pritamd47

import scipy.stats as stats
import numpy as np

def get_stats(obs, mod):
    corr, corr_p = stats.pearsonr(obs, mod)
    nse = 1 - (np.sum((obs - mod)**2)/np.sum((obs - np.mean(obs))**2))
    nse1 = 1 - (np.sum(np.abs(obs - mod))/np.sum(np.abs(obs - np.mean(obs))))
    rmse = np.sqrt(np.sum((obs-mod)**2)/len(mod))
    mae = np.sum(np.abs(mod-obs))/len(mod)

pritamd47

# Clip time-series
def clip_ts(*tss):
    mint = max([min(ts.index) for ts in tss])
    maxt = min([max(ts.index) for ts in tss])

    # clipped_tss = [ts[mint:maxt] for ts in tss]
    clipped_tss = [ts.loc[(ts.index>=mint)&(ts.index<=maxt)] for ts in tss]

    return clipped_tss