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.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.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, **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 –

  • 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.