Example Code: C++ and C for Python#

Use libst to solve a propagating linear wave (01_linear.py).#
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#!/usr/bin/env python3

# [begin example]
import numpy as np
from matplotlib import pyplot as plt

# Import the extension module that is written in C++
import libst

# Build the one-dimensional uniform grid and the corresponding solver
grid = libst.Grid(0, 4*2*np.pi, 4*64)
cfl = 1
dx = (grid.xmax - grid.xmin) / grid.ncelm
dt = dx * cfl
svr = libst.LinearScalarSolver(grid=grid, time_increment=dt)

# Initialize the field using a sinusoidal
for e in svr.selms(odd_plane=False):
    if e.xctr < 2*np.pi or e.xctr > 2*2*np.pi:
        v = 0
        dv = 0
    else:
        v = np.sin(e.xctr)
        dv = np.cos(e.xctr)
    e.set_so0(0, v)
    e.set_so1(0, dv)

# Set up plotting
plt.figure(figsize=(15,10))
plt.xlim((0, 8))
plt.xlabel('$x$ $(\pi)$')
plt.ylabel('$u$')
plt.grid()

# Plot the initial condition
plt.plot(svr.xctr() / np.pi, svr.get_so0(0).ndarray, '-', label='begin')

# Time march
svr.setup_march()
svr.march_alpha2(50)

# Plot the time marched solution
plt.plot(svr.xctr() / np.pi, svr.get_so0(0).ndarray, '-', label='end')

plt.legend()
# [end example]

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)
Use libst to solve the Bergers equation (01_burgers.py).#
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#!/usr/bin/env python3

# [begin example]
import numpy as np
from matplotlib import pyplot as plt

# Import the extension module that is written in C++
import libst

# Build the one-dimensional uniform grid and the corresponding solver
res = 32
xcrd = np.arange(res+1) / res * 2 * np.pi

time_stop = 2*np.pi

grid = libst.Grid(xcrd)
cfl_max = 1.0
dx = (grid.xmax - grid.xmin) / grid.ncelm
dt_max = dx * cfl_max
nstep = int(np.ceil(time_stop / dt_max))
dt = time_stop / nstep
cfl = dt / dx

svr = libst.InviscidBurgersSolver(grid=grid, time_increment=dt)

# Initialize the field using a sinusoidal
svr.set_so0(0, np.sin(svr.xctr()))
svr.set_so1(0, np.cos(svr.xctr()))

# Set up plotting
plt.figure(figsize=(15,10))
plt.xlim((0, 2))
plt.xlabel('$x$ $(\pi)$')
plt.ylabel('$u$')
plt.grid()

# Plot the initial condition
plt.plot(svr.xctr() / np.pi, svr.get_so0(0).ndarray, '-', label='begin')

# Time march
svr.setup_march()
svr.march_alpha2(50)

# Plot the time marched solution
plt.plot(svr.xctr() / np.pi, svr.get_so0(0).ndarray, '-', label='end')

plt.legend()
# [end example]

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)
setup.py for pybind11 (setup.py).#
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# This file is copied from
# https://github.com/pybind/python_example/blob/master/setup.py

from setuptools import setup

# Available at setup time due to pyproject.toml
from pybind11.setup_helpers import Pybind11Extension, build_ext
from pybind11 import get_cmake_dir

import sys

__version__ = "0.0.1"

# The main interface is through Pybind11Extension.
# * You can add cxx_std=11/14/17, and then build_ext can be removed.
# * You can set include_pybind11=false to add the include directory yourself,
#   say from a submodule.
#
# Note:
#   Sort input source files if you glob sources to ensure bit-for-bit
#   reproducible builds (https://github.com/pybind/python_example/pull/53)

ext_modules = [
    Pybind11Extension("python_example",
        ["main.cpp"],
        # Example: passing in the version to the compiled code
        define_macros = [('VERSION_INFO', __version__)],
        ),
]

setup(
    name="python_example",
    version=__version__,
    author="Sylvain Corlay",
    author_email="sylvain.corlay@gmail.com",
    url="https://github.com/pybind/python_example",
    description="A test project using pybind11",
    long_description="",
    ext_modules=ext_modules,
    extras_require={"test": "pytest"},
    # Currently, build_ext only provides an optional "highest supported C++
    # level" feature, but in the future it may provide more features.
    cmdclass={"build_ext": build_ext},
    zip_safe=False,
)
Simple C++ code for using pybind11 (main.cpp).#
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#include <pybind11/pybind11.h>

#define STRINGIFY(x) #x
#define MACRO_STRINGIFY(x) STRINGIFY(x)

int add(int i, int j)
{
    return i + j;
}

namespace py = pybind11;

PYBIND11_MODULE(python_example, m)
{
    m.doc() = R"pbdoc(
        Pybind11 example plugin
        -----------------------

        .. currentmodule:: python_example

        .. autosummary::
           :toctree: _generate

           add
           subtract
    )pbdoc";

    m.def
    (
        "add"
      , &add
      , R"pbdoc(
        Add two numbers

        Some other explanation about the add function.
        )pbdoc"
    );

    m.def
    (
        "subtract"
      , [](int i, int j) { return i - j; }
      , R"pbdoc(
        Subtract two numbers

        Some other explanation about the subtract function.
        )pbdoc"
    );

#ifdef VERSION_INFO
    m.attr("__version__") = MACRO_STRINGIFY(VERSION_INFO);
#else
    m.attr("__version__") = "dev";
#endif
}
Build setup.py with main.cpp.#
$ python3 setup.py build_ext --inplace
Show how the C++-to-Python adapter for iterator works (04_iter.py).#
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#!/usr/bin/env python3

# [begin example]
import numpy as np
from matplotlib import pyplot as plt

# Import the extension module that is written in C++
import libst

# Build the one-dimensional uniform grid and the corresponding solver
grid = libst.Grid(0, 4*2*np.pi, 4*64)
cfl = 1
dx = (grid.xmax - grid.xmin) / grid.ncelm
dt = dx * cfl
svr = libst.LinearScalarSolver(grid=grid, time_increment=dt)

# Initialize
# NOTE: 'selms' returns a template instance of SolverElementIterator
for e in svr.selms(odd_plane=False):
    if e.xctr < 2*np.pi or e.xctr > 2*2*np.pi:
        v = 0
        dv = 0
    else:
        v = np.sin(e.xctr)
        dv = np.cos(e.xctr)
    e.set_so0(0, v)
    e.set_so1(0, dv)

# Set up plotting
plt.figure(figsize=(15,10))
plt.xlim((0, 8))
plt.xlabel('$x$ $(\pi)$')
plt.ylabel('$u$')
plt.grid()

# Plot the initial condition
plt.plot(svr.xctr() / np.pi, svr.get_so0(0).ndarray, '-')
# [end example]

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)