rdkit.Chem.Draw.SimilarityMaps

Package rdkit :: Package Chem :: Package Draw :: Module SimilarityMaps |
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# Module SimilarityMaps

source code

Functions | [hide private]
GetAtomicWeightsForFingerprint(refMol, probeMol, fpFunction, metric=<Boost.Python.function object at 0x27a3170>) Calculates the atomic weights for the probe molecule based on a fingerprint function and a metric. | source code
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. | source code
GetStandardizedWeights(weights) Normalizes the weights, such that the absolute maximum weight equals 1.0. | source code
GetSimilarityMapFromWeights(mol, weights, 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. | source code
GetSimilarityMapForFingerprint(refMol, probeMol, fpFunction, metric=<Boost.Python.function object at 0x27a3170>, **kwargs) Generates the similarity map for a given reference and probe molecule, fingerprint function and similarity metric. | source code
GetSimilarityMapForModel(probeMol, fpFunction, predictionFunction, **kwargs) Generates the similarity map for a given ML model and probe molecule, and fingerprint function. | source code
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. | source code
GetTTFingerprint(mol, atomId=-1, fpType=`'``normal``'`, nBits=2048, targetSize=4, nBitsPerEntry=4, **kwargs) Calculates the topological torsion fingerprint with the pairs of atomId removed. | source code
GetMorganFingerprint(mol, atomId=-1, radius=2, fpType=`'``bv``'`, nBits=2048, useFeatures=False, **kwargs) Calculates the Morgan fingerprint with the environments of atomId removed. | source code
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. | source code

Variables | [hide private]
| apDict = `{}`
| ttDict = `{}`
| __package__ = ``'``rdkit.Chem.Draw``'``

Imports: copy, math, cm, LinearSegmentedColormap, numpy, Chem, DataStructs, Draw, rdMD, iteritems

Function Details | [hide private]

### GetAtomicWeightsForFingerprint(refMol, probeMol, fpFunction, metric=<Boost.Python.function object at 0x27a3170>) | source code
    Calculates the atomic weights for the probe molecule
    based on a fingerprint function and a metric.

    Parameters:
      refMol -- the reference molecule
      probeMol -- the probe molecule
      fpFunction -- the fingerprint function
      metric -- the similarity metric

    Note:
      If fpFunction needs additional parameters, use a lambda construct

### GetAtomicWeightsForModel(probeMol, fpFunction, predictionFunction) | source code
    Calculates the atomic weights for the probe molecule based on
    a fingerprint function and the prediction function of a ML model.

    Parameters:
      probeMol -- the probe molecule
      fpFunction -- the fingerprint function
      predictionFunction -- the prediction function of the ML model

### GetStandardizedWeights(weights) | source code
    Normalizes the weights,
    such that the absolute maximum weight equals 1.0.

    Parameters:
      weights -- the list with the atomic weights

### GetSimilarityMapFromWeights(mol, weights, colorMap=None, scale=-1, size=`(`250`,` 250`)`, sigma=None, coordScale=1.5, step=0.01, colors=`'``k``'`, contourLines=10, alpha=0.5, **kwargs) | source code
    Generates the similarity map for a molecule given the atomic weights.

    Parameters:
      mol -- the molecule of interest
      colorMap -- the matplotlib color map scheme, default is custom PiWG color map
      scale -- the scaling: scale < 0 -> the absolute maximum weight is used as maximum scale
                            scale = double -> this is the maximum scale
      size -- the size of the figure
      sigma -- the sigma for the Gaussians
      coordScale -- scaling factor for the coordinates
      step -- the step for calcAtomGaussian
      colors -- color of the contour lines
      contourLines -- if integer number N: N contour lines are drawn
                      if list(numbers): contour lines at these numbers are drawn
      alpha -- the alpha blending value for the contour lines
      kwargs -- additional arguments for drawing

### GetSimilarityMapForFingerprint(refMol, probeMol, fpFunction, metric=<Boost.Python.function object at 0x27a3170>, **kwargs) | source code
    Generates the similarity map for a given reference and probe molecule,
    fingerprint function and similarity metric.

    Parameters:
      refMol -- the reference molecule
      probeMol -- the probe molecule
      fpFunction -- the fingerprint function
      metric -- the similarity metric.
      kwargs -- additional arguments for drawing

### GetSimilarityMapForModel(probeMol, fpFunction, predictionFunction, **kwargs) | source code
    Generates the similarity map for a given ML model and probe molecule,
    and fingerprint function.

    Parameters:
      probeMol -- the probe molecule
      fpFunction -- the fingerprint function
      predictionFunction -- the prediction function of the ML model
      kwargs -- additional arguments for drawing

### GetAPFingerprint(mol, atomId=-1, fpType=`'``normal``'`, nBits=2048, minLength=1, maxLength=30, nBitsPerEntry=4, **kwargs) | source code
    Calculates the atom pairs fingerprint with the torsions of atomId removed.

    Parameters:
      mol -- the molecule of interest
      atomId -- the atom to remove the pairs for (if -1, no pair is removed)
      fpType -- the type of AP fingerprint ('normal', 'hashed', 'bv')
      nBits -- the size of the bit vector (only for fpType='bv')
      minLength -- the minimum path length for an atom pair
      maxLength -- the maxmimum path length for an atom pair
      nBitsPerEntry -- the number of bits available for each pair

### GetTTFingerprint(mol, atomId=-1, fpType=`'``normal``'`, nBits=2048, targetSize=4, nBitsPerEntry=4, **kwargs) | source code
    Calculates the topological torsion fingerprint with the pairs of atomId removed.

    Parameters:
      mol -- the molecule of interest
      atomId -- the atom to remove the torsions for (if -1, no torsion is removed)
      fpType -- the type of TT fingerprint ('normal', 'hashed', 'bv')
      nBits -- the size of the bit vector (only for fpType='bv')
      minLength -- the minimum path length for an atom pair
      maxLength -- the maxmimum path length for an atom pair
      nBitsPerEntry -- the number of bits available for each torsion

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

### GetMorganFingerprint(mol, atomId=-1, radius=2, fpType=`'``bv``'`, nBits=2048, useFeatures=False, **kwargs) | source code
    Calculates the Morgan fingerprint with the environments of atomId removed.

    Parameters:
      mol -- the molecule of interest
      radius -- the maximum radius
      fpType -- the type of Morgan fingerprint: 'count' or 'bv'
      atomId -- the atom to remove the environments for (if -1, no environments is removed)
      nBits -- the size of the bit vector (only for fpType = 'bv')
      useFeatures -- if false: ConnectivityMorgan, if true: FeatureMorgan

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

### GetRDKFingerprint(mol, atomId=-1, fpType=`'``bv``'`, nBits=2048, minPath=1, maxPath=5, nBitsPerHash=2, **kwargs) | source code
    Calculates the RDKit fingerprint with the paths of atomId removed.

    Parameters:
      mol -- the molecule of interest
      atomId -- the atom to remove the paths for (if -1, no path is removed)
      fpType -- the type of RDKit fingerprint: 'bv'
      nBits -- the size of the bit vector
      minPath -- minimum path length
      maxPath -- maximum path length
      nBitsPerHash -- number of to set per path