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from __future__ import print_function
import nilmtk
import matplotlib.pyplot as plt
%matplotlib inline
First, load the UKDALE dataset into NILMTK. Here we are loading the HDF5 version of UKDALE which you can download by following the instructions on the UKDALE website.
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dataset = nilmtk.DataSet('/data/mine/vadeec/merged/ukdale.h5')
Next, to speed up processing, we'll set a "window of interest" so NILMTK will only consider one month of data.
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dataset.set_window("2014-06-01", "2014-07-01")
Get the ElecMeter associated with the Fridge in House 1:
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BUILDING = 1
elec = dataset.buildings[BUILDING].elec
fridge = elec['fridge']
Now load the activations:
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activations = fridge.get_activations()
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print("Number of activations =", len(activations))
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activations[1].plot()
plt.show()
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