Example usage for com.fasterxml.jackson.dataformat.csv CsvMapper writeValueAsString

Introduction

In this page you can find the example usage for com.fasterxml.jackson.dataformat.csv CsvMapper writeValueAsString.

Prototype

@SuppressWarnings("resource")
public String writeValueAsString(Object value) throws JsonProcessingException 

Source Link

Document

Method that can be used to serialize any Java value as a String.

Usage

From source file:edu.cmu.cs.lti.discoursedb.annotation.lightside.io.LightSideService.java

/**
 * Exports data in a format that can be imported into LightSide and then annotated with a classifier that was training with
 * data generated by the exportAnnotations methods.
 * /*ww  w. j  a v  a  2  s.com*/
 * @param outputFilePath path to the output file to which the extracted data should be written
 * @param contributions contributions that should be exported for annotation
 */
@Transactional(readOnly = true)
public void exportDataForAnnotation(String outputFilePath, Iterable<Contribution> contributions) {
    Assert.hasText(outputFilePath, "Path to the output file cannot be empty.");
    File outputFile = new File(outputFilePath);
    Assert.isTrue(!outputFile.isDirectory(),
            outputFilePath + " points to a directory but should point to a file.");

    StringBuilder output = new StringBuilder();
    CsvMapper mapper = new CsvMapper();
    try {
        if (!outputFile.exists()) {
            //only add header once
            output.append(mapper.writeValueAsString(new String[] { TEXT_COL, ID_COL }));
        }
        for (Contribution contrib : contributions) {
            output.append(mapper.writeValueAsString(
                    new String[] { contrib.getCurrentRevision().getText(), String.valueOf(contrib.getId()) }));
        }
        FileUtils.writeStringToFile(outputFile, output.toString(), true);
    } catch (IOException e) {
        log.error("Error writing exported data to csv");
    }
}

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From source file:edu.cmu.cs.lti.discoursedb.annotation.lightside.io.LightSideService.java

@Transactional(readOnly = true)
private String generateLightSideOutput(List<RawDataInstance> data) throws JsonProcessingException {
    StringBuilder output = new StringBuilder();
    CsvMapper mapper = new CsvMapper();

    //generate list of binary label types
    Set<String> binaryLabelTypes = data.stream().parallel()
            .flatMap(instance -> instance.getAnnotations().entrySet().stream())
            .filter(m -> m.getValue().toLowerCase().equals(LABEL_ASSIGNED_VAL))
            .map(m -> m.getKey().toLowerCase()).collect(Collectors.toSet());

    //generate header
    Set<String> types = data.stream().parallel()
            .flatMap(instance -> instance.getAnnotations().entrySet().stream())
            .map(m -> m.getKey().toLowerCase()).collect(Collectors.toSet());

    Assert.isTrue(!types.contains(TEXT_COL), "No feature with the name \"" + TEXT_COL + "\" is allowed.");

    List<String> header = new ArrayList<>(types.size() + 1);
    header.add(TEXT_COL);//from   w w w .j a  va  2s. c o  m
    header.addAll(types);
    output.append(mapper.writeValueAsString(header));

    //generate data vectors
    for (RawDataInstance instance : data) {
        List<String> featVector = new ArrayList<>(header.size());
        featVector.add(instance.getText());
        Map<String, String> curInstAnnos = instance.getAnnotations();
        for (String type : types) {
            //Label assigned to current instance 
            if (curInstAnnos.containsKey(type)) {
                featVector.add(curInstAnnos.get(type));
            }
            //Label not assigned to current instance - handle missing value 
            else {
                if (binaryLabelTypes.contains(type)) {
                    //missing binary label interpreted as "false"
                    featVector.add(LABEL_MISSING_VAL);
                } else {
                    //missing value on interpreted as "null"
                    featVector.add(VALUE_MISSING_VAL);
                }
            }
        }
        Assert.isTrue(featVector.size() == header.size(), "Error writing feature vector. Wrong size.");
        output.append(mapper.writeValueAsString(featVector));
    }
    return output.toString();
}

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