For an hourly dataset, the shaded area is not plotted correctly (should have been light blue).
Scripot : (same as demo.py with 'H' instead of 'D' for frequency)
import numpy as np
import pandas as pd
if __name__ == '__main__':
# generate a hourly signal covering one year 2016 in a pandas dataframe
N = 365
np.random.seed(seed=1960)
df_train = pd.DataFrame({"Date" : pd.date_range(start="2016-01-25", periods=N, freq='H'),
"Signal" : (np.arange(N)//40 + np.arange(N) % 21 + np.random.randn(N))})
# print(df_train.head(N))
import pyaf.ForecastEngine as autof
# create a forecast engine. This is the main object handling all the operations
lEngine = autof.cForecastEngine()
# get the best time series model for predicting one week
lEngine.train(iInputDS = df_train, iTime = 'Date', iSignal = 'Signal', iHorizon = 7);
lEngine.getModelInfo() # => relative error 7% (MAPE)
lEngine.standardPlots("outputs/bug_hourly_");
Plot :
For an hourly dataset, the shaded area is not plotted correctly (should have been light blue).
Scripot : (same as demo.py with 'H' instead of 'D' for frequency)
Plot :