from IPython.display import display
from IPython.display import HTML
import IPython.core.display as di # Example: di.display_html('<h3>%s:</h3>' % str, raw=True)

# This line will hide code by default when the notebook is exported as HTML
di.display_html('<script>jQuery(function() {if (jQuery("body.notebook_app").length == 0) { jQuery(".input_area").toggle(); jQuery(".prompt").toggle();}});</script>', raw=True)

# This line will add a button to toggle visibility of code blocks, for use with the HTML export version
di.display_html('''<button onclick="jQuery('.input_area').toggle(); jQuery('.prompt').toggle();">Toggle code</button>''', raw=True)

# %matplotlib inline
import numpy as np, pandas as pd, matplotlib.pyplot as plt, seaborn as sns
import pickle, os, gc, re

from utility import *
BES_data_folder = '../BES_analysis_data/'
Pollbase_folder = create_subdir(BES_data_folder,"Pollbase")

from bokeh.models import ColumnDataSource
from bokeh.plotting import figure, show,  output_notebook
from bokeh.layouts import column, row
from bokeh.embed import components
output_notebook()

from bokeh.models import HoverTool
from bokeh.models import Span, Label
from bokeh.models import BoxAnnotation

from datetime import timedelta
from scipy.signal import find_peaks
from datetime import datetime
import pytz

df = pd.read_csv(Pollbase_folder+"MarkPackPollBase_flat_v7.csv",
                 parse_dates=['Fieldwork_Start_Date', 'Fieldwork_Finish_Date',
       'Fieldwork_Midpoint_Date'],index_col="Unnamed: 0")

tools='box_select,pan,xwheel_zoom,box_zoom,reset'
active_drag='pan'
active_scroll='xwheel_zoom'

hover_tool = HoverTool(names=['polls'],tooltips = [
          ('Type','@Poll_Type'),
          ('By','@Polling'),
          ('For','@Publisher'),
          ('Fieldwork Start','@Fieldwork_Start_Date{%d/%m/%y}'),
          ('Fieldwork Finish','@Fieldwork_Finish_Date{%d/%m/%y}'),
          ('Con [lead]','@Con{%0.1f} (@{Con Change}{%0.1f}) [@{Con lead}{%0.1f} (@{Con lead Change}{%0.1f})]'),
          ('Lab','@Lab{%0.1f} (@{Lab Change}{%0.1f})'),
          ('LD','@Lab{%0.1f} (@{LD Change}{%0.1f})'),
         ],
    formatters={'Fieldwork_Start_Date': 'datetime',
                'Fieldwork_Finish_Date': 'datetime',
                'Con' : 'printf',
                'Con Change' : 'printf',
                'Con lead' : 'printf',
                'Con lead Change' : 'printf',                
                'Lab' : 'printf',
                'Lab Change' : 'printf',               
                'LD' : 'printf',
                'LD Change' : 'printf',               
               },
    # display a tooltip whenever the cursor is vertically in line with a glyph
#                 mode='vline'
         )

normal_poll_source = ColumnDataSource(df)

plot_width = 980
plot_height = 250


p1 = figure(x_axis_type="datetime",x_axis_label = "Fieldwork_Midpoint_Date",y_axis_label="%",
            plot_width=plot_width, plot_height=plot_height, title="Conservative Voting Intention",
            tools=tools, active_drag=active_drag,active_scroll=active_scroll)
p1.scatter('Fieldwork_Midpoint_Date', 'Con', source=normal_poll_source, color='blue',name='polls')
p1.add_tools(hover_tool)

p2 = figure(x_axis_type="datetime",x_axis_label = "Fieldwork_Midpoint_Date",y_axis_label="%",
            plot_width=plot_width, plot_height=plot_height, title="Labour Voting Intention",
            tools=tools, active_drag=active_drag,active_scroll=active_scroll)
p2.scatter('Fieldwork_Midpoint_Date', 'Lab', source=normal_poll_source, color='red',name='polls')
p2.add_tools(hover_tool)

p3 = figure(x_axis_type="datetime",x_axis_label = "Fieldwork_Midpoint_Date",y_axis_label="%",
            plot_width=plot_width, plot_height=plot_height, title="LibDem Voting Intention",
            tools=tools, active_drag=active_drag,active_scroll=active_scroll)
p3.scatter('Fieldwork_Midpoint_Date', 'LD', source=normal_poll_source, color='orange',name='polls')
p3.add_tools(hover_tool)

# Link the x_range of p2 to p1: p2.x_range
p2.x_range = p1.x_range

# Link the y_range of p2 to p1: p2.y_range
p2.y_range = p1.y_range

# Link the x_range of p3 to p1: p3.x_range
p3.x_range = p1.x_range

# Link the y_range of p3 to p1: p3.y_range
p3.y_range = p1.y_range

layout = column(p1,p2,p3)
show(layout)

normal_poll_source = ColumnDataSource( df[df["Poll_Type"]=="Normal Poll"] )
result_source = ColumnDataSource( df[df["Poll_Type"]=="Result"] )
exit_poll_source = ColumnDataSource( df[df["Poll_Type"]=="Exit Poll"] )

def VI_time_series(title,col,colour):
    p = figure(x_axis_type="datetime",x_axis_label = "Fieldwork_Midpoint_Date",y_axis_label="%",
                plot_width=plot_width, plot_height=plot_height, title=title,
                tools=tools, active_drag=active_drag,active_scroll=active_scroll)
    p.scatter('Fieldwork_Midpoint_Date', col, source=normal_poll_source, color=colour,name='polls')
    p.diamond('Fieldwork_Midpoint_Date', col, source=result_source, color=colour, size=40,fill_alpha=0.3,line_alpha=0.0,name='polls')
    p.x('Fieldwork_Midpoint_Date', col, source=exit_poll_source, color=colour, size=40,fill_alpha=0.3,line_alpha=0.3,name='polls')    
    p.add_tools(hover_tool)
    return p





# Conservatives
p1 = VI_time_series(title="Conservative (Voting Intention)",col="Con",colour='blue')

# Labour
p2 = VI_time_series(title="Labour (Voting Intention)",col="Lab",colour='red')

# Con-Lab
p3 = VI_time_series(title="Conservative lead over Labour (Voting Intention)",col="Con lead",colour='pink')

# LibDems
p4 = VI_time_series(title="LibDem (Voting Intention)",col="LD",colour='orange')

# UKIP
p5 = VI_time_series(title="UKIP (Voting Intention)",col="UKIP",colour='purple')

# Green
p6 = VI_time_series(title="Green (Voting Intention)",col="Green",colour='green')

# BNP
p7 = VI_time_series(title="BNP (Voting Intention)",col="BNP",colour='black')

# SDP
p8 = VI_time_series(title="SDP (Voting Intention)",col="SDP",colour='yellow')

# BXP
p9 = VI_time_series(title="BXP (Voting Intention)",col="BXP",colour='cyan')

# TIG/CUK
p10 = VI_time_series(title="TIG/CUK (Voting Intention)",col="TIG/CUK",colour='grey')

# TIG/CUK
p11 = VI_time_series(title="Referendum (Voting Intention)",col="Referendum",colour='purple')

# Link the x/y ranges
# okay - not the y-range, that makes LD invisible!
# p2.y_range = p1.y_range
# p3.y_range = p1.y_range

p2.x_range = p1.x_range
p3.x_range = p1.x_range
figs = [p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11]
for fig in figs[1:]:
    fig.x_range = p1.x_range

layout = column(figs)
show(layout)

# df["Con Change"].hist(bins=223);

# df["Con Change"].value_counts()

# df.loc[(df["Con Change"]<=-11)]