EMD decomposition of a given time series with a given sifting stop condition.

Takes a sized vector to ensure that:

1. The resulting EMD contains IMFs that are all the same length as the input vector
2. We provide a vector of size of at least one.

emd, but tracing results to stdout as IMFs are found. Useful for debugging to see how long each step is taking.

emd with a callback for each found IMF.

Collapse an EMD back into its original time series. Should be a left-inverse to emd: using iemd on the result of emd should give back the original vector.

Since: 0.1.5.0

An EMD v n a is an Empirical Mode Decomposition of a time series with n items of type a stored in a vector v.

The component-wise sum of emdIMFs and emdResidual should yield exactly the original series (see iemd).

Options for EMD composition.

Default EMDOpts

Note: If you immediately use this and set eoSifter, then v will be ambiguous. Explicitly set v with type applications to appease GHC

defaultEO @(Data.Vector.Vector)
   { eoSifter = scTimes 100
   }

Boundary conditions for splines.

A sift stopping condition.

It is a Pipe consumer that takes single sift step results upstream and terminates with () as soon as it is satisfied with the latest sift step.

Use combinators like siftOr and siftAnd to combine sifters, and the various sifters in Numeric.EMD.Sift to create sifters from commonly established ones or new ones from scratch.

Since: 0.2.0.0

Default Sifter

defaultSifter = siftStdDev 0.3 siftOr siftTimes 50

R package uses siftTimes 20, Matlab uses no limit

End condition for spline

Iterated sifting process, used to produce either an IMF or a residual.

The result of a sifting operation. Each sift either yields a residual, or a new IMF.

Returns cubic splines of local minimums and maximums. Returns Nothing if there are not enough local minimum or maximums to create the splines.