rdkit.ML.InfoTheory.BitRank

Package rdkit :: Package ML :: Package InfoTheory :: Module BitRank |
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# Module BitRank

source code

    Functionality for ranking bits using info gains

    **Definitions used in this module**

       - *sequence*: an object capable of containing other objects which supports
         __getitem__() and __len__().  Examples of these include lists, tuples, and
         Numeric arrays.

       - *IntVector*: an object containing integers which supports __getitem__() and
          __len__(). Examples include lists, tuples, Numeric Arrays, and BitVects.

    **NOTE**: Neither *sequences* nor *IntVectors* need to support item assignment.
      It is perfectly acceptable for them to be read-only, so long as they are
      random-access.

Functions | [hide private]
FormCounts(bitVects, actVals, whichBit, nPossibleActs, nPossibleBitVals=2) generates the counts matrix for a particular bit | source code
CalcInfoGains(bitVects, actVals, nPossibleActs, nPossibleBitVals=2) Calculates the information gain for a set of points and activity values | source code
RankBits(bitVects, actVals, nPossibleBitVals=2, metricFunc=<function CalcInfoGains at 0x7fc42987e6e0>) Rank a set of bits according to a metric function | source code
AnalyzeSparseVects(bitVects, actVals) #DOC | source code
SparseRankBits(bitVects, actVals, metricFunc=<function AnalyzeSparseVects at 0x7fc42987e8c0>) Rank a set of bits according to a metric function | source code

Variables | [hide private]
| __package__ = ``'``rdkit.ML.InfoTheory``'``

Imports: numpy, entropy

Function Details | [hide private]

### FormCounts(bitVects, actVals, whichBit, nPossibleActs, nPossibleBitVals=2) | source code
    generates the counts matrix for a particular bit

    **Arguments**

      - bitVects: a *sequence* containing *IntVectors*

      - actVals: a *sequence*

      - whichBit: an integer, the bit number to use.

      - nPossibleActs: the (integer) number of possible activity values.

      - nPossibleBitVals: (optional) if specified, this integer provides the maximum
        value attainable by the (increasingly inaccurately named) bits in _bitVects_.

    **Returns**

      a Numeric array with the counts

    **Notes**

      This is really intended for internal use.

### CalcInfoGains(bitVects, actVals, nPossibleActs, nPossibleBitVals=2) | source code
    Calculates the information gain for a set of points and activity values

    **Arguments**

      - bitVects: a *sequence* containing *IntVectors*

      - actVals: a *sequence*

      - nPossibleActs: the (integer) number of possible activity values.

      - nPossibleBitVals: (optional) if specified, this integer provides the maximum
        value attainable by the (increasingly inaccurately named) bits in _bitVects_.

     **Returns**

       a list of floats

### RankBits(bitVects, actVals, nPossibleBitVals=2, metricFunc=<function CalcInfoGains at 0x7fc42987e6e0>) | source code
    Rank a set of bits according to a metric function

    **Arguments**

      - bitVects: a *sequence* containing *IntVectors*

      - actVals: a *sequence*

      - nPossibleBitVals: (optional) if specified, this integer provides the maximum
        value attainable by the (increasingly inaccurately named) bits in _bitVects_.

      - metricFunc: (optional) the metric function to be used.  See _CalcInfoGains()_
        for a description of the signature of this function.

     **Returns**

       A 2-tuple containing:

         - the relative order of the bits (a list of ints)

         - the metric calculated for each bit (a list of floats)

### AnalyzeSparseVects(bitVects, actVals) | source code
    #DOC

    **Arguments**

      - bitVects: a *sequence* containing SBVs

      - actVals: a *sequence*

     **Returns**

       a list of floats

     **Notes**

        - these need to be bit vects and binary activities

### SparseRankBits(bitVects, actVals, metricFunc=<function AnalyzeSparseVects at 0x7fc42987e8c0>) | source code
    Rank a set of bits according to a metric function

    **Arguments**

      - bitVects: a *sequence* containing SBVs

      - actVals: a *sequence*

      - metricFunc: (optional) the metric function to be used.  See _SparseCalcInfoGains()_
        for a description of the signature of this function.

     **Returns**

       A 2-tuple containing:

         - the relative order of the bits (a list of ints)

         - the metric calculated for each bit (a list of floats)

      **Notes**

        - these need to be bit vects and binary activities