How to understand a lambda function in a library

Question

Question

Here's a function to calculate alphashape of a set of points. It's from the documentation of the library 'alphashape'.

points_2d = [(0., 0.), (0., 1.), (1., 1.), (1., 0.),(0.5, 0.25), (0.5, 0.75), (0.25, 0.5), (0.75, 0.5)]

alpha_shape = alphashape(
    points_2d,
    lambda ind, r: 1.0 + any(np.array(points_2d)[ind][:,0] == 0.0))

I don't understand how the lambda function above works in the following context (an excerpt from library's source code).

Specifically, my questions are:

• where does variable r come from?
• what does [:,0] mean?

Context

def alphashape(points: Union[List[Tuple[float]], np.ndarray],
               alpha: Union[None, float] = None):
    coords = np.array(points)
    for point_indices, circumradius in alphasimplices(coords):
        if callable(alpha):
            resolved_alpha = alpha(point_indices, circumradius)

from scipy.spatial import Delaunay

def alphasimplices(points: Union[List[Tuple[float]], np.ndarray]) -> \
        Union[List[Tuple[float]], np.ndarray]:
    coords = np.asarray(points)
    tri = Delaunay(coords)

    for simplex in tri.simplices:
        simplex_points = coords[simplex]
        try:
            yield simplex, circumradius(simplex_points)    

def circumradius(points: Union[List[Tuple[float]], np.ndarray]) -> float:
    points = np.asarray(points)
    return np.linalg.norm(points[0, :] - np.dot(circumcenter(points), points))

def circumcenter(points: Union[List[Tuple[float]], np.ndarray]) -> np.ndarray:
    points = np.asarray(points)
    num_rows, num_columns = points.shape
    A = np.bmat([[2 * np.dot(points, points.T),
                  np.ones((num_rows, 1))],
                 [np.ones((1, num_rows)), np.zeros((1, 1))]])
    b = np.hstack((np.sum(points * points, axis=1),
                   np.ones((1))))
    return np.linalg.solve(A, b)[:-1]