rdkit.ML.EnrichPlot

Package rdkit :: Package ML :: Module EnrichPlot |
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# Module EnrichPlot

source code

    Command line tool to construct an enrichment plot from saved composite models

    Usage:  EnrichPlot [optional args] -d dbname -t tablename <models>

    Required Arguments:
      -d "dbName": the name of the database for screening

      -t "tablename": provide the name of the table with the data to be screened

      <models>: file name(s) of pickled composite model(s).
         If the -p argument is also provided (see below), this argument is ignored.

    Optional Arguments:
      - -a "list": the list of result codes to be considered active.  This will be
            eval'ed, so be sure that it evaluates as a list or sequence of
            integers. For example, -a "[1,2]" will consider activity values 1 and 2
            to be active

      - --enrich "list": identical to the -a argument above.

      - --thresh: sets a threshold for the plot.  If the confidence falls below
              this value, picking will be terminated

      - -H: screen only the hold out set (works only if a version of
            BuildComposite more recent than 1.2.2 was used).

      - -T: screen only the training set (works only if a version of
            BuildComposite more recent than 1.2.2 was used).

      - -S: shuffle activity values before screening

      - -R: randomize activity values before screening

      - -F *filter frac*: filters the data before training to change the
         distribution of activity values in the training set.  *filter frac*
         is the fraction of the training set that should have the target value.
         **See note in BuildComposite help about data filtering**

      - -v *filter value*: filters the data before training to change the
         distribution of activity values in the training set. *filter value*
         is the target value to use in filtering.
         **See note in BuildComposite help about data filtering**

      - -p "tableName": provides the name of a db table containing the
          models to be screened.  If you use this argument, you should also
          use the -N argument (below) to specify a note value.

      - -N "note": provides a note to be used to pull models from a db table.

      - --plotFile "filename": writes the data to an output text file (filename.dat)
        and creates a gnuplot input file (filename.gnu) to plot it

      - --showPlot: causes the gnuplot plot constructed using --plotFile to be
        displayed in gnuplot.

Functions | [hide private]
message(msg, noRet=0, dest=sys.stderr) emits messages to _sys.stderr_ override this in modules which import this one to redirect output | source code
error(msg, dest=sys.stderr) emits messages to _sys.stderr_ override this in modules which import this one to redirect output | source code
ScreenModel(mdl, descs, data, picking=`[`1`]`, indices=`[``]`, errorEstimate=0) collects the results of screening an individual composite model that match a particular value | source code
AccumulateCounts(predictions, thresh=0, sortIt=1) Accumulates the data for the enrichment plot for a single model | source code
MakePlot(details, final, counts, pickVects, nModels, nTrueActs=-1) | source code
Usage() displays a usage message and exits | source code

Variables | [hide private]
| __VERSION_STRING = ``'``2.4.0``'``

Imports: RDConfig, numpy, cPickle, copy, DataUtils, SplitData, Stats, DbConnect, DataStructs, CompositeRun, sys, os, types

Function Details | [hide private]

### message(msg, noRet=0, dest=sys.stderr) | source code
    emits messages to _sys.stderr_
    override this in modules which import this one to redirect output

    **Arguments**

      - msg: the string to be displayed

### error(msg, dest=sys.stderr) | source code
    emits messages to _sys.stderr_
    override this in modules which import this one to redirect output

    **Arguments**

      - msg: the string to be displayed

### ScreenModel(mdl, descs, data, picking=`[`1`]`, indices=`[``]`, errorEstimate=0) | source code
    collects the results of screening an individual composite model that match
     a particular value

    **Arguments**

      - mdl: the composite model

      - descs: a list of descriptor names corresponding to the data set

      - data: the data set, a list of points to be screened.

      - picking: (Optional) a list of values that are to be collected.
        For examples, if you want an enrichment plot for picking the values
        1 and 2, you'd having picking=[1,2].

     **Returns**

       a list of 4-tuples containing:

          - the id of the point

          - the true result (from the data set)

          - the predicted result

          - the confidence value for the prediction

### AccumulateCounts(predictions, thresh=0, sortIt=1) | source code
    Accumulates the data for the enrichment plot for a single model

    **Arguments**

      - predictions: a list of 3-tuples (as returned by _ScreenModels_)

      - thresh: a threshold for the confidence level.  Anything below
        this threshold will not be considered

      - sortIt: toggles sorting on confidence levels

    **Returns**

      - a list of 3-tuples:

        - the id of the active picked here

        - num actives found so far

        - number of picks made so far