Using property values calculates gradient based on a Delauney triangulation

Referance code is in the /ref folder

/ref/trigradient_demo.py : This example is a good referance for taking a set of points with location and value(calculated) and constricting a Delauney triagulation and then calculated gradiant. The plot is not quite what we want.

/ref/tricontour_vs_griddata.py: Comparison of griddata and tricontour for an unstructured triangular grid.

Jeff Kaufman has some great maps using rent data. Visualy this is what I want. Here are some examples http://rentheatmap.com/ Code here https://github.com/jeffkaufman/apartment_prices He uses his own K nearest algorythm, scipy has an implimentation here http://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.cKDTree.html#scipy.spatial.cKDTree

Useful Scipy page http://docs.scipy.org/doc/scipy/reference/spatial.html

For geocoding: pygeocoder seems to work well http://code.xster.net/pygeocoder/wiki/Home it uses the google api. geopy Have not tried. https://code.google.com/p/geopy/wiki/GettingStarted