common: Drop custom functions for one and zero

These are pretty silly and a bit too magical. Just use casts when it is
neccessary.

Author: StollD

src/common/constants.hpp

@@ -3,7 +3,7 @@
 #ifndef IPTSD_CONTACTS_CONTACT_HPP
 #define IPTSD_CONTACTS_CONTACT_HPP
 
-#include <common/constants.hpp>
+#include <common/casts.hpp>
 #include <common/types.hpp>
 
 #include <optional>
@@ -22,21 +22,21 @@ class Contact {
 	 *
 	 * Range: [0, 1] if normalized, [0, <input dimensions>] if not.
 	 */
-	Vector2<T> mean {Zero<T>(), Zero<T>()};
+	Vector2<T> mean = Vector2<T>::Zero();
 
 	/*
 	 * The size of the contact (diameter of major and minor axis).
 	 *
 	 * Range: [0, 1] if normalized, [0, <hypot of input dimensions>] if not.
 	 */
-	Vector2<T> size {Zero<T>(), Zero<T>()};
+	Vector2<T> size = Vector2<T>::Zero();
 
 	/*
 	 * The orientation of the contact.
 	 *
 	 * Range: [0, 1) if normalized, [0, pi) if not.
 	 */
-	T orientation = Zero<T>();
+	T orientation = casts::to<T>(0);
 
 	/*
 	 * Whether the stored values are normalized.

src/contacts/contact.hpp

@@ -30,6 +30,8 @@ void run_generic(const DenseBase<DerivedData> &in,
 {
 	using T = typename DenseBase<DerivedKernel>::Scalar;
 
+	constexpr isize size_zero = 0;
+
 	const Eigen::Index cols = in.cols();
 	const Eigen::Index rows = in.rows();
 
@@ -47,13 +49,13 @@ void run_generic(const DenseBase<DerivedData> &in,
 
 			for (Eigen::Index oy = 0; oy < rows; oy++) {
 				const isize sy = casts::to_signed(oy + ky) - dy;
-				const isize cy = std::clamp(sy, Zero<isize>(), rows - 1);
+				const isize cy = std::clamp(sy, size_zero, rows - 1);
 
 				const Eigen::Index iy = casts::to_eigen(cy);
 
 				for (Eigen::Index ox = 0; ox < cols; ox++) {
 					const isize sx = casts::to_signed(ox + kx) - dx;
-					const isize cx = std::clamp(sx, Zero<isize>(), cols - 1);
+					const isize cx = std::clamp(sx, size_zero, cols - 1);
 
 					const Eigen::Index ix = casts::to_eigen(cx);
 

src/contacts/detection/algorithms/convolution.hpp

@@ -4,7 +4,6 @@
 #define IPTSD_CONTACTS_DETECTION_ALGORITHMS_GAUSSIAN_HPP
 
 #include <common/casts.hpp>
-#include <common/constants.hpp>
 #include <common/types.hpp>
 
 #include <gsl/gsl>
@@ -222,7 +221,7 @@ void update_weight_maps(std::vector<Parameters<typename DenseBase<Derived>::Scal
 			for (Eigen::Index x = bmin.x(); x <= bmax.x(); x++) {
 				const T t = total(y, x);
 
-				if (t > Zero<T>())
+				if (t > casts::to<T>(0))
 					p.weights(y - bmin.y(), x - bmin.x()) /= t;
 			}
 		}
@@ -250,7 +249,7 @@ bool ge_solve(Matrix6<T> a, Vector6<T> b, Vector6<T> &x)
 		{
 			// step 1: find element with largest absolute value in column
 			Eigen::Index r = 0;
-			T v = Zero<T>();
+			T v = casts::to<T>(0);
 
 			for (Eigen::Index i = c; i < 6; ++i) {
 				const T vi = std::abs(a(c, i));

src/contacts/detection/algorithms/gaussian.hpp

@@ -2,7 +2,6 @@
 
 #include <common/buildopts.hpp>
 #include <common/casts.hpp>
-#include <common/constants.hpp>
 #include <common/types.hpp>
 
 namespace iptsd::contacts::detection::convolution::impl {
@@ -58,7 +57,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 	{
 		// x = 0
 		{
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, 0, 0) * k(-1, -1); // extended
 			v += d(i, 0, 0) * k(0, -1);  // extended
@@ -78,7 +77,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 		// 0 < x < n
 		const auto limit = i + cols - 2;
 		while (i < limit) {
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, -1, 0) * k(-1, -1); // extended
 			v += d(i, 0, 0) * k(0, -1);   // extended
@@ -97,7 +96,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 
 		// x = n - 1
 		{
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, -1, 0) * k(-1, -1); // extended
 			v += d(i, 0, 0) * k(0, -1);   // extended
@@ -119,7 +118,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 	while (i < cols * (rows - 1)) {
 		// x = 0
 		{
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, 0, -1) * k(-1, -1); // extended
 			v += d(i, 0, -1) * k(0, -1);
@@ -139,7 +138,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 		// 0 < x < n
 		const auto limit = i + cols - 2;
 		while (i < limit) {
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, -1, -1) * k(-1, -1);
 			v += d(i, 0, -1) * k(0, -1);
@@ -158,7 +157,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 
 		// x = n - 1
 		{
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, -1, -1) * k(-1, -1);
 			v += d(i, 0, -1) * k(0, -1);
@@ -180,7 +179,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 	{
 		// x = 0
 		{
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, 0, -1) * k(-1, -1); // extended
 			v += d(i, 0, -1) * k(0, -1);
@@ -200,7 +199,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 		// 1 < x < n - 2
 		const auto limit = i + cols - 2;
 		while (i < limit) {
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, -1, -1) * k(-1, -1);
 			v += d(i, 0, -1) * k(0, -1);
@@ -219,7 +218,7 @@ inline void run_3x3(const DenseBase<DerivedData> &in,
 
 		// x = n - 1
 		{
-			auto v = Zero<T>();
+			auto v = casts::to<T>(0);
 
 			v += d(i, -1, -1) * k(-1, -1);
 			v += d(i, 0, -1) * k(0, -1);