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#include <catch2/catch_all.hpp>
#include <numeric>
#include <random>
#include <utility>
#include "sopt/maths.h"
#include "sopt/relative_variation.h"
#include "sopt/sampling.h"
#include "sopt/types.h"
using Catch::Approx;
TEST_CASE("Projector on positive quadrant", "[utility][project]") {
using namespace sopt;
SECTION("Real matrix") {
Image<> input = Image<>::Ones(5, 5) + Image<>::Random(5, 5) * 0.55;
input(1, 1) *= -1;
input(3, 2) *= -1;
auto const expr = positive_quadrant(input);
CAPTURE(input);
CAPTURE(expr);
CHECK(expr(1, 1) == Approx(0));
CHECK(expr(3, 2) == Approx(0));
auto value = expr.eval();
CHECK(value(1, 1) == Approx(0));
CHECK(value(3, 2) == Approx(0));
value(1, 1) = input(1, 1);
value(3, 2) = input(3, 2);
CHECK(value.isApprox(input));
}
SECTION("Complex matrix") {
Image<t_complex> input = Image<t_complex>::Ones(5, 5) + Image<t_complex>::Random(5, 5) * 0.55;
input.real()(1, 1) *= -1;
input.real()(3, 2) *= -1;
auto const expr = positive_quadrant(input);
CAPTURE(input);
CAPTURE(expr);
CHECK(expr.imag().isApprox(Image<>::Zero(5, 5)));
auto value = expr.eval();
CHECK(value.real()(1, 1) == Approx(0));
CHECK(value.real()(3, 2) == Approx(0));
value(1, 1) = input.real()(1, 1);
value(3, 2) = input.real()(3, 2);
CHECK(value.real().isApprox(input.real()));
CHECK(value.imag().isApprox(0e0 * input.real()));
}
}
TEST_CASE("Weighted l1 norm", "[utility][l1]") {
sopt::Array<> weight(4);
weight << 1, 2, 3, 4;
SECTION("Real valued") {
sopt::Array<> input(4);
input << 5, -6, 7, -8;
CHECK(sopt::l1_norm(input, weight) == Approx(5 + 12 + 21 + 32));
}
SECTION("Complex valued") {
sopt::t_complex const i(0, 1);
sopt::Array<sopt::t_complex> input(4);
input << 5. + 5. * i, 6. + 6. * i, 7. + 7. * i, 8. + 8. * i;
CHECK(sopt::l1_norm(input, weight) == Approx(std::sqrt(2) * (5 + 12 + 21 + 32)));
}
}
TEST_CASE("Soft threshhold", "[utility][threshhold]") {
sopt::Array<> input(6);
input << 1e1, 2e1, 3e1, 4e1, 1e4, 2e4;
SECTION("Single-valued threshhold") {
// check thresshold
CHECK(sopt::soft_threshhold(input, 1.1e1)(0) == Approx(0));
CHECK(not(sopt::soft_threshhold(input, 1.1e1)(1) == Approx(0)));
// check linearity
auto a = sopt::soft_threshhold(input, 9e0)(0);
auto b = sopt::soft_threshhold(input, 4.5e0)(0);
auto c = sopt::soft_threshhold(input, 2.25e0)(0);
CAPTURE(b - a);
CAPTURE(c - b);
CHECK((b - a) == Approx(2 * (c - b)));
}
SECTION("Multi-values threshhold") {
using namespace sopt;
Array<> threshhold(6);
input[2] *= -1;
threshhold << 1.1e1, 1.1e1, 1e0, 4.5, 2.25, 2.26;
SECTION("Real input") {
Array<> const actual = soft_threshhold(input, threshhold);
CHECK(actual(0) == 0e0);
CHECK(actual(1) == input(1) - threshhold(1));
CHECK(actual(2) == input(2) + threshhold(2));
CHECK(actual(3) == input(3) - threshhold(3));
#ifdef CATCH_HAS_THROWS_AS
CHECK_THROWS_AS(soft_threshhold(input, threshhold.head(2)), sopt::Exception);
#endif
}
SECTION("Complex input") {
Array<t_complex> const actual = soft_threshhold(input.cast<t_complex>(), threshhold);
CHECK(actual(0) == 0e0);
CHECK(actual(1) == input(1) - threshhold(1));
CHECK(actual(2) == input(2) + threshhold(2));
CHECK(actual(3) == input(3) - threshhold(3));
#ifdef CATCH_HAS_THROWS_AS
CHECK_THROWS_AS(soft_threshhold(input, threshhold.head(2)), sopt::Exception);
#endif
}
}
}
TEST_CASE("Sampling", "[utility][sampling]") {
using t_Vector = sopt::Vector<int>;
t_Vector const input = t_Vector::Random(12);
sopt::Sampling const sampling(12, {1, 3, 6, 5});
t_Vector down = t_Vector::Zero(4);
sampling(down, input);
CHECK(down.size() == 4);
CHECK(down(0) == input(1));
CHECK(down(1) == input(3));
CHECK(down(2) == input(6));
CHECK(down(3) == input(5));
t_Vector up = t_Vector::Zero(input.size());
sampling.adjoint(up, down);
CHECK(up(1) == input(1));
CHECK(up(3) == input(3));
CHECK(up(6) == input(6));
CHECK(up(5) == input(5));
up(1) = 0;
up(3) = 0;
up(6) = 0;
up(5) = 0;
CHECK(up == t_Vector::Zero(up.size()));
}
TEST_CASE("Relative variation", "[utility][convergence]") {
sopt::RelativeVariation<double> relvar(1e-8);
sopt::Array<> const input = sopt::Array<>::Random(6);
CHECK(not relvar(input));
CHECK(relvar(input));
CHECK(relvar(input + relvar.tolerance() * 0.5 / 6. * sopt::Array<>::Random(6)));
CHECK(not relvar(input + relvar.tolerance() * 1.1 * sopt::Array<>::Ones(6)));
}
TEST_CASE("Scalar elative variation", "[utility][convergence]") {
sopt::ScalarRelativeVariation<double> relvar(1e-8, 1e-8, "Yo");
sopt::t_real const input = sopt::Array<>::Random(1)(0);
CHECK(not relvar(input));
CHECK(relvar(input));
CHECK(not relvar(input + 0.1));
CHECK(relvar(input + 0.1 + 0.1 * relvar.relative_tolerance()));
}
TEST_CASE("Standard deviation", "[utility]") {
sopt::Array<sopt::t_complex> input = sopt::Array<sopt::t_complex>::Random(6) + 1e0;
sopt::t_complex const mean = input.mean();
sopt::t_real stddev = 0e0;
for (sopt::Vector<>::Index i(0); i < input.size(); ++i)
stddev += std::real(std::conj(input(i) - mean) * (input(i) - mean));
stddev = std::sqrt(stddev) / std::sqrt(static_cast<sopt::t_real>(input.size()));
CHECK(std::abs(sopt::standard_deviation(input) - stddev) < 1e-8);
CHECK(std::abs(sopt::standard_deviation(input.matrix()) - stddev) < 1e-8);
}
// Checks type traits work
static_assert(not sopt::details::HasValueType<double>::value, "");
static_assert(not sopt::details::HasValueType<std::pair<double, int>>::value, "");
static_assert(sopt::details::HasValueType<std::complex<double>>::value, "");
static_assert(sopt::details::HasValueType<sopt::Image<sopt::t_complex>::Scalar>::value, "");
static_assert(std::is_same<sopt::real_type<sopt::t_real>::type, sopt::t_real>::value, "");
static_assert(std::is_same<sopt::real_type<sopt::t_complex>::type, sopt::t_real>::value, "");
static_assert(sopt::is_complex<std::complex<double>>::value, "Testing is_complex");
static_assert(sopt::is_complex<std::complex<int>>::value, "Testing is_complex");
static_assert(not sopt::is_complex<double>::value, "Testing is_complex");
static_assert(not sopt::is_complex<sopt::Vector<double>>::value, "Testing is_complex");
static_assert(not sopt::is_complex<sopt::Vector<std::complex<int>>>::value, "Testing is_complex");
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