Contains classes and functions related to the generation and processing of pharmacophore and molecule descriptors. More...

Classes
class	AtomAutoCorrelation3DVectorCalculator
	AutoCorrelation3DVectorCalculator implementation for the calculation of atom-centered 3D auto-correlation vectors of chemical structures. More...

class	AtomRDFCodeCalculator
	RDFCodeCalculator implementation for the calculation of atom-centered radial distribution function (RDF) codes of chemical structures. More...

class	AutoCorrelation2DVectorCalculator
	Calculation of the topological (2D) auto-correlation vector of a molecular graph. More...

class	AutoCorrelation3DVectorCalculator
	Generic implementation of the 3D auto-correlation vector calculation for sequences of entities of arbitrary type. More...

class	BCUTDescriptorCalculator
	Calculation of the BCUT (Burden-CAS-University-of-Texas) descriptor of a molecular graph. More...

class	BulkSimilarityCalculator
	Calculator that performs a bulk pairwise comparison of a single query descriptor against a stored set of target descriptors using a configurable similarity function. More...

class	BurdenMatrixGenerator
	Calculation of the Burden matrix of a molecular graph. More...

class	CircularFingerprintGenerator
	Generation of atom-centered circular substructure fingerprints in the spirit of SciTegic's Extended Connectivity Fingerprints (ECFP). More...

class	FeatureAutoCorrelation3DVectorCalculator
	AutoCorrelation3DVectorCalculator specialization for feature-centered 3D auto-correlation vectors of pharmacophores. More...

class	FeatureRDFCodeCalculator
	RDFCodeCalculator implementation for the calculation of feature-centered radial distribution function (RDF) codes of pharmacophores. More...

class	KuvekPocketDescriptorCalculator
	Implements the algorithm devised by Kuvek et al. [KBPD] for the calculation of receptor binding pocket shape and surface electrostatics descriptors. More...

class	MACCSFingerprintGenerator
	Generation of 166 bit MACCS key fingerprints. More...

class	MolecularComplexityCalculator
	Calculation of the molecular complexity of a molecular graph after Hendrickson, Huang and Toczko. More...

class	MoleculeAutoCorr2DDescriptorCalculator
	Calculation of a topological (2D) auto-correlation descriptor of a molecular graph partitioned by specific atom types. More...

class	MoleculeAutoCorr3DDescriptorCalculator
	Calculation of a 3D auto-correlation descriptor of a molecular graph partitioned by specific atom types. More...

class	MoleculeRDFDescriptorCalculator
	Calculation of an RDF descriptor of a molecular graph partitioned by specific atom types. More...

class	NPoint2DPharmacophoreFingerprintGenerator
	N-point pharmacophore fingerprint generator that uses topological feature distances. More...

class	NPoint3DPharmacophoreFingerprintGenerator
	N-point pharmacophore fingerprint generator that uses spatial 3D feature distances. More...

class	NPointPharmacophoreFingerprintGenerator
	Abstract base for N-point pharmacophore fingerprint generators. More...

class	PathFingerprintGenerator
	Generation of Daylight-style path fingerprints of molecular graphs. More...

class	PharmacophoreAutoCorr3DDescriptorCalculator
	Calculation of a 3D auto-correlation descriptor of a pharmacophore partitioned by specific feature types. More...

class	PharmacophoreRDFDescriptorCalculator
	Calculation of an RDF descriptor of a pharmacophore partitioned by specific feature types. More...

class	PubChemFingerprintGenerator
	Generation of 881 bit PubChem fingerprints. More...

class	RDFCodeCalculator
	Generic implementation of the radial distribution function (RDF) code calculation for sequences of entities of arbitrary type. More...

class	TanimotoSimilarity
	Functor class for calculating Tanimoto Similarities [CITB] of bitsets and vectors. More...

class	CosineSimilarity
	Functor class for calculating Cosine Similarities [WCOS] of bitsets and vectors. More...

class	EuclideanSimilarity
	Functor class for calculating the Euclidean Similarity [GSIM] of bitsets. More...

class	ManhattanSimilarity
	Functor class for calculating the Manhattan Similarity [GSIM] of bitsets. More...

class	DiceSimilarity
	Functor class for calculating the Dice Similarity [GSIM] of bitsets. More...

class	TverskySimilarity
	Functor class for calculating the Tversky Similarity [GSIM] of bitsets. More...

class	HammingDistance
	Functor class for calculating the Hamming Distance [WHAM, CITB] between bitsets. More...

class	ManhattanDistance
	Functor class for calculating the Manhattan Distance [MADI] between bitsets and vectors. More...

class	EuclideanDistance
	Functor class for calculating the Euclidean Distance [CITB] between bitsets and vectors. More...

Functions
CDPL_DESCR_API double	calcGeometricalRadius (const Chem::AtomContainer &cntnr, const Chem::Atom3DCoordinatesFunction &coords_func)
	Calculates the geometrical radius of the atoms in cntnr. More...

CDPL_DESCR_API double	calcGeometricalDiameter (const Chem::AtomContainer &cntnr, const Chem::Atom3DCoordinatesFunction &coords_func)
	Calculates the geometrical diameter of the atoms in cntnr. More...

CDPL_DESCR_API double	calcGeometricalRadius (const Chem::Entity3DContainer &cntnr)
	Calculates the geometrical radius of the entities in cntnr. More...

CDPL_DESCR_API double	calcGeometricalDiameter (const Chem::Entity3DContainer &cntnr)
	Calculates the geometrical diameter of the entities in cntnr. More...

CDPL_DESCR_API std::size_t	calcTopologicalRadius (const Chem::MolecularGraph &molgraph)
	Calculates the topological radius (minimum atom eccentricity) of molgraph. More...

CDPL_DESCR_API std::size_t	calcTopologicalDiameter (const Chem::MolecularGraph &molgraph)
	Calculates the topological diameter (maximum atom-pair topological distance) of molgraph. More...

CDPL_DESCR_API double	calcRingComplexity (const Chem::MolecularGraph &molgraph)
	Calculates the ring complexity of molgraph. More...

CDPL_DESCR_API double	calcMolecularComplexity (const Chem::MolecularGraph &molgraph)
	Calculates the molecular complexity of molgraph (Hendrickson, Huang and Toczko). More...

CDPL_DESCR_API double	calcKierShape1 (const Chem::MolecularGraph &molgraph)
	Calculates the first Kier shape index ( \( \kappa_1 \)) of molgraph. More...

CDPL_DESCR_API double	calcKierShape2 (const Chem::MolecularGraph &molgraph)
	Calculates the second Kier shape index ( \( \kappa_2 \)) of molgraph. More...

CDPL_DESCR_API double	calcKierShape3 (const Chem::MolecularGraph &molgraph)
	Calculates the third Kier shape index ( \( \kappa_3 \)) of molgraph. More...

CDPL_DESCR_API std::size_t	calcWienerIndex (const Chem::MolecularGraph &molgraph)
	Calculates the Wiener index of molgraph. More...

CDPL_DESCR_API double	calcRandicIndex (const Chem::MolecularGraph &molgraph)
	Calculates the Randic connectivity index of molgraph. More...

CDPL_DESCR_API std::size_t	calcZagrebIndex1 (const Chem::MolecularGraph &molgraph)
	Calculates the first Zagreb index ( \( M_1 \)) of molgraph. More...

CDPL_DESCR_API std::size_t	calcZagrebIndex2 (const Chem::MolecularGraph &molgraph)
	Calculates the second Zagreb index ( \( M_2 \)) of molgraph. More...

CDPL_DESCR_API std::size_t	calcTotalWalkCount (const Chem::MolecularGraph &molgraph)
	Calculates the total walk count of molgraph. More...

CDPL_DESCR_API double	calcTanimotoSimilarity (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Tanimoto Similarity [CITB] of the bitsets bs1 and bs2. More...

template<typename V >
double	calcTanimotoSimilarity (const V &v1, const V &v2)
	Calculates the Tanimoto Similarity [CITB] of the vectors v1 and v2. More...

CDPL_DESCR_API double	calcCosineSimilarity (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Cosine Similarity [WCOS] of the bitsets bs1 and bs2. More...

template<typename V >
double	calcCosineSimilarity (const V &v1, const V &v2)
	Calculates the Cosine Similarity [WCOS] of the vectors v1 and v2. More...

CDPL_DESCR_API double	calcEuclideanSimilarity (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Euclidean Similarity [GSIM] of the bitsets bs1 and bs2. More...

CDPL_DESCR_API double	calcManhattanSimilarity (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Manhattan Similarity [GSIM] of the bitsets bs1 and bs2. More...

CDPL_DESCR_API double	calcDiceSimilarity (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Dice Similarity [GSIM] of the bitsets bs1 and bs2. More...

CDPL_DESCR_API double	calcTverskySimilarity (const Util::BitSet &bs1, const Util::BitSet &bs2, double a, double b)
	Calculates the Tversky Similarity [GSIM] of the bitsets bs1 and bs2. More...

CDPL_DESCR_API std::size_t	calcHammingDistance (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Hamming Distance [WHAM, CITB] between the bitsets bs1 and bs2. More...

template<typename V >
double	calcManhattanDistance (const V &v1, const V &v2)
	Calculates the Manhattan Distance [MADI] between the vectors v1 and v2. More...

CDPL_DESCR_API double	calcEuclideanDistance (const Util::BitSet &bs1, const Util::BitSet &bs2)
	Calculates the Euclidean Distance [CITB] between the bitsets bs1 and bs2. More...

template<typename V >
double	calcEuclideanDistance (const V &v1, const V &v2)
	Calculates the Euclidean Distance [CITB] between the vectors v1 and v2. More...

Detailed Description

Contains classes and functions related to the generation and processing of pharmacophore and molecule descriptors.

Function Documentation

◆ calcGeometricalRadius() [1/2]

CDPL_DESCR_API double CDPL::Descr::calcGeometricalRadius	(	const Chem::AtomContainer &	cntnr,
		const Chem::Atom3DCoordinatesFunction &	coords_func
	)

Calculates the geometrical radius of the atoms in cntnr.

The geometrical radius is the minimum, taken over all atoms, of the maximum distance from a given atom to any other atom in the container. If cntnr contains at most one atom, 0 is returned.

Parameters

cntnr	The container with the atoms for which to calculate the geometrical radius.
coords_func	A function that provides the 3D coordinates of an atom.

Returns: The calculated geometrical radius.

◆ calcGeometricalDiameter() [1/2]

CDPL_DESCR_API double CDPL::Descr::calcGeometricalDiameter	(	const Chem::AtomContainer &	cntnr,
		const Chem::Atom3DCoordinatesFunction &	coords_func
	)

Calculates the geometrical diameter of the atoms in cntnr.

The geometrical diameter is the maximum distance between any pair of atoms in the container. If cntnr contains at most one atom, 0 is returned.

Parameters

cntnr	The container with the atoms for which to calculate the geometrical diameter.
coords_func	A function that provides the 3D coordinates of an atom.

Returns: The calculated geometrical diameter.

◆ calcGeometricalRadius() [2/2]

CDPL_DESCR_API double CDPL::Descr::calcGeometricalRadius ( const Chem::Entity3DContainer & cntnr )

Calculates the geometrical radius of the entities in cntnr.

The geometrical radius is the minimum, taken over all entities, of the maximum distance from a given entity to any other entity in the container. If cntnr contains at most one entity, 0 is returned.

Parameters

cntnr The container with the 3D entities for which to calculate the geometrical radius.

Returns: The calculated geometrical radius.

◆ calcGeometricalDiameter() [2/2]

CDPL_DESCR_API double CDPL::Descr::calcGeometricalDiameter ( const Chem::Entity3DContainer & cntnr )

Calculates the geometrical diameter of the entities in cntnr.

The geometrical diameter is the maximum distance between any pair of entities in the container. If cntnr contains at most one entity, 0 is returned.

Parameters

cntnr The container with the 3D entities for which to calculate the geometrical diameter.

Returns: The calculated geometrical diameter.

◆ calcTopologicalRadius()

CDPL_DESCR_API std::size_t CDPL::Descr::calcTopologicalRadius ( const Chem::MolecularGraph & molgraph )

Calculates the topological radius (minimum atom eccentricity) of molgraph.

Parameters

molgraph The molecular graph.

Returns: The topological radius.

◆ calcTopologicalDiameter()

CDPL_DESCR_API std::size_t CDPL::Descr::calcTopologicalDiameter ( const Chem::MolecularGraph & molgraph )

Calculates the topological diameter (maximum atom-pair topological distance) of molgraph.

Parameters

molgraph The molecular graph.

Returns: The topological diameter.

◆ calcRingComplexity()

CDPL_DESCR_API double CDPL::Descr::calcRingComplexity ( const Chem::MolecularGraph & molgraph )

Calculates the ring complexity of molgraph.

Parameters

molgraph The molecular graph.

Returns: The calculated ring complexity.

◆ calcMolecularComplexity()

CDPL_DESCR_API double CDPL::Descr::calcMolecularComplexity ( const Chem::MolecularGraph & molgraph )

Calculates the molecular complexity of molgraph (Hendrickson, Huang and Toczko).

Parameters

molgraph The molecular graph.

Returns: The calculated molecular complexity.

See also: [MCPLX]

◆ calcKierShape1()

CDPL_DESCR_API double CDPL::Descr::calcKierShape1 ( const Chem::MolecularGraph & molgraph )

Calculates the first Kier shape index ( \( \kappa_1 \)) of molgraph.

Parameters

molgraph The molecular graph.

Returns: The calculated Kier shape index \( \kappa_1 \).

◆ calcKierShape2()

CDPL_DESCR_API double CDPL::Descr::calcKierShape2 ( const Chem::MolecularGraph & molgraph )

Calculates the second Kier shape index ( \( \kappa_2 \)) of molgraph.

Parameters

molgraph The molecular graph.

Returns: The calculated Kier shape index \( \kappa_2 \).

◆ calcKierShape3()

CDPL_DESCR_API double CDPL::Descr::calcKierShape3 ( const Chem::MolecularGraph & molgraph )

Calculates the third Kier shape index ( \( \kappa_3 \)) of molgraph.

Parameters

molgraph The molecular graph.

Returns: The calculated Kier shape index \( \kappa_3 \).

◆ calcWienerIndex()

CDPL_DESCR_API std::size_t CDPL::Descr::calcWienerIndex ( const Chem::MolecularGraph & molgraph )

Calculates the Wiener index of molgraph.

The Wiener index is the sum of the topological distances over all pairs of heavy atoms.

Parameters

molgraph The molecular graph.

Returns: The Wiener index.

◆ calcRandicIndex()

CDPL_DESCR_API double CDPL::Descr::calcRandicIndex ( const Chem::MolecularGraph & molgraph )

Calculates the Randic connectivity index of molgraph.

Parameters

molgraph The molecular graph.

Returns: The Randic index.

◆ calcZagrebIndex1()

CDPL_DESCR_API std::size_t CDPL::Descr::calcZagrebIndex1 ( const Chem::MolecularGraph & molgraph )

Calculates the first Zagreb index ( \( M_1 \)) of molgraph.

\( M_1 \) is the sum of squared heavy atom degrees over all heavy atoms.

Parameters

molgraph The molecular graph.

Returns: The first Zagreb index.

◆ calcZagrebIndex2()

CDPL_DESCR_API std::size_t CDPL::Descr::calcZagrebIndex2 ( const Chem::MolecularGraph & molgraph )

Calculates the second Zagreb index ( \( M_2 \)) of molgraph.

\( M_2 \) is the sum of the products of the heavy atom degrees over all heavy bonds.

Parameters

molgraph The molecular graph.

Returns: The second Zagreb index.

◆ calcTotalWalkCount()

CDPL_DESCR_API std::size_t CDPL::Descr::calcTotalWalkCount ( const Chem::MolecularGraph & molgraph )

Calculates the total walk count of molgraph.

Parameters

molgraph The molecular graph.

Returns: The total walk count.

◆ calcTanimotoSimilarity() [1/2]

CDPL_DESCR_API double CDPL::Descr::calcTanimotoSimilarity	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Tanimoto Similarity [CITB] of the bitsets bs1 and bs2.

The Tanimoto Similarity \( S_{ab} \) is calculated by:

\[ S_{ab} = \frac{N_{ab}}{N_a + N_b - N_{ab}} \]

where \( N_{ab} \) is the number of bits that are set in both bitsets, \( N_a \) is the number of bits that are set in the first bitset and \( N_b \) is the number of bits that are set in the second bitset.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated similarity measure.

◆ calcTanimotoSimilarity() [2/2]

template<typename V >

double CDPL::Descr::calcTanimotoSimilarity	(	const V &	v1,
		const V &	v2
	)

inline

Calculates the Tanimoto Similarity [CITB] of the vectors v1 and v2.

The Tanimoto Similarity \( S_{12} \) is calculated by:

\[ S_{12} = \frac{\vec{v}_1 \cdot \vec{v}_2}{{\left \| \vec{v}_1 \right \|}^2 + {\left \| \vec{v}_2 \right \|}^2 - \vec{v}_1 \cdot \vec{v}_2} \]

Parameters

v1	The first vector.
v2	The second vector.

Returns: The calculated similarity measure.

Since: 1.2.3

◆ calcCosineSimilarity() [1/2]

CDPL_DESCR_API double CDPL::Descr::calcCosineSimilarity	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Cosine Similarity [WCOS] of the bitsets bs1 and bs2.

The Cosine Similarity \( S_{ab} \) is calculated by:

\[ S_{ab} = \frac{N_{ab}}{\sqrt{N_a \: N_b}} \]

where \( N_{ab} \) is the number of bits that are set in both bitsets, \( N_a \) is the number of bits that are set in the first bitset and \( N_b \) is the number of bits that are set in the second bitset.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated similarity measure.

◆ calcCosineSimilarity() [2/2]

template<typename V >

double CDPL::Descr::calcCosineSimilarity	(	const V &	v1,
		const V &	v2
	)

inline

Calculates the Cosine Similarity [WCOS] of the vectors v1 and v2.

The Cosine Similarity \( S_{12} \) is calculated by:

\[ S_{12} = \frac{\vec{v}_1 \cdot \vec{v}_2}{{\left \| \vec{v}_1 \right \|}{\left \| \vec{v}_2 \right \|}} \]

Parameters

v1	The first vector.
v2	The second vector.

Returns: The calculated similarity measure.

Since: 1.2.3

◆ calcEuclideanSimilarity()

CDPL_DESCR_API double CDPL::Descr::calcEuclideanSimilarity	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Euclidean Similarity [GSIM] of the bitsets bs1 and bs2.

The Euclidean Similarity \( S_{ab} \) is calculated by:

\[ S_{ab} = \sqrt{\frac{N_{ab} + N_{!ab}}{N_a + N_b + N_{ab} + N_{!ab}}} \]

where \( N_{ab} \) is the number of bits that are set in both bitsets, \( N_a \) is the number of bits that are set only in the first bitset, \( N_b \) is the number of bits that are set only in the second bitset and \( N_{!ab} \) is the number of bits that are not set in both bitsets.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated similarity measure.

◆ calcManhattanSimilarity()

CDPL_DESCR_API double CDPL::Descr::calcManhattanSimilarity	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Manhattan Similarity [GSIM] of the bitsets bs1 and bs2.

The Manhattan Similarity \( S_{ab} \) is calculated by:

\[ S_{ab} = 1 - \frac{N_a + N_b}{N_a + N_b + N_{ab} + N_{!ab}} \]

where \( N_{ab} \) is the number of bits that are set in both bitsets, \( N_a \) is the number of bits that are set only in the first bitset, \( N_b \) is the number of bits that are set only in the second bitset and \( N_{!ab} \) is the number of bits that are not set in both bitsets.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated similarity measure.

◆ calcDiceSimilarity()

CDPL_DESCR_API double CDPL::Descr::calcDiceSimilarity	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Dice Similarity [GSIM] of the bitsets bs1 and bs2.

The Dice Similarity \( S_{ab} \) is calculated by:

\[ S_{ab} = \frac{2 \: N_{ab}}{N_a + N_b + 2 \: N_{ab}} \]

where \( N_{ab} \) is the number of bits that are set in both bitsets, \( N_a \) is the number of bits that are only set in the first bitset and \( N_b \) is the number of bits that are only set in the second bitset.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated similarity measure.

◆ calcTverskySimilarity()

CDPL_DESCR_API double CDPL::Descr::calcTverskySimilarity	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2,
		double	a,
		double	b
	)

Calculates the Tversky Similarity [GSIM] of the bitsets bs1 and bs2.

The Tversky Similarity \( S_{ab} \) is calculated by:

\[ S_{ab} = \frac{N_{ab}}{\alpha \: N_a + \beta \: N_b + N_{ab}} \]

where \( N_{ab} \) is the number of bits that are set in both bitsets, \( N_a \) is the number of bits that are only set in the first bitset and \( N_b \) is the number of bits that are only set in the second bitset. \( \alpha \) and \( \beta \) are bitset contribution weighting factors.

The Tversky measure is asymmetric. Setting the parameters \( \alpha = \beta = 1.0 \) makes it identical to the Tanimoto measure.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.
a	Weights the contribution of the first bitset.
b	Weights the contribution of the second bitset.

Returns: The calculated similarity measure.

◆ calcHammingDistance()

CDPL_DESCR_API std::size_t CDPL::Descr::calcHammingDistance	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Hamming Distance [WHAM, CITB] between the bitsets bs1 and bs2.

The Hamming Distance \( D_{ab} \) is calculated by:

\[ D_{ab} = N_a + N_b \]

where \( N_a \) is the number of bits that are set in the first bitset but not in the second bitset and \( N_b \) is the number of bits that are set in the second bitset but not in the first one.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated distance.

◆ calcManhattanDistance()

template<typename V >

double CDPL::Descr::calcManhattanDistance	(	const V &	v1,
		const V &	v2
	)

inline

Calculates the Manhattan Distance [MADI] between the vectors v1 and v2.

The Manhattan Distance \( D_{12} \) is calculated by:

\[ D_{12} = {\left \| \vec{v}_1 - \vec{v}_2 \right \|}_1 \]

Parameters

v1	The first vector.
v2	The second vector.

Returns: The calculated distance measure.

Since: 1.2.3

◆ calcEuclideanDistance() [1/2]

CDPL_DESCR_API double CDPL::Descr::calcEuclideanDistance	(	const Util::BitSet &	bs1,
		const Util::BitSet &	bs2
	)

Calculates the Euclidean Distance [CITB] between the bitsets bs1 and bs2.

The Euclidean Distance \( D_{ab} \) is calculated by:

\[ D_{ab} = \sqrt{N_a + N_b} \]

where \( N_a \) is the number of bits that are set in the first bitset but not in the second bitset and \( N_b \) is the number of bits that are set in the second bitset but not in the first one.

If the specified bitsets bs1 and bs2 are of different size, missing bits at the end of the smaller bitset are assumed to be zero.

Parameters

bs1	The first bitset.
bs2	The second bitset.

Returns: The calculated distance.

◆ calcEuclideanDistance() [2/2]

template<typename V >

double CDPL::Descr::calcEuclideanDistance	(	const V &	v1,
		const V &	v2
	)

inline

Calculates the Euclidean Distance [CITB] between the vectors v1 and v2.

The Euclidean Distance \( D_{12} \) is calculated by:

\[ D_{12} = {\left \| \vec{v}_1 - \vec{v}_2 \right \|} \]

Parameters

v1	The first vector.
v2	The second vector.

Returns: The calculated distance measure.

Since: 1.2.3

Classes

Functions

Detailed Description

Function Documentation

◆ calcGeometricalRadius() [1/2]

◆ calcGeometricalDiameter() [1/2]

◆ calcGeometricalRadius() [2/2]

◆ calcGeometricalDiameter() [2/2]

◆ calcTopologicalRadius()

◆ calcTopologicalDiameter()

◆ calcRingComplexity()

◆ calcMolecularComplexity()

◆ calcKierShape1()

◆ calcKierShape2()

◆ calcKierShape3()

◆ calcWienerIndex()

◆ calcRandicIndex()

◆ calcZagrebIndex1()

◆ calcZagrebIndex2()

◆ calcTotalWalkCount()

◆ calcTanimotoSimilarity() [1/2]

◆ calcTanimotoSimilarity() [2/2]

◆ calcCosineSimilarity() [1/2]

◆ calcCosineSimilarity() [2/2]

◆ calcEuclideanSimilarity()

◆ calcManhattanSimilarity()

◆ calcDiceSimilarity()

◆ calcTverskySimilarity()

◆ calcHammingDistance()

◆ calcManhattanDistance()

◆ calcEuclideanDistance() [1/2]

◆ calcEuclideanDistance() [2/2]