import plotly
import plotly.plotly as py
import plotly.graph_objs as go
import random
import datetime

# setup the date series
#  we need day of week (dow) and if it is a weekday (wday) too
sdate = datetime.datetime.strptime("2016-01-01", '%Y-%m-%d').date()
edate = datetime.datetime.strptime("2016-02-28", '%Y-%m-%d').date()
ndays = (edate - sdate).days + 1
dates = [sdate + datetime.timedelta(days=x) for x in range(ndays)]
dow   = [(x+5) % 7 for x in range(ndays)]
wday  = [1 if dow[x]<=4 else 0 for x in range(ndays)]

# now some fake power consumption
# weekdays will have 150 power consumption on average
# weekend will have 100 power consumption on average
# and we add about 20 in random noise to both
pwval  = [ 90+wday[x]*50 + random.randrange(0,20) for x in range(ndays)]
# limits - higher limits during the week (150) compared to the weekend (100)
pwlim  = [150 if dow[x]<=4 else 100 for x in range(ndays)]

# now the colors
clrred = 'rgb(222,0,0)'
clrgrn = 'rgb(0,222,0)'
clrs  = [clrred if pwval[x]>=pwlim[x] else clrgrn for x in range(ndays)]

# first trace (layer) is our power consumption bar
trace0 = go.Bar(
    x=dates,
    y=pwval,
    name="Power Consumption",
    marker=dict(color=clrs)
)
# second trace is our line showing the power limit
trace1 = go.Scatter(
    x=dates,
    y=pwlim,
    name = 'Power Limit',
    line = dict(
        color = ('rgb(0,0,222)'),
        width = 2,
        dash = 'dot')
)
data = [trace0,trace1]
layout = go.Layout( title='Power')
fig = go.Figure(data=data, layout=layout)
py.iplot(fig, filename='power-limits-1')