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[ Module Hierarchy | Class Hierarchy ]

# Class Hierarchy

- Chem.Pharm3D.Pharmacophore.ExplicitPharmacophore: this is a pharmacophore with explicit point locations and radii...
- Chem.Pharm3D.Pharmacophore.Pharmacophore
- DataStructs.BitVect.BitVect
  - DataStructs.BitVect.SparseBitVect
- DataStructs.LazySignature.LazySig
- Logger.demo.Foo: a simple class...
- ML.CompositeRun.CompositeRun: class to store parameters for and results from Composite building This class has a default set of fields which are added to the database.
- ML.DecTree.Tree.TreeNode: This is your bog standard Tree class.
  - ML.DecTree.DecTree.DecTreeNode: This is used to represent decision trees _DecTreeNode_s are simultaneously the roots and branches of decision trees.
    - ML.DecTree.SigTree.SigTreeNode: ...
    - ML.DecTree.QuantTree.QuantTreeNode: ...
- ML.Descriptors.Descriptors.DescriptorCalculator: abstract base class for descriptor calculators...
  - ML.Descriptors.MoleculeDescriptors.MolecularDescriptorCalculator: used for calculating descriptors for molecules...
  - ML.Descriptors.CompoundDescriptors.CompoundDescriptorCalculator: used for calculating descriptors This is the central point for descriptor calculation **Notes** - There are two kinds of descriptors this cares about: 1) *Simple Descriptors* can be calculated solely using atomic descriptor values and the composition of the compound.
- ML.Descriptors.DescriptorsCOM.DescriptorServer: exposes an interface for descriptor calculator COM servers...
- ML.NaiveBayes.ClassificationModel.NaiveBayesClassifier: _NaiveBayesClassifier_s can save the following pieces of internal state, accessible via...
- ML.Neural.NetNode.NetNode: a node in a neural network...
- ML.Neural.Network.Network: a neural network...
- ML.files.ReFile: convenience class for dealing with files with comments blank (all whitespace) lines, and lines beginning with comment characters are skipped.
- VLib.NodeLib.DbPickleSupplier._lazyDataSeq: These classes are used to speed up (a lot) the process of pulling pickled objects from PostgreSQL databases.
- object: The most base type
  - Chem.FastSDMolSupplier.FastSDMolSupplier: A wrapper around an SDMolSupplier that precomputes and stores molecular indices (via text processing) to allow quick length calculations and random access.
  - DataStructs.HierarchyVis.VisOpts
  - Chem.FeatMaps.FeatMapUtils.MergeMethod
  - Dbase.DbResultSet.DbResultBase
    - Dbase.DbResultSet.RandomAccessDbResultSet: Supports random access...
    - Dbase.DbResultSet.DbResultSet: Only supports forward iteration...
  - PySVD.SVDSimilarity.SimilarityCalculator
  - exceptions.BaseException: Common base class for all exceptions
    - exceptions.Exception: Common base class for all non-exit exceptions.
      - ML.ModelPackage.Packager.ClassificationError: used to signal problems generating predictions
      - exceptions.StandardError: Base class for all standard Python exceptions that do not represent interpreter exiting.
        - exceptions.ValueError: Inappropriate argument value (of correct type).
          - Chem.FeatMaps.FeatMapParser.FeatMapParseError
        - exceptions.RuntimeError: Unspecified run-time error.
          - Dbase.DbConnection.DbError
        - exceptions.AssertionError: Assertion failed.
      - RDConfig.ObsoleteCodeError
      - RDConfig.UnimplementedCodeError
      - Chem.Pharm2D.Matcher.MatchError
      - sre_constants.error
      - ML.ModelPackage.Packager.DescriptorCalculationError: used to signal problems generating descriptor values
  - ML.Composite.CompositeCOM.CompositeServer: exposes an interface for composite COM servers...
  - ML.Cluster.Clusters.Cluster: a class for storing clusters/data **General Remarks** - It is assumed that the bottom of any cluster hierarchy tree is composed of the individual data points which were clustered.
  - Chem.FeatMaps.FeatMaps.FeatMapParams: one of these should be instantiated for each...
  - Chem.DSViewer.MolViewer
  - Chem.Draw.MolDrawing.MolDrawing
  - Chem.Subshape.SubshapeObjects.SubshapeShape
  - Chem.FeatMaps.FeatMaps.FeatMapScoreMode
  - Chem.FeatMaps.FeatMaps.FeatMap
  - unittest.TestCase: A class whose instances are single test cases.
    - Chem.ChemUtils.SDFToCSV.TestCase
  - Chem.Recap.RecapHierarchyNode: This class is used to hold the Recap hiearchy...
  - Chem.Fingerprints.SimilarityScreener.SimilarityScreener: base class important attributes: probe: the probe fingerprint against which we screen.
    - Chem.Fingerprints.SimilarityScreener.TopNScreener: A screener that only returns the top N hits found...
    - Chem.Fingerprints.SimilarityScreener.ThresholdScreener: Used to return all compounds that have a similarity to the probe beyond a threshold value **Notes**: - This is as lazy as possible, so the data source isn't queried until the client asks for a hit.
  - DataStructs.SparseIntVect.pySparseIntVect: this class is pretty much obsolete (it's in C++ now)
  - Chem.Pharm3D.ExcludedVolume.ExcludedVolume
  - Chem.Fingerprints.FingerprintMols.FingerprinterDetails: class for storing the details of a fingerprinting run,...
  - Logger.Logger.Callable: this is just a simple class with a __call__ method we'll use to pass any method invocations back to the caller.
  - RDLogger.logger
  - Chem.FeatMaps.FeatMapUtils.MergeMetric
  - Chem.Suppliers.MolSupplier.MolSupplier: we must, at minimum, support forward iteration...
    - Chem.Suppliers.DbMolSupplier.DbMolSupplier: new molecules come back with all additional fields from the...
      - Chem.Suppliers.DbMolSupplier.RandomAccessDbMolSupplier
      - Chem.Suppliers.DbMolSupplier.ForwardDbMolSupplier: DbMol supplier supporting only forward iteration...
  - ML.Neural.Trainers.Trainer: "virtual base class" for network trainers...
    - ML.Neural.Trainers.BackProp: implement back propagation (algorithm on pp 153-154 of Patterson) I don't *think* that I've made any assumptions about the connectivity of the net (i.e.
  - Chem.Draw.MolDrawing.Font
  - Chem.BuildFragmentCatalog.RunDetails
  - Logger.Logger.Logger: This is the actual wrapper class.
  - Chem.FeatMaps.FeatMapUtils.DirMergeMode
  - Dbase.DbReport.RDImageTransformer
  - Chem.Subshape.SubshapeBuilder.SubshapeCombineOperations
  - ML.InfoTheory.BitClusterer.BitClusterer: Class to cluster a set of bits based on their correllation...
  - unreachable.instance
    - Chem.rdchem.Atom: The class to store Atoms.
    - rdBase._vectd
    - Chem.rdmolfiles.SDMolSupplier: A class which supplies molecules from an SD file.
    - Chem.rdmolfiles.TDTMolSupplier: A class which supplies molecules from a TDT file.
    - Chem.rdmolfiles.SmilesWriter: A class for writing molecules to text files.
    - rdBase._vectSt6vectorIiSaIiEE
    - Chem.rdfragcatalog.FragFPGenerator
    - Geometry.rdGeometry.Point2D: A class to represent a two-dimensional point
    - Chem.rdChemicalFeatures.FreeChemicalFeature: Class to represent a free chemical features.
      - Chem.FeatMaps.FeatMapPoint.FeatMapPoint
    - Chem.rdmolfiles.TDTWriter: A class for writing molecules to TDT files.
    - Chem.rdchem._listPN5RDKit4AtomE
    - DataStructs.cDataStructs.DiscreteValueVect: A container class for storing unsigned integer values within a particular range.
    - Chem.rdchem.Conformer: The class to store 2D or 3D conformation of a molecule
    - Chem.rdmolfiles.SmilesMolSupplier: A class which supplies molecules from a text file.
    - Chem.rdchem.EditableMol: an editable molecule class
    - DataStructs.cDataStructs.SparseBitVect: A class to store sparse bit vectors.
    - SimDivFilters.rdSimDivPickers.HierarchicalClusterPicker: A class for diversity picking of items using Hierarchical Clustering
    - Chem.rdfragcatalog.FragCatGenerator
    - rdBase._listSt6vectorIiSaIiEE
    - Chem.rdchem._ROAtomSeq: Read-only sequence of atoms, not constructable from Python.
    - Chem.rdchem.PeriodicTable: A class which stores information from the Periodic Table.
    - DataStructs.cDataStructs.UIntSparseIntVect: A container class for storing integer values within a particular range.
    - ForceField.rdForceField.ForceField: A force field
    - rdBase._vectj
    - Chem.rdchem._ROBondSeq: Read-only sequence of bonds, not constructable from Python.
    - ML.InfoTheory.rdInfoTheory.BitCorrMatGenerator: A class to generate a pariwise correlation matrix between a list of bits...
    - Chem.rdChemReactions.ChemicalReaction: A class for storing and applying chemical reactions.
    - Chem.rdMolCatalog.MolCatalog
    - rdBase._listi
    - rdBase._vecti
    - Geometry.rdGeometry.UniformGrid3D_: Class to represent a uniform three-dimensional cubic grid.
    - Chem.rdchem._listPN5RDKit4BondE
    - Chem.rdfragcatalog.FragCatParams
    - Geometry.rdGeometry.PointND: A class to represent an N-dimensional point
    - rdBase._vectSt6vectorIjSaIjEE
    - Chem.rdMolCatalog.MolCatalogEntry
    - Chem.rdchem.Mol: The Molecule class.
    - ML.InfoTheory.rdInfoTheory.InfoBitRanker: A class to rank the bits from a series of labelled fingerprints A simple demonstration may help clarify what this class does.
    - Chem.rdMolChemicalFeatures.MolChemicalFeatureFactory: Class to featurize a molecule
    - rdBase._vectSs
    - rdBase._vectSt6vectorIdSaIdEE
    - Chem.rdmolfiles.SDWriter: A class for writing molecules to SD files.
    - SimDivFilters.rdSimDivPickers.MaxMinPicker: A class for diversity picking of items using the MaxMin Algorithm
    - Chem.rdchem.Bond: The class to store Bonds.
    - Chem.rdchem.RingInfo: contains information about a molecule's rings
    - DataStructs.cDataStructs.LongSparseIntVect: A container class for storing integer values within a particular range.
    - Geometry.rdGeometry.Point3D: A class to represent a three-dimensional point The x, y, and z coordinates can be read and written using either attributes (i.e.
    - DataStructs.cDataStructs.ExplicitBitVect: A class to store explicit bit vectors.
    - DataStructs.cDataStructs.IntSparseIntVect: A container class for storing integer values within a particular range.
    - DataStructs.cDataStructs.ULongSparseIntVect: A container class for storing integer values within a particular range.
    - Chem.rdMolDescriptors.AtomPairsParameters
    - Chem.rdfragcatalog.FragCatalog
    - Chem.rdMolChemicalFeatures.MolChemicalFeature: Class to represent a chemical feature.
  - Chem.FragmentCatalog.BitGainsInfo
  - int: int(x[, base]) -> integer Convert a string or number to an integer, if possible.
    - unreachable.enum
      - Chem.rdchem.BondType
      - Chem.rdchem.HybridizationType
      - Chem.rdchem.BondStereo
      - Chem.rdchem.BondDir
      - SimDivFilters.rdSimDivPickers.ClusterMethod
      - Chem.rdchem.ChiralType
      - DataStructs.cDataStructs.DiscreteValueType
      - ML.InfoTheory.rdInfoTheory.InfoType
  - Dbase.DbReport.CactvsImageTransformer
  - ML.DecTree.TreeVis.VisOpts
  - Chem.Subshape.SubshapeObjects.ShapeWithSkeleton
  - Dbase.DbReport.CDXImageTransformer
  - Chem.FeatMaps.FeatMapParser.FeatMapParser
  - DataStructs.TopNContainer.TopNContainer: maintains a sorted list of a particular number of data elements.
  - Chem.Subshape.SubshapeAligner.SubshapeAlignment
  - Chem.Pharm2D.Signature.Pharm2DSig: **Notes on Use** - After any changes, the Init() method should be called **Important Attributes** - patterns: a list of SmartsPatterns used to determine the features patterns can be initialized directly from the list or from a list of SMARTS strings - bins: the list of distance bins to be used.
  - Dbase.DbConnection.DbConnect: This class is intended to abstract away many of the details of interacting with databases.
  - Chem.Pharm2D.LazyGenerator.Generator: Important attributes: - mol: the molecules whose signature is being worked with - sig: the signature to be used to decide what bits are set in the molecule.
  - Chem.PyMol.MolViewer
  - ML.ModelPackage.Packager.ModelPackage: a container class to package a composite model with a descriptor...
  - Chem.FeatMaps.FeatMaps.FeatDirScoreMode
  - Dbase.Pubmed.Records.Record
    - Dbase.Pubmed.Records.LinkRecord
    - Dbase.Pubmed.Records.JournalArticleRecord
    - Dbase.Pubmed.Records.SummaryRecord
  - ML.DecTree.Forest.Forest: a forest of unique decision trees.
  - Dbase.DbReport.ReportLabImageTransformer
  - Chem.Subshape.SubshapeAligner.SubshapeDistanceMetric
  - ML.KNN.KNNModel.KNNModel: This is a base class used by KNNClassificationModel and KNNRegressionModel to represent a k-nearest neighbor predictor.
    - ML.KNN.KNNClassificationModel.KNNClassificationModel: This is used to represent a k-nearest neighbor classifier...
    - ML.KNN.KNNRegressionModel.KNNRegressionModel: This is used to represent a k-nearest neighbor classifier...
  - VLib.Node.VLibNode: base class for all virtual library nodes,...
    - VLib.Filter.FilterNode: base class for nodes which filter their input Assumptions: - filter function takes a number of arguments equal to the number of inputs we have.
      - VLib.NodeLib.SmartsMolFilter.SmartsFilter: filter out molecules matching one or more SMARTS patterns There is a count associated with each pattern.
      - VLib.NodeLib.SmilesDupeFilter.DupeFilter: canonical-smiles based duplicate filter...
    - VLib.Supply.SupplyNode: base class for nodes which supply things Assumptions: 1) no parents Usage Example: >>> supplier = SupplyNode(contents=[1,2,3]) >>> supplier.next() 1 >>> supplier.next() 2 >>> supplier.next() 3 >>> supplier.next() Traceback (most recent call last): ...
      - VLib.NodeLib.SmilesSupply.SmilesSupplyNode: Smiles supplier...
      - VLib.NodeLib.DbPickleSupplier.DbPickleSupplyNode: Supplies pickled objects from a db result set:...
      - VLib.NodeLib.DbMolSupply.DbMolSupplyNode: Supplies molecules from a db result set:...
      - VLib.NodeLib.SDSupply.SDSupplyNode: SD supplier...
    - VLib.Output.OutputNode: base class for nodes which dump output...
      - VLib.NodeLib.SmilesOutput.OutputNode: dumps smiles output...
    - Chem.Fingerprints.DbFpSupplier.DbFpSupplier: new fps come back with all additional fields from the...
      - Chem.Fingerprints.DbFpSupplier.RandomAccessDbFpSupplier: DbFp supplier supporting random access: >>> import os.path >>> from Dbase.DbConnection import DbConnect >>> fName = RDConfig.RDTestDatabase >>> conn = DbConnect(fName,'simple_combined') >>> suppl = RandomAccessDbFpSupplier(conn.GetData()) >>> len(suppl) 12 we can pull individual fingerprints: >>> fp = suppl[5] >>> fp.GetNumBits() 128 >>> fp.GetNumOnBits() 54 a standard loop over the fingerprints: >>> fps = [] >>> for fp in suppl: ...
      - Chem.Fingerprints.DbFpSupplier.ForwardDbFpSupplier: DbFp supplier supporting only forward iteration >>> import os.path >>> from Dbase.DbConnection import DbConnect >>> fName = RDConfig.RDTestDatabase >>> conn = DbConnect(fName,'simple_combined') >>> suppl = ForwardDbFpSupplier(conn.GetData()) we can loop over the supplied fingerprints: >>> fps = [] >>> for fp in suppl: ...
    - VLib.Transform.TransformNode: base class for nodes which filter their input Assumptions: - transform function takes a number of arguments equal to the number of inputs we have.
      - VLib.NodeLib.SmartsRemover.SmartsRemover: transforms molecules by removing atoms matching smarts patterns...
  - ML.Cluster.ClusterVis.VisOpts: stores visualization options for cluster viewing...
  - Chem.Pharm2D.SigFactory.SigFactory: SigFactory's are used by creating one, setting the relevant parameters, then calling the GetSignature() method each time a signature is required.
  - ML.Composite.Composite.Composite: a composite model **Notes** - adding a model which is already present just results in its count field being incremented and the errors being averaged.
    - ML.Composite.BayesComposite.BayesComposite: a composite model using Bayesian statistics in the Decision Proxy **Notes** - typical usage: 1) grow the composite with AddModel until happy with it 2) call AverageErrors to calculate the average error values 3) call SortModels to put things in order by either error or count 4) call Train to update the Bayesian stats.
  - DataStructs.VectCollection.VectCollection: >>> vc = VectCollection()...
  - Chem.Subshape.SubshapeAligner.SubshapeAligner
  - Chem.DSViewer.Displayable
  - Chem.Subshape.SubshapeObjects.SkeletonPoint
  - SimDivFilters.SimilarityPickers.GenericPicker
    - SimDivFilters.SimilarityPickers.TopNOverallPicker: A class for picking the top N overall best matches across a library Connect to a database and build molecules: >>> import Chem >>> import os.path >>> from Dbase.DbConnection import DbConnect >>> dbName = RDConfig.RDTestDatabase >>> conn = DbConnect(dbName,'simple_mols1') >>> [x.upper() for x in conn.GetColumnNames()] ['SMILES', 'ID'] >>> mols = [] >>> for smi,id in conn.GetData(): ...
    - SimDivFilters.SimilarityPickers.SpreadPicker: A class for picking the best matches across a library Connect to a database: >>> import Chem >>> import os.path >>> from Dbase.DbConnection import DbConnect >>> dbName = RDConfig.RDTestDatabase >>> conn = DbConnect(dbName,'simple_mols1') >>> [x.upper() for x in conn.GetColumnNames()] ['SMILES', 'ID'] >>> mols = [] >>> for smi,id in conn.GetData(): ...
  - ML.Data.MLData.MLDataSet: A data set for holding general data (floats, ints, and strings) **Note** this is intended to be a read-only data structure (i.e.
    - ML.Data.MLData.MLQuantDataSet: a data set for holding quantized data **Note** this is intended to be a read-only data structure (i.e.
  - Chem.FeatMaps.FeatMaps.FeatMapParams.FeatProfile: scoring profile of the feature
  - Chem.FragmentMatcher.FragmentMatcher
  - ML.Neural.ActFuncs.ActFunc: "virtual base class" for activation functions...
    - ML.Neural.ActFuncs.TanH: the standard hyperbolic tangent function
    - ML.Neural.ActFuncs.Sigmoid: the standard sigmoidal function
  - ML.Cluster.ClusterVis.ClusterRenderer
  - DataStructs.BitEnsemble.BitEnsemble: used to store a collection of bits and score BitVects (or signatures) against them.
  - Chem.Subshape.SubshapeBuilder.SubshapeBuilder
- re.Scanner