find_closest_point

pyhelpers.geom.find_closest_point(pt, ref_pts, as_geom=True)[source]

Find the closest point in a sequence of reference points to a given point.

This function calculates and returns the point closest to pt from a sequence of reference points ref_pts. The closest point can be returned either as a Shapely Point geometry (shapely.geometry.Point) or as a numpy.ndarray.

Parameters:

  • pt (tuple | list | shapely.geometry.Point) – Point for which the closest point is to be found.

  • ref_pts (Iterable | numpy.ndarray | list | tuple | shapely.geometry.base.BaseGeometry) – Sequence of reference points to search for the closest point.

  • as_geom (bool) – Whether to return the closest point as a shapely.geometry.Point; defaults to True.

Returns:

Closest point to pt from ref_pts.

Return type:

shapely.geometry.Point | numpy.ndarray

Examples:

>>> from pyhelpers.geom import find_closest_point
>>> from pyhelpers._cache import example_dataframe
>>> example_df = example_dataframe()
>>> example_df
            Longitude   Latitude
City
London      -0.127647  51.507322
Birmingham  -1.902691  52.479699
Manchester  -2.245115  53.479489
Leeds       -1.543794  53.797418
>>> # Find the city closest to London
>>> london = example_df.loc['London'].values
>>> ref_cities = example_df.loc['Birmingham':, :].values
>>> closest_to_london = find_closest_point(pt=london, ref_pts=ref_cities)
>>> closest_to_london.wkt  # Birmingham
'POINT (-1.9026911 52.4796992)'
>>> # Find the city closest to Leeds
>>> leeds = example_df.loc['Leeds'].values
>>> ref_cities = example_df.loc[:'Manchester', :].values
>>> closest_to_leeds = find_closest_point(pt=leeds, ref_pts=ref_cities)
>>> closest_to_leeds.wkt  # Manchester
'POINT (-2.2451148 53.4794892)'
>>> closest_to_leeds = find_closest_point(pt=leeds, ref_pts=ref_cities, as_geom=False)
>>> closest_to_leeds  # Manchester
array([-2.2451148, 53.4794892])