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matplotlibcpp.h
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//
// Wishlist:
// * (WIP) Make work for Eigen Vectors and Matrices
// * export functions in different files for better structure
// * make plot(y) work with x of unsigned type, or get to the bottom of that
// problem at least
// * errorbar for xerr and yerr
// * errorbar for yerr of shape (2, N)
//
// Changed:
// * Implement a better way for named_plot, maybe just as additional
// method with extra keyword
// * add location keyword for legend
//
#pragma once
#include <algorithm>
#include <array>
#include <cstdint> // <cstdint> requires c++11 support
#include <functional>
#include <iostream>
#include <map>
#include <numeric>
#include <stdexcept>
#include <vector>
#include <sstream>
#include <Python.h>
#ifndef WITHOUT_NUMPY
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
#include <numpy/arrayobject.h>
#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_contour;
PyObject *s_python_function_colormap;
PyObject *s_python_function_axhline;
PyObject *s_python_function_axvline;
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_scatter;
PyObject *s_python_function_spy;
PyObject *s_python_function_subplot;
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_xlabel;
PyObject *s_python_function_ylabel;
PyObject *s_python_function_xticks;
PyObject *s_python_function_yticks;
PyObject *s_python_function_xscale;
PyObject *s_python_function_yscale;
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_subplots_adjust;
PyObject *s_python_function_imshow;PyObject *s_python_function_colorbar;
/* 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;
}
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 = PyObject_GetAttrString(pymod, "show");
s_python_function_close = PyObject_GetAttrString(pymod, "close");
s_python_function_draw = PyObject_GetAttrString(pymod, "draw");
s_python_function_pause = PyObject_GetAttrString(pymod, "pause");
s_python_function_figure = PyObject_GetAttrString(pymod, "figure");
s_python_function_fignum_exists =
PyObject_GetAttrString(pymod, "fignum_exists");
s_python_function_plot = PyObject_GetAttrString(pymod, "plot");
s_python_function_quiver = PyObject_GetAttrString(pymod, "quiver");
s_python_function_contour = PyObject_GetAttrString(pymod, "contour");
s_python_function_axhline = PyObject_GetAttrString(pymod, "axhline");
s_python_function_axvline = PyObject_GetAttrString(pymod, "axvline");
s_python_function_semilogx = PyObject_GetAttrString(pymod, "semilogx");
s_python_function_semilogy = PyObject_GetAttrString(pymod, "semilogy");
s_python_function_loglog = PyObject_GetAttrString(pymod, "loglog");
s_python_function_fill = PyObject_GetAttrString(pymod, "fill");
s_python_function_fill_between =
PyObject_GetAttrString(pymod, "fill_between");
s_python_function_hist = PyObject_GetAttrString(pymod, "hist");
s_python_function_scatter = PyObject_GetAttrString(pymod, "scatter");
s_python_function_spy = PyObject_GetAttrString(pymod, "spy");
s_python_function_subplot = PyObject_GetAttrString(pymod, "subplot");
s_python_function_legend = PyObject_GetAttrString(pymod, "legend");
s_python_function_ylim = PyObject_GetAttrString(pymod, "ylim");
s_python_function_title = PyObject_GetAttrString(pymod, "title");
s_python_function_axis = PyObject_GetAttrString(pymod, "axis");
s_python_function_xlabel = PyObject_GetAttrString(pymod, "xlabel");
s_python_function_ylabel = PyObject_GetAttrString(pymod, "ylabel");
s_python_function_xticks = PyObject_GetAttrString(pymod, "xticks");
s_python_function_yticks = PyObject_GetAttrString(pymod, "yticks");
s_python_function_xscale = PyObject_GetAttrString(pymod, "xscale");
s_python_function_yscale = PyObject_GetAttrString(pymod, "yscale");
s_python_function_grid = PyObject_GetAttrString(pymod, "grid");
s_python_function_xlim = PyObject_GetAttrString(pymod, "xlim");
s_python_function_ion = PyObject_GetAttrString(pymod, "ion");
s_python_function_ginput = PyObject_GetAttrString(pymod, "ginput");
s_python_function_save = PyObject_GetAttrString(pylabmod, "savefig");
s_python_function_annotate = PyObject_GetAttrString(pymod, "annotate");
s_python_function_clf = PyObject_GetAttrString(pymod, "clf");
s_python_function_errorbar = PyObject_GetAttrString(pymod, "errorbar");
s_python_function_tight_layout =
PyObject_GetAttrString(pymod, "tight_layout");
s_python_function_stem = PyObject_GetAttrString(pymod, "stem");
s_python_function_xkcd = PyObject_GetAttrString(pymod, "xkcd");
s_python_function_text = PyObject_GetAttrString(pymod, "text");
s_python_function_suptitle = PyObject_GetAttrString(pymod, "suptitle");
s_python_function_bar = PyObject_GetAttrString(pymod, "bar");
s_python_function_subplots_adjust =
PyObject_GetAttrString(pymod, "subplots_adjust");
s_python_function_imshow = PyObject_GetAttrString(pymod, "imshow");
s_python_function_colorbar = PyObject_GetAttrString(pymod, "colorbar");
if (!s_python_function_show || !s_python_function_close ||
!s_python_function_draw || !s_python_function_pause ||
!s_python_function_figure || !s_python_function_fignum_exists ||
!s_python_function_plot || !s_python_function_quiver ||
!s_python_function_contour || !s_python_function_colorbar ||
!s_python_function_semilogx || !s_python_function_semilogy ||
!s_python_function_loglog || !s_python_function_fill ||
!s_python_function_fill_between || !s_python_function_subplot ||
!s_python_function_legend || !s_python_function_ylim ||
!s_python_function_title || !s_python_function_axis ||
!s_python_function_xlabel || !s_python_function_ylabel ||
!s_python_function_xticks || !s_python_function_yticks ||
!s_python_function_xscale || !s_python_function_yscale ||
!s_python_function_grid || !s_python_function_xlim ||
!s_python_function_ion || !s_python_function_ginput ||
!s_python_function_save || !s_python_function_clf ||
!s_python_function_annotate || !s_python_function_errorbar ||
!s_python_function_errorbar || !s_python_function_tight_layout ||
!s_python_function_stem || !s_python_function_xkcd ||
!s_python_function_text || !s_python_function_suptitle ||
!s_python_function_bar || !s_python_function_subplots_adjust ||
!s_python_function_spy || !s_python_function_imshow) {
throw std::runtime_error("Couldn't find required function!");
}
if (!PyFunction_Check(s_python_function_show) ||
!PyFunction_Check(s_python_function_close) ||
!PyFunction_Check(s_python_function_draw) ||
!PyFunction_Check(s_python_function_pause) ||
!PyFunction_Check(s_python_function_figure) ||
!PyFunction_Check(s_python_function_fignum_exists) ||
!PyFunction_Check(s_python_function_plot) ||
!PyFunction_Check(s_python_function_quiver) ||
!PyFunction_Check(s_python_function_contour) ||
!PyFunction_Check(s_python_function_semilogx) ||
!PyFunction_Check(s_python_function_semilogy) ||
!PyFunction_Check(s_python_function_loglog) ||
!PyFunction_Check(s_python_function_fill) ||
!PyFunction_Check(s_python_function_fill_between) ||
!PyFunction_Check(s_python_function_spy) ||
!PyFunction_Check(s_python_function_subplot) ||
!PyFunction_Check(s_python_function_legend) ||
!PyFunction_Check(s_python_function_annotate) ||
!PyFunction_Check(s_python_function_ylim) ||
!PyFunction_Check(s_python_function_title) ||
!PyFunction_Check(s_python_function_axis) ||
!PyFunction_Check(s_python_function_xlabel) ||
!PyFunction_Check(s_python_function_ylabel) ||
!PyFunction_Check(s_python_function_xticks) ||
!PyFunction_Check(s_python_function_yticks) ||
!PyFunction_Check(s_python_function_xscale) ||
!PyFunction_Check(s_python_function_yscale) ||
!PyFunction_Check(s_python_function_grid) ||
!PyFunction_Check(s_python_function_xlim) ||
!PyFunction_Check(s_python_function_ion) ||
!PyFunction_Check(s_python_function_ginput) ||
!PyFunction_Check(s_python_function_save) ||
!PyFunction_Check(s_python_function_clf) ||
!PyFunction_Check(s_python_function_tight_layout) ||
!PyFunction_Check(s_python_function_errorbar) ||
!PyFunction_Check(s_python_function_stem) ||
!PyFunction_Check(s_python_function_xkcd) ||
!PyFunction_Check(s_python_function_text) ||
!PyFunction_Check(s_python_function_suptitle) ||
!PyFunction_Check(s_python_function_bar) ||
!PyFunction_Check(s_python_function_subplots_adjust) ||
!PyFunction_Check(s_python_function_imshow) ||
!PyFunction_Check(s_python_function_colorbar)
) {
throw std::runtime_error(
"Python object is unexpectedly not a PyFunction.");
}
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) {
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;
}
#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 Vector> PyObject *get_array(const Vector &v) {
detail::_interpreter::get(); // interpreter needs to be initialized for the
// numpy commands to work
// both Eigen::Matrix<..> and std::vector<..> have the member value_type
NPY_TYPES type = select_npy_type<typename Vector::value_type>::type;
if (type == NPY_NOTYPE) {
std::vector<double> vd(v.size());
npy_intp vsize = v.size();
// Eigen Vectors do not support begin/end() in the currently stable version
// this can be changed once Eigen 3.4. is released
// data() returns a pointer to the storage of the first element. If the
// vector is modified afterwards, it may be rendedered invalid.
// Note, that this is not an issue since get_array() is called by a
// plot command using the instantaneous state of the vector.
// The pointer is not reused. If the vector is plotted anew, data() is
// called again and again get's the current, valid storage location.
std::copy(v.data(), v.data() + v.size(), 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;
}
// specialized get_2darray function for nested std::vectors
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_2darray 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("mismatched array size");
std::copy(v_row.begin(), v_row.end(), vd_begin);
vd_begin += vsize[1];
}
return reinterpret_cast<PyObject *>(varray);
}
// suitable for more general matrices (especially Eigen matrices)
template <typename Matrix> PyObject *get_2darray(const Matrix &A) {
detail::_interpreter::get(); // interpreter needs to be initialized for the
// numpy commands to work
if (A.size() < 1)
throw std::runtime_error("get_2darray A too small");
npy_intp vsize[2] = {static_cast<npy_intp>(A.rows()),
static_cast<npy_intp>(A.cols())};
PyArrayObject *varray =
(PyArrayObject *)PyArray_SimpleNew(2, vsize, NPY_DOUBLE);
double *vd_begin = static_cast<double *>(PyArray_DATA(varray));
for (std::size_t i = 0; i < A.rows(); ++i) {
for (std::size_t j = 0; j < A.cols(); ++j) {
*(vd_begin + i * A.cols() + j) = A(i, j);
}
}
return reinterpret_cast<PyObject *>(varray);
}
#else // fallback if we don't have numpy: copy every element of the given vector
template <typename Vector> PyObject *get_array(const Vector &v) {
detail::_interpreter::get();
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
namespace detail {
// @brief Since most of the plot commands require the exact same usage apart
// from the call to the correct Python function, we encapsulate this
// @param pyfunc The matplotlib function to be called with the given arguments
// @param x The x vector
// @param y The y vector
// @param s The formatting string for colour, marker and linestyle
// @param keywords Additional keywords, such as label
// @return true if plot was successful, false otherwise
template <typename VectorX, typename VectorY>
bool plot_base(PyObject *const pyfunc, const VectorX &x, const VectorY &y,
const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
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 *kwargs = PyDict_New();
for (auto const &item : keywords) {
PyDict_SetItemString(kwargs, item.first.c_str(),
PyString_FromString(item.second.c_str()));
}
PyObject *res = PyObject_Call(pyfunc, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if (res)
Py_DECREF(res);
return res;
}
} // namespace detail
// @brief standard plot function supporting the args (x, y, s, keywords)
// @param x The x vector
// @param y The y vector
// @param s The formatting string
// @param keywords Additional keywords
// @return true, if successful, false otherwise
template <typename VectorX, typename VectorY>
bool plot(const VectorX &x, const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
return detail::plot_base(detail::_interpreter::get().s_python_function_plot,
x, y, s, keywords);
}
// @brief standard plot function without formatting string, needed if
// keywords are given but formatting string is not
template <typename VectorX, typename VectorY>
bool plot(const VectorX &x, const VectorY &y,
const std::map<std::string, std::string> &keywords) {
return plot(x, y, "", keywords);
}
// @brief standard plot function if x data is not specified
template <typename VectorY = std::vector<double>>
bool plot(const VectorY &y, const std::string &format = "",
const std::map<std::string, std::string> &keywords = {}) {
// Note: cannot be an unsigned type for some reason, yields an overflow
// problem..
std::vector<int> x(y.size());
for (int i = 0; i < x.size(); ++i)
x.at(i) = i;
return plot(x, y, format);
}
// @brief standard plot function if x data is not specified and the formatting
// string is missing
template <typename VectorY = std::vector<double>>
bool plot(const VectorY &y,
const std::map<std::string, std::string> &keywords) {
std::vector<int> x(y.size());
for (int i = 0; i < x.size(); ++i)
x.at(i) = i;
return plot(x, y, "", keywords);
}
// @brief loglog plot function, see `plot` for more detail
template <typename VectorX, typename VectorY>
bool loglog(const VectorX &x, const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
return detail::plot_base(detail::_interpreter::get().s_python_function_loglog,
x, y, s, keywords);
}
template <typename VectorX, typename VectorY>
bool loglog(const VectorX &x, const VectorY &y,
const std::map<std::string, std::string> &keywords) {
return loglog(x, y, "", keywords);
}
template <typename VectorY = std::vector<double>>
bool loglog(const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
std::vector<std::size_t> x(y.size());
for (std::size_t i = 0; i < x.size(); ++i)
x.at(i) = i;
return loglog(x, y, s, keywords);
}
template <typename VectorY = std::vector<double>>
bool loglog(const VectorY &y,
const std::map<std::string, std::string> &keywords) {
std::vector<std::size_t> x(y.size());
for (std::size_t i = 0; i < x.size(); ++i)
x.at(i) = i;
return loglog(x, y, "", keywords);
}
// @brief semilogx plot function, see `plot` for more detail
template <typename VectorX, typename VectorY>
bool semilogx(const VectorX &x, const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
return detail::plot_base(
detail::_interpreter::get().s_python_function_semilogx, x, y, s,
keywords);
}
template <typename VectorX, typename VectorY>
bool semilogx(const VectorX &x, const VectorY &y,
const std::map<std::string, std::string> &keywords) {
return semilogx(x, y, "", keywords);
}
template <typename VectorY = std::vector<double>>
bool semilogx(const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
std::vector<std::size_t> x(y.size());
for (std::size_t i = 0; i < x.size(); ++i)
x.at(i) = i;
return semilogx(x, y, s, keywords);
}
template <typename VectorY = std::vector<double>>
bool semilogx(const VectorY &y,
const std::map<std::string, std::string> &keywords) {
std::vector<std::size_t> x(y.size());
for (std::size_t i = 0; i < x.size(); ++i)
x.at(i) = i;
return semilogx(x, y, "", keywords);
}
// @brief semilogy plot function, see `plot` for more detail
template <typename VectorX, typename VectorY>
bool semilogy(const VectorX &x, const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
return detail::plot_base(
detail::_interpreter::get().s_python_function_semilogy, x, y, s,
keywords);
}
template <typename VectorX, typename VectorY>
bool semilogy(const VectorX &x, const VectorY &y,
const std::map<std::string, std::string> &keywords) {
return semilogy(x, y, "", keywords);
}
template <typename VectorY = std::vector<double>>
bool semilogy(const VectorY &y, const std::string &s = "",
const std::map<std::string, std::string> &keywords = {}) {
std::vector<std::size_t> x(y.size());
for (std::size_t i = 0; i < x.size(); ++i)
x.at(i) = i;
return semilogy(x, y, s, keywords);
}
template <typename VectorY = std::vector<double>>
bool semilogy(const VectorY &y,
const std::map<std::string, std::string> &keywords) {
std::vector<std::size_t> x(y.size());
for (std::size_t i = 0; i < x.size(); ++i)
x.at(i) = i;
return semilogy(x, y, "", keywords);
}
template <typename Matrix>
void imshow(const Matrix& X, const std::map<std::string, std::string> &keywords = {}) {
PyObject *Xarray = get_2darray(X);
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 *plot_args = PyTuple_New(1);
PyTuple_SetItem(plot_args, 0, Xarray);
PyObject *res = PyObject_Call(
detail::_interpreter::get().s_python_function_imshow, plot_args, kwargs);
Py_DECREF(plot_args);
Py_DECREF(kwargs);
if (res)
Py_DECREF(res);
}
// @brief Add the colorbar
void colorbar() {
PyObject *res =
PyObject_CallObject(detail::_interpreter::get().s_python_function_colorbar,
detail::_interpreter::get().s_python_empty_tuple);
if (!res)
throw std::runtime_error("Call to colorbar() failed.");
}
// @brief plot_surface for datapoints (x_ij, y_ij, z_ij) with i,j = 0..n
// @param x The x values of the datapoints in a matrix
// @param y The y values of the datapoints in a matrix
// @param z The function value of the datapoints in a matrix
// @param keywords Additional keywords
template <typename Matrix>
void plot_surface(const Matrix &x, const Matrix &y, const Matrix &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);
}
// @brief plot_surface for datapoints (x_ij, y_ij, z_ij) with i,j = 0..n
// @param x The x values of the datapoints in a matrix
// @param y The y values of the datapoints in a matrix
// @param z The function value of the datapoints in a matrix
// @param keywords Additional keywords
template <typename Matrix>
void contour(const Matrix &x, const Matrix &y, const Matrix &z,
const std::map<std::string, std::string> &keywords = {}) {
detail::_interpreter::get();
// 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();
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 surface");
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 VectorY>
bool hist(const VectorY &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;
}
// @brief Scatter plot
// @param x x-coordinates of the 2d points
// @param y y-coordinates of the 2d points
// @param s the marker size in points**2
// @param keywords Additional keywords
template <typename VectorX, typename VectorY>
bool scatter(const VectorX &x, const VectorY &y, const double s = 1.0,
const std::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", PyFloat_FromDouble(s));
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()));
}