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//
// Created by Alan Freitas on 2020-07-03.
//
#ifndef MATPLOTPLUSPLUS_COMMON_H
#define MATPLOTPLUSPLUS_COMMON_H
#include <vector>
#include <string>
#include <sstream>
#include <complex>
#include <map>
#include <functional>
#include <algorithm>
#include <matplot/util/concepts.h>
namespace matplot {
bool iequals(const std::string& str1, const std::string& str2);
bool is_true(const std::string& str);
bool is_false(const std::string& str);
std::string run_and_get_output(const std::string& command);
std::string escape(const std::string& label);
inline void ltrim(std::string &s) {
s.erase(s.begin(), std::find_if(s.begin(), s.end(), [](int ch) {
return !std::isspace(ch);
}));
}
inline void rtrim(std::string &s) {
s.erase(std::find_if(s.rbegin(), s.rend(), [](int ch) {
return !std::isspace(ch);
}).base(), s.end());
}
inline void rtrim(std::string &s, char d) {
s.erase(std::find_if(s.rbegin(), s.rend(), [d](int ch) {
return ch != d;
}).base(), s.end());
}
template <class T>
std::string num2str(Arithmetic<T> num) {
std::ostringstream ss;
ss << num;
return ss.str();
}
template <class T>
std::string num2str(Arithmetic<T> num, const std::string& format) {
constexpr size_t max_buffer_size = 100;
char buffer[max_buffer_size];
int cx = snprintf(buffer, max_buffer_size, format.c_str(), num);
if (cx >= 0 && cx < max_buffer_size) {
return std::string(buffer);
} else {
return num2str(num);
}
}
template <class T = double>
T str2num(const std::string &Text) {
std::istringstream ss(Text);
T result;
return ss >> result ? result : 0;
}
using vector_1d = std::vector<double>;
using vector_2d = std::vector<vector_1d>;
std::vector<double> linspace(double lower_bound, double upper_bound);
std::vector<double> linspace(double lower_bound, double upper_bound, size_t n);
std::vector<double> logspace(double lower_bound, double upper_bound);
std::vector<double> logspace(double lower_bound, double upper_bound, size_t n);
std::vector<double> iota(double lower_bound, double upper_bound);
std::vector<double> iota(double lower_bound, double step, double upper_bound);
vector_1d transform(const vector_1d& x, std::function<double(double)> fn);
vector_1d transform(const vector_1d& x, const vector_1d& y, std::function<double(double,double)> fn);
vector_2d transform(const vector_2d& x, std::function<double(double)> fn);
vector_2d transform(const vector_2d& x, const vector_2d& y, std::function<double(double,double)> fn);
vector_1d flatten(const vector_2d& x);
std::vector<double> unique(const std::vector<double>& x);
double min(const std::vector<double>& x);
double min(const std::vector<std::vector<double>>& x);
double max(const std::vector<double>& x);
double max(const std::vector<std::vector<double>>& x);
std::pair<double,double> minmax(const std::vector<double>& x);
template<typename T>
T min(T val1, T val2)
{
return val1 < val2 ? val1 : val2;
}
template<typename T, typename... Ts>
T min(T val1, T val2, Ts&&... vs)
{
return val1 < val2 ?
min(val1, std::forward<Ts>(vs)...) :
min(val2, std::forward<Ts>(vs)...);
}
template<typename T>
T max(T val1, T val2)
{
return val1 > val2 ? val1 : val2;
}
template<typename T, typename... Ts>
T max(T val1, T val2, Ts&&... vs)
{
return val1 > val2 ?
max(val1, std::forward<Ts>(vs)...) :
max(val2, std::forward<Ts>(vs)...);
}
double mean(const std::vector<double>& x);
double stddev(const std::vector<double>& x);
void wait();
constexpr double pi = 3.141592653589793238462643383279502884197169399375105820974944592307816406286;
constexpr double NaN = std::numeric_limits<double>::quiet_NaN();
template <class T>
std::vector<T> vectorize(const std::vector<T>& result) {
return result;
}
template <class T>
std::vector<T> vectorize(const T& result) {
return std::vector<T>({result});
}
template <size_t N, class T>
inline std::array<T,N> to_array(std::initializer_list<T> il) {
std::array<T,N> r;
auto r_it = r.begin();
auto il_it = il.begin();
while (r_it != r.end() && il_it != il.end()) {
*r_it = *il_it;
++r_it;
++il_it;
}
return r;
}
template <size_t N, class T>
inline std::array<T,N> to_array(const std::vector<T>& v) {
std::array<T,N> r;
auto r_it = r.begin();
auto v_it = v.begin();
while (r_it != r.end() && v_it != v.end()) {
*r_it = *v_it;
++r_it;
++v_it;
}
return r;
}
template <class T>
std::vector<vector_2d> to_vector_3d(const T& v) {
std::vector<vector_2d> r(v.size());
size_t matrix_index = 0;
for (auto matrix_it = v.begin(); matrix_it != v.end(); ++matrix_it, ++matrix_index) {
r[matrix_index] = vector_2d(matrix_it->size());
size_t i = 0;
for (auto v_it = matrix_it->begin(); v_it != matrix_it->end(); ++v_it, ++i) {
r[matrix_index][i] = vector_1d(v_it->size());
size_t j = 0;
for (auto vj_it = v_it->begin(); vj_it != v_it->end(); ++vj_it, ++j) {
r[matrix_index][i][j] = static_cast<double>(*vj_it);
}
}
}
return r;
}
template <class T, class DESTINATION_VALUE_TYPE = double>
vector_2d to_vector_2d(const T& v) {
std::vector<std::vector<DESTINATION_VALUE_TYPE>> r(v.size());
size_t i = 0;
for (auto v_it = v.begin(); v_it != v.end(); ++v_it, ++i) {
r[i] = std::vector<DESTINATION_VALUE_TYPE>(v_it->size());
size_t j = 0;
for (auto vj_it = v_it->begin(); vj_it != v_it->end(); ++vj_it, ++j) {
r[i][j] = static_cast<DESTINATION_VALUE_TYPE>(*vj_it);
}
}
return r;
}
template <class T, class DESTINATION_VALUE_TYPE = double>
vector_1d to_vector_1d(const T& v) {
std::vector<DESTINATION_VALUE_TYPE> r(v.size());
size_t i = 0;
for (auto v_it = v.begin(); v_it != v.end(); ++v_it, ++i) {
r[i] = static_cast<DESTINATION_VALUE_TYPE>(*v_it);
}
return r;
}
template <class T>
inline T norm(const std::vector<T>& v) {
T sum = 0.;
for (const auto &vk : v) {
sum += pow(vk,2.);
}
return sqrt(sum);
}
double randn(double mean, double stddev);
std::vector<double> randn(size_t n, double mean, double stddev);
/// Exponential distribution
double rande(double lambda, double multiplier = 1.0);
std::vector<double> rande(size_t n, double lambda, double multiplier = 1.0);
/// Pareto distribution
double randp(double scale, double shape = 1.0);
std::vector<double> randp(size_t n, double scale, double shape = 1.0);
int randi(int imin, int imax);
std::vector<int> randi(size_t n, int imin, int imax);
double rand(double lower_bound, double upper_bound);
vector_1d rand(size_t n, double lower_bound, double upper_bound);
vector_2d rand(size_t rows, size_t cols, double lower_bound, double upper_bound);
std::vector<double> reshape(const std::vector<std::vector<double>>& X);
std::vector<double> concat(const std::vector<double>& a, const std::vector<double>& b);
template <class ...Args>
std::vector<double> concat(const std::vector<double>& a, const std::vector<double>& b, Args... args) {
std::vector<double> r = concat(a,b);
return concat(r, args...);
}
double truncate(double x, double lower_bound, double upper_bound);
template <class Arg1, class TUPLE>
void reorder_parameter_pack_in_tuple(TUPLE& t, Arg1 x) {
std::get<Arg1>(t) = x;
}
template <class Arg1, class ...Args, class TUPLE>
void reorder_parameter_pack_in_tuple(TUPLE& t, Arg1 x, Args... args) {
std::get<Arg1>(t) = x;
reorder_parameter_pack_in_tuple(t, args...);
}
std::string fileread(const std::string& filename);
template <class T, class T2 = T, class FN = std::less<T>>
void rank_elements(T first, T last, T2 rank_input, FN comp = std::less<T>()) {
using value_and_rank = std::pair<std::remove_reference_t<decltype(*first)> const *, size_t>;
std::vector<value_and_rank> v;
size_t r = 0;
while (first != last) {
v.emplace_back(&(*first), r);
++first;
++r;
}
std::sort(v.begin(), v.end(), [comp](const auto& a, const auto& b) {
return comp(*a.first,*b.first);
});
for (const auto &[ptr, ranking] : v) {
*rank_input = ranking;
++rank_input;
}
}
/// Cosine of argument in degreescollapse
double cosd(double degrees);
/// Sine of argument in degreescollapse
double sind(double degrees);
/// Sine of argument in degreescollapse
std::vector<double> deg2rad(const std::vector<double>& degrees);
double deg2rad(double rho);
/// Round up the maximum polar value
double round_polar_max(double polar_max);
double to_positive_radian(double radian);
/// Calculate the radians rho of a vector (u,v)
double vector_radians(double u, double v);
/// Calculate the magnitude theta of a vector (u,v)
double vector_magnitude(double u, double v);
/// Calculate the radians rho of a complex number u + iv
double vector_radians(std::complex<double> v);
/// Calculate the magnitude theta of a complex number u + iv
double vector_magnitude(std::complex<double> v);
/// Calculate cartesian coordinates of vector in polar coordinates
std::pair<double,double> pol2cart(double theta, double rho);
std::pair<vector_1d,vector_1d> pol2cart(vector_1d theta, vector_1d rho);
std::pair<vector_1d,vector_1d> pol2cart(vector_1d theta, double rho);
std::pair<double,double> elliptic2cart(double theta, double rho_w, double rho_h);
std::pair<vector_1d,vector_1d> elliptic2cart(vector_1d theta, double rho_w, double rho_h);
std::pair<vector_1d,vector_1d> elliptic2cart(vector_1d theta, vector_1d rho_w, vector_1d rho_h);
std::pair<vector_2d,vector_2d> meshgrid(const vector_1d& x, const vector_1d& y);
std::pair<vector_2d,vector_2d> meshgrid(const vector_1d& x_and_y);
vector_1d gradient(const vector_1d& z, double spacing = 1.0);
std::pair<vector_2d,vector_2d> gradient(const vector_2d& z, double spacing = 1.0);
std::pair<vector_2d,vector_2d> gradient(const vector_2d& z, double spacing_x, double spacing_y);
double peaks(double x, double y);
vector_2d peaks(const vector_2d& X, const vector_2d& Y);
std::tuple<vector_2d,vector_2d,vector_2d> peaks(size_t N = 49);
template <class T1, class T2>
struct pair_hash {
std::size_t operator()(const std::pair<int,int>& p) const
{
std::size_t h1 = std::hash<T1>()(p.first);
std::size_t h2 = std::hash<T2>()(p.second);
return h1 ^ h2;
}
};
template <class T>
std::pair<size_t, size_t> size(const std::vector<T>& v) {
if (v.empty()) {
return std::make_pair(0, 0);
} else {
return std::make_pair(v.size(), v[0].size());
}
}
vector_2d zeros(size_t rows, size_t cols);
vector_2d ones(size_t rows, size_t cols);
using image_row_t = std::vector<unsigned char>;
using image_channel_t = std::vector<image_row_t>;
// The image might have 1 channel (B&W), 3 channels (RGB), or 4 channels (RGBA)
using image_channels_t = std::vector<image_channel_t>;
/// Core imread function
/// Return grayscale image (vector::size() == 1),
/// rgb image (vector::size() == 3),
/// rgba image (vector::size() == 4),
/// empty image (vector::size() == 0)
image_channels_t imread(const std::string& filename);
enum class image_interpolation {
raw,
additional_space,
nearest,
moving_average,
bilinear,
grid,
bicubic,
lanczos
};
image_channel_t rgb2gray(const image_channels_t& A);
image_channels_t gray2rgb(const image_channel_t& A, const std::vector<std::vector<double>>& colormap);
image_channels_t gray2rgb(const image_channel_t& A);
image_channels_t gray2rgb(const image_channels_t& A, const std::vector<std::vector<double>>& colormap);
image_channels_t gray2rgb(const image_channels_t& A);
image_channels_t imresize(const image_channels_t& A, double scale, image_interpolation m = image_interpolation::bicubic);
image_channels_t imresize(const image_channels_t& A, size_t height, size_t width, image_interpolation m = image_interpolation::bicubic);
void imwrite(const image_channels_t& A, const std::string& filename);
void imwrite(const image_channel_t& A, const std::vector<std::vector<double>>& colormap, const std::string& filename);
void imwrite(const image_channels_t& A, const std::string& filename);
image_channels_t imvignette(const image_channels_t& A, double min_radius = 1., double exponent = 0.5);
template <class T = double>
std::vector<std::vector<T>> eye(size_t n) {
std::vector<std::vector<T>> r(n, std::vector<T>(n, static_cast<T>(0)));
for (size_t i = 0; i < n; ++i) {
r[i][i] = 1.;
}
return r;
}
vector_2d transpose(const vector_2d& z);
std::vector<std::string> tokenize(const std::string &text, std::string delimiters = " ',\n\r\t\".!?:");
std::pair<std::vector<std::string>,std::vector<size_t>> wordcount(const std::vector<std::string> &tokens, const std::vector<std::string> &black_list, const std::string &delimiters = " ',\n\r\t\".!?:;", size_t max_cloud_size = 100);
std::pair<std::vector<std::string>,std::vector<size_t>> wordcount(const std::string &text, const std::vector<std::string> &black_list, const std::string &delimiters = " ',\n\r\t\".!?:;", size_t max_cloud_size = 100);
// Distance from x to the next larger floating point number
template <class FLOAT>
std::enable_if_t<std::is_same_v<FLOAT, float> || std::is_same_v<FLOAT, double> || std::is_same_v<FLOAT, long double>, FLOAT>
eps(FLOAT x = 1.) {
constexpr long double max_long_double = std::numeric_limits<long double>::max();
// std::nexttoward is more precise than std::nextafter
if constexpr (std::is_same_v<FLOAT, double>) {
return std::nexttoward(x, max_long_double) - x;
} else if constexpr (std::is_same_v<FLOAT, float>) {
return std::nexttowardf(x, max_long_double) - x;
} else if constexpr (std::is_same_v<FLOAT, long double>) {
return std::nexttowardl(x, max_long_double) - x;
} else {
throw std::logic_error("eps: FLOAT type needs to be float, double or long double");
}
}
template <class T>
std::vector<T> repmat(const std::vector<T>& a, size_t n) {
std::vector<T> b(a.size() * n);
for (size_t i = 0; i < n; ++i) {
for (size_t j = 0; j < a.size(); ++j) {
b[i * a.size() + j] = a[j];
}
}
return b;
}
struct ticks_results {
std::vector<double> ticks;
std::vector<std::string> tickLabels;
std::string scaleStr;
std::vector<double> minorTicks;
std::vector<double> overhang;
};
/// \brief Find ticks at "nice" intervals for an axis
/// For now, we only use our own ticks when we need to take control
/// over the gnuplot ticks. Sometimes the gnuplot ticks does not
/// give us the behaviour we expect. For instance, this is the case
/// when plotting parallel coordinates.
/// We could easily adapt class axis to always use this function
/// instead of the automatic gnuplot ticks but there's no need
/// for that at the moment.
/// The algorithm in this function is inspired by this matplot script:
/// https://www.mathworks.com/matlabcentral/fileexchange/30671-calcticks
/// We don't implement the version for log scale because, by coincidence,
/// the library does not need it at this point.
/// \param limits_min Minimum value
/// \param limits_max Maximum value
/// \param horizontal True if axis is horizontal (this changes the room for labels)
/// \param text_size Size in height or width of a char
/// \param log True if scale is logarithmic (this will throw an error for now)
/// \return Nice ticks and their labels in a ticks_results struct
/// \see https://www.mathworks.com/matlabcentral/fileexchange/30671-calcticks
ticks_results calcticks(double limits_min = -5, double limits_max = +5, bool horizontal = false, double text_size = 1.25, bool separateExp = true, bool log = false);
double distance(double x1, double y1, double x2, double y2);
}
#endif //MATPLOTPLUSPLUS_COMMON_H