ray_polyline_intersect

ray_polyline_intersect(position, direction, polyline_vertices, max_distance=100.0, EC=None)

Shoot a ray in 2D from a position and see where it crashes into a given polyline

Calculates the intersection point between a ray and a given polyline in 2D

Parameters:

Name	Type	Description	Default
position	numpy double array	Vector of camera position coordinates	required
direction	numpy double array	Vector of camera direction	required
polyline_vertices	numpy double array	Matrix of polyline vertex coordinates	required
max_distance	double, optional (default 100.0)	Maximum ray distance to consider	100.0
EC	numpy int array, optional (default None)	Matrix of edge indices into polyline_vertices	None

Returns:

Name	Type	Description
x	numpy double array	Vector of intersection point coordinates (np.Inf if no intersection)
n	numpy double array	Vector of polyline normal at intersection (zeros if no intersection)
ind	int	Index into EC of intersection edge (-1 if no intersection)

See Also

test_ray_mesh_intersect.

Notes

This does a for loop on all the edges of the polyline, suffering performance.

Examples:

# Build a polyline; for example, a square
V = np.array([ [-1.0, -1.0], [-1.0, 1.0], [1.0, 1.0], [1.0, -1.0] ])
# Camera position and direction
cam_pos = np.array([-0.5,-1.5])
cam_dir = np.array([0.0,1.0])
# Looking upwards: intersection should be [-0.5,-1.0], normal downwards
x, n, ind = gpytoolbox.ray_polyline_intersect(cam_pos,cam_dir,V)

Source code in src/gpytoolbox/ray_polyline_intersect.py

def ray_polyline_intersect(position, direction, polyline_vertices, max_distance = 100.0, EC=None):
    """Shoot a ray in 2D from a position and see where it crashes into a given polyline

    Calculates the intersection point between a ray and a given polyline in 2D

    Parameters
    ----------
    position : numpy double array
        Vector of camera position coordinates
    direction : numpy double array
        Vector of camera direction 
    polyline_vertices : numpy double array
        Matrix of polyline vertex coordinates
    max_distance : double, optional (default 100.0)
        Maximum ray distance to consider
    EC : numpy int array, optional (default None)
        Matrix of edge indices into polyline_vertices

    Returns
    -------
    x : numpy double array
        Vector of intersection point coordinates (np.Inf if no intersection)
    n : numpy double array
        Vector of polyline normal at intersection (zeros if no intersection)
    ind : int 
        Index into EC of intersection edge (-1 if no intersection)

    See Also
    --------
    test_ray_mesh_intersect.

    Notes
    -----
    This does a for loop on all the edges of the polyline, suffering performance.

    Examples
    --------
    ```python
    # Build a polyline; for example, a square
    V = np.array([ [-1.0, -1.0], [-1.0, 1.0], [1.0, 1.0], [1.0, -1.0] ])
    # Camera position and direction
    cam_pos = np.array([-0.5,-1.5])
    cam_dir = np.array([0.0,1.0])
    # Looking upwards: intersection should be [-0.5,-1.0], normal downwards
    x, n, ind = gpytoolbox.ray_polyline_intersect(cam_pos,cam_dir,V)
    ```
    """

    if (EC is None):
        EC = edge_indices(polyline_vertices.shape[0],closed=True)
    ind = -1
    x = np.array([np.Inf, np.Inf])
    n = np.array([0.0, 0.0])
    distance_to_hit = max_distance 
    for i in range(0,EC.shape[0]):
        # Two endpoints of segment in polyline
        a0 = polyline_vertices[EC[i,0],:]
        a1 = polyline_vertices[EC[i,1],:]
        # Linear system will have this determinant
        det = direction[0]*(a1[1]- a0[1]) - direction[1]*(a1[0]- a0[0])
        if np.abs(det)<1e-8:
            # Parallel. Find out if intersecting (coincident) or not
            # Plug one of the segment endpoints into our ray equation
            eq0 = direction[1]*(a0[0] - position[0]) - direction[0]*(a0[1] - position[1])
            if np.abs(eq0)<1e-8: # Coincident
                # Is it behind us?
                sign0 = np.dot(a0 - position,direction)
                sign1 = np.dot(a1 - position,direction)
                # How far are they?
                t0 = np.linalg.norm(a0 - position)/np.linalg.norm(direction)
                t1 = np.linalg.norm(a0 - position)/np.linalg.norm(direction)
                hit = -1
                if sign0>0 and sign1>0:
                    if t0<t1:
                        hit = 0
                    else:
                        hit = 1
                elif sign0>0:
                    hit = 0
                elif sign1>0:
                    hit = 1
                # Assign
                if hit==0:
                    distance_to_hit = t0
                    x = position + t0*direction
                    ind = i
                    n = np.array([-(a1[1] - a0[1]),a1[0] - a0[0]])
                    # This isn't robust but honestly just don't repeat points in the polyline!
                    n = n/np.linalg.norm(n)
                elif hit==1:
                    distance_to_hit = t1
                    x = position + t1*direction
                    ind = i
                    n = np.array([-(a1[1] - a0[1]),a1[0] - a0[0]])
                    # This isn't robust but honestly just don't repeat points in the polyline!
                    n = n/np.linalg.norm(n)
        else: # Not parallel, there must be an intersection (even if outside segment bounds)
            A = np.array( [ [ direction[0] , a1[0] - a0[0] ] , [direction[1] , a1[1]- a0[1] ] ])
            b = np.reshape(a1 - position,(2,1))
            t = solve(A,b)
            if t[1]>0.0 and t[1]<1.0 and t[0]>0 and t[0]<distance_to_hit:
                distance_to_hit = t[0]
                x = position + t[0]*direction
                ind = i
                n = np.array([-(a1[1] - a0[1]),a1[0] - a0[0]])
                # This isn't robust but honestly just don't repeat points in the polyline!
                n = n/np.linalg.norm(n)
    return x, n, ind