pointpats.weighted_mean_center¶

pointpats.weighted_mean_center(points, weights)[source]¶

pointpats.weighted_mean_center(points: ndarray, weights: Sequence) → ndarray[tuple[Any, ...], dtype[float64]]

pointpats.weighted_mean_center(points: GeoPandasBase, weights) → Point

Find weighted mean center of a marked point pattern.

Parameters:

pointsarraylike: array representing a point pattern
weightsarraylike: a series of attribute values of length n.

Returns:

center: center of a given point pattern

Examples

>>> import numpy as np
>>> import geopandas as gpd

Create an array of point coordinates.

>>> coords = np.array(
...     [
...         [66.22, 32.54],
...         [22.52, 22.39],
...         [31.01, 81.21],
...         [9.47, 31.02],
...         [30.78, 60.10],
...         [75.21, 58.93],
...         [79.26, 7.68],
...         [8.23, 39.93],
...         [98.73, 77.17],
...         [89.78, 42.53],
...         [65.19, 92.08],
...         [54.46, 8.48],
...     ]
... )
>>> weight = np.arange(1, 13, 1)

Passing an array of coordinates returns an array capturing the center.

>>> weighted_mean_center(coords, weight)
array([59.29448718, 47.52282051])

Passing a GeoPandas object returns a shapely geometry.

>>> geoms = gpd.GeoSeries.from_xy(*coords.T)
>>> weighted_mean_center(geoms, weight)
<POINT (59.294 47.523)>