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/***************************************************************************
* Copyright (c) Johan Mabille, Sylvain Corlay, Wolf Vollprecht and *
* Martin Renou *
* Copyright (c) QuantStack *
* Copyright (c) Serge Guelton *
* *
* Distributed under the terms of the BSD 3-Clause License. *
* *
* The full license is in the file LICENSE, distributed with this software. *
****************************************************************************/
#include "xsimd/xsimd.hpp"
#ifndef XSIMD_NO_SUPPORTED_ARCHITECTURE
#include "test_utils.hpp"
template <class B>
struct complex_exponential_test
{
using batch_type = B;
using real_batch_type = typename B::real_batch;
using value_type = typename B::value_type;
using real_value_type = typename value_type::value_type;
static constexpr size_t size = B::size;
using vector_type = std::vector<value_type>;
size_t nb_input;
vector_type exp_input;
vector_type huge_exp_input;
vector_type log_input;
vector_type expected;
vector_type res;
complex_exponential_test()
{
nb_input = 10000 * size;
exp_input.resize(nb_input);
huge_exp_input.resize(nb_input);
log_input.resize(nb_input);
for (size_t i = 0; i < nb_input; ++i)
{
exp_input[i] = value_type(real_value_type(-1.5) + i * real_value_type(3) / nb_input,
real_value_type(-1.3) + i * real_value_type(2) / nb_input);
huge_exp_input[i] = value_type(real_value_type(0), real_value_type(102.12) + i * real_value_type(100.) / nb_input);
log_input[i] = value_type(real_value_type(0.001 + i * 100 / nb_input),
real_value_type(0.002 + i * 110 / nb_input));
}
expected.resize(nb_input);
res.resize(nb_input);
}
void test_exp()
{
std::transform(exp_input.cbegin(), exp_input.cend(), expected.begin(),
[](const value_type& v)
{ using std::exp; return exp(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, exp_input, i);
out = exp(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_expm1()
{
std::transform(exp_input.cbegin(), exp_input.cend(), expected.begin(),
[](const value_type& v)
{ using xsimd::expm1; return expm1(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, exp_input, i);
out = expm1(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_huge_exp()
{
std::transform(huge_exp_input.cbegin(), huge_exp_input.cend(), expected.begin(),
[](const value_type& v)
{ using std::exp; return exp(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, huge_exp_input, i);
out = exp(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_log()
{
std::transform(log_input.cbegin(), log_input.cend(), expected.begin(),
[](const value_type& v)
{ using std::log; return log(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, log_input, i);
out = log(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_log2()
{
std::transform(log_input.cbegin(), log_input.cend(), expected.begin(),
[](const value_type& v)
{ using xsimd::log2; return log2(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, log_input, i);
out = log2(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_log10()
{
std::transform(log_input.cbegin(), log_input.cend(), expected.begin(),
[](const value_type& v)
{ using std::log10; return log10(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, log_input, i);
out = log10(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_log1p()
{
std::transform(log_input.cbegin(), log_input.cend(), expected.begin(),
[](const value_type& v)
{ using xsimd::log1p; return log1p(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, log_input, i);
out = log1p(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
void test_sign()
{
std::transform(log_input.cbegin(), log_input.cend(), expected.begin(),
[](const value_type& v)
{ using xsimd::sign; return sign(v); });
batch_type in, out;
for (size_t i = 0; i < nb_input; i += size)
{
detail::load_batch(in, log_input, i);
out = sign(in);
detail::store_batch(out, res, i);
}
size_t diff = detail::get_nb_diff(res, expected);
CHECK_EQ(diff, 0);
}
};
TEST_CASE_TEMPLATE("[complex exponential]", B, BATCH_COMPLEX_TYPES)
{
complex_exponential_test<B> Test;
SUBCASE("exp")
{
Test.test_exp();
}
SUBCASE("expm1")
{
Test.test_expm1();
}
SUBCASE("huge_exp")
{
Test.test_huge_exp();
}
SUBCASE("log")
{
Test.test_log();
}
SUBCASE("log2")
{
Test.test_log2();
}
SUBCASE("log10")
{
Test.test_log10();
}
SUBCASE("log1p")
{
Test.test_log1p();
}
SUBCASE("sign")
{
Test.test_sign();
}
}
#endif
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