C++ polygon drawing on console Linux [closed] - c++

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I am using the boost geometry library to store polygons and I want to print different polygons on the console to debug my geometries like rectangle, n point polygon. Is there any library to do so in Linux? Thanks!

For sheer fun, I adapted that Canvas example from yesterday (Draw Line using c++ without graphics) with some Boost Geometry support.
You can use it like:
int main() {
using manip::as_geo;
Polygon poly;
bg::read_wkt("POLYGON((0 0,0 7,4 2,2 0,0 0))", poly);
std::cout << as_geo(poly);
// a polygon with a hole
std::cout << as_geo<Polygon>("POLYGON((0 0,0 7,4 2,2 0,0 0) (1.5 2.5, 1.5 3.0, 2.5 3.0, 2.5 2.5, 1.5 2.5))");
// custom canvas size and glyphs
std::cout << as_geo<60, 30>(poly, '#', '%');
}
Which renders the first polygon as
The second polygon has a rectangular inner ring and shows as
The third option uses a custom canvas size and drawing glyphs:
Implementation
Utility Vec2
There's a generic x/y pair class with many conversions and basic arithmetic operations (for scaling, offsetting, logical-physical conversions):
namespace Utility {
template <typename T> struct Vec2 {
T x, y;
Vec2(T x = {}, T y = {}) : x(x), y(y) {}
template <typename U, typename V> Vec2(U const& x, V const& y) : x(x), y(y) {}
template <typename U> Vec2(Vec2<U> const& rhs) : Vec2(rhs.x, rhs.y) {}
template <typename U> Vec2& operator=(Vec2<U> const& rhs) {
return *this = {rhs.x, rhs.y};
}
#define VEC_OPS VEC_DECLARE_OP(*) VEC_DECLARE_OP(/) VEC_DECLARE_OP(+) VEC_DECLARE_OP(-)
#define VEC_DECLARE_OP(op) template <typename U, typename R = typename std::common_type<T, U>::type> \
Vec2<R> operator op(Vec2<U> const& rhs) const { return {x op rhs.x, y op rhs.y}; }
VEC_OPS
#undef VEC_DECLARE_OP
#define VEC_DECLARE_OP(op) template <typename U, typename R = typename std::common_type<T, U>::type> \
Vec2<R> operator op(U const& rhs) const { return {x op rhs, y op rhs}; }
VEC_OPS
#undef VEC_DECLARE_OP
#define VEC_DECLARE_OP(op) template <typename U, typename R = typename std::common_type<T, U>::type> \
Vec2& operator op##=(U const& rhs) { return operator=((*this) op rhs); }
VEC_OPS
#undef VEC_DECLARE_OP
private:
friend std::ostream& operator<<(std::ostream& os, Vec2 const& xy) {
return os << "{" << xy.x << "," << xy.y << "}";
}
};
}
Canvas Type
Let's start with defining some useful building blocks:
using Physical = Utility::Vec2<int>;
using Logical = Utility::Vec2<double>;
using Scale = Utility::Vec2<double>;
struct Extents {
Logical TopLeft, BottomRight;
void normalize() {
if (TopLeft.y < BottomRight.y) std::swap(TopLeft.y, BottomRight.y);
if (TopLeft.x > BottomRight.x) std::swap(TopLeft.x, BottomRight.x);
}
auto height() const { return std::abs(TopLeft.y - BottomRight.y); }
auto width() const { return std::abs(BottomRight.x - TopLeft.x); }
friend std::ostream& operator<<(std::ostream& os, Extents const& e) {
return os << "{" << e.TopLeft << " - " << e.BottomRight << "; " << e.width() << "×" << e.height() << "}";
}
};
Now we can go ahead with the canvas, largely the same as in the previous answer:
template <int Columns = 100, int Rows = 50>
struct BasicCanvas {
using Line = std::array<char, Columns>;
using Screen = std::array<Line, Rows>;
static constexpr size_t rows() { return Rows; }
static constexpr size_t columns() { return Columns; }
BasicCanvas(Logical origin = {Columns/2, Rows/2}, Scale scale = {1.0, 1.0}) : origin(origin), scale(scale) {
clear();
}
BasicCanvas(Extents extents) {
extents.normalize();
using Utility::Vec2;
scale = Vec2{extents.width(), extents.height()} / Vec2{Columns, Rows};
origin = { -extents.TopLeft.x, -extents.BottomRight.y };
clear();
}
Screen screen;
Logical origin;
Scale scale; // physical * scale = logical
Logical to_logical(Physical const& phys) const { return (phys * scale) - origin; }
Physical to_physical(Logical const& log) const { return (log + origin) / scale; }
Extents extents() const { return { to_logical({ 0, Rows }), to_logical({ Columns, 0}) }; }
friend std::ostream& operator<<(std::ostream& os, BasicCanvas const& c) {
for (auto& line : c.screen) {
os.write(line.data(), line.size()) << "\n";
}
return os;
}
Line& operator[](size_t y) { return screen.at(screen.size()-(y+1)); }
Line const& operator[](size_t y) const { return screen.at(screen.size()-(y+1)); }
char& operator[](Physical coord) { return operator[](coord.y).at(coord.x); }
char const& operator[](Physical coord) const { return operator[](coord.y).at(coord.x); }
void clear(char filler = '.') {
Line empty;
std::fill(empty.begin(), empty.end(), filler);
std::fill(screen.begin(), screen.end(), empty);
}
void axes() {
Physical phys_org = to_physical({0,0});
auto const y_shown = (phys_org.x >= 0 && phys_org.x < Columns);
auto const x_shown = (phys_org.y >= 0 && phys_org.y < Rows);
if (y_shown)
for (auto& line : screen)
line.at(phys_org.x) = '|';
if (x_shown) {
auto& y_axis = operator[](phys_org.y);
for (auto& cell : y_axis)
cell = '-';
if (y_shown)
y_axis.at(phys_org.x) = '+';
}
}
template <typename F>
void plot(F f) {
for (size_t x_tick = 0; x_tick < Columns; ++x_tick) {
auto x = to_logical({ x_tick, 0 }).x;
auto y = f(x);
auto y_ = derivative(f, x, scale.x/2);
size_t y_tick = to_physical({x, y}).y;
if (y_tick < Rows)
operator[]({x_tick, y_tick}) = line_glyph(y_);
}
}
private:
template <typename F>
auto derivative(F const& f, double x, double dx = 0.01) {
return (f(x+dx)-f(x-dx))/(2*dx);
}
char line_glyph(double tangent) {
auto angle = atan(tangent);
while (angle < 0)
angle += 2*M_PI;
int angle_index = 2.0 * angle / atan(1);
return R"(--/||\--)"[angle_index % 8];
}
};
Note This now contains some operations (axes() and plot() that aren't strictly required for the purpose of this answer.
Supporting Boost Geometry
In the interest of de-coupling, let's define the drawing operations out-of-class.
For the purpose of this demonstration I have only implemented an operation fill(geo, filler_char), which implies we can handle planar surfaces for now. Line-segments and linestrings could be added similarly to the plot operation above, but I suggest to look at the Bresenham Algorithm to avoid sub-optimal results.
Let's introduce Boost Geometry:
#include <boost/geometry.hpp>
#include <boost/geometry/geometries/point_xy.hpp>
#include <boost/geometry/geometries/polygon.hpp>
#include <boost/geometry/geometries/box.hpp>
#include <boost/geometry/io/io.hpp>
namespace bg = boost::geometry;
using Point = bg::model::d2::point_xy<double, bg::cs::cartesian>;
using Polygon = bg::model::polygon<Point>;
using Box = bg::model::box<Point>;
We are going to use Box to detect a bounding rectangle for the geometry we're about to draw. This way we don't have to worry about scaling the geometry to fit the canvas.
Assuming we have the canvas set-up, we can implement fill quite simply as:
template <typename Canvas, typename G>
void fill(Canvas& canvas, G const& geo, char filler = '*') {
for (size_t x_tick = 0; x_tick < canvas.columns(); ++x_tick) {
for (size_t y_tick = 0; y_tick < canvas.rows(); ++y_tick) {
Physical phys { x_tick, y_tick };
Logical log = canvas.to_logical(phys);
if (bg::within(Point(log.x, log.y), geo))
canvas[{x_tick, y_tick}] = filler;
}
}
}
Note: no performance considerations have been taken into account for now
A Stream IO Manipulator
To glue it all together like in the sample we started with, we create an IO manipulator that takes care of
calculating the bounding box
instantiating a canvas with sufficient extent to fit the bounding box
draw the background
fill the geometry
optionally parses the geometry right from WKT, in which case the caller must specify the type to deserialize
template <typename Geo, int Columns = 100, int Rows = 50>
struct geo_manip {
Geo _geo_or_ref;
char _filler, _bg;
friend std::ostream& operator<<(std::ostream& os, geo_manip const& gm) {
Box bounding;
bg::envelope(gm._geo_or_ref, bounding);
BasicCanvas<Columns, Rows> canvas(Extents {
{bounding.max_corner().x(), bounding.max_corner().y()},
{bounding.min_corner().x(), bounding.min_corner().y()}});
canvas.clear(gm._bg);
fill(canvas, gm._geo_or_ref, gm._filler);
os << "Canvas extents: " << canvas.extents() << "\n";
os << "Canvas origin:" << canvas.origin << " scale:" << canvas.scale << "\n";
return os << canvas;
}
};
The convenience function as_geo makes it easy to create the manipulator, either for existing Geometries (by reference) or parsing a WKT fragment:
template <int Columns = 100, int Rows = 50, typename Geo>
geo_manip<Geo const&, Columns, Rows> as_geo(Geo const& geo, char filler = '*', char background = ' ') {
return {geo, filler, background};
}
template <typename Geo = Polygon, int Columns = 100, int Rows = 50>
geo_manip<Geo, Columns, Rows> as_geo(std::string const& wkt, char filler = '*', char background = ' ') {
Geo geo;
bg::read_wkt(wkt, geo);
return {geo, filler, background};
}
Full Live Demo
Live On Coliru
#include <iostream>
#include <array>
#include <limits>
#include <cmath>
namespace Utility {
template <typename T> struct Vec2 {
T x, y;
Vec2(T x = {}, T y = {}) : x(x), y(y) {}
template <typename U, typename V> Vec2(U const& x, V const& y) : x(x), y(y) {}
template <typename U> Vec2(Vec2<U> const& rhs) : Vec2(rhs.x, rhs.y) {}
template <typename U> Vec2& operator=(Vec2<U> const& rhs) {
return *this = {rhs.x, rhs.y};
}
#define VEC_OPS VEC_DECLARE_OP(*) VEC_DECLARE_OP(/) VEC_DECLARE_OP(+) VEC_DECLARE_OP(-)
#define VEC_DECLARE_OP(op) template <typename U, typename R = typename std::common_type<T, U>::type> \
Vec2<R> operator op(Vec2<U> const& rhs) const { return {x op rhs.x, y op rhs.y}; }
VEC_OPS
#undef VEC_DECLARE_OP
#define VEC_DECLARE_OP(op) template <typename U, typename R = typename std::common_type<T, U>::type> \
Vec2<R> operator op(U const& rhs) const { return {x op rhs, y op rhs}; }
VEC_OPS
#undef VEC_DECLARE_OP
#define VEC_DECLARE_OP(op) template <typename U, typename R = typename std::common_type<T, U>::type> \
Vec2& operator op##=(U const& rhs) { return operator=((*this) op rhs); }
VEC_OPS
#undef VEC_DECLARE_OP
private:
friend std::ostream& operator<<(std::ostream& os, Vec2 const& xy) {
return os << "{" << xy.x << "," << xy.y << "}";
}
};
}
using Physical = Utility::Vec2<int>;
using Logical = Utility::Vec2<double>;
using Scale = Utility::Vec2<double>;
struct Extents {
Logical TopLeft, BottomRight;
void normalize() {
if (TopLeft.y < BottomRight.y) std::swap(TopLeft.y, BottomRight.y);
if (TopLeft.x > BottomRight.x) std::swap(TopLeft.x, BottomRight.x);
}
auto height() const { return std::abs(TopLeft.y - BottomRight.y); }
auto width() const { return std::abs(BottomRight.x - TopLeft.x); }
friend std::ostream& operator<<(std::ostream& os, Extents const& e) {
return os << "{" << e.TopLeft << " - " << e.BottomRight << "; " << e.width() << "×" << e.height() << "}";
}
};
template <int Columns = 100, int Rows = 50>
struct BasicCanvas {
using Line = std::array<char, Columns>;
using Screen = std::array<Line, Rows>;
static constexpr size_t rows() { return Rows; }
static constexpr size_t columns() { return Columns; }
BasicCanvas(Logical origin = {Columns/2, Rows/2}, Scale scale = {1.0, 1.0}) : origin(origin), scale(scale) {
clear();
}
BasicCanvas(Extents extents) {
extents.normalize();
using Utility::Vec2;
scale = Vec2{extents.width(), extents.height()} / Vec2{Columns, Rows};
origin = { -extents.TopLeft.x, -extents.BottomRight.y };
clear();
}
Screen screen;
Logical origin;
Scale scale; // physical * scale = logical
Logical to_logical(Physical const& phys) const { return (phys * scale) - origin; }
Physical to_physical(Logical const& log) const { return (log + origin) / scale; }
Extents extents() const { return { to_logical({ 0, Rows }), to_logical({ Columns, 0}) }; }
friend std::ostream& operator<<(std::ostream& os, BasicCanvas const& c) {
for (auto& line : c.screen) {
os.write(line.data(), line.size()) << "\n";
}
return os;
}
Line& operator[](size_t y) { return screen.at(screen.size()-(y+1)); }
Line const& operator[](size_t y) const { return screen.at(screen.size()-(y+1)); }
char& operator[](Physical coord) { return operator[](coord.y).at(coord.x); }
char const& operator[](Physical coord) const { return operator[](coord.y).at(coord.x); }
void clear(char filler = '.') {
Line empty;
std::fill(empty.begin(), empty.end(), filler);
std::fill(screen.begin(), screen.end(), empty);
}
void axes() {
Physical phys_org = to_physical({0,0});
auto const y_shown = (phys_org.x >= 0 && phys_org.x < Columns);
auto const x_shown = (phys_org.y >= 0 && phys_org.y < Rows);
if (y_shown)
for (auto& line : screen)
line.at(phys_org.x) = '|';
if (x_shown) {
auto& y_axis = operator[](phys_org.y);
for (auto& cell : y_axis)
cell = '-';
if (y_shown)
y_axis.at(phys_org.x) = '+';
}
}
template <typename F>
void plot(F f) {
for (size_t x_tick = 0; x_tick < Columns; ++x_tick) {
auto x = to_logical({ x_tick, 0 }).x;
auto y = f(x);
auto y_ = derivative(f, x, scale.x/2);
size_t y_tick = to_physical({x, y}).y;
if (y_tick < Rows)
operator[]({x_tick, y_tick}) = line_glyph(y_);
}
}
private:
template <typename F>
auto derivative(F const& f, double x, double dx = 0.01) {
return (f(x+dx)-f(x-dx))/(2*dx);
}
char line_glyph(double tangent) {
auto angle = atan(tangent);
while (angle < 0)
angle += 2*M_PI;
int angle_index = 2.0 * angle / atan(1);
return R"(--/||\--)"[angle_index % 8];
}
};
#include <boost/geometry.hpp>
#include <boost/geometry/geometries/point_xy.hpp>
#include <boost/geometry/geometries/polygon.hpp>
#include <boost/geometry/geometries/box.hpp>
#include <boost/geometry/io/io.hpp>
namespace bg = boost::geometry;
using Point = bg::model::d2::point_xy<double, bg::cs::cartesian>;
using Polygon = bg::model::polygon<Point>;
using Box = bg::model::box<Point>;
template <typename Canvas, typename G>
void fill(Canvas& canvas, G const& geo, char filler = '*') {
for (size_t x_tick = 0; x_tick < canvas.columns(); ++x_tick) {
for (size_t y_tick = 0; y_tick < canvas.rows(); ++y_tick) {
Physical phys { x_tick, y_tick };
Logical log = canvas.to_logical(phys);
if (bg::within(Point(log.x, log.y), geo))
canvas[phys] = filler;
}
}
}
namespace manip {
template <typename Geo, int Columns = 100, int Rows = 50>
struct geo_manip {
Geo _geo_or_ref;
char _filler, _bg;
friend std::ostream& operator<<(std::ostream& os, geo_manip const& gm) {
Box bounding;
bg::envelope(gm._geo_or_ref, bounding);
BasicCanvas<Columns, Rows> canvas(Extents {
{bounding.max_corner().x(), bounding.max_corner().y()},
{bounding.min_corner().x(), bounding.min_corner().y()}});
canvas.clear(gm._bg);
fill(canvas, gm._geo_or_ref, gm._filler);
os << "Canvas extents: " << canvas.extents() << "\n";
os << "Canvas origin:" << canvas.origin << " scale:" << canvas.scale << "\n";
return os << canvas;
}
};
template <int Columns = 100, int Rows = 50, typename Geo>
geo_manip<Geo const&, Columns, Rows> as_geo(Geo const& geo, char filler = '*', char background = ' ') {
return {geo, filler, background};
}
template <typename Geo = Polygon, int Columns = 100, int Rows = 50>
geo_manip<Geo, Columns, Rows> as_geo(std::string const& wkt, char filler = '*', char background = ' ') {
Geo geo;
bg::read_wkt(wkt, geo);
return {geo, filler, background};
}
}
int main() {
using manip::as_geo;
Polygon poly;
bg::read_wkt("POLYGON((0 0,0 7,4 2,2 0,0 0))", poly);
std::cout << as_geo(poly);
// a polygon with a hole
std::cout << as_geo<Polygon>("POLYGON((0 0,0 7,4 2,2 0,0 0) (1.5 2.5, 1.5 3.0, 2.5 3.0, 2.5 2.5, 1.5 2.5))");
// custom canvas size and glyphs
std::cout << as_geo<60, 30>(poly, '#', '%');
}
The output is also live on coliru.

Related

C++ keep force driven entities in the window

I have a window application of 1024 width and 768 height and contains a bunch of meteorites, ships and boats. The meteorites freely roam across the window driven by forces.
The forces are: random position, towards/away from boat, towards/away from ship and cohesion, seperation, alignment to other meteorites
I feel like the forces are not fully working since they sometimes move off the screen and move with inverted velocity eg: they are roaming from top right straight to top left and when reached go straight to bottom left.
Are my calculations correct or did I mess up something at the forces?
Meteorite header:
#include <chrono>
#include <cmath>
#include <array>
#include <random>
#include <algorithm>
using scalar = float;
template <typename Scalar> class basic_vector2d {
public:
constexpr basic_vector2d() noexcept = default;
constexpr basic_vector2d(Scalar x, Scalar y) noexcept : x_{ x }, y_{ y } {}
constexpr Scalar x() const noexcept { return x_; }
constexpr void x(Scalar newX) noexcept { x_ = newX; }
constexpr Scalar y() const noexcept { return y_; }
constexpr void y(Scalar newY) noexcept { y_ = newY; }
constexpr bool operator==(basic_vector2d other) const noexcept {
return x_ == other.x_ && y_ == other.y_;
}
constexpr bool operator!=(basic_vector2d other) const noexcept {
return x_ != other.x_ || y_ != other.y_;
}
constexpr basic_vector2d& operator+=(basic_vector2d other) noexcept {
x_ += other.x_;
y_ += other.y_;
return *this;
}
constexpr basic_vector2d& operator-=(basic_vector2d other) noexcept {
x_ -= other.x_;
y_ -= other.y_;
return *this;
}
constexpr basic_vector2d& operator*=(Scalar s) noexcept {
x_ *= s;
y_ *= s;
return *this;
}
constexpr basic_vector2d& operator/=(Scalar s) noexcept {
x_ /= s;
y_ /= s;
return *this;
}
private:
Scalar x_{};
Scalar y_{};
};
template <typename Scalar>
constexpr basic_vector2d<Scalar> operator-(basic_vector2d<Scalar> a,
basic_vector2d<Scalar> b) {
return { a.x() - b.x(), a.y() - b.y() };
}
template <typename Scalar>
constexpr basic_vector2d<Scalar> operator+(basic_vector2d<Scalar> a,
basic_vector2d<Scalar> b) {
return { a.x() + b.x(), a.y() + b.y() };
}
template <typename Scalar>
constexpr basic_vector2d<Scalar> operator*(basic_vector2d<Scalar> v, scalar s) {
return v *= s;
}
template <typename Scalar>
constexpr basic_vector2d<Scalar> operator*(scalar s, basic_vector2d<Scalar> v) {
return operator*(v, s);
}
template <typename Scalar>
constexpr basic_vector2d<Scalar> operator/(basic_vector2d<Scalar> v, scalar s) {
return v /= s;
}
template <typename Scalar>
constexpr basic_vector2d<Scalar> operator/(scalar s, basic_vector2d<Scalar> v) {
return operator/(v, s);
}
template <typename Scalar>
constexpr scalar dot(basic_vector2d<Scalar> a, basic_vector2d<Scalar> b) {
return a.x() * b.x() + a.y() * b.y();
}
template <typename Scalar> constexpr auto norm(basic_vector2d<Scalar> p) {
return std::sqrt(dot(p, p));
}
template <typename Scalar>
constexpr basic_vector2d<Scalar> normalize(basic_vector2d<Scalar> p) {
auto ls = norm(p);
return { p.x() / ls, p.y() / ls };
}
using vector2d = basic_vector2d<scalar>;
template <typename T> class basic_size {
public:
constexpr basic_size() noexcept = default;
constexpr basic_size(T width, T height) noexcept
: width_{ width }, height_{ height } {}
constexpr T width() const noexcept { return width_; }
constexpr T height() const noexcept { return height_; }
constexpr void width(T new_width) noexcept { width_ = new_width; }
constexpr void height(T new_height) noexcept { height_ = new_height; }
constexpr basic_size& operator*=(T x) {
width(width() * x);
height(height() * x);
return *this;
}
private:
T width_{};
T height_{};
};
using size = basic_size<scalar>;
template <typename Scalar> class basic_rectangle {
public:
constexpr basic_rectangle(basic_vector2d<Scalar> top_left,
basic_size<Scalar> size)
: top_left_{ top_left }, size_{ size } {}
constexpr basic_vector2d<Scalar> const& top_left() const noexcept {
return top_left_;
}
constexpr basic_size<Scalar> const& size() const noexcept { return size_; }
private:
basic_vector2d<Scalar> top_left_;
basic_size<Scalar> size_;
};
using rectangle = basic_rectangle<scalar>;
inline float to_seconds(std::chrono::nanoseconds dt) {
return std::chrono::duration_cast<std::chrono::duration<float>>(dt).count();
}
class meteorite {
public:
meteorite(int id, vector2d location);
int id;
/*!
* Called every tick
* \param dt the time that has passed since the previous tick
*/
void act(std::chrono::nanoseconds dt);
vector2d location() const { return location_; }
std::vector<vector2d> random_meteorite_locations(std::size_t n);
private:
vector2d velocity;
scalar max_velocity;
vector2d location_;
vector2d acceleration;
void location(vector2d loc) { location_ = loc; }
void random_position_force();
void screen_force(std::chrono::nanoseconds dt);
void move(std::chrono::nanoseconds dt);
void add_force(vector2d force);
void island_avoidance();
};
Meteorite source:
#include "meteorite.h"
meteorite::meteorite(int id, vector2d location) : id(id), velocity{ 0, 0 }, max_velocity(0.15), acceleration{ 0, 0 }, location_(location) {}
void meteorite::act(std::chrono::nanoseconds dt) {
move(dt);
}
void meteorite::move(std::chrono::nanoseconds dt) {
this->location(this->location() + velocity);
random_position_force();
screen_force(dt);
this->velocity += this->acceleration * to_seconds(dt);
// prevent velocity from exceeding max_velocity
float velocity_length = std::sqrt((this->velocity.x() * this->velocity.x()) + (this->velocity.y() * this->velocity.y()));
if (velocity_length >= this->max_velocity) {
this->velocity = normalize(this->velocity) * this->max_velocity;
}
/*directions:
* y -1 up
* y 1 down
*
* x 1 right
* x -1 left
*/
// reset acceleration to 0 for the next set of forces to be applied
this->acceleration = vector2d(0, 0);
}
// add force propeling meteorite to a random position
void meteorite::random_position_force() {
float x = (rand() % 100 - 50);
float y = (rand() % 100 - 50);
add_force(this->velocity + vector2d((x / 5), (y / 5)));
}
void meteorite::add_force(vector2d force) {
this->acceleration += force;
}
void meteorite::screen_force(std::chrono::nanoseconds dt)
{
auto new_position = this->location() + (this->velocity + (this->acceleration * to_seconds(dt)));
auto height = 1068 - 32;
auto width = 724 - 32;
if (new_position.x() <= 32) {
vector2d screen_vector = vector2d(0, 0);
if (this->acceleration.x() < 0)
{
screen_vector = vector2d(-this->acceleration.x() * 2, 0);
}
add_force(screen_vector);
}
else if (new_position.x() >= width)
{
vector2d screen_vector = vector2d(0, 0);
if (this->acceleration.x() > 0)
{
screen_vector = vector2d(-this->acceleration.x() * 2, 0);
}
add_force(screen_vector);
}
if (new_position.y() <= 32) {
vector2d screen_vector = vector2d(0, 0);
if (this->acceleration.y() < 0)
{
screen_vector = vector2d(0, -this->acceleration.y() * 2);
}
add_force(screen_vector);
}
else if (new_position.y() >= height)
{
vector2d screen_vector = vector2d(0, 0);
if (this->acceleration.y() > 0)
{
screen_vector = vector2d(0, -this->acceleration.y() * 2);
}
add_force(screen_vector);
}
}
std::vector<vector2d> meteorite::random_meteorite_locations(std::size_t n) {
// from 0x2 to 13x17 = 195
// from 13x0 to 28x9 = 135
// from 20x9 to 32x19 = 120
// from 6x17 to 25x24 = 133
// sum = 583
std::random_device rd{};
std::default_random_engine re{ rd() };
std::uniform_int_distribution<> id{ 0, 583 };
std::uniform_real_distribution<scalar> sd{ 0, 1 };
auto rv = [&](rectangle const& r) {
return r.top_left() + vector2d{ r.size().width() * sd(re),
r.size().height() * sd(re) };
};
std::array<rectangle, 4> rects{
rectangle{vector2d{0.1f, 2}, size{13, 15}},
rectangle{vector2d{13.f, 0.1f}, size{15, 9}},
rectangle{vector2d{20, 9}, size{12, 10}},
rectangle{vector2d{6, 17}, size{17, 6}} };
auto to_index = [](int i) -> std::size_t {
if (i < 195)
return 0;
else if (i < 330)
return 1;
else if (i < 450)
return 2;
else
return 3;
};
std::vector<vector2d> result(n);
std::generate_n(result.begin(), result.size(), [&] {
auto val = id(re);
auto index = to_index(val);
auto rect = rects[index];
return 32 * rv(rect);
});
return result;
}
Main.cpp
#include <iostream>
#include "meteorite.h"
int main()
{
meteorite m = meteorite{ 0, {} };
std::vector<meteorite*> meteorites;
std::vector<vector2d> locations = m.random_meteorite_locations(1);
int i = 1;
for (auto& loc : locations) {
meteorites.push_back(new meteorite(i, loc));
}
auto t_prev = std::chrono::high_resolution_clock::now();
while (true) {
auto t_current = std::chrono::high_resolution_clock::now();
std::chrono::nanoseconds dt = std::chrono::nanoseconds(200);
t_prev = t_current;
for (auto& m : meteorites) {
m->act(dt);
std::cout << m->location().x() << " " << m->location().y() << "\n";
}
}
for (auto& m : meteorites) {
delete m;
}
}
You're computing the new position incorrectly in both places, move() and screen_force(). You're doing s = s0 + (v + a * t), but you should be doing s = s0 + v * t + (a * t^2) / 2.
Here's a working example:
http://cpp.sh/9uu3w

How to find point of intersection in qcustomplot?

I have an app based on qt (qcustomplot) that prints two different graphs. They have one point of intersection. How to find x and y coordinates of this point?
This doesn't have much to do with plotting, since you'd be investigating the underlying data. Let's say that we can interpolate between data points using lines, and the data sets are single-valued (i.e. for any x or key coordinate, there's only one value).
Online demo of the code below
Let's sketch a solution. First, some preliminaries, and we detect whether QCustomPlot was included so that the code can be tested without it - the necessary classes are mocked:
#define _USE_MATH_DEFINES
#include <algorithm>
#include <cassert>
#include <cmath>
#include <iostream>
#include <optional>
#include <type_traits>
#include <vector>
//#include "qcustomplot.h"
constexpr bool debugOutput = false;
#ifndef QCP_PLOTTABLE_GRAPH_H
struct QCPGraphData {
double key, value;
QCPGraphData() = default;
QCPGraphData(double x, double y) : key(x), value(y) {}
};
#endif
auto keyLess(const QCPGraphData &l, const QCPGraphData &r) { return l.key < r.key; }
#ifndef QCP_PLOTTABLE_GRAPH_H
template <typename T> struct QCPDataContainer : public std::vector<T> {
using std::vector<T>::vector;
void sort() { std::sort(this->begin(), this->end(), keyLess); }
};
using QCPGraphDataContainer = QCPDataContainer<QCPGraphData>;
#endif
using Point = QCPGraphData;
using Container = QCPGraphDataContainer;
static_assert(std::is_copy_constructible_v<Point>, "Point must be copy-constructible");
Some helper functions:
std::ostream &operator<<(std::ostream &os, const Point &p) {
return os << "(" << p.key << ", " << p.value << ")";
}
template <class T> bool has_unique_keys(const T &v) {
constexpr auto keyEqual = [](const Point &l, const Point &r) { return l.key == r.key; };
return std::adjacent_find(std::begin(v), std::end(v), keyEqual) == std::end(v);
}
template <class T> bool has_valid_points(const T& v) {
constexpr auto isValid = [](const Point &p) { return std::isfinite(p.key) && std::isfinite(p.value); };
return std::all_of(std::begin(v), std::end(v), isValid);
}
The line segment intersection finder:
// intersection of two line segments
std::optional<Point> intersection(const Point &a1, const Point &a2, const Point &b1, const Point &b2)
{
auto p1 = a1, p2 = a2, p3 = b1, p4 = b2;
assert(p1.key <= p2.key);
assert(p3.key <= p4.key);
if (debugOutput) std::cout << p1 << "-" << p2 << ", " << p3 << "-" << p4;
auto const denom = (p1.key - p2.key)*(p3.value - p4.value)
- (p1.value - p2.value)*(p3.key - p4.key);
if (fabs(denom) > 1e-6*(p2.key - p1.key)) {
// the lines are not parallel
auto const scale = 1.0/denom;
auto const q = p1.key*p2.value - p1.value*p2.key;
auto const r = p3.key*p4.value - p3.value*p4.key;
auto const x = (q*(p3.key-p4.key) - (p1.key-p2.key)*r) * scale;
if (debugOutput) std::cout << " x=" << x << "\n";
if (p1.key <= x && x <= p2.key && p3.key <= x && x <= p4.key) {
auto const y = (q*(p3.value-p4.value) - (p1.value-p2.value)*r) * scale;
return std::optional<Point>(std::in_place, x, y);
}
}
else if (debugOutput) std::cout << "\n";
return std::nullopt;
}
An algorithm that walks down two lists of points sorted in ascending key (x) order, and finds all intersections of line segments spanning consecutive point pairs from these two lists:
std::vector<Point> findIntersections(const Container &a_, const Container &b_)
{
if (a_.size() < 2 || b_.size() < 2) return {};
static constexpr auto check = [](const auto &c){
assert(has_valid_points(c));
assert(std::is_sorted(c.begin(), c.end(), keyLess));
assert(has_unique_keys(c));
};
check(a_);
check(b_);
bool aFirst = a_.front().key <= b_.front().key;
const auto &a = aFirst ? a_ : b_, &b = aFirst ? b_ : a_;
assert(a.front().key <= b.front().key);
if (a.back().key < b.front().key) return {}; // the key spans don't overlap
std::vector<Point> intersections;
auto ia = a.begin(), ib = b.begin();
Point a1 = *ia++, b1 = *ib++;
while (ia->key < b1.key) a1=*ia++; // advance a until the key spans overlap
for (Point a2 = *ia, b2 = *ib;;) {
auto const ipt = intersection(a1, a2, b1, b2);
if (ipt)
intersections.push_back(*ipt);
bool advanceA = a2.key <= b2.key, advanceB = b2.key <= a2.key;
if (advanceA) {
if (++ia == a.end()) break;
a1 = a2, a2 = *ia;
}
if (advanceB) {
if (++ib == b.end()) break;
b1 = b2, b2 = *ib;
}
}
return intersections;
}
And a more generic version that can also sort the points in ascending key order:
auto findIntersections(Container &d1, Container &d2, bool presorted)
{
if (!presorted) {
d1.sort();
d2.sort();
}
return findIntersections(d1, d2);
}
And now some simple demonstration:
template <typename Fun>
Container makeGraph(double start, double step, double end, Fun &&fun) {
Container result;
int i = 0;
for (auto x = start; x <= end; x = ++i * step)
result.emplace_back(x, fun(x));
return result;
}
int main()
{
for (auto step2: {0.1, 0.1151484584}) {
auto sinPlot = makeGraph(-2*M_PI, 0.1, 3*M_PI, sin);
auto cosPlot = makeGraph(0., step2, 2*M_PI, cos);
auto intersections = findIntersections(sinPlot, cosPlot);
std::cout << "Intersections:\n";
for (auto &ip : intersections)
std::cout << " at " << ip << "\n";
}
}
Demo output:
Intersections:
at (0.785613, 0.706509)
at (3.92674, -0.706604)
Intersections:
at (0.785431, 0.706378)
at (3.92693, -0.706732)

C++: How to implement polymorphic object creator to populate a table

I have a table widget object that can be resized with set_num_col(int) and set_num_row(int).
A call to each of these functions will call a resize_table() function to populate the widget with table_cells objects.
However, I have two polymorphic types of cells: table_cell_default and table_cell_custom, derived from the same base class.
Upon creation of the table, how can I populate it with mixed types of cells, considering that the client knows which cells will be custom and which will be of default type?
I thought about adding a map in the table class, and populate this map with for example set_custom_cells( vector<index>() ), with the ij indices of the cells as keys and the corresponding lamda creator returning the correct type as value, but this map will only be used once to populate the table and never again. Is there a more dynamic way, using a lambda as a table_cell creator to fill that widget in a better way?
Thanks
Here's an example of using a factory lambda to produce the initial cells in the Table's constructor. Refer to main function where the lambda is located, and the Table constructor for how it is used.
I do not know what your code looks like, so I just wrap each cell into an object_t and put that into the Table.
#include <cstdint>
#include <functional>
#include <iostream>
#include <memory>
#include <sstream>
#include <string>
#include <vector>
// Not idempotent. Should be last include.
#include <cassert>
using std::cout;
using std::function;
using std::make_shared;
using std::move;
using std::ostream;
using std::shared_ptr;
using std::size_t;
using std::string;
using std::stringstream;
using std::vector;
namespace {
template <typename T>
void draw_right_justified(T const& x, ostream& out, size_t width) {
stringstream ss;
ss << x;
string s = ss.str();
size_t pad_width = s.length() < width ? width - s.length() : 1;
out << string(pad_width, ' ') << s;
}
class object_t {
public:
template <typename T>
object_t(T x) : self_{make_shared<model<T>>(move(x))}
{ }
friend void draw_right_justified(object_t const& x, ostream& out, size_t width) {
x.self_->draw_right_justified_thunk(out, width);
}
private:
struct concept_t {
virtual ~concept_t() = default;
virtual void draw_right_justified_thunk(ostream&, size_t) const = 0;
};
template <typename T>
struct model : concept_t {
model(T x) : data_{move(x)} { }
void draw_right_justified_thunk(ostream& out, size_t width) const {
draw_right_justified(data_, out, width);
}
T data_;
};
shared_ptr<const concept_t> self_;
};
class Table {
size_t col;
size_t row;
// data will be constructed with col_ * row_ entries.
vector<object_t> data;
public:
using object_factory = function<object_t(size_t, size_t)>;
Table(size_t col_, size_t row_, object_factory& fn);
auto operator()(size_t x, size_t y) const -> object_t;
void display(ostream& out) const;
};
Table::Table(size_t col_, size_t row_, Table::object_factory& fn)
: col{col_}, row{row_}
{
data.reserve(col * row);
for (size_t y = 0; y < row; ++y) {
for (size_t x = 0; x < row; ++x) {
data.emplace_back(fn(x, y));
}
}
}
object_t Table::operator()(size_t x, size_t y) const {
assert(x < col);
assert(y < row);
return data[y * row + x];
}
void Table::display(ostream& out) const {
auto const& self = *this;
for (size_t y = 0; y < row; ++y) {
for (size_t x = 0; x < col; ++x) {
draw_right_justified(self(x, y), out, 8);
}
out << "\n";
}
}
struct empty_t {};
void draw_right_justified(empty_t, ostream& out, size_t width) {
string s = "(empty)";
size_t pad_width = s.length() < width ? width - s.length() : 1;
out << string(pad_width, ' ') << s;
}
struct bunny { string name; };
void draw_right_justified(bunny const& bunny, ostream& out, size_t width) {
auto const& s = bunny.name;
size_t pad_width = s.length() < width ? width - s.length() : 1;
out << string(pad_width, ' ') << s;
}
} // anon
int main() {
Table::object_factory maker = [](size_t x, size_t y) {
if (x == 0 && y == 1) return object_t{bunny{"Bugs"}};
if (x == 0 && y == 0) return object_t{empty_t{}};
if (x == y) return object_t{string("EQUAL")};
return object_t{x * y};
};
auto table = Table{3, 5, maker};
table.display(cout);
}
Output...
(empty) 0 0
Bugs EQUAL 2
0 2 EQUAL
0 3 6
0 4 8

How to have inheritance between template with union?

I have the following two objects. Im wondering if there is a way to have Pixel as a base class of PixelBGR so that any operator (+,-,*,/, [], etc.) could be used without redefining them ?
template<class T, std::size_t N>
struct Pixel
{
T ch[N];
inline T& operator[](const int x)
{
return ch[x];
}
};
template<class T>
struct PixelBGR
{
union
{
struct
{
T b;
T g;
T r;
};
T ch[3];
};
inline T& operator[](const int x)
{
return ch[x];
}
};
EDIT: As suggested by πάντα ῥεῖ, here more details about what Im trying to do.
Im trying to have a generic class Pixel, which will be template to handle any type or size.
The usual are 1,2,3,4,8 or 16. The class with defines some operator such as +,-,*, etc.
Since most of the time, the Pixel<T,3> is a BGR pixel, I would like to define rapid access to r,g and b to avoid confusion, but still store it as BGR.
But the derived class should also provide the Operator which will be generic based on N.
EDIT2: By reading the comment of SergeyA, I forgot to say that the struct Pixel must not change size.
So I think balki answer is the best, by using member function. I was trying to make it with variables to avoid too much char ie: adding the (), but it seems to be too complicated for nothing. I still investigating CRTP, but I dont get it well, Im reading on that.
Answering the question as asked, this should give OP reuse of the operators without any undefined behavior:
#include <cstddef>
template<class T, std::size_t N>
struct Pixel
{
T ch[N];
inline T& operator[](const int x)
{
return ch[x];
}
Pixel& operator+= (const Pixel& ) { return *this;}
};
template<class T, std::size_t N>
Pixel<T, N> operator+ (const Pixel<T, N>& l, const Pixel<T, N>& r);
template<class T>
struct BgrPixel : Pixel<T, 3> {
using base = Pixel<T, 3>;
using base::base;
BgrPixel(const base& b) : base(b) { };
T& b = base::ch[0];
T& g = base::ch[1];
T& r = base::ch[2];
};
BgrPixel<int> a, b;
BgrPixel<int> c = a + b;
Alterinative would be to have b(), g() and r() as a member functions, but this would require you to access them as functions. You would also need const and non-const versions of them.
The benefits, however, would be that the size of the struct will not be increased and copy assignment would work naturally (which, in turn, could be solved by providing custom copy assignment).
The Curiously Recurring Template Pattern (CRTP) would work well in this case. In the CRTP the Derived class is used as a template argument to the Base class. Chapter 16.3 The Curiously Recurring Template Pattern (CRTP), from the C++ Templates - The Complete Guide, by David Vandevoorde and Nicolai M. Josuttis, explains things in more detail.
From the comments below, the usage of a union{struct{...}...} causes undefined behaviour (UB), but there have been some contradicting opinions upon this. As far as I'm aware, it is a gnu extension and supported by almost every compiler. glm for example uses union-structs quite very often.
As an alternative approach, you can use aliases (references) for the r,g,b variables.
#include <iostream>
template<typename T, std::size_t N, template<typename,std::size_t> class B >
struct Pixel
{
B<T,N> *crtp = static_cast<B<T,N>*>(this);
T& operator[](std::size_t x)
{
return crtp->ch[x];
}
Pixel& operator = (const Pixel &t)
{
crtp->ch[0] = t.crtp->ch[0];
crtp->ch[1] = t.crtp->ch[1];
crtp->ch[2] = t.crtp->ch[2];
return *crtp;
}
B<T,N> operator + (const B<T,N> &t)
{
B<T,N> tmp;
tmp[0] = crtp->ch[0] + t.crtp->ch[0];
tmp[1] = crtp->ch[1] + t.crtp->ch[1];
tmp[2] = crtp->ch[2] + t.crtp->ch[2];
return tmp;
}
B<T,N> operator - (const B<T,N> &t)
{
B<T,N> tmp;
tmp[0] = crtp->ch[0] - t.crtp->ch[0];
tmp[1] = crtp->ch[1] - t.crtp->ch[1];
tmp[2] = crtp->ch[2] - t.crtp->ch[2];
return tmp;
}
};
template<typename T, std::size_t N=3>
struct PixelBGR : Pixel<T, N, PixelBGR>
{
T ch[3];
T &r;
T &g;
T &b;
PixelBGR() : ch{},r(ch[0]),g(ch[1]),b(ch[2])
{}
PixelBGR& operator = (const PixelBGR &p)
{
ch[0] = p.ch[0];
ch[1] = p.ch[1];
ch[2] = p.ch[2];
return *this;
}
};
int main()
{
PixelBGR<int> p;
p.r = 25;
p.g = 14;
p.b = 58;
std::cout<< p[0] <<" , "<<p[1]<<" , "<<p[2] <<std::endl;
PixelBGR<int> q;
q = p;
std::cout<< q[0] <<" , "<<q[1]<<" , "<<q[2] <<std::endl;
PixelBGR<int> res1;
res1 = q + p;
std::cout<< res1.r <<" , "<<res1.g<<" , "<<res1.b <<std::endl;
PixelBGR<int> res2;
res2 = q - p;
std::cout<< res2.r <<" , "<<res2.g<<" , "<<res2.b <<std::endl;
}
Result:
25 , 14 , 58
25 , 14 , 58
50 , 28 , 116
0 , 0 , 0
Example using references: https://rextester.com/AZWG4319
Example using union-struct: https://rextester.com/EACC87146
First thanks to all of you for advise, and special thanks to #Constantinos Glynos, #balki and #SergeyA for the example they provide, those help me to achieve a solution that match my need.
I implemented the BGR and BGRA to show that the N works fine, now I just need to implement all the operator, and functions that I require.
Please feel free to edit, or tell me if there is something wrong with this.
Pixel.h
#include <cstdio> // std::size_t
#include <iostream> // std::cout
template<typename T, std::size_t N, template<typename, std::size_t> class B >
struct Pixel
{
T ch[N];
// ==============================================================
// Overload the accessor (so .ch[0] == direct access with [0].
T& operator[](std::size_t x){ return ch[x]; }
// ==============================================================
// Copy-assignement
Pixel& operator=( const Pixel &t )
{
for ( int i = 0; i < N; i++ )
ch[i] = t.ch[i];
return *this;
}
// ==============================================================
// Operator
B<T, N> operator+( const B<T, N> &t )
{
B<T, N> tmp;
for ( int i = 0; i < N; i++ )
tmp[i] = ch[i] + t.ch[i];
return tmp;
}
B<T, N> operator-( const B<T, N> &t )
{
B<T, N> tmp;
for ( int i = 0; i < N; i++ )
tmp[i] = ch[i] - t.ch[i];
return tmp;
}
template<typename T, std::size_t N, template<typename, std::size_t> class B >
friend std::ostream& operator<<( std::ostream& os, const Pixel &t );
};
// To print the vector
template<typename T, std::size_t N, template<typename, std::size_t> class B >
std::ostream& operator<<( std::ostream& os, const B<T, N> &t )
{
os << "Pixel: (" << t.ch[0];
for ( int i = 1; i < N; i++ )
os << ", " << t.ch[i];
os << ")";
return os;
}
template<typename T, std::size_t N = 3>
struct BGR : Pixel<T, N, BGR>
{
T& b() { return ch[0]; }
T& g() { return ch[1]; }
T& r() { return ch[2]; }
};
template<typename T, std::size_t N = 4>
struct BGRA : Pixel<T, N, BGRA>
{
T& b() { return ch[0]; }
T& g() { return ch[1]; }
T& r() { return ch[2]; }
T& a() { return ch[3]; }
};
Main.cpp
int main() {
std::cout << "Sizeof a float BGR: " << sizeof(BGR<float>) << std::endl;
std::cout << "Sizeof a float BGRA: " << sizeof(BGRA<float>) << std::endl;
BGR<int> p;
p.r() = 25;
p.g() = 14;
p.b() = 58;
std::cout << p << std::endl;
std::cout << p[0] << " , " << p[1] << " , " << p[2] << std::endl;
std::cout << p.b() << " , " << p.g() << " , " << p.r() << std::endl;
BGR<int> q;
q = p;
std::cout << q[0] << " , " << q[1] << " , " << q[2] << std::endl;
BGR<int> res1;
res1 = q + p;
std::cout << res1.r() << " , " << res1.g() << " , " << res1.b() << std::endl;
BGR<int> res2;
res2 = q - p;
std::cout << res2.r() << " , " << res2.g() << " , " << res2.b() << std::endl;
BGRA<float> a;
a.r() = 255.0f;
a.g() = 0.0f;
a.b() = 0.0f;
a.a() = 128.5f;
BGRA<float> b = a;
std::cout << a << std::endl;
return 0;
}

How to implement a tensor class for Kronecker-Produkt [closed]

Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 5 years ago.
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Currently I came across an interesting article what's called the Kronecker-Produkt. At the same time I'm working on my neural network library.
So that my algorithm works, I need a tensor class, where I can get the product of two tensor's with an overloaded * operator.
Consider the following example/questions:
How to efficiently construct/store the nested matrices?
How to perform the product of two tensor's?
How to visualize tensor c as simply as possible?
My class 3 tensor which currently only supports 3 dimensions:
#pragma once
#include <iostream>
#include <sstream>
#include <random>
#include <cmath>
#include <iomanip>
template<typename T>
class tensor {
public:
const unsigned int x, y, z, s;
tensor(unsigned int x, unsigned int y, unsigned int z, T val) : x(x), y(y), z(z), s(x * y * z) {
p_data = new T[s];
for (unsigned int i = 0; i < s; i++) p_data[i] = val;
}
tensor(const tensor<T> & other) : x(other.x), y(other.y), z(other.z), s(other.s) {
p_data = new T[s];
memcpy(p_data, other.get_data(), s * sizeof(T));
}
~tensor() {
delete[] p_data;
p_data = nullptr;
}
T * get_data() {
return p_data;
}
static tensor<T> * random(unsigned int x, unsigned int y, unsigned int z, T val, T min, T max) {
tensor<T> * p_tensor = new tensor<T>(x, y, z, val);
std::random_device rd;
std::mt19937 mt(rd());
std::uniform_real_distribution<T> dist(min, max);
for (unsigned int i = 0; i < p_tensor->s; i++) {
T rnd = dist(mt);
while (abs(rnd) < 0.001) rnd = dist(mt);
p_tensor->get_data()[i] = rnd;
}
return p_tensor;
}
static tensor<T> * from(std::vector<T> * p_data, T val) {
tensor<T> * p_tensor = new tensor<T>(p_data->size(), 1, 1, val);
for (unsigned int i = 0; i < p_tensor->get_x(); i++) p_tensor->set_data(i + 0 * p_tensor->get_x() * + 0 * p_tensor->get_x() * p_tensor->get_y(), p_data->at(i));
return p_tensor;
}
friend std::ostream & operator <<(std::ostream & stream, tensor<T> & tensor) {
stream << "(" << tensor.x << "," << tensor.y << "," << tensor.z << ") Tensor\n";
for (unsigned int i = 0; i < tensor.x; i++) {
for (unsigned int k = 0; k < tensor.z; k++) {
stream << "[";
for (unsigned int j = 0; j < tensor.y; j++) {
stream << std::setw(5) << roundf(tensor(i, j, k) * 1000) / 1000;
if (j + 1 < tensor.y) stream << ",";
}
stream << "]";
}
stream << std::endl;
}
return stream;
}
tensor<T> & operator +(tensor<T> & other) {
tensor<T> result(*this);
return result;
}
tensor<T> & operator -(tensor<T> & other) {
tensor<T> result(*this);
return result;
}
tensor<T> & operator *(tensor<T> & other) {
tensor<T> result(*this);
return result;
}
T & operator ()(unsigned int i, unsigned int j, unsigned int k) {
return p_data[i + (j * x) + (k * x * y)];
}
T & operator ()(unsigned int i) {
return p_data[i];
}
private:
T * p_data = nullptr;
};
int main() {
tensor<double> * p_tensor_input = tensor<double>::random(6, 2, 3, 0.0, 0.0, 1.0);
tensor<double> * p_tensor_weight = tensor<double>::random(2, 6, 3, 0.0, 0.0, 1.0);
std::cout << *p_tensor_input << std::endl;
std::cout << *p_tensor_weight << std::endl;
tensor<double> p_tensor_output = *p_tensor_input + *p_tensor_weight;
return 0;
}
Your first step is #2 -- and get it correct.
After that, optimize.
Start with a container C<T>.
Define some operations on it. wrap(T) returns a C<T> containing that T. map takes a C<T> and a function on T U f(T) and returns C<U>. flatten takes a C<C<U>> and returns a C<U>.
Define scale( T, C<T> ) which takes a T and a C<T> and returns a C<T> with the elements scaled. Aka, scalar multiplication.
template<class T>
C<T> scale( T scalar, C<T> container ) {
return map( container, [&](T t){ return t*scalar; } );
}
Then we have:
template<class T>
C<T> tensor( C<T> lhs, C<T> rhs ) {
return flatten( map( lhs, [&](T t) { return scale( t, rhs ); } ) );
}
is your tensor product. And yes, that can be your actual code. I would tweak it a bit for efficiency.
(Note I used different terms, but I'm basically describing monadic operations using different words.)
After you have this, test, optimize, and iterate.
As for 3, the result of tensor products get large and complex, there is no simple visualization for a large tensor.
Oh, and keep things simple and store data in a std::vector to start.
Here are some tricks for efficient vectors i learned in class, but they should be equally good for a tensor.
Define an empty constructor and assignment operator. For example
tensor(unsigned int x, unsigned int y, unsigned int z) : x(x), y(y), z(z), s(x * y * z) {
p_data = new T[s];
}
tensor& operator=( tensor const& that ) {
for (int i=0; i<size(); ++i) {
p_data[i] = that(i) ;
}
return *this ;
}
template <typename T>
tensor& operator=( T const& that ) {
for (int i=0; i<size(); ++i) {
p_data[i] = that(i) ;
}
return *this ;
}
Now we can implement things like addition and scaling with deferred evaluation. For example:
template<typename T1, typename T2>
class tensor_sum {
//add value_type to base tensor class for this to work
typedef decltype( typename T1::value_type() + typename T2::value_type() ) value_type ;
//also add function to get size of tensor
value_type operator()( int i, int j, int k ) const {
return t1_(i,j,k) + v2_(i,j,k) ;
}
value_type operator()( int i ) const {
return t1_(i) + v2_(i) ;
}
private:
T1 const& t1_;
T2 const& t2_;
}
template <typename T1, typename T2>
tensor_sum<T1,T2> operator+(T1 const& t1, T2 const& t2 ) {
return vector_sum<T1,T2>(t1,t2) ;
}
This tensor_sum behaves exactly like any normal tensor, except that we don't have to allocate memory to store the result. So we can do something like this:
tensor<double> t0(...);
tensor<double> t1(...);
tensor<double> t2(...);
tensor<double> result(...); //define result to be empty, we will fill it later
result = t0 + t1 + 5.0*t2;
The compiler should optimize this to be just one loop, without storing intermediate results or modifying the original tensors. You can do the same thing for scaling and the kronecker product. Depending on what you want to do with the tensors, this can be a big advantage. But be careful, this isn't always the best option.
When implementing the kronecker product you should be careful of the of the ordering of your loop, try to go through the tensors in the order they are stored for cache efficiency.