tft_oos4

# retrieve forecast series for chosen quantiles, 
# inverse-transform each series,
# insert them as columns in a new dataframe dfY
q50_RMSE = np.inf
q50_MAPE = np.inf
ts_q50 = None
pd.options.display.float_format = '{:,.2f}'.format
dfY = pd.DataFrame()
#dfY["Actual"] = TimeSeries.pd_series(ts_test)
 
# call helper function predQ, once for every quantile
_ = [predQ(ts_tpred, q) for q in QUANTILES]

# move Q50 column to the left, then insert Actual column
col = dfY.pop("Q50")
dfY.insert(0, col.name, col)
dfY.insert(0, "Actual", TimeSeries.pd_series(ts_test))

# show first and last 13 timestamps of forecast
dfY.iloc[np.r_[0:1, -13:0]]