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from bokeh.io import show, output_notebook
output_notebook()


    

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from app.utils import timelog_path


    

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import pandas as pd
import numpy as np
import datetime

raw = pd.read_table(timelog_path, quotechar=' ', sep=': ', names=['timestamp', 'activity'], engine='python',)

# Set the column types

raw.timestamp = pd.to_datetime(raw.timestamp)
raw = raw.drop_duplicates()

### Build the times
raw['formatted_time'] = raw.timestamp.apply(lambda x: x.strftime("%I %p"))  # Used for hover tools
raw['end'] = raw.timestamp
raw['start'] = raw['end'].shift(1)

raw['start'] = np.where(
    raw['activity'] == 'start',  # If the activity is start
    raw['timestamp'],  # Set the start to timestamp
    raw['start'],  # Else leave it as start
)

raw['delta'] = raw.end - raw.start
# Remove the non-work activities which all have ***
raw = raw[~raw.activity.str.contains('\*\*\*')]
# Boil down the categories to the main work categories
raw.activity = raw.activity.str.split(' ').str[0]

raw.head()


    

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# Build a dictionary of frames - one for each category

activities = list(raw.activity.unique())
activities.remove('start')
start_df = raw[raw.activity == 'start']
nan_df = start_df.copy()
nan_df['delta'] = np.NaN
nan_df['activity'] = '_'

dfs = {}

for activity in activities:
    activity_df = raw[raw.activity == activity]
    
    # Add in the start rows with 0 deltas and do cumsum
    activity_df = activity_df.append(start_df)
    activity_df.sort('timestamp', inplace=True)
    activity_df['cumsum'] = np.cumsum(activity_df.groupby(activity_df.timestamp.dt.date)['delta'])
    activity_df['cumsum_hrs'] = activity_df['cumsum'].dt.seconds / (60 * 60)
    
    # Add in the nan rows so bokeh can plobt
    activity_df = activity_df.append(nan_df)
    activity_df.sort(['timestamp', 'activity'], inplace=True)
    
    dfs[activity] = activity_df

    
terra = dfs['terra']
terra.head()


    

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from bokeh.models import (
    Plot, Line, ColumnDataSource,  DataRange1d, 
    LinearAxis, BasicTicker,
    DatetimeAxis, DatetimeTicker, DatetimeTickFormatter,
    BoxZoomTool, PanTool, ResetTool, WheelZoomTool, 
    HoverTool, Grid
)
from bokeh import palettes


    

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plot = Plot(
    x_range=DataRange1d(), 
    y_range=DataRange1d(), 
    background_fill='black', 
    border_fill='black',
    outline_line_color=None,
    plot_width=900,
    plot_height=300
)

yticker = BasicTicker(min_interval=4)
close_ticker = DatetimeTicker(desired_num_ticks=8)
year_ticker = DatetimeTicker(desired_num_ticks=4)
year_ticks = DatetimeTickFormatter(
    formats={
        'years': ["%Y"],
        'months': ["%Y"],
        'days': ["%Y"],
        'hours': ["%Y"]
    }
)
close_ticks = DatetimeTickFormatter(
    formats={
        'years': ["%b"],
        'months': ["%b"],
        'days': ["%a %d %b"],
        'hours': ["%I%p %d %b"]
    }
)

axis_properties = dict(
    major_label_text_color='white',
)
plot.add_layout(LinearAxis(ticker=yticker, **axis_properties), 'left')
plot.add_layout(DatetimeAxis(formatter=close_ticks, ticker=close_ticker, **axis_properties), 'below')
plot.add_layout(DatetimeAxis(formatter=year_ticks, ticker=year_ticker, **axis_properties), 'below')
plot.add_layout(Grid(dimension=1, ticker=yticker, grid_line_alpha=0.3))


tool_opts = dict(dimensions=['width'])
plot.add_tools(
    BoxZoomTool(**tool_opts), 
    WheelZoomTool(**tool_opts), 
    PanTool(**tool_opts), 
    ResetTool(),
    
)

palette = getattr(palettes, 'Spectral%s' % len(activities))

for i, activity in enumerate(activities):
    frame = dfs[activity][['cumsum_hrs', 'timestamp', 'formatted_time']]
    source = ColumnDataSource(frame)
    line = Line(
        line_color=palette[i], 
        line_join='round', line_cap='round', line_width=5, line_alpha=0.75,
        x='timestamp', y='cumsum_hrs'
    )
    plot.add_glyph(source, line)

show(plot)


    

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