rdkit.Chem.Draw.SimilarityMaps module

rdkit.Chem.Draw.SimilarityMaps.GetAPFingerprint(mol, atomId=-1, fpType='normal', nBits=2048, minLength=1, maxLength=30, nBitsPerEntry=4, **kwargs)

Calculates the atom pairs fingerprint with the torsions of atomId removed.

Parameters:

  • interest (mol -- the molecule of)

  • for (atomId -- the atom to remove the pairs)

  • fingerprint (fpType -- the type of AP)

  • vector (nBits -- the size of the bit)

  • pair (nBitsPerEntry -- the number of bits available for each)

  • pair

  • pair

rdkit.Chem.Draw.SimilarityMaps.GetAtomicWeightsForFingerprint(refMol, probeMol, fpFunction, metric=<Boost.Python.function object>)

Calculates the atomic weights for the probe molecule based on a fingerprint function and a metric.

Parameters:

  • molecule (probeMol -- the probe)

  • molecule

  • function (fpFunction -- the fingerprint)

  • metric (metric -- the similarity)

Note

If fpFunction needs additional parameters, use a lambda construct

rdkit.Chem.Draw.SimilarityMaps.GetAtomicWeightsForFingerprintGenerator(refMol, probeMol, fpg, useCounts=False, metric=<Boost.Python.function object>)

Calculates the atomic weights for the probe molecule based on a fingerprint function and a metric.

Parameters:

  • molecule (probeMol -- the probe)

  • molecule

  • generator (fpg -- the fingerprint)

  • metric (metric -- the similarity)

rdkit.Chem.Draw.SimilarityMaps.GetAtomicWeightsForModel(probeMol, fpFunction, predictionFunction)

Calculates the atomic weights for the probe molecule based on a fingerprint function and the prediction function of a ML model.

Parameters:

  • molecule (probeMol -- the probe)

  • function (fpFunction -- the fingerprint)

  • model (predictionFunction -- the prediction function of the ML)

rdkit.Chem.Draw.SimilarityMaps.GetMorganFingerprint(mol, atomId=-1, radius=2, fpType='bv', nBits=2048, useFeatures=False, **kwargs)

Calculates the Morgan fingerprint with the environments of atomId removed.

Parameters:

  • interest (mol -- the molecule of)

  • radius (radius -- the maximum)

  • fingerprint (fpType -- the type of Morgan) – ‘count’ or ‘bv’

  • for (atomId -- the atom to remove the environments)

  • vector (nBits -- the size of the bit)

  • false (useFeatures -- if) – ConnectivityMorgan, if true: FeatureMorgan

any additional keyword arguments will be passed to the fingerprinting function.

rdkit.Chem.Draw.SimilarityMaps.GetRDKFingerprint(mol, atomId=-1, fpType='bv', nBits=2048, minPath=1, maxPath=5, nBitsPerHash=2, **kwargs)

Calculates the RDKit fingerprint with the paths of atomId removed.

Parameters:

  • interest (mol -- the molecule of)

  • for (atomId -- the atom to remove the paths)

  • fingerprint (fpType -- the type of RDKit) – ‘bv’

  • vector (nBits -- the size of the bit)

  • length (maxPath -- maximum path)

  • length

  • path (nBitsPerHash -- number of to set per)

rdkit.Chem.Draw.SimilarityMaps.GetSimilarityMapForFingerprint(refMol, probeMol, fpFunction, draw2d, metric=<Boost.Python.function object>, **kwargs)

Generates the similarity map for a given reference and probe molecule, fingerprint function and similarity metric.

Parameters:

  • molecule (probeMol -- the probe)

  • molecule

  • function (fpFunction -- the fingerprint)

  • metric. (metric -- the similarity)

  • drawing (kwargs -- additional arguments for)

rdkit.Chem.Draw.SimilarityMaps.GetSimilarityMapForFingerprintGenerator(refMol, probeMol, fpg, draw2d, metric=<Boost.Python.function object>, useCounts=False, **kwargs)

Generates the similarity map for a given reference and probe molecule, fingerprint function and similarity metric.

Parameters:

  • molecule (probeMol -- the probe)

  • molecule

  • generator (fpg -- the fingerprint)

  • metric. (metric -- the similarity)

  • drawing (kwargs -- additional arguments for)

rdkit.Chem.Draw.SimilarityMaps.GetSimilarityMapForModel(probeMol, fpFunction, predictionFunction, draw2d, **kwargs)

Generates the similarity map for a given ML model and probe molecule, and fingerprint function.

Parameters:

  • molecule (probeMol -- the probe)

  • function (fpFunction -- the fingerprint)

  • model (predictionFunction -- the prediction function of the ML)

  • drawing (kwargs -- additional arguments for)

rdkit.Chem.Draw.SimilarityMaps.GetSimilarityMapFromWeights(mol, weights, draw2d, colorMap=None, scale=-1, size=(250, 250), sigma=None, coordScale=1.5, step=0.01, colors='k', contourLines=10, alpha=0.5, gridResolution=0.1, extraGridPadding=0.5, useFillThreshold=False, fillThreshold=0.01, fillThresholdIsFraction=True, **kwargs)

Generates the similarity map for a molecule given the atomic weights.

Parameters:

  • interest (mol -- the molecule of)

  • use (weights -- the weights to)

  • object (draw2d -- the RDKit drawing)

  • scheme (colorMap -- the matplotlib color map)

  • map (default is custom PiWG color)

  • scaling (scale -- the) – scale < 0 -> the absolute maximum weight is used as maximum scale scale = double -> this is the maximum scale

  • figure (size -- the size of the)

  • Gaussians (sigma -- the sigma for the)

  • coordinates (coordScale -- scaling factor for the)

  • calcAtomGaussian (step -- the step for)

  • lines (alpha -- the alpha blending value for the contour)

  • N (contourLines -- if integer number) – N contour lines are drawn if list(numbers): contour lines at these numbers are drawn

  • lines

  • grid (extraGridPadding -- the extra padding of the)

  • grid

  • filled (useFillThreshold -- use a magnitude threshold to determine if a grid box is)

  • boxes (fillThreshold -- the magnitude threshold for filling grid)

  • True (fillThresholdIsFraction -- if)

  • range (the fillThreshold is a fraction of the data)

  • drawing (kwargs -- additional arguments for)

rdkit.Chem.Draw.SimilarityMaps.GetStandardizedWeights(weights)

Normalizes the weights, such that the absolute maximum weight equals 1.0.

Parameters:

weights (weights -- the list with the atomic)

rdkit.Chem.Draw.SimilarityMaps.GetTTFingerprint(mol, atomId=-1, fpType='normal', nBits=2048, targetSize=4, nBitsPerEntry=4, **kwargs)

Calculates the topological torsion fingerprint with the pairs of atomId removed.

Parameters:

  • interest (mol -- the molecule of)

  • for (atomId -- the atom to remove the torsions)

  • fingerprint (fpType -- the type of TT)

  • vector (nBits -- the size of the bit)

  • pair (maxLength -- the maxmimum path length for an atom)

  • pair

  • torsion (nBitsPerEntry -- the number of bits available for each)

any additional keyword arguments will be passed to the fingerprinting function.