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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 Output, Input
import plotly.express as px
from plotly.subplots import make_subplots
import plotly.figure_factory as fac
import plotly.graph_objects as go
import dash_bootstrap_components as dbc
import pandas as pd
#import pandas_datareader.data as web
import datetime
from rosely import WindRose
import numpy as N
app = dash.Dash(__name__,
external_stylesheets=[dbc.themes.CERULEAN],
meta_tags=[{'name': 'viewport',
'content': 'width=device-width, initial-scale=1.0'}]
)
server = app.server
#set positions to plot
list_pos=[]
list_pos.append(dict(name="conquet",lon=-4.87,lat=48.33))
list_pos.append(dict(name="groix",lon=-3.4903,lat=47.59))
list_pos.append(dict(name="large",lon=-3.9819,lat=47.60))
name_list=[x["name"] for x in list_pos]
lon_list=[x["lon"] for x in list_pos]
lat_list=[x["lat"] for x in list_pos]
stat="conquet"
##########
#wind plot
##########
spd = pd.read_pickle('wind_spd.pkl')
direction=pd.read_pickle('wind_dir.pkl')
fig1 = make_subplots(specs=[[{"secondary_y": True}]])
fig1.add_trace(go.Scatter(x=spd.index,y=spd[stat],name="speed"))
fig1.add_trace(go.Scatter(x=direction.index,y=direction[stat],name="dir"),secondary_y=True)
fig1.update_layout(title=dict(text='Wind from Arome Model - %s'%(stat),x=0.5),
xaxis_title='',
yaxis_title='speed(m/s)')
test_rose=pd.DataFrame(data=dict(date=spd.index,ws=spd[stat],wd=direction[stat]))
wind=WindRose(test_rose)
wind.calc_stats(normed=True,bins=8)
fig4 = px.bar_polar(wind.wind_df, r="frequency", theta="direction",
color="speed", template="plotly_white",
color_discrete_sequence= px.colors.sequential.Plasma_r)
fig4.update_layout(title=dict(text='Wind Rose - %s'%(stat),x=0.5))
##########
#WAVE plot
##########
wave_hs = pd.read_pickle('wave_hs.pkl')
wave_dir = pd.read_pickle('wave_dir.pkl')
wave_data=pd.DataFrame(data=dict(date=wave_hs.index,ws=wave_hs[stat],wd=wave_dir[stat]))
wave_rose=WindRose(wave_data)
#fig3=px.line(wave,x=wave.index,y='hs')
fig3=go.Figure()
fig3.add_trace(go.Scatter(x=wave_hs.index,y=wave_hs['groix']))
fig3.update_layout(title=dict(text='Hs from WAM Model - %s'%(stat),x=0.5),
xaxis_title='',
yaxis_title='Hs(m)')
#rose
wave_rose.calc_stats(normed=True,bins=8)
wave_rose.wind_df=wave_rose.wind_df.rename(columns={"speed":'Hs'})
fig5 = px.bar_polar(wave_rose.wind_df, r="frequency", theta="direction",
color="Hs", template="plotly_white",
color_discrete_sequence= px.colors.sequential.Plasma_r)
fig5.update_layout(title=dict(text='Wave Rose - %s'%(stat),x=0.5))
##########
#HYDRO plot
##########
hydro=pd.read_pickle('hydro.pkl')
hydro_fig = make_subplots(specs=[[{"secondary_y": True}]])
#fig.add_trace(go.Scatter(x=data.index,y=data.xe,name="level"))
hydro_fig.add_trace(go.Scatter(x=hydro.index,y=hydro.xe,name="level",fill=None))
hydro_fig.add_trace(go.Scatter(x=hydro.index,y=hydro.xe+hydro.delta_xe,line_width=0.4,name="surcote",fill="tonexty"))#,secondary_y=True)
hydro_fig.update_layout(legend=dict(
yanchor="top",
y=0.99,
xanchor="right",
x=0.9))
hydro_fig2 = make_subplots(specs=[[{"secondary_y": True}]])
u=hydro.u.values
v=hydro.v.values
x=N.linspace(0,1,len(hydro))
y=N.zeros(len(x))
npt=4
spd=N.sqrt(u**2+v**2)
u1 = N.ma.where(spd!=0., u/spd, u)
v1 = N.ma.where(spd!=0., v/spd, v)
x1=x[::npt]
y1=spd[::npt]
y1=y[::npt]
u1=u1[::npt]
v1=v1[::npt]
dates=hydro.index[::npt]
hydro_fig2.add_trace(go.Scatter(x=x,y=spd,mode='lines',name="current speed"))
quiv=fac.create_quiver(x1,y1,u1,v1,scale =0.1, scaleratio = 0.25,arrow_scale=0.2,name="current Direction")
hydro_fig2.add_trace(quiv.data[0])
hydro_fig2.update_layout(xaxis_tickvals =x1[::8],xaxis_ticktext=dates[::8])
hydro_fig2.add_trace(go.Scatter(x=x,y=hydro.xe.values,line_width=0.5,name="water level",fill=None),secondary_y=True)
hydro_fig2.update_layout(legend=dict(
yanchor="top",
y=0.99,
xanchor="right",
x=0.9))
######
#map
######
fig2 = go.Figure(data=go.Scattermapbox(
lon = lon_list,
lat = lat_list,
text = name_list,
mode = 'markers',
marker=go.scattermapbox.Marker(
size=14),
) )
fig2.update_layout(mapbox_style="open-street-map",
mapbox=dict(center=go.layout.mapbox.Center(lon=-4.49,lat=48.35),
zoom=6)
)
app.layout = dbc.Container([
dbc.Row(
dbc.Col(html.H1("Meteo Dashboard",
className='text-center text-primary mb-4'),
width=12)
),
dbc.Row([
dbc.Col([
dcc.Graph(id='map-fig', figure=fig2)
], width=6),
], justify="center"),
dbc.Row([
dbc.Col([
dcc.Graph(id='wind-fig', figure=fig1),
], width={'size': 6, 'offset': 0}),
dbc.Col([
dcc.Graph(id='wind_dir-fig', figure=fig4),
], width={'size': 6, 'offset': 0}),
], align='center', no_gutters=True, justify='start'),
dbc.Row([
dbc.Col([
dcc.Graph(id='wave-fig', figure=fig3),
], width={'size': 6, 'offset': 0}),
dbc.Col([
dcc.Graph(id='wave-fig2', figure=fig5),
], width={'size': 6, 'offset': 0}),
]),
dbc.Row([
dbc.Col([
dcc.Graph(id='hydro-fig1', figure=hydro_fig),
], width=6),
dbc.Col([
dcc.Graph(id='hydro-fig22', figure=hydro_fig2),
], width=6),
], no_gutters=True)
], fluid=True)
@app.callback(output=Output('wave-fig', 'figure'),
inputs=Input('map-fig', 'clickData'))
def _update_graph(clickData):
print(clickData)
# click
stat = clickData['points'][0]['text']
print("stat=", stat)
fig = go.Figure()
fig.add_trace(go.Scatter(x=wave.index, y=wave[stat]))
fig.update_layout(title=dict(text='Hs from WAM Model - %s' % (stat), x=0.5),
xaxis_title='',
yaxis_title='Hs(m)')
return fig
@app.callback(output=Output('wind-fig', 'figure'),
inputs=Input('map-fig', 'clickData'))
def _update_graph(clickData):
print(clickData)
# click
stat = clickData['points'][0]['text']
print("stat=", stat)
fig = make_subplots(specs=[[{"secondary_y": True}]])
fig.add_trace(go.Scatter(x=spd.index, y=spd[stat], name="speed"))
fig.add_trace(go.Scatter(x=direction.index, y=direction[stat], name="dir"), secondary_y=True)
fig.update_layout(title=dict(text='Wind from Arome Model - %s' % (stat), x=0.5),
xaxis_title='',
yaxis_title='speed(m/s)')
return fig
@app.callback(output=Output('wind_dir-fig', 'figure'),
inputs=Input('map-fig', 'clickData'))
def _update_graph(clickData):
print(clickData)
# click
stat = clickData['points'][0]['text']
print("stat=", stat)
test_rose = pd.DataFrame(data=dict(date=spd.index, ws=spd[stat], wd=direction[stat]))
wind = WindRose(test_rose)
wind.calc_stats(normed=True, bins=8)
fig = px.bar_polar(wind.wind_df, r="frequency", theta="direction",
color="speed", template="plotly_white",
color_discrete_sequence=px.colors.sequential.Plasma_r)
fig.update_layout(title=dict(text='Wind Rose - %s' % (stat), x=0.5))
return fig
#RUN SERVER
if __name__ == '__main__':
app.run_server( port = 8090, debug=True)