#pragma once

#include <vector>

#include <map>

#include <array>

#include <numeric>

#include <algorithm>

#include <stdexcept>

#include <iostream>

#include <cstdint> // <cstdint> requires c++11 support

#include <functional>

#include <unordered_map>

#include <Python.h>

#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_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_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_axvline;

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_tick_params;

PyObject *s_python_function_grid;

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_colorbar;

PyObject *s_python_function_subplots_adjust;

/* 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.

http://bytes.com/topic/python/answers/793370-multiple-independent-python-interpreters-c-c-program

*/

static _interpreter& get() {

static _interpreter ctx;

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();

#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_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_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_ylim = safe_import(pymod, "ylim");

s_python_function_title = safe_import(pymod, "title");

s_python_function_axis = safe_import(pymod, "axis");

s_python_function_axvline = safe_import(pymod, "axvline");

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_tick_params = safe_import(pymod, "tick_params");

s_python_function_grid = safe_import(pymod, "grid");

s_python_function_xlim = safe_import(pymod, "xlim");

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_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_colorbar = PyObject_GetAttrString(pymod, "colorbar");

s_python_function_subplots_adjust = safe_import(pymod,"subplots_adjust");

#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

// must be called before the first regular call to matplotlib to have any effect

inline void backend(const std::string& name)

{

detail::s_backend = name;

}

inline bool annotate(std::string annotation, double x, double y)

{

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;

}

#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)

{

detail::_interpreter::get(); //interpreter needs to be initialized for the numpy commands to work

NPY_TYPES type = select_npy_type<Numeric>::type;

if (type == NPY_NOTYPE)

{

std::vector<double> vd(v.size());

npy_intp vsize = v.size();

std::copy(v.begin(),v.end(),vd.begin());

PyObject* varray = PyArray_SimpleNewFromData(1, &vsize, NPY_DOUBLE, (void*)(vd.data()));

return varray;

}

npy_intp vsize = v.size();

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)

{

detail::_interpreter::get(); //interpreter needs to be initialized for the numpy commands to work

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);

}

// sometimes, for labels and such, we need string arrays

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;

}

#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

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());

// using numpy arrays

PyObject* xarray = get_array(x);

PyObject* yarray = 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 `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>())

{

// 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 = get_2darray(x);

PyObject *yarray = get_2darray(y);

PyObject *zarray = 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) {

PyDict_SetItemString(kwargs, it->first.c_str(),

PyString_FromString(it->second.c_str()));

}

PyObject *fig =

PyObject_CallObject(detail::_interpreter::get().s_python_function_figure,

detail::_interpreter::get().s_python_empty_tuple);

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);

}

#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>())

{

// 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 = get_array(x);

PyObject *yarray = get_array(y);

PyObject *zarray = 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 =

PyObject_CallObject(detail::_interpreter::get().s_python_function_figure,

detail::_interpreter::get().s_python_empty_tuple);

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());

// using numpy arrays

PyObject* xarray = get_array(x);

PyObject* yarray = 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());

// using numpy arrays

PyObject* xarray = get_array(x);

PyObject* yarray = 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());

// using numpy arrays

PyObject* xarray = get_array(x);

PyObject* y1array = get_array(y1);

PyObject* y2array = 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 hist(const std::vector<Numeric>& y, long bins=10,std::string color="b",

double alpha=1.0, bool cumulative=false)

{

PyObject* yarray = 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 internal {

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(); //interpreter needs to be initialized for the numpy commands to work

// 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 internal

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)

{

internal::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)

{

internal::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);

}

internal::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::unordered_map<std::string, std::string> & keywords = {})

{

assert(x.size() == y.size());

PyObject* xarray = get_array(x);

PyObject* yarray = get_array(y);

PyObject* kwargs = PyDict_New();

PyDict_SetItemString(kwargs, "s", PyLong_FromLong(s));

for (const auto& it : keywords)

{

PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str()));

}

PyObject* plot_args = PyTuple_New(2);

PyTuple_SetItem(plot_args, 0, xarray);

PyTuple_SetItem(plot_args, 1, yarray);

PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_scatter, plot_args, kwargs);

Py_DECREF(plot_args);

Py_DECREF(kwargs);

if(res) Py_DECREF(res);

return res;

}

template<typename Numeric>

bool boxplot(const std::vector<std::vector<Numeric>>& data,

const std::vector<std::string>& labels = {},

const std::unordered_map<std::string, std::string> & keywords = {})

{

PyObject* listlist = get_listlist(data);

PyObject* args = PyTuple_New(1);

PyTuple_SetItem(args, 0, listlist);

PyObject* kwargs = PyDict_New();

// kwargs needs the labels, if there are (the correct number of) labels

if (!labels.empty() && labels.size() == data.size()) {

PyDict_SetItemString(kwargs, "labels", get_array(labels));

}

// take care of the remaining keywords

for (const auto& it : keywords)

{

PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str()));

}

PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_boxplot, args, kwargs);

Py_DECREF(args);

Py_DECREF(kwargs);

if(res) Py_DECREF(res);

return res;

}

template<typename Numeric>

bool boxplot(const std::vector<Numeric>& data,

const std::unordered_map<std::string, std::string> & keywords = {})

{

PyObject* vector = get_array(data);

PyObject* args = PyTuple_New(1);

PyTuple_SetItem(args, 0, vector);

PyObject* kwargs = PyDict_New();

for (const auto& it : keywords)

{

PyDict_SetItemString(kwargs, it.first.c_str(), PyString_FromString(it.second.c_str()));

}

PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_boxplot, args, kwargs);

Py_DECREF(args);

Py_DECREF(kwargs);

if(res) Py_DECREF(res);

return res;

}

template <typename Numeric>

bool bar(const std::vector<Numeric> & x,

const std::vector<Numeric> & y,

std::string ec = "black",

std::string ls = "-",

double lw = 1.0,

const std::map<std::string, std::string> & keywords = {}) {

PyObject * xarray = get_array(x);

PyObject * yarray = get_array(y);

PyObject * kwargs = PyDict_New();

PyDict_SetItemString(kwargs, "ec", PyString_FromString(ec.c_str()));

PyDict_SetItemString(kwargs, "ls", PyString_FromString(ls.c_str()));

PyDict_SetItemString(kwargs, "lw", PyFloat_FromDouble(lw));

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 * plot_args = PyTuple_New(2);

PyTuple_SetItem(plot_args, 0, xarray);

PyTuple_SetItem(plot_args, 1, yarray);

PyObject * res = PyObject_Call(

detail::_interpreter::get().s_python_function_bar, plot_args, kwargs);

Py_DECREF(plot_args);

Py_DECREF(kwargs);

if (res) Py_DECREF(res);

return res;

}

template <typename Numeric>

bool bar(const std::vector<Numeric> & y,

std::string ec = "black",

std::string ls = "-",

double lw = 1.0,

const std::map<std::string, std::string> & keywords = {}) {

using T = typename std::remove_reference<decltype(y)>::type::value_type;

std::vector<T> x;

for (std::size_t i = 0; i < y.size(); i++) { x.push_back(i); }

return bar(x, y, ec, ls, lw, keywords);

}

inline bool subplots_adjust(const std::map<std::string, double>& keywords = {})

{

PyObject* kwargs = PyDict_New();

for (std::map<std::string, double>::const_iterator it =

keywords.begin(); it != keywords.end(); ++it) {

PyDict_SetItemString(kwargs, it->first.c_str(),

PyFloat_FromDouble(it->second));

}

PyObject* plot_args = PyTuple_New(0);

PyObject* res = PyObject_Call(detail::_interpreter::get().s_python_function_subplots_adjust, plot_args, kwargs);

Py_DECREF(plot_args);

Py_DECREF(kwargs);

if(res) Py_DECREF(res);

return res;

}

template< typename Numeric>

bool named_hist(std::string label,const std::vector<Numeric>& y, long bins=10, std::string color="b", double alpha=1.0)

{

PyObject* yarray = get_array(y);

PyObject* kwargs = PyDict_New();

PyDict_SetItemString(kwargs, "label", PyString_FromString(label.c_str()));

PyDict_SetItemString(kwargs, "bins", PyLong_FromLong(bins));

PyDict_SetItemString(kwargs, "color", PyString_FromString(color.c_str()));

PyDict_SetItemString(kwargs, "alpha", PyFloat_FromDouble(alpha));

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;

}

template<typename NumericX, typename NumericY>

bool plot(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::string& s = "")

{

assert(x.size() == y.size());

PyObject* xarray = get_array(x);

PyObject* yarray = get_array(y);

PyObject* pystring = PyString_FromString(s.c_str());

PyObject* plot_args = PyTuple_New(3);

PyTuple_SetItem(plot_args, 0, xarray);

PyTuple_SetItem(plot_args, 1, yarray);

PyTuple_SetItem(plot_args, 2, pystring);

PyObject* res = PyObject_CallObject(detail::_interpreter::get().s_python_function_plot, plot_args);

Py_DECREF(plot_args);

if(res) Py_DECREF(res);

return res;

}

template<typename NumericX, typename NumericY, typename NumericU, typename NumericW>

bool quiver(const std::vector<NumericX>& x, const std::vector<NumericY>& y, const std::vector<NumericU>& u, const std::vector<NumericW>& w, const std::map<std::string, std::string>& keywords = {})

{

assert(x.size() == y.size() && x.size() == u.size() && u.size() == w.size());

PyObject* xarray = get_array(x);

PyObject* yarray = get_array(y);

PyObject* uarray = get_array(u);

PyObject* warray = get_array(w);

PyObject* plot_args = PyTuple_New(4);

PyTuple_SetItem(plot_args, 0, xarray);

PyTuple_SetItem(plot_args, 1, yarray);

PyTuple_SetItem(plot_args, 2, uarray);

PyTuple_SetItem(plot_args, 3, warray);