def get_clean_links(nodes=None, delaytype = 'Polynomial', parameters = matrix([0.0, 0.0, 0.0, 0.15])):
links = np.genfromtxt('Data/Network/CSV/LA_big_box_arterials/links_qgis_cap.csv', delimiter = ',', skiprows = 1)
tmp = links
links = []
speed_limit_freeway = 33.33 #unit: m/s
dict_cap2speed ={600:12.5, 1000:16.67, 2000:16.67, 4000:16.67, 5000:16.67, 1500:16.67, 3000:22.22, 6000:22.22, 9000:22.22, 4500:22.22, 7500:22.22, 10500:22.22}
if delaytype=='None':
for startnode, endnode, category in tmp:
arc = distance_on_unit_sphere(nodes[startnode-1][2], nodes[startnode-1][1], nodes[endnode-1][2], nodes[endnode-1][1])
if category == 1: ffdelay = arc/speed_limit_freeway
if category == 2: ffdelay = arc/16.67
if category !=0: links.append((startnode, endnode, 1, ffdelay, None))
if delaytype=='Polynomial':
theta = parameters
degree = len(theta)
for startnode, endnode, category, cap in tmp:
arc = distance_on_unit_sphere(nodes[startnode-1][1], nodes[startnode-1][0], nodes[endnode-1][1], nodes[endnode-1][0])
if category == 1: ffdelay, slope = arc/speed_limit_freeway, 1/cap
if category == 2:
if dict_cap2speed.has_key(cap):
ffdelay, slope = arc/dict_cap2speed[cap], 1/cap
else : ffdelay, slope = arc/16.67, 1/cap
coef = [ffdelay*a*b for a,b in zip(theta, np.power(slope, range(1,degree+1)))]
links.append((startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
return links
def get_clean_links(nodes=None,
delaytype='Polynomial',
parameters=matrix([0.0, 0.0, 0.0, 0.15])):
links = np.genfromtxt(
'Data/Network/CSV/LA_big_box_arterials/links_qgis_cap.csv',
delimiter=',',
skiprows=1)
tmp = links
links = []
speed_limit_freeway = 33.33 #unit: m/s
dict_cap2speed = {
600: 12.5,
1000: 16.67,
2000: 16.67,
4000: 16.67,
5000: 16.67,
1500: 16.67,
3000: 22.22,
6000: 22.22,
9000: 22.22,
4500: 22.22,
7500: 22.22,
10500: 22.22
}
if delaytype == 'None':
for startnode, endnode, category in tmp:
arc = distance_on_unit_sphere(nodes[startnode - 1][2],
nodes[startnode - 1][1],
nodes[endnode - 1][2],
nodes[endnode - 1][1])
if category == 1: ffdelay = arc / speed_limit_freeway
if category == 2: ffdelay = arc / 16.67
if category != 0:
links.append((startnode, endnode, 1, ffdelay, None))
if delaytype == 'Polynomial':
theta = parameters
degree = len(theta)
for startnode, endnode, category, cap in tmp:
arc = distance_on_unit_sphere(nodes[startnode - 1][1],
nodes[startnode - 1][0],
nodes[endnode - 1][1],
nodes[endnode - 1][0])
if category == 1:
ffdelay, slope = arc / speed_limit_freeway, 1 / cap
if category == 2:
if dict_cap2speed.has_key(cap):
ffdelay, slope = arc / dict_cap2speed[cap], 1 / cap
else:
ffdelay, slope = arc / 16.67, 1 / cap
coef = [
ffdelay * a * b
for a, b in zip(theta, np.power(slope, range(1, degree + 1)))
]
links.append(
(startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
return links
def los_angeles_2(parameters=None, delaytype='None'):
"""Generate larger map of L.A. with 664 links and 194 nodes
"""
nodes = np.genfromtxt('LA_medium_data/nodes_LA_toy.csv', delimiter = ',', skip_header = 1)
nodes = nodes[:,1:3]
links = np.genfromtxt('LA_medium_data/links_qgis_cap.csv', delimiter = ',', skip_header = 1)
tmp = links
links = []
speed_limit_freeway = 33.33 #unit: m/s
dict_cap2speed ={600:12.5, 1000:16.67, 2000:16.67, 4000:16.67, 5000:16.67, 1500:16.67, 3000:22.22, 6000:22.22, 9000:22.22, 4500:22.22, 7500:22.22, 10500:22.22}
if delaytype=='None':
for startnode, endnode, category in tmp:
arc = distance_on_unit_sphere(nodes[startnode-1][2], nodes[startnode-1][1], nodes[endnode-1][2], nodes[endnode-1][1])
if category == 1: ffdelay = arc/speed_limit_freeway
if category == 2: ffdelay = arc/16.67
if category !=0: links.append((startnode, endnode, 1, ffdelay, None))
if delaytype=='Polynomial':
theta = parameters
degree = len(theta)
for startnode, endnode, category, cap in tmp:
arc = distance_on_unit_sphere(nodes[startnode-1][1], nodes[startnode-1][0], nodes[endnode-1][1], nodes[endnode-1][0])
if category == 1: ffdelay, slope = arc/speed_limit_freeway, 1/cap
if category == 2:
if dict_cap2speed.has_key(cap):
ffdelay, slope = arc/dict_cap2speed[cap], 1/cap
else : ffdelay, slope = arc/16.67, 1/cap
coef = [ffdelay*a*b for a,b in zip(theta, np.power(slope, range(1,degree+1)))]
links.append((startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
dest1 = 50
dest2 = 100
ODs=[]
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 10, 10, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 20, nodes, 6000.0)
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 2, 30, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 40, nodes, 6000.0)
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 2, 50, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 60, nodes, 6000.0)
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 2, 70, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 80, nodes, 6000.0)
#ODs = [[ 57. , 50. , 4. ],[ 20. , 162. , 56.4]]
ODs = Create_ODs_nodes_unique(nodes)
ODs = ODs[1:5]
print ODs
return g.create_graph_from_list(nodes, links, delaytype, ODs, 'Larger map of L.A.')
def notify_fb_friends(self, oauth_token, trip):
graph = GraphAPI(oauth_token)
profile = graph.get_object("me")
friends = graph.get_connections("me", "friends")
friend_list = [friend['id'] for friend in friends['data']]
pton_in_friends = User.query.filter(User.fbid.in_(friend_list)).all()
for friend in pton_in_friends:
# i bet this won't scale
trips = Trip.query.filter_by(user_id=friend.id)
for friend_trip in trips:
if friend_trip.start_date < trip.end_date and \
friend_trip.end_date > trip.start_date:
d = distance_on_unit_sphere(
trip.location_lat, trip.location_long,
friend_trip.location_lat, friend_trip.location_long)
max_dist_in_miles = 50
if d <= max_dist_in_miles:
send_notif(
to_user_firstname=friend.first_name,
friend_fullname="%s %s" % (self.first_name, self.last_name),
friend_loc=trip.location_name,
startdate=trip.start_date,
enddate=trip.end_date,
to_email=friend.email)
"""
def dist_to_I210box(lat, lng, box = [34.124918, 34.1718, -118.1224, -118.02524]):
if lat > box[1]:
if lng < box[2]: return distance_on_unit_sphere(lat, lng, box[1], box[2])
if lng > box[3]: return distance_on_unit_sphere(lat, lng, box[1], box[3])
else : return distance_on_unit_sphere(lat, lng, box[1], lng)
if lat < box[0]:
if lng < box[2]: return distance_on_unit_sphere(lat, lng, box[0], box[2])
if lng > box[3]: return distance_on_unit_sphere(lat, lng, box[0], box[3])
else : return distance_on_unit_sphere(lat, lng, box[0], lng)
elif lng < box[2]: return distance_on_unit_sphere(lat, lng, lat, box[2])
elif lng > box[3]: return distance_on_unit_sphere(lat, lng, lat, box[3])
else : return 0
def get_json_list(self, _filter, get_data=False):
data = []
feeds = self.objects.filter(likes__gte=_filter['likes'])
for feed in feeds:
if distance_on_unit_sphere(
feed.latitude,
feed.longitude,
_filter['latitude'],
_filter['longitude']
) < _filter['_range'] and feed.reply_set.count() >= _filter['num_reply']:
data.append(feed.get_json(get_data=True))
if get_data:
return data
return json.dumps(data)
def test_LA(datapath='', parameters=None, delaytype='None'):
nodes = np.genfromtxt(datapath+'Data/Network/CSV/test_LA/test_nodes.csv', delimiter = ',', skip_header = 1)
nodes = nodes[:,1:3]
#link_data = np.genfromtxt('Data/Network/CSV/test_LA/test_links.csv', delimiter = ',', skip_header = 1)
link_data = np.genfromtxt(datapath+'Data/Network/CSV/test_LA/test_links_C.csv', delimiter = ',', skip_header=1)
if delaytype=='None':
links = []
speed_limit_freeway = 30.00 #unit: m/s
dict_cap2speed ={600:12.5, 1000:16.67, 2000:16.67, 4000:16.67, 5000:16.67, 1500:16.67, 3000:22.22, 6000:22.22, 9000:22.22, 4500:22.22, 7500:22.22, 10500:22.22}
for startnode, endnode, category in link_data:
arc = distance_on_unit_sphere(nodes[startnode-1][2], nodes[startnode-1][1], nodes[endnode-1][2], nodes[endnode-1][1])
if category == 1: ffdelay = arc/speed_limit_freeway
if category == 2: ffdelay = arc/16.67
if category !=0: links.append((startnode, endnode, 1, ffdelay, None))
if delaytype=='Polynomial':
#theta = parameters
#degree = len(theta)
#for startnode, endnode, category, cap in tmp:
#arc = distance_on_unit_sphere(nodes[startnode-1][1], nodes[startnode-1][0], nodes[endnode-1][1], nodes[endnode-1][0])
#if category == 1: ffdelay, slope = arc/speed_limit_freeway, 1./cap
#if category == 2:
#if dict_cap2speed.has_key(cap):
#ffdelay, slope = arc/dict_cap2speed[cap], 1./cap
#else : ffdelay, slope = arc/16.67, 1./cap
#coef = [ffdelay*a*b for a,b in zip(theta, np.power(slope, range(1,degree+1)))]
#links.append((startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
theta = parameters
degree = len(theta)
links=[]
for link_entry in link_data:
startnode = int(link_entry[1])
endnode = int(link_entry[2])
length = link_entry[3]
cap = link_entry[5]
freespeed = link_entry[6]
ff_d=length/freespeed
#change a capacity (slop=1) to simulate an accident
#slope= 2000 / cap
slope= 1. / cap
coef = [ff_d*a*b for a,b in zip(theta, np.power(slope, range(1,degree+1)))]
links.append((startnode, endnode, 1, ff_d, (ff_d, slope, coef), cap, length,freespeed))
ODs = Create_ODs_nodes_unique(nodes, datapath)
#ODs = ODs[1:5]
#print ODs
return g.create_graph_from_list(nodes, links, delaytype, ODs, 'test L.A.')
def filter_ODs_whithin_I210_box(ODs_list, nodes_list):
nodes = nodes_list
temp = ODs_list
ODs_sorted = []
for od in temp:
startnode = nodes[od[0]-1]
endnode = nodes[od[1]-1]
ODs_sorted.append([od[0], od[1], od[2], distance_on_unit_sphere(nodes[od[0]-1][1], nodes[od[0]-1][0], nodes[od[1]-1][1], nodes[od[1]-1][0]), Is_in_I210box(startnode[1], startnode[0], 'medium'), Is_in_I210box(endnode[1], endnode[0], 'medium')])
ODs_sorted = np.asarray(ODs_sorted)
print ODs_sorted[0:20]
temp = ODs_sorted
ODs_sorted = []
for od in temp:
if od[4]+od[5]>1 : ODs_sorted.append(od[0:4])
return np.asarray(ODs_sorted)
def Get_links_from_csv(Nodes):
data = np.genfromtxt('Data/links_qgis.csv', delimiter = ',', skiprows=1)
Links_table=[]
theta = matrix([0.0, 0.0, 0.0, 0.15])
degree=len(theta)
for i in range(len(data)):
startnode, endnode, type= int(data[i][0]), int(data[i][1]), data[i][2]
length = distance_on_unit_sphere(Nodes[startnode-1][2], Nodes[startnode-1][1], Nodes[endnode-1][2], Nodes[endnode-1][1])
if type==1:
ffdelay=length / 32
slope = 0.2
else: ffdelay, slope = length / 17, 0.75
coef = [ffdelay*a*b for a,b in zip(theta, np.power(slope, range(1,degree+1)))]
Links_table.append((startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
return Links_table
def getAverageStopCloseness(self, refdata):
all_data = self.getList()
value = 0
stopPoints = self.getStopPlace()
num_stop = len(stopPoints)
for point in all_data:
latitude = point.getLatitude()
longtitude = point.getLongtitude()
closeness = 10000000
if point.getPointNumber() in stopPoints:
for stop in refdata.getStopList():
temp_close = distance_on_unit_sphere(stop.getLatitude(), stop.getLongtitude(), latitude, longtitude)
if temp_close < closeness:
closeness = temp_close
value = value + closeness
value = value / num_stop
return value
def dist_to_I210box(lat, lng, box=[34.124918, 34.1718, -118.1224, -118.02524]):
if lat > box[1]:
if lng < box[2]:
return distance_on_unit_sphere(lat, lng, box[1], box[2])
if lng > box[3]:
return distance_on_unit_sphere(lat, lng, box[1], box[3])
else:
return distance_on_unit_sphere(lat, lng, box[1], lng)
if lat < box[0]:
if lng < box[2]:
return distance_on_unit_sphere(lat, lng, box[0], box[2])
if lng > box[3]:
return distance_on_unit_sphere(lat, lng, box[0], box[3])
else:
return distance_on_unit_sphere(lat, lng, box[0], lng)
elif lng < box[2]:
return distance_on_unit_sphere(lat, lng, lat, box[2])
elif lng > box[3]:
return distance_on_unit_sphere(lat, lng, lat, box[3])
else:
return 0
def filter_ODs_whithin_I210_box(ODs_list, nodes_list):
nodes = nodes_list
temp = ODs_list
ODs_sorted = []
for od in temp:
startnode = nodes[od[0] - 1]
endnode = nodes[od[1] - 1]
ODs_sorted.append([
od[0], od[1], od[2],
distance_on_unit_sphere(nodes[od[0] - 1][1], nodes[od[0] - 1][0],
nodes[od[1] - 1][1], nodes[od[1] - 1][0]),
Is_in_I210box(startnode[1], startnode[0], 'medium'),
Is_in_I210box(endnode[1], endnode[0], 'medium')
])
ODs_sorted = np.asarray(ODs_sorted)
print ODs_sorted[0:20]
temp = ODs_sorted
ODs_sorted = []
for od in temp:
if od[4] + od[5] > 1: ODs_sorted.append(od[0:4])
return np.asarray(ODs_sorted)
def Get_links_from_csv(Nodes):
data = np.genfromtxt('Data/links_qgis.csv', delimiter=',', skiprows=1)
Links_table = []
theta = matrix([0.0, 0.0, 0.0, 0.15])
degree = len(theta)
for i in range(len(data)):
startnode, endnode, type = int(data[i][0]), int(data[i][1]), data[i][2]
length = distance_on_unit_sphere(Nodes[startnode - 1][2],
Nodes[startnode - 1][1],
Nodes[endnode - 1][2],
Nodes[endnode - 1][1])
if type == 1:
ffdelay = length / 32
slope = 0.2
else:
ffdelay, slope = length / 17, 0.75
coef = [
ffdelay * a * b
for a, b in zip(theta, np.power(slope, range(1, degree + 1)))
]
Links_table.append(
(startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
return Links_table
def LA_county(datapath='', parameters=None, delaytype='None', cur_gis=None):
nodes = np.genfromtxt(datapath+'Data/Network/CSV/LA_county/nodes.csv', delimiter = ',', skip_header = 1)
nodes = nodes[:,:2]
link_data = np.genfromtxt('Data/Network/CSV/LA_county/links.csv', delimiter = ',', skip_header = 1)
link_data = np.hstack((link_data[:,[-1]], link_data[:,:-1]))
if delaytype=='None':
links = []
speed_limit_freeway = 30.00 #unit: m/s
dict_cap2speed ={600:12.5, 1000:16.67, 2000:16.67, 4000:16.67, 5000:16.67, 1500:16.67, 3000:22.22, 6000:22.22, 9000:22.22, 4500:22.22, 7500:22.22, 10500:22.22}
for startnode, endnode, category in link_data:
arc = distance_on_unit_sphere(nodes[startnode-1][2], nodes[startnode-1][1], nodes[endnode-1][2], nodes[endnode-1][1])
if category == 1: ffdelay = arc/speed_limit_freeway
if category == 2: ffdelay = arc/16.67
if category !=0: links.append((startnode, endnode, 1, ffdelay, None))
if delaytype=='Polynomial':
theta = parameters
degree = len(theta)
links=[]
for link_entry in link_data:
startnode = int(link_entry[1])
endnode = int(link_entry[2])
length = link_entry[3]
cap = link_entry[5]
freespeed = link_entry[6]
ff_d=length/freespeed
#change a capacity (slop=1) to simulate an accident
#slope= 2000 / cap
slope= 1. / cap
coef = [ff_d*a*b for a,b in zip(theta, np.power(slope, range(1,degree+1)))]
links.append((startnode, endnode, 1, ff_d, (ff_d, slope, coef), cap, length,freespeed))
ODs = Create_ODs_nodes_unique(nodes, datapath, cur_gis)
#ODs = ODs[ODs[:,-1]>np.sum(ODs[:,-1])/1000.,:]
return g.create_graph_from_list(nodes, links, delaytype, ODs, 'LA county')
def test6():
"""Test distance_on_unit_sphere()"""
arc = util.distance_on_unit_sphere(34.049240, -118.238456, 34.073238, -118.284118)
print 'distance in miles', 3960.0*arc
print 'distance in km', 6373.0*arc
def __init__(self):
Gtk.ApplicationWindow.__init__(self)
self.set_title('GeoCaching Details')
self.set_default_size(400, 650)
self.set_icon_from_file(ICON_FILE)
mycache = json.loads(util.get_json_row(cacheid))
header = Gtk.HeaderBar(title=mycache['cachename'])
header.set_show_close_button(False)
self.set_titlebar(header)
button = Gtk.MenuButton()
header.pack_end(button)
menumodel = Gio.Menu()
menumodel.append("Log Visit", "win.log_visit")
menumodel.append("Open in Browser", "win.browser")
# menumodel.append("Quit", "win.quit")
button.set_menu_model(menumodel)
log_visit_action = Gio.SimpleAction.new("log_visit", None)
log_visit_action.connect("activate", self.log_visit_callback)
self.add_action(log_visit_action)
browser_action = Gio.SimpleAction.new("browser", None)
browser_action.connect("activate", self.browser_callback)
self.add_action(browser_action)
button = Gtk.Button(label="<")
button.connect("clicked", self.on_button_clicked)
header.pack_start(button)
grid1 = Gtk.Grid()
row = 0
mystr = "<big><b>" + mycache['cachename'] + "</b></big>"
row = self.add_grid_row("Cache Name:", mystr, grid1, row)
mystr = "<big>" + mycache['cachetype'] + "</big>"
row = self.add_grid_row("Cache Type:", mystr, grid1, row)
mystr = "<big>" + mycache['cachesize'] + "</big>"
row = self.add_grid_row("Cache Size:", mystr, grid1, row)
mystr = "<big>" + mycache['cacheid'] + "</big>"
row = self.add_grid_row("Cache ID:", mystr, grid1, row)
fwd_az = util.get_azimuth(lat, lon, mycache['lat'], mycache['lon'])
dist = util.distance_on_unit_sphere(lat, lon, mycache['lat'],
mycache['lon'])
mystr = "<big>" + str(int(round(dist * 1000, 0))) + "m @ " + \
str(int(round(fwd_az, 0))) + "°</big>"
row = self.add_grid_row("Distance:", mystr, grid1, row)
mystr = "<big>" + str(float(mycache['diff'])) + "/5.0</big>"
row = self.add_grid_row("Difficulty:", mystr, grid1, row)
mystr = "<big>" + str(float(mycache['terr'])) + "/5.0</big>"
row = self.add_grid_row("Terrain:", mystr, grid1, row)
mystr = "<big>" + mycache['cacheowner'] + "</big>"
row = self.add_grid_row("Owner:", mystr, grid1, row)
mystr = time.strftime('%d %b %Y', time.localtime(mycache['hidden']))
row = self.add_grid_row("Hidden:", mystr, grid1, row)
date = time.strftime('%d %b %Y', time.localtime(mycache['lastfound']))
mystr = "<big>" + date + "</big>"
row = self.add_grid_row("Last Found:", mystr, grid1, row)
mystr = util.from_decimal(mycache['lat'], 'lat') + " - " + \
util.from_decimal(mycache['lon'], 'lon')
row = self.add_grid_row("Cache Location:", mystr, grid1, row)
row = self.show_icons(grid1, row)
label = Gtk.Label()
label.set_halign(Gtk.Align.START)
label.set_hexpand(True)
agetext = util.stored_age(mycache['dltime'])
label.set_markup("Stored in Device: " + agetext)
grid1.attach(label, 0, row, 2, 1)
row += 1
logdesc = "<html><body>"
logdesc += mycache['short'] + mycache['body'] + "<br/>\n<br/>\n"
if mycache['hint'] != "":
logdesc += "<b><big>Hint:</big></b><br/>\n"
logdesc += "<div id='enc_hint' onClick='update()'>" + mycache[
'hint'] + "</div>"
logdesc += "<div id='dec_hint' onClick='update()' style='display:none'>"
logdesc += codecs.encode(mycache['hint'], 'rot_13') + "</div>"
logdesc += "<br/><br/>"
logdesc += """
<script type="text/javascript">
function update()
{
if(document.getElementById('enc_hint').style.display == '')
{
document.getElementById('enc_hint').style.display = 'none';
document.getElementById('dec_hint').style.display = '';
} else {
document.getElementById('enc_hint').style.display = '';
document.getElementById('dec_hint').style.display = 'none';
}
}
</script>
"""
logdesc += "</body></html>"
base_uri = "file:///"
webkit1 = WebKit2.WebView()
webkit1.load_html(logdesc, base_uri)
logs = util.get_html_logs(cacheid)
# print(logs)
self.webkit = WebKit2.WebView()
self.webkit.load_html(logs, base_uri)
self.notebook = Gtk.Notebook()
self.notebook.set_scrollable(True)
self.dlabel = Gtk.Label(label="Details")
self.desclabel = Gtk.Label(label="Description")
self.lblabel = Gtk.Label(label="Logbook")
self.notebook.append_page(grid1, self.dlabel)
self.notebook.append_page(webkit1, self.desclabel)
self.notebook.append_page(self.webkit, self.lblabel)
self.add(self.notebook)
dict_unique[(od[0], od[1])] += od[2]/5. #We divide by 5 because peak hour lasts 5 hours
else : dict_unique[(od[0], od[1])] = od[2]/5.
for od, value in dict_unique.iteritems():
ODs_unique.append([od[0], od[1], value])
return ODs_unique
if __name__ == "__main__":
nodes = np.genfromtxt('Data/Network/CSV/LA_big_box_arterials/nodes_LA_toy.csv', delimiter = ',', skiprows = 1)
nodes = nodes[:,1:3]
ODs = Create_ODs_nodes_unique(nodes)
def Get_key(item):
return item[2]
M = m.Manips()
ODs_sorted = np.asarray(sorted(ODs, key = Get_key))
temp = ODs_sorted
ODs_sorted = []
for od in temp:
startnode = nodes[od[0]-1]
endnode = nodes[od[1]-1]
ODs_sorted.append([od[0], od[1], od[2], distance_on_unit_sphere(nodes[od[0]-1][1], nodes[od[0]-1][0], nodes[od[1]-1][1], nodes[od[1]-1][0]), m.Is_in_I210box(startnode[1], startnode[0], 'medium'), m.Is_in_I210box(endnode[1], endnode[0], 'medium')])
ODs_sorted = np.asarray(ODs_sorted)
temp = ODs_sorted
ODs_sorted = []
for od in temp:
if od[4]+od[5]>1 : ODs_sorted.append(od[0:4])
ODs_sorted = np.asarray(ODs_sorted)
def test6():
"""Test distance_on_unit_sphere()"""
arc = util.distance_on_unit_sphere(34.049240, -118.238456, 34.073238,
-118.284118)
print 'distance in miles', 3960.0 * arc
print 'distance in km', 6373.0 * arc
def los_angeles_2(parameters=None, delaytype='None'):
"""Generate larger map of L.A. with 664 links and 194 nodes
"""
nodes = np.genfromtxt('LA_medium_data/nodes_LA_toy.csv',
delimiter=',',
skiprows=1)
nodes = nodes[:, 1:3]
links = np.genfromtxt('LA_medium_data/links_qgis_cap.csv',
delimiter=',',
skiprows=1)
tmp = links
links = []
speed_limit_freeway = 33.33 #unit: m/s
dict_cap2speed = {
600: 12.5,
1000: 16.67,
2000: 16.67,
4000: 16.67,
5000: 16.67,
1500: 16.67,
3000: 22.22,
6000: 22.22,
9000: 22.22,
4500: 22.22,
7500: 22.22,
10500: 22.22
}
if delaytype == 'None':
for startnode, endnode, category in tmp:
arc = distance_on_unit_sphere(nodes[startnode - 1][2],
nodes[startnode - 1][1],
nodes[endnode - 1][2],
nodes[endnode - 1][1])
if category == 1: ffdelay = arc / speed_limit_freeway
if category == 2: ffdelay = arc / 16.67
if category != 0:
links.append((startnode, endnode, 1, ffdelay, None))
if delaytype == 'Polynomial':
theta = parameters
degree = len(theta)
for startnode, endnode, category, cap in tmp:
arc = distance_on_unit_sphere(nodes[startnode - 1][1],
nodes[startnode - 1][0],
nodes[endnode - 1][1],
nodes[endnode - 1][0])
if category == 1:
ffdelay, slope = arc / speed_limit_freeway, 1 / cap
if category == 2:
if dict_cap2speed.has_key(cap):
ffdelay, slope = arc / dict_cap2speed[cap], 1 / cap
else:
ffdelay, slope = arc / 16.67, 1 / cap
coef = [
ffdelay * a * b
for a, b in zip(theta, np.power(slope, range(1, degree + 1)))
]
links.append(
(startnode, endnode, 1, ffdelay, (ffdelay, slope, coef)))
dest1 = 50
dest2 = 100
ODs = []
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 10, 10, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 20, nodes, 6000.0)
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 2, 30, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 40, nodes, 6000.0)
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 2, 50, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 60, nodes, 6000.0)
#ODs+=create_linear_ODs(34.044801, -117.831116, 33.955998, -118.309021, 2, 70, nodes, 6000.0)
#ODs+=create_linear_ODs(34.162493, -118.301468, 34.106226, -117.903214, 2, 80, nodes, 6000.0)
#ODs = [[ 57. , 50. , 4. ],[ 20. , 162. , 56.4]]
ODs = Create_ODs_nodes_unique(nodes)
ODs = ODs[1:5]
print ODs
return g.create_graph_from_list(nodes, links, delaytype, ODs,
'Larger map of L.A.')
def Dist_between_TAZ(self, tazi, tazj):
return distance_on_unit_sphere(self.List_TAZ[self.dict_TAZ[tazi]][1], self.List_TAZ[self.dict_TAZ[tazi]][2], self.List_TAZ[self.dict_TAZ[tazj]][1], self.List_TAZ[self.dict_TAZ[tazj]][2])
def Dist_between_TAZ(self, tazi, tazj):
return distance_on_unit_sphere(self.List_TAZ[self.dict_TAZ[tazi]][1],
self.List_TAZ[self.dict_TAZ[tazi]][2],
self.List_TAZ[self.dict_TAZ[tazj]][1],
self.List_TAZ[self.dict_TAZ[tazj]][2])
