Class FeatureSource<T extends InputFromManager, S, U extends FeatureInput>

Object
AnchorBean<FeatureSource<T,S,U>>
FeatureSource<T,S,U>
Type Parameters:
T - input-type from which one or more rows of features are derived
S - row-source that is duplicated for each new thread (to prevent any concurrency issues)
U - feature-input type for features bean-field
Direct Known Subclasses:
SingleRowPerInput
public abstract class FeatureSource<T extends InputFromManager, S, U extends FeatureInput> extends AnchorBean<FeatureSource<T,S,U>>
Extracts features from some kind of inputs to produce one or more rows in a feature-table.
Author:
Owen Feehan

  • Constructor Summary

    Constructors
    Constructor
    Description
    FeatureSource()
     

  • Method Summary

    Modifier and Type
    Method
    Description
    abstract void
    calculateAndOutput(T input, FeatureCalculationContext<S> context)
    Processes one input to calculate feature-results and output them to the file-system.
    abstract FeatureExporter<S>
    createExporter(LabelHeaders metadataHeaders, List<NamedBean<FeatureListProvider<U>>> features, FeatureOutputNames outputNames, Optional<InputGrouper> grouper, FeatureExporterContext context)
    Creates the FeatureExporter to be used for calculating and exporting feature-results.
    abstract LabelHeaders
    headers(boolean groupsEnabled)
    Generates label-headers for the non-feature-result columns in the CSV.
    abstract boolean
    includeGroupInExperiment(boolean groupGeneratorDefined)
    Determines if group columns should be added to the CSV exports and other group exports may occur in sub-directories.
    abstract InputTypesExpected
    inputTypesExpected()
    Specifies the highest class(es) that will function as a valid input.

    Methods inherited from class org.anchoranalysis.bean.AnchorBean

    checkMisconfigured, describeBean, describeChildren, duplicateBean, fields, findFieldsOfClass, getBeanName, getLocalPath, localise, toString

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

  • Constructor Details

    • FeatureSource

      public FeatureSource()

  • Method Details

    • createExporter

      public abstract FeatureExporter<S> createExporter(LabelHeaders metadataHeaders, List<NamedBean<FeatureListProvider<U>>> features, FeatureOutputNames outputNames, Optional<InputGrouper> grouper, FeatureExporterContext context) throws CreateException
      Creates the FeatureExporter to be used for calculating and exporting feature-results.
      Parameters:
      metadataHeaders - headers to use for additional "metadata" before feature-results.
      features - the features to calculate.
      outputNames - the names of various kind of outputs.
      grouper - when defined, assigns each input to a group.
      context - IO-context.
      Returns:
      a newly created FeatureExporter as matches this source of features.
      Throws:
      CreateException - if it cannot be created.

    • includeGroupInExperiment

      public abstract boolean includeGroupInExperiment(boolean groupGeneratorDefined)
      Determines if group columns should be added to the CSV exports and other group exports may occur in sub-directories.
      Parameters:
      groupGeneratorDefined - has a group-generator been defined for this experiment?
      Returns:
      true if a group-generator has been defined, false otherwise

    • headers

      public abstract LabelHeaders headers(boolean groupsEnabled)
      Generates label-headers for the non-feature-result columns in the CSV.
      Parameters:
      groupsEnabled - whether groups are enabled
      Returns:
      a LabelHeaders object for the non-feature-result columns

    • calculateAndOutput

      public abstract void calculateAndOutput(T input, FeatureCalculationContext<S> context) throws OperationFailedException
      Processes one input to calculate feature-results and output them to the file-system.
      Parameters:
      input - one particular input that will create one or more "rows" in a feature-table
      context - the FeatureCalculationContext for calculation
      Throws:
      OperationFailedException - if the operation fails

    • inputTypesExpected

      public abstract InputTypesExpected inputTypesExpected()
      Specifies the highest class(es) that will function as a valid input.

      This is usually the class of T (or sometimes the absolute base class InputFromManager)

      Returns:
      an InputTypesExpected object specifying the expected input types