Chlorine

This dataset was originally defined in a PhD thesis by Lei Li (Carnegie Mellon University). It was produced by EPANET that models the hydraulic and water quality behavior of water distribution piping systems. EPANET can track, in a given water network, the water level and pressure in each tank, the water flow in the pipes and the concentration of a chemical species (Chlorine in this case) throughout the network within a simulated duration. The data set consists of 166 nodes (pipe junctions) and measurement of the Chlorine concentration level at all these nodes during 15 days (one measurement for every 5 minutes, a total of 4310 time ticks). This is a modified and preprocessed version of the dataset saved in numpy format. The original dataset was obtained from here. The dataset consists of univariate time series associated with a class label. It can be loaded as follows: loaded_data = np.load("Chlorine.npz") Xtr = loaded_data['Xtr'] # Training data of shape (467, 166) Ytr = loaded_data['Ytr'] # Training labels of shape (467, 1) Xte = loaded_data['Xte'] # Test data of shape (3840, 166) Yte = loaded_data['Yte'] # Test labels of shape (3840, 1)