Calculating Point Density using Python

Question

I have a list of X and Y coordinates from geodata of a specific part of the world. I want to assign each coordinate, a weight, based upon where it lies in the graph.

Answer 1

You initial inclination to draw a circle around each point and count the number of other points in that circle is a good one and as mentioned by unutbu, a KDTree will be a fast way to solve this problem.

This can be done very easily with PySAL, which using scipy's kdtree under the hood.

import pysal
import numpy
pts = numpy.random.random((100,2)) #generate some random points
radius = 0.2 #pick an arbitrary radius

#Build a Spatial Weights Matrix
W = pysal.threshold_continuousW_from_array(pts, threshold=radius)
# Note: if your points are in Latitude and Longitude you can increase the accuracy by
#       passing the radius of earth to this function and it will use arc distances.
# W = pysal.threshold_continuousW_from_array(pts, threshold=radius, radius=pysal.cg.RADIUS_EARTH_KM)

print W.cardinalities
#{0: 10, 1: 15, ..... }

If your data is in a Shapefile, simply replace threshold_continuousW_from_array with threshold_continuousW_from_shapefile, see the docs for details.