/
app.py
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/
app.py
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import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from plotly import graph_objs as go
import pandas as pd
import numpy as np
mapbox_access_token = 'pk.eyJ1IjoiamFja2x1byIsImEiOiJjajNlcnh3MzEwMHZtMzNueGw3NWw5ZXF5In0.fk8k06T96Ml9CLGgKmk81w'
##################################################
trd = pd.read_csv('./data/UNI_TRD_ENF17.csv')
conj_name = {
15615: 'Boa Aventura',
16070: 'Nova Friburgo',
16068: 'Campo do Coelho',
15616: 'Vale dos Peoes',
16069: 'Conselheiro Paulino'
}
trd['CONJ_N'] = trd.CONJ.copy()
for i,c in enumerate(trd.CONJ_N.unique()):
trd.CONJ_N.replace(c,i,inplace=True)
map_layout = go.Layout(
mapbox= go.layout.Mapbox(
accesstoken= mapbox_access_token,
center= dict(lat=trd.lat[0], lon=trd.lon[0]),
zoom=10,
pitch=45,
style='light'),
margin= dict(l=0,t=0,b=0,r=0)
)
FIC_dist_layout = go.Layout(
title= 'Distribucion Frecuencia de Cortes',
height= 300,
margin= dict(l=30,t=50,b=30,r=30),
barmode='overlay',
legend_orientation='h'
)
DIC_dist_layout = go.Layout(
title= 'Distribucion Duracion de Cortes',
height= 300,
margin= dict(l=30,t=50,b=30,r=30),
barmode='overlay',
legend_orientation='h'
)
ENE_dist_layout = go.Layout(
title= 'Distribucion Consumo',
height= 300,
margin= dict(l=30,t=50,b=30,r=30),
barmode='overlay',
legend_orientation='h'
)
app = dash.Dash(__name__)
server = app.server
###################################################
# Layout
###################################################
app.layout = html.Div([
html.Div([
html.H2(" Mapa de distribucion Electrica")
], style={'text-align': 'center'}),
html.Div([
html.Div([
html.H6("Seleccione Regiones"),
dcc.Dropdown(
id= 'dd_region',
multi= True,
placeholder= 'Regiones',
options= [dict(label=conj_name[x], value=x) for x in trd.CONJ.unique()],
value= list(trd.CONJ.unique()))
], className= 'pretty_container four columns'),
html.Div([
html.H6("Codificacion color"),
dcc.RadioItems(
id= 'ra_color',
options= [
dict(label='Frecuencia de Cortes', value='FIC'),
dict(label='Duracion Media de Cortes', value='DIC'),
dict(label='Grupo Electrico', value='CONJ_N')],
value= 'FIC'
)
], className= 'pretty_container four columns'),
html.Div([
html.H6("Codificacion tamaño"),
dcc.RadioItems(
id= 'ra_size',
options= [
dict(label='No Codificar', value='FIX_SIZE'),
dict(label='Duracion Media de Cortes', value='DIC'),
dict(label='Consumo Total', value='ENE_12')],
value= 'FIX_SIZE'
)
], className= 'pretty_container four columns')
], className='row'),
html.Div([
html.Div([
dcc.Graph(id = 'map')
], className= 'pretty_container eight columns'),
html.Div(id='map_side_div', children=[], className= 'pretty_container four columns')
], className='row'),
html.Div([
html.H6(" Seleccione un area del mapa para comparar distribuciones")
]),
html.Div([
html.Div([
dcc.Graph(id='FIC_dist')
], className= 'pretty_container four columns'),
html.Div([
dcc.Graph(id='DIC_dist')
], className= 'pretty_container four columns'),
html.Div([
dcc.Graph(id='ENE_dist')
], className= 'pretty_container four columns')
], className='row'),
], className= 'mainContainer')
###################################################
# CallBacks
###################################################
@app.callback(
[Output(component_id='map', component_property='figure'),
Output('map_side_div', 'children')],
[Input('dd_region', 'value'),
Input('ra_color', 'value'),
Input('ra_size', 'value')],
[State("map", "relayoutData")]
)
def update_map(region, color_var, size_var, map_layout_data):
print(region, color_var, size_var)
if region:
trd_selection = trd[trd.CONJ.isin(region)]
color_norm = trd_selection[color_var].clip(0, trd_selection[color_var].quantile(0.9))
if size_var == 'FIX_SIZE':
size_norm = 10
trd_selection['FIX_SIZE'] = trd_selection[color_var]
else:
trd_max = trd_selection[size_var].quantile(0.95)
size_norm = np.log1p(trd_selection[size_var]/trd_max)*30
size_norm.clip(6, 25, inplace=True)
info = trd_selection.FIC.map('<b>Frec Corte:</b> {:,.2f}'.format) + \
trd_selection.DIC.map('<br><b>Dur Corte:</b> {:,.2f}'.format) + \
trd_selection.ENE_12.map('<br><b>Consumo:</b> {:,.2f}'.format)
map_data = [
go.Scattermapbox(
lat= trd_selection.lat,
lon= trd_selection.lon,
text= info,
hoverinfo= 'text',
mode='markers',
marker= dict(
size = size_norm,
color = color_norm,
colorscale = 'RdBu',
showscale=True,
opacity=0.7
),
)]
side_graph = dcc.Graph(figure = go.Figure(
data=[
go.Line(x=trd_selection[color_var], y=trd_selection[size_var],
mode='markers', name='Correlacion')
],
layout= go.Layout(
title='Correlacion Entre Variables',
margin=dict(l=20, t=50, b=20, r=20),
)
)
)
if map_layout_data:
print(map_layout_data)
print(map_layout_data.keys())
if 'mapbox.center' in map_layout_data.keys():
# Lock Camera Position
cam_lat = float(map_layout_data['mapbox.center']['lat'])
cam_lon = float(map_layout_data['mapbox.center']['lon'])
cam_zoom = float(map_layout_data['mapbox.zoom'])
map_layout.mapbox.center.lat = cam_lat
map_layout.mapbox.center.lon = cam_lon
map_layout.mapbox.zoom = cam_zoom
else:
map_data = [
go.Scattermapbox(
lat= [],
lon= [],
mode='markers'
)
]
side_graph = []
return dict(data=map_data, layout=map_layout), side_graph
@app.callback(
[Output('FIC_dist','figure'),
Output('DIC_dist','figure'),
Output('ENE_dist','figure')],
[Input('map', 'selectedData')]
)
def plot_dist(selectedData):
print('seleccion:')
if selectedData:
sel_index = [x['pointIndex'] for x in selectedData['points']]
FIC_dist_data = [go.Histogram(x=trd.FIC,
nbinsx=30, histnorm='probability density', name='Total', opacity=0.75),
go.Histogram(x=trd.iloc[sel_index].FIC,
nbinsx=30, histnorm='probability density', name='Seleccion', opacity=0.75)]
DIC_dist_data = [go.Histogram(x=trd.DIC,
nbinsx=30, histnorm='probability density', name='Total', opacity=0.75),
go.Histogram(x=trd.iloc[sel_index].DIC,
nbinsx=30, histnorm='probability density', name='Seleccion', opacity=0.75)]
ENE_dist_data = [go.Histogram(x=trd.ENE_12,
nbinsx=30, histnorm='probability density', name='Total', opacity=0.75),
go.Histogram(x=trd.iloc[sel_index].ENE_12,
nbinsx=30, histnorm='probability density', name='Seleccion', opacity=0.75)]
else:
FIC_dist_data = [go.Histogram(x=trd.FIC,
nbinsx=30, histnorm='probability density', name='Total', opacity=0.75)]
DIC_dist_data = [go.Histogram(x=trd.DIC,
nbinsx=30, histnorm='probability density', name='Total', opacity=0.75)]
ENE_dist_data = [go.Histogram(x=trd.ENE_12,
nbinsx=30, histnorm='probability density', name='Total', opacity=0.75)]
return dict(data=FIC_dist_data, layout=FIC_dist_layout),\
dict(data=DIC_dist_data, layout=DIC_dist_layout),\
dict(data=ENE_dist_data, layout=ENE_dist_layout)
#####################################################
if __name__ == '__main__':
app.run_server(debug=True)