def plot_forecasts()

in notebooks/common/util/fcst_utils.py [0:0]

• 18 lines of code
• 1 McCabe index (conditional complexity)

def plot_forecasts(fcsts, exact, freq = '1H', forecastHorizon=24, time_back = 80):
    p10 = pd.DataFrame(fcsts['Forecast']['Predictions']['p10'])
    p50 = pd.DataFrame(fcsts['Forecast']['Predictions']['p50'])
    p90 = pd.DataFrame(fcsts['Forecast']['Predictions']['p90'])
    pred_int = p50['Timestamp'].apply(lambda x: pd.Timestamp(x))
    fcst_start_date = pred_int.iloc[0]
    fcst_end_date = pred_int.iloc[-1]
    time_int = exact['timestamp'].apply(lambda x: pd.Timestamp(x))
    plt.plot(time_int[-time_back:],exact['target'].values[-time_back:], color = 'r')
    plt.plot(pred_int, p50['Value'].values, color = 'k')
    plt.fill_between(pred_int, 
                     p10['Value'].values,
                     p90['Value'].values,
                     color='b', alpha=0.3);
    plt.axvline(x=pd.Timestamp(fcst_start_date), linewidth=3, color='g', ls='dashed')
    plt.axvline(x=pd.Timestamp(fcst_end_date), linewidth=3, color='g', ls='dashed')
    plt.xticks(rotation=30)
    plt.legend(['Target', 'Forecast'], loc = 'lower left')