#!/usr/bin/env python
# coding: utf-8

# In[1]:


import numpy as np
import pandas as pd
import datetime

from bokeh.io import output_notebook, show
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource, LinearColorMapper, DatetimeTickFormatter
from bokeh.palettes import Blues9, Greens9, Reds9

output_notebook()


# ## Create some dummy data

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start_dt = datetime.datetime(2016,1,1)

params = ['p1', 'p2', 'p3']

dfs = []
for p in params:
    
    dates = [start_dt + datetime.timedelta(minutes=int(x)) for x in np.random.randint(1,400,300).cumsum()]    
    dfs.append(pd.DataFrame({p: np.random.randn(len(dates))}, index=dates))
    
df = pd.concat(dfs, axis=1)

dfday = df.groupby(lambda x: x.date()).count()

dfday['start'] = dfday.index
dfday['end'] = [x+datetime.timedelta(days=1) for x in dfday.index]
dfday.head()


# ## Define colormaps for each param

# In[3]:


cmaps = {}
cmaps['p1'] =  LinearColorMapper(palette=Reds9)
cmaps['p2'] =  LinearColorMapper(palette=Blues9)
cmaps['p3'] =  LinearColorMapper(palette=Greens9)


# ## Plot

# In[4]:


p = figure(x_axis_type="datetime", x_range=(dfday.index[0], dfday.index[-1]), y_range=[0,4],
           tools='xpan, xwheel_zoom, reset, save, resize', width=800, height=300)

for i, par in enumerate(params):
    
    p.quad(left='start', right='end', bottom=.6+i, top=1.4+i,
           color={'field': par, 'transform': cmaps[par]}, source=ColumnDataSource(dfday))

p.xaxis.formatter = DatetimeTickFormatter(days=['%d-%b-%Y'])
    
show(p)


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