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#include <imgen.h>
#include <cmath>
#include <algorithm>
template <int p>
double minkowski_metric(int refX, int refY, int x, int y) {
return std::pow(
std::pow(std::abs(refX - x), p) + std::pow(std::abs(refY - y), p),
1.0/p
);
}
double euclidean_metric(int refX, int refY, int x, int y) {
return minkowski_metric<2>(refX, refY, x, y);
}
int manhattan_metric(int refX, int refY, int x, int y) {
return minkowski_metric<1>(refX, refY, x, y);
}
int main(int, char*[]) {
using refpos = std::tuple<int, int, imgen::color>;
std::array<refpos, 5> ref{
refpos(100, 50, imgen::color(255, 0, 0 )),
refpos(490, 300, imgen::color(0, 255, 0 )),
refpos(250, 250, imgen::color(0, 0, 255)),
refpos(400, 20, imgen::color(100, 10, 100)),
refpos(60, 400, imgen::color(20, 60, 300))
};
imgen::write_ppm(
"test.ppm",
500,
500,
[&ref](std::size_t x, std::size_t y) -> imgen::color {
const refpos& nearest = *std::min_element(
ref.begin(),
ref.end(),
[x, y](const refpos& a, const refpos& b) -> bool {
return minkowski_metric<5>(std::get<0>(a), std::get<1>(a), x, y)
< minkowski_metric<5>(std::get<0>(b), std::get<1>(b), x, y);
}
);
if ( euclidean_metric(std::get<0>(nearest), std::get<1>(nearest), x, y) <= 5 ) {
return imgen::color(0, 0, 0);
} else {
return std::get<2>(nearest);
}
}
);
}
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