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Commit 1e961fd3 authored by Leon Merten Lohse's avatar Leon Merten Lohse
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add cpplint

parent fa1223b3
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.gitlab-ci.yml
View file @ 1e961fd3
......@@ -8,3 +8,9 @@ flake8:
script:
- pip install flake8
- flake8 --max-line-length=120 fresnel/*py
cpplint:
stage: lint
script:
- pip install cpplint
- cpplint --linelength=120 --filter=-legal/copyright,-build/include_order,-build/include_subdir,-runtime/references source/*cpp source/*h
source/finite_difference.h
View file @ 1e961fd3
......@@ -2,13 +2,12 @@
#include <complex>
#include <Eigen/Dense>
//#include <iostream>
namespace algebra{
namespace algebra {
template <typename T>
using array1d = Eigen::Array<T, Eigen::Dynamic, 1>;
template <typename T>
using TriMatrix = Eigen::Array<T, 3, Eigen::Dynamic>;
......@@ -19,18 +18,18 @@ namespace algebra{
*
* Modifies the input coefficients b and r!
*/
template <typename T>
array1d<T> tridiagonal(TriMatrix<T> &m, array1d<T> &r) {
int n = r.size();
auto a = m.row(0);
auto b = m.row(1);
auto c = m.row(2);
array1d<T> x(n,1);
for (int i=1; i<n; i++) {
array1d<T> x(n, 1);
for (int i=1; i < n; i++) {
T w = a(i) / b(i-1);
b(i) -= w * c(i-1);
r(i) -= w * r(i-1);
......@@ -38,15 +37,15 @@ namespace algebra{
x(n-1) = r(n-1) / b(n-1);
for (int i=n-2; i>=0; i--) {
for (int i=n-2; i >= 0; i--) {
x(i) = (r(i) - c(i) * x(i+1)) / b(i);
}
return x;
}
}
} // namespace algebra
namespace finite_differences{
namespace finite_differences {
using real = double;
using complex = std::complex<real>;
......@@ -56,6 +55,7 @@ namespace finite_differences{
using array_1D = Eigen::Array<scalar, Eigen::Dynamic, 1>;
using array_2D = Eigen::Array<scalar, Eigen::Dynamic, Eigen::Dynamic>;
/*
using shape_t = std::pair<size_t, size_t>;
template <typename T>
......@@ -69,6 +69,7 @@ namespace finite_differences{
throw std::invalid_argument("shape does not match");
dst = src;
}
*/
const array_1D step1d_A0F(const Eigen::Ref<const array_1D> rz,
......@@ -77,39 +78,38 @@ namespace finite_differences{
const Eigen::Ref<const array_1D> f,
const Eigen::Ref<const array_1D> up,
const Eigen::Ref<const array_1D> u) {
// _p : i
// _ : i+1
size_t n = u.size()-2;
// _p : i
// _ : i+1
size_t n = u.size()-2;
// setup tridiagonal n x n matrix M = tridiag(a,b,c) and rhs r
algebra::TriMatrix<scalar> m = algebra::TriMatrix<scalar>::Zero(3, n);
array_1D r = array_1D::Zero(n,1);
array_1D r = array_1D::Zero(n, 1);
// Note that matrix indices go from 1 to u.size()-1, so that indices are off by 1
for (size_t i = 1; i <= n; ++i) {
m(0, i-1) = - rxx(i); // lower
m(1, i-1) = rz(i) + 2. * rxx(i) - f(i); // diagonal
m(2, i-1) = - rxx(i); // upper;
r(i-1) = ( rz(i) - 2. * rxx(i) + fp(i) ) * up(i)
m(0, i-1) = - rxx(i); // lower
m(1, i-1) = rz(i) + 2. * rxx(i) - f(i); // diagonal
m(2, i-1) = - rxx(i); // upper;
r(i-1) = (rz(i) - 2. * rxx(i) + fp(i)) * up(i)
+ rxx(i) * up(i-1)
+ rxx(i) * up(i+1);
}
// boundary
r(0) += rxx(1) * u(0);
r(n-1) += rxx(n) * u(n+1);
// initialize writeable copy
array_1D u_new {u};
u_new.segment(1,n) = algebra::tridiagonal(m,r);
u_new.segment(1, n) = algebra::tridiagonal(m, r);
return u_new;
}
const array_1D step1d_AAF(const Eigen::Ref<const array_1D> rz,
const Eigen::Ref<const array_1D> rxx,
......@@ -118,39 +118,37 @@ namespace finite_differences{
const Eigen::Ref<const array_1D> f,
const Eigen::Ref<const array_1D> up,
const Eigen::Ref<const array_1D> u) {
// _p : i
// _ : i+1
// _p : i
// _ : i+1
size_t n = u.size()-2;
size_t n = u.size()-2;
// setup tridiagonal n x n matrix M = tridiag(a,b,c) and rhs r
algebra::TriMatrix<scalar> m = algebra::TriMatrix<scalar>::Zero(3, n);
array_1D r = array_1D::Zero(n,1);
array_1D r = array_1D::Zero(n, 1);
for (size_t i = 1; i <= n; ++i) {
m(0, i-1) = -rxx(i) + rx(i); // lower
m(1, i-1) = rz(i) + 2. * rxx(i) - f(i); // diagonal
m(2, i-1) = -rxx(i) - rx(i); // upper;
r(i-1) = ( rz(i) - 2. * rxx(i) + f(i) ) * up(i)
m(0, i-1) = -rxx(i) + rx(i); // lower
m(1, i-1) = rz(i) + 2. * rxx(i) - f(i); // diagonal
m(2, i-1) = -rxx(i) - rx(i); // upper;
r(i-1) = (rz(i) - 2. * rxx(i) + f(i)) * up(i)
+ (rxx(i) - rx(i)) * up(i-1)
+ (rxx(i) + rx(i)) * up(i+1);
}
// boundary
r(0) += (rxx(1) - rx(1)) * u(0);
r(n-1) += (rxx(n) + rx(n)) * u(n+1);
// initialize writeable copy
array_1D u_new {u};
u_new.segment(1,n) = algebra::tridiagonal(m,r);
u_new.segment(1, n) = algebra::tridiagonal(m, r);
return u_new;
}
// Two-step alternating-direction Peaceman-Rachford scheme (J. W. Thomas: Numerical Partial Differential Equations)
const array_2D step2d_A0F(
......@@ -161,88 +159,86 @@ namespace finite_differences{
const Eigen::Ref<const array_2D> &f,
const Eigen::Ref<const array_2D> &up,
const Eigen::Ref<const array_2D> &u) {
// rxx and ryy differ by a factor of 1/2 from the definitions in Fuhse et al. (2005)
// .p : i
// . : i+1
// TODO: interpolate for half-step?
// .p : i
// . : i+1
// TODO(Leon): interpolate for half-step?
// coordinate system:
// numpy (z,y,x), eigen (rows, cols): x <-> cols, y <-> rows
size_t nx = u.rows() - 2;
size_t ny = u.cols() - 2;
// std::cout << "nx " << u.cols() << ", ny " << u.rows() << std::endl;
// first halfstep
// x at i + 1/2
// y at i
array_2D uhalf = array_2D::Zero(u.rows(), u.cols());
#pragma omp parallel for
for (size_t iy = 1; iy <= ny; ++iy) {
algebra::TriMatrix<scalar> m = algebra::TriMatrix<scalar>::Zero(3, nx);
array_1D r = array_1D::Zero(nx,1);
for (size_t ix = 1; ix <= nx; ++ ix) {
m(0,ix-1) = - rxx(ix - 1,iy);
m(1,ix-1) = rz(ix, iy) + 2. * rxx(ix, iy) - f(ix, iy);
m(2,ix-1) = - rxx(ix, iy);
array_1D r = array_1D::Zero(nx, 1);
for (size_t ix = 1; ix <= nx; ++ix) {
m(0, ix-1) = - rxx(ix - 1, iy);
m(1, ix-1) = rz(ix, iy) + 2. * rxx(ix, iy) - f(ix, iy);
m(2, ix-1) = - rxx(ix, iy);
r(ix-1) = (rz(ix, iy) - 2. * ryy(ix, iy) + fp(ix, iy)) * up(ix, iy)
+ ryy(ix, iy) * up(ix, iy - 1)
+ ryy(ix, iy) * up(ix, iy - 1)
+ ryy(ix, iy) * up(ix, iy + 1);
}
// boundary conditions
// TODO: use interpolated values?
// TODO(Leon): use interpolated values?
r(0) += rxx(1, iy) * u(0, iy);
r(nx-1) += rxx(nx, iy) * u(nx+1, iy);
uhalf.col(iy).segment(1,nx) = algebra::tridiagonal(m, r);
uhalf.col(iy).segment(1, nx) = algebra::tridiagonal(m, r);
}
// second halfstep
// note: internal storage is column-major such that column-wise access would be much faster
array_2D u_new_trans = array_2D::Zero(u.cols(), u.rows()); //transposed shape
array_2D u_new_trans = array_2D::Zero(u.cols(), u.rows()); // transposed shape
#pragma omp parallel for
for (size_t ix = 1; ix <= nx; ++ix) {
algebra::TriMatrix<scalar> m = algebra::TriMatrix<scalar>::Zero(3, ny);
array_1D r = array_1D::Zero(ny,1);
for (size_t iy = 1; iy <= ny; ++ iy) {
m(0,iy-1) = - ryy(ix, iy-1);
m(1,iy-1) = rz(ix, iy) + 2. * ryy(ix, iy) - f(ix, iy);
m(2,iy-1) = - ryy(ix, iy);
r(iy-1) = ( rz(ix, iy) - 2. * rxx(ix, iy) + fp(ix, iy) ) * uhalf(ix, iy)
+ rxx(ix, iy) * uhalf(ix-1, iy)
+ rxx(ix, iy) * uhalf(ix+1, iy);
array_1D r = array_1D::Zero(ny, 1);
for (size_t iy = 1; iy <= ny; ++iy) {
m(0, iy-1) = - ryy(ix, iy-1);
m(1, iy-1) = rz(ix, iy) + 2. * ryy(ix, iy) - f(ix, iy);
m(2, iy-1) = - ryy(ix, iy);
r(iy-1) = (rz(ix, iy) - 2. * rxx(ix, iy) + fp(ix, iy)) * uhalf(ix, iy)
+ rxx(ix, iy) * uhalf(ix-1, iy)
+ rxx(ix, iy) * uhalf(ix+1, iy);
}
r(0) += ryy(ix, 1) * u(ix, 0);
r(ny-1) += ryy(ix, ny) * u(ix, ny+1);
u_new_trans.col(ix).segment(1,ny) = algebra::tridiagonal(m, r);
u_new_trans.col(ix).segment(1, ny) = algebra::tridiagonal(m, r);
}
array_2D u_new {u_new_trans.transpose()};
return u_new;
}
// Scalar Version
// Two-step alternating-direction Peaceman-Rachford scheme (J. W. Thomas: Numerical Partial Differential Equations)
/* Two-step alternating-direction Peaceman-Rachford scheme
(J. W. Thomas: Numerical Partial Differential Equations)
*/
const array_2D step2d_A0Fs(
const complex rz,
const complex rxx,
......@@ -251,82 +247,78 @@ namespace finite_differences{
const Eigen::Ref<const array_2D> &f,
const Eigen::Ref<const array_2D> &up,
const Eigen::Ref<const array_2D> &u) {
// rxx and ryy differ by a factor of 1/2 from the definitions in Fuhse et al. (2005)
// .p : i
// . : i+1
// TODO: interpolate for half-step?
// .p : i
// . : i+1
// TODO(Leon): interpolate for half-step?
// coordinate system:
// numpy (z,y,x), eigen (rows, cols): x <-> cols, y <-> rows
size_t nx = u.rows() - 2;
size_t ny = u.cols() - 2;
// std::cout << "nx " << u.cols() << ", ny " << u.rows() << std::endl;
// first halfstep
// x at i + 1/2
// y at i
array_2D uhalf = array_2D::Zero(u.rows(), u.cols());
#pragma omp parallel for
for (size_t iy = 1; iy <= ny; ++iy) {
algebra::TriMatrix<scalar> m = algebra::TriMatrix<scalar>::Zero(3, nx);
array_1D r = array_1D::Zero(nx,1);
for (size_t ix = 1; ix <= nx; ++ ix) {
m(0,ix-1) = - rxx;
m(1,ix-1) = rz + 2. * rxx - f(ix, iy);
m(2,ix-1) = - rxx;
array_1D r = array_1D::Zero(nx, 1);
for (size_t ix = 1; ix <= nx; ++ix) {
m(0, ix-1) = - rxx;
m(1, ix-1) = rz + 2. * rxx - f(ix, iy);
m(2, ix-1) = - rxx;
r(ix-1) = (rz - 2. * ryy + fp(ix, iy)) * up(ix, iy)
+ ryy * up(ix, iy - 1)
+ ryy * up(ix, iy - 1)
+ ryy * up(ix, iy + 1);
}
// boundary conditions
// TODO: use interpolated values?
// TODO(Leon): use interpolated values?
r(0) += rxx * u(0, iy);
r(nx-1) += rxx * u(nx+1, iy);
uhalf.col(iy).segment(1,nx) = algebra::tridiagonal(m, r);
uhalf.col(iy).segment(1, nx) = algebra::tridiagonal(m, r);
}
// second halfstep
// note: internal storage is column-major such that column-wise access would be much faster
array_2D u_new_trans = array_2D::Zero(u.cols(), u.rows()); //transposed shape
array_2D u_new_trans = array_2D::Zero(u.cols(), u.rows()); // transposed shape
#pragma omp parallel for
for (size_t ix = 1; ix <= nx; ++ix) {
algebra::TriMatrix<scalar> m = algebra::TriMatrix<scalar>::Zero(3, ny);
array_1D r = array_1D::Zero(ny,1);
for (size_t iy = 1; iy <= ny; ++ iy) {
m(0,iy-1) = - ryy;
m(1,iy-1) = rz + 2. * ryy - f(ix, iy);
m(2,iy-1) = - ryy;
r(iy-1) = ( rz - 2. * rxx + fp(ix, iy) ) * uhalf(ix, iy)
+ rxx * uhalf(ix-1, iy)
+ rxx * uhalf(ix+1, iy);
array_1D r = array_1D::Zero(ny, 1);
for (size_t iy = 1; iy <= ny; ++iy) {
m(0, iy-1) = - ryy;
m(1, iy-1) = rz + 2. * ryy - f(ix, iy);
m(2, iy-1) = - ryy;
r(iy-1) = (rz - 2. * rxx + fp(ix, iy)) * uhalf(ix, iy)
+ rxx * uhalf(ix-1, iy)
+ rxx * uhalf(ix+1, iy);
}
r(0) += ryy * u(ix, 0);
r(ny-1) += ryy * u(ix, ny+1);
u_new_trans.col(ix).segment(1,ny) = algebra::tridiagonal(m, r);
u_new_trans.col(ix).segment(1, ny) = algebra::tridiagonal(m, r);
}
array_2D u_new {u_new_trans.transpose()};
return u_new;
}
}
} // namespace finite_differences
source/solver_py.cpp
View file @ 1e961fd3
......@@ -6,50 +6,46 @@
namespace py = pybind11;
using namespace finite_differences;
namespace fd = finite_differences;
PYBIND11_MODULE(_solver, m){
PYBIND11_MODULE(_solver, m) {
m.def("step1d_A0F",
&finite_differences::step1d_A0F,
&fd::step1d_A0F,
py::arg("rz").noconvert(),
py::arg("rxx").noconvert(),
py::arg("fp").noconvert(),
py::arg("f").noconvert(),
py::arg("up").noconvert(),
py::arg("u").noconvert()
);
py::arg("u").noconvert() );
m.def("step2d_A0F",
&finite_differences::step2d_A0F,
&fd::step2d_A0F,
py::arg("rz").noconvert(),
py::arg("rxx").noconvert(),
py::arg("ryy").noconvert(),
py::arg("fp").noconvert(),
py::arg("f").noconvert(),
py::arg("up").noconvert(),
py::arg("u").noconvert()
);
py::arg("u").noconvert() );
m.def("step2d_A0Fs",
&finite_differences::step2d_A0Fs,
&fd::step2d_A0Fs,
py::arg("rz").noconvert(),
py::arg("rxx").noconvert(),
py::arg("ryy").noconvert(),
py::arg("fp").noconvert(),
py::arg("f").noconvert(),
py::arg("up").noconvert(),
py::arg("u").noconvert()
);
py::arg("u").noconvert() );
m.def("step1d_AAF",
&finite_differences::step1d_AAF,
&fd::step1d_AAF,
py::arg("rz").noconvert(),
py::arg("rxx").noconvert(),
py::arg("rx").noconvert(),
py::arg("fp").noconvert(),
py::arg("f").noconvert(),
py::arg("up").noconvert(),
py::arg("u").noconvert()
);
}
\ No newline at end of file
py::arg("u").noconvert() );
}
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