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/*******************************************************
* Copyright (c) 2015, ArrayFire
* All rights reserved.
*
* This file is distributed under 3-clause BSD license.
* The complete license agreement can be obtained at:
* http://arrayfire.com/licenses/BSD-3-Clause
********************************************************/
#include <gtest/gtest.h>
#include <arrayfire.h>
#include <af/dim4.hpp>
#include <af/traits.hpp>
#include <string>
#include <vector>
#include <testHelpers.hpp>
using std::string;
using std::vector;
template<typename T>
class GaussianKernel : public ::testing::Test
{
public:
virtual void SetUp() {}
};
// create a list of types to be tested
typedef ::testing::Types<float> TestTypes;
// register the type list
TYPED_TEST_CASE(GaussianKernel, TestTypes);
template<typename T>
void gaussianKernelTest(string pFileName, double sigma)
{
if (noDoubleTests<T>()) return;
vector<af::dim4> numDims;
vector<vector<int> > in;
vector<vector<T> > tests;
readTestsFromFile<int,T>(pFileName, numDims, in, tests);
af_array outArray = 0;
vector<int> input(in[0].begin(), in[0].end());
ASSERT_EQ(AF_SUCCESS, af_gaussian_kernel(&outArray, input[0], input[1], sigma, sigma));
dim_t outElems = 0;
ASSERT_EQ(AF_SUCCESS, af_get_elements(&outElems, outArray));
T *outData = new T[outElems];
ASSERT_EQ(AF_SUCCESS, af_get_data_ptr((void*)outData, outArray));
vector<T> currGoldBar(tests[0].begin(), tests[0].end());
size_t nElems = currGoldBar.size();
ASSERT_EQ(outElems, (dim_t)nElems);
for (size_t elIter=0; elIter<nElems; ++elIter) {
ASSERT_NEAR(currGoldBar[elIter], outData[elIter], 1.0e-3)<< "at: " << elIter<< std::endl;
}
delete[] outData;
ASSERT_EQ(AF_SUCCESS, af_release_array(outArray));
}
TYPED_TEST(GaussianKernel, Small1D)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss1_7.test"), 0.0);
}
TYPED_TEST(GaussianKernel, Large1D)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss1_15.test"), 0.0);
}
TYPED_TEST(GaussianKernel, Small1DWithSigma)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss1_7_sigma1.test"), 1.0);
}
TYPED_TEST(GaussianKernel, SmallSmall2D)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss2_7x7.test"), 0.0);
}
TYPED_TEST(GaussianKernel, LargeSmall2D)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss2_15x7.test"), 0.0);
}
TYPED_TEST(GaussianKernel, LargeLarge2D)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss2_15x15.test"), 0.0);
}
TYPED_TEST(GaussianKernel, SmallSmall2DWithSigma)
{
gaussianKernelTest<TypeParam>(string(TEST_DIR"/gaussian/gauss2_7x7_sigma1.test"), 1.0);
}
//////////////////////////////// CPP ////////////////////////////////////
// test mean_all interface using cpp api
#include <iostream>
void gaussianKernelTestCPP(string pFileName, double sigma)
{
using af::array;
using af::gaussianKernel;
vector<af::dim4> numDims;
vector<vector<int> > in;
vector<vector<float> > tests;
readTestsFromFile<int,float>(pFileName, numDims, in, tests);
vector<int> input(in[0].begin(), in[0].end());
array out = gaussianKernel(input[0], input[1], sigma, sigma);
dim_t outElems = out.elements();
float *outData = new float[outElems];
out.host(outData);
vector<float> currGoldBar(tests[0].begin(), tests[0].end());
size_t nElems = currGoldBar.size();
ASSERT_EQ(outElems, (dim_t)nElems);
for (size_t elIter=0; elIter<nElems; ++elIter) {
ASSERT_NEAR(currGoldBar[elIter], outData[elIter], 1.0e-3)<< "at: " << elIter<< std::endl;
}
delete[] outData;
}
TEST(GaussianKernel, Small1D_CPP)
{
gaussianKernelTestCPP(string(TEST_DIR"/gaussian/gauss1_7.test"), 0.0);
}
TEST(GaussianKernel, Small1DWithSigma_CPP)
{
gaussianKernelTestCPP(string(TEST_DIR"/gaussian/gauss1_7_sigma1.test"), 1.0);
}
TEST(GaussianKernel, SmallSmall2D_CPP)
{
gaussianKernelTestCPP(string(TEST_DIR"/gaussian/gauss2_7x7.test"), 0.0);
}
TEST(GaussianKernel, SmallSmall2DWithSigma_CPP)
{
gaussianKernelTestCPP(string(TEST_DIR"/gaussian/gauss2_7x7_sigma1.test"), 1.0);
}
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