c#代码实现lhf的答案:

// https://en.wikipedia.org/wiki/Curve_orientation#Orientation_of_a_simple_polygon
public static WindingOrder DetermineWindingOrder(IList<Vector2> vertices)
{
    int nVerts = vertices.Count;
    // If vertices duplicates first as last to represent closed polygon,
    // skip last.
    Vector2 lastV = vertices[nVerts - 1];
    if (lastV.Equals(vertices[0]))
        nVerts -= 1;
    int iMinVertex = FindCornerVertex(vertices);
    // Orientation matrix:
    //     [ 1  xa  ya ]
    // O = | 1  xb  yb |
    //     [ 1  xc  yc ]
    Vector2 a = vertices[WrapAt(iMinVertex - 1, nVerts)];
    Vector2 b = vertices[iMinVertex];
    Vector2 c = vertices[WrapAt(iMinVertex + 1, nVerts)];
    // determinant(O) = (xb*yc + xa*yb + ya*xc) - (ya*xb + yb*xc + xa*yc)
    double detOrient = (b.X * c.Y + a.X * b.Y + a.Y * c.X) - (a.Y * b.X + b.Y * c.X + a.X * c.Y);

    // TBD: check for "==0", in which case is not defined?
    // Can that happen?  Do we need to check other vertices / eliminate duplicate vertices?
    WindingOrder result = detOrient > 0
            ? WindingOrder.Clockwise
            : WindingOrder.CounterClockwise;
    return result;
}

public enum WindingOrder
{
    Clockwise,
    CounterClockwise
}

// Find vertex along one edge of bounding box.
// In this case, we find smallest y; in case of tie also smallest x.
private static int FindCornerVertex(IList<Vector2> vertices)
{
    int iMinVertex = -1;
    float minY = float.MaxValue;
    float minXAtMinY = float.MaxValue;
    for (int i = 0; i < vertices.Count; i++)
    {
        Vector2 vert = vertices[i];
        float y = vert.Y;
        if (y > minY)
            continue;
        if (y == minY)
            if (vert.X >= minXAtMinY)
                continue;

        // Minimum so far.
        iMinVertex = i;
        minY = y;
        minXAtMinY = vert.X;
    }

    return iMinVertex;
}

// Return value in (0..n-1).
// Works for i in (-n..+infinity).
// If need to allow more negative values, need more complex formula.
private static int WrapAt(int i, int n)
{
    // "+n": Moves (-n..) up to (0..).
    return (i + n) % n;
}

下面是一个基于@Beta答案的算法的简单c#实现。

让我们假设我们有一个Vector类型，它的X和Y属性为double类型。

public bool IsClockwise(IList<Vector> vertices)
{
    double sum = 0.0;
    for (int i = 0; i < vertices.Count; i++) {
        Vector v1 = vertices[i];
        Vector v2 = vertices[(i + 1) % vertices.Count];
        sum += (v2.X - v1.X) * (v2.Y + v1.Y);
    }
    return sum > 0.0;
}

%是执行模运算的模运算符或余数运算符，该运算符(根据维基百科)在一个数除以另一个数后求余数。

根据@MichelRouzic评论的优化版本:

double sum = 0.0;
Vector v1 = vertices[vertices.Count - 1]; // or vertices[^1] with
                                          // C# 8.0+ and .NET Core
for (int i = 0; i < vertices.Count; i++) {
    Vector v2 = vertices[i];
    sum += (v2.X - v1.X) * (v2.Y + v1.Y);
    v1 = v2;
}
return sum > 0.0;

这不仅节省了模运算%，还节省了数组索引。

测试(参见与@WDUK的讨论)

public static bool IsClockwise(IList<(double X, double Y)> vertices)
{
    double sum = 0.0;
    var v1 = vertices[^1];
    for (int i = 0; i < vertices.Count; i++) {
        var v2 = vertices[i];
        sum += (v2.X - v1.X) * (v2.Y + v1.Y);
        Console.WriteLine($"(({v2.X,2}) - ({v1.X,2})) * (({v2.Y,2}) + ({v1.Y,2})) = {(v2.X - v1.X) * (v2.Y + v1.Y)}");
        v1 = v2;
    }
    Console.WriteLine(sum);
    return sum > 0.0;
}

public static void Test()
{
    Console.WriteLine(IsClockwise(new[] { (-5.0, -5.0), (-5.0, 5.0), (5.0, 5.0), (5.0, -5.0) }));

    // infinity Symbol
    //Console.WriteLine(IsClockwise(new[] { (-5.0, -5.0), (-5.0, 5.0), (5.0, -5.0), (5.0, 5.0) }));
}

我将提出另一个解决方案，因为它很简单，不需要大量的数学运算，它只是使用了基本的代数。计算多边形的带符号面积。如果是负的，点是顺时针的，如果是正的，点是逆时针的。(这与Beta的解决方案非常相似。)

计算带符号的面积: A = 1/2 * (x1*y2 - x2*y1 + x2*y3 - x3*y2 +…+ xn*y1 - x1*yn)

或者在伪代码中:

signedArea = 0
for each point in points:
    x1 = point[0]
    y1 = point[1]
    if point is last point
        x2 = firstPoint[0]
        y2 = firstPoint[1]
    else
        x2 = nextPoint[0]
        y2 = nextPoint[1]
    end if

    signedArea += (x1 * y2 - x2 * y1)
end for
return signedArea / 2

注意，如果你只是检查顺序，你不需要麻烦除以2。

来源:http://mathworld.wolfram.com/PolygonArea.html

正如这篇维基百科文章中所解释的曲线方向，给定平面上的3个点p, q和r(即x和y坐标)，您可以计算以下行列式的符号

如果行列式为负(即定向(p, q, r) < 0)，则多边形是顺时针方向(CW)。如果行列式为正(即定向(p, q, r) > 0)，则多边形是逆时针方向(CCW)。如果点p, q和r共线，行列式为零(即定向(p, q, r) == 0)。

在上面的公式中，由于我们使用的是齐次坐标，我们将1放在p, q和r的坐标前面。

这是我使用其他答案中的解释的解决方案:

def segments(poly):
    """A sequence of (x,y) numeric coordinates pairs """
    return zip(poly, poly[1:] + [poly[0]])

def check_clockwise(poly):
    clockwise = False
    if (sum(x0*y1 - x1*y0 for ((x0, y0), (x1, y1)) in segments(poly))) < 0:
        clockwise = not clockwise
    return clockwise

poly = [(2,2),(6,2),(6,6),(2,6)]
check_clockwise(poly)
False

poly = [(2, 6), (6, 6), (6, 2), (2, 2)]
check_clockwise(poly)
True

解决方案R确定方向和反向如果顺时针(发现这是必要的owin对象):

coords <- cbind(x = c(5,6,4,1,1),y = c(0,4,5,5,0))
a <- numeric()
for (i in 1:dim(coords)[1]){
  #print(i)
  q <- i + 1
  if (i == (dim(coords)[1])) q <- 1
  out <- ((coords[q,1]) - (coords[i,1])) * ((coords[q,2]) + (coords[i,2]))
  a[q] <- out
  rm(q,out)
} #end i loop

rm(i)

a <- sum(a) #-ve is anti-clockwise

b <- cbind(x = rev(coords[,1]), y = rev(coords[,2]))

if (a>0) coords <- b #reverses coords if polygon not traced in anti-clockwise direction