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Write tests related to SamplingSVE #39

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merged 5 commits into from
Dec 10, 2024
Merged

Write tests related to SamplingSVE #39

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52fcaa5
Define default constructor
terasakisatoshi Dec 10, 2024
dc396bd
Add comments
terasakisatoshi Dec 10, 2024
0bd4688
don't use shared_ptr
terasakisatoshi Dec 10, 2024
9afd981
create an instance of SamplingSVE
terasakisatoshi Dec 10, 2024
5b914f8
update
terasakisatoshi Dec 10, 2024
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4 changes: 4 additions & 0 deletions include/sparseir/gauss.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -46,8 +46,12 @@ class Rule {
// TODO: Define x and w as Eigen::VectorXd
std::vector<T> x, w, x_forward, x_backward;
T a, b;
// Default constructor
Rule() {};
// Constructor with x, w, x_forward, x_backward, a, b
Rule(const std::vector<T>& x, const std::vector<T>& w, std::vector<T> x_forward, std::vector<T> x_backward, T a = -1, T b = 1)
: x(x), w(w), x_forward(x_forward), x_backward(x_backward), a(a), b(b) {}
// Constructor with x, w, a, b
Rule(const std::vector<T>& x, const std::vector<T>& w, T a = -1, T b = 1)
: x(x), w(w), a(a), b(b) {
this->x_forward = x_forward.empty() ? std::vector<T>(x.size(), 0) : x_forward;
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22 changes: 11 additions & 11 deletions include/sparseir/sve.hpp
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Expand Up @@ -130,7 +130,7 @@ class AbstractSVE {
template <typename K, typename T = double>
class SamplingSVE : public AbstractSVE<K, T> {
public:
std::shared_ptr<const K> kernel;
K kernel;
double epsilon;
int n_gauss;
int nsvals_hint;
Expand All @@ -142,25 +142,25 @@ class SamplingSVE : public AbstractSVE<K, T> {
Rule<T> gauss_y;

// Constructor
SamplingSVE(std::shared_ptr<const K> kernel_, double epsilon_, int n_gauss_ = -1)
SamplingSVE(K kernel_, double epsilon_, int n_gauss_ = -1)
: kernel(kernel_),
epsilon(epsilon_),
n_gauss((n_gauss_ > 0) ? n_gauss_ : sve_hints(*kernel, epsilon).ngauss()),
rule(convert<T>(legendre(n_gauss))),
gauss_x(rule.piecewise(segs_x)), // Initialize gauss_x
gauss_y(rule.piecewise(segs_y)) // Initialize gauss_y
epsilon(epsilon_)
{
auto hints = sve_hints(*kernel, epsilon);
// TODO: This is not correct, we need to use the segments from the hints
n_gauss = (n_gauss_ > 0) ? n_gauss_ : sve_hints(kernel, epsilon).ngauss();
// TODO: Implement Rule<T>(n_gauss)
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TODO

rule = convert<T>(legendre(n_gauss));
auto hints = sve_hints(kernel, epsilon);
nsvals_hint = hints.nsvals();
segs_x = hints.template segments_x<T>();
segs_y = hints.template segments_y<T>();
gauss_x = rule.piecewise(segs_x);
gauss_y = rule.piecewise(segs_y);
}

// Compute matrices for SVD
std::vector<Eigen::MatrixX<T>> matrices() const override {
std::vector<Eigen::MatrixX<T>> mats;
Eigen::MatrixX<T> A = matrix_from_gauss(*kernel, gauss_x, gauss_y);
Eigen::MatrixX<T> A = matrix_from_gauss(kernel, gauss_x, gauss_y);
// Element-wise multiplication with square roots of weights
for (int i = 0; i < gauss_x.w.size(); ++i)
{
Expand Down Expand Up @@ -304,7 +304,7 @@ class SamplingSVE : public AbstractSVE<K, T> {
PiecewiseLegendrePolyVector ulx(polyvec_u);
PiecewiseLegendrePolyVector vly(polyvec_v);
canonicalize(ulx, vly);
return SVEResult<K>(ulx, s, vly, *kernel, epsilon);
return SVEResult<K>(ulx, s, vly, kernel, epsilon);
}
};

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36 changes: 25 additions & 11 deletions test/sve.cxx
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Expand Up @@ -13,8 +13,6 @@

using std::invalid_argument;

using xprec::DDouble;

// Function to check smoothness
void check_smooth(const std::function<double(double)>& u, const std::vector<double>& s, double uscale, double fudge_factor) {
/*
Expand Down Expand Up @@ -58,15 +56,31 @@ void check_smooth(const std::function<double(double)>& u, const std::vector<doub

TEST_CASE("AbstractSVE", "[sve]"){
sparseir::LogisticKernel lk(10.0);
//auto sve = sparseir::compute_sve(lk);
//REQUIRE(true);
// auto sve = sparseir::SamplingSVE<sparseir::LogisticKernel, double>(std::make_shared<sparseir::LogisticKernel>(sparseir::LogisticKernel(10.0)), 1e-6);
// REQUIRE(sve.nsvals_hint == 10);
// REQUIRE(sve.n_gauss == 10);
// REQUIRE(sve.segs_x.size() == 10);
// REQUIRE(sve.segs_y.size() == 10);
// REQUIRE(sve.gauss_x.size() == 10);
// REQUIRE(sve.gauss_y.size() == 10);
auto hints = sparseir::sve_hints(lk, 1e-6);
int nsvals_hint = hints.nsvals();
int n_gauss = hints.ngauss();
std::vector<double> segs_x = hints.template segments_x<double>();
std::vector<double> segs_y = hints.template segments_y<double>();

// Ensure `convert` is declared before this line
sparseir::Rule<double> rule = sparseir::convert<double>(sparseir::legendre(n_gauss));

sparseir::Rule<double> gauss_x = rule.piecewise(segs_x);
sparseir::Rule<double> gauss_y = rule.piecewise(segs_y);
auto ssve1 = sparseir::SamplingSVE<sparseir::LogisticKernel>(lk, 1e-6);
REQUIRE(ssve1.n_gauss == n_gauss);
auto ssve2 = sparseir::SamplingSVE<sparseir::LogisticKernel>(lk, 1e-6, 12);
REQUIRE(ssve2.n_gauss == 12);

auto ssve1_double = sparseir::SamplingSVE<sparseir::LogisticKernel, double>(lk, 1e-6);
REQUIRE(ssve1_double.n_gauss == n_gauss);
auto ssve2_double = sparseir::SamplingSVE<sparseir::LogisticKernel, double>(lk, 1e-6, 12);
REQUIRE(ssve2_double.n_gauss == 12);

//auto ssve1_ddouble = sparseir::SamplingSVE<sparseir::LogisticKernel, xprec::DDouble>(lk, 1e-6);
//REQUIRE(ssve1_ddouble.n_gauss == n_gauss);
//auto ssve2_ddouble = sparseir::SamplingSVE<sparseir::LogisticKernel, xprec::DDouble>(lk, 1e-6, 12);
//REQUIRE(ssve2_ddouble.n_gauss == 12);
}

TEST_CASE("sve.cpp", "[sve]")
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