utils.py

import os
import numpy as np

# Quality functions
def qualitySSE(x,y):
    # Sum squared error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    return ((x-y)**2).sum(), (x-y)**2

def qualityMSE(x,y):
    # Mean squared error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    return ((x-y)**2).mean() , (x-y)**2

def qualityRMSE(x,y):
    # Root mean squared error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    return (((x-y)**2).mean())**(0.5) , (x-y)**2

def qualityMAE(x,y):
    # Mean absolute error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    return (x-y).abs().mean(), (x-y).abs()

def qualityMAPE(x,y):
    # Mean absolute percentage error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    qlt = ((x-y).abs()/x).replace([np.inf, -np.inf], np.nan)
    return qlt.mean() , (x-y).abs()

def qualityMACAPE(x,y):
    # Mean average corrected absolute percentage error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    qlt = (2*(x-y).abs()/(x+y)).replace([np.inf, -np.inf], np.nan)
    return qlt.mean() , (x-y).abs()

def qualityMedianAE(x,y):
    # Median absolute error
    # x,y - pandas structures
    # x - real values
    # y - forecasts
    return ((x-y).abs()).median(), (x-y).abs()

def ExponentialSmoothing(x, h, Params):
    T = len(x)
    alpha = Params['alpha']
    AdaptationPeriod=Params['AdaptationPeriod']
    FORECAST = [np.NaN]*(T+h)
    if alpha>1:
        w.warn('Alpha can not be more than 1')
        #alpha = 1
        return FORECAST
    if alpha<0:
        w.warn('Alpha can not be less than 0')
        #alpha = 0
        return FORECAST
    y = x[0]
    t0=0
    for t in range(0, T):
        if not math.isnan(x[t]):
            if math.isnan(y):
                y=x[t]
                t0=t
            if (t-t0+1)<AdaptationPeriod:
                y = y*(1-alpha*(t-t0+1)/(AdaptationPeriod)) + alpha*(t-t0+1)/(AdaptationPeriod)*x[t]
            y = y*(1-alpha) + alpha*x[t]
            #else do not nothing
        FORECAST[t+h] = y
    return FORECAST