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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 tmpo

from opengrid import config
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
    # these lines has to be BEFORE any plt import, also in other packages.
    import matplotlib
    matplotlib.use('Agg') 

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

if DEV:
    if c.get('env', 'plots') == 'inline':
        %matplotlib inline
    else:
        %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')


    

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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')


    

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hp = houseprint.load_houseprint_from_file('new_houseprint.pkl')


    

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pd.__version__


    

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%%bash
pip install --upgrade pandas


    

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hp.sync_tmpos()


    

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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()


    

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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()


    

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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:
    if not sensor.key.startswith('565de'): # 3E's sensor creates ram issues on the droplet.  To be fixed in tmpo?
        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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