Beispiel #1
0
// TrueCentroid returns the true centroid of the spherical triangle ABC multiplied by the
// signed area of spherical triangle ABC. The result is not normalized.
// The reasons for multiplying by the signed area are (1) this is the quantity
// that needs to be summed to compute the centroid of a union or difference of triangles,
// and (2) it's actually easier to calculate this way. All points must have unit length.
//
// The true centroid (mass centroid) is defined as the surface integral
// over the spherical triangle of (x,y,z) divided by the triangle area.
// This is the point that the triangle would rotate around if it was
// spinning in empty space.
//
// The best centroid for most purposes is the true centroid. Unlike the
// planar and surface centroids, the true centroid behaves linearly as
// regions are added or subtracted. That is, if you split a triangle into
// pieces and compute the average of their centroids (weighted by triangle
// area), the result equals the centroid of the original triangle. This is
// not true of the other centroids.
func TrueCentroid(a, b, c Point) Point {
	ra := float64(1)
	if sa := float64(b.Distance(c)); sa != 0 {
		ra = sa / math.Sin(sa)
	}
	rb := float64(1)
	if sb := float64(c.Distance(a)); sb != 0 {
		rb = sb / math.Sin(sb)
	}
	rc := float64(1)
	if sc := float64(a.Distance(b)); sc != 0 {
		rc = sc / math.Sin(sc)
	}

	// Now compute a point M such that:
	//
	//  [Ax Ay Az] [Mx]                       [ra]
	//  [Bx By Bz] [My]  = 0.5 * det(A,B,C) * [rb]
	//  [Cx Cy Cz] [Mz]                       [rc]
	//
	// To improve the numerical stability we subtract the first row (A) from the
	// other two rows; this reduces the cancellation error when A, B, and C are
	// very close together. Then we solve it using Cramer's rule.
	//
	// This code still isn't as numerically stable as it could be.
	// The biggest potential improvement is to compute B-A and C-A more
	// accurately so that (B-A)x(C-A) is always inside triangle ABC.
	x := r3.Vector{a.X, b.X - a.X, c.X - a.X}
	y := r3.Vector{a.Y, b.Y - a.Y, c.Y - a.Y}
	z := r3.Vector{a.Z, b.Z - a.Z, c.Z - a.Z}
	r := r3.Vector{ra, rb - ra, rc - ra}

	return Point{r3.Vector{y.Cross(z).Dot(r), z.Cross(x).Dot(r), x.Cross(y).Dot(r)}.Mul(0.5)}
}
Beispiel #2
0
// RobustSign returns a Direction representing the ordering of the points.
// CounterClockwise is returned if the points are in counter-clockwise order,
// Clockwise for clockwise, and Indeterminate if any two points are the same (collinear),
// or the sign could not completely be determined.
//
// This function has additional logic to make sure that the above properties hold even
// when the three points are coplanar, and to deal with the limitations of
// floating-point arithmetic.
//
// RobustSign satisfies the following conditions:
//
//  (1) RobustSign(a,b,c) == 0 if and only if a == b, b == c, or c == a
//  (2) RobustSign(b,c,a) == RobustSign(a,b,c) for all a,b,c
//  (3) RobustSign(c,b,a) == -RobustSign(a,b,c) for all a,b,c
//
// In other words:
//
//  (1) The result is zero if and only if two points are the same.
//  (2) Rotating the order of the arguments does not affect the result.
//  (3) Exchanging any two arguments inverts the result.
//
// On the other hand, note that it is not true in general that
// RobustSign(-a,b,c) == -RobustSign(a,b,c), or any similar identities
// involving antipodal points.
//
// C++ Equivalent: RobustCCW()
func RobustSign(a, b, c Point) Direction {
	// This method combines the computations from the C++ methods
	// RobustCCW, TriageCCW, ExpensiveCCW, and StableCCW.
	// TODO: Split these extra functions out when the need arises.

	// Start with TriageCCW
	det := c.Cross(a.Vector).Dot(b.Vector)
	if det > maxDeterminantError {
		return CounterClockwise
	}
	if det < -maxDeterminantError {
		return Clockwise
	}

	// ExpensiveCCW
	if a == b || b == c || c == a {
		return Indeterminate
	}

	// StableCCW
	ab := a.Sub(b.Vector)
	ab2 := ab.Norm2()
	bc := b.Sub(c.Vector)
	bc2 := bc.Norm2()
	ca := c.Sub(a.Vector)
	ca2 := ca.Norm2()

	// The two shortest edges, pointing away from their common point.
	var e1, e2, op r3.Vector

	if ab2 >= bc2 && ab2 >= ca2 {
		// AB is the longest edge.
		e1, e2, op = ca, bc, c.Vector
	} else if bc2 >= ca2 {
		// BC is the longest edge.
		e1, e2, op = ab, ca, a.Vector
	} else {
		// CA is the longest edge.
		e1, e2, op = bc, ab, b.Vector
	}

	det = e1.Cross(e2).Dot(op)
	maxErr := detErrorMultiplier * math.Sqrt(e1.Norm2()*e2.Norm2())

	// If the determinant isn't zero, we know definitively the point ordering.
	if det > maxErr {
		return CounterClockwise
	}
	if det < -maxErr {
		return Clockwise
	}

	// In the C++ version, the final computation is performed using OpenSSL's
	// Bignum exact precision math library. The existence of an equivalent
	// library in Go is indeterminate. In C++, using the exact precision library
	// to solve this stage is ~300x slower than the above checks.
	// TODO(roberts): Select and incorporate an appropriate Go exact precision
	// floating point library for the remaining calculations.
	return Indeterminate
}
Beispiel #3
0
// face returns face ID from 0 to 5 containing the r. For points on the
// boundary between faces, the result is arbitrary but deterministic.
func face(r r3.Vector) int {
	abs := r.Abs()
	id := 0
	value := r.X
	if abs.Y > abs.X {
		id = 1
		value = r.Y
	}
	if abs.Z > math.Abs(value) {
		id = 2
		value = r.Z
	}
	if value < 0 {
		id += 3
	}
	return id
}
Beispiel #4
0
// stableSign reports the direction sign of the points in a numerically stable way.
// Unlike triageSign, this method can usually compute the correct determinant sign even when all
// three points are as collinear as possible.  For example if three points are
// spaced 1km apart along a random line on the Earth's surface using the
// nearest representable points, there is only a 0.4% chance that this method
// will not be able to find the determinant sign.  The probability of failure
// decreases as the points get closer together; if the collinear points are
// 1 meter apart, the failure rate drops to 0.0004%.
//
// This method could be extended to also handle nearly-antipodal points (and
// in fact an earlier version of this code did exactly that), but antipodal
// points are rare in practice so it seems better to simply fall back to
// exact arithmetic in that case.
func stableSign(a, b, c Point) Direction {
	ab := a.Sub(b.Vector)
	ab2 := ab.Norm2()
	bc := b.Sub(c.Vector)
	bc2 := bc.Norm2()
	ca := c.Sub(a.Vector)
	ca2 := ca.Norm2()

	// Now compute the determinant ((A-C)x(B-C)).C, where the vertices have been
	// cyclically permuted if necessary so that AB is the longest edge.  (This
	// minimizes the magnitude of cross product.)  At the same time we also
	// compute the maximum error in the determinant.

	// The two shortest edges, pointing away from their common point.
	var e1, e2, op r3.Vector
	if ab2 >= bc2 && ab2 >= ca2 {
		// AB is the longest edge.
		e1, e2, op = ca, bc, c.Vector
	} else if bc2 >= ca2 {
		// BC is the longest edge.
		e1, e2, op = ab, ca, a.Vector
	} else {
		// CA is the longest edge.
		e1, e2, op = bc, ab, b.Vector
	}

	det := e1.Cross(e2).Dot(op)
	maxErr := detErrorMultiplier * math.Sqrt(e1.Norm2()*e2.Norm2())

	// If the determinant isn't zero, within maxErr, we know definitively the point ordering.
	if det > maxErr {
		return CounterClockwise
	}
	if det < -maxErr {
		return Clockwise
	}
	return Indeterminate
}