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authorPatrick Simianer <simianer@cl.uni-heidelberg.de>2012-05-02 15:03:24 +0200
committerPatrick Simianer <simianer@cl.uni-heidelberg.de>2012-05-02 15:03:24 +0200
commit45cb0f7426de97cc181079daf3ca04dbc52dee3c (patch)
treeabd2158a559480504525082760a618c78847fcf7 /utils/m_test.cc
parent5a8ef8ba65b244837e9cedbd64793b82bf284f93 (diff)
parent1c32f3e2831aefdf50fd226d3e1b314c804afc3b (diff)
Merge remote-tracking branch 'upstream/master'
Diffstat (limited to 'utils/m_test.cc')
-rw-r--r--utils/m_test.cc52
1 files changed, 21 insertions, 31 deletions
diff --git a/utils/m_test.cc b/utils/m_test.cc
index c4d6a166..7851e4ac 100644
--- a/utils/m_test.cc
+++ b/utils/m_test.cc
@@ -1,20 +1,15 @@
#include "m.h"
+#define BOOST_TEST_MODULE MTest
+#include <boost/test/unit_test.hpp>
+#include <boost/test/floating_point_comparison.hpp>
+
#include <iostream>
-#include <gtest/gtest.h>
#include <cassert>
using namespace std;
-class MTest : public testing::Test {
- public:
- MTest() {}
- protected:
- virtual void SetUp() { }
- virtual void TearDown() { }
-};
-
-TEST_F(MTest, Densities) {
+BOOST_AUTO_TEST_CASE(Densities) {
double px1 = Md::log_gaussian_density(1.0, 0.0, 1.0);
double px2 = Md::log_gaussian_density(-1.0, 0.0, 1.0);
double py1 = Md::log_laplace_density(1.0, 0.0, 1.0);
@@ -22,70 +17,65 @@ TEST_F(MTest, Densities) {
double pz1 = Md::log_triangle_density(1.0, -2.0, 2.0, 0.0);
double pz2 = Md::log_triangle_density(1.0, -2.0, 2.0, 0.0);
cerr << px1 << " " << py1 << " " << pz2 << endl;
- EXPECT_FLOAT_EQ(px1, px2);
- EXPECT_FLOAT_EQ(py1, py2);
- EXPECT_FLOAT_EQ(pz1, pz2);
+ BOOST_CHECK_CLOSE(px1, px2, 1e-6);
+ BOOST_CHECK_CLOSE(py1, py2, 1e-6);
+ BOOST_CHECK_CLOSE(pz1, pz2, 1e-6);
double b1 = Md::log_bivariate_gaussian_density(1.0, -1.0, 0.0, 0.0, 1.0, 1.0, -0.8);
double b2 = Md::log_bivariate_gaussian_density(-1.0, 1.0, 0.0, 0.0, 1.0, 1.0, -0.8);
cerr << b1 << " " << b2 << endl;
}
-TEST_F(MTest, Poisson) {
+BOOST_AUTO_TEST_CASE(Poisson) {
double prev = 1.0;
double tot = 0;
for (int i = 0; i < 10; ++i) {
double p = Md::log_poisson(i, 0.99);
cerr << "p(i=" << i << ") = " << exp(p) << endl;
- EXPECT_LT(p, prev);
+ assert(p < prev);
tot += exp(p);
prev = p;
}
cerr << " tot=" << tot << endl;
- EXPECT_LE(tot, 1.0);
+ assert(tot < 1.0);
}
-TEST_F(MTest, YuleSimon) {
+BOOST_AUTO_TEST_CASE(YuleSimon) {
double prev = 1.0;
double tot = 0;
for (int i = 0; i < 10; ++i) {
double p = Md::log_yule_simon(i, 1.0);
cerr << "p(i=" << i << ") = " << exp(p) << endl;
- EXPECT_LT(p, prev);
+ assert(p < prev);
tot += exp(p);
prev = p;
}
cerr << " tot=" << tot << endl;
- EXPECT_LE(tot, 1.0);
+ assert(tot < 1.0);
}
-TEST_F(MTest, LogGeometric) {
+BOOST_AUTO_TEST_CASE(LogGeometric) {
double prev = 1.0;
double tot = 0;
for (int i = 0; i < 10; ++i) {
double p = Md::log_geometric(i, 0.5);
cerr << "p(i=" << i << ") = " << exp(p) << endl;
- EXPECT_LT(p, prev);
+ assert(p < prev);
tot += exp(p);
prev = p;
}
cerr << " tot=" << tot << endl;
- EXPECT_LE(tot, 1.0);
+ assert(tot <= 1.0);
}
-TEST_F(MTest, GeneralizedFactorial) {
+BOOST_AUTO_TEST_CASE(GeneralizedFactorial) {
for (double i = 0.3; i < 10000; i += 0.4) {
double a = Md::log_generalized_factorial(1.0, i);
double b = lgamma(1.0 + i);
- EXPECT_FLOAT_EQ(a,b);
+ BOOST_CHECK_CLOSE(a,b,1e-6);
}
double gf_3_6 = 3.0 * 4.0 * 5.0 * 6.0 * 7.0 * 8.0;
- EXPECT_FLOAT_EQ(Md::log_generalized_factorial(3.0, 6.0), std::log(gf_3_6));
+ BOOST_CHECK_CLOSE(Md::log_generalized_factorial(3.0, 6.0), std::log(gf_3_6), 1e-6);
double gf_314_6 = 3.14 * 4.14 * 5.14 * 6.14 * 7.14 * 8.14;
- EXPECT_FLOAT_EQ(Md::log_generalized_factorial(3.14, 6.0), std::log(gf_314_6));
-}
-
-int main(int argc, char** argv) {
- testing::InitGoogleTest(&argc, argv);
- return RUN_ALL_TESTS();
+ BOOST_CHECK_CLOSE(Md::log_generalized_factorial(3.14, 6.0), std::log(gf_314_6), 1e-6);
}