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matplotlibcpp.h
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3002 lines (2332 loc) · 97.7 KB
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#pragma once
// Python headers must be included before any system headers, since
// they define _POSIX_C_SOURCE
#include <Python.h>
#include <vector>
#include <map>
#include <array>
#include <numeric>
#include <algorithm>
#include <stdexcept>
#include <iostream>
#include <cstdint> // <cstdint> requires c++11 support
#include <functional>
#include <string> // std::stod
#ifndef WITHOUT_NUMPY
# define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
# include <numpy/arrayobject.h>
# ifdef WITH_OPENCV
# include <opencv2/opencv.hpp>
# endif // WITH_OPENCV
/*
* A bunch of constants were removed in OpenCV 4 in favour of enum classes, so
* define the ones we need here.
*/
# if CV_MAJOR_VERSION > 3
# define CV_BGR2RGB cv::COLOR_BGR2RGB
# define CV_BGRA2RGBA cv::COLOR_BGRA2RGBA
# endif
#endif // WITHOUT_NUMPY
#if PY_MAJOR_VERSION >= 3
# define PyString_FromString PyUnicode_FromString
# define PyInt_FromLong PyLong_FromLong
# define PyString_FromString PyUnicode_FromString
#endif
namespace matplotlibcpp {
namespace detail {
static std::string s_backend;
struct _interpreter {
PyObject* s_python_function_arrow;
PyObject *s_python_function_show;
PyObject *s_python_function_close;
PyObject *s_python_function_draw;
PyObject *s_python_function_pause;
PyObject *s_python_function_save;
PyObject *s_python_function_figure;
PyObject *s_python_function_fignum_exists;
PyObject *s_python_function_plot;
PyObject *s_python_function_quiver;
PyObject* s_python_function_contour;
PyObject *s_python_function_semilogx;
PyObject *s_python_function_semilogy;
PyObject *s_python_function_loglog;
PyObject *s_python_function_fill;
PyObject *s_python_function_fill_between;
PyObject *s_python_function_hist;
PyObject *s_python_function_imshow;
PyObject *s_python_function_scatter;
PyObject *s_python_function_boxplot;
PyObject *s_python_function_subplot;
PyObject *s_python_function_subplot2grid;
PyObject *s_python_function_legend;
PyObject *s_python_function_xlim;
PyObject *s_python_function_ion;
PyObject *s_python_function_ginput;
PyObject *s_python_function_ylim;
PyObject *s_python_function_title;
PyObject *s_python_function_axis;
PyObject *s_python_function_axhline;
PyObject *s_python_function_axvline;
PyObject *s_python_function_axvspan;
PyObject *s_python_function_xlabel;
PyObject *s_python_function_ylabel;
PyObject *s_python_function_gca;
PyObject *s_python_function_xticks;
PyObject *s_python_function_yticks;
PyObject* s_python_function_margins;
PyObject *s_python_function_tick_params;
PyObject *s_python_function_grid;
PyObject* s_python_function_cla;
PyObject *s_python_function_clf;
PyObject *s_python_function_errorbar;
PyObject *s_python_function_annotate;
PyObject *s_python_function_tight_layout;
PyObject *s_python_colormap;
PyObject *s_python_empty_tuple;
PyObject *s_python_function_stem;
PyObject *s_python_function_xkcd;
PyObject *s_python_function_text;
PyObject *s_python_function_suptitle;
PyObject *s_python_function_bar;
PyObject *s_python_function_barh;
PyObject *s_python_function_colorbar;
PyObject *s_python_function_subplots_adjust;
PyObject *s_python_function_rcparams;
PyObject *s_python_function_spy;
/* For now, _interpreter is implemented as a singleton since its currently not possible to have
multiple independent embedded python interpreters without patching the python source code
or starting a separate process for each. [1]
Furthermore, many python objects expect that they are destructed in the same thread as they
were constructed. [2] So for advanced usage, a `kill()` function is provided so that library
users can manually ensure that the interpreter is constructed and destroyed within the
same thread.
1: http://bytes.com/topic/python/answers/793370-multiple-independent-python-interpreters-c-c-program
2: https://github.com/lava/matplotlib-cpp/pull/202#issue-436220256
*/
static _interpreter& get() {
return interkeeper(false);
}
static _interpreter& kill() {
return interkeeper(true);
}
// Stores the actual singleton object referenced by `get()` and `kill()`.
static _interpreter& interkeeper(bool should_kill) {
static _interpreter ctx;
if (should_kill)
ctx.~_interpreter();
return ctx;
}
PyObject* safe_import(PyObject* module, std::string fname) {
PyObject* fn = PyObject_GetAttrString(module, fname.c_str());
if (!fn)
throw std::runtime_error(std::string("Couldn't find required function: ") + fname);
if (!PyFunction_Check(fn))
throw std::runtime_error(fname + std::string(" is unexpectedly not a PyFunction."));
return fn;
}
private:
#ifndef WITHOUT_NUMPY
# if PY_MAJOR_VERSION >= 3
void *import_numpy() {
import_array(); // initialize C-API
return NULL;
}
# else
void import_numpy() {
import_array(); // initialize C-API
}
# endif
#endif
_interpreter() {
// optional but recommended
#if PY_MAJOR_VERSION >= 3
wchar_t name[] = L"plotting";
#else
char name[] = "plotting";
#endif
Py_SetProgramName(name);
Py_Initialize();
wchar_t const *dummy_args[] = {L"Python", NULL}; // const is needed because literals must not be modified
wchar_t const **argv = dummy_args;
int argc = sizeof(dummy_args)/sizeof(dummy_args[0])-1;
#if PY_MAJOR_VERSION >= 3
PySys_SetArgv(argc, const_cast<wchar_t **>(argv));
#else
PySys_SetArgv(argc, (char **)(argv));
#endif
#ifndef WITHOUT_NUMPY
import_numpy(); // initialize numpy C-API
#endif
PyObject* matplotlibname = PyString_FromString("matplotlib");
PyObject* pyplotname = PyString_FromString("matplotlib.pyplot");
PyObject* cmname = PyString_FromString("matplotlib.cm");
PyObject* pylabname = PyString_FromString("pylab");
if (!pyplotname || !pylabname || !matplotlibname || !cmname) {
throw std::runtime_error("couldnt create string");
}
PyObject* matplotlib = PyImport_Import(matplotlibname);
Py_DECREF(matplotlibname);
if (!matplotlib) {
PyErr_Print();
throw std::runtime_error("Error loading module matplotlib!");
}
// matplotlib.use() must be called *before* pylab, matplotlib.pyplot,
// or matplotlib.backends is imported for the first time
if (!s_backend.empty()) {
PyObject_CallMethod(matplotlib, const_cast<char*>("use"), const_cast<char*>("s"), s_backend.c_str());
}
PyObject* pymod = PyImport_Import(pyplotname);
Py_DECREF(pyplotname);
if (!pymod) { throw std::runtime_error("Error loading module matplotlib.pyplot!"); }
s_python_colormap = PyImport_Import(cmname);
Py_DECREF(cmname);
if (!s_python_colormap) { throw std::runtime_error("Error loading module matplotlib.cm!"); }
PyObject* pylabmod = PyImport_Import(pylabname);
Py_DECREF(pylabname);
if (!pylabmod) { throw std::runtime_error("Error loading module pylab!"); }
s_python_function_arrow = safe_import(pymod, "arrow");
s_python_function_show = safe_import(pymod, "show");
s_python_function_close = safe_import(pymod, "close");
s_python_function_draw = safe_import(pymod, "draw");
s_python_function_pause = safe_import(pymod, "pause");
s_python_function_figure = safe_import(pymod, "figure");
s_python_function_fignum_exists = safe_import(pymod, "fignum_exists");
s_python_function_plot = safe_import(pymod, "plot");
s_python_function_quiver = safe_import(pymod, "quiver");
s_python_function_contour = safe_import(pymod, "contour");
s_python_function_semilogx = safe_import(pymod, "semilogx");
s_python_function_semilogy = safe_import(pymod, "semilogy");
s_python_function_loglog = safe_import(pymod, "loglog");
s_python_function_fill = safe_import(pymod, "fill");
s_python_function_fill_between = safe_import(pymod, "fill_between");
s_python_function_hist = safe_import(pymod,"hist");
s_python_function_scatter = safe_import(pymod,"scatter");
s_python_function_boxplot = safe_import(pymod,"boxplot");
s_python_function_subplot = safe_import(pymod, "subplot");
s_python_function_subplot2grid = safe_import(pymod, "subplot2grid");
s_python_function_legend = safe_import(pymod, "legend");
s_python_function_xlim = safe_import(pymod, "xlim");
s_python_function_ylim = safe_import(pymod, "ylim");
s_python_function_title = safe_import(pymod, "title");
s_python_function_axis = safe_import(pymod, "axis");
s_python_function_axhline = safe_import(pymod, "axhline");
s_python_function_axvline = safe_import(pymod, "axvline");
s_python_function_axvspan = safe_import(pymod, "axvspan");
s_python_function_xlabel = safe_import(pymod, "xlabel");
s_python_function_ylabel = safe_import(pymod, "ylabel");
s_python_function_gca = safe_import(pymod, "gca");
s_python_function_xticks = safe_import(pymod, "xticks");
s_python_function_yticks = safe_import(pymod, "yticks");
s_python_function_margins = safe_import(pymod, "margins");
s_python_function_tick_params = safe_import(pymod, "tick_params");
s_python_function_grid = safe_import(pymod, "grid");
s_python_function_ion = safe_import(pymod, "ion");
s_python_function_ginput = safe_import(pymod, "ginput");
s_python_function_save = safe_import(pylabmod, "savefig");
s_python_function_annotate = safe_import(pymod,"annotate");
s_python_function_cla = safe_import(pymod, "cla");
s_python_function_clf = safe_import(pymod, "clf");
s_python_function_errorbar = safe_import(pymod, "errorbar");
s_python_function_tight_layout = safe_import(pymod, "tight_layout");
s_python_function_stem = safe_import(pymod, "stem");
s_python_function_xkcd = safe_import(pymod, "xkcd");
s_python_function_text = safe_import(pymod, "text");
s_python_function_suptitle = safe_import(pymod, "suptitle");
s_python_function_bar = safe_import(pymod,"bar");
s_python_function_barh = safe_import(pymod, "barh");
s_python_function_colorbar = PyObject_GetAttrString(pymod, "colorbar");
s_python_function_subplots_adjust = safe_import(pymod,"subplots_adjust");
s_python_function_rcparams = PyObject_GetAttrString(pymod, "rcParams");
s_python_function_spy = PyObject_GetAttrString(pymod, "spy");
#ifndef WITHOUT_NUMPY
s_python_function_imshow = safe_import(pymod, "imshow");
#endif
s_python_empty_tuple = PyTuple_New(0);
}
~_interpreter() {
Py_Finalize();
}
};
} // end namespace detail
/// Select the backend
///
/// **NOTE:** This must be called before the first plot command to have
/// any effect.
///
/// Mainly useful to select the non-interactive 'Agg' backend when running
/// matplotlibcpp in headless mode, for example on a machine with no display.
///
/// See also: https://matplotlib.org/2.0.2/api/matplotlib_configuration_api.html#matplotlib.use
inline void backend(const std::string& name)
{
detail::s_backend = name;
}
inline bool annotate(std::string annotation, double x, double y)
{
detail::_interpreter::get();
PyObject * xy = PyTuple_New(2);
PyObject * str = PyString_FromString(annotation.c_str());
PyTuple_SetItem(xy,0,PyFloat_FromDouble(x));
PyTuple_SetItem(xy,1,PyFloat_FromDouble(y));
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "xy", xy);
PyObject* args = PyTuple_New(1);
PyTuple_SetItem(args, 0, str);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_annotate, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
namespace detail {
#ifndef WITHOUT_NUMPY
// Type selector for numpy array conversion
template <typename T> struct select_npy_type { const static NPY_TYPES type = NPY_NOTYPE; }; //Default
template <> struct select_npy_type<double> { const static NPY_TYPES type = NPY_DOUBLE; };
template <> struct select_npy_type<float> { const static NPY_TYPES type = NPY_FLOAT; };
template <> struct select_npy_type<bool> { const static NPY_TYPES type = NPY_BOOL; };
template <> struct select_npy_type<int8_t> { const static NPY_TYPES type = NPY_INT8; };
template <> struct select_npy_type<int16_t> { const static NPY_TYPES type = NPY_SHORT; };
template <> struct select_npy_type<int32_t> { const static NPY_TYPES type = NPY_INT; };
template <> struct select_npy_type<int64_t> { const static NPY_TYPES type = NPY_INT64; };
template <> struct select_npy_type<uint8_t> { const static NPY_TYPES type = NPY_UINT8; };
template <> struct select_npy_type<uint16_t> { const static NPY_TYPES type = NPY_USHORT; };
template <> struct select_npy_type<uint32_t> { const static NPY_TYPES type = NPY_ULONG; };
template <> struct select_npy_type<uint64_t> { const static NPY_TYPES type = NPY_UINT64; };
template<typename Numeric>
PyObject* get_array(const std::vector<Numeric>& v)
{
npy_intp vsize = v.size();
NPY_TYPES type = select_npy_type<Numeric>::type;
if (type == NPY_NOTYPE) {
size_t memsize = v.size()*sizeof(double);
double* dp = static_cast<double*>(::malloc(memsize));
for (size_t i=0; i<v.size(); ++i)
dp[i] = v[i];
PyObject* varray = PyArray_SimpleNewFromData(1, &vsize, NPY_DOUBLE, dp);
PyArray_UpdateFlags(reinterpret_cast<PyArrayObject*>(varray), NPY_ARRAY_OWNDATA);
return varray;
}
PyObject* varray = PyArray_SimpleNewFromData(1, &vsize, type, (void*)(v.data()));
return varray;
}
template<typename Numeric>
PyObject* get_2darray(const std::vector<::std::vector<Numeric>>& v)
{
if (v.size() < 1) throw std::runtime_error("get_2d_array v too small");
npy_intp vsize[2] = {static_cast<npy_intp>(v.size()),
static_cast<npy_intp>(v[0].size())};
PyArrayObject *varray =
(PyArrayObject *)PyArray_SimpleNew(2, vsize, NPY_DOUBLE);
double *vd_begin = static_cast<double *>(PyArray_DATA(varray));
for (const ::std::vector<Numeric> &v_row : v) {
if (v_row.size() != static_cast<size_t>(vsize[1]))
throw std::runtime_error("Missmatched array size");
std::copy(v_row.begin(), v_row.end(), vd_begin);
vd_begin += vsize[1];
}
return reinterpret_cast<PyObject *>(varray);
}
#else // fallback if we don't have numpy: copy every element of the given vector
template<typename Numeric>
PyObject* get_array(const std::vector<Numeric>& v)
{
PyObject* list = PyList_New(v.size());
for(size_t i = 0; i < v.size(); ++i) {
PyList_SetItem(list, i, PyFloat_FromDouble(v.at(i)));
}
return list;
}
#endif // WITHOUT_NUMPY
// sometimes, for labels and such, we need string arrays
inline PyObject * get_array(const std::vector<std::string>& strings)
{
PyObject* list = PyList_New(strings.size());
for (std::size_t i = 0; i < strings.size(); ++i) {
PyList_SetItem(list, i, PyString_FromString(strings[i].c_str()));
}
return list;
}
// not all matplotlib need 2d arrays, some prefer lists of lists
template<typename Numeric>
PyObject* get_listlist(const std::vector<std::vector<Numeric>>& ll)
{
PyObject* listlist = PyList_New(ll.size());
for (std::size_t i = 0; i < ll.size(); ++i) {
PyList_SetItem(listlist, i, get_array(ll[i]));
}
return listlist;
}
} // namespace detail
/// Plot a line through the given x and y data points..
///
/// See: https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.plot.html
template<typename Numeric>
bool plot(const std::vector<Numeric> &x, const std::vector<Numeric> &y, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y.size());
detail::_interpreter::get();
// using numpy arrays
PyObject* xarray = detail::get_array(x);
PyObject* yarray = detail::get_array(y);
// construct positional args
PyObject* args = PyTuple_New(2);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
// construct keyword args
PyObject* kwargs = PyDict_New();
for(std::map<std::string, std::string>::const_iterator it = keywords.begin(); it != keywords.end(); ++it)
{
PyDict_SetItemString(kwargs, it->first.c_str(), PyString_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_plot, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
// TODO - it should be possible to make this work by implementing
// a non-numpy alternative for `detail::get_2darray()`.
#ifndef WITHOUT_NUMPY
template <typename Numeric>
void plot_surface(const std::vector<::std::vector<Numeric>> &x,
const std::vector<::std::vector<Numeric>> &y,
const std::vector<::std::vector<Numeric>> &z,
const std::map<std::string, std::string> &keywords =
std::map<std::string, std::string>(),
const long fig_number=0)
{
detail::_interpreter::get();
// We lazily load the modules here the first time this function is called
// because I'm not sure that we can assume "matplotlib installed" implies
// "mpl_toolkits installed" on all platforms, and we don't want to require
// it for people who don't need 3d plots.
static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr;
if (!mpl_toolkitsmod) {
detail::_interpreter::get();
PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits");
PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d");
if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); }
mpl_toolkitsmod = PyImport_Import(mpl_toolkits);
Py_DECREF(mpl_toolkits);
if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); }
axis3dmod = PyImport_Import(axis3d);
Py_DECREF(axis3d);
if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); }
}
assert(x.size() == y.size());
assert(y.size() == z.size());
// using numpy arrays
PyObject *xarray = detail::get_2darray(x);
PyObject *yarray = detail::get_2darray(y);
PyObject *zarray = detail::get_2darray(z);
// construct positional args
PyObject *args = PyTuple_New(3);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
PyTuple_SetItem(args, 2, zarray);
// Build up the kw args.
PyObject *kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "rstride", PyInt_FromLong(1));
PyDict_SetItemString(kwargs, "cstride", PyInt_FromLong(1));
PyObject *python_colormap_coolwarm = PyObject_GetAttrString(
detail::_interpreter::get().s_python_colormap, "coolwarm");
PyDict_SetItemString(kwargs, "cmap", python_colormap_coolwarm);
for (std::map<std::string, std::string>::const_iterator it = keywords.begin();
it != keywords.end(); ++it) {
if (it->first == "linewidth" || it->first == "alpha") {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyFloat_FromDouble(std::stod(it->second)));
} else {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyString_FromString(it->second.c_str()));
}
}
PyObject *fig_args = PyTuple_New(1);
PyObject* fig = nullptr;
PyTuple_SetItem(fig_args, 0, PyLong_FromLong(fig_number));
PyObject *fig_exists =
PyObject_CallObject(
detail::_interpreter::get().s_python_function_fignum_exists, fig_args);
if (!PyObject_IsTrue(fig_exists)) {
fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure,
detail::_interpreter::get().s_python_empty_tuple);
} else {
fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure,
fig_args);
}
Py_DECREF(fig_exists);
if (!fig) throw std::runtime_error("Call to figure() failed.");
PyObject *gca_kwargs = PyDict_New();
PyDict_SetItemString(gca_kwargs, "projection", PyString_FromString("3d"));
PyObject *gca = PyObject_GetAttrString(fig, "gca");
if (!gca) throw std::runtime_error("No gca");
Py_INCREF(gca);
PyObject *axis = PyObject_Call(
gca, detail::_interpreter::get().s_python_empty_tuple, gca_kwargs);
if (!axis) throw std::runtime_error("No axis");
Py_INCREF(axis);
Py_DECREF(gca);
Py_DECREF(gca_kwargs);
PyObject *plot_surface = PyObject_GetAttrString(axis, "plot_surface");
if (!plot_surface) throw std::runtime_error("No surface");
Py_INCREF(plot_surface);
PyObject *res = PyObject_Call(plot_surface, args, kwargs);
if (!res) throw std::runtime_error("failed surface");
Py_DECREF(plot_surface);
Py_DECREF(axis);
Py_DECREF(args);
Py_DECREF(kwargs);
if (res) Py_DECREF(res);
}
template <typename Numeric>
void contour(const std::vector<::std::vector<Numeric>> &x,
const std::vector<::std::vector<Numeric>> &y,
const std::vector<::std::vector<Numeric>> &z,
const std::map<std::string, std::string> &keywords = {})
{
detail::_interpreter::get();
// using numpy arrays
PyObject *xarray = detail::get_2darray(x);
PyObject *yarray = detail::get_2darray(y);
PyObject *zarray = detail::get_2darray(z);
// construct positional args
PyObject *args = PyTuple_New(3);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
PyTuple_SetItem(args, 2, zarray);
// Build up the kw args.
PyObject *kwargs = PyDict_New();
PyObject *python_colormap_coolwarm = PyObject_GetAttrString(
detail::_interpreter::get().s_python_colormap, "coolwarm");
PyDict_SetItemString(kwargs, "cmap", python_colormap_coolwarm);
for (std::map<std::string, std::string>::const_iterator it = keywords.begin();
it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyString_FromString(it->second.c_str()));
}
PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_contour, args, kwargs);
if (!res)
throw std::runtime_error("failed contour");
Py_DECREF(args);
Py_DECREF(kwargs);
if (res) Py_DECREF(res);
}
template <typename Numeric>
void spy(const std::vector<::std::vector<Numeric>> &x,
const double markersize = -1, // -1 for default matplotlib size
const std::map<std::string, std::string> &keywords = {})
{
detail::_interpreter::get();
PyObject *xarray = detail::get_2darray(x);
PyObject *kwargs = PyDict_New();
if (markersize != -1) {
PyDict_SetItemString(kwargs, "markersize", PyFloat_FromDouble(markersize));
}
for (std::map<std::string, std::string>::const_iterator it = keywords.begin();
it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyString_FromString(it->second.c_str()));
}
PyObject *plot_args = PyTuple_New(1);
PyTuple_SetItem(plot_args, 0, xarray);
PyObject *res = PyObject_Call(
detail::_interpreter::get().s_python_function_spy, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if (res) Py_DECREF(res);
}
#endif // WITHOUT_NUMPY
template <typename Numeric>
void plot3(const std::vector<Numeric> &x,
const std::vector<Numeric> &y,
const std::vector<Numeric> &z,
const std::map<std::string, std::string> &keywords =
std::map<std::string, std::string>(),
const long fig_number=0)
{
detail::_interpreter::get();
// Same as with plot_surface: We lazily load the modules here the first time
// this function is called because I'm not sure that we can assume "matplotlib
// installed" implies "mpl_toolkits installed" on all platforms, and we don't
// want to require it for people who don't need 3d plots.
static PyObject *mpl_toolkitsmod = nullptr, *axis3dmod = nullptr;
if (!mpl_toolkitsmod) {
detail::_interpreter::get();
PyObject* mpl_toolkits = PyString_FromString("mpl_toolkits");
PyObject* axis3d = PyString_FromString("mpl_toolkits.mplot3d");
if (!mpl_toolkits || !axis3d) { throw std::runtime_error("couldnt create string"); }
mpl_toolkitsmod = PyImport_Import(mpl_toolkits);
Py_DECREF(mpl_toolkits);
if (!mpl_toolkitsmod) { throw std::runtime_error("Error loading module mpl_toolkits!"); }
axis3dmod = PyImport_Import(axis3d);
Py_DECREF(axis3d);
if (!axis3dmod) { throw std::runtime_error("Error loading module mpl_toolkits.mplot3d!"); }
}
assert(x.size() == y.size());
assert(y.size() == z.size());
PyObject *xarray = detail::get_array(x);
PyObject *yarray = detail::get_array(y);
PyObject *zarray = detail::get_array(z);
// construct positional args
PyObject *args = PyTuple_New(3);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
PyTuple_SetItem(args, 2, zarray);
// Build up the kw args.
PyObject *kwargs = PyDict_New();
for (std::map<std::string, std::string>::const_iterator it = keywords.begin();
it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyString_FromString(it->second.c_str()));
}
PyObject *fig_args = PyTuple_New(1);
PyObject* fig = nullptr;
PyTuple_SetItem(fig_args, 0, PyLong_FromLong(fig_number));
PyObject *fig_exists =
PyObject_CallObject(detail::_interpreter::get().s_python_function_fignum_exists, fig_args);
if (!PyObject_IsTrue(fig_exists)) {
fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure,
detail::_interpreter::get().s_python_empty_tuple);
} else {
fig = PyObject_CallObject(detail::_interpreter::get().s_python_function_figure,
fig_args);
}
if (!fig) throw std::runtime_error("Call to figure() failed.");
PyObject *gca_kwargs = PyDict_New();
PyDict_SetItemString(gca_kwargs, "projection", PyString_FromString("3d"));
PyObject *gca = PyObject_GetAttrString(fig, "gca");
if (!gca) throw std::runtime_error("No gca");
Py_INCREF(gca);
PyObject *axis = PyObject_Call(
gca, detail::_interpreter::get().s_python_empty_tuple, gca_kwargs);
if (!axis) throw std::runtime_error("No axis");
Py_INCREF(axis);
Py_DECREF(gca);
Py_DECREF(gca_kwargs);
PyObject *plot3 = PyObject_GetAttrString(axis, "plot");
if (!plot3) throw std::runtime_error("No 3D line plot");
Py_INCREF(plot3);
PyObject *res = PyObject_Call(plot3, args, kwargs);
if (!res) throw std::runtime_error("Failed 3D line plot");
Py_DECREF(plot3);
Py_DECREF(axis);
Py_DECREF(args);
Py_DECREF(kwargs);
if (res) Py_DECREF(res);
}
template<typename Numeric>
bool stem(const std::vector<Numeric> &x, const std::vector<Numeric> &y, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y.size());
detail::_interpreter::get();
// using numpy arrays
PyObject* xarray = detail::get_array(x);
PyObject* yarray = detail::get_array(y);
// construct positional args
PyObject* args = PyTuple_New(2);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
// construct keyword args
PyObject* kwargs = PyDict_New();
for (std::map<std::string, std::string>::const_iterator it =
keywords.begin(); it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(),
PyString_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(
detail::_interpreter::get().s_python_function_stem, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if (res)
Py_DECREF(res);
return res;
}
template< typename Numeric >
bool fill(const std::vector<Numeric>& x, const std::vector<Numeric>& y, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y.size());
detail::_interpreter::get();
// using numpy arrays
PyObject* xarray = detail::get_array(x);
PyObject* yarray = detail::get_array(y);
// construct positional args
PyObject* args = PyTuple_New(2);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, yarray);
// construct keyword args
PyObject* kwargs = PyDict_New();
for (auto it = keywords.begin(); it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_fill, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if (res) Py_DECREF(res);
return res;
}
template< typename Numeric >
bool fill_between(const std::vector<Numeric>& x, const std::vector<Numeric>& y1, const std::vector<Numeric>& y2, const std::map<std::string, std::string>& keywords)
{
assert(x.size() == y1.size());
assert(x.size() == y2.size());
detail::_interpreter::get();
// using numpy arrays
PyObject* xarray = detail::get_array(x);
PyObject* y1array = detail::get_array(y1);
PyObject* y2array = detail::get_array(y2);
// construct positional args
PyObject* args = PyTuple_New(3);
PyTuple_SetItem(args, 0, xarray);
PyTuple_SetItem(args, 1, y1array);
PyTuple_SetItem(args, 2, y2array);
// construct keyword args
PyObject* kwargs = PyDict_New();
for(std::map<std::string, std::string>::const_iterator it = keywords.begin(); it != keywords.end(); ++it) {
PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str()));
}
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_fill_between, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
template <typename Numeric>
bool arrow(Numeric x, Numeric y, Numeric end_x, Numeric end_y, const std::string& fc = "r",
const std::string ec = "k", Numeric head_length = 0.25, Numeric head_width = 0.1625) {
PyObject* obj_x = PyFloat_FromDouble(x);
PyObject* obj_y = PyFloat_FromDouble(y);
PyObject* obj_end_x = PyFloat_FromDouble(end_x);
PyObject* obj_end_y = PyFloat_FromDouble(end_y);
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "fc", PyString_FromString(fc.c_str()));
PyDict_SetItemString(kwargs, "ec", PyString_FromString(ec.c_str()));
PyDict_SetItemString(kwargs, "head_width", PyFloat_FromDouble(head_width));
PyDict_SetItemString(kwargs, "head_length", PyFloat_FromDouble(head_length));
PyObject* plot_args = PyTuple_New(4);
PyTuple_SetItem(plot_args, 0, obj_x);
PyTuple_SetItem(plot_args, 1, obj_y);
PyTuple_SetItem(plot_args, 2, obj_end_x);
PyTuple_SetItem(plot_args, 3, obj_end_y);
PyObject* res =
PyObject_Call(detail::_interpreter::get().s_python_function_arrow, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if (res)
Py_DECREF(res);
return res;
}
template< typename Numeric>
bool hist(const std::vector<Numeric>& y, long bins=10,std::string color="b",
double alpha=1.0, bool cumulative=false)
{
detail::_interpreter::get();
PyObject* yarray = detail::get_array(y);
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "bins", PyLong_FromLong(bins));
PyDict_SetItemString(kwargs, "color", PyString_FromString(color.c_str()));
PyDict_SetItemString(kwargs, "alpha", PyFloat_FromDouble(alpha));
PyDict_SetItemString(kwargs, "cumulative", cumulative ? Py_True : Py_False);
PyObject* plot_args = PyTuple_New(1);
PyTuple_SetItem(plot_args, 0, yarray);
PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_hist, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if(res) Py_DECREF(res);
return res;
}
#ifndef WITHOUT_NUMPY
namespace detail {
inline void imshow(void *ptr, const NPY_TYPES type, const int rows, const int columns, const int colors, const std::map<std::string, std::string> &keywords, PyObject** out)
{
assert(type == NPY_UINT8 || type == NPY_FLOAT);
assert(colors == 1 || colors == 3 || colors == 4);
detail::_interpreter::get();
// construct args
npy_intp dims[3] = { rows, columns, colors };
PyObject *args = PyTuple_New(1);
PyTuple_SetItem(args, 0, PyArray_SimpleNewFromData(colors == 1 ? 2 : 3, dims, type, ptr));
// construct keyword args
PyObject* kwargs = PyDict_New();
for(std::map<std::string, std::string>::const_iterator it = keywords.begin(); it != keywords.end(); ++it)
{
PyDict_SetItemString(kwargs, it->first.c_str(), PyUnicode_FromString(it->second.c_str()));
}
PyObject *res = PyObject_Call(detail::_interpreter::get().s_python_function_imshow, args, kwargs);
Py_DECREF(args);
Py_DECREF(kwargs);
if (!res)
throw std::runtime_error("Call to imshow() failed");
if (out)
*out = res;
else
Py_DECREF(res);
}
} // namespace detail
inline void imshow(const unsigned char *ptr, const int rows, const int columns, const int colors, const std::map<std::string, std::string> &keywords = {}, PyObject** out = nullptr)
{
detail::imshow((void *) ptr, NPY_UINT8, rows, columns, colors, keywords, out);
}
inline void imshow(const float *ptr, const int rows, const int columns, const int colors, const std::map<std::string, std::string> &keywords = {}, PyObject** out = nullptr)
{
detail::imshow((void *) ptr, NPY_FLOAT, rows, columns, colors, keywords, out);
}
#ifdef WITH_OPENCV
void imshow(const cv::Mat &image, const std::map<std::string, std::string> &keywords = {})
{
// Convert underlying type of matrix, if needed
cv::Mat image2;
NPY_TYPES npy_type = NPY_UINT8;
switch (image.type() & CV_MAT_DEPTH_MASK) {
case CV_8U:
image2 = image;
break;
case CV_32F:
image2 = image;
npy_type = NPY_FLOAT;
break;
default:
image.convertTo(image2, CV_MAKETYPE(CV_8U, image.channels()));
}
// If color image, convert from BGR to RGB
switch (image2.channels()) {
case 3:
cv::cvtColor(image2, image2, CV_BGR2RGB);
break;
case 4:
cv::cvtColor(image2, image2, CV_BGRA2RGBA);
}
detail::imshow(image2.data, npy_type, image2.rows, image2.cols, image2.channels(), keywords);
}
#endif // WITH_OPENCV
#endif // WITHOUT_NUMPY
template<typename NumericX, typename NumericY>
bool scatter(const std::vector<NumericX>& x,
const std::vector<NumericY>& y,
const double s=1.0, // The marker size in points**2
const std::map<std::string, std::string> & keywords = {})
{
detail::_interpreter::get();
assert(x.size() == y.size());
PyObject* xarray = detail::get_array(x);
PyObject* yarray = detail::get_array(y);
PyObject* kwargs = PyDict_New();
PyDict_SetItemString(kwargs, "s", PyLong_FromLong(s));
for (const auto& it : keywords)