RDInfoTheory Namespace Reference

Class used to rank bits based on a specified measure of infomation. More...

Classes
class	BitCorrMatGenerator
class	InfoBitRanker
Typedefs
typedef std::vector < RDKit::USHORT >	USHORT_VECT
typedef std::vector< USHORT_VECT >	VECT_USHORT_VECT
Functions
template<class T>
double	ChiSquare (T *dMat, long int dim1, long int dim2)
template<class T>
double	InfoEntropy (T *tPtr, long int dim)
template<class T>
double	InfoEntropyGain (T *dMat, long int dim1, long int dim2)

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Detailed Description

Class used to rank bits based on a specified measure of infomation.

Basically a primitive mimic of the CombiChem "signal" functionality To use:

• create an instance of this class
• loop over the fingerprints in the dataset by calling accumulateVotes method
• call getTopN to get the top n ranked bits

Sample usage and results from the python wrapper: Here's a small set of vectors: >>> for i,bv in enumerate(bvs): print bv.ToBitString(),acts[i] ... 0001 0 0101 0 0010 1 1110 1

Default ranker, using infogain: >>> ranker = InfoBitRanker(4,2) >>> for i,bv in enumerate(bvs): ranker.AccumulateVotes(bv,acts[i]) ... >>> for bit,gain,n0,n1 in ranker.GetTopN(3): print int(bit),'%.3f'gain,int(n0),int(n1) ... 3 1.000 2 0 2 1.000 0 2 0 0.311 0 1

Using the biased infogain: >>> ranker = InfoBitRanker(4,2,InfoTheory.InfoType.BIASENTROPY) >>> ranker.SetBiasList((1,)) >>> for i,bv in enumerate(bvs): ranker.AccumulateVotes(bv,acts[i]) ... >>> for bit,gain,n0,n1 in ranker.GetTopN(3): print int(bit),'%.3f'gain,int(n0),int(n1) ... 2 1.000 0 2 0 0.311 0 1 1 0.000 1 1

A chi squared ranker is also available: >>> ranker = InfoBitRanker(4,2,InfoTheory.InfoType.CHISQUARE) >>> for i,bv in enumerate(bvs): ranker.AccumulateVotes(bv,acts[i]) ... >>> for bit,gain,n0,n1 in ranker.GetTopN(3): print int(bit),'%.3f'gain,int(n0),int(n1) ... 3 4.000 2 0 2 4.000 0 2 0 1.333 0 1

As is a biased chi squared: >>> ranker = InfoBitRanker(4,2,InfoTheory.InfoType.BIASCHISQUARE) >>> ranker.SetBiasList((1,)) >>> for i,bv in enumerate(bvs): ranker.AccumulateVotes(bv,acts[i]) ... >>> for bit,gain,n0,n1 in ranker.GetTopN(3): print int(bit),'%.3f'gain,int(n0),int(n1) ... 2 4.000 0 2 0 1.333 0 1 1 0.000 1 1

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Typedef Documentation

typedef std::vector<RDKit::USHORT> RDInfoTheory::USHORT_VECT

Definition at line 75 of file InfoBitRanker.h.

typedef std::vector<USHORT_VECT> RDInfoTheory::VECT_USHORT_VECT

Definition at line 76 of file InfoBitRanker.h.

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Function Documentation

template<class T>

double RDInfoTheory::ChiSquare	(	T *	dMat,
		long int	dim1,
		long int	dim2
	)			[inline]

Definition at line 13 of file InfoGainFuncs.h.

template<class T>

double RDInfoTheory::InfoEntropy	(	T *	tPtr,
		long int	dim
	)			[inline]

Definition at line 63 of file InfoGainFuncs.h.

Referenced by InfoEntropyGain().

template<class T>

double RDInfoTheory::InfoEntropyGain	(	T *	dMat,
		long int	dim1,
		long int	dim2
	)			[inline]

Definition at line 83 of file InfoGainFuncs.h.

References InfoEntropy().