Return a mask to reduce the density of points in irregularly-spaced data.
This function is used to down-sample a collection of scattered points (e.g. surface
data), returning a mask that can be used to select the points from one or more arrays
(e.g. arrays of temperature and dew point). The points selected can be controlled by
providing an array of priority values (e.g. rainfall totals to ensure that
stations with higher precipitation remain in the mask). The points and radius can be
specified with units. If none are provided, meters are assumed.
points ((N, K) array-like) – N locations of the points in K dimensional space
radius (pint.Quantity or float) – Minimum radius allowed between points. If units are not provided, meters is assumed.
priority ((N, K) array-like, optional) – If given, this should have the same shape as points; these values will
be used to control selection priority for points.
(N,) array-like of boolean values indicating whether points should be kept. This
can be used directly to index numpy arrays to return only the desired points.
>>> metpy.calc.reduce_point_density(np.array([1, 2, 3]), 1.)
array([ True, False, True])
>>> metpy.calc.reduce_point_density(np.array([1, 2, 3]), 1.,
... priority=np.array([0.1, 0.9, 0.3]))
array([False, True, False])
Mesonet Station Plot¶