appliances = ["hvac", "fridge", "wm", "dw", "ec", "mw", "oven", "wh"]
features = ["Static", "Monthly+Static", "Monthly"]
appliances = ['fridge,"hvac']

import sys
CLUSTER = True
if CLUSTER:
    sys.path.insert(0, '/if6/nb2cz/anaconda/lib/python2.7/site-packages')

sys.path.insert(0, '../code')

import numpy as np
import pandas as pd

from create_df_larger import read_df_larger
df, dfc, all_homes, appliance_min, national_average = read_df_larger()

df = df.rename(
    columns={
        'house_num_rooms': 'num_rooms',
        'num_occupants': 'total_occupants',
        'difference_ratio_min_max': 'ratio_difference_min_max'
    })
K_min, K_max = 1, 3
F_min, F_max = 1, 8

from all_functions import *
from features_larger import *

SLURM_OUT = "../slurm_out"
from subprocess import Popen
# NEED TO RUN ON CLUSTER
import sys
CLUSTER=True
if CLUSTER:
    sys.path.insert(0, '/if6/nb2cz/anaconda/lib/python2.7/site-packages')

import  os

import numpy as np
import pandas as pd


from create_df_larger import read_df_larger
df, dfc, all_homes, appliance_min, national_average = read_df_larger()

df = df.rename(columns={'house_num_rooms':'num_rooms',
                        'num_occupants':'total_occupants',
                        'difference_ratio_min_max':'ratio_difference_min_max'})
K_min, K_max = 1,6
F_min, F_max=1,8

from all_functions import *
from features_larger import *

import sys

from sklearn.neighbors import KNeighborsRegressor
from sklearn.cross_validation import ShuffleSplit
from sklearn.cross_validation import LeaveOneOut

NUM_NEIGHBOUR_MAX = 6