Introduce `imgen::vector` tuple alias, generate metrics as double

3 files changed, 28 insertions, 33 deletions

diff --git a/src/imgen.h b/src/imgen.h
index 6954239..20705b4 100644
--- a/src/imgen.h
+++ b/src/imgen.h
@@ -7,7 +7,8 @@
 
 namespace imgen {
 
-using colored_vector = std::tuple<int, int, color>;
+using vector         = std::tuple<std::ptrdiff_t, std::ptrdiff_t>;
+using colored_vector = std::tuple<std::ptrdiff_t, std::ptrdiff_t, color>;
 
 void write_ppm(
 	const std::string&                                   path,
diff --git a/unit_circle.cc b/unit_circle.cc
index 283fb53..aa12bf7 100644
--- a/unit_circle.cc
+++ b/unit_circle.cc
@@ -4,13 +4,12 @@
 #include <vector>
 #include <algorithm>
 
-int p_norm(double p, int x, int y) {
-	return static_cast<int>(std::nearbyint(
-		std::pow(
-			std::pow(std::abs(x), p) + std::pow(std::abs(y), p),
-			1.0 / p
-		)
-	));
+double p_norm(double p, int x, int y) {
+	return std::pow(
+		  std::pow(std::abs(x), p)
+		+ std::pow(std::abs(y), p),
+		1.0 / p
+	);
 }
 
 void generate_p_unit_circle(
@@ -24,7 +23,7 @@ void generate_p_unit_circle(
 			128,
 			128,
 			[p](std::ptrdiff_t x, std::ptrdiff_t y) -> imgen::color {
-				if ( p_norm(p, x, y) <= 32 ) {
+				if ( p_norm(p, x, y) <= 32.0 ) {
 					return imgen::black();
 				} else {
 					return imgen::white();
diff --git a/voronoi.cc b/voronoi.cc
index 4c864fd..00a49d6 100644
--- a/voronoi.cc
+++ b/voronoi.cc
@@ -5,33 +5,24 @@
 #include <vector>
 #include <algorithm>
 
-std::ptrdiff_t minkowski_metric(
-	const double p,
-	const std::ptrdiff_t refX, const std::ptrdiff_t refY,
-	const std::ptrdiff_t x,    const std::ptrdiff_t y
+double minkowski_metric(
+	const double         p,
+	const imgen::vector& a,
+	const imgen::vector& b
 ) {
-	return static_cast<std::ptrdiff_t>(
-		std::nearbyint(
-			std::pow(
-				std::pow(std::abs(refX - x), p) + std::pow(std::abs(refY - y), p),
-				1.0 / p
-			)
-		)
+	return std::pow(
+		  std::pow(std::abs(std::get<0>(a) - std::get<0>(b)), p)
+		+ std::pow(std::abs(std::get<1>(a) - std::get<1>(b)), p),
+		1.0 / p
 	);
 }
 
-std::ptrdiff_t manhattan_metric(
-	const std::ptrdiff_t refX, const std::ptrdiff_t refY,
-	const std::ptrdiff_t x,    const std::ptrdiff_t y
-) {
-	return minkowski_metric(1, refX, refY, x, y);
+double manhattan_metric(const imgen::vector& a, const imgen::vector& b) {
+	return minkowski_metric(1, a, b);
 }
 
-std::ptrdiff_t euclidean_metric(
-	const std::ptrdiff_t refX, const std::ptrdiff_t refY,
-	const std::ptrdiff_t x,    const std::ptrdiff_t y
-) {
-	return minkowski_metric(2, refX, refY, x, y);
+double euclidean_metric(const imgen::vector& a, const imgen::vector& b) {
+	return minkowski_metric(2, a, b);
 }
 
 void generate_minkowski_voronoi(const double p) {
@@ -52,14 +43,18 @@ void generate_minkowski_voronoi(const double p) {
 		512,
 		512,
 		[&ref, p](std::ptrdiff_t x, std::ptrdiff_t y) -> imgen::color {
-			std::array<std::ptrdiff_t, 9> distances;
+			std::array<double, 9> distances;
 
 			std::transform(
 				ref.begin(),
 				ref.end(),
 				distances.begin(),
 				[x, y, p](const imgen::colored_vector& pos) {
-				return minkowski_metric(p, std::get<0>(pos), std::get<1>(pos), x, y);
+				return minkowski_metric(
+					p,
+					imgen::vector{std::get<0>(pos), std::get<1>(pos)},
+					imgen::vector{x, y}
+				);
 			});
 
 			const auto& minimal_distance = std::min_element(
@@ -70,7 +65,7 @@ void generate_minkowski_voronoi(const double p) {
 				std::distance(distances.begin(), minimal_distance)
 			];
 
-			if ( *minimal_distance <= 5 ) {
+			if ( *minimal_distance <= 5.0 ) {
 				return imgen::black();
 			} else {
 				return std::get<2>(nearest);