diff --git a/src/feature_creation/feature_space/FeatureSpace.cpp b/src/feature_creation/feature_space/FeatureSpace.cpp
index f75ae553b063b6ac5456ff61cd19a58ee7f45a51..c39918405fed857a454e322be8ccde11f4fdcb61 100644
--- a/src/feature_creation/feature_space/FeatureSpace.cpp
+++ b/src/feature_creation/feature_space/FeatureSpace.cpp
@@ -107,20 +107,14 @@ void FeatureSpace::initialize_fs()
int n_max_ops = 0;
for(int rr = 0; rr < _max_phi - _n_rung_store; ++rr)
n_max_ops += std::pow(2, rr);
- if((n_max_ops > _phi_0.size()) && (_n_rung_store == 0))
- {
- std::cerr << "WARNING: Setting _n_rung_store to 1 to prevent possible overwrite issues" << std::endl;
- ++_n_rung_store;
- _n_rung_generate -= (_n_rung_generate == 1) && (_n_rung_store + _n_rung_generate > _max_phi);
- }
initialize_fs_output_files();
- project_funcs::set_project_fxn(project_type, _task_sizes.size(), _project, _project_no_omp);
- comp_feats::set_is_valid_fxn(project_type, _cross_cor_max, _n_samp, _is_valid, _is_valid_feat_list);
+ project_funcs::set_project_fxn(_project_type, _task_sizes.size(), _project, _project_no_omp);
+ comp_feats::set_is_valid_fxn(_project_type, _cross_cor_max, _n_samp, _is_valid, _is_valid_feat_list);
set_op_lists();
double start = omp_get_wtime();
- generate_feature_space(prop);
+ generate_feature_space();
_mpi_comm->barrier();
double duration = omp_get_wtime() - start;
if(_mpi_comm->rank() == 0)
diff --git a/src/feature_creation/node/operator_nodes/allowed_operator_nodes/abs_diff/absolute_difference.cpp b/src/feature_creation/node/operator_nodes/allowed_operator_nodes/abs_diff/absolute_difference.cpp
index 7422e108fb2a832757e130eabbe059b4fc577330..e5da83a0611bfbc452a296d94be64f11df4d7dbd 100644
--- a/src/feature_creation/node/operator_nodes/allowed_operator_nodes/abs_diff/absolute_difference.cpp
+++ b/src/feature_creation/node/operator_nodes/allowed_operator_nodes/abs_diff/absolute_difference.cpp
@@ -1,4 +1,5 @@
#include <feature_creation/node/operator_nodes/allowed_operator_nodes/abs_diff/absolute_difference.hpp>
+#include <feature_creation/node/operator_nodes/allowed_operator_nodes/sub/subtract.hpp>
void generateAbsDiffNode(std::vector<node_ptr>& feat_list, node_ptr feat_1, node_ptr feat_2, unsigned long int& feat_ind, double l_bound, double u_bound)
{
diff --git a/src/feature_creation/node/value_storage/nodes_value_containers.hpp b/src/feature_creation/node/value_storage/nodes_value_containers.hpp
index 1e73ab5f094394fd506539a76e05de7e2b7a238f..5bc3930b3718048564fa19058de613a72487f67a 100644
--- a/src/feature_creation/node/value_storage/nodes_value_containers.hpp
+++ b/src/feature_creation/node/value_storage/nodes_value_containers.hpp
@@ -81,7 +81,7 @@ namespace node_value_arrs
* @param n_feat number of features to store
* @param use_temp If true keep the temporary_storage
*/
- void resize_values_arr(int n_dims, unsigned long int n_feat, bool use_temp);
+ void resize_values_arr(int n_dims, int n_feat, bool use_temp);
/**
* @brief Initialize the descriptor matrix
diff --git a/src/mpi_interface/MPI_ops.cpp b/src/mpi_interface/MPI_ops.cpp
index 00c3cbf39980f66b9d243f58280dcdbc3dbd9ac2..4adc7290e73e812a48a538453d032b276d93560b 100644
--- a/src/mpi_interface/MPI_ops.cpp
+++ b/src/mpi_interface/MPI_ops.cpp
@@ -13,16 +13,16 @@ void mpi_reduce_op::set_op(std::string project_type, double cross_cor_max, int n
if(project_type.compare("classification") == 0)
{
if(CROSS_COR_MAX < 0.99999)
- IS_VALID = comp_feats::valid_feature_against_spearman_selected_feat;
+ IS_VALID = comp_feats::valid_feature_against_selected_spearman_mpi_op;
else
- IS_VALID = comp_feats::valid_feature_against_spearman_selected_max_corr_1;
+ IS_VALID = comp_feats::valid_feature_against_selected_spearman_max_corr_1_mpi_op;
}
else
{
if(CROSS_COR_MAX < 0.99999)
- IS_VALID = comp_feats::valid_feature_against_pearson_selected_feat;
+ IS_VALID = comp_feats::valid_feature_against_selected_pearson_mpi_op;
else
- IS_VALID = comp_feats::valid_feature_against_pearson_selected_max_corr_1;
+ IS_VALID = comp_feats::valid_feature_against_selected_pearson_max_corr_1_mpi_op;
}
}
diff --git a/src/utils/compare_features.cpp b/src/utils/compare_features.cpp
index 1475bc2a177ae74f21c9f38f3304415f97282f6a..7e87475e0fcdc1087ff86ca52b95c21593cea39e 100644
--- a/src/utils/compare_features.cpp
+++ b/src/utils/compare_features.cpp
@@ -17,12 +17,12 @@ void comp_feats::set_is_valid_fxn(
if(max_corr < 0.99999)
{
is_valid = valid_feature_against_selected_pearson;
- is_valid_feat_list = valid_feature_against_selected_pearson;
+ is_valid_feat_list = valid_feature_against_selected_pearson_feat_list;
}
else
{
is_valid = valid_feature_against_selected_pearson_max_corr_1;
- is_valid_feat_list = valid_feature_against_selected_pearson_max_corr_1;
+ is_valid_feat_list = valid_feature_against_selected_pearson_max_corr_1_feat_list;
}
}
else
@@ -33,12 +33,12 @@ void comp_feats::set_is_valid_fxn(
if(max_corr < 0.99999)
{
is_valid = valid_feature_against_selected_spearman;
- is_valid_feat_list = valid_feature_against_selected_spearman;
+ is_valid_feat_list = valid_feature_against_selected_spearman_feat_list;
}
else
{
is_valid = valid_feature_against_selected_spearman_max_corr_1;
- is_valid_feat_list = valid_feature_against_selected_spearman_max_corr_1;
+ is_valid_feat_list = valid_feature_against_selected_spearman_max_corr_1_feat_list;
}
}
}
@@ -59,7 +59,7 @@ bool comp_feats::valid_feature_against_selected_pearson_max_corr_1(double* val_p
return true;
}
-bool comp_feats::valid_feature_against_selected_pearson_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
+bool comp_feats::valid_feature_against_selected_pearson_max_corr_1_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
{
double base_val = util_funcs::r(val_ptr, val_ptr, n_samp);
@@ -74,7 +74,7 @@ bool comp_feats::valid_feature_against_selected_pearson_max_corr_1(double* val_p
return true;
}
-bool comp_feats::valid_feature_against_selected_pearson_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
+bool comp_feats::valid_feature_against_selected_pearson_max_corr_1_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
{
double base_val = util_funcs::r(val_ptr, val_ptr, n_samp);
@@ -107,7 +107,7 @@ bool comp_feats::valid_feature_against_selected_pearson(double* val_ptr, int n_s
return is_valid;
}
-bool comp_feats::valid_feature_against_selected_pearson(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
+bool comp_feats::valid_feature_against_selected_pearson_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
{
double base_val = util_funcs::r(val_ptr, val_ptr, n_samp);
@@ -119,7 +119,7 @@ bool comp_feats::valid_feature_against_selected_pearson(double* val_ptr, int n_s
return true;
}
-bool comp_feats::valid_feature_against_selected_pearson(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
+bool comp_feats::valid_feature_against_selected_pearson_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
{
double base_val = util_funcs::r(val_ptr, val_ptr, n_samp);
@@ -149,7 +149,7 @@ bool comp_feats::valid_feature_against_selected_spearman_max_corr_1(double* val_
return true;
}
-bool comp_feats::valid_feature_against_selected_spearman_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
+bool comp_feats::valid_feature_against_selected_spearman_max_corr_1_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
{
double base_val = std::abs(util_funcs::spearman_r(val_ptr, val_ptr, &RANK[omp_get_thread_num() * 4 * n_samp], &RANK[(omp_get_thread_num() * 4 + 2) * n_samp], &INDEX[omp_get_thread_num() * 2 * n_samp], n_samp));
@@ -166,7 +166,7 @@ bool comp_feats::valid_feature_against_selected_spearman_max_corr_1(double* val_
return true;
}
-bool comp_feats::valid_feature_against_selected_spearman_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
+bool comp_feats::valid_feature_against_selected_spearman_max_corr_1_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
{
double base_val = std::abs(util_funcs::spearman_r(val_ptr, val_ptr, &RANK[omp_get_thread_num() * 4 * n_samp], &RANK[(omp_get_thread_num() * 4 + 2) * n_samp], &INDEX[omp_get_thread_num() * 2 * n_samp], n_samp));
@@ -201,7 +201,7 @@ bool comp_feats::valid_feature_against_selected_spearman(double* val_ptr, int n_
return is_valid;
}
-bool comp_feats::valid_feature_against_selected_spearman(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
+bool comp_feats::valid_feature_against_selected_spearman_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score)
{
double base_val = std::abs(util_funcs::spearman_r(val_ptr, val_ptr, &RANK[omp_get_thread_num() * 4 * n_samp], &RANK[(omp_get_thread_num() * 4 + 2) * n_samp], &INDEX[omp_get_thread_num() * 2 * n_samp], n_samp));
@@ -215,7 +215,7 @@ bool comp_feats::valid_feature_against_selected_spearman(double* val_ptr, int n_
return true;
}
-bool comp_feats::valid_feature_against_selected_spearman(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
+bool comp_feats::valid_feature_against_selected_spearman_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score)
{
double base_val = std::abs(util_funcs::spearman_r(val_ptr, val_ptr, &RANK[omp_get_thread_num() * 4 * n_samp], &RANK[(omp_get_thread_num() * 4 + 2) * n_samp], &INDEX[omp_get_thread_num() * 2 * n_samp], n_samp));
diff --git a/src/utils/compare_features.hpp b/src/utils/compare_features.hpp
index 0badade62e81b40cc32c5698ac26a7e2e6e666a1..0cd67b52048abfb22589414a09f51935903ca2a5 100644
--- a/src/utils/compare_features.hpp
+++ b/src/utils/compare_features.hpp
@@ -59,7 +59,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_pearson_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
+ bool valid_feature_against_selected_pearson_max_corr_1_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the Pearson correlation coefficient with a maximum cross-correlation of 1.0)
@@ -73,7 +73,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_pearson_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
+ bool valid_feature_against_selected_pearson_max_corr_1_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the Pearson correlation coefficient)
@@ -98,7 +98,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_pearson(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
+ bool valid_feature_against_selected_pearson_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the Pearson correlation coefficient)
@@ -112,7 +112,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_pearson(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
+ bool valid_feature_against_selected_pearson_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the rank correlation coefficient with a maximum cross-correlation of 1.0)
@@ -137,7 +137,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_spearman_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
+ bool valid_feature_against_selected_spearman_max_corr_1_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the rank correlation coefficient with a maximum cross-correlation of 1.0)
@@ -151,7 +151,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_spearman_max_corr_1(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
+ bool valid_feature_against_selected_spearman_max_corr_1_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the rank correlation coefficient)
@@ -176,7 +176,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_spearman(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
+ bool valid_feature_against_selected_spearman_feat_list(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_ptr>& selected, std::vector<double>& scores_sel, double cur_score);
/**
* @brief Checks the feature to see if it is still valid against previously selected features (using the rank correlation coefficient)
@@ -190,7 +190,7 @@ namespace comp_feats
*
* @return True if the feature is still valid
*/
- bool valid_feature_against_selected_spearman(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
+ bool valid_feature_against_selected_spearman_mpi_op(double* val_ptr, int n_samp, double cross_cor_max, std::vector<node_sc_pair>& out_vec, double cur_score);
}
#endif
diff --git a/src/utils/project.cpp b/src/utils/project.cpp
index 8efa8739001702adcd0d2ed23f312d0d19a8641c..bcae3d995af223d5ffb3f7a6cd64907b9a6c4333 100644
--- a/src/utils/project.cpp
+++ b/src/utils/project.cpp
@@ -3,8 +3,8 @@
void project_funcs::set_project_fxn(
const std::string project_type,
const int n_task,
- std::function<void(double*, double*, std::vector<node_ptr>&, std::vector<int>&, int)>& project,
- std::function<void(double*, double*, std::vector<node_ptr>&, std::vector<int>&, int)>& project_no_omp
+ std::function<void(double*, double*, std::vector<node_ptr>&, const std::vector<int>&, int)>& project,
+ std::function<void(double*, double*, std::vector<node_ptr>&, const std::vector<int>&, int)>& project_no_omp
)
{
if(project_type.compare("regression") == 0)
diff --git a/src/utils/project.hpp b/src/utils/project.hpp
index 24f7afc922cd442ab6e2904d1c2f6b914028bbc5..d5741287377e0de66aa3044e9ec87e258195bf59 100644
--- a/src/utils/project.hpp
+++ b/src/utils/project.hpp
@@ -27,8 +27,8 @@ namespace project_funcs
void set_project_fxn(
const std::string project_type,
const int n_task,
- std::function<void(double*, double*, std::vector<node_ptr>&, std::vector<int>&, int)>& project,
- std::function<void(double*, double*, std::vector<node_ptr>&, std::vector<int>&, int)>& project_no_omp
+ std::function<void(double*, double*, std::vector<node_ptr>&, const std::vector<int>&, int)>& project,
+ std::function<void(double*, double*, std::vector<node_ptr>&, const std::vector<int>&, int)>& project_no_omp
);
/**
diff --git a/tests/googletest/utils/test_compare_features.cc b/tests/googletest/utils/test_compare_features.cc
index 831c4a156ac5119ec7143abea957eeb3d4aba403..75903be67c9c9ac77e6070f6117e8c528f91e421 100644
--- a/tests/googletest/utils/test_compare_features.cc
+++ b/tests/googletest/utils/test_compare_features.cc
@@ -21,14 +21,14 @@ namespace {
std::copy_n(val_3.data(), val_3.size(), node_value_arrs::get_d_matrix_ptr(0));
- EXPECT_FALSE(comp_feats::valid_feature_against_selected_max_corr_1_pearson(val_1.data(), 4, 1.0, scores, 0.9897782665572893, 1, 0));
- EXPECT_FALSE(comp_feats::valid_feature_against_selected_max_corr_1_feat_list_pearson(val_1.data(), 4, 1.0, selected, scores, 0.9897782665572893));
+ EXPECT_FALSE(comp_feats::valid_feature_against_selected_pearson_max_corr_1(val_1.data(), 4, 1.0, scores, 0.9897782665572893, 1, 0));
+ EXPECT_FALSE(comp_feats::valid_feature_against_selected_pearson_max_corr_1_feat_list(val_1.data(), 4, 1.0, selected, scores, 0.9897782665572893));
EXPECT_FALSE(comp_feats::valid_feature_against_selected_pearson(val_1.data(), 4, 1.0, scores, 0.9897782665572893, 1, 0));
- EXPECT_FALSE(comp_feats::valid_feature_against_selected_feat_list_pearson(val_1.data(), 4, 1.0, selected, scores, 0.9897782665572893));
+ EXPECT_FALSE(comp_feats::valid_feature_against_selected_pearson_feat_list(val_1.data(), 4, 1.0, selected, scores, 0.9897782665572893));
- EXPECT_TRUE(comp_feats::valid_feature_against_selected_max_corr_1_pearson(val_2.data(), 4, 1.0, scores, 0.9028289727756884, 1, 0));
- EXPECT_TRUE(comp_feats::valid_feature_against_selected_max_corr_1_feat_list_pearson(val_2.data(), 4, 1.0, selected, scores, 0.9028289727756884));
+ EXPECT_TRUE(comp_feats::valid_feature_against_selected_pearson_max_corr_1(val_2.data(), 4, 1.0, scores, 0.9028289727756884, 1, 0));
+ EXPECT_TRUE(comp_feats::valid_feature_against_selected_pearson_max_corr_1_feat_list(val_2.data(), 4, 1.0, selected, scores, 0.9028289727756884));
EXPECT_TRUE(comp_feats::valid_feature_against_selected_pearson(val_2.data(), 4, 1.0, scores, 0.9028289727756884, 1, 0));
- EXPECT_TRUE(comp_feats::valid_feature_against_selected_feat_list_pearson(val_2.data(), 4, 1.0, selected, scores, 0.9028289727756884));
+ EXPECT_TRUE(comp_feats::valid_feature_against_selected_pearson_feat_list(val_2.data(), 4, 1.0, selected, scores, 0.9028289727756884));
}
}