# shapely.hausdorff_distance#

hausdorff_distance(a, b, densify=None, **kwargs)#

Compute the discrete Hausdorff distance between two geometries.

The Hausdorff distance is a measure of similarity: it is the greatest distance between any point in A and the closest point in B. The discrete distance is an approximation of this metric: only vertices are considered. The parameter ‘densify’ makes this approximation less coarse by splitting the line segments between vertices before computing the distance.

Parameters:
a, bGeometry or array_like
densifyfloat or array_like, optional

The value of densify is required to be between 0 and 1.

**kwargs

See NumPy ufunc docs for other keyword arguments.

Examples

```>>> from shapely import LineString
>>> line1 = LineString([(130, 0), (0, 0), (0, 150)])
>>> line2 = LineString([(10, 10), (10, 150), (130, 10)])
>>> hausdorff_distance(line1, line2)
14.14...
>>> hausdorff_distance(line1, line2, densify=0.5)
70.0
>>> hausdorff_distance(line1, LineString())
nan
>>> hausdorff_distance(line1, None)
nan
```