low_density_coords = ps.paths_in_shape(np.column_stack((Hmaxx, Hmaxy))) #N_cluster_points = kmeans(low_density_coords, N)[0] density_coords = DENSITY.select_points() # make sure that your density coords are within the boundary shape density_coords = INPOLY.points_in(density_coords) #cluster = True if counter == 0: grad_ideal = 1e6 avg_ideal = 0 if grad_check1 < grad_ideal and avg_ideal < H_avg1: with open(u'ideal_coordinates.pickle', 'wb') as f: print "\nExporting new ideal coordinates." pickle.dump(coords, f, protocol=2) DENSITY.plot_field() #nodes=POLY_NODES)#SHAPE=UNIQUE_SHAPE) grad_ideal = grad_check1 avg_ideal = H_avg1 coords = COORDS.del_N(N=N, inputs=coords) paths = COORDS.del_N(N=N, inputs=paths) paths = list(paths) counter += 1 t1 = datetime.datetime.now() print "That loop took: ", t1 - t0
#N_cluster_points = kmeans(low_density_coords, N)[0] density_coords = DENSITY.select_points() # make sure that your density coords are within the boundary shape density_coords = INPOLY.points_in(density_coords) #cluster = True if counter == 0: grad_ideal = 1e6 avg_ideal = 0 if grad_check1 < grad_ideal and avg_ideal < H_avg1: with open(u'ideal_coordinates.pickle', 'wb') as f: print "\nExporting new ideal coordinates." pickle.dump(coords, f, protocol=2) DENSITY.plot_field(SHAPE=UNIQUE_SHAPE) grad_ideal = grad_check1 avg_ideal = H_avg1 coords = COORDS.del_N(N=n_stations, inputs=coords) paths = COORDS.del_N(N=n_stations, inputs=paths) paths=list(paths) counter+=1 t1 = datetime.datetime.now() print "That loop took: ", t1-t0
#N_cluster_points = kmeans(low_density_coords, N)[0] density_coords = DENSITY.select_points() # make sure that your density coords are within the boundary shape density_coords = INPOLY.points_in(density_coords) #cluster = True if counter == 0: grad_ideal = 1e6 avg_ideal = 0 if grad_check1 < grad_ideal and avg_ideal < H_avg1: with open(u'ideal_coordinates.pickle', 'wb') as f: print "\nExporting new ideal coordinates." pickle.dump(coords, f, protocol=2) DENSITY.plot_field(SHAPE=UNIQUE_SHAPE) grad_ideal = grad_check1 avg_ideal = H_avg1 coords = COORDS.del_N(N=N, inputs=coords) paths = COORDS.del_N(N=N, inputs=paths) paths=list(paths) counter+=1 t1 = datetime.datetime.now() print "That loop took: ", t1-t0
#N_cluster_points = kmeans(low_density_coords, N)[0] density_coords = DENSITY.select_points() # make sure that your density coords are within the boundary shape density_coords = INPOLY.points_in(density_coords) #cluster = True if counter == 0: grad_ideal = 1e6 avg_ideal = 0 if grad_check1 < grad_ideal and avg_ideal < H_avg1: with open(u'ideal_coordinates.pickle', 'wb') as f: print "\nExporting new ideal coordinates." pickle.dump(coords, f, protocol=2) DENSITY.plot_field(SHAPE=UNIQUE_SHAPE) grad_ideal = grad_check1 avg_ideal = H_avg1 coords = COORDS.del_N(N=n_stations, inputs=coords) paths = COORDS.del_N(N=n_stations, inputs=paths) paths = list(paths) counter += 1 t1 = datetime.datetime.now() print "That loop took: ", t1 - t0