// Copyright 2016 Google Inc. All rights reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. package s2 // This file contains various predicates that are guaranteed to produce // correct, consistent results. They are also relatively efficient. This is // achieved by computing conservative error bounds and falling back to high // precision or even exact arithmetic when the result is uncertain. Such // predicates are useful in implementing robust algorithms. // // See also EdgeCrosser, which implements various exact // edge-crossing predicates more efficiently than can be done here. import ( "math" "math/big" "github.com/golang/geo/r3" "github.com/golang/geo/s1" ) const ( // If any other machine architectures need to be suppported, these next three // values will need to be updated. // epsilon is a small number that represents a reasonable level of noise between two // values that can be considered to be equal. epsilon = 1e-15 // dblEpsilon is a smaller number for values that require more precision. // This is the C++ DBL_EPSILON equivalent. dblEpsilon = 2.220446049250313e-16 // dblError is the C++ value for S2 rounding_epsilon(). dblError = 1.110223024625156e-16 // maxDeterminantError is the maximum error in computing (AxB).C where all vectors // are unit length. Using standard inequalities, it can be shown that // // fl(AxB) = AxB + D where |D| <= (|AxB| + (2/sqrt(3))*|A|*|B|) * e // // where "fl()" denotes a calculation done in floating-point arithmetic, // |x| denotes either absolute value or the L2-norm as appropriate, and // e is a reasonably small value near the noise level of floating point // number accuracy. Similarly, // // fl(B.C) = B.C + d where |d| <= (|B.C| + 2*|B|*|C|) * e . // // Applying these bounds to the unit-length vectors A,B,C and neglecting // relative error (which does not affect the sign of the result), we get // // fl((AxB).C) = (AxB).C + d where |d| <= (3 + 2/sqrt(3)) * e maxDeterminantError = 1.8274 * dblEpsilon // detErrorMultiplier is the factor to scale the magnitudes by when checking // for the sign of set of points with certainty. Using a similar technique to // the one used for maxDeterminantError, the error is at most: // // |d| <= (3 + 6/sqrt(3)) * |A-C| * |B-C| * e // // If the determinant magnitude is larger than this value then we know // its sign with certainty. detErrorMultiplier = 3.2321 * dblEpsilon ) // Direction is an indication of the ordering of a set of points. type Direction int // These are the three options for the direction of a set of points. const ( Clockwise Direction = -1 Indeterminate Direction = 0 CounterClockwise Direction = 1 ) // newBigFloat constructs a new big.Float with maximum precision. func newBigFloat() *big.Float { return new(big.Float).SetPrec(big.MaxPrec) } // Sign returns true if the points A, B, C are strictly counterclockwise, // and returns false if the points are clockwise or collinear (i.e. if they are all // contained on some great circle). // // Due to numerical errors, situations may arise that are mathematically // impossible, e.g. ABC may be considered strictly CCW while BCA is not. // However, the implementation guarantees the following: // // If Sign(a,b,c), then !Sign(c,b,a) for all a,b,c. func Sign(a, b, c Point) bool { // NOTE(dnadasi): In the C++ API the equivalent method here was known as "SimpleSign". // We compute the signed volume of the parallelepiped ABC. The usual // formula for this is (A ⨯ B) · C, but we compute it here using (C ⨯ A) · B // in order to ensure that ABC and CBA are not both CCW. This follows // from the following identities (which are true numerically, not just // mathematically): // // (1) x ⨯ y == -(y ⨯ x) // (2) -x · y == -(x · y) return c.Cross(a.Vector).Dot(b.Vector) > 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) == Indeterminate 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 Indeterminate 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. func RobustSign(a, b, c Point) Direction { sign := triageSign(a, b, c) if sign == Indeterminate { sign = expensiveSign(a, b, c) } return sign } // 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, 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 := b.Sub(a.Vector) ab2 := ab.Norm2() bc := c.Sub(b.Vector) bc2 := bc.Norm2() ca := a.Sub(c.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 } // triageSign returns the direction sign of the points. It returns Indeterminate if two // points are identical or the result is uncertain. Uncertain cases can be resolved, if // desired, by calling expensiveSign. // // The purpose of this method is to allow additional cheap tests to be done without // calling expensiveSign. func triageSign(a, b, c Point) Direction { det := a.Cross(b.Vector).Dot(c.Vector) if det > maxDeterminantError { return CounterClockwise } if det < -maxDeterminantError { return Clockwise } return Indeterminate } // expensiveSign reports the direction sign of the points. It returns Indeterminate // if two of the input points are the same. It uses multiple-precision arithmetic // to ensure that its results are always self-consistent. func expensiveSign(a, b, c Point) Direction { // Return Indeterminate if and only if two points are the same. // This ensures RobustSign(a,b,c) == Indeterminate if and only if a == b, b == c, or c == a. // ie. Property 1 of RobustSign. if a == b || b == c || c == a { return Indeterminate } // Next we try recomputing the determinant still using floating-point // arithmetic but in a more precise way. This is more expensive than the // simple calculation done by triageSign, but it is still *much* cheaper // than using arbitrary-precision arithmetic. This optimization is able to // compute the correct determinant sign in virtually all cases except when // the three points are truly collinear (e.g., three points on the equator). detSign := stableSign(a, b, c) if detSign != Indeterminate { return detSign } // Otherwise fall back to exact arithmetic and symbolic permutations. return exactSign(a, b, c, true) } // exactSign reports the direction sign of the points computed using high-precision // arithmetic and/or symbolic perturbations. func exactSign(a, b, c Point, perturb bool) Direction { // Sort the three points in lexicographic order, keeping track of the sign // of the permutation. (Each exchange inverts the sign of the determinant.) permSign := CounterClockwise pa := &a pb := &b pc := &c if pa.Cmp(pb.Vector) > 0 { pa, pb = pb, pa permSign = -permSign } if pb.Cmp(pc.Vector) > 0 { pb, pc = pc, pb permSign = -permSign } if pa.Cmp(pb.Vector) > 0 { pa, pb = pb, pa permSign = -permSign } // Construct multiple-precision versions of the sorted points and compute // their precise 3x3 determinant. xa := r3.PreciseVectorFromVector(pa.Vector) xb := r3.PreciseVectorFromVector(pb.Vector) xc := r3.PreciseVectorFromVector(pc.Vector) xbCrossXc := xb.Cross(xc) det := xa.Dot(xbCrossXc) // The precision of big.Float is high enough that the result should always // be exact enough (no rounding was performed). // If the exact determinant is non-zero, we're done. detSign := Direction(det.Sign()) if detSign == Indeterminate && perturb { // Otherwise, we need to resort to symbolic perturbations to resolve the // sign of the determinant. detSign = symbolicallyPerturbedSign(xa, xb, xc, xbCrossXc) } return permSign * detSign } // symbolicallyPerturbedSign reports the sign of the determinant of three points // A, B, C under a model where every possible Point is slightly perturbed by // a unique infinitesmal amount such that no three perturbed points are // collinear and no four points are coplanar. The perturbations are so small // that they do not change the sign of any determinant that was non-zero // before the perturbations, and therefore can be safely ignored unless the // determinant of three points is exactly zero (using multiple-precision // arithmetic). This returns CounterClockwise or Clockwise according to the // sign of the determinant after the symbolic perturbations are taken into account. // // Since the symbolic perturbation of a given point is fixed (i.e., the // perturbation is the same for all calls to this method and does not depend // on the other two arguments), the results of this method are always // self-consistent. It will never return results that would correspond to an // impossible configuration of non-degenerate points. // // This requires that the 3x3 determinant of A, B, C must be exactly zero. // And the points must be distinct, with A < B < C in lexicographic order. // // Reference: // "Simulation of Simplicity" (Edelsbrunner and Muecke, ACM Transactions on // Graphics, 1990). // func symbolicallyPerturbedSign(a, b, c, bCrossC r3.PreciseVector) Direction { // This method requires that the points are sorted in lexicographically // increasing order. This is because every possible Point has its own // symbolic perturbation such that if A < B then the symbolic perturbation // for A is much larger than the perturbation for B. // // Alternatively, we could sort the points in this method and keep track of // the sign of the permutation, but it is more efficient to do this before // converting the inputs to the multi-precision representation, and this // also lets us re-use the result of the cross product B x C. // // Every input coordinate x[i] is assigned a symbolic perturbation dx[i]. // We then compute the sign of the determinant of the perturbed points, // i.e. // | a.X+da.X a.Y+da.Y a.Z+da.Z | // | b.X+db.X b.Y+db.Y b.Z+db.Z | // | c.X+dc.X c.Y+dc.Y c.Z+dc.Z | // // The perturbations are chosen such that // // da.Z > da.Y > da.X > db.Z > db.Y > db.X > dc.Z > dc.Y > dc.X // // where each perturbation is so much smaller than the previous one that we // don't even need to consider it unless the coefficients of all previous // perturbations are zero. In fact, it is so small that we don't need to // consider it unless the coefficient of all products of the previous // perturbations are zero. For example, we don't need to consider the // coefficient of db.Y unless the coefficient of db.Z *da.X is zero. // // The follow code simply enumerates the coefficients of the perturbations // (and products of perturbations) that appear in the determinant above, in // order of decreasing perturbation magnitude. The first non-zero // coefficient determines the sign of the result. The easiest way to // enumerate the coefficients in the correct order is to pretend that each // perturbation is some tiny value "eps" raised to a power of two: // // eps** 1 2 4 8 16 32 64 128 256 // da.Z da.Y da.X db.Z db.Y db.X dc.Z dc.Y dc.X // // Essentially we can then just count in binary and test the corresponding // subset of perturbations at each step. So for example, we must test the // coefficient of db.Z*da.X before db.Y because eps**12 > eps**16. // // Of course, not all products of these perturbations appear in the // determinant above, since the determinant only contains the products of // elements in distinct rows and columns. Thus we don't need to consider // da.Z*da.Y, db.Y *da.Y, etc. Furthermore, sometimes different pairs of // perturbations have the same coefficient in the determinant; for example, // da.Y*db.X and db.Y*da.X have the same coefficient (c.Z). Therefore // we only need to test this coefficient the first time we encounter it in // the binary order above (which will be db.Y*da.X). // // The sequence of tests below also appears in Table 4-ii of the paper // referenced above, if you just want to look it up, with the following // translations: [a,b,c] -> [i,j,k] and [0,1,2] -> [1,2,3]. Also note that // some of the signs are different because the opposite cross product is // used (e.g., B x C rather than C x B). detSign := bCrossC.Z.Sign() // da.Z if detSign != 0 { return Direction(detSign) } detSign = bCrossC.Y.Sign() // da.Y if detSign != 0 { return Direction(detSign) } detSign = bCrossC.X.Sign() // da.X if detSign != 0 { return Direction(detSign) } detSign = newBigFloat().Sub(newBigFloat().Mul(c.X, a.Y), newBigFloat().Mul(c.Y, a.X)).Sign() // db.Z if detSign != 0 { return Direction(detSign) } detSign = c.X.Sign() // db.Z * da.Y if detSign != 0 { return Direction(detSign) } detSign = -(c.Y.Sign()) // db.Z * da.X if detSign != 0 { return Direction(detSign) } detSign = newBigFloat().Sub(newBigFloat().Mul(c.Z, a.X), newBigFloat().Mul(c.X, a.Z)).Sign() // db.Y if detSign != 0 { return Direction(detSign) } detSign = c.Z.Sign() // db.Y * da.X if detSign != 0 { return Direction(detSign) } // The following test is listed in the paper, but it is redundant because // the previous tests guarantee that C == (0, 0, 0). // (c.Y*a.Z - c.Z*a.Y).Sign() // db.X detSign = newBigFloat().Sub(newBigFloat().Mul(a.X, b.Y), newBigFloat().Mul(a.Y, b.X)).Sign() // dc.Z if detSign != 0 { return Direction(detSign) } detSign = -(b.X.Sign()) // dc.Z * da.Y if detSign != 0 { return Direction(detSign) } detSign = b.Y.Sign() // dc.Z * da.X if detSign != 0 { return Direction(detSign) } detSign = a.X.Sign() // dc.Z * db.Y if detSign != 0 { return Direction(detSign) } return CounterClockwise // dc.Z * db.Y * da.X } // CompareDistances returns -1, 0, or +1 according to whether AX < BX, A == B, // or AX > BX respectively. Distances are measured with respect to the positions // of X, A, and B as though they were reprojected to lie exactly on the surface of // the unit sphere. Furthermore, this method uses symbolic perturbations to // ensure that the result is non-zero whenever A != B, even when AX == BX // exactly, or even when A and B project to the same point on the sphere. // Such results are guaranteed to be self-consistent, i.e. if AB < BC and // BC < AC, then AB < AC. func CompareDistances(x, a, b Point) int { // We start by comparing distances using dot products (i.e., cosine of the // angle), because (1) this is the cheapest technique, and (2) it is valid // over the entire range of possible angles. (We can only use the sin^2 // technique if both angles are less than 90 degrees or both angles are // greater than 90 degrees.) sign := triageCompareCosDistances(x, a, b) if sign != 0 { return sign } // Optimization for (a == b) to avoid falling back to exact arithmetic. if a == b { return 0 } // It is much better numerically to compare distances using cos(angle) if // the distances are near 90 degrees and sin^2(angle) if the distances are // near 0 or 180 degrees. We only need to check one of the two angles when // making this decision because the fact that the test above failed means // that angles "a" and "b" are very close together. cosAX := a.Dot(x.Vector) if cosAX > 1/math.Sqrt2 { // Angles < 45 degrees. sign = triageCompareSin2Distances(x, a, b) } else if cosAX < -1/math.Sqrt2 { // Angles > 135 degrees. sin^2(angle) is decreasing in this range. sign = -triageCompareSin2Distances(x, a, b) } // C++ adds an additional check here using 80-bit floats. // This is skipped in Go because we only have 32 and 64 bit floats. if sign != 0 { return sign } sign = exactCompareDistances(r3.PreciseVectorFromVector(x.Vector), r3.PreciseVectorFromVector(a.Vector), r3.PreciseVectorFromVector(b.Vector)) if sign != 0 { return sign } return symbolicCompareDistances(x, a, b) } // cosDistance returns cos(XY) where XY is the angle between X and Y, and the // maximum error amount in the result. This requires X and Y be normalized. func cosDistance(x, y Point) (cos, err float64) { cos = x.Dot(y.Vector) return cos, 9.5*dblError*math.Abs(cos) + 1.5*dblError } // sin2Distance returns sin**2(XY), where XY is the angle between X and Y, // and the maximum error amount in the result. This requires X and Y be normalized. func sin2Distance(x, y Point) (sin2, err float64) { // The (x-y).Cross(x+y) trick eliminates almost all of error due to x // and y being not quite unit length. This method is extremely accurate // for small distances; the *relative* error in the result is O(dblError) for // distances as small as dblError. n := x.Sub(y.Vector).Cross(x.Add(y.Vector)) sin2 = 0.25 * n.Norm2() err = ((21+4*math.Sqrt(3))*dblError*sin2 + 32*math.Sqrt(3)*dblError*dblError*math.Sqrt(sin2) + 768*dblError*dblError*dblError*dblError) return sin2, err } // triageCompareCosDistances returns -1, 0, or +1 according to whether AX < BX, // A == B, or AX > BX by comparing the distances between them using cosDistance. func triageCompareCosDistances(x, a, b Point) int { cosAX, cosAXerror := cosDistance(a, x) cosBX, cosBXerror := cosDistance(b, x) diff := cosAX - cosBX err := cosAXerror + cosBXerror if diff > err { return -1 } if diff < -err { return 1 } return 0 } // triageCompareSin2Distances returns -1, 0, or +1 according to whether AX < BX, // A == B, or AX > BX by comparing the distances between them using sin2Distance. func triageCompareSin2Distances(x, a, b Point) int { sin2AX, sin2AXerror := sin2Distance(a, x) sin2BX, sin2BXerror := sin2Distance(b, x) diff := sin2AX - sin2BX err := sin2AXerror + sin2BXerror if diff > err { return 1 } if diff < -err { return -1 } return 0 } // exactCompareDistances returns -1, 0, or 1 after comparing using the values as // PreciseVectors. func exactCompareDistances(x, a, b r3.PreciseVector) int { // This code produces the same result as though all points were reprojected // to lie exactly on the surface of the unit sphere. It is based on testing // whether x.Dot(a.Normalize()) < x.Dot(b.Normalize()), reformulated // so that it can be evaluated using exact arithmetic. cosAX := x.Dot(a) cosBX := x.Dot(b) // If the two values have different signs, we need to handle that case now // before squaring them below. aSign := cosAX.Sign() bSign := cosBX.Sign() if aSign != bSign { // If cos(AX) > cos(BX), then AX < BX. if aSign > bSign { return -1 } return 1 } cosAX2 := newBigFloat().Mul(cosAX, cosAX) cosBX2 := newBigFloat().Mul(cosBX, cosBX) cmp := newBigFloat().Sub(cosBX2.Mul(cosBX2, a.Norm2()), cosAX2.Mul(cosAX2, b.Norm2())) return aSign * cmp.Sign() } // symbolicCompareDistances returns -1, 0, or +1 given three points such that AX == BX // (exactly) according to whether AX < BX, AX == BX, or AX > BX after symbolic // perturbations are taken into account. func symbolicCompareDistances(x, a, b Point) int { // Our symbolic perturbation strategy is based on the following model. // Similar to "simulation of simplicity", we assign a perturbation to every // point such that if A < B, then the symbolic perturbation for A is much, // much larger than the symbolic perturbation for B. We imagine that // rather than projecting every point to lie exactly on the unit sphere, // instead each point is positioned on its own tiny pedestal that raises it // just off the surface of the unit sphere. This means that the distance AX // is actually the true distance AX plus the (symbolic) heights of the // pedestals for A and X. The pedestals are infinitesmally thin, so they do // not affect distance measurements except at the two endpoints. If several // points project to exactly the same point on the unit sphere, we imagine // that they are placed on separate pedestals placed close together, where // the distance between pedestals is much, much less than the height of any // pedestal. (There are a finite number of Points, and therefore a finite // number of pedestals, so this is possible.) // // If A < B, then A is on a higher pedestal than B, and therefore AX > BX. switch a.Cmp(b.Vector) { case -1: return 1 case 1: return -1 default: return 0 } } var ( // ca45Degrees is a predefined ChordAngle representing (approximately) 45 degrees. ca45Degrees = s1.ChordAngleFromSquaredLength(2 - math.Sqrt2) ) // CompareDistance returns -1, 0, or +1 according to whether the distance XY is // respectively less than, equal to, or greater than the provided chord angle. Distances are measured // with respect to the positions of all points as though they are projected to lie // exactly on the surface of the unit sphere. func CompareDistance(x, y Point, r s1.ChordAngle) int { // As with CompareDistances, we start by comparing dot products because // the sin^2 method is only valid when the distance XY and the limit "r" are // both less than 90 degrees. sign := triageCompareCosDistance(x, y, float64(r)) if sign != 0 { return sign } // Unlike with CompareDistances, it's not worth using the sin^2 method // when the distance limit is near 180 degrees because the ChordAngle // representation itself has has a rounding error of up to 2e-8 radians for // distances near 180 degrees. if r < ca45Degrees { sign = triageCompareSin2Distance(x, y, float64(r)) if sign != 0 { return sign } } return exactCompareDistance(r3.PreciseVectorFromVector(x.Vector), r3.PreciseVectorFromVector(y.Vector), big.NewFloat(float64(r)).SetPrec(big.MaxPrec)) } // triageCompareCosDistance returns -1, 0, or +1 according to whether the distance XY is // less than, equal to, or greater than r2 respectively using cos distance. func triageCompareCosDistance(x, y Point, r2 float64) int { cosXY, cosXYError := cosDistance(x, y) cosR := 1.0 - 0.5*r2 cosRError := 2.0 * dblError * cosR diff := cosXY - cosR err := cosXYError + cosRError if diff > err { return -1 } if diff < -err { return 1 } return 0 } // triageCompareSin2Distance returns -1, 0, or +1 according to whether the distance XY is // less than, equal to, or greater than r2 respectively using sin^2 distance. func triageCompareSin2Distance(x, y Point, r2 float64) int { // Only valid for distance limits < 90 degrees. sin2XY, sin2XYError := sin2Distance(x, y) sin2R := r2 * (1.0 - 0.25*r2) sin2RError := 3.0 * dblError * sin2R diff := sin2XY - sin2R err := sin2XYError + sin2RError if diff > err { return 1 } if diff < -err { return -1 } return 0 } var ( bigOne = big.NewFloat(1.0).SetPrec(big.MaxPrec) bigHalf = big.NewFloat(0.5).SetPrec(big.MaxPrec) ) // exactCompareDistance returns -1, 0, or +1 after comparing using PreciseVectors. func exactCompareDistance(x, y r3.PreciseVector, r2 *big.Float) int { // This code produces the same result as though all points were reprojected // to lie exactly on the surface of the unit sphere. It is based on // comparing the cosine of the angle XY (when both points are projected to // lie exactly on the sphere) to the given threshold. cosXY := x.Dot(y) cosR := newBigFloat().Sub(bigOne, newBigFloat().Mul(bigHalf, r2)) // If the two values have different signs, we need to handle that case now // before squaring them below. xySign := cosXY.Sign() rSign := cosR.Sign() if xySign != rSign { if xySign > rSign { return -1 } return 1 // If cos(XY) > cos(r), then XY < r. } cmp := newBigFloat().Sub( newBigFloat().Mul( newBigFloat().Mul(cosR, cosR), newBigFloat().Mul(x.Norm2(), y.Norm2())), newBigFloat().Mul(cosXY, cosXY)) return xySign * cmp.Sign() } // TODO(roberts): Differences from C++ // CompareEdgeDistance // CompareEdgeDirections // EdgeCircumcenterSign // GetVoronoiSiteExclusion // GetClosestVertex // TriageCompareLineSin2Distance // TriageCompareLineCos2Distance // TriageCompareLineDistance // TriageCompareEdgeDistance // ExactCompareLineDistance // ExactCompareEdgeDistance // TriageCompareEdgeDirections // ExactCompareEdgeDirections // ArePointsAntipodal // ArePointsLinearlyDependent // GetCircumcenter // TriageEdgeCircumcenterSign // ExactEdgeCircumcenterSign // UnperturbedSign // SymbolicEdgeCircumcenterSign // ExactVoronoiSiteExclusion