[mlpack-git] master: Spelling fixes in test. (eaa7182)
gitdub at mlpack.org
gitdub at mlpack.org
Wed Jun 29 11:59:55 EDT 2016
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/809ed4bf33cef9de8412fc167cb0e356a369e3b6...eaa7182ebed8cce3fd6191dc1f8170546ea297da
>---------------------------------------------------------------
commit eaa7182ebed8cce3fd6191dc1f8170546ea297da
Author: Ryan Curtin <ryan at ratml.org>
Date: Wed Jun 29 11:59:41 2016 -0400
Spelling fixes in test.
>---------------------------------------------------------------
eaa7182ebed8cce3fd6191dc1f8170546ea297da
src/mlpack/tests/akfn_test.cpp | 34 +++++++++---------
src/mlpack/tests/aknn_test.cpp | 81 +++++++++++++++++++++---------------------
2 files changed, 58 insertions(+), 57 deletions(-)
diff --git a/src/mlpack/tests/akfn_test.cpp b/src/mlpack/tests/akfn_test.cpp
index 61ec6f5..5769899 100644
--- a/src/mlpack/tests/akfn_test.cpp
+++ b/src/mlpack/tests/akfn_test.cpp
@@ -23,7 +23,7 @@ BOOST_AUTO_TEST_SUITE(AKFNTest);
*
* Errors are produced if the results are not according to relative error.
*/
-BOOST_AUTO_TEST_CASE(AproxVsExact1)
+BOOST_AUTO_TEST_CASE(ApproxVsExact1)
{
arma::mat dataset;
@@ -58,12 +58,12 @@ BOOST_AUTO_TEST_CASE(AproxVsExact1)
// Now perform the actual calculation.
akfn = new KFN(dataset, false, false, epsilon);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
- akfn->Search(dataset, 15, neighborsAprox, distancesAprox);
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
+ akfn->Search(dataset, 15, neighborsApprox, distancesApprox);
- for (size_t i = 0; i < neighborsAprox.n_elem; i++)
- REQUIRE_RELATIVE_ERR(distancesAprox(i), distancesExact(i), epsilon);
+ for (size_t i = 0; i < neighborsApprox.n_elem; i++)
+ REQUIRE_RELATIVE_ERR(distancesApprox(i), distancesExact(i), epsilon);
// Clean the memory.
delete akfn;
@@ -76,7 +76,7 @@ BOOST_AUTO_TEST_CASE(AproxVsExact1)
*
* Errors are produced if the results are not according to relative error.
*/
-BOOST_AUTO_TEST_CASE(AproxVsExact2)
+BOOST_AUTO_TEST_CASE(ApproxVsExact2)
{
arma::mat dataset;
@@ -89,12 +89,12 @@ BOOST_AUTO_TEST_CASE(AproxVsExact2)
exact.Search(15, neighborsExact, distancesExact);
KFN akfn(dataset, false, false, 0.05);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
- akfn.Search(15, neighborsAprox, distancesAprox);
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
+ akfn.Search(15, neighborsApprox, distancesApprox);
- for (size_t i = 0; i < neighborsAprox.n_elem; i++)
- REQUIRE_RELATIVE_ERR(distancesAprox[i], distancesExact[i], 0.05);
+ for (size_t i = 0; i < neighborsApprox.n_elem; i++)
+ REQUIRE_RELATIVE_ERR(distancesApprox[i], distancesExact[i], 0.05);
}
/**
@@ -116,12 +116,12 @@ BOOST_AUTO_TEST_CASE(SingleTreeVsExact)
exact.Search(15, neighborsExact, distancesExact);
KFN akfn(dataset, false, true, 0.05);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
- akfn.Search(15, neighborsAprox, distancesAprox);
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
+ akfn.Search(15, neighborsApprox, distancesApprox);
- for (size_t i = 0; i < neighborsAprox.n_elem; i++)
- REQUIRE_RELATIVE_ERR(distancesAprox[i], distancesExact[i], 0.05);
+ for (size_t i = 0; i < neighborsApprox.n_elem; i++)
+ REQUIRE_RELATIVE_ERR(distancesApprox[i], distancesExact[i], 0.05);
}
/**
diff --git a/src/mlpack/tests/aknn_test.cpp b/src/mlpack/tests/aknn_test.cpp
index 4af732b..6a7f734 100644
--- a/src/mlpack/tests/aknn_test.cpp
+++ b/src/mlpack/tests/aknn_test.cpp
@@ -26,7 +26,7 @@ BOOST_AUTO_TEST_SUITE(AKNNTest);
*
* Errors are produced if the results are not according to relative error.
*/
-BOOST_AUTO_TEST_CASE(AproxVsExact1)
+BOOST_AUTO_TEST_CASE(ApproxVsExact1)
{
arma::mat dataset;
@@ -61,12 +61,12 @@ BOOST_AUTO_TEST_CASE(AproxVsExact1)
// Now perform the actual calculation.
aknn = new KNN(dataset, false, false, epsilon);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
- aknn->Search(dataset, 15, neighborsAprox, distancesAprox);
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
+ aknn->Search(dataset, 15, neighborsApprox, distancesApprox);
- for (size_t i = 0; i < neighborsAprox.n_elem; i++)
- REQUIRE_RELATIVE_ERR(distancesAprox(i), distancesExact(i), epsilon);
+ for (size_t i = 0; i < neighborsApprox.n_elem; i++)
+ REQUIRE_RELATIVE_ERR(distancesApprox(i), distancesExact(i), epsilon);
// Clean the memory.
delete aknn;
@@ -79,7 +79,7 @@ BOOST_AUTO_TEST_CASE(AproxVsExact1)
*
* Errors are produced if the results are not according to relative error.
*/
-BOOST_AUTO_TEST_CASE(AproxVsExact2)
+BOOST_AUTO_TEST_CASE(ApproxVsExact2)
{
arma::mat dataset;
@@ -92,12 +92,12 @@ BOOST_AUTO_TEST_CASE(AproxVsExact2)
exact.Search(15, neighborsExact, distancesExact);
KNN aknn(dataset, false, false, 0.05);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
- aknn.Search(15, neighborsAprox, distancesAprox);
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
+ aknn.Search(15, neighborsApprox, distancesApprox);
- for (size_t i = 0; i < neighborsAprox.n_elem; i++)
- REQUIRE_RELATIVE_ERR(distancesAprox(i), distancesExact(i), 0.05);
+ for (size_t i = 0; i < neighborsApprox.n_elem; i++)
+ REQUIRE_RELATIVE_ERR(distancesApprox(i), distancesExact(i), 0.05);
}
/**
@@ -106,7 +106,7 @@ BOOST_AUTO_TEST_CASE(AproxVsExact2)
*
* Errors are produced if the results are not according to relative error.
*/
-BOOST_AUTO_TEST_CASE(SingleTreeAproxVsExact)
+BOOST_AUTO_TEST_CASE(SingleTreeApproxVsExact)
{
arma::mat dataset;
@@ -119,12 +119,12 @@ BOOST_AUTO_TEST_CASE(SingleTreeAproxVsExact)
exact.Search(15, neighborsExact, distancesExact);
KNN aknn(dataset, false, true, 0.05);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
- aknn.Search(15, neighborsAprox, distancesAprox);
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
+ aknn.Search(15, neighborsApprox, distancesApprox);
- for (size_t i = 0; i < neighborsAprox.n_elem; i++)
- REQUIRE_RELATIVE_ERR(distancesAprox[i], distancesExact[i], 0.05);
+ for (size_t i = 0; i < neighborsApprox.n_elem; i++)
+ REQUIRE_RELATIVE_ERR(distancesApprox[i], distancesExact[i], 0.05);
}
/**
@@ -323,19 +323,20 @@ BOOST_AUTO_TEST_CASE(KNNModelTest)
if (j == 2)
models[i].BuildModel(std::move(referenceCopy), 20, true, false);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
- models[i].Search(std::move(queryCopy), 3, neighborsAprox, distancesAprox);
+ models[i].Search(std::move(queryCopy), 3, neighborsApprox,
+ distancesApprox);
- BOOST_REQUIRE_EQUAL(neighborsAprox.n_rows, neighborsExact.n_rows);
- BOOST_REQUIRE_EQUAL(neighborsAprox.n_cols, neighborsExact.n_cols);
- BOOST_REQUIRE_EQUAL(neighborsAprox.n_elem, neighborsExact.n_elem);
- BOOST_REQUIRE_EQUAL(distancesAprox.n_rows, distancesExact.n_rows);
- BOOST_REQUIRE_EQUAL(distancesAprox.n_cols, distancesExact.n_cols);
- BOOST_REQUIRE_EQUAL(distancesAprox.n_elem, distancesExact.n_elem);
- for (size_t k = 0; k < distancesAprox.n_elem; ++k)
- REQUIRE_RELATIVE_ERR(distancesAprox[k], distancesExact[k], 0.05);
+ BOOST_REQUIRE_EQUAL(neighborsApprox.n_rows, neighborsExact.n_rows);
+ BOOST_REQUIRE_EQUAL(neighborsApprox.n_cols, neighborsExact.n_cols);
+ BOOST_REQUIRE_EQUAL(neighborsApprox.n_elem, neighborsExact.n_elem);
+ BOOST_REQUIRE_EQUAL(distancesApprox.n_rows, distancesExact.n_rows);
+ BOOST_REQUIRE_EQUAL(distancesApprox.n_cols, distancesExact.n_cols);
+ BOOST_REQUIRE_EQUAL(distancesApprox.n_elem, distancesExact.n_elem);
+ for (size_t k = 0; k < distancesApprox.n_elem; ++k)
+ REQUIRE_RELATIVE_ERR(distancesApprox[k], distancesExact[k], 0.05);
}
}
}
@@ -384,19 +385,19 @@ BOOST_AUTO_TEST_CASE(KNNModelMonochromaticTest)
if (j == 1)
models[i].BuildModel(std::move(referenceCopy), 20, false, true, 0.05);
- arma::Mat<size_t> neighborsAprox;
- arma::mat distancesAprox;
+ arma::Mat<size_t> neighborsApprox;
+ arma::mat distancesApprox;
- models[i].Search(3, neighborsAprox, distancesAprox);
+ models[i].Search(3, neighborsApprox, distancesApprox);
- BOOST_REQUIRE_EQUAL(neighborsAprox.n_rows, neighborsExact.n_rows);
- BOOST_REQUIRE_EQUAL(neighborsAprox.n_cols, neighborsExact.n_cols);
- BOOST_REQUIRE_EQUAL(neighborsAprox.n_elem, neighborsExact.n_elem);
- BOOST_REQUIRE_EQUAL(distancesAprox.n_rows, distancesExact.n_rows);
- BOOST_REQUIRE_EQUAL(distancesAprox.n_cols, distancesExact.n_cols);
- BOOST_REQUIRE_EQUAL(distancesAprox.n_elem, distancesExact.n_elem);
- for (size_t k = 0; k < distancesAprox.n_elem; ++k)
- REQUIRE_RELATIVE_ERR(distancesAprox[k], distancesExact[k], 0.05);
+ BOOST_REQUIRE_EQUAL(neighborsApprox.n_rows, neighborsExact.n_rows);
+ BOOST_REQUIRE_EQUAL(neighborsApprox.n_cols, neighborsExact.n_cols);
+ BOOST_REQUIRE_EQUAL(neighborsApprox.n_elem, neighborsExact.n_elem);
+ BOOST_REQUIRE_EQUAL(distancesApprox.n_rows, distancesExact.n_rows);
+ BOOST_REQUIRE_EQUAL(distancesApprox.n_cols, distancesExact.n_cols);
+ BOOST_REQUIRE_EQUAL(distancesApprox.n_elem, distancesExact.n_elem);
+ for (size_t k = 0; k < distancesApprox.n_elem; ++k)
+ REQUIRE_RELATIVE_ERR(distancesApprox[k], distancesExact[k], 0.05);
}
}
}
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