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
