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Improper scaling #21
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I believe your
scale_data()
is scaling horizontally across the signals rather than down the time series for each of signal itself. I used:def scale_linear_bycolumn(rawpoints, high=1.0, low=-1.0):
mins = np.min(rawpoints, axis=0)
maxs = np.max(rawpoints, axis=0)
rng = maxs - mins
return high - (((high - low) * (maxs - rawpoints)) / rng)
I think it would make sense to scale the whole signals's timeseries (down the column) rather than across at each time step. I noticed this when I was inputing signals with different amplitudes and the values starting to fill as NaN because it was being scaled across signals at a timestep rather than down the signal to all the values for that signal's time series.
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