2D坐标数组的Python Numpy实现:

import numpy as np


def dist2d(p1, p2, coords):
    ''' Distance from points to a finite line btwn p1 -> p2 '''
    assert coords.ndim == 2 and coords.shape[1] == 2, 'coords is not 2 dim'
    dp = p2 - p1
    st = dp[0]**2 + dp[1]**2
    u = ((coords[:, 0] - p1[0]) * dp[0] + (coords[:, 1] - p1[1]) * dp[1]) / st

    u[u > 1.] = 1.
    u[u < 0.] = 0.

    dx = (p1[0] + u * dp[0]) - coords[:, 0]
    dy = (p1[1] + u * dp[1]) - coords[:, 1]

    return np.sqrt(dx**2 + dy**2)


# Usage:
p1 = np.array([0., 0.])
p2 = np.array([0., 10.])

# List of coordinates
coords = np.array(
    [[0., 0.],
     [5., 5.],
     [10., 10.],
     [20., 20.]
     ])

d = dist2d(p1, p2, coords)

# Single coordinate
coord = np.array([25., 25.])
d = dist2d(p1, p2, coord[np.newaxis, :])

I'm assuming you want to find the shortest distance between the point and a line segment; to do this, you need to find the line (lineA) which is perpendicular to your line segment (lineB) which goes through your point, determine the intersection between that line (lineA) and your line which goes through your line segment (lineB); if that point is between the two points of your line segment, then the distance is the distance between your point and the point you just found which is the intersection of lineA and lineB; if the point is not between the two points of your line segment, you need to get the distance between your point and the closer of two ends of the line segment; this can be done easily by taking the square distance (to avoid a square root) between the point and the two points of the line segment; whichever is closer, take the square root of that one.

忍不住用python来编码:)

from math import sqrt, fabs
def pdis(a, b, c):
    t = b[0]-a[0], b[1]-a[1]           # Vector ab
    dd = sqrt(t[0]**2+t[1]**2)         # Length of ab
    t = t[0]/dd, t[1]/dd               # unit vector of ab
    n = -t[1], t[0]                    # normal unit vector to ab
    ac = c[0]-a[0], c[1]-a[1]          # vector ac
    return fabs(ac[0]*n[0]+ac[1]*n[1]) # Projection of ac to n (the minimum distance)

print pdis((1,1), (2,2), (2,0))        # Example (answer is 1.414)

fortran也是一样:)

real function pdis(a, b, c)
    real, dimension(0:1), intent(in) :: a, b, c
    real, dimension(0:1) :: t, n, ac
    real :: dd
    t = b - a                          ! Vector ab
    dd = sqrt(t(0)**2+t(1)**2)         ! Length of ab
    t = t/dd                           ! unit vector of ab
    n = (/-t(1), t(0)/)                ! normal unit vector to ab
    ac = c - a                         ! vector ac
    pdis = abs(ac(0)*n(0)+ac(1)*n(1))  ! Projection of ac to n (the minimum distance)
end function pdis


program test
    print *, pdis((/1.0,1.0/), (/2.0,2.0/), (/2.0,0.0/))   ! Example (answer is 1.414)
end program test

in R

     #distance beetween segment ab and point c in 2D space
getDistance_ort_2 <- function(a, b, c){
  #go to complex numbers
  A<-c(a[1]+1i*a[2],b[1]+1i*b[2])
  q=c[1]+1i*c[2]
  
  #function to get coefficients of line (ab)
  getAlphaBeta <- function(A)
  { a<-Re(A[2])-Re(A[1])
    b<-Im(A[2])-Im(A[1])
    ab<-as.numeric()
    ab[1] <- -Re(A[1])*b/a+Im(A[1])
    ab[2] <-b/a
    if(Im(A[1])==Im(A[2])) ab<- c(Im(A[1]),0)
    if(Re(A[1])==Re(A[2])) ab <- NA
    return(ab)
  }
  
  #function to get coefficients of line ortogonal to line (ab) which goes through point q
  getAlphaBeta_ort<-function(A,q)
  { ab <- getAlphaBeta(A) 
  coef<-c(Re(q)/ab[2]+Im(q),-1/ab[2])
  if(Re(A[1])==Re(A[2])) coef<-c(Im(q),0)
  return(coef)
  }
  
  #function to get coordinates of interception point 
  #between line (ab) and its ortogonal which goes through point q
  getIntersection_ort <- function(A, q){
    A.ab <- getAlphaBeta(A)
    q.ab <- getAlphaBeta_ort(A,q)
    if (!is.na(A.ab[1])&A.ab[2]==0) {
      x<-Re(q)
      y<-Im(A[1])}
    if (is.na(A.ab[1])) {
      x<-Re(A[1])
      y<-Im(q)
    } 
    if (!is.na(A.ab[1])&A.ab[2]!=0) {
      x <- (q.ab[1] - A.ab[1])/(A.ab[2] - q.ab[2])
      y <- q.ab[1] + q.ab[2]*x}
    xy <- x + 1i*y  
    return(xy)
  }
  
  intersect<-getIntersection_ort(A,q)
  if ((Mod(A[1]-intersect)+Mod(A[2]-intersect))>Mod(A[1]-A[2])) {dist<-min(Mod(A[1]-q),Mod(A[2]-q))
  } else dist<-Mod(q-intersect)
  return(dist)
}



 

这里没有看到Java实现，所以我将Javascript函数从接受的答案转换为Java代码:

static double sqr(double x) {
    return x * x;
}
static double dist2(DoublePoint v, DoublePoint w) {
    return sqr(v.x - w.x) + sqr(v.y - w.y);
}
static double distToSegmentSquared(DoublePoint p, DoublePoint v, DoublePoint w) {
    double l2 = dist2(v, w);
    if (l2 == 0) return dist2(p, v);
    double t = ((p.x - v.x) * (w.x - v.x) + (p.y - v.y) * (w.y - v.y)) / l2;
    if (t < 0) return dist2(p, v);
    if (t > 1) return dist2(p, w);
    return dist2(p, new DoublePoint(
            v.x + t * (w.x - v.x),
            v.y + t * (w.y - v.y)
    ));
}
static double distToSegment(DoublePoint p, DoublePoint v, DoublePoint w) {
    return Math.sqrt(distToSegmentSquared(p, v, w));
}
static class DoublePoint {
    public double x;
    public double y;

    public DoublePoint(double x, double y) {
        this.x = x;
        this.y = y;
    }
}

本想在GLSL中这样做，但如果可能的话，最好避免所有这些条件。使用clamp()可以避免两种端点情况:

// find closest point to P on line segment AB:
vec3 closest_point_on_line_segment(in vec3 P, in vec3 A, in vec3 B) {
    vec3 AP = P - A, AB = B - A;
    float l = dot(AB, AB);
    if (l <= 0.0000001) return A;    // A and B are practically the same
    return AP - AB*clamp(dot(AP, AB)/l, 0.0, 1.0);  // do the projection
}

如果您可以确定A和B彼此不会非常接近，则可以简化为删除If()。事实上，即使A和B是相同的，我的GPU仍然给出了这个无条件版本的正确结果(但这是使用pre-OpenGL 4.1，其中GLSL除零是未定义的):

// find closest point to P on line segment AB:
vec3 closest_point_on_line_segment(in vec3 P, in vec3 A, in vec3 B) {
    vec3 AP = P - A, AB = B - A;
    return AP - AB*clamp(dot(AP, AB)/dot(AB, AB), 0.0, 1.0);
}

计算距离是很简单的——GLSL提供了一个distance()函数，你可以在这个最近的点和P。

灵感来自Iñigo Quilez的胶囊距离函数代码