def Make_Map(green_data, zips):
sizes = []
for tup in green_data.values():
sizes.append(tup[0])
max_size = max(sizes)
colors = []
for tup in green_data.values():
colors.append(tup[1])
max_color = max(colors)
for element in green_data.keys():
if element in zips.keys():
#create the data to make a dot for
data = {'zip':zips[element][0], 'lat': [(zips[element][1])], 'lon': [(zips[element][2])], \
'color': [int(255*(green_data[element][1]/max_color)), 255, int(255*(green_data[element][1]/max_color))], \
'size':50*(int(green_data[element][0])/max_size)}
#add the dot for the zipcode
geoplotlib.add_layer(dd(data, data['color'], data['size'], f_tooltip=None))
#add labels for zipcode
geoplotlib.labels(data, 'zip' , color='k', font_name= 'helvetica', \
font_size=8, anchor_x='left', anchor_y='top')
geoplotlib.show()
def visualize(recs):
'''
Takes the direct output from calculation, maps the 3 recommendations
based on their cuisine locations
'''
if recs != []:
rv = []
for idx, tup in enumerate(recs):
lat, lon = tup[1]['coordinates']
rv.append(["#" + str(idx + 1) + ". " + tup[1]['name'] + \
" (" + tup[1]['cuisine'] + ")", lat, lon])
header = ['name', 'lat', 'lon']
with open("form/static_files/img/visualization.csv", "w") as csvfile:
writer = csv.writer(csvfile)
writer.writerow([h for h in header])
writer.writerows(rv)
data = geoplotlib.utils.read_csv(
"form/static_files/img/visualization.csv")
geoplotlib.dot(data)
geoplotlib.labels(data, 'name', color=[0, 0, 255, 255], font_size=10, \
anchor_x='center')
geoplotlib.savefig("form/static_files/img/visualization")
import geoplotlib
from geoplotlib.colors import colorbrewer
from geoplotlib.utils import epoch_to_str, BoundingBox, read_csv
data = read_csv('./data/metro.csv')
geoplotlib.dot(data, 'r')
geoplotlib.labels(data,
'name',
color=[0, 0, 255, 255],
font_size=10,
anchor_x='center')
geoplotlib.set_bbox(BoundingBox.KBH)
geoplotlib.show()
import geoplotlib
from geoplotlib.colors import colorbrewer
from geoplotlib.utils import epoch_to_str, BoundingBox, read_csv
data = read_csv('./data/metro.csv')
geoplotlib.dot(data, 'r')
geoplotlib.labels(data, 'name', color=[0,0,255,255], font_size=10, anchor_x='center')
geoplotlib.set_bbox(BoundingBox.KBH)
geoplotlib.show()
f = open("VLOCs.csv", "w+")
f.close()
#write csv to be read by geoplotlib
with open('VLOCs.csv', mode='w', newline='') as VLOCs:
VLOCs = csv.writer(VLOCs, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
VLOCs.writerow(['name', 'S_lat', 'S_lon', 'D_lat', 'D_lon'])
for station in Locations:
VLOCs.writerow([station[0], station[1], station[2], station[3], station[4]])
#empty SLOCs.csv
f = open("SLOCs.csv", "w+")
f.close()
#write csv to be read by geoplotlib
with open('SLOCs.csv', mode='w', newline='') as SLOCs:
SLOCs = csv.writer(SLOCs, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
SLOCs.writerow(['name', 'lat', 'lon'])
for station in Locations:
SLOCs.writerow([station[0], station[1], station[2]])
#plot stations
Plotdata1 = read_csv('VLOCs.csv')
Plotdata2 = read_csv('SLOCs.csv')
gp.set_bbox(BoundingBox(north=9, west=110, south=1, east=95))
gp.graph(Plotdata1, 'S_lat', 'S_lon', 'D_lat', 'D_lon', linewidth=2, color='Blues')
gp.dot(Plotdata2, color='blue', point_size=3)
gp.labels(Plotdata2, 'name', color='black', font_size=8, anchor_x='center')
gp.tiles_provider('positron')
gp.show()