Source code for ltsm.utils.metrics

import numpy as np




def RSE(pred, true):
    return np.sqrt(np.sum((true - pred) ** 2)) / np.sqrt(np.sum((true - true.mean()) ** 2))





def CORR(pred, true):
    u = ((true - true.mean(0)) * (pred - pred.mean(0))).sum(0)
    d = np.sqrt(((true - true.mean(0)) ** 2 * (pred - pred.mean(0)) ** 2).sum(0))
    return (u / d).mean(-1)





def MAE(pred, true):
    return np.mean(np.abs(pred - true))





def MSE(pred, true):
    return np.mean((pred - true) ** 2)





def RMSE(pred, true):
    return np.sqrt(MSE(pred, true))





def MAPE(pred, true):
    return np.mean(np.abs(100 * (pred - true) / (true +1e-8)))





def MSPE(pred, true):
    return np.mean(np.square((pred - true) / (true + 1e-8)))




def SMAPE(pred, true):
    return np.mean(200 * np.abs(pred - true) / (np.abs(pred) + np.abs(true) + 1e-8))

    # return np.mean(200 * np.abs(pred - true) / (pred + true + 1e-8))



def ND(pred, true):
    return np.mean(np.abs(true - pred)) / np.mean(np.abs(true))




def metric(pred, true):
    mae = MAE(pred, true)
    mse = MSE(pred, true)
    rmse = RMSE(pred, true)
    mape = MAPE(pred, true)
    mspe = MSPE(pred, true)
    smape = SMAPE(pred, true)
    nd = ND(pred, true)

    return mae, mse, rmse, mape, mspe, smape, nd