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[ Module Hierarchy | Class Hierarchy ]

# Module Hierarchy

- rdkit.Avalon
- rdkit.Chem: A module for molecules and stuff
  - rdkit.Chem.AllChem: Import all RDKit chemistry modules
  - rdkit.Chem.AtomPairs
    - rdkit.Chem.AtomPairs.Pairs: Contains an implementation of Atom-pair fingerprints, as described in:
    - rdkit.Chem.AtomPairs.Sheridan: Contains an implementation of Physicochemical property fingerprints, as described in: Kearsley, S.
    - rdkit.Chem.AtomPairs.Torsions: Contains an implementation of Topological-torsion fingerprints, as described in:
    - rdkit.Chem.AtomPairs.Utils
  - rdkit.Chem.BRICS: Implementation of the BRICS algorithm from Degen et al.
  - rdkit.Chem.BuildFragmentCatalog: command line utility for working with FragmentCatalogs (CASE-type analysis)
  - rdkit.Chem.ChemUtils
    - rdkit.Chem.ChemUtils.AlignDepict
    - rdkit.Chem.ChemUtils.BulkTester
    - rdkit.Chem.ChemUtils.SDFToCSV
    - rdkit.Chem.ChemUtils.TemplateExpand
  - rdkit.Chem.ChemicalFeatures
  - rdkit.Chem.ChemicalForceFields
  - rdkit.Chem.Crippen: Atom-based calculation of LogP and MR using Crippen's approach
  - rdkit.Chem.DSViewer: uses DSViewer to interact with molecules
  - rdkit.Chem.Descriptors
  - rdkit.Chem.Draw
    - rdkit.Chem.Draw.IPythonConsole
    - rdkit.Chem.Draw.MolDrawing
    - rdkit.Chem.Draw.SimilarityMaps
    - rdkit.Chem.Draw.aggCanvas
    - rdkit.Chem.Draw.cairoCanvas
    - rdkit.Chem.Draw.canvasbase
    - rdkit.Chem.Draw.mplCanvas
    - rdkit.Chem.Draw.qtCanvas
    - rdkit.Chem.Draw.spingCanvas
  - rdkit.Chem.EState: A module for Kier and Hall's EState Descriptors
    - rdkit.Chem.EState.AtomTypes: contains SMARTS definitions and calculators for EState atom types
    - rdkit.Chem.EState.EState: Basic EState definitions
    - rdkit.Chem.EState.EState_VSA: Hybrid EState-VSA descriptors (like the MOE VSA descriptors)
    - rdkit.Chem.EState.Fingerprinter: EState fingerprinting
  - rdkit.Chem.FastSDMolSupplier
  - rdkit.Chem.FeatFinderCLI
  - rdkit.Chem.FeatMaps
    - rdkit.Chem.FeatMaps.FeatMapParser
    - rdkit.Chem.FeatMaps.FeatMapPoint
    - rdkit.Chem.FeatMaps.FeatMapUtils
    - rdkit.Chem.FeatMaps.FeatMaps
  - rdkit.Chem.Features
    - rdkit.Chem.Features.FeatDirUtilsRD
    - rdkit.Chem.Features.ShowFeats
  - rdkit.Chem.FilterCatalog
  - rdkit.Chem.Fingerprints
    - rdkit.Chem.Fingerprints.ClusterMols: utility functionality for clustering molecules using fingerprints includes a command line app for clustering
    - rdkit.Chem.Fingerprints.DbFpSupplier: Supplies a class for working with fingerprints from databases...
    - rdkit.Chem.Fingerprints.FingerprintMols: utility functionality for fingerprinting sets of molecules includes a command line app for working with fingerprints and databases
    - rdkit.Chem.Fingerprints.MolSimilarity: utility functionality for molecular similarity includes a command line app for screening databases
    - rdkit.Chem.Fingerprints.SimilarityScreener: class definitions for similarity screening
  - rdkit.Chem.Fraggle
    - rdkit.Chem.Fraggle.FraggleSim
  - rdkit.Chem.FragmentCatalog
  - rdkit.Chem.FragmentMatcher: exposes a class for matching fragments of molecules.
  - rdkit.Chem.Fragments: functions to match a bunch of fragment descriptors from a file
  - rdkit.Chem.FunctionalGroups
  - rdkit.Chem.GraphDescriptors: Calculation of topological/topochemical descriptors.
  - rdkit.Chem.Graphs: Python functions for manipulating molecular graphs
  - rdkit.Chem.Lipinski: Calculation of Lipinski parameters for molecules
  - rdkit.Chem.MACCSkeys: SMARTS definitions for the publically available MACCS keys and a MACCS fingerprinter
  - rdkit.Chem.MCS
  - rdkit.Chem.MolCatalog
  - rdkit.Chem.MolDb
    - rdkit.Chem.MolDb.FingerprintUtils
    - rdkit.Chem.MolDb.Loader
    - rdkit.Chem.MolDb.Loader_orig
    - rdkit.Chem.MolDb.Loader_sa
  - rdkit.Chem.MolKey
    - rdkit.Chem.MolKey.InchiInfo
    - rdkit.Chem.MolKey.MolKey
  - rdkit.Chem.MolSurf: Exposes functionality for MOE-like approximate molecular surface area descriptors.
  - rdkit.Chem.PandasTools: Importing pandasTools enables several features that allow for using RDKit molecules as columns of a Pandas dataframe.
  - rdkit.Chem.PeriodicTable: periodic table data, **obsolete**
  - rdkit.Chem.Pharm2D: module with functionality for 2D pharmacophores
    - rdkit.Chem.Pharm2D.Generate: generation of 2D pharmacophores
    - rdkit.Chem.Pharm2D.Gobbi_Pharm2D: Definitions for 2D Pharmacophores from: Gobbi and Poppinger, Biotech.
    - rdkit.Chem.Pharm2D.LazyGenerator
    - rdkit.Chem.Pharm2D.Matcher: functionality for finding pharmacophore matches in molecules
    - rdkit.Chem.Pharm2D.SigFactory: contains factory class for producing signatures
    - rdkit.Chem.Pharm2D.Utils: utility functionality for the 2D pharmacophores code
  - rdkit.Chem.Pharm3D
    - rdkit.Chem.Pharm3D.EmbedLib
    - rdkit.Chem.Pharm3D.ExcludedVolume
    - rdkit.Chem.Pharm3D.Pharmacophore
  - rdkit.Chem.PropertyMol
  - rdkit.Chem.PyMol: uses pymol to interact with molecules
  - rdkit.Chem.Randomize
  - rdkit.Chem.Recap: Implementation of the RECAP algorithm from Lewell et al.
  - rdkit.Chem.ReducedGraphs
  - rdkit.Chem.SATIS: Functionality for SATIS typing atoms
  - rdkit.Chem.SaltRemover
  - rdkit.Chem.Scaffolds
    - rdkit.Chem.Scaffolds.MurckoScaffold: Generation of Murcko scaffolds from a molecule
  - rdkit.Chem.ShowMols
  - rdkit.Chem.SimpleEnum
    - rdkit.Chem.SimpleEnum.Enumerator
  - rdkit.Chem.Subshape
    - rdkit.Chem.Subshape.BuilderUtils
    - rdkit.Chem.Subshape.SubshapeAligner
    - rdkit.Chem.Subshape.SubshapeBuilder
    - rdkit.Chem.Subshape.SubshapeObjects
  - rdkit.Chem.Suppliers
    - rdkit.Chem.Suppliers.DbMolSupplier: Supplies a class for working with molecules from databases...
    - rdkit.Chem.Suppliers.MolSupplier: Supplies an abstract class for working with sequences of molecules
  - rdkit.Chem.TemplateAlign
  - rdkit.Chem.TorsionFingerprints: Torsion Fingerprints (Deviation) (TFD) According to a paper from Schulz-Gasch et al., JCIM, 52, 1499-1512 (2012).
  - rdkit.Chem.fmcs: Actual implementation of the FMCS algorithm...
    - rdkit.Chem.fmcs.fmcs: FMCS - Find Maximum Common Substructure
  - rdkit.Chem.inchi
- rdkit.DataManip
  - rdkit.DataManip.Metric
- rdkit.DataStructs
  - rdkit.DataStructs.BitEnsemble: #DOC
  - rdkit.DataStructs.BitEnsembleDb: This functionality gets mixed into the BitEnsemble class
  - rdkit.DataStructs.BitUtils
  - rdkit.DataStructs.HierarchyVis: functionality for drawing hierarchical catalogs on sping...
  - rdkit.DataStructs.LazySignature
  - rdkit.DataStructs.TopNContainer
  - rdkit.DataStructs.VectCollection
- rdkit.Dbase: a module for interacting with databases
  - rdkit.Dbase.DbConnection: defines class _DbConnect_, for abstracting connections to databases
  - rdkit.Dbase.DbInfo
  - rdkit.Dbase.DbModule
  - rdkit.Dbase.DbReport
  - rdkit.Dbase.DbResultSet: defines class _DbResultSet_ for lazy interactions with Db query results
  - rdkit.Dbase.DbUtils: a set of functions for interacting with databases
  - rdkit.Dbase.StorageUtils: Various storage (molecular and otherwise) functionality
- rdkit.DistanceGeometry
- rdkit.ForceField
- rdkit.Geometry: A module for Geometry stuff ...
- rdkit.ML: module containing machine learning code
  - rdkit.ML.AnalyzeComposite: command line utility to report on the contributions of descriptors to tree-based composite models
  - rdkit.ML.BuildComposite: command line utility for building composite models
  - rdkit.ML.Cluster
    - rdkit.ML.Cluster.Butina: Implementation of the clustering algorithm published in:...
    - rdkit.ML.Cluster.ClusterUtils: utility functions for clustering
    - rdkit.ML.Cluster.ClusterVis: Cluster tree visualization using Sping
    - rdkit.ML.Cluster.Clusters: contains the Cluster class for representing hierarchical cluster trees
    - rdkit.ML.Cluster.Murtagh: Interface to the C++ Murtagh hierarchic clustering code
    - rdkit.ML.Cluster.Resemblance: code for dealing with resemblance (metric) matrices
    - rdkit.ML.Cluster.Standardize: contains code for standardization of data matrices for clustering
  - rdkit.ML.Composite
    - rdkit.ML.Composite.AdjustComposite: functionality to allow adjusting composite model contents
    - rdkit.ML.Composite.BayesComposite: code for dealing with Bayesian composite models
    - rdkit.ML.Composite.Composite: code for dealing with composite models
  - rdkit.ML.CompositeRun: contains a class to store parameters for and results from...
  - rdkit.ML.Data
    - rdkit.ML.Data.DataUtils: Utilities for data manipulation
    - rdkit.ML.Data.FindQuantBounds
    - rdkit.ML.Data.MLData: classes to be used to help work with data sets
    - rdkit.ML.Data.Quantize: Automatic search for quantization bounds
    - rdkit.ML.Data.SplitData
    - rdkit.ML.Data.Stats: various statistical operations on data
    - rdkit.ML.Data.Transforms
  - rdkit.ML.DecTree: Here we're implementing the Decision Tree stuff found in Chapter 3 of Tom Mitchell's Machine Learning Book.
    - rdkit.ML.DecTree.BuildQuantTree:
    - rdkit.ML.DecTree.BuildSigTree:
    - rdkit.ML.DecTree.CrossValidate: handles doing cross validation with decision trees
    - rdkit.ML.DecTree.DecTree: Defines the class _DecTreeNode_, used to represent decision trees
    - rdkit.ML.DecTree.Forest: code for dealing with forests (collections) of decision trees
    - rdkit.ML.DecTree.ID3: ID3 Decision Trees
    - rdkit.ML.DecTree.PruneTree: Contains functionality for doing tree pruning
    - rdkit.ML.DecTree.QuantTree: Defines the class _QuantTreeNode_, used to represent decision trees with automatic quantization bounds
    - rdkit.ML.DecTree.SigTree: Defines the class SigTreeNode, used to represent trees that use signatures (bit vectors) to represent data.
    - rdkit.ML.DecTree.Tree: Implements a class used to represent N-ary trees
    - rdkit.ML.DecTree.TreeUtils: Utilities for working with trees
    - rdkit.ML.DecTree.TreeVis: functionality for drawing trees on sping canvases
  - rdkit.ML.Descriptors
    - rdkit.ML.Descriptors.CompoundDescriptors: descriptor calculator for compounds defined by a composition alone...
    - rdkit.ML.Descriptors.Descriptors: Various bits and pieces for calculating descriptors
    - rdkit.ML.Descriptors.MoleculeDescriptors: Various bits and pieces for calculating Molecular descriptors
    - rdkit.ML.Descriptors.Parser: The "parser" for compound descriptors.
  - rdkit.ML.EnrichPlot: Command line tool to construct an enrichment plot from saved composite models
  - rdkit.ML.GrowComposite: command line utility for growing composite models
  - rdkit.ML.InfoTheory: Information Theory functionality
    - rdkit.ML.InfoTheory.BitClusterer
    - rdkit.ML.InfoTheory.BitRank: Functionality for ranking bits using info gains
    - rdkit.ML.InfoTheory.entropy: Informational Entropy functions
  - rdkit.ML.KNN:
    - rdkit.ML.KNN.CrossValidate: handles doing cross validation with k-nearest neighbors model
    - rdkit.ML.KNN.DistFunctions
    - rdkit.ML.KNN.KNNClassificationModel: Define the class _KNNClassificationModel_, used to represent a k-nearest neighbhors classification model
    - rdkit.ML.KNN.KNNModel: Define the class _KNNModel_, used to represent a k-nearest neighbhors model
    - rdkit.ML.KNN.KNNRegressionModel: Define the class _KNNRegressionModel_, used to represent a k-nearest neighbhors regression model
  - rdkit.ML.MLUtils
    - rdkit.ML.MLUtils.VoteImg: functionality for generating an image showing the results of a composite model voting on a data set
  - rdkit.ML.MatOps: Matrix operations which may or may not come in handy some day
  - rdkit.ML.ModelPackage
    - rdkit.ML.ModelPackage.PackageUtils
    - rdkit.ML.ModelPackage.Packager
  - rdkit.ML.NaiveBayes:
    - rdkit.ML.NaiveBayes.ClassificationModel: Defines Naive Baysean classification model...
    - rdkit.ML.NaiveBayes.CrossValidate: handles doing cross validation with naive bayes models...
  - rdkit.ML.Neural
    - rdkit.ML.Neural.ActFuncs: Activation functions for neural network nodes
    - rdkit.ML.Neural.CrossValidate: handles doing cross validation with neural nets
    - rdkit.ML.Neural.NetNode: Contains the class _NetNode_ which is used to represent nodes in neural nets
    - rdkit.ML.Neural.Network: Contains the class _Network_ which is used to represent neural nets
    - rdkit.ML.Neural.Trainers: Training algorithms for feed-forward neural nets
  - rdkit.ML.SLT
    - rdkit.ML.SLT.Risk: code for calculating empirical risk
  - rdkit.ML.Scoring
    - rdkit.ML.Scoring.Scoring: $Id$
  - rdkit.ML.ScreenComposite: command line utility for screening composite models
  - rdkit.ML.files: Generic file manipulation stuff
- rdkit.Numerics: A module for Numerics stuff ...
- rdkit.SimDivFilters
  - rdkit.SimDivFilters.SimilarityPickers
- rdkit.VLib
  - rdkit.VLib.Filter
  - rdkit.VLib.Node
  - rdkit.VLib.NodeLib
    - rdkit.VLib.NodeLib.DbMolSupply
    - rdkit.VLib.NodeLib.DbPickleSupplier
    - rdkit.VLib.NodeLib.SDSupply
    - rdkit.VLib.NodeLib.SmartsMolFilter
    - rdkit.VLib.NodeLib.SmartsRemover
    - rdkit.VLib.NodeLib.SmilesDupeFilter
    - rdkit.VLib.NodeLib.SmilesOutput
    - rdkit.VLib.NodeLib.SmilesSupply
    - rdkit.VLib.NodeLib.demo
  - rdkit.VLib.Output
  - rdkit.VLib.Supply
  - rdkit.VLib.Transform
- RDRandom: making random numbers consistent so we get good regressions