(i) = samples(i,j); 153 utility:: vector centered( Nrow );153 utility::Vector centered( Nrow ); 154 154 for( size_t i = 0; i < Nrow; ++i ) 155 155 centered(i) = temp(i) - meanvalues_(i); 156 utility:: vector proj( eigenvectors_ * centered );156 utility::Vector proj( eigenvectors_ * centered ); 157 157 for( size_t i = 0; i < Ncol; ++i ) 158 158 projs(i,j)=proj(i); … … 191 191 void PCA::row_center(utility::matrix& A_center) 192 192 { 193 meanvalues_ = vector(A_.rows());194 utility:: vector A_row_sum(A_.rows());193 meanvalues_ = Vector(A_.rows()); 194 utility::Vector A_row_sum(A_.rows()); 195 195 for (size_t i=0; i<A_row_sum.size(); ++i){ 196 196 A_row_sum(i) = sum(A_.row_const_view(i)); -
trunk/yat/utility/PCA.h
r1000 r1120 30 30 31 31 #include "matrix.h" 32 #include " vector.h"32 #include "Vector.h" 33 33 34 34 namespace theplu { … … 73 73 eigenvalues. 74 74 */ 75 const utility:: vector& eigenvalues(void) const;75 const utility::Vector& eigenvalues(void) const; 76 76 77 77 /** … … 119 119 120 120 utility::matrix A_; 121 utility:: vector eigenvalues_;121 utility::Vector eigenvalues_; 122 122 utility::matrix eigenvectors_; 123 utility:: vector meanvalues_;123 utility::Vector meanvalues_; 124 124 }; 125 125 -
trunk/yat/utility/SVD.cc
r1016 r1120 26 26 27 27 #include "SVD.h" 28 #include " vector.h"28 #include "Vector.h" 29 29 #include "VectorBase.h" 30 30 … … 72 72 int SVD::golub_reinsch(void) 73 73 { 74 utility:: vector w(U_.columns());74 utility::Vector w(U_.columns()); 75 75 return gsl_linalg_SV_decomp(U_.gsl_matrix_p(), V_.gsl_matrix_p(), 76 76 s_.gsl_vector_p(), w.gsl_vector_p()); … … 87 87 int SVD::modified_golub_reinsch(void) 88 88 { 89 utility:: vector w(U_.columns());89 utility::Vector w(U_.columns()); 90 90 utility::matrix X(U_.columns(),U_.columns()); 91 91 return gsl_linalg_SV_decomp_mod(U_.gsl_matrix_p(), X.gsl_matrix_p(), … … 95 95 96 96 97 const utility:: vector& SVD::s(void) const97 const utility::Vector& SVD::s(void) const 98 98 { 99 99 return s_; … … 101 101 102 102 103 void SVD::solve(const utility::VectorBase& b, utility:: vector& x)103 void SVD::solve(const utility::VectorBase& b, utility::Vector& x) 104 104 { 105 105 int status=gsl_linalg_SV_solve(U_.gsl_matrix_p(), V_.gsl_matrix_p(), -
trunk/yat/utility/SVD.h
r1016 r1120 30 30 31 31 #include "matrix.h" 32 #include " vector.h"32 #include "Vector.h" 33 33 34 34 #include <gsl/gsl_linalg.h> … … 103 103 is undefined. 104 104 */ 105 const utility:: vector& s(void) const;105 const utility::Vector& s(void) const; 106 106 107 107 /** … … 114 114 \throw GSL_error if the underlying GSL function fails. 115 115 */ 116 void solve(const utility::VectorBase& b, utility:: vector& x);116 void solve(const utility::VectorBase& b, utility::Vector& x); 117 117 118 118 /** … … 159 159 160 160 utility::matrix U_, V_; 161 utility:: vector s_;161 utility::Vector s_; 162 162 }; 163 163 -
trunk/yat/utility/Vector.cc
r1118 r1120 25 25 */ 26 26 27 #include " vector.h"27 #include "Vector.h" 28 28 #include "matrix.h" 29 29 #include "utility.h" … … 43 43 44 44 45 vector::vector(void)45 Vector::Vector(void) 46 46 : VectorMutable() 47 47 { … … 49 49 50 50 51 vector::vector(size_t n, double init_value)51 Vector::Vector(size_t n, double init_value) 52 52 : VectorMutable(gsl_vector_alloc(n)) 53 53 { 54 54 if (!vec_) 55 throw utility::GSL_error(" vector::vector failed to allocate memory");55 throw utility::GSL_error("Vector::Vector failed to allocate memory"); 56 56 assert(const_vec_); 57 57 all(init_value); … … 59 59 60 60 61 vector::vector(const vector& other)61 Vector::Vector(const Vector& other) 62 62 : VectorMutable(create_gsl_vector_copy(other)) 63 63 { … … 65 65 66 66 67 vector::vector(const VectorBase& other)67 Vector::Vector(const VectorBase& other) 68 68 : VectorMutable(create_gsl_vector_copy(other)) 69 69 { … … 71 71 72 72 73 vector::vector(std::istream& is, char sep)73 Vector::Vector(std::istream& is, char sep) 74 74 throw (utility::IO_error, std::exception) 75 75 : VectorMutable() … … 117 117 else if (nof_rows && (nof_columns>1)) { 118 118 std::ostringstream s; 119 s << " vector::vector(std::istream&) data file error:\n"119 s << "Vector::Vector(std::istream&) data file error:\n" 120 120 << " File has inconsistent number of rows (" << nof_rows 121 121 << ") and columns (" << nof_columns 122 << ").\n Expected a row or a column vector.";122 << ").\n Expected a row or a column Vector."; 123 123 throw utility::IO_error(s.str()); 124 124 } 125 125 else if (v.size()!=nof_columns) { 126 126 std::ostringstream s; 127 s << " vector::vector(std::istream&) data file error:\n"127 s << "Vector::Vector(std::istream&) data file error:\n" 128 128 << " Line " << nof_rows << " has " << v.size() 129 129 << " columns; expected " << nof_columns << " column."; … … 138 138 vec_ = gsl_vector_alloc(nof_rows*nof_columns); 139 139 if (!vec_) 140 throw utility::GSL_error(" vector::vector failed to allocate memory");140 throw utility::GSL_error("Vector::Vector failed to allocate memory"); 141 141 size_t n=0; 142 142 // if gsl error handler disabled, out of bounds index will not … … 149 149 150 150 151 vector::~vector(void)151 Vector::~Vector(void) 152 152 { 153 153 delete_allocated_memory(); … … 155 155 156 156 157 const vector& vector::assign(const VectorBase& other)157 const Vector& Vector::assign(const VectorBase& other) 158 158 { 159 159 delete_allocated_memory(); … … 162 162 vec_ = gsl_vector_alloc(other.size()); 163 163 if (!vec_) 164 throw utility::GSL_error(" vector failed to allocate memory");164 throw utility::GSL_error("Vector failed to allocate memory"); 165 165 gsl_vector_memcpy(vec_,other.gsl_vector_p()); 166 166 const_vec_ = vec_; … … 170 170 171 171 172 gsl_vector* vector::create_gsl_vector_copy(const VectorBase& other) const172 gsl_vector* Vector::create_gsl_vector_copy(const VectorBase& other) const 173 173 { 174 174 gsl_vector* vec = gsl_vector_alloc(other.size()); 175 175 if (!vec) 176 throw utility::GSL_error(" vector::create_gsl_vector_copy failed to allocate memory");176 throw utility::GSL_error("Vector::create_gsl_vector_copy failed to allocate memory"); 177 177 if (gsl_vector_memcpy(vec, other.gsl_vector_p())) 178 throw utility::GSL_error(" vector::create_gsl_matrix_copy dimension mis-match");178 throw utility::GSL_error("Vector::create_gsl_matrix_copy dimension mis-match"); 179 179 return vec; 180 180 } 181 181 182 182 183 void vector::delete_allocated_memory(void)183 void Vector::delete_allocated_memory(void) 184 184 { 185 185 if (vec_) … … 189 189 190 190 191 bool vector::isview(void) const191 bool Vector::isview(void) const 192 192 { 193 193 return false; … … 195 195 196 196 197 void vector::resize(size_t n, double init_value)197 void Vector::resize(size_t n, double init_value) 198 198 { 199 199 delete_allocated_memory(); 200 200 const_vec_ = vec_ = gsl_vector_alloc(n); 201 201 if (!vec_) 202 throw utility::GSL_error(" vector::vector failed to allocate memory");202 throw utility::GSL_error("Vector::Vector failed to allocate memory"); 203 203 all(init_value); 204 204 } 205 205 206 206 207 void set_basis( vector& v, size_t i)207 void set_basis(Vector& v, size_t i) 208 208 { 209 209 assert(v.gsl_vector_p()); … … 212 212 213 213 214 void sort( vector& v)214 void sort(Vector& v) 215 215 { 216 216 assert(v.gsl_vector_p()); … … 219 219 220 220 221 void swap( vector& v, vector& w)221 void swap(Vector& v, Vector& w) 222 222 { 223 223 assert(v.gsl_vector_p()); assert(w.gsl_vector_p()); 224 224 int status=gsl_vector_swap(v.gsl_vector_p(),w.gsl_vector_p()); 225 225 if (status) 226 throw utility::GSL_error(std::string("swap( vector&,vector&)",status));227 } 228 229 230 const vector& vector::operator=( const VectorBase& other )226 throw utility::GSL_error(std::string("swap(Vector&,Vector&)",status)); 227 } 228 229 230 const Vector& Vector::operator=( const VectorBase& other ) 231 231 { 232 232 return assign(other); … … 234 234 235 235 236 const vector& vector::operator=( const vector& other )236 const Vector& Vector::operator=( const Vector& other ) 237 237 { 238 238 return assign(other); -
trunk/yat/utility/Vector.h
r1118 r1120 58 58 */ 59 59 60 class vector : public VectorMutable60 class Vector : public VectorMutable 61 61 { 62 62 public: … … 64 64 \brief The default constructor. 65 65 */ 66 vector(void);66 Vector(void); 67 67 68 68 /** … … 72 72 \throw GSL_error if memory allocation fails. 73 73 */ 74 vector(size_t n, double init_value=0);74 Vector(size_t n, double init_value=0); 75 75 76 76 /** … … 80 80 fails. 81 81 */ 82 vector(const vector& other);82 Vector(const Vector& other); 83 83 84 84 /** … … 88 88 fails. 89 89 */ 90 vector(const VectorBase& other);90 Vector(const VectorBase& other); 91 91 92 92 /** … … 97 97 sep. When delimiter \a sep is used empty elements are stored as 98 98 NaN's (except that empty lines are ignored). The end of input 99 to the vector is at end of file marker.99 to the Vector is at end of file marker. 100 100 101 101 \throw GSL_error if memory allocation fails, IO_error if 102 102 unexpected input is found in the input stream. 103 103 */ 104 explicit vector(std::istream &, char sep='\0')104 explicit Vector(std::istream &, char sep='\0') 105 105 throw(utility::IO_error, std::exception); 106 106 … … 108 108 /// The destructor. 109 109 /// 110 ~ vector(void);110 ~Vector(void); 111 111 112 112 /** … … 116 116 117 117 /** 118 \brief Resize vector118 \brief Resize Vector 119 119 120 120 All elements are set to \a init_value. 121 121 122 122 \note Underlying GSL vector is destroyed and a view into this 123 vector becomes invalid.123 Vector becomes invalid. 124 124 */ 125 125 void resize(size_t, double init_value=0); … … 128 128 \brief The assignment operator. 129 129 130 \note Invalidates views of vector.130 \note Invalidates views of Vector. 131 131 132 \return A const reference to the resulting vector.132 \return A const reference to the resulting Vector. 133 133 */ 134 const vector& operator=(const vector&);134 const Vector& operator=(const Vector&); 135 135 136 136 /** 137 137 \brief The assignment operator. 138 138 139 \note Invalidates views of vector.139 \note Invalidates views of Vector. 140 140 141 \return A const reference to the resulting vector.141 \return A const reference to the resulting Vector. 142 142 */ 143 const vector& operator=(const VectorBase&);143 const Vector& operator=(const VectorBase&); 144 144 145 145 private: 146 const vector& assign(const VectorBase& other);146 const Vector& assign(const VectorBase& other); 147 147 148 148 /** … … 163 163 164 164 /** 165 \brief Swap vector elements by copying.165 \brief Swap Vector elements by copying. 166 166 167 The two vectors must have the same length.167 The two Vectors must have the same length. 168 168 169 \throw GSL_error if vector lengths differs.169 \throw GSL_error if Vector lengths differs. 170 170 */ 171 void swap( vector&, vector&);171 void swap(Vector&, Vector&); 172 172 173 173 }}} // of namespace utility, yat, and theplu -
trunk/yat/utility/VectorBase.cc
r1038 r1120 167 167 168 168 169 bool nan(const VectorBase& templat, vector& flag)169 bool nan(const VectorBase& templat, Vector& flag) 170 170 { 171 171 size_t vsize(templat.size()); 172 flag = vector(vsize, 1.0);172 flag = Vector(vsize, 1.0); 173 173 bool nan=false; 174 174 for (size_t i=0; i<vsize; i++) -
trunk/yat/utility/VectorBase.h
r1046 r1120 45 45 46 46 class matrix; 47 class vector;47 class Vector; 48 48 49 49 /** … … 213 213 \return True if the \a templat VectorBase contains at least one NaN. 214 214 */ 215 bool nan(const VectorBase& templat, vector& flag);215 bool nan(const VectorBase& templat, Vector& flag); 216 216 217 217 /** -
trunk/yat/utility/VectorMutable.h
r1118 r1120 46 46 47 47 class matrix; 48 class vector;48 class Vector; 49 49 50 50 /** -
trunk/yat/utility/VectorView.h
r1118 r1120 44 44 45 45 class matrix; 46 class vector;46 class Vector; 47 47 48 48 /** -
trunk/yat/utility/matrix.cc
r1103 r1120 25 25 */ 26 26 27 #include " matrix.h"28 #include " vector.h"27 #include "yat/utility/matrix.h" 28 #include "yat/utility/Vector.h" 29 29 #include "VectorBase.h" 30 30 #include "VectorConstView.h" … … 576 576 577 577 578 vector operator*(const matrix& m, const VectorBase& v)579 { 580 utility:: vector res(m.rows());578 Vector operator*(const matrix& m, const VectorBase& v) 579 { 580 utility::Vector res(m.rows()); 581 581 for (size_t i=0; i<res.size(); ++i) 582 582 res(i) = VectorConstView(m,i) * v; … … 585 585 586 586 587 vector operator*(const VectorBase& v, const matrix& m)588 { 589 utility:: vector res(m.columns());587 Vector operator*(const VectorBase& v, const matrix& m) 588 { 589 utility::Vector res(m.columns()); 590 590 for (size_t i=0; i<res.size(); ++i) 591 591 res(i) = v * VectorConstView(m,i,false); -
trunk/yat/utility/matrix.h
r1103 r1120 31 31 #include "Exception.h" 32 32 #include "StrideIterator.h" 33 #include " vector.h"33 #include "Vector.h" 34 34 #include "VectorConstView.h" 35 35 #include "VectorView.h" … … 538 538 \brief vector matrix multiplication 539 539 */ 540 vector operator*(const matrix&, const VectorBase&);540 Vector operator*(const matrix&, const VectorBase&); 541 541 542 542 /** 543 543 \brief matrix vector multiplication 544 544 */ 545 vector operator*(const VectorBase&, const matrix&);545 Vector operator*(const VectorBase&, const matrix&); 546 546 547 547 }}} // of namespace utility, yat, and theplu
Note: See TracChangeset
for help on using the changeset viewer.