/// <summary>
/// Same as max_min_norm, but it performs the operation inplace, without allocating further memory.
/// </summary>
/// <param name="tss">Expects an input array whose dimension zero is the length of the time series (all the same) and dimension
/// one indicates the number of time series.</param>
/// <param name="high">Maximum final value (Defaults to 1.0).</param>
/// <param name="low">Minimum final value (Defaults to 0.0).</param>
/// <param name="epsilon">Safeguard for constant (or near constant) time series as the operation implies a unit scale operation
/// between min and max values in the tss.</param>
public static void MaxMinNorm(ref KhivaArray tss, double high, double low, double epsilon = 0.00000001)
{
var reference = tss.Reference;
DLLNormalization.max_min_norm_in_place(ref reference, ref high, ref low, ref epsilon);
tss.Reference = reference;
}
/// <summary>
/// Adjusts the time series in the given input and performs z-norm inplace(without allocating further memory).
/// </summary>
/// <param name="tss"> Expects an input array whose dimension zero is the length of the time
/// series(all the same) and dimension one indicates the number of time series.</param>
/// <param name="epsilon">Minimum standard deviation to consider. It acts as a gatekeeper for
/// those time series that may be constant or near constant.</param>
public static void ZNorm(ref KhivaArray tss, double epsilon)
{
var reference = tss.Reference;
DLLNormalization.znorm_in_place(ref reference, ref epsilon);
tss.Reference = reference;
}
/// <summary>
/// Same as decimal_scaling_norm, but it performs the operation inplace, without allocating further memory.
/// </summary>
/// <param name="tss">Expects an input array whose dimension zero is the length of the time series (all the same) and dimension
/// one indicates the number of time series.</param>
public static void DecimalScalingNorm(ref KhivaArray tss)
{
var reference = tss.Reference;
DLLNormalization.decimal_scaling_norm_in_place(ref reference);
tss.Reference = reference;
}
/// <summary>
/// Normalizes the given time series according to its maximum-minimum value and its mean. It follows the following
/// formulae:
/// \f[
/// \acute{x} = \frac{x - mean(x)}{max(x) - min(x)}.
/// \f]
/// </summary>
/// <param name="tss">Expects an input array whose dimension zero is the length of the time series (all the same) and dimension
/// one indicates the number of time series.</param>
public static void MeanNorm(ref KhivaArray tss)
{
var reference = tss.Reference;
DLLNormalization.mean_norm_in_place(ref reference);
tss.Reference = reference;
}