rdkit.ML.MLUtils.VoteImg module¶
functionality for generating an image showing the results of a composite model voting on a data set
Uses Numeric and PIL
- rdkit.ML.MLUtils.VoteImg.BuildVoteImage(nModels, data, values, trueValues=[], sortTrueVals=0, xScale=10, yScale=2, addLine=1)¶
constructs the actual image
Arguments
nModels: the number of models in the composite
data: the results of voting
values: predicted values for each example
trueValues: true values for each example
sortTrueVals: if nonzero the votes will be sorted so that the _trueValues_ are in order, otherwise the sort is by _values_
xScale: number of pixels per vote in the x direction
yScale: number of pixels per example in the y direction
- addLine: if nonzero, a purple line is drawn separating
the votes from the examples
Returns
a PIL image
- rdkit.ML.MLUtils.VoteImg.CollectVotes(composite, data, badOnly)¶
collects the votes from _composite_ for the examples in _data_
Arguments
composite: a composite model
data: a list of examples to run through _composite_
badOnly: if set only bad (misclassified) examples will be kept
Returns
a 4-tuple containing:
the expanded list of vote details (see below)
the list of predicted results
the list of true results
the number of miscounted examples
Notes
pp - the expanded list of vote details consists of:
‘[ vote1, vote2, … voteN, 0, res, trueRes]’
where _res_ is the predicted results and _trueRes_ is the actual result. The extra zero is included to allow a line to be drawn between the votes and the results.
- rdkit.ML.MLUtils.VoteImg.Usage()¶
provides a list of arguments for when this is used from the command line
- rdkit.ML.MLUtils.VoteImg.VoteAndBuildImage(composite, data, badOnly=0, sortTrueVals=0, xScale=10, yScale=2, addLine=1)¶
collects votes on the examples and constructs an image
Arguments
composte: a composite model
data: the examples to be voted upon
badOnly: if nonzero only the incorrect votes will be shown
sortTrueVals: if nonzero the votes will be sorted so that the _trueValues_ are in order, otherwise the sort is by _values_
xScale: number of pixels per vote in the x direction
yScale: number of pixels per example in the y direction
- addLine: if nonzero, a purple line is drawn separating
the votes from the examples
Returns
a PIL image