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add get eqn
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@lacava
lacava committed Aug 16, 2023
1 parent d7cfd4a commit 74ae07c
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Showing 5 changed files with 128 additions and 122 deletions.
2 changes: 1 addition & 1 deletion docs/conf.py
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Expand Up @@ -52,7 +52,7 @@
'sphinx.ext.githubpages',
'sphinx.ext.napoleon',
'sphinx_copybutton',
"sphinx.ext.mathjax",

'sphinx_math_dollar',
# 'recommonmark',
'nbsphinx',
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9 changes: 8 additions & 1 deletion docs/index.md
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Expand Up @@ -12,9 +12,16 @@
:maxdepth: 2
installation
overview
basics
```

```{toctree}
:caption: User Guide
:maxdepth: 2
contributing
overview
```

```{toctree}
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12 changes: 6 additions & 6 deletions src/feat.cc
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Expand Up @@ -475,9 +475,9 @@ float Feat::get_fb(){ return params.feedback; }
///return best model
string Feat::get_representation(){ return best_ind.get_eqn();}

string Feat::get_eqn(bool sort){ return this->get_eqn(sort, this->best_ind); };
string Feat::get_eqn(bool sort){ return this->get_ind_eqn(sort, this->best_ind); };

string Feat::get_eqn(bool sort, Individual& ind)
string Feat::get_ind_eqn(bool sort, Individual& ind)
{
vector<string> features = ind.get_features();
vector<float> weights = ind.ml->get_weights();
Expand Down Expand Up @@ -838,7 +838,7 @@ void Feat::simplify_model(DataRef& d, Individual& ind)
if (tmp_ind.size() < ind.size())
{
ind = tmp_ind;
logger.log("new model:" + this->get_eqn(false, ind),2);
logger.log("new model:" + this->get_ind_eqn(false, ind),2);
}

///////////////////
Expand Down Expand Up @@ -905,7 +905,7 @@ void Feat::simplify_model(DataRef& d, Individual& ind)
+ to_string(starting_size - end_size)
+ " nodes\n=========\n", 2);
if (end_size < starting_size)
logger.log("new model:" + this->get_eqn(false, ind),2);
logger.log("new model:" + this->get_ind_eqn(false, ind),2);

/////////////////
// prune subtrees
Expand Down Expand Up @@ -1461,7 +1461,7 @@ void Feat::print_stats(std::ofstream& log, float fraction)
{
std::string lim_model;

std::string model = this->get_eqn(false, archive.individuals[i]);
std::string model = this->get_ind_eqn(false, archive.individuals[i]);
/* std::string model = archive.individuals[i].get_eqn(); */
for (unsigned j = 0; j< std::min(model.size(),size_t(60)); ++j)
{
Expand Down Expand Up @@ -1492,7 +1492,7 @@ void Feat::print_stats(std::ofstream& log, float fraction)
for (unsigned j = 0; j < std::min(num_models,unsigned(f.size())); ++j)
{
std::string lim_model;
std::string model = this->get_eqn(false,pop.individuals[f[j]]);
std::string model = this->get_ind_eqn(false,pop.individuals[f[j]]);
/* std::string model = this->pop.individuals[f[j]].get_eqn(); */
for (unsigned j = 0; j< std::min(model.size(),size_t(60)); ++j)
lim_model.push_back(model.at(j));
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2 changes: 1 addition & 1 deletion src/feat.h
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Expand Up @@ -319,7 +319,7 @@ class Feat
///return best model, in tabular form
string get_model(bool sort=true);
///return best model as a single line equation
string get_eqn(bool sort, Individual& ind);
string get_ind_eqn(bool sort, Individual& ind);
string get_eqn(bool sort=false);
///get number of parameters in best
int get_n_params();
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225 changes: 112 additions & 113 deletions src/pybind.cc
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Expand Up @@ -12,8 +12,6 @@ license: GNU/GPL v3
#include "pybind11_json/pybind11_json.hpp"
#include "nlohmann/json.hpp"



// py::dict obj = py::dict("number"_a=1234, "hello"_a="world");
// // Automatic py::dict->nl::json conversion
// nl::json j = obj;
Expand All @@ -33,7 +31,8 @@ using namespace FT;
namespace nl = nlohmann;
using namespace pybind11::literals;

PYBIND11_MODULE(_feat, m) {
PYBIND11_MODULE(_feat, m)
{
m.doc() = R"pbdoc(
Python binding for Feat
--------------------------
Expand All @@ -43,115 +42,115 @@ PYBIND11_MODULE(_feat, m) {
)pbdoc";

// #ifdef VERSION_INFO
// m.attr("__version__") = MACRO_STRINGIFY(VERSION_INFO);
// #else
// m.attr("__version__") = "dev";
// #endif
// #ifdef VERSION_INFO
// m.attr("__version__") = MACRO_STRINGIFY(VERSION_INFO);
// #else
// m.attr("__version__") = "dev";
// #endif

py::class_<Feat>(m, "cppFeat", py::dynamic_attr() )
// .def(py::init<>())
.def(py::init([]() { Feat est; return est; }))
.def_property("stats_", &Feat::get_stats, nullptr)
.def_property("pop_size", &Feat::get_pop_size, &Feat::set_pop_size)
.def_property("gens", &Feat::get_gens, &Feat::set_gens)
.def_property("ml", &Feat::get_ml, &Feat::set_ml)
.def_property("classification", &Feat::get_classification, &Feat::set_classification)
.def_property("verbosity", &Feat::get_verbosity, &Feat::set_verbosity)
.def_property("max_stall", &Feat::get_max_stall, &Feat::set_max_stall)
.def_property("sel", &Feat::get_sel, &Feat::set_sel)
.def_property("surv", &Feat::get_surv, &Feat::set_surv)
.def_property("cross_rate", &Feat::get_cross_rate, &Feat::set_cross_rate)
.def_property("root_xo_rate", &Feat::get_root_xo_rate, &Feat::set_root_xo_rate)
.def_property("otype", &Feat::get_otype, &Feat::set_otype)
.def_property("max_depth", &Feat::get_max_depth, &Feat::set_max_depth)
.def_property("max_dim", &Feat::get_max_dim, &Feat::set_max_dim)
.def_property("random_state", &Feat::get_random_state, &Feat::set_random_state)
.def_property("erc", &Feat::get_erc, &Feat::set_erc)
.def_property("objectives", &Feat::get_objectives, &Feat::set_objectives)
.def_property("functions", &Feat::get_functions, &Feat::set_functions)
.def_property("shuffle", &Feat::get_shuffle, &Feat::set_shuffle)
.def_property("split", &Feat::get_split, &Feat::set_split)
.def_property("fb", &Feat::get_fb, &Feat::set_fb)
.def_property("scorer", &Feat::get_scorer, &Feat::set_scorer)
.def_property("feature_names", &Feat::get_feature_names, &Feat::set_feature_names)
.def_property("backprop", &Feat::get_backprop, &Feat::set_backprop)
.def_property("iters", &Feat::get_iters, &Feat::set_iters)
.def_property("lr", &Feat::get_lr, &Feat::set_lr)
.def_property("batch_size", &Feat::get_batch_size, &Feat::set_batch_size)
.def_property("n_jobs", &Feat::get_n_jobs, &Feat::set_n_jobs)
.def_property("hillclimb", &Feat::get_hillclimb, &Feat::set_hillclimb)
.def_property("logfile", &Feat::get_logfile, &Feat::set_logfile)
.def_property("max_time", &Feat::get_max_time, &Feat::set_max_time)
.def_property("residual_xo", &Feat::get_residual_xo, &Feat::set_residual_xo)
.def_property("stagewise_xo", &Feat::get_stagewise_xo, &Feat::set_stagewise_xo)
.def_property("stagewise_xo_tol", &Feat::get_stagewise_xo_tol,
&Feat::set_stagewise_xo_tol)
.def_property("softmax_norm", &Feat::get_softmax_norm, &Feat::set_softmax_norm)
.def_property("save_pop", &Feat::get_save_pop, &Feat::set_save_pop)
.def_property("normalize", &Feat::get_normalize, &Feat::set_normalize)
.def_property("val_from_arch", &Feat::get_val_from_arch, &Feat::set_val_from_arch)
.def_property("corr_delete_mutate", &Feat::get_corr_delete_mutate,
&Feat::set_corr_delete_mutate)
.def_property("simplify", &Feat::get_simplify, &Feat::set_simplify)
.def_property("protected_groups",
&Feat::get_protected_groups, &Feat::set_protected_groups)
.def_property("tune_initial", &Feat::get_tune_initial, &Feat::set_tune_initial)
.def_property("tune_final", &Feat::get_tune_final, &Feat::set_tune_final)
.def_property("starting_pop", &Feat::get_starting_pop, &Feat::set_starting_pop)
// .def_property("fitted_", &Feat::get_is_fitted, &Feat::set_is_fitted)
.def("fit",
py::overload_cast<MatrixXf&, VectorXf&>(&Feat::fit),
py::call_guard<
py::scoped_ostream_redirect,
py::scoped_estream_redirect,
py::gil_scoped_release
>(),
"fit from X,y data")
.def("fit",
py::overload_cast<MatrixXf&, VectorXf&, LongData&>(&Feat::fit),
py::call_guard<
py::scoped_ostream_redirect,
py::scoped_estream_redirect,
py::gil_scoped_release
>(),
"fit from X,y,Z data")
.def("transform",
py::overload_cast<MatrixXf&>(&Feat::transform),
"transform from X data")
.def("transform",
py::overload_cast<MatrixXf&, LongData&>(&Feat::transform),
"transform from X,Z data")
.def("predict",
py::overload_cast<MatrixXf&>(&Feat::predict),
"predict from X data")
.def("predict",
py::overload_cast<MatrixXf&, LongData&>(&Feat::predict),
"predict from X,Z data")
.def("predict_proba",
py::overload_cast<MatrixXf&>(&Feat::predict_proba),
"predict probabilities from X data")
.def("predict_proba",
py::overload_cast<MatrixXf&, LongData&>(&Feat::predict_proba),
"predict probabilities from X data")
.def("predict_archive",
py::overload_cast<int,MatrixXf&>(&Feat::predict_archive),
"predict from individual in archive")
.def("predict_archive",
py::overload_cast<int,MatrixXf&,LongData&>(&Feat::predict_archive),
"predict from individual in archive")
.def("predict_proba_archive",
py::overload_cast<int,MatrixXf&>(&Feat::predict_proba_archive),
"predict from individual in archive")
.def("predict_proba_archive",
py::overload_cast<int,MatrixXf&,LongData&>(&Feat::predict_proba_archive),
"predict from individual in archive")
.def("get_archive",&Feat::get_archive, py::arg("front") = false)
.def("get_coefs",&Feat::get_coefs)
.def("save",&Feat::save)
.def("load",&Feat::load)
.def("get_representation",&Feat::get_representation)
.def("get_model",&Feat::get_model, py::arg("sort") = true)
;
// py::add_ostream_redirect(m, "ostream_redirect");
py::class_<Feat>(m, "cppFeat", py::dynamic_attr())
// .def(py::init<>())
.def(py::init([]()
{ Feat est; return est; }))
.def_property("stats_", &Feat::get_stats, nullptr)
.def_property("pop_size", &Feat::get_pop_size, &Feat::set_pop_size)
.def_property("gens", &Feat::get_gens, &Feat::set_gens)
.def_property("ml", &Feat::get_ml, &Feat::set_ml)
.def_property("classification", &Feat::get_classification, &Feat::set_classification)
.def_property("verbosity", &Feat::get_verbosity, &Feat::set_verbosity)
.def_property("max_stall", &Feat::get_max_stall, &Feat::set_max_stall)
.def_property("sel", &Feat::get_sel, &Feat::set_sel)
.def_property("surv", &Feat::get_surv, &Feat::set_surv)
.def_property("cross_rate", &Feat::get_cross_rate, &Feat::set_cross_rate)
.def_property("root_xo_rate", &Feat::get_root_xo_rate, &Feat::set_root_xo_rate)
.def_property("otype", &Feat::get_otype, &Feat::set_otype)
.def_property("max_depth", &Feat::get_max_depth, &Feat::set_max_depth)
.def_property("max_dim", &Feat::get_max_dim, &Feat::set_max_dim)
.def_property("random_state", &Feat::get_random_state, &Feat::set_random_state)
.def_property("erc", &Feat::get_erc, &Feat::set_erc)
.def_property("objectives", &Feat::get_objectives, &Feat::set_objectives)
.def_property("functions", &Feat::get_functions, &Feat::set_functions)
.def_property("shuffle", &Feat::get_shuffle, &Feat::set_shuffle)
.def_property("split", &Feat::get_split, &Feat::set_split)
.def_property("fb", &Feat::get_fb, &Feat::set_fb)
.def_property("scorer", &Feat::get_scorer, &Feat::set_scorer)
.def_property("feature_names", &Feat::get_feature_names, &Feat::set_feature_names)
.def_property("backprop", &Feat::get_backprop, &Feat::set_backprop)
.def_property("iters", &Feat::get_iters, &Feat::set_iters)
.def_property("lr", &Feat::get_lr, &Feat::set_lr)
.def_property("batch_size", &Feat::get_batch_size, &Feat::set_batch_size)
.def_property("n_jobs", &Feat::get_n_jobs, &Feat::set_n_jobs)
.def_property("hillclimb", &Feat::get_hillclimb, &Feat::set_hillclimb)
.def_property("logfile", &Feat::get_logfile, &Feat::set_logfile)
.def_property("max_time", &Feat::get_max_time, &Feat::set_max_time)
.def_property("residual_xo", &Feat::get_residual_xo, &Feat::set_residual_xo)
.def_property("stagewise_xo", &Feat::get_stagewise_xo, &Feat::set_stagewise_xo)
.def_property("stagewise_xo_tol", &Feat::get_stagewise_xo_tol,
&Feat::set_stagewise_xo_tol)
.def_property("softmax_norm", &Feat::get_softmax_norm, &Feat::set_softmax_norm)
.def_property("save_pop", &Feat::get_save_pop, &Feat::set_save_pop)
.def_property("normalize", &Feat::get_normalize, &Feat::set_normalize)
.def_property("val_from_arch", &Feat::get_val_from_arch, &Feat::set_val_from_arch)
.def_property("corr_delete_mutate", &Feat::get_corr_delete_mutate,
&Feat::set_corr_delete_mutate)
.def_property("simplify", &Feat::get_simplify, &Feat::set_simplify)
.def_property("protected_groups",
&Feat::get_protected_groups, &Feat::set_protected_groups)
.def_property("tune_initial", &Feat::get_tune_initial, &Feat::set_tune_initial)
.def_property("tune_final", &Feat::get_tune_final, &Feat::set_tune_final)
.def_property("starting_pop", &Feat::get_starting_pop, &Feat::set_starting_pop)
// .def_property("fitted_", &Feat::get_is_fitted, &Feat::set_is_fitted)
.def("fit",
py::overload_cast<MatrixXf &, VectorXf &>(&Feat::fit),
py::call_guard<
py::scoped_ostream_redirect,
py::scoped_estream_redirect,
py::gil_scoped_release>(),
"fit from X,y data")
.def("fit",
py::overload_cast<MatrixXf &, VectorXf &, LongData &>(&Feat::fit),
py::call_guard<
py::scoped_ostream_redirect,
py::scoped_estream_redirect,
py::gil_scoped_release>(),
"fit from X,y,Z data")
.def("transform",
py::overload_cast<MatrixXf &>(&Feat::transform),
"transform from X data")
.def("transform",
py::overload_cast<MatrixXf &, LongData &>(&Feat::transform),
"transform from X,Z data")
.def("predict",
py::overload_cast<MatrixXf &>(&Feat::predict),
"predict from X data")
.def("predict",
py::overload_cast<MatrixXf &, LongData &>(&Feat::predict),
"predict from X,Z data")
.def("predict_proba",
py::overload_cast<MatrixXf &>(&Feat::predict_proba),
"predict probabilities from X data")
.def("predict_proba",
py::overload_cast<MatrixXf &, LongData &>(&Feat::predict_proba),
"predict probabilities from X data")
.def("predict_archive",
py::overload_cast<int, MatrixXf &>(&Feat::predict_archive),
"predict from individual in archive")
.def("predict_archive",
py::overload_cast<int, MatrixXf &, LongData &>(&Feat::predict_archive),
"predict from individual in archive")
.def("predict_proba_archive",
py::overload_cast<int, MatrixXf &>(&Feat::predict_proba_archive),
"predict from individual in archive")
.def("predict_proba_archive",
py::overload_cast<int, MatrixXf &, LongData &>(&Feat::predict_proba_archive),
"predict from individual in archive")
.def("get_archive", &Feat::get_archive, py::arg("front") = false)
.def("get_coefs", &Feat::get_coefs)
.def("save", &Feat::save)
.def("load", &Feat::load)
.def("get_representation", &Feat::get_representation)
.def("get_model", &Feat::get_model, py::arg("sort") = true)
.def("get_eqn", &Feat::get_eqn, py::arg("sort") = true)
;
// py::add_ostream_redirect(m, "ostream_redirect");
}

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