rmontanana/BayesNet
1
0
Fork 0
Code Issues 2 Pull Requests 1 Actions Packages Projects Releases 6 Wiki Activity

Add some more tests to 97% coverage

Browse Source
This commit is contained in:
Ricardo Montañana Gómez
2024-04-11 17:29:46 +02:00
parent 8eeaa1beee
commit 503ad687dc
8 changed files with 75 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
tests/TestBayesClassifier.cc
View File

@@ -54,6 +54,13 @@ TEST_CASE("Invalid feature name", "[Classifier]")
REQUIRE_THROWS_AS(model.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, statest), std::invalid_argument);
REQUIRE_THROWS_WITH(model.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, statest), "feature [petallength] not found in states");
}
TEST_CASE("Invalid hyperparameter", "[Classifier]")
{
auto model = bayesnet::KDB(2);
auto raw = RawDatasets("iris", true);
REQUIRE_THROWS_AS(model.setHyperparameters({ { "alpha", "0.0" } }), std::invalid_argument);
REQUIRE_THROWS_WITH(model.setHyperparameters({ { "alpha", "0.0" } }), "Invalid hyperparameters{\"alpha\":\"0.0\"}");
}
TEST_CASE("Topological order", "[Classifier]")
{
auto model = bayesnet::TAN();

11
tests/TestBayesEnsemble.cc
View File

@@ -3,6 +3,8 @@
#include <catch2/catch_approx.hpp>
#include <catch2/generators/catch_generators.hpp>
#include "bayesnet/ensembles/BoostAODE.h"
#include "bayesnet/ensembles/AODE.h"
#include "bayesnet/ensembles/AODELd.h"
#include "TestUtils.h"
@@ -73,6 +75,15 @@ TEST_CASE("Graph", "[Ensemble]")
clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
auto graph = clf.graph();
REQUIRE(graph.size() == 56);
auto clf2 = bayesnet::AODE();
clf2.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
graph = clf2.graph();
REQUIRE(graph.size() == 56);
raw = RawDatasets("glass", false);
auto clf3 = bayesnet::AODELd();
clf3.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
graph = clf3.graph();
REQUIRE(graph.size() == 261);
}
TEST_CASE("Compute ArgMax", "[Ensemble]")
{

44
tests/TestBayesModels.cc
View File

@@ -14,7 +14,7 @@
#include "bayesnet/ensembles/BoostAODE.h"
#include "TestUtils.h"
const std::string ACTUAL_VERSION = "1.0.4";
const std::string ACTUAL_VERSION = "1.0.4.1";
TEST_CASE("Test Bayesian Classifiers score & version", "[Models]")
{
@@ -52,6 +52,7 @@ TEST_CASE("Test Bayesian Classifiers score & version", "[Models]")
auto score = clf->score(raw.Xt, raw.yt);
INFO("Classifier: " + name + " File: " + file_name);
REQUIRE(score == Catch::Approx(scores[{file_name, name}]).epsilon(raw.epsilon));
REQUIRE(clf->getStatus() == bayesnet::NORMAL);
}
}
SECTION("Library check version")
@@ -61,7 +62,7 @@ TEST_CASE("Test Bayesian Classifiers score & version", "[Models]")
}
delete clf;
}
TEST_CASE("Models features", "[Models]")
TEST_CASE("Models features & Graph", "[Models]")
{
auto graph = std::vector<std::string>({ "digraph BayesNet {\nlabel=<BayesNet Test>\nfontsize=30\nfontcolor=blue\nlabelloc=t\nlayout=circo\n",
"class [shape=circle, fontcolor=red, fillcolor=lightblue, style=filled ] \n",
@@ -70,15 +71,30 @@ TEST_CASE("Models features", "[Models]")
"sepallength -> sepalwidth", "sepalwidth [shape=circle] \n", "sepalwidth -> petalwidth", "}\n"
}
);
auto raw = RawDatasets("iris", true);
auto clf = bayesnet::TAN();
clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
REQUIRE(clf.getNumberOfNodes() == 5);
REQUIRE(clf.getNumberOfEdges() == 7);
REQUIRE(clf.getNumberOfStates() == 19);
REQUIRE(clf.getClassNumStates() == 3);
REQUIRE(clf.show() == std::vector<std::string>{"class -> sepallength, sepalwidth, petallength, petalwidth, ", "petallength -> sepallength, ", "petalwidth -> ", "sepallength -> sepalwidth, ", "sepalwidth -> petalwidth, "});
REQUIRE(clf.graph("Test") == graph);
SECTION("Test TAN")
{
auto raw = RawDatasets("iris", true);
auto clf = bayesnet::TAN();
clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
REQUIRE(clf.getNumberOfNodes() == 5);
REQUIRE(clf.getNumberOfEdges() == 7);
REQUIRE(clf.getNumberOfStates() == 19);
REQUIRE(clf.getClassNumStates() == 3);
REQUIRE(clf.show() == std::vector<std::string>{"class -> sepallength, sepalwidth, petallength, petalwidth, ", "petallength -> sepallength, ", "petalwidth -> ", "sepallength -> sepalwidth, ", "sepalwidth -> petalwidth, "});
REQUIRE(clf.graph("Test") == graph);
}
SECTION("Test TANLd")
{
auto clf = bayesnet::TANLd();
auto raw = RawDatasets("iris", false);
clf.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
REQUIRE(clf.getNumberOfNodes() == 5);
REQUIRE(clf.getNumberOfEdges() == 7);
REQUIRE(clf.getNumberOfStates() == 19);
REQUIRE(clf.getClassNumStates() == 3);
REQUIRE(clf.show() == std::vector<std::string>{"class -> sepallength, sepalwidth, petallength, petalwidth, ", "petallength -> sepallength, ", "petalwidth -> ", "sepallength -> sepalwidth, ", "sepalwidth -> petalwidth, "});
REQUIRE(clf.graph("Test") == graph);
}
}
TEST_CASE("Get num features & num edges", "[Models]")
{
@@ -222,6 +238,12 @@ TEST_CASE("KDB with hyperparameters", "[Models]")
REQUIRE(score == Catch::Approx(0.827103).epsilon(raw.epsilon));
REQUIRE(scoret == Catch::Approx(0.761682).epsilon(raw.epsilon));
}
TEST_CASE("Incorrect type of data for SPODELd", "[Models]")
{
auto raw = RawDatasets("iris", true);
auto clf = bayesnet::SPODELd(0);
REQUIRE_THROWS_AS(clf.fit(raw.dataset, raw.featurest, raw.classNamet, raw.statest), std::runtime_error);
}
TEST_CASE("Predict, predict_proba & score without fitting", "[Models]")
{
auto clf = bayesnet::AODE();

7
tests/TestBoostAODE.cc
View File

@@ -157,18 +157,13 @@ TEST_CASE("Bisection", "[BoostAODE]")
TEST_CASE("Block Update", "[BoostAODE]")
{
auto clf = bayesnet::BoostAODE();
// auto raw = RawDatasets("mfeat-factors", true);
auto raw = RawDatasets("glass", true);
auto raw = RawDatasets("mfeat-factors", true);
clf.setHyperparameters({
{"bisection", true},
{"block_update", true},
{"maxTolerance", 3},
{"convergence", true},
});
// clf.setHyperparameters({
// {"block_update", true},
// });
clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
REQUIRE(clf.getNumberOfNodes() == 217);
REQUIRE(clf.getNumberOfEdges() == 431);

12
tests/TestFeatureSelection.cc
View File

@@ -1,6 +1,7 @@
#include <catch2/catch_test_macros.hpp>
#include <catch2/catch_approx.hpp>
#include <catch2/generators/catch_generators.hpp>
#include <catch2/matchers/catch_matchers.hpp>
#include "bayesnet/utils/BayesMetrics.h"
#include "bayesnet/feature_selection/CFS.h"
#include "bayesnet/feature_selection/FCBF.h"
@@ -68,4 +69,15 @@ TEST_CASE("Features Selected", "[FeatureSelection]")
delete featureSelector;
}
}
}
TEST_CASE("Oddities", "[FeatureSelection]")
{
auto raw = RawDatasets("iris", true);
// FCBF Limits
REQUIRE_THROWS_AS(bayesnet::FCBF(raw.dataset, raw.featuresv, raw.classNamev, raw.featuresv.size(), raw.classNumStates, raw.weights, 1e-8), std::invalid_argument);
REQUIRE_THROWS_WITH(bayesnet::FCBF(raw.dataset, raw.featuresv, raw.classNamev, raw.featuresv.size(), raw.classNumStates, raw.weights, 1e-8), "Threshold cannot be less than 1e-7");
REQUIRE_THROWS_AS(bayesnet::IWSS(raw.dataset, raw.featuresv, raw.classNamev, raw.featuresv.size(), raw.classNumStates, raw.weights, -1e4), std::invalid_argument);
REQUIRE_THROWS_WITH(bayesnet::IWSS(raw.dataset, raw.featuresv, raw.classNamev, raw.featuresv.size(), raw.classNumStates, raw.weights, -1e4), "Threshold has to be in [0, 0.5]");
REQUIRE_THROWS_AS(bayesnet::IWSS(raw.dataset, raw.featuresv, raw.classNamev, raw.featuresv.size(), raw.classNumStates, raw.weights, 0.501), std::invalid_argument);
REQUIRE_THROWS_WITH(bayesnet::IWSS(raw.dataset, raw.featuresv, raw.classNamev, raw.featuresv.size(), raw.classNumStates, raw.weights, 0.501), "Threshold has to be in [0, 0.5]");
}