uk.ac.ebi.intact.application.dataConversion.ExperimentListGenerator java code examples

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}

public List<ExperimentListItem> generateAllClassifications() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  List<ExperimentListItem> allItems = new ArrayList<ExperimentListItem>();
  allItems.addAll( generateClassificationBySpecies() );
  allItems.addAll( generateClassificationByPublications() );
  return allItems;
}

public Set<Experiment> getNegativeExperiments() {
  if ( negativeExperiments == null ) {
    classifyNegatives();
  }
  return negativeExperiments;
}

public List<ExperimentListItem> generateClassificationByDatasets() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( datasetsListItems != null && !datasetsListItems.isEmpty() ) {
    return datasetsListItems;
  }
  createItemClassificationByDataset();
  return datasetsListItems;
}

public List<ExperimentListItem> generateClassificationByPublications() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( publicationsListItems != null && !publicationsListItems.isEmpty() ) {
    return publicationsListItems;
  }
  createItemClassificationByPubmed();
  return publicationsListItems;
}

public List<ExperimentListItem> generateClassificationBySpecies() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( speciesListItems != null && !speciesListItems.isEmpty() ) {
    return speciesListItems;
  }
  createItemClassificationBySpecies();
  return speciesListItems;
}

private void createExperimentListItems( String name,
                    Collection<SimplifiedAnnotatedObject<Experiment>> exps,
                    Integer chunkNumber,
                    Classification classification,
                    Integer largeScaleChunkSize ) {
  List<String> labels = new ArrayList<String>();
  List<String> labelsNegative = new ArrayList<String>();
  for ( SimplifiedAnnotatedObject exp : exps ) {
    if ( isNegative( exp.getShortLabel() ) ) {
      labelsNegative.add( exp.getShortLabel() );
    } else {
      labels.add( exp.getShortLabel() );
    }
  }
  String parentFolders = parentFolders( exps, classification );
  if ( !labels.isEmpty() ) {
    addToList( new ExperimentListItem( labels, name, parentFolders, false, chunkNumber, largeScaleChunkSize ), classification );
  }
  if ( !labelsNegative.isEmpty() ) {
    addToList( new ExperimentListItem( labelsNegative, name, parentFolders, true, chunkNumber, largeScaleChunkSize ), classification );
  }
}

final int size = interactionsForExperiment( experiment.getAc() );
    createExperimentListItems( largeScalePrefix, largeScale, chunk, classification, largeScaleChunkSize );
    chunk++;
createExperimentListItems( smallScalePrefix, chunk, index, classification, null );

public void createItemClassificationBySpecies() {
  for ( SimplifiedAnnotatedObject<BioSource> bioSource : species2experimentSet.keySet() ) {
    Collection<SimplifiedAnnotatedObject<Experiment>> smallScaleExp = species2experimentSet.get( bioSource );
    // split the set into subset of size under SMALL_SCALE_LIMIT
    String filePrefixGlobal = bioSource.getShortLabel().replace( ' ', '-' );
    createExpListItems( smallScaleExp,
              filePrefixGlobal + "_" + SMALL, // small scale
              filePrefixGlobal,              // large scale
              Classification.SPECIES );
  }
}

public Map<String, String> getExperimentWithErrors() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  return experimentsWithErrors;
}

private void createExperimentListItems( String name,
                    Collection<SimplifiedAnnotatedObject<Experiment>> exps,
                    Integer chunkNumber,
                    Classification classification,
                    Integer largeScaleChunkSize ) {
  List<String> labels = new ArrayList<String>();
  List<String> labelsNegative = new ArrayList<String>();
  for ( SimplifiedAnnotatedObject exp : exps ) {
    if ( isNegative( exp.getShortLabel() ) ) {
      labelsNegative.add( exp.getShortLabel() );
    } else {
      labels.add( exp.getShortLabel() );
    }
  }
  String parentFolders = parentFolders( exps, classification );
  if ( !labels.isEmpty() ) {
    addToList( new ExperimentListItem( labels, name, parentFolders, false, chunkNumber, largeScaleChunkSize ), classification );
  }
  if ( !labelsNegative.isEmpty() ) {
    addToList( new ExperimentListItem( labelsNegative, name, parentFolders, true, chunkNumber, largeScaleChunkSize ), classification );
  }
}

public List<ExperimentListItem> generateClassificationByPublications() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( publicationsListItems != null && !publicationsListItems.isEmpty() ) {
    return publicationsListItems;
  }
  createItemClassificationByPubmed();
  return publicationsListItems;
}

public List<ExperimentListItem> generateClassificationBySpecies() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( speciesListItems != null && !speciesListItems.isEmpty() ) {
    return speciesListItems;
  }
  createItemClassificationBySpecies();
  return speciesListItems;
}

final int size = interactionsForExperiment( experiment.getAc() );
    createExperimentListItems( largeScalePrefix, largeScale, chunk, classification, largeScaleChunkSize );
    chunk++;
createExperimentListItems( smallScalePrefix, chunk, index, classification, null );

public void createItemClassificationBySpecies() {
  for ( SimplifiedAnnotatedObject<BioSource> bioSource : species2experimentSet.keySet() ) {
    Collection<SimplifiedAnnotatedObject<Experiment>> smallScaleExp = species2experimentSet.get( bioSource );
    // split the set into subset of size under SMALL_SCALE_LIMIT
    String filePrefixGlobal = bioSource.getShortLabel().replace( ' ', '-' );
    createExpListItems( smallScaleExp,
              filePrefixGlobal + "_" + SMALL, // small scale
              filePrefixGlobal,              // large scale
              Classification.SPECIES );
  }
}

public Map<String, String> getExperimentWithErrors() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  return experimentsWithErrors;
}

public List<ExperimentListItem> generateAllClassifications() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  List<ExperimentListItem> allItems = new ArrayList<ExperimentListItem>();
  allItems.addAll( generateClassificationBySpecies() );
  allItems.addAll( generateClassificationByPublications() );
  return allItems;
}

private void createExperimentListItems( String name,
                    Collection<SimplifiedAnnotatedObject<Experiment>> exps,
                    Integer chunkNumber,
                    Classification classification,
                    Integer largeScaleChunkSize ) {
  List<String> labels = new ArrayList<String>();
  List<String> labelsNegative = new ArrayList<String>();
  for ( SimplifiedAnnotatedObject exp : exps ) {
    if ( isNegative( exp.getShortLabel() ) ) {
      labelsNegative.add( exp.getShortLabel() );
    } else {
      labels.add( exp.getShortLabel() );
    }
  }
  String parentFolders = parentFolders( exps, classification );
  if ( !labels.isEmpty() ) {
    addToList( new ExperimentListItem( labels, name, parentFolders, false, chunkNumber, largeScaleChunkSize ), classification );
  }
  if ( !labelsNegative.isEmpty() ) {
    addToList( new ExperimentListItem( labelsNegative, name, parentFolders, true, chunkNumber, largeScaleChunkSize ), classification );
  }
}

public List<ExperimentListItem> generateClassificationByPublications() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( publicationsListItems != null && !publicationsListItems.isEmpty() ) {
    return publicationsListItems;
  }
  createItemClassificationByPubmed();
  return publicationsListItems;
}

public List<ExperimentListItem> generateClassificationBySpecies() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( speciesListItems != null && !speciesListItems.isEmpty() ) {
    return speciesListItems;
  }
  createItemClassificationBySpecies();
  return speciesListItems;
}

public List<ExperimentListItem> generateClassificationByDatasets() {
  if ( !experimentsClassified ) {
    classifyExperiments();
  }
  if ( datasetsListItems != null && !datasetsListItems.isEmpty() ) {
    return datasetsListItems;
  }
  createItemClassificationByDataset();
  return datasetsListItems;
}

Javadoc

 
Generates a classified list of experiments based on : 
- their count of interaction, 
- the fact that they contain negative interaction.

Most used methods

addToList
classifyExperiments
Classify experiments matching searchPattern into a data structure according to species and experimen
classifyNegatives
Checks for a negative interaction. NB This will have to be done using SQL otherwise we end up materi
createExpListItems
createExperimentListItems
createItemClassificationByDataset
Build the classification by dataset. We keep the negative experiment separated from the non negative
createItemClassificationByPubmed
Build the classification by pubmed id. We keep the negative experiment separated from the non negati
createItemClassificationBySpecies
generateClassificationByPublications
generateClassificationBySpecies
getCreatedYear
Given a set of Experiments, it returns the year of the date of creation of the oldest experiment.
getDaoFactory

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How to useExperimentListGenerator in uk.ac.ebi.intact.application.dataConversion

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