
# coding: utf-8

# ## This script shows the visualization of electricity, water and gas consumption using carpet plots
# 
# To get started, first run the 'Synchronize data' script
# 
# #### Imports and paths

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import os
import sys
import pytz
import time
import inspect
import numpy as np
import pandas as pd
import datetime as dt
import matplotlib.pyplot as plt
import tmpo

from opengrid import config
from opengrid.library import plotting
from opengrid.library import houseprint

c=config.Config()

try:
    if os.path.exists(c.get('tmpo', 'data')):
        path_to_tmpo_data = c.get('tmpo', 'data')
except:
    path_to_tmpo_data = None

# configuration for the plots
DEV = c.get('env', 'type') == 'dev' # DEV is True if we are in development environment, False if on the droplet
print("Environment configured for development: {}".format(DEV))
if not DEV:
    # production environment: don't try to display plots
    import matplotlib
    matplotlib.use('Agg')

import matplotlib.pyplot as plt
from matplotlib.dates import MinuteLocator, HourLocator, DateFormatter, AutoDateLocator, num2date

if DEV:
    if c.get('env', 'plots') == 'inline':
        get_ipython().magic(u'matplotlib inline')
    else:
        get_ipython().magic(u'matplotlib qt')
else:
    pass # don't try to render plots

plt.rcParams['figure.figsize'] = 16,8

# path to data
path_to_data = c.get('data', 'folder')
if not os.path.exists(path_to_data):
    raise IOError("Provide your path to the data in your config.ini file. ")
else:
    path_to_fig = os.path.join(path_to_data, 'figures')
    if not os.path.isdir(path_to_fig): os.makedirs(path_to_fig)


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c.get('data','folder')


# ### Loading meta data and user variables

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hp = houseprint.Houseprint()

end = pd.Timestamp(time.time(), unit='s')
start = end - pd.Timedelta('21 days')


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hp.save('new_houseprint.pkl')


# ## Plotting

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#hp.sync_tmpos()


# ### Water sensors

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water_sensors = hp.get_sensors(sensortype='water')
print("{} water sensors".format(len(water_sensors)))


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for sensor in water_sensors:
    ts = sensor.get_data(head=start, tail=end)
    if not ts.dropna().empty:
        plotting.carpet(ts, title=' - '.join([sensor.device.key, sensor.description, sensor.key]), zlabel=r'Flow [l/min]')
        plt.savefig(os.path.join(path_to_fig, 'carpet_'+sensor.type+'_'+sensor.key), dpi=100)
        if not DEV:
            plt.close()


# ### Gas sensors

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gas_sensors = hp.get_sensors(sensortype=('gas'))
print("{} gas sensors".format(len(gas_sensors)))


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for sensor in gas_sensors:
    ts = sensor.get_data(head=start, tail=end)
    if not ts.dropna().empty:
        plotting.carpet(ts, title=' - '.join([sensor.device.key, sensor.description, sensor.key]), zlabel=r'Gas consumption [W]')
        plt.savefig(os.path.join(path_to_fig, 'carpet_'+sensor.type+'_'+sensor.key), dpi=100)
        if not DEV:
            plt.close()


# ### Electricity sensors

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elec_sensors = hp.get_sensors(sensortype=('electricity'))
print("{} electricity sensors".format(len(elec_sensors)))


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for sensor in elec_sensors:
    ts = sensor.get_data(head=start, tail=end)
    if not ts.dropna().empty:
        plotting.carpet(ts, title=' - '.join([sensor.device.key, sensor.description, sensor.key]), zlabel=r'Power [W]')
        plt.savefig(os.path.join(path_to_fig, 'carpet_'+sensor.type+'_'+sensor.key), dpi=100)
        if not DEV:
            plt.close()


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