uadapy.data package

uadapy.data.data module

uadapy.data.data.generate_synthetic_timeseries(timesteps=200)

Generates synthetic time series data by modeling a combination of trend, periodic patterns, and noise using a multivariate normal distribution with an exponential quadratic kernel for covariance.

Parameters:

timesteps (int) – The time steps of the time series. Default value is 200.

Returns:

timeseries – An instance of the TimeSeries class, which represents a univariate time series.

Return type:

Timeseries object

uadapy.data.data.load_iris()

Uses the iris dataset and fits a normal distribution :return:

uadapy.data.data.load_iris_normal()

Uses the iris dataset and fits a normal distribution :return: