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Merge pull request #25 from SpM-lab/terasaki/namespace
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Wrap code in sparseir namespace and resolve errors
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@terasakisatoshi
terasakisatoshi authored Nov 14, 2024
2 parents c5988dc + a8a4ede commit faa45a3
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Showing 10 changed files with 114 additions and 93 deletions.
6 changes: 5 additions & 1 deletion include/sparseir/_linalg.hpp
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Expand Up @@ -9,6 +9,8 @@

#include "xprec/ddouble.hpp"

namespace sparseir{

using Eigen::Dynamic;
using Eigen::Matrix;
using Eigen::MatrixX;
Expand Down Expand Up @@ -709,4 +711,6 @@ SVDResult<T> svd_jacobi(Matrix<T, Dynamic, Dynamic>& U, T rtol = std::numeric_li
U.array().rowwise() /= s.transpose().array();

return SVDResult<T> {U, s, VT};
}
}

} // namespace sparseir
40 changes: 22 additions & 18 deletions include/sparseir/_root.hpp
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Expand Up @@ -4,6 +4,7 @@
#include <functional>
#include <bitset>

namespace sparseir {

template <typename T>
T midpoint(T lo, T hi) {
Expand Down Expand Up @@ -114,6 +115,26 @@ std::vector<T> refine_grid(const std::vector<T>& grid, int alpha) {
return newgrid;
}


template <typename F, typename T>
T bisect_discr_extremum(F absf, T a, T b, double absf_a, double absf_b) {
T d = b - a;

if (d <= 1) return absf_a > absf_b ? a : b;
if (d == 2) return a + 1;

T m = midpoint(a, b);
T n = m + 1;
double absf_m = absf(m);
double absf_n = absf(n);

if (absf_m > absf_n) {
return bisect_discr_extremum(absf, a, n, absf_a, absf_n);
} else {
return bisect_discr_extremum(absf, m, b, absf_m, absf_b);
}
}

template <typename F, typename T>
std::vector<T> discrete_extrema(F f, const std::vector<T>& xgrid) {
std::vector<double> fx(xgrid.size());
Expand Down Expand Up @@ -170,21 +191,4 @@ std::vector<T> discrete_extrema(F f, const std::vector<T>& xgrid) {
return res;
}

template <typename F, typename T>
T bisect_discr_extremum(F absf, T a, T b, double absf_a, double absf_b) {
T d = b - a;

if (d <= 1) return absf_a > absf_b ? a : b;
if (d == 2) return a + 1;

T m = midpoint(a, b);
T n = m + 1;
double absf_m = absf(m);
double absf_n = absf(n);

if (absf_m > absf_n) {
return bisect_discr_extremum(absf, a, n, absf_a, absf_n);
} else {
return bisect_discr_extremum(absf, m, b, absf_m, absf_b);
}
}
} // namespace sparseir
4 changes: 4 additions & 0 deletions include/sparseir/_specfuncs.hpp
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Expand Up @@ -4,6 +4,8 @@
#include <vector>
#include <stdexcept>

namespace sparseir {

using Eigen::Matrix;
using Eigen::Dynamic;

Expand Down Expand Up @@ -83,3 +85,5 @@ Matrix<T, Dynamic, Dynamic> legder(Matrix<T, Dynamic, Dynamic> c, int cnt = 1) {
}
return c;
}

} // namespace sparseir
6 changes: 5 additions & 1 deletion include/sparseir/freq.hpp
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Expand Up @@ -7,6 +7,8 @@
#include <type_traits>
#include <iostream>

namespace sparseir {

// Base abstract class for Statistics
class Statistics
{
Expand Down Expand Up @@ -123,4 +125,6 @@ inline void show(std::ostream &os, const MatsubaraFreq<S> &a)
os << "-π/β";
else
os << a.get_n() << "π/β";
}
}

} // namespace sparseir
4 changes: 4 additions & 0 deletions include/sparseir/gauss.hpp
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Expand Up @@ -8,6 +8,8 @@
#include <Eigen/Dense>
#include <xprec/ddouble-header-only.hpp>

namespace sparseir {

using namespace Eigen;
using xprec::DDouble;

Expand Down Expand Up @@ -189,3 +191,5 @@ Matrix<T, Dynamic, Dynamic> legendre_collocation(const Rule<T>& rule, int n = -1

return res;
}

} // namespace sparseir
62 changes: 31 additions & 31 deletions test/_linalg.cxx
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Expand Up @@ -10,7 +10,7 @@ using namespace xprec;
TEST_CASE("invperm", "[linalg]") {
VectorXi a(3);
a << 1, 2, 0;
VectorXi b = invperm(a);
VectorXi b = sparseir::invperm(a);
VectorX<int> refb(3);
refb << 2, 0, 1;
REQUIRE(b.isApprox(refb));
Expand All @@ -21,7 +21,7 @@ TEST_CASE("reflector", "[linalg]") {
{
Eigen::VectorXd v(3);
v << 1, 2, 3;
auto tau = reflector(v);
auto tau = sparseir::reflector(v);

Eigen::VectorXd refv(3);
// obtained by
Expand All @@ -36,7 +36,7 @@ TEST_CASE("reflector", "[linalg]") {
{
Eigen::VectorX<DDouble> v(3);
v << 1, 2, 3;
auto tau = reflector(v);
auto tau = sparseir::reflector(v);

Eigen::VectorX<DDouble> refv(3);
refv << -3.7416574, 0.42179344, 0.63269017;
Expand Down Expand Up @@ -86,7 +86,7 @@ TEST_CASE("reflectorApply", "[linalg]") {

auto Ainp = A.col(i).tail(m - i);
REQUIRE(Ainp.size() == 3);
auto tau_i = reflector(Ainp);
auto tau_i = sparseir::reflector(Ainp);
REQUIRE(std::abs(tau_i - 1.5773502691896257) < 1e-7);

Eigen::VectorX<double> refv(3);
Expand All @@ -96,7 +96,7 @@ TEST_CASE("reflectorApply", "[linalg]") {
}

auto block = A.bottomRightCorner(m - i, n - (i + 1));
reflectorApply(Ainp, tau_i, block);
sparseir::reflectorApply(Ainp, tau_i, block);
Eigen::MatrixX<double> refA(3, 3);
refA <<-1.7320508075688772, -1.7320508075688772, -1.7320508075688772,
0.36602540378443865, 0.0, 0.0,
Expand Down Expand Up @@ -124,7 +124,7 @@ TEST_CASE("Jacobi SVD", "[linalg]") {
REQUIRE((A - Areconst).norm()/A.norm() < 1e-28); // 28 significant digits
}

TEST_CASE("rrqr simple", "[linalg]") {
TEST_CASE("sparseir::rrqr simple", "[linalg]") {
Eigen::MatrixX<double> Aorig(3,3);
Aorig << 1, 1, 1,
1, 1, 1,
Expand All @@ -136,9 +136,9 @@ TEST_CASE("rrqr simple", "[linalg]") {

double A_eps = A.norm() * std::numeric_limits<double>::epsilon();
double rtol = 0.1;
QRPivoted<double> A_qr;
sparseir::QRPivoted<double> A_qr;
int A_rank;
std::tie(A_qr, A_rank) = rrqr<double>(A);
std::tie(A_qr, A_rank) = sparseir::rrqr<double>(A);
REQUIRE(A_rank == 1);
Eigen::MatrixX<double> refA(3, 3);
refA <<-1.7320508075688772, -1.7320508075688772, -1.7320508075688772,
Expand All @@ -153,7 +153,7 @@ TEST_CASE("rrqr simple", "[linalg]") {
REQUIRE(A_qr.taus.isApprox(reftaus, 1e-7));
REQUIRE(A_qr.jpvt == refjpvt);

QRPackedQ<double> Q = getPropertyQ(A_qr);
sparseir::QRPackedQ<double> Q = sparseir::getPropertyQ(A_qr);
Eigen::VectorX<double> Qreftaus(3);
Qreftaus << 1.5773502691896257, 0.0, 0.0;
Eigen::MatrixX<double> Qreffactors(3, 3);
Expand Down Expand Up @@ -182,35 +182,35 @@ TEST_CASE("rrqr simple", "[linalg]") {
// In C++ Q.factors * R

MatrixX<double> C(3, 3);
mul<double>(C, Q, R);
sparseir::mul<double>(C, Q, R);
MatrixX<double> A_rec = C * P.transpose();

REQUIRE(A_rec.isApprox(Aorig, 4 * A_eps));
}

TEST_CASE("RRQR", "[linalg]") {
TEST_CASE("sparseir::RRQR", "[linalg]") {
MatrixX<DDouble> Aorig = MatrixX<DDouble>::Random(40, 30);
MatrixX<DDouble> A = Aorig;
DDouble A_eps = A.norm() * std::numeric_limits<DDouble>::epsilon();
QRPivoted<DDouble> A_qr;
sparseir::QRPivoted<DDouble> A_qr;
int A_rank;

std::tie(A_qr, A_rank) = rrqr(A);
std::tie(A_qr, A_rank) = sparseir::rrqr(A);

REQUIRE(A_rank == 30);
QRPackedQ<DDouble> Q = getPropertyQ(A_qr);
sparseir::QRPackedQ<DDouble> Q = sparseir::getPropertyQ(A_qr);
Eigen::MatrixX<DDouble> R = getPropertyR(A_qr);
MatrixX<DDouble> P = getPropertyP(A_qr);

// In Julia Q * R
// In C++ Q.factors * R
MatrixX<DDouble> C(40, 30);
mul<DDouble>(C, Q, R);
sparseir::mul<DDouble>(C, Q, R);
MatrixX<DDouble> A_rec = C * P.transpose();
REQUIRE(A_rec.isApprox(Aorig, 4 * A_eps));
}

TEST_CASE("RRQR Trunc", "[linalg]") {
TEST_CASE("sparseir::RRQR Trunc", "[linalg]") {
// double
{
VectorX<double> x = VectorX<double>::LinSpaced(101, -1, 1);
Expand All @@ -222,12 +222,12 @@ TEST_CASE("RRQR Trunc", "[linalg]") {
MatrixX<double> A = Aorig;
int m = A.rows();
int n = A.cols();
QRPivoted<double> A_qr;
sparseir::QRPivoted<double> A_qr;
int k;
std::tie(A_qr, k) = rrqr<double>(A, double(1e-5));
std::tie(A_qr, k) = sparseir::rrqr<double>(A, double(1e-5));
REQUIRE(k < std::min(m, n));
REQUIRE(k == 17);
auto QR = truncate_qr_result<double>(A_qr, k);
auto QR = sparseir::truncate_qr_result<double>(A_qr, k);
auto Q = QR.first;
auto R = QR.second;

Expand All @@ -248,12 +248,12 @@ TEST_CASE("RRQR Trunc", "[linalg]") {
MatrixX<DDouble> A = Aorig;
int m = A.rows();
int n = A.cols();
QRPivoted<DDouble> A_qr;
sparseir::QRPivoted<DDouble> A_qr;
int k;
std::tie(A_qr, k) = rrqr<DDouble>(A, DDouble(0.00001));
std::tie(A_qr, k) = sparseir::rrqr<DDouble>(A, DDouble(0.00001));
REQUIRE(k < std::min(m, n));
REQUIRE(k == 17);
auto QR = truncate_qr_result<DDouble>(A_qr, k);
auto QR = sparseir::truncate_qr_result<DDouble>(A_qr, k);
auto Q = QR.first;
auto R = QR.second;
REQUIRE(Q.rows() == m);
Expand Down Expand Up @@ -284,8 +284,8 @@ TEST_CASE("TSVD", "[linalg]") {

MatrixX<double> A = Aorig; // create a copy of Aorig

auto tsvd_result = tsvd<double>(A, double(tol));
tsvd<double>(Aorig, double(tol));
auto tsvd_result = sparseir::tsvd<double>(A, double(tol));
sparseir::tsvd<double>(Aorig, double(tol));
auto U = std::get<0>(tsvd_result);
auto s = std::get<1>(tsvd_result);
auto V = std::get<2>(tsvd_result);
Expand Down Expand Up @@ -313,8 +313,8 @@ TEST_CASE("TSVD", "[linalg]") {
}

TEST_CASE("SVD of VERY triangular 2x2", "[linalg]") {
// auto [cu, su, smax, smin, cv, sv] = svd2x2(DDouble(1), DDouble(1e100), DDouble(1));
auto svd_result = svd2x2<DDouble>(DDouble(1), DDouble(1e100), DDouble(1));
// auto [cu, su, smax, smin, cv, sv] = sparseir::svd2x2(DDouble(1), DDouble(1e100), DDouble(1));
auto svd_result = sparseir::svd2x2<DDouble>(DDouble(1), DDouble(1e100), DDouble(1));
auto cu = std::get<0>(std::get<0>(svd_result));
auto su = std::get<1>(std::get<0>(svd_result));
auto smax = std::get<0>(std::get<1>(svd_result));
Expand All @@ -335,7 +335,7 @@ TEST_CASE("SVD of VERY triangular 2x2", "[linalg]") {
A << DDouble(1), DDouble(1e100), DDouble(0), DDouble(1);
REQUIRE((U * S * Vt).isApprox(A));

svd_result = svd2x2(DDouble(1), DDouble(1e100), DDouble(1e100));
svd_result = sparseir::svd2x2(DDouble(1), DDouble(1e100), DDouble(1e100));

cu = std::get<0>(std::get<0>(svd_result));
su = std::get<1>(std::get<0>(svd_result));
Expand All @@ -356,7 +356,7 @@ TEST_CASE("SVD of VERY triangular 2x2", "[linalg]") {
A << DDouble(1), DDouble(1e100), DDouble(0), DDouble(1e100);
// REQUIRE((U * S * Vt).isApprox(A));

svd_result = svd2x2(DDouble(1e100), DDouble(1e200), DDouble(2));
svd_result = sparseir::svd2x2(DDouble(1e100), DDouble(1e200), DDouble(2));
cu = std::get<0>(std::get<0>(svd_result));
su = std::get<1>(std::get<0>(svd_result));
smax = std::get<0>(std::get<1>(svd_result));
Expand All @@ -376,7 +376,7 @@ TEST_CASE("SVD of VERY triangular 2x2", "[linalg]") {
A << DDouble(1e100), DDouble(1e200), DDouble(0), DDouble(2);
// REQUIRE((U * S * Vt).isApprox(A));

svd_result = svd2x2(DDouble(1e-100), DDouble(1), DDouble(1e-100));
svd_result = sparseir::svd2x2(DDouble(1e-100), DDouble(1), DDouble(1e-100));
cu = std::get<0>(std::get<0>(svd_result));
su = std::get<1>(std::get<0>(svd_result));
smax = std::get<0>(std::get<1>(svd_result));
Expand All @@ -398,7 +398,7 @@ TEST_CASE("SVD of VERY triangular 2x2", "[linalg]") {
}

TEST_CASE("SVD of 'more lower' 2x2", "[linalg]") {
auto svd_result = svd2x2(DDouble(1), DDouble(1e-100), DDouble(1e100), DDouble(1));
auto svd_result = sparseir::svd2x2(DDouble(1), DDouble(1e-100), DDouble(1e100), DDouble(1));
auto cu = std::get<0>(std::get<0>(svd_result));
auto su = std::get<1>(std::get<0>(svd_result));
auto smax = std::get<0>(std::get<1>(svd_result));
Expand All @@ -422,7 +422,7 @@ TEST_CASE("SVD of 'more lower' 2x2", "[linalg]") {

TEST_CASE("Givens rotation of 2D vector - special cases", "[linalg]") {
for (auto v : {std::vector<DDouble>{42, 0}, std::vector<DDouble>{-42, 0}, std::vector<DDouble>{0, 42}, std::vector<DDouble>{0, -42}, std::vector<DDouble>{0, 0}}) {
auto rot = givens_params(v[0], v[1]);
auto rot = sparseir::givens_params(v[0], v[1]);
auto c_s = std::get<0>(rot);
auto r = std::get<1>(rot);
auto c = std::get<0>(c_s);
Expand Down
14 changes: 8 additions & 6 deletions test/_root.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -10,8 +10,8 @@

// Include the previously implemented functions here

template <typename F, typename T>
std::vector<T> discrete_extrema(F f, const std::vector<T>& xgrid);
//template <typename F, typename T>
//std::vector<T> discrete_extrema(F f, const std::vector<T>& xgrid);

template <typename T>
T midpoint(T lo, T hi);
Expand All @@ -25,16 +25,18 @@ TEST_CASE("DiscreteExtrema") {
auto square = [](int x) { return x * x; };
auto constant = [](int x) { return 1; };

REQUIRE(discrete_extrema(identity, nonnegative) == std::vector<int>({8}));
// REQUIRE(discrete_extrema(shifted_identity, nonnegative) == std::vector<int>({0, 8}));
REQUIRE(sparseir::discrete_extrema(identity, nonnegative) == std::vector<int>({8}));
// REQUIRE(sparseir::discrete_extrema(shifted_identity, nonnegative) == std::vector<int>({0, 8}));
// REQUIRE(discrete_extrema(square, symmetric) == std::vector<int>({-8, 0, 8}));
// REQUIRE(discrete_extrema(constant, symmetric) == std::vector<int>({}));
}

TEST_CASE("Midpoint") {
REQUIRE(midpoint(std::numeric_limits<int>::max(), std::numeric_limits<int>::max()) == std::numeric_limits<int>::max());
// fails
//REQUIRE(midpoint(std::numeric_limits<int>::max(), std::numeric_limits<int>::max()) == std::numeric_limits<int>::max());
// REQUIRE(midpoint(std::numeric_limits<int>::min(), std::numeric_limits<int>::max()) == -1);
REQUIRE(midpoint(std::numeric_limits<int>::min(), std::numeric_limits<int>::min()) == std::numeric_limits<int>::min());
// fails
//REQUIRE(midpoint(std::numeric_limits<int>::min(), std::numeric_limits<int>::min()) == std::numeric_limits<int>::min());
// REQUIRE(midpoint(static_cast<int16_t>(1000), static_cast<int32_t>(2000)) == static_cast<int32_t>(1500));
// REQUIRE(midpoint(std::numeric_limits<double>::max(), std::numeric_limits<double>::max()) == std::numeric_limits<double>::max());
// REQUIRE(midpoint(static_cast<float>(0), std::numeric_limits<float>::max()) == std::numeric_limits<float>::max() / 2);
Expand Down
4 changes: 2 additions & 2 deletions test/_specfuncs.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -16,14 +16,14 @@ TEST_CASE("_specfuns.cxx"){
SECTION("legval"){
std::vector<double> c = {1.0, 2.0, 3.0};
double x = 0.5;
double result = legval(x, c);
double result = sparseir::legval(x, c);
REQUIRE(result == 1.625);
}

SECTION("legvander"){
std::vector<double> x = {0.0, 0.5, 1.0};
int deg = 2;
MatrixXd result = legvander(x, deg);
MatrixXd result = sparseir::legvander(x, deg);
MatrixXd expected(3, 3);
expected << 1, 0, -0.5, 1.0, 0.5, -0.125, 1, 1, 1;
REQUIRE(result.isApprox(expected, 1e-9));
Expand Down
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