ComplexityDecomposition.nb

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Tisean Plotting Routines - Calculate Entropies and Excess Entropy from TISEAN \
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The h2 files contain the entropy rate\
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The main Function is DecomposeAndPlotExcessEntropy, see below\
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Theoretically for a D-dim attractor with D=Floor[D] + \[Delta]D
we should have
\[Delta]h = - (1 - \[Delta]D) log \[Epsilon] if m = Floor[D]
\[Delta]h = - \[Delta]D log \[Epsilon] if m = Floor[D]+1
See DecomposeAndPlotExcessEntropy2m\
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In the real data we find often more than 2 \[Delta]h with a significant \
nonzero incline, so that we use a set of \[Delta]h that are eps - dependent\
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Slice is a vertical slice though the data (see \
DataWithFitsAndDerivativesTagged) , so we have
{{{x, y\[CloseCurlyQuote], dy\[CloseCurlyQuote]/dx,y}, True | \
False(fitted),True | False(extrapolated), prevStraight}, { ...}}
for the same x, Length[slice]=max_m
assignedMRange is one element of the output of AssignMRangeToStochasticRanges \
(which \[Delta]H-range is  eps-dependent etc)
Output: {x,state,middle,memory,excess_raw, RulesforQualityValues}
state+middle+memory is the excess entropy (from fits). The excess entropy \
from raw data is in excess_raw)
MiddleFitted tells whether the components of the middle sum are fitted or not\
\
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