# LCOV - BayesNet Coverage Report - bayesnet/classifiers/TANLd.cc

LCOV - code coverage report

Current view: | top level - bayesnet/classifiers - TANLd.cc (source / functions) |  |  | Coverage | Total | Hit
Test: | BayesNet Coverage Report |  | Lines: | 100.0 % | 17 | 17
Test Date: | 2024-05-06 17:54:04 |  | Functions: | 100.0 % | 4 | 4
Legend: | Lines: hit not hit |

                Line data    Source code

           1              : // ***************************************************************
           2              : // SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
           3              : // SPDX-FileType: SOURCE
           4              : // SPDX-License-Identifier: MIT
           5              : // ***************************************************************
           6              :
           7              : #include "TANLd.h"
           8              :
           9              : namespace bayesnet {
          10           68 :     TANLd::TANLd() : TAN(), Proposal(dataset, features, className) {}
          11           20 :     TANLd& TANLd::fit(torch::Tensor& X_, torch::Tensor& y_, const std::vector<std::string>& features_, const std::string& className_, map<std::string, std::vector<int>>& states_)
          12              :     {
          13           20 :         checkInput(X_, y_);
          14           20 :         features = features_;
          15           20 :         className = className_;
          16           20 :         Xf = X_;
          17           20 :         y = y_;
          18              :         // Fills std::vectors Xv & yv with the data from tensors X_ (discretized) & y
          19           20 :         states = fit_local_discretization(y);
          20              :         // We have discretized the input data
          21              :         // 1st we need to fit the model to build the normal TAN structure, TAN::fit initializes the base Bayesian network
          22           20 :         TAN::fit(dataset, features, className, states);
          23           20 :         states = localDiscretizationProposal(states, model);
          24           20 :         return *this;
          25              :
          26              :     }
          27           16 :     torch::Tensor TANLd::predict(torch::Tensor& X)
          28              :     {
          29           16 :         auto Xt = prepareX(X);
          30           32 :         return TAN::predict(Xt);
          31           16 :     }
          32            4 :     std::vector<std::string> TANLd::graph(const std::string& name) const
          33              :     {
          34            4 :         return TAN::graph(name);
          35              :     }
          36              : }

Generated by: LCOV version 2.0-1