def demo3(self): import ambry import ambry.library as dl import ambry.geo as dg from matplotlib import pyplot as plt import numpy as np l = dl.get_library() aa = dg.get_analysis_area(l, geoid='CG0666000') r = l.find(dl.QueryCommand().identity(id='a2z2HM').partition(table='incidents',space=aa.geoid)).pop() p = l.get(r.partition).partition a = aa.new_array() k = dg.ConstantKernel(9) print aa k.apply_add(a, dg.Point(400,1919)) k.apply_add(a, dg.Point(400,1920)) k.apply_add(a, dg.Point(400,1921)) k.apply_add(a, dg.Point(400,1922)) k.apply_add(a, dg.Point(400,1923)) for row in p.query("select date, time, cellx, celly from incidents"): p = dg.Point(row['cellx'],row['celly']) k.apply_add(a, p) a /= np.max(a) print np.sum(a) img = plt.imshow(a, interpolation='nearest') img.set_cmap('spectral_r') plt.colorbar() plt.show()
def demo3(self): import ambry.library as dl import ambry.geo as dg from matplotlib import pyplot as plt import numpy as np l = dl.get_library() aa = dg.get_analysis_area(l, geoid='CG0666000') r = l.find(dl.QueryCommand().identity(id='a2z2HM').partition(table='incidents',space=aa.geoid)).pop() p = l.get(r.partition).partition a = aa.new_array() k = dg.ConstantKernel(9) print aa k.apply_add(a, dg.Point(400,1919)) k.apply_add(a, dg.Point(400,1920)) k.apply_add(a, dg.Point(400,1921)) k.apply_add(a, dg.Point(400,1922)) k.apply_add(a, dg.Point(400,1923)) for row in p.query("select date, time, cellx, celly from incidents"): p = dg.Point(row['cellx'],row['celly']) k.apply_add(a, p) a /= np.max(a) print np.sum(a) img = plt.imshow(a, interpolation='nearest') img.set_cmap('spectral_r') plt.colorbar() plt.show()
def get_library(self): """Clear out the database before the test run""" l = get_library(self.client_rc, 'client') l.database.clean() l.logger.setLevel(logging.DEBUG) return l