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app.py
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app.py
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# Import dependencies
import geopandas as gpd
import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_table_experiments as dt
import flask
#import networkx as nx
import numpy as np
import pandas as pd
import pickle
import plotly
#import osmnx as ox
import os
import requests
import time
#import googlemaps
import matplotlib as plt
from dash.dependencies import Input, Output, State
from shapely.geometry import LineString, Point
from warnings import filterwarnings
filterwarnings('ignore')
# Initialize dash application
app = dash.Dash()
server = app.server
app.title = 'Rutas de Evacuación'
if 'DYNO' in os.environ:
# Add Google Analytics
app.scripts.append_script({
'external_url': 'https://cdn.rawgit.com/chriddyp/ca0d8f02a1659981a0ea7f013a378bbd/raw/e79f3f789517deec58f41251f7dbb6bee72c44ab/plotly_ga.js'
})
# API keys
if 'DYNO' in os.environ:
mapbox_access_token = os.getenv('MAPBOX_API_KEY')
# gmaps = googlemaps.Client(key=os.getenv('GOOGLE_MAPS_API_KEY'))
else:
from mykeys import MAPBOX_API_KEY, GOOGLE_MAPS_API_KEY
mapbox_access_token = MAPBOX_API_KEY
# gmaps = googlemaps.Client(key=GOOGLE_MAPS_API_KEY)
# Coordinate system
proj_utm = {'datum': 'WGS84', 'ellps': 'WGS84', 'proj': 'utm', 'zone': 18, 'units': 'm'}
#colormapping
def fadeColor(c1,c2,mix=0): #fade (linear interpolate) from color c1 (at mix=0) to c2 (mix=1)
assert len(c1)==len(c2)
assert mix>=0 and mix<=1, 'mix='+str(mix)
rgb1=np.array([int(c1[ii:ii+2],16) for ii in range(1,len(c1),2)])
rgb2=np.array([int(c2[ii:ii+2],16) for ii in range(1,len(c2),2)])
rgb=((1-mix)*rgb1+mix*rgb2).astype(int)
#cOld='#'+''.join([hex(a)[2:] for a in rgb])
#print(11,[hex(a)[2:].zfill(2) for a in rgb])
c='#'+('{:}'*3).format(*[hex(a)[2:].zfill(2) for a in rgb])
#print(rgb1, rgb2, rgb, cOld, c)
return c
# Datasets
map_data = pd.read_csv('./data/merge/POIsWithFIS.csv', index_col=0)
map_data["color"] = map_data.apply(lambda x: '#4682B4' if x['TYPE'] == "Colegio" else fadeColor('#2ca02c','#ff0000',x['fis_score']), axis=1)
map_data = gpd.GeoDataFrame(
data=map_data,
crs={'init': 'epsg:4326'},
geometry=[Point(xy) for xy in zip(map_data['C_LONG'], map_data['C_LAT'])]
)
#map_data = map_data.to_crs(proj_utm)
print("Loading graph")
init = time.time()
#graph = pickle.load(open("data/input/lima_graph_proj.pk","rb"))
wait = time.time() - init
print("graph loaded in", wait)
print("Loading nodes")
init = time.time()
#nodes = ox.graph_to_gdfs(graph, nodes=True, edges=False)
wait = time.time() - init
print("nodes loaded in", wait)
print('#'*40)
#print('n_nodes:',len(nodes))
print('#'*40)
layout = dict(
font=dict(color="#edefef"),
titlefont=dict(
color="#edefef",
size='14'
),
margin=dict(
l=0,
r=0,
b=0,
t=0
),
hovermode="closest",
plot_bgcolor='#4b4b4b',
paper_bgcolor='#4b4b4b',
showlegend=False,
title='Rutas de Evacuación de Colegio a Hospitales',
images= [dict(
source= "https://image.ibb.co/eyXtYV/legend.png",
xref= "x",
yref= "y",
x= 4.7,
y= 3.85,
sizex= 1,
sizey= 1)],
mapbox=dict(
accesstoken=mapbox_access_token,
bearing=0,
style="light",
center=dict(
lon=-76.925824,
lat=-12.081203,
),
pitch=0,
zoom=10
)
)
def gen_map(map_data, route_line=None, route_labels=None, initial_map=True):
points = {
"type": "scattermapbox",
"lat": map_data['C_LAT'],
"lon": map_data['C_LONG'],
"text": map_data['NOMBRE'],
"name": map_data['NOMBRE'],
"customdata": map_data['LINK'],
"hoverinfo": "text",
"legendgroup": map_data['TYPE'],
"mode": "markers",
"marker": {
"size": 10,
"opacity": 0.5,
"color": map_data['color']
}
}
points_inner = {
"type": "scattermapbox",
"lat": map_data['C_LAT'],
"lon": map_data['C_LONG'],
"text": map_data['NOMBRE'],
"name": map_data['NOMBRE'],
"customdata": map_data['LINK'],
"hoverinfo": "text",
"legendgroup": map_data['TYPE'],
"mode": "markers",
"marker": {
"size": 5,
"opacity": 0.5,
"color": map_data['color']
}
}
if route_line != None:
route = {
"type": "scattermapbox",
"lat": [tuple_xy[0] for tuple_xy in route_line],
"lon": [tuple_xy[1] for tuple_xy in route_line],
"mode": "lines+markers",
"hoverinfo": "text",
"line": {
"width": 5,
"opacity": 0.5,
"color": 'green',
}
}
print(route_labels)
print(type(route_labels))
source_target_points = {
"type": "scattermapbox",
"lat": [route_line[i][0] for i in [0,-1]],
"lon": [route_line[i][1] for i in [0,-1]],
"text": route_labels,
"hoverinfo": "text",
"mode": "markers",
"marker": {
"size": 20,
"opacity": 0.5,
"color": []
}
}
if initial_map:
return {
"data": [points, points_inner],
"layout": layout,
}
else:
return {
"data": [points, points_inner, route, source_target_points],
"layout": layout,
}
app.layout = html.Div([
html.H1('Rutas de evacuación de colegios a hospitales', style={'font-family': 'Dosis'}),
html.P('Selecciona un colegio para ver la ruta más corta hacia el hospital asignado.', style={'font-family': 'Dosis'}),
dcc.Graph(id='map-graph', style={'height':'75vh'}),
html.P('Selecciona el medio de transporte de la ruta.'),
dcc.Dropdown(
id='route_profile',
options=[
{'label': 'En automóvil', 'value':'driving'},
{'label': 'Caminando', 'value':'walking'}
],
value='walking',
style={
'height':'5vh',
#'marginLeft':'-0.5vh',
#'marginRigth':'0vh',
#'marginTop':'2vh',
#'marginBottom':'0vh'
}
)
])
#### Obtain route from graph ####
## Helpers
def get_boundingbox(x, y, margin):
x = Point(x)
y = Point(y)
xy = gpd.GeoDataFrame(geometry=[x, y], crs=proj_utm)
xmin, ymin, xmax, ymax = xy.unary_union.bounds
xmin -= margin
ymin -= margin
xmax += margin
ymax += margin
print('bbox:', xmin, xmax, ymin, ymax)
return xmin, ymin, xmax, ymax
def get_subgraph(graph, nodes, source, target, margin):
xmin, ymin, xmax, ymax = get_boundingbox(source, target, margin=margin)
subgraph_nodes_ix = nodes.cx[xmin:xmax, ymin:ymax].index
print('n_subgraph_nodes:',len(subgraph_nodes_ix))
print("Getting subgraph")
init = time.time()
subgraph = graph.subgraph(subgraph_nodes_ix)
wait = time.time() - init
print("subgraph loaded in", wait)
return subgraph, subgraph_nodes_ix
def get_nearest_nodes(graph, source, target):
print("Getting nearest nodes")
init = time.time()
origin_node = ox.get_nearest_node(G=graph, point=(source[1],source[0]), method='euclidean')
target_node = ox.get_nearest_node(G=graph, point=(target[1], target[0]), method='euclidean')
wait = time.time() - init
print("nereast nodes loaded in", wait)
return origin_node, target_node
def get_route_data(route, nodes):
route_nodes = nodes.loc[route]
print('n_route_nodes:',len(route_nodes))
route_line = list(zip(route_nodes.lat, route_nodes.lon))
route_linestr = LineString(route_nodes.geometry.values.tolist())
route_geom = gpd.GeoDataFrame(crs=nodes.crs)
route_geom['geometry'] = None
route_geom['osmids'] = None
route_geom.loc[0,'geometry'] = route_linestr
route_geom.loc[0,'osmids'] = str(list(route_nodes['osmid'].values))
route_geom['length_m'] = route_geom.length
return route_geom, route_line
## Main function
def get_scattermap_lines(source, target):
# Filter graph to reduce time
subgraph, subgraph_nodes_ix = get_subgraph(graph, nodes, source, target, 5000)
# Get nearest nodes in the subgraph
source_node_id, target_node_id = get_nearest_nodes(subgraph, source, target)
print('#'*20,'source and target nodes')
print(source_node_id)
print(target_node_id)
print('#'*30)
# Get shortest_path (list of nodes)
print("Getting shortest path")
init = time.time()
opt_route = nx.shortest_path(G=subgraph, source=source_node_id,
target=target_node_id, weight='length')
wait = time.time() - init
print("shortest path in", wait)
print('#'*40)
print(opt_route)
print('#'*40)
# Get route data
route_df, route_line = get_route_data(opt_route, nodes)
return route_line
###################################
#### Obtain route from external API ####
def ldict2ltup(d):
#maps a list of dictionaries to a list of tuples
return (d['lat'],d['lng'])
def llist2ltup(d):
#maps a list of coordinate lists to a list of tuples
return (d[1],d[0])
def get_directions_mapbox(source, target, profile):
# Mapbox driving direction API call
source_str = "{},{}".format(source[0],source[1])
target_str = "{},{}".format(target[0],target[1])
coords = ";".join([source_str,target_str])
print(coords)
ROUTE_URL = "https://api.mapbox.com/directions/v5/mapbox/" + profile + "/" + coords + "?geometries=geojson&access_token=" + mapbox_access_token
result = requests.get(ROUTE_URL)
data = result.json()
print(data)
route_data = data["routes"][0]["geometry"]["coordinates"]
print(data.keys())
print(type(data['routes']))
print(len(data['routes']))
print(data['routes'][0]['duration'])
route_duration = round(data['routes'][0]['duration'] / 60, 2) # seconds to minutes
route_distance = round(data['routes'][0]['distance'], 2) # meters
return list(map(llist2ltup,route_data)), route_duration, route_distance
def get_directions_google(gmaps, origin, destination):
dirs = gmaps.directions(origin=origin, destination=destination)
overview_polyline = dirs[0].get('overview_polyline')
if overview_polyline is not None:
route_decoded = googlemaps.convert.decode_polyline(overview_polyline['points'])
else:
pass
return list(map(ldict2ltup,route_decoded))
########################################
# Functions to update mapscatter component
@app.callback(Output('map-graph', 'figure'),
[Input('map-graph', 'clickData'),
Input('route_profile', 'value')],
[State('map-graph', 'relayoutData')])
def _update_routes(clickData, profile, relayoutData):
if clickData == None:
print('Initial Map')
return gen_map(map_data)
else:
print('#'*30)
print(clickData)
print('#'*30)
print(relayoutData)
print('Click Event')
source_data = map_data.loc[clickData['points'][0]['pointIndex'],:]
target_data = map_data.loc[source_data['LINK'],:]
# source = tuple([source_data['C_LAT'], source_data['C_LONG']])
# target = tuple([target_data['C_LAT'], target_data['C_LONG']])
source = tuple([source_data.geometry.x, source_data.geometry.y])
target = tuple([target_data.geometry.x, target_data.geometry.y])
#route_line = get_scattermap_lines(source, target) # Obtain route from graph
#print(route_line)
#route_line = get_directions_google(gmaps, source, target) # Obtain route from google maps API
route_line, route_duration, route_distance = get_directions_mapbox(source, target, profile=profile) # Obtain route from mapbox API
route_line.insert(0, tuple([source_data['C_LAT'], source_data['C_LONG']]))
route_line.append(tuple([target_data['C_LAT'], target_data['C_LONG']]))
route_labels = [source_data['NOMBRE'], target_data['NOMBRE']]
new_map = gen_map(map_data, route_line, route_labels, initial_map=False)
print(route_duration, route_distance)
new_map['data'][3]['marker']['color'] = [source_data['color'], target_data['color']]
new_map['data'][2]['text'] = ['Duración: '+str(route_duration)+' minutos\n '+'Distancia: '+str(route_distance)+' segundos' for x in range(len(route_line))]
if relayoutData:
if 'mapbox.center' in relayoutData:
new_map['layout']['mapbox']['center'] = relayoutData['mapbox.center']
if 'mapbox.zoom' in relayoutData:
new_map['layout']['mapbox']['zoom'] = relayoutData['mapbox.zoom']
return new_map
# Boostrap CSS.
external_css = ["https://cdnjs.cloudflare.com/ajax/libs/skeleton/2.0.4/skeleton.min.css",
"https://fonts.googleapis.com/css?family=Raleway:400,300,600",
"https://fonts.googleapis.com/css?family=Dosis:Medium",
"https://cdn.rawgit.com/plotly/dash-app-stylesheets/62f0eb4f1fadbefea64b2404493079bf848974e8/dash-uber-ride-demo.css",
"https://maxcdn.bootstrapcdn.com/font-awesome/4.7.0/css/font-awesome.min.css"]
for css in external_css:
app.css.append_css({"external_url": css})
if __name__ == '__main__':
if 'DYNO' in os.environ:
app.run_server(debug=False)
else:
app.run_server(debug=True)