/////////////////////////////////////////////////////////////////////////////
/////////////// (point along edge) functions ///////////////
// Given a point X and an edge AB, returns the distance ratio AX / (AX + BX).
// If X happens to be on the line segment AB, this is the fraction "t" such
// that X == Interpolate(A, B, t). Requires that A and B are distinct.
public static double GetDistanceFraction(S2Point x, S2Point a, S2Point b)
{
System.Diagnostics.Debug.Assert(a != b);
var da = x.Angle(a);
var db = x.Angle(b);
return(da / (da + db));
}
private static void GatherStats(S2Cell cell)
{
var s = level_stats[cell.Level];
double exact_area = cell.ExactArea();
double approx_area = cell.ApproxArea();
double min_edge = 100, max_edge = 0, avg_edge = 0;
double min_diag = 100, max_diag = 0;
double min_width = 100, max_width = 0;
double min_angle_span = 100, max_angle_span = 0;
for (int i = 0; i < 4; ++i)
{
double edge = cell.VertexRaw(i).Angle(cell.VertexRaw(i + 1));
min_edge = Math.Min(edge, min_edge);
max_edge = Math.Max(edge, max_edge);
avg_edge += 0.25 * edge;
S2Point mid = cell.VertexRaw(i) + cell.VertexRaw(i + 1);
double width = S2.M_PI_2 - mid.Angle(cell.EdgeRaw(i + 2));
min_width = Math.Min(width, min_width);
max_width = Math.Max(width, max_width);
if (i < 2)
{
double diag = cell.VertexRaw(i).Angle(cell.VertexRaw(i + 2));
min_diag = Math.Min(diag, min_diag);
max_diag = Math.Max(diag, max_diag);
double angle_span = cell.EdgeRaw(i).Angle(-cell.EdgeRaw(i + 2));
min_angle_span = Math.Min(angle_span, min_angle_span);
max_angle_span = Math.Max(angle_span, max_angle_span);
}
}
s.Count += 1;
s.Min_area = Math.Min(exact_area, s.Min_area);
s.Max_area = Math.Max(exact_area, s.Max_area);
s.Avg_area += exact_area;
s.Min_width = Math.Min(min_width, s.Min_width);
s.Max_width = Math.Max(max_width, s.Max_width);
s.Avg_width += 0.5 * (min_width + max_width);
s.Min_edge = Math.Min(min_edge, s.Min_edge);
s.Max_edge = Math.Max(max_edge, s.Max_edge);
s.Avg_edge += avg_edge;
s.Max_edge_aspect = Math.Max(max_edge / min_edge, s.Max_edge_aspect);
s.Min_diag = Math.Min(min_diag, s.Min_diag);
s.Max_diag = Math.Max(max_diag, s.Max_diag);
s.Avg_diag += 0.5 * (min_diag + max_diag);
s.Max_diag_aspect = Math.Max(max_diag / min_diag, s.Max_diag_aspect);
s.Min_angle_span = Math.Min(min_angle_span, s.Min_angle_span);
s.Max_angle_span = Math.Max(max_angle_span, s.Max_angle_span);
s.Avg_angle_span += 0.5 * (min_angle_span + max_angle_span);
double approx_ratio = approx_area / exact_area;
s.Min_approx_ratio = Math.Min(approx_ratio, s.Min_approx_ratio);
s.Max_approx_ratio = Math.Max(approx_ratio, s.Max_approx_ratio);
}
public void Test_S2CellId_Coverage()
{
// Make sure that random points on the sphere can be represented to the
// expected level of accuracy, which in the worst case is Math.Sqrt(2/3) times
// the maximum arc length between the points on the sphere associated with
// adjacent values of "i" or "j". (It is Math.Sqrt(2/3) rather than 1/2 because
// the cells at the corners of each face are stretched -- they have 60 and
// 120 degree angles.)
double max_dist = 0.5 * S2.kMaxDiag.GetValue(S2.kMaxCellLevel);
for (int i = 0; i < 1000000; ++i)
{
S2Point p = S2Testing.RandomPoint();
S2Point q = new S2CellId(p).ToPointRaw();
Assert.True(p.Angle(q) <= max_dist);
}
}
// Returns the true centroid of the spherical triangle ABC multiplied by the
// signed area of spherical triangle ABC. 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.
//
// Note that the result of this function is defined to be S2Point.Empty if
// the triangle is degenerate (and that this is intended behavior).
public static S2Point TrueCentroid(S2Point a, S2Point b, S2Point c)
{
System.Diagnostics.Debug.Assert(a.IsUnitLength());
System.Diagnostics.Debug.Assert(b.IsUnitLength());
System.Diagnostics.Debug.Assert(c.IsUnitLength());
// I couldn't find any references for computing the true centroid of a
// spherical triangle... I have a truly marvellous demonstration of this
// formula which this margin is too narrow to contain :)
// Use Angle() in order to get accurate results for small triangles.
var angle_a = b.Angle(c);
var angle_b = c.Angle(a);
var angle_c = a.Angle(b);
var ra = (angle_a == 0) ? 1 : (angle_a / Math.Sin(angle_a));
var rb = (angle_b == 0) ? 1 : (angle_b / Math.Sin(angle_b));
var rc = (angle_c == 0) ? 1 : (angle_c / Math.Sin(angle_c));
// 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.
//
// The result is the true centroid of the triangle multiplied by the
// triangle's area.
//
// TODO(b/205027737): 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.
var x = new S2Point(a.X, b.X - a.X, c.X - a.X);
var y = new S2Point(a.Y, b.Y - a.Y, c.Y - a.Y);
var z = new S2Point(a.Z, b.Z - a.Z, c.Z - a.Z);
var r = new S2Point(ra, rb - ra, rc - ra);
return(0.5 * new S2Point(
y.CrossProd(z).DotProd(r),
z.CrossProd(x).DotProd(r),
x.CrossProd(y).DotProd(r)));
}
public void Test_TriangleTrueCentroid_SmallTriangles()
{
// Test TrueCentroid() with very small triangles. This test assumes that
// the triangle is small enough so that it is nearly planar.
for (int iter = 0; iter < 100; ++iter)
{
S2Testing.GetRandomFrame(out var p, out var x, out var y);
double d = 1e-4 * Math.Pow(1e-4, S2Testing.Random.RandDouble());
S2Point p0 = (p - d * x).Normalize();
S2Point p1 = (p + d * x).Normalize();
S2Point p2 = (p + 3 * d * y).Normalize();
S2Point centroid = S2Centroid.TrueCentroid(p0, p1, p2).Normalize();
// The centroid of a planar triangle is at the intersection of its
// medians, which is two-thirds of the way along each median.
S2Point expected_centroid = (p + d * y).Normalize();
Assert.True(centroid.Angle(expected_centroid) <= 2e-8);
}
}
public void testCoverage()
{
Trace.WriteLine("TestCoverage");
// Make sure that random points on the sphere can be represented to the
// expected level of accuracy, which in the worst case is sqrt(2/3) times
// the maximum arc length between the points on the sphere associated with
// adjacent values of "i" or "j". (It is sqrt(2/3) rather than 1/2 because
// the cells at the corners of each face are stretched -- they have 60 and
// 120 degree angles.)
var maxDist = 0.5 * S2Projections.MaxDiag.GetValue(S2CellId.MaxLevel);
for (var i = 0; i < 1000000; ++i)
{
// randomPoint();
var p = new S2Point(0.37861576725894824, 0.2772406863275093, 0.8830558887338725);
var q = S2CellId.FromPoint(p).ToPointRaw();
Assert.True(p.Angle(q) <= maxDist);
}
}
// Return the area of triangle ABC. This method combines two different
// algorithms to get accurate results for both large and small triangles.
// The maximum error is about 5e-15 (about 0.25 square meters on the Earth's
// surface), the same as GirardArea() below, but unlike that method it is
// also accurate for small triangles. Example: when the true area is 100
// square meters, Area() yields an error about 1 trillion times smaller than
// GirardArea().
//
// All points should be unit length, and no two points should be antipodal.
// The area is always positive.
public static double Area(S2Point a, S2Point b, S2Point c)
{
System.Diagnostics.Debug.Assert(a.IsUnitLength());
System.Diagnostics.Debug.Assert(b.IsUnitLength());
System.Diagnostics.Debug.Assert(c.IsUnitLength());
// This method is based on l'Huilier's theorem,
//
// tan(E/4) = Math.Sqrt(tan(s/2) tan((s-a)/2) tan((s-b)/2) tan((s-c)/2))
//
// where E is the spherical excess of the triangle (i.e. its area),
// a, b, c, are the side lengths, and
// s is the semiperimeter (a + b + c) / 2 .
//
// The only significant source of error using l'Huilier's method is the
// cancellation error of the terms (s-a), (s-b), (s-c). This leads to a
// *relative* error of about 1e-16 * s / Math.Min(s-a, s-b, s-c). This compares
// to a relative error of about 1e-15 / E using Girard's formula, where E is
// the true area of the triangle. Girard's formula can be even worse than
// this for very small triangles, e.g. a triangle with a true area of 1e-30
// might evaluate to 1e-5.
//
// So, we prefer l'Huilier's formula unless dmin < s * (0.1 * E), where
// dmin = Math.Min(s-a, s-b, s-c). This basically includes all triangles
// except for extremely long and skinny ones.
//
// Since we don't know E, we would like a conservative upper bound on
// the triangle area in terms of s and dmin. It's possible to show that
// E <= k1 * s * Math.Sqrt(s * dmin), where k1 = 2*Math.Sqrt(3)/Pi (about 1).
// Using this, it's easy to show that we should always use l'Huilier's
// method if dmin >= k2 * s^5, where k2 is about 1e-2. Furthermore,
// if dmin < k2 * s^5, the triangle area is at most k3 * s^4, where
// k3 is about 0.1. Since the best case error using Girard's formula
// is about 1e-15, this means that we shouldn't even consider it unless
// s >= 3e-4 or so.
//
// TODO(ericv): Implement rigorous error bounds (analysis already done).
double sa = b.Angle(c);
double sb = c.Angle(a);
double sc = a.Angle(b);
double s = 0.5 * (sa + sb + sc);
if (s >= 3e-4)
{
// Consider whether Girard's formula might be more accurate.
double s2 = s * s;
double dmin = s - Math.Max(sa, Math.Max(sb, sc));
if (dmin < 1e-2 * s * s2 * s2)
{
// This triangle is skinny enough to consider using Girard's formula.
// We increase the area by the approximate maximum error in the Girard
// calculation in order to ensure that this test is conservative.
double area = GirardArea(a, b, c);
if (dmin < s * (0.1 * (area + 5e-15)))
{
return(area);
}
}
}
// Use l'Huilier's formula.
return(4 * Math.Atan(Math.Sqrt(Math.Max(0.0, Math.Tan(0.5 * s) * Math.Tan(0.5 * (s - sa)) *
Math.Tan(0.5 * (s - sb)) * Math.Tan(0.5 * (s - sc))))));
}
/**
* Return true if two points are within the given distance of each other
* (mainly useful for testing).
*/
public static bool ApproxEquals(S2Point a, S2Point b, double maxError)
{
return a.Angle(b) <= maxError;
}
/**
* Return the area of triangle ABC. The method used is about twice as
* expensive as Girard's formula, but it is numerically stable for both large
* and very small triangles. The points do not need to be normalized. The area
* is always positive.
*
* The triangle area is undefined if it contains two antipodal points, and
* becomes numerically unstable as the length of any edge approaches 180
* degrees.
*/
internal static double Area(S2Point a, S2Point b, S2Point c)
{
// This method is based on l'Huilier's theorem,
//
// tan(E/4) = sqrt(tan(s/2) tan((s-a)/2) tan((s-b)/2) tan((s-c)/2))
//
// where E is the spherical excess of the triangle (i.e. its area),
// a, b, c, are the side lengths, and
// s is the semiperimeter (a + b + c) / 2 .
//
// The only significant source of error using l'Huilier's method is the
// cancellation error of the terms (s-a), (s-b), (s-c). This leads to a
// *relative* error of about 1e-16 * s / Min(s-a, s-b, s-c). This compares
// to a relative error of about 1e-15 / E using Girard's formula, where E is
// the true area of the triangle. Girard's formula can be even worse than
// this for very small triangles, e.g. a triangle with a true area of 1e-30
// might evaluate to 1e-5.
//
// So, we prefer l'Huilier's formula unless dmin < s * (0.1 * E), where
// dmin = Min(s-a, s-b, s-c). This basically includes all triangles
// except for extremely long and skinny ones.
//
// Since we don't know E, we would like a conservative upper bound on
// the triangle area in terms of s and dmin. It's possible to show that
// E <= k1 * s * sqrt(s * dmin), where k1 = 2*sqrt(3)/Pi (about 1).
// Using this, it's easy to show that we should always use l'Huilier's
// method if dmin >= k2 * s^5, where k2 is about 1e-2. Furthermore,
// if dmin < k2 * s^5, the triangle area is at most k3 * s^4, where
// k3 is about 0.1. Since the best case error using Girard's formula
// is about 1e-15, this means that we shouldn't even consider it unless
// s >= 3e-4 or so.
// We use volatile doubles to force the compiler to truncate all of these
// quantities to 64 bits. Otherwise it may compute a value of dmin > 0
// simply because it chose to spill one of the intermediate values to
// memory but not one of the others.
var sa = b.Angle(c);
var sb = c.Angle(a);
var sc = a.Angle(b);
var s = 0.5*(sa + sb + sc);
if (s >= 3e-4)
{
// Consider whether Girard's formula might be more accurate.
var s2 = s*s;
var dmin = s - Math.Max(sa, Math.Max(sb, sc));
if (dmin < 1e-2*s*s2*s2)
{
// This triangle is skinny enough to consider Girard's formula.
var area = GirardArea(a, b, c);
if (dmin < s*(0.1*area))
{
return area;
}
}
}
// Use l'Huilier's formula.
return 4
*Math.Atan(
Math.Sqrt(
Math.Max(0.0,
Math.Tan(0.5*s)*Math.Tan(0.5*(s - sa))*Math.Tan(0.5*(s - sb))
*Math.Tan(0.5*(s - sc)))));
}
private void TestFaceClipping(S2Point a_raw, S2Point b_raw)
{
S2Point a = a_raw.Normalize();
S2Point b = b_raw.Normalize();
// First we test GetFaceSegments.
FaceSegmentVector segments = new();
GetFaceSegments(a, b, segments);
int n = segments.Count;
Assert.True(n >= 1);
var msg = new StringBuilder($"\nA={a_raw}\nB={b_raw}\nN={S2.RobustCrossProd(a, b)}\nSegments:\n");
int i1 = 0;
foreach (var s in segments)
{
msg.AppendLine($"{i1++}: face={s.face}, a={s.a}, b={s.b}");
}
_logger.WriteLine(msg.ToString());
R2Rect biunit = new(new R1Interval(-1, 1), new R1Interval(-1, 1));
var kErrorRadians = kFaceClipErrorRadians;
// The first and last vertices should approximately equal A and B.
Assert.True(a.Angle(S2.FaceUVtoXYZ(segments[0].face, segments[0].a)) <=
kErrorRadians);
Assert.True(b.Angle(S2.FaceUVtoXYZ(segments[n - 1].face, segments[n - 1].b)) <=
kErrorRadians);
S2Point norm = S2.RobustCrossProd(a, b).Normalize();
S2Point a_tangent = norm.CrossProd(a);
S2Point b_tangent = b.CrossProd(norm);
for (int i = 0; i < n; ++i)
{
// Vertices may not protrude outside the biunit square.
Assert.True(biunit.Contains(segments[i].a));
Assert.True(biunit.Contains(segments[i].b));
if (i == 0)
{
continue;
}
// The two representations of each interior vertex (on adjacent faces)
// must correspond to exactly the same S2Point.
Assert.NotEqual(segments[i - 1].face, segments[i].face);
Assert.Equal(S2.FaceUVtoXYZ(segments[i - 1].face, segments[i - 1].b),
S2.FaceUVtoXYZ(segments[i].face, segments[i].a));
// Interior vertices should be in the plane containing A and B, and should
// be contained in the wedge of angles between A and B (i.e., the dot
// products with a_tangent and b_tangent should be non-negative).
S2Point p = S2.FaceUVtoXYZ(segments[i].face, segments[i].a).Normalize();
Assert.True(Math.Abs(p.DotProd(norm)) <= kErrorRadians);
Assert.True(p.DotProd(a_tangent) >= -kErrorRadians);
Assert.True(p.DotProd(b_tangent) >= -kErrorRadians);
}
// Now we test ClipToPaddedFace (sometimes with a padding of zero). We do
// this by defining an (x,y) coordinate system for the plane containing AB,
// and converting points along the great circle AB to angles in the range
// [-Pi, Pi]. We then accumulate the angle intervals spanned by each
// clipped edge; the union over all 6 faces should approximately equal the
// interval covered by the original edge.
double padding = S2Testing.Random.OneIn(10) ? 0.0 : 1e-10 * Math.Pow(1e-5, S2Testing.Random.RandDouble());
S2Point x_axis = a, y_axis = a_tangent;
S1Interval expected_angles = new(0, a.Angle(b));
S1Interval max_angles = expected_angles.Expanded(kErrorRadians);
S1Interval actual_angles = new();
for (int face = 0; face < 6; ++face)
{
if (ClipToPaddedFace(a, b, face, padding, out var a_uv, out var b_uv))
{
S2Point a_clip = S2.FaceUVtoXYZ(face, a_uv).Normalize();
S2Point b_clip = S2.FaceUVtoXYZ(face, b_uv).Normalize();
Assert.True(Math.Abs(a_clip.DotProd(norm)) <= kErrorRadians);
Assert.True(Math.Abs(b_clip.DotProd(norm)) <= kErrorRadians);
if (a_clip.Angle(a) > kErrorRadians)
{
Assert2.DoubleEqual(1 + padding, Math.Max(Math.Abs(a_uv[0]), Math.Abs(a_uv[1])));
}
if (b_clip.Angle(b) > kErrorRadians)
{
Assert2.DoubleEqual(1 + padding, Math.Max(Math.Abs(b_uv[0]), Math.Abs(b_uv[1])));
}
double a_angle = Math.Atan2(a_clip.DotProd(y_axis), a_clip.DotProd(x_axis));
double b_angle = Math.Atan2(b_clip.DotProd(y_axis), b_clip.DotProd(x_axis));
// Rounding errors may cause b_angle to be slightly less than a_angle.
// We handle this by constructing the interval with FromPointPair(),
// which is okay since the interval length is much less than Math.PI.
S1Interval face_angles = S1Interval.FromPointPair(a_angle, b_angle);
Assert.True(max_angles.Contains(face_angles));
actual_angles = actual_angles.Union(face_angles);
}
}
Assert.True(actual_angles.Expanded(kErrorRadians).Contains(expected_angles));
}
private static IEnumerable <T> GetSurfaceIntegral <T>(S2PointLoopSpan loop, Func <S2Point, S2Point, S2Point, T> f_tri)
{
// We sum "f_tri" over a collection T of oriented triangles, possibly
// overlapping. Let the sign of a triangle be +1 if it is CCW and -1
// otherwise, and let the sign of a point "x" be the sum of the signs of the
// triangles containing "x". Then the collection of triangles T is chosen
// such that every point in the loop interior has the same sign x, and every
// point in the loop exterior has the same sign (x - 1). Furthermore almost
// always it is true that x == 0 or x == 1, meaning that either
//
// (1) Each point in the loop interior has sign +1, and sign 0 otherwise; or
// (2) Each point in the loop exterior has sign -1, and sign 0 otherwise.
//
// The triangles basically consist of a "fan" from vertex 0 to every loop
// edge that does not include vertex 0. However, what makes this a bit
// tricky is that spherical edges become numerically unstable as their
// length approaches 180 degrees. Of course there is not much we can do if
// the loop itself contains such edges, but we would like to make sure that
// all the triangle edges under our control (i.e., the non-loop edges) are
// stable. For example, consider a loop around the equator consisting of
// four equally spaced points. This is a well-defined loop, but we cannot
// just split it into two triangles by connecting vertex 0 to vertex 2.
//
// We handle this type of situation by moving the origin of the triangle fan
// whenever we are about to create an unstable edge. We choose a new
// location for the origin such that all relevant edges are stable. We also
// create extra triangles with the appropriate orientation so that the sum
// of the triangle signs is still correct at every point.
// The maximum length of an edge for it to be considered numerically stable.
// The exact value is fairly arbitrary since it depends on the stability of
// the "f_tri" function. The value below is quite conservative but could be
// reduced further if desired.
const double kMaxLength = Math.PI - 1e-5;
if (loop.Count < 3)
{
yield break;
}
S2Point origin = loop[0];
for (int i = 1; i + 1 < loop.Count; ++i)
{
// Let V_i be loop[i], let O be the current origin, and let length(A, B)
// be the length of edge (A, B). At the start of each loop iteration, the
// "leading edge" of the triangle fan is (O, V_i), and we want to extend
// the triangle fan so that the leading edge is (O, V_i+1).
//
// Invariants:
// 1. length(O, V_i) < kMaxLength for all (i > 1).
// 2. Either O == V_0, or O is approximately perpendicular to V_0.
// 3. "sum" is the oriented integral of f over the area defined by
// (O, V_0, V_1, ..., V_i).
System.Diagnostics.Debug.Assert(i == 1 || origin.Angle(loop[i]) < kMaxLength);
System.Diagnostics.Debug.Assert(origin == loop[0] || Math.Abs(origin.DotProd(loop[0])) < S2.DoubleError);
if (loop[i + 1].Angle(origin) > kMaxLength)
{
// We are about to create an unstable edge, so choose a new origin O'
// for the triangle fan.
S2Point old_origin = origin;
if (origin == loop[0])
{
// The following point O' is well-separated from V_i and V_0 (and
// therefore V_i+1 as well). Moving the origin transforms the leading
// edge of the triangle fan into a two-edge chain (V_0, O', V_i).
origin = S2.RobustCrossProd(loop[0], loop[i]).Normalize();
}
else if (loop[i].Angle(loop[0]) < kMaxLength)
{
// All edges of the triangle (O, V_0, V_i) are stable, so we can
// revert to using V_0 as the origin. This changes the leading edge
// chain (V_0, O, V_i) back into a single edge (V_0, V_i).
origin = loop[0];
}
else
{
// (O, V_i+1) and (V_0, V_i) are antipodal pairs, and O and V_0 are
// perpendicular. Therefore V_0.CrossProd(O) is approximately
// perpendicular to all of {O, V_0, V_i, V_i+1}, and we can choose
// this point O' as the new origin.
//
// NOTE(ericv): The following line is the reason why in rare cases the
// triangle sum can have a sign other than -1, 0, or 1. To fix this
// we would need to choose either "-origin" or "origin" below
// depending on whether the signed area of the triangles chosen so far
// is positive or negative respectively. This is easy in the case of
// GetSignedArea() but would be extra work for GetCentroid(). In any
// case this does not cause any problems in practice.
origin = loop[0].CrossProd(old_origin);
// The following two triangles transform the leading edge chain from
// (V_0, O, V_i) to (V_0, O', V_i+1).
//
// First we advance the edge (V_0, O) to (V_0, O').
yield return(f_tri(loop[0], old_origin, origin));
}
// Advance the edge (O, V_i) to (O', V_i).
yield return(f_tri(old_origin, loop[i], origin));
}
// Advance the edge (O, V_i) to (O, V_i+1).
yield return(f_tri(origin, loop[i], loop[i + 1]));
}
// If the origin is not V_0, we need to sum one more triangle.
if (origin != loop[0])
{
// Advance the edge (O, V_n-1) to (O, V_0).
yield return(f_tri(origin, loop[^ 1], loop[0]));
public void testCoverage()
{
Trace.WriteLine("TestCoverage");
// Make sure that random points on the sphere can be represented to the
// expected level of accuracy, which in the worst case is sqrt(2/3) times
// the maximum arc length between the points on the sphere associated with
// adjacent values of "i" or "j". (It is sqrt(2/3) rather than 1/2 because
// the cells at the corners of each face are stretched -- they have 60 and
// 120 degree angles.)
var maxDist = 0.5*S2Projections.MaxDiag.GetValue(S2CellId.MaxLevel);
for (var i = 0; i < 1000000; ++i)
{
// randomPoint();
var p = new S2Point(0.37861576725894824, 0.2772406863275093, 0.8830558887338725);
var q = S2CellId.FromPoint(p).ToPointRaw();
Assert.True(p.Angle(q) <= maxDist);
}
}
/**
* Given a point X and an edge AB, return the distance ratio AX / (AX + BX).
* If X happens to be on the line segment AB, this is the fraction "t" such
* that X == Interpolate(A, B, t). Requires that A and B are distinct.
*/
public static double GetDistanceFraction(S2Point x, S2Point a0, S2Point a1)
{
Preconditions.CheckArgument(!a0.Equals(a1));
var d0 = x.Angle(a0);
var d1 = x.Angle(a1);
return d0/(d0 + d1);
}
