Example Code: C++ and C for Python#
Generate a Cartesian grid of $51times51$ (
01_grid.py
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | #!/usr/bin/env python3
from matplotlib import pyplot as plt
# [begin example]
import numpy as np
def make_grid():
# Number of the grid points.
nx = 51
# Produce the x coordinates.
x = np.linspace(0, 1, nx)
# Create the two arrays for x and y coordinates of the grid.
gx, gy = np.meshgrid(x, x)
# Create the field and zero-initialize it.
u = np.zeros_like(gx)
# Set the boundary condition.
u[0,:] = 0
u[-1,:] = 1 * np.sin(np.linspace(0,np.pi,nx))
u[:,0] = 0
u[:,-1] = 0
# Return all values.
return nx, x, u
nx, x, uoriginal = make_grid()
# [end example]
def show_grid(size):
fig, ax = plt.subplots(figsize=(size,size))
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
ax.set_xticks(x, minor=True)
ax.set_yticks(x, minor=True)
ax.set_xlabel('$x$')
ax.set_ylabel('$y$')
ax.grid(True, which='major', linewidth=2)
ax.grid(True, which='minor', linewidth=1)
show_grid(10)
plt.rc('figure', figsize=(8, 8))
import os
imagedir = os.path.join(os.path.dirname(__file__), '..', 'image')
imagebase = os.path.splitext(os.path.basename(__file__))[0] + '.png'
imagepath = os.path.join(imagedir, imagebase)
print('write to {}'.format(imagepath))
plt.savefig(imagepath, dpi=150)
# vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4 tw=79:
|
Solve the Laplace equation using Python nested loops
(
01_solve_python_loop.py
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 | #!/usr/bin/env python3
import numpy as np
from matplotlib import pyplot as plt
def make_grid():
nx = 51
x = np.linspace(0, 1, nx)
gx, gy = np.meshgrid(x, x)
u = np.zeros_like(gx)
u[0,:] = 0
u[-1,:] = 1 * np.sin(np.linspace(0,np.pi,nx))
u[:,0] = 0
u[:,-1] = 0
return nx, x, u
nx, x, uoriginal = make_grid()
import time
import numpy as np
class Timer:
def __enter__(self):
self._t0 = time.time()
def __exit__(self, *args, **kw):
self._t1 = time.time()
print("Wall time: {:g} s".format(self._t1 - self._t0))
# [begin example]
def solve_python_loop():
u = uoriginal.copy() # Input from outer scope
un = u.copy() # Create the buffer for the next time step
converged = False
step = 0
# Outer loop.
while not converged:
step += 1
# Inner loops. One for x and the other for y.
for it in range(1, nx-1):
for jt in range(1, nx-1):
un[it,jt] = (u[it+1,jt] + u[it-1,jt] + u[it,jt+1] + u[it,jt-1]) / 4
norm = np.abs(un-u).max()
u[...] = un[...]
converged = True if norm < 1.e-5 else False
return u, step, norm
# [end example]
with Timer():
u, step, norm = solve_python_loop()
print(step)
# Run the Python solver
def show_result(u, step, norm, size=7):
print("step", step, "norm", norm)
fig, ax = plt.subplots(figsize=(size,size))
cs = ax.contour(x, x, u.T)
ax.clabel(cs, inline=1, fontsize=10)
ax.set_xticks(np.linspace(0,1,6))
ax.set_yticks(np.linspace(0,1,6))
ax.set_xlabel('$x$')
ax.set_ylabel('$y$')
ax.grid(True, which='minor')
show_result(u, step, norm)
plt.rc('figure', figsize=(8, 8))
import os
imagedir = os.path.join(os.path.dirname(__file__), '..', 'image')
imagebase = os.path.splitext(os.path.basename(__file__))[0] + '.png'
imagepath = os.path.join(imagedir, imagebase)
print('write to {}'.format(imagepath))
plt.savefig(imagepath, dpi=150)
# vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4 tw=79:
|
The analytical solution of the Laplace equation
(
01_solve_analytical.py
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | #!/usr/bin/env python3
import numpy as np
def make_grid():
nx = 51
x = np.linspace(0, 1, nx)
gx, gy = np.meshgrid(x, x)
u = np.zeros_like(gx)
u[0,:] = 0
u[-1,:] = 1 * np.sin(np.linspace(0,np.pi,nx))
u[:,0] = 0
u[:,-1] = 0
return nx, x, u
nx, x, uoriginal = make_grid()
import numpy as np
# [begin example]
def solve_analytical():
u = np.empty((len(x), len(x)), dtype='float64')
for ix, cx in enumerate(x):
u[ix, :] = np.sinh(np.pi*cx) / np.sinh(np.pi) * np.sin(np.pi*x)
return u
# [end example]
def solve_python_loop():
u = uoriginal.copy() # Input from outer scope
un = u.copy() # Create the buffer for the next time step
converged = False
step = 0
# Outer loop.
while not converged:
step += 1
# Inner loops. One for x and the other for y.
for it in range(1, nx-1):
for jt in range(1, nx-1):
un[it,jt] = (u[it+1,jt] + u[it-1,jt] + u[it,jt+1] + u[it,jt-1]) / 4
norm = np.abs(un-u).max()
u[...] = un[...]
converged = True if norm < 1.e-5 else False
return u, step, norm
u, step, norm = solve_python_loop()
# [begin pycon]
uanalytical = solve_analytical()
# Calculate the L inf norm.
print("Linf of difference is %f" % np.abs(u - uanalytical).max())
# [end pycon]
from matplotlib import pyplot as plt
def show_result(u, step, norm, size=7):
print("step", step, "norm", norm)
fig, ax = plt.subplots(figsize=(size,size))
cs = ax.contour(x, x, u.T)
ax.clabel(cs, inline=1, fontsize=10)
ax.set_xticks(np.linspace(0,1,6))
ax.set_yticks(np.linspace(0,1,6))
ax.set_xlabel('$x$')
ax.set_ylabel('$y$')
ax.grid(True, which='minor')
show_result(uanalytical, 0, 0)
plt.rc('figure', figsize=(8, 8))
import os
imagedir = os.path.join(os.path.dirname(__file__), '..', 'image')
imagebase = os.path.splitext(os.path.basename(__file__))[0] + '.png'
imagepath = os.path.join(imagedir, imagebase)
print('write to {}'.format(imagepath))
plt.savefig(imagepath, dpi=150)
# vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4 tw=79:
|
Solve the Laplace equation using numpy (
02_solve_array.py
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | #!/usr/bin/env python3
import numpy as np
def make_grid():
nx = 51
x = np.linspace(0, 1, nx)
gx, gy = np.meshgrid(x, x)
u = np.zeros_like(gx)
u[0,:] = 0
u[-1,:] = 1 * np.sin(np.linspace(0,np.pi,nx))
u[:,0] = 0
u[:,-1] = 0
return nx, x, u
nx, x, uoriginal = make_grid()
import numpy as np
# [begin example]
def solve_array():
u = uoriginal.copy() # Input from outer scope
un = u.copy() # Create the buffer for the next time step
converged = False
step = 0
while not converged:
step += 1
un[1:nx-1,1:nx-1] = (u[2:nx,1:nx-1] + u[0:nx-2,1:nx-1] +
u[1:nx-1,2:nx] + u[1:nx-1,0:nx-2]) / 4
norm = np.abs(un-u).max()
u[...] = un[...]
converged = True if norm < 1.e-5 else False
return u, step, norm
# [end example]
import time
class Timer:
def __enter__(self):
self._t0 = time.time()
def __exit__(self, *args, **kw):
self._t1 = time.time()
print("Wall time: {:g} s".format(self._t1 - self._t0))
# [begin pycon]
# Run the Python solver
with Timer():
u, step, norm = solve_array()
# [end pycon]
from matplotlib import pyplot as plt
def show_result(u, step, norm, size=7):
print("step", step, "norm", norm)
fig, ax = plt.subplots(figsize=(size,size))
cs = ax.contour(x, x, u.T)
ax.clabel(cs, inline=1, fontsize=10)
ax.set_xticks(np.linspace(0,1,6))
ax.set_yticks(np.linspace(0,1,6))
ax.set_xlabel('$x$')
ax.set_ylabel('$y$')
ax.grid(True, which='minor')
show_result(u, step, norm)
plt.rc('figure', figsize=(8, 8))
import os
imagedir = os.path.join(os.path.dirname(__file__), '..', 'image')
imagebase = os.path.splitext(os.path.basename(__file__))[0] + '.png'
imagepath = os.path.join(imagedir, imagebase)
print('write to {}'.format(imagepath))
plt.savefig(imagepath, dpi=150)
# vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4 tw=79:
|
Solve the Laplace equation using the C++ code (
solve_cpp.cpp
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 | #include <pybind11/pybind11.h>
#include <modmesh/buffer/buffer.hpp>
#include <modmesh/buffer/pymod/buffer_pymod.hpp>
#include <vector>
#include <algorithm>
#include <tuple>
#include <iostream>
#include <pybind11/numpy.h>
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include <numpy/arrayobject.h>
namespace modmesh
{
namespace python
{
void import_numpy()
{
auto local_import_numpy = []()
{
import_array2("cannot import numpy", false); // or numpy c api segfault.
return true;
};
if (!local_import_numpy())
{
throw pybind11::error_already_set();
}
}
} /* end namespace python */
} /* end namespace modmesh */
template <typename T>
T calc_norm_amax(modmesh::SimpleArray<T> const & arr0, modmesh::SimpleArray<T> const & arr1)
{
size_t const nelm = arr0.size();
T ret = 0;
for (size_t it = 0; it < nelm; ++it)
{
T const val = std::abs(arr0[it] - arr1[it]);
if (val > ret)
{
ret = val;
}
}
return ret;
}
// [begin example]
std::tuple<modmesh::SimpleArray<double>, size_t, double>
solve1(modmesh::SimpleArray<double> u)
{
const size_t nx = u.shape(0);
modmesh::SimpleArray<double> un = u;
bool converged = false;
size_t step = 0;
double norm;
while (!converged)
{
norm = 0.0;
++step;
for (size_t it=1; it<nx-1; ++it)
{
for (size_t jt=1; jt<nx-1; ++jt)
{
un(it,jt) = (u(it+1,jt) + u(it-1,jt) + u(it,jt+1) + u(it,jt-1)) / 4;
double const v = std::abs(un(it,jt) - u(it,jt));
if (v > norm)
{
norm = v;
}
}
}
// additional loop slows down: norm = calc_norm_amax(u, un);
if (norm < 1.e-5) { converged = true; }
u = un;
}
return std::make_tuple(u, step, norm);
}
// Expose the C++ helper to Python
PYBIND11_MODULE(solve_cpp, m)
{
// Boilerplate for using the SimpleArray with Python
{
modmesh::python::import_numpy();
modmesh::python::wrap_ConcreteBuffer(m);
modmesh::python::wrap_SimpleArray(m);
}
m.def
(
"solve_cpp"
, [](pybind11::array_t<double> & uin)
{
auto ret = solve1(modmesh::python::makeSimpleArray(uin));
return std::make_tuple(
modmesh::python::to_ndarray(std::get<0>(ret)),
std::get<1>(ret),
std::get<2>(ret));
}
);
}
// [end example]
// vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4:
|
The Python driver to solve the Laplace equation using the C++ code
(
03_solve_cpp.py
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | #!/usr/bin/env python3
import numpy as np
def make_grid():
nx = 51
x = np.linspace(0, 1, nx)
gx, gy = np.meshgrid(x, x)
u = np.zeros_like(gx)
u[0,:] = 0
u[-1,:] = 1 * np.sin(np.linspace(0,np.pi,nx))
u[:,0] = 0
u[:,-1] = 0
return nx, x, u
nx, x, uoriginal = make_grid()
# [begin example]
import solve_cpp
# [end example]
import time
class Timer:
def __enter__(self):
self._t0 = time.time()
def __exit__(self, *args, **kw):
self._t1 = time.time()
print("Wall time: {:g} s".format(self._t1 - self._t0))
# [begin pycon]
with Timer():
u, step, norm = solve_cpp.solve_cpp(uoriginal)
# [end pycon]
from matplotlib import pyplot as plt
def show_result(u, step, norm, size=7):
print("step", step, "norm", norm)
fig, ax = plt.subplots(figsize=(size,size))
cs = ax.contour(x, x, u.T)
ax.clabel(cs, inline=1, fontsize=10)
ax.set_xticks(np.linspace(0,1,6))
ax.set_yticks(np.linspace(0,1,6))
ax.set_xlabel('$x$')
ax.set_ylabel('$y$')
ax.grid(True, which='minor')
show_result(u, step, norm)
plt.rc('figure', figsize=(8, 8))
import os
imagedir = os.path.join(os.path.dirname(__file__), '..', 'image')
imagebase = os.path.splitext(os.path.basename(__file__))[0] + '.png'
imagepath = os.path.join(imagedir, imagebase)
print('write to {}'.format(imagepath))
plt.savefig(imagepath, dpi=150)
# vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4 tw=79:
|
C++ code for least-square regression to polynomial functions
(
data_prep.cpp
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 | #include <pybind11/pybind11.h>
#include <modmesh/buffer/buffer.hpp>
#include <modmesh/buffer/pymod/buffer_pymod.hpp>
#include <pybind11/numpy.h>
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include <numpy/arrayobject.h>
#ifdef HASMKL
#include <mkl_lapack.h>
#include <mkl_lapacke.h>
#else // HASMKL
#ifdef __MACH__
#include <clapack.h>
#include <Accelerate/Accelerate.h>
#endif // __MACH__
#endif // HASMKL
#include <vector>
#include <algorithm>
namespace modmesh
{
namespace python
{
void import_numpy()
{
auto local_import_numpy = []()
{
import_array2("cannot import numpy", false); // or numpy c api segfault.
return true;
};
if (!local_import_numpy())
{
throw pybind11::error_already_set();
}
}
} /* end namespace python */
} /* end namespace modmesh */
modmesh::SimpleArray<double> solve
(
modmesh::SimpleArray<double> const & sarr
, modmesh::SimpleArray<double> const & rhs
)
{
// Populate the column major input by transposing
modmesh::SimpleArray<double> mat(
std::vector<size_t>{sarr.shape(1), sarr.shape(0)});
for (size_t i = 0; i < mat.shape(0); ++i)
{
for (size_t j = 0; j < mat.shape(1); ++j)
{
mat(i, j) = sarr(j, i);
}
}
modmesh::SimpleArray<double> b = rhs;
int n = rhs.size();
modmesh::SimpleArray<int> ipiv(n);
int status;
int nn = mat.shape(0);
int bncol = 1;
int bnrow = b.shape(0);
int matnrow = mat.shape(1);
// FIXME: This call is not yet validated. I am not sure about the
// correctness of the solution.
dgesv_( // column major.
&nn // int * n: number of linear equation
, &bncol // int * nrhs: number of RHS
, mat.data() // double * a: array (lda, n)
, &matnrow // int * lda: leading dimension of array a
, ipiv.data() // int * ipiv: pivot indices
, b.data() // double * b: array (ldb, nrhs)
, &bnrow // int * ldb: leading dimension of array b
, &status // for column major matrix, ldb remains the leading dimension.
);
return b;
}
// [begin example: single fit]
/**
* This function calculates the least-square regression of a point cloud to a
* polynomial function of a given order.
*/
modmesh::SimpleArray<double> fit_poly
(
modmesh::SimpleArray<double> const & xarr
, modmesh::SimpleArray<double> const & yarr
, size_t start
, size_t stop
, size_t order
)
{
if (xarr.size() != yarr.size())
{
throw std::runtime_error("xarr and yarr size mismatch");
}
// The rank of the linear map is (order+1).
modmesh::SimpleArray<double> matrix(std::vector<size_t>{order+1, order+1});
// Use the x coordinates to build the linear map for least-square
// regression.
for (size_t it=0; it<order+1; ++it)
{
for (size_t jt=0; jt<order+1; ++jt)
{
double & val = matrix(it, jt);
val = 0;
for (size_t kt=start; kt<stop; ++kt)
{
val += pow(xarr[kt], it+jt);
}
}
}
// Use the x and y coordinates to build the vector in the right-hand side
// of the linear system.
modmesh::SimpleArray<double> rhs(std::vector<size_t>{order+1});
for (size_t jt=0; jt<order+1; ++jt)
{
rhs[jt] = 0;
for (size_t kt=start; kt<stop; ++kt)
{
rhs[jt] += pow(xarr[kt], jt) * yarr[kt];
}
}
// Solve the linear system for the least-square minimization.
modmesh::SimpleArray<double> lhs = solve(matrix, rhs);
std::reverse(lhs.begin(), lhs.end()); // to make numpy.poly1d happy.
return lhs;
}
// [end example: single fit]
// [begin example: multiple fit]
/**
* This function calculates the least-square regression of multiple sets of
* point clouds to the corresponding polynomial functions of a given order.
*/
modmesh::SimpleArray<double> fit_polys
(
modmesh::SimpleArray<double> const & xarr
, modmesh::SimpleArray<double> const & yarr
, size_t order
)
{
size_t xmin = std::floor(*std::min_element(xarr.begin(), xarr.end()));
size_t xmax = std::ceil(*std::max_element(xarr.begin(), xarr.end()));
size_t ninterval = xmax - xmin;
modmesh::SimpleArray<double> lhs(std::vector<size_t>{ninterval, order+1});
std::fill(lhs.begin(), lhs.end(), 0); // sentinel.
size_t start=0;
for (size_t it=0; it<xmax; ++it)
{
// NOTE: We take advantage of the intrinsic features of the input data
// to determine the grouping. This is ad hoc and hard to maintain. We
// play this trick to demonstrate a hackish way of performing numerical
// calculation.
size_t stop;
for (stop=start; stop<xarr.size(); ++stop)
{
if (xarr[stop]>=it+1) { break; }
}
// Use the single polynomial helper function.
auto sub_lhs = fit_poly(xarr, yarr, start, stop, order);
for (size_t jt=0; jt<order+1; ++jt)
{
lhs(it, jt) = sub_lhs[jt];
}
start = stop;
}
return lhs;
}
// [end example: multiple fit]
// [begin example: wrapping]
/**
* The pybind11 wrapper for the helper functions for polynomial fitting.
*/
PYBIND11_MODULE(data_prep, m)
{
// Boilerplate for using the SimpleArray with Python
{
modmesh::python::import_numpy();
modmesh::python::wrap_ConcreteBuffer(m);
modmesh::python::wrap_SimpleArray(m);
}
m.def
(
"fit_poly"
, []
(
pybind11::array_t<double> & xarr_in
, pybind11::array_t<double> & yarr_in
, size_t order
)
{
auto xarr = modmesh::python::makeSimpleArray(xarr_in);
auto yarr = modmesh::python::makeSimpleArray(yarr_in);
auto ret = fit_poly(xarr, yarr, 0, xarr.size(), order);
return modmesh::python::to_ndarray(ret);
}
);
m.def
(
"fit_polys"
, []
(
pybind11::array_t<double> & xarr_in
, pybind11::array_t<double> & yarr_in
, size_t order
)
{
auto xarr = modmesh::python::makeSimpleArray(xarr_in);
auto yarr = modmesh::python::makeSimpleArray(yarr_in);
auto ret = fit_polys(xarr, yarr, order);
return modmesh::python::to_ndarray(ret);
}
);
}
// [end example: wrapping]
// vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4:
|
The Python driver to the least-square regression using the C++ code
(
04_fit_poly.py
).#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | #!/usr/bin/env python3
import numpy as np
from matplotlib import pyplot as plt
import time
class Timer:
def __enter__(self):
self._t0 = time.time()
def __exit__(self, *args, **kw):
self._t1 = time.time()
print("Wall time: {:g} s".format(self._t1 - self._t0))
print("prep")
# [begin prep pycon]
with Timer():
# np.unique returns a sorted array.
xdata = np.unique(np.random.sample(1000000) * 1000)
ydata = np.random.sample(len(xdata)) * 1000
# [end prep pycon]
# [begin fit_poly pycon]
import data_prep
plt.rc('figure', figsize=(12, 8))
def plot_poly_fitted(i):
slct = (xdata>=i)&(xdata<(i+1))
sub_x = xdata[slct]
sub_y = ydata[slct]
poly = data_prep.fit_poly(sub_x, sub_y, 3)
print(poly)
poly = np.poly1d(poly)
xp = np.linspace(sub_x.min(), sub_x.max(), 100)
plt.plot(sub_x, sub_y, '.', xp, poly(xp), '-')
plot_poly_fitted(10)
# [end fit_poly pycon]
import os
imagedir = os.path.join(os.path.dirname(__file__), '..', 'image')
imagebase = os.path.splitext(os.path.basename(__file__))[0] + '.png'
imagepath = os.path.join(imagedir, imagebase)
print('write to {}'.format(imagepath))
plt.savefig(imagepath, dpi=150)
print("lumped")
# [begin lumped pycon]
with Timer():
# Do the calculation for the 1000 groups of points.
polygroup = np.empty((1000, 3), dtype='float64')
for i in range(1000):
# Use numpy to build the point group.
slct = (xdata>=i)&(xdata<(i+1))
sub_x = xdata[slct]
sub_y = ydata[slct]
polygroup[i,:] = data_prep.fit_poly(sub_x, sub_y, 2)
# [end lumped pycon]
print("point build")
# [begin point build pycon]
with Timer():
# Using numpy to build the point groups takes a lot of time.
data_groups = []
for i in range(1000):
slct = (xdata>=i)&(xdata<(i+1))
data_groups.append((xdata[slct], ydata[slct]))
# [end point build pycon]
print("fitting")
# [begin fitting pycon]
with Timer():
# Fitting helper runtime is much less than building the point groups.
polygroup = np.empty((1000, 3), dtype='float64')
for it, (sub_x, sub_y) in enumerate(data_groups):
polygroup[it,:] = data_prep.fit_poly(sub_x, sub_y, 2)
# [end fitting pycon]
print("batch")
# [begin batch pycon]
with Timer():
rbatch = data_prep.fit_polys(xdata, ydata, 2)
# [end batch pycon]
print(rbatch.shape)
# Verify batch.
assert len(rbatch) == len(polygroup)
for i in range(1000):
assert (rbatch[i] == polygroup[i]).all()
# vim: set ff=unix fenc=utf8 et sw=4 ts=4 sts=4 tw=79:
|
ConcreteBuffer
for memory control
(ConcreteBuffer.hpp
). See
https://github.com/solvcon/modmesh for how it works in an application.#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 | #pragma once
/*
* Copyright (c) 2019, Yung-Yu Chen <yyc@solvcon.net>
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* - Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* - Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* - Neither the name of the copyright holder nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#include <modmesh/buffer/small_vector.hpp>
#include <stdexcept>
#include <memory>
#include <algorithm>
#include <sstream>
namespace modmesh
{
namespace detail
{
// Take the remover and deleter classes outside ConcreteBuffer to work around
// https://bugzilla.redhat.com/show_bug.cgi?id=1569374
/**
* The base class of memory deallocator for ConcreteBuffer. When the object
* exists in ConcreteBufferDataDeleter (the unique_ptr deleter), the deleter
* calls it to release the memory of the ConcreteBuffer data buffer.
*/
struct ConcreteBufferRemover
{
ConcreteBufferRemover() = default;
ConcreteBufferRemover(ConcreteBufferRemover const &) = default;
ConcreteBufferRemover(ConcreteBufferRemover &&) = default;
ConcreteBufferRemover & operator=(ConcreteBufferRemover const &) = default;
ConcreteBufferRemover & operator=(ConcreteBufferRemover &&) = default;
virtual ~ConcreteBufferRemover() = default;
// NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays,readability-non-const-parameter)
virtual void operator()(int8_t * p) const
{
// NOLINTNEXTLINE(cppcoreguidelines-owning-memory)
delete[] p;
}
}; /* end struct ConcreteBufferRemover */
struct ConcreteBufferNoRemove : public ConcreteBufferRemover
{
// NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays,readability-non-const-parameter)
void operator()(int8_t *) const override {}
}; /* end struct ConcreteBufferNoRemove */
struct ConcreteBufferDataDeleter
{
using remover_type = ConcreteBufferRemover;
ConcreteBufferDataDeleter(ConcreteBufferDataDeleter const &) = delete;
ConcreteBufferDataDeleter & operator=(ConcreteBufferDataDeleter const &) = delete;
ConcreteBufferDataDeleter() = default;
ConcreteBufferDataDeleter(ConcreteBufferDataDeleter &&) = default;
ConcreteBufferDataDeleter & operator=(ConcreteBufferDataDeleter &&) = default;
~ConcreteBufferDataDeleter() = default;
explicit ConcreteBufferDataDeleter(std::unique_ptr<remover_type> && remover_in)
: remover(std::move(remover_in))
{
}
// NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays,readability-non-const-parameter)
void operator()(int8_t * p) const
{
if (!remover)
{
// NOLINTNEXTLINE(cppcoreguidelines-owning-memory)
delete[] p;
}
else
{
(*remover)(p);
}
}
std::unique_ptr<remover_type> remover{nullptr};
}; /* end struct ConcreteBufferDataDeleter */
} /* end namespace detail */
/**
* Untyped and unresizeable memory buffer for contiguous data storage.
*/
class ConcreteBuffer
: public std::enable_shared_from_this<ConcreteBuffer>
{
private:
struct ctor_passkey
{
};
using data_deleter_type = detail::ConcreteBufferDataDeleter;
public:
using remover_type = detail::ConcreteBufferRemover;
static std::shared_ptr<ConcreteBuffer> construct(size_t nbytes)
{
return std::make_shared<ConcreteBuffer>(nbytes, ctor_passkey());
}
/*
* This factory method is dangerous since the data pointer passed in will
* not be owned by the ConcreteBuffer created. It is an error if the
* number of bytes of the externally owned buffer doesn't match the value
* passed in (but we cannot know here).
*/
static std::shared_ptr<ConcreteBuffer> construct(size_t nbytes, int8_t * data, std::unique_ptr<remover_type> && remover)
{
return std::make_shared<ConcreteBuffer>(nbytes, data, std::move(remover), ctor_passkey());
}
static std::shared_ptr<ConcreteBuffer> construct(size_t nbytes, void * data, std::unique_ptr<remover_type> && remover)
{
return construct(nbytes, static_cast<int8_t *>(data), std::move(remover));
}
static std::shared_ptr<ConcreteBuffer> construct() { return construct(0); }
std::shared_ptr<ConcreteBuffer> clone() const
{
std::shared_ptr<ConcreteBuffer> ret = construct(nbytes());
std::copy_n(data(), size(), (*ret).data());
return ret;
}
/**
* \param[in] nbytes
* Size of the memory buffer in bytes.
*/
ConcreteBuffer(size_t nbytes, const ctor_passkey &)
: m_nbytes(nbytes)
, m_data(allocate(nbytes))
{
}
/**
* \param[in] nbytes
* Size of the memory buffer in bytes.
* \param[in] data
* Pointer to the memory buffer that is not supposed to be owned by
* this ConcreteBuffer.
* \param[in] remover
* The memory deallocator for the unowned data buffer passed in.
*/
// NOLINTNEXTLINE(readability-non-const-parameter)
ConcreteBuffer(size_t nbytes, int8_t * data, std::unique_ptr<remover_type> && remover, const ctor_passkey &)
: m_nbytes(nbytes)
, m_data(data, data_deleter_type(std::move(remover)))
{
}
~ConcreteBuffer() = default;
ConcreteBuffer() = delete;
ConcreteBuffer(ConcreteBuffer &&) = delete;
ConcreteBuffer & operator=(ConcreteBuffer &&) = delete;
#ifdef __GNUC__
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wextra"
#endif
// Avoid enabled_shared_from_this copy constructor
// NOLINTNEXTLINE(bugprone-copy-constructor-init)
ConcreteBuffer(ConcreteBuffer const & other)
: m_nbytes(other.m_nbytes)
, m_data(allocate(other.m_nbytes))
{
if (size() != other.size())
{
throw std::out_of_range("Buffer size mismatch");
}
std::copy_n(other.data(), size(), data());
}
#ifdef __GNUC__
#pragma GCC diagnostic pop
#endif
ConcreteBuffer & operator=(ConcreteBuffer const & other)
{
if (this != &other)
{
if (size() != other.size())
{
throw std::out_of_range("Buffer size mismatch");
}
std::copy_n(other.data(), size(), data());
}
return *this;
}
explicit operator bool() const noexcept { return bool(m_data); }
size_t nbytes() const noexcept { return m_nbytes; }
size_t size() const noexcept { return nbytes(); }
using iterator = int8_t *;
using const_iterator = int8_t const *;
iterator begin() noexcept { return data(); }
iterator end() noexcept { return data() + size(); }
const_iterator begin() const noexcept { return data(); }
const_iterator end() const noexcept { return data() + size(); }
const_iterator cbegin() const noexcept { return begin(); }
const_iterator cend() const noexcept { return end(); }
int8_t operator[](size_t it) const { return data(it); }
int8_t & operator[](size_t it) { return data(it); }
int8_t at(size_t it) const
{
validate_range(it);
return data(it);
}
int8_t & at(size_t it)
{
validate_range(it);
return data(it);
}
/* Backdoor */
int8_t data(size_t it) const { return data()[it]; }
int8_t & data(size_t it) { return data()[it]; }
int8_t const * data() const noexcept { return data<int8_t>(); }
int8_t * data() noexcept { return data<int8_t>(); }
// clang-format off
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-reinterpret-cast)
template <typename T> T const * data() const noexcept { return reinterpret_cast<T *>(m_data.get()); }
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-reinterpret-cast)
template <typename T> T * data() noexcept { return reinterpret_cast<T *>(m_data.get()); }
// clang-format on
bool has_remover() const noexcept { return bool(m_data.get_deleter().remover); }
remover_type const & get_remover() const { return *m_data.get_deleter().remover; }
remover_type & get_remover() { return *m_data.get_deleter().remover; }
// NOLINTNEXTLINE(modernize-avoid-c-arrays,cppcoreguidelines-avoid-c-arrays)
using unique_ptr_type = std::unique_ptr<int8_t, data_deleter_type>;
void validate_range(size_t it) const
{
if (it >= size())
{
std::ostringstream ms;
ms << "ConcreteBuffer: index " << it << " is out of bounds with size " << size();
throw std::out_of_range(ms.str());
}
}
static unique_ptr_type allocate(size_t nbytes)
{
unique_ptr_type ret(nullptr, data_deleter_type());
if (0 != nbytes)
{
ret = unique_ptr_type(new int8_t[nbytes], data_deleter_type());
}
return ret;
}
size_t m_nbytes;
unique_ptr_type m_data;
}; /* end class ConcreteBuffer */
} /* end namespace modmesh */
/* vim: set et ts=4 sw=4: */
|
SimpleArray
for multi-dimensional array
(SimpleArray.hpp
). See
https://github.com/solvcon/modmesh for how it works in an application.#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 | #pragma once
/*
* Copyright (c) 2019, Yung-Yu Chen <yyc@solvcon.net>
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* - Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* - Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* - Neither the name of the copyright holder nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#include <modmesh/buffer/ConcreteBuffer.hpp>
#include <stdexcept>
#if defined(_MSC_VER)
#include <BaseTsd.h>
typedef SSIZE_T ssize_t;
#endif
namespace modmesh
{
namespace detail
{
template <size_t D, typename S>
size_t buffer_offset_impl(S const &)
{
return 0;
}
template <size_t D, typename S, typename Arg, typename... Args>
size_t buffer_offset_impl(S const & strides, Arg arg, Args... args)
{
return arg * strides[D] + buffer_offset_impl<D + 1>(strides, args...);
}
} /* end namespace detail */
template <typename S, typename... Args>
size_t buffer_offset(S const & strides, Args... args)
{
return detail::buffer_offset_impl<0>(strides, args...);
}
inline size_t buffer_offset(small_vector<size_t> const & stride, small_vector<size_t> const & idx)
{
if (stride.size() != idx.size())
{
std::ostringstream ms;
// clang-format off
ms << "stride size " << stride.size() << " != " << "index size " << idx.size();
// clang-format on
throw std::out_of_range(ms.str());
}
size_t offset = 0;
for (size_t it = 0; it < stride.size(); ++it)
{
offset += stride[it] * idx[it];
}
return offset;
}
/**
* Simple array type for contiguous memory storage. Size does not change. The
* copy semantics performs data copy. The move semantics invalidates the
* existing memory buffer.
*/
template <typename T>
class SimpleArray
{
public:
using value_type = T;
using shape_type = small_vector<size_t>;
using sshape_type = small_vector<ssize_t>;
using buffer_type = ConcreteBuffer;
static constexpr size_t ITEMSIZE = sizeof(value_type);
static constexpr size_t itemsize() { return ITEMSIZE; }
explicit SimpleArray(size_t length)
: m_buffer(buffer_type::construct(length * ITEMSIZE))
, m_shape{length}
, m_stride{1}
, m_body(m_buffer->data<T>())
{
}
template <class InputIt>
SimpleArray(InputIt first, InputIt last)
: SimpleArray(last - first)
{
std::copy(first, last, data());
}
// NOLINTNEXTLINE(modernize-pass-by-value)
explicit SimpleArray(small_vector<size_t> const & shape)
: m_shape(shape)
, m_stride(calc_stride(m_shape))
{
if (!m_shape.empty())
{
m_buffer = buffer_type::construct(m_shape[0] * m_stride[0] * ITEMSIZE);
m_body = m_buffer->data<T>();
}
}
// NOLINTNEXTLINE(modernize-pass-by-value)
explicit SimpleArray(small_vector<size_t> const & shape, value_type const & value)
: SimpleArray(shape)
{
std::fill(begin(), end(), value);
}
explicit SimpleArray(std::vector<size_t> const & shape)
: m_shape(shape)
, m_stride(calc_stride(m_shape))
{
if (!m_shape.empty())
{
m_buffer = buffer_type::construct(m_shape[0] * m_stride[0] * ITEMSIZE);
m_body = m_buffer->data<T>();
}
}
explicit SimpleArray(std::vector<size_t> const & shape, value_type const & value)
: SimpleArray(shape)
{
std::fill(begin(), end(), value);
}
explicit SimpleArray(std::shared_ptr<buffer_type> const & buffer)
{
if (buffer)
{
const size_t nitem = buffer->nbytes() / ITEMSIZE;
if (buffer->nbytes() != nitem * ITEMSIZE)
{
throw std::runtime_error("SimpleArray: input buffer size must be divisible");
}
m_shape = shape_type{nitem};
m_stride = shape_type{1};
m_buffer = buffer;
m_body = m_buffer->data<T>();
}
else
{
throw std::runtime_error("SimpleArray: buffer cannot be null");
}
}
explicit SimpleArray(small_vector<size_t> const & shape, std::shared_ptr<buffer_type> const & buffer)
: SimpleArray(buffer)
{
if (buffer)
{
m_shape = shape;
m_stride = calc_stride(m_shape);
const size_t nbytes = m_shape[0] * m_stride[0] * ITEMSIZE;
if (nbytes != buffer->nbytes())
{
std::ostringstream ms;
ms << "SimpleArray: shape byte count " << nbytes << " differs from buffer " << buffer->nbytes();
throw std::runtime_error(ms.str());
}
}
}
SimpleArray(std::initializer_list<T> init)
: SimpleArray(init.size())
{
std::copy_n(init.begin(), init.size(), data());
}
SimpleArray()
: SimpleArray(0)
{
}
SimpleArray(SimpleArray const & other)
: m_buffer(other.m_buffer->clone())
, m_shape(other.m_shape)
, m_stride(other.m_stride)
, m_nghost(other.m_nghost)
, m_body(calc_body(m_buffer->data<T>(), m_stride, other.m_nghost))
{
}
SimpleArray(SimpleArray && other) noexcept
: m_buffer(std::move(other.m_buffer))
, m_shape(std::move(other.m_shape))
, m_stride(std::move(other.m_stride))
, m_nghost(other.m_nghost)
, m_body(other.m_body)
{
}
SimpleArray & operator=(SimpleArray const & other)
{
if (this != &other)
{
*m_buffer = *(other.m_buffer); // Size is checked inside.
m_shape = other.m_shape;
m_stride = other.m_stride;
m_nghost = other.m_nghost;
m_body = calc_body(m_buffer->data<T>(), m_stride, other.m_nghost);
}
return *this;
}
SimpleArray & operator=(SimpleArray && other) noexcept
{
if (this != &other)
{
m_buffer = std::move(other.m_buffer);
m_shape = std::move(other.m_shape);
m_stride = std::move(other.m_stride);
m_nghost = other.m_nghost;
m_body = other.m_body;
}
return *this;
}
~SimpleArray() = default;
template <typename... Args>
SimpleArray & remake(Args &&... args)
{
SimpleArray(args...).swap(*this);
return *this;
}
static shape_type calc_stride(shape_type const & shape)
{
shape_type stride(shape.size());
if (!shape.empty())
{
stride[shape.size() - 1] = 1;
for (size_t it = shape.size() - 1; it > 0; --it)
{
stride[it - 1] = stride[it] * shape[it];
}
}
return stride;
}
static T * calc_body(T * data, shape_type const & stride, size_t nghost)
{
if (nullptr == data || stride.empty() || 0 == nghost)
{
// Do nothing.
}
else
{
shape_type shape(stride.size(), 0);
shape[0] = nghost;
data += buffer_offset(stride, shape);
}
return data;
}
explicit operator bool() const noexcept { return bool(m_buffer) && bool(*m_buffer); }
size_t nbytes() const noexcept { return m_buffer ? m_buffer->nbytes() : 0; }
size_t size() const noexcept { return nbytes() / ITEMSIZE; }
using iterator = T *;
using const_iterator = T const *;
iterator begin() noexcept { return data(); }
iterator end() noexcept { return data() + size(); }
const_iterator begin() const noexcept { return data(); }
const_iterator end() const noexcept { return data() + size(); }
const_iterator cbegin() const noexcept { return begin(); }
const_iterator cend() const noexcept { return end(); }
value_type const & operator[](size_t it) const noexcept { return data(it); }
value_type & operator[](size_t it) noexcept { return data(it); }
value_type const & at(size_t it) const
{
validate_range(it);
return data(it);
}
value_type & at(size_t it)
{
validate_range(it);
return data(it);
}
value_type const & at(ssize_t it) const
{
validate_range(it);
it += m_nghost;
return data(it);
}
value_type & at(ssize_t it)
{
validate_range(it);
it += m_nghost;
return data(it);
}
value_type const & at(std::vector<size_t> const & idx) const { return at(shape_type(idx)); }
value_type & at(std::vector<size_t> const & idx) { return at(shape_type(idx)); }
value_type const & at(shape_type const & idx) const
{
const size_t offset = buffer_offset(m_stride, idx);
validate_range(offset);
return data(offset);
}
value_type & at(shape_type const & idx)
{
const size_t offset = buffer_offset(m_stride, idx);
validate_range(offset);
return data(offset);
}
value_type const & at(std::vector<ssize_t> const & idx) const { return at(sshape_type(idx)); }
value_type & at(std::vector<ssize_t> const & idx) { return at(sshape_type(idx)); }
value_type const & at(sshape_type sidx) const
{
validate_shape(sidx);
sidx[0] += m_nghost;
shape_type const idx(sidx.begin(), sidx.end());
const size_t offset = buffer_offset(m_stride, idx);
return data(offset);
}
value_type & at(sshape_type sidx)
{
validate_shape(sidx);
sidx[0] += m_nghost;
shape_type const idx(sidx.begin(), sidx.end());
const size_t offset = buffer_offset(m_stride, idx);
return data(offset);
}
size_t ndim() const noexcept { return m_shape.size(); }
shape_type const & shape() const { return m_shape; }
size_t shape(size_t it) const noexcept { return m_shape[it]; }
size_t & shape(size_t it) noexcept { return m_shape[it]; }
shape_type const & stride() const { return m_stride; }
size_t stride(size_t it) const noexcept { return m_stride[it]; }
size_t & stride(size_t it) noexcept { return m_stride[it]; }
size_t nghost() const { return m_nghost; }
size_t nbody() const { return m_shape.empty() ? 0 : m_shape[0] - m_nghost; }
bool has_ghost() const { return m_nghost != 0; }
void set_nghost(size_t nghost)
{
if (0 != nghost)
{
if (0 == ndim())
{
std::ostringstream ms;
ms << "SimpleArray: cannot set nghost " << nghost << " > 0 to an empty array";
throw std::out_of_range(ms.str());
}
if (nghost > shape(0))
{
std::ostringstream ms;
ms << "SimpleArray: cannot set nghost " << nghost << " > shape(0) " << shape(0);
throw std::out_of_range(ms.str());
}
}
m_nghost = nghost;
if (bool(*this))
{
m_body = calc_body(m_buffer->data<T>(), m_stride, m_nghost);
}
}
template <typename U>
SimpleArray<U> reshape(shape_type const & shape) const
{
return SimpleArray<U>(shape, m_buffer);
}
SimpleArray reshape(shape_type const & shape) const
{
return SimpleArray(shape, m_buffer);
}
SimpleArray reshape() const
{
return SimpleArray(m_shape, m_buffer);
}
void swap(SimpleArray & other) noexcept
{
if (this != &other)
{
std::swap(m_buffer, other.m_buffer);
std::swap(m_shape, other.m_shape);
std::swap(m_stride, other.m_stride);
std::swap(m_nghost, other.m_nghost);
std::swap(m_body, other.m_body);
}
}
template <typename... Args>
value_type const & operator()(Args... args) const { return *vptr(args...); }
template <typename... Args>
value_type & operator()(Args... args) { return *vptr(args...); }
template <typename... Args>
value_type const * vptr(Args... args) const { return m_body + buffer_offset(m_stride, args...); }
template <typename... Args>
value_type * vptr(Args... args) { return m_body + buffer_offset(m_stride, args...); }
/* Backdoor */
value_type const & data(size_t it) const { return data()[it]; }
value_type & data(size_t it) { return data()[it]; }
value_type const * data() const { return buffer().template data<value_type>(); }
value_type * data() { return buffer().template data<value_type>(); }
buffer_type const & buffer() const { return *m_buffer; }
buffer_type & buffer() { return *m_buffer; }
value_type const * body() const { return m_body; }
value_type * body() { return m_body; }
private:
void validate_range(ssize_t it) const
{
if (m_nghost != 0 && ndim() != 1)
{
std::ostringstream ms;
ms << "SimpleArray::validate_range(): cannot handle "
<< ndim() << "-dimensional (more than 1) array with non-zero nghost: " << m_nghost;
throw std::out_of_range(ms.str());
}
if (it < -static_cast<ssize_t>(m_nghost))
{
std::ostringstream ms;
ms << "SimpleArray: index " << it << " < -nghost: " << -static_cast<ssize_t>(m_nghost);
throw std::out_of_range(ms.str());
}
if (it >= static_cast<ssize_t>(size() - m_nghost))
{
std::ostringstream ms;
ms << "SimpleArray: index " << it << " >= " << size() - m_nghost
<< " (size: " << size() << " - nghost: " << m_nghost << ")";
throw std::out_of_range(ms.str());
}
}
void validate_shape(small_vector<ssize_t> const & idx) const
{
auto index2string = [&idx]()
{
std::ostringstream ms;
ms << "[";
for (size_t it = 0; it < idx.size(); ++it)
{
ms << idx[it];
if (it != idx.size() - 1)
{
ms << ", ";
}
}
ms << "]";
return ms.str();
};
// Test for the "index shape".
if (idx.empty())
{
throw std::out_of_range("SimpleArray::validate_shape(): empty index");
}
if (idx.size() != m_shape.size())
{
std::ostringstream ms;
ms << "SimpleArray: dimension of input indices " << index2string() << " != array dimension " << m_shape.size();
throw std::out_of_range(ms.str());
}
// Test the first dimension.
if (idx[0] < -static_cast<ssize_t>(m_nghost))
{
std::ostringstream ms;
ms << "SimpleArray: dim 0 in " << index2string() << " < -nghost: " << -static_cast<ssize_t>(m_nghost);
throw std::out_of_range(ms.str());
}
if (idx[0] >= static_cast<ssize_t>(nbody()))
{
std::ostringstream ms;
// clang-format off
ms << "SimpleArray: dim 0 in " << index2string() << " >= nbody: " << nbody()
<< " (shape[0]: " << m_shape[0] << " - nghost: " << nghost() << ")";
// clang-format on
throw std::out_of_range(ms.str());
}
// Test the rest of the dimensions.
for (size_t it = 1; it < m_shape.size(); ++it)
{
if (idx[it] < 0)
{
std::ostringstream ms;
ms << "SimpleArray: dim " << it << " in " << index2string() << " < 0";
throw std::out_of_range(ms.str());
}
if (idx[it] >= static_cast<ssize_t>(m_shape[it]))
{
std::ostringstream ms;
ms << "SimpleArray: dim " << it << " in " << index2string()
<< " >= shape[" << it << "]: " << m_shape[it];
throw std::out_of_range(ms.str());
}
}
}
/// Contiguous data buffer for the array.
std::shared_ptr<buffer_type> m_buffer;
/// Each element in this vector is the number of element in the
/// corresponding dimension.
shape_type m_shape;
/// Each element in this vector is the number of elements (not number of
/// bytes) to skip for advancing an index in the corresponding dimension.
shape_type m_stride;
size_t m_nghost = 0;
value_type * m_body = nullptr;
}; /* end class SimpleArray */
template <typename S>
using is_simple_array = std::is_same<
std::remove_reference_t<S>,
SimpleArray<typename std::remove_reference_t<S>::value_type>>;
template <typename S>
inline constexpr bool is_simple_array_v = is_simple_array<S>::value;
} /* end namespace modmesh */
/* vim: set et ts=4 sw=4: */
|
Small vector optimization
(
small_vector.hpp
). See
https://github.com/solvcon/modmesh for how it works in an application.#1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 | #pragma once
/*
* Copyright (c) 2020, Yung-Yu Chen <yyc@solvcon.net>
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* - Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
* - Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
* - Neither the name of the copyright holder nor the names of its contributors
* may be used to endorse or promote products derived from this software
* without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
* LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*/
#include <stdexcept>
#include <array>
#include <vector>
#include <algorithm>
namespace modmesh
{
template <typename T, size_t N = 3>
class small_vector
{
public:
using value_type = T;
using iterator = T *;
using const_iterator = T const *;
explicit small_vector(size_t size)
: m_size(static_cast<unsigned int>(size))
{
if (m_size > N)
{
m_capacity = m_size;
// NOLINTNEXTLINE(cppcoreguidelines-owning-memory)
m_head = new T[m_capacity];
}
else
{
m_capacity = N;
m_head = m_data.data();
}
}
explicit small_vector(size_t size, T const & v)
: small_vector(size)
{
std::fill(begin(), end(), v);
}
explicit small_vector(std::vector<T> const & vector)
: small_vector(vector.size())
{
std::copy_n(vector.begin(), m_size, begin());
}
template <class InputIt>
small_vector(InputIt first, InputIt last)
: small_vector(last - first)
{
std::copy(first, last, begin());
}
small_vector(std::initializer_list<T> init)
: small_vector(init.size())
{
std::copy_n(init.begin(), m_size, begin());
}
small_vector() { m_head = m_data.data(); }
small_vector(small_vector const & other)
: m_size(other.m_size)
{
if (other.m_head == other.m_data.data())
{
m_capacity = N;
m_head = m_data.data();
}
else
{
m_capacity = m_size;
// NOLINTNEXTLINE(cppcoreguidelines-owning-memory)
m_head = new T[m_capacity];
}
std::copy_n(other.m_head, m_size, m_head);
}
small_vector(small_vector && other) noexcept
: m_size(other.m_size)
{
if (other.m_head == other.m_data.data())
{
m_capacity = N;
std::copy_n(other.m_data.begin(), m_size, m_data.begin());
m_head = m_data.data();
}
else
{
m_capacity = m_size;
m_head = other.m_head;
other.m_size = 0;
other.m_capacity = N;
other.m_head = other.m_data.data();
}
}
small_vector & operator=(small_vector const & other)
{
if (this != &other)
{
if (other.m_head == other.m_data.data())
{
if (m_head != m_data.data())
{
delete[] m_head;
m_head = m_data.data();
}
m_size = other.m_size;
m_capacity = N;
}
else
{
if (m_capacity < other.m_size)
{
delete[] m_head;
m_head = nullptr;
}
if (m_head == m_data.data() || m_head == nullptr)
{
m_capacity = other.m_size;
// NOLINTNEXTLINE(cppcoreguidelines-owning-memory)
m_head = new T[m_capacity];
}
m_size = other.m_size;
}
std::copy_n(other.m_head, m_size, m_head);
}
return *this;
}
small_vector & operator=(small_vector && other) noexcept
{
if (this != &other)
{
if (other.m_head == other.m_data.data())
{
if (m_head != m_data.data())
{
delete[] m_head;
m_head = m_data.data();
}
m_size = other.m_size;
m_capacity = N;
std::copy_n(other.m_data.begin(), m_size, m_data.begin());
}
else
{
m_size = other.m_size;
m_capacity = other.m_capacity;
m_head = other.m_head;
other.m_size = 0;
other.m_capacity = N;
other.m_head = other.m_data.data();
}
}
return *this;
}
small_vector & operator=(std::vector<T> const & other)
{
if (size() < other.size())
{
std::copy(other.begin(), other.begin() + size(), begin());
for (size_t it = size(); it < other.size(); ++it)
{
push_back(other[it]);
}
}
else
{
std::copy(other.begin(), other.end(), begin());
m_size = static_cast<unsigned int>(other.size());
}
return *this;
}
~small_vector()
{
if (m_head != m_data.data() && m_head != nullptr)
{
delete[] m_head;
m_head = nullptr;
}
}
size_t size() const noexcept { return m_size; }
size_t capacity() const noexcept { return m_capacity; }
bool empty() const noexcept { return 0 == m_size; }
iterator begin() noexcept { return m_head; }
iterator end() noexcept { return m_head + m_size; }
const_iterator begin() const noexcept { return m_head; }
const_iterator end() const noexcept { return m_head + m_size; }
const_iterator cbegin() const noexcept { return begin(); }
const_iterator cend() const noexcept { return end(); }
T const & operator[](size_t it) const { return m_head[it]; }
T & operator[](size_t it) { return m_head[it]; }
T const & at(size_t it) const
{
validate_range(it);
return (*this)[it];
}
T & at(size_t it)
{
validate_range(it);
return (*this)[it];
}
T const * data() const { return m_head; }
T * data() { return m_head; }
void clear() noexcept
{
if (m_head != m_data.data())
{
delete[] m_head;
m_head = m_data.data();
}
m_size = 0;
m_capacity = N;
}
void push_back(T const & value)
{
if (m_size == m_capacity)
{
m_capacity *= 2;
// NOLINTNEXTLINE(cppcoreguidelines-owning-memory)
T * storage = new T[m_capacity];
std::copy_n(m_head, m_size, storage);
if (m_head != m_data.data())
{
delete[] m_head;
}
m_head = storage;
}
m_head[m_size++] = value;
}
private:
void validate_range(size_t it) const
{
if (it >= size())
{
throw std::out_of_range("small_vector: index out of range");
}
}
T * m_head = nullptr;
unsigned int m_size = 0;
unsigned int m_capacity = N;
std::array<T, N> m_data;
}; /* end class small_vector */
template <typename T>
bool operator==(small_vector<T> const & lhs, small_vector<T> const & rhs)
{
return std::equal(lhs.begin(), lhs.end(), rhs.begin());
}
static_assert(sizeof(small_vector<size_t>) == 40, "small_vector<size_t> should use 40 bytes");
} /* end namespace modmesh */
/* vim: set et ts=4 sw=4: */
|