Examples with StorageService org.dkpro.lab.storage.StorageService used on opensource projects

Example 6 with StorageService

use of org.dkpro.lab.storage.StorageService in project dkpro-tc by dkpro.

the class BatchCrossValidationReport method execute.

@Override
public void execute() throws Exception {
    StorageService store = getContext().getStorageService();
    TcFlexTable<String> table = TcFlexTable.forClass(String.class);
    table.setDefaultValue("");
    Set<String> idPool = getTaskIdsFromMetaData(getSubtasks());
    String learningMode = determineLearningMode(store, idPool);
    for (String id : idPool) {
        if (!TcTaskTypeUtil.isCrossValidationTask(store, id)) {
            continue;
        }
        Map<String, String> discriminatorsMap = getDiscriminatorsForContext(store, id, Task.DISCRIMINATORS_KEY);
        discriminatorsMap = ReportUtils.removeKeyRedundancy(discriminatorsMap);
        Map<String, String> values = new HashMap<String, String>();
        values.putAll(discriminatorsMap);
        // The classification result is always there
        File combinedId2outcome = store.locateKey(id, FILE_COMBINED_ID_OUTCOME_KEY);
        Map<String, String> results = MetricComputationUtil.getResults(combinedId2outcome, learningMode);
        values.putAll(results);
        // Majority baseline is not defined for regression i.e. might not be there
        File majBaseline = store.locateKey(id, FILE_COMBINED_BASELINE_MAJORITY_OUTCOME_KEY);
        if (isAvailable(majBaseline)) {
            Map<String, String> r = MetricComputationUtil.getResults(majBaseline, learningMode);
            for (Entry<String, String> e : r.entrySet()) {
                values.put(e.getKey() + ".MajorityBaseline", e.getValue());
            }
        }
        // Random baseline is not defined for regression i.e. might not be there
        File randomBaseline = store.locateKey(id, FILE_COMBINED_BASELINE_RANDOM_OUTCOME_KEY);
        if (isAvailable(randomBaseline)) {
            Map<String, String> r = MetricComputationUtil.getResults(randomBaseline, learningMode);
            for (Entry<String, String> e : r.entrySet()) {
                values.put(e.getKey() + ".RandomBaseline", e.getValue());
            }
        }
        table.addRow(getContextLabel(id), values);
    }
    /*
         * TODO: make rows to columns e.g. create a new table and set columns to rows of old table
         * and rows to columns but than must be class FlexTable in this case adapted accordingly:
         * enable setting
         */
    ReportUtils.writeExcelAndCSV(getContext(), getContextLabel(), table, EVAL_FILE_NAME, SUFFIX_EXCEL, SUFFIX_CSV);
}

Example 7 with StorageService

use of org.dkpro.lab.storage.StorageService in project dkpro-tc by dkpro.

the class BatchTrainTestReport method execute.

@Override
public void execute() throws Exception {
    StorageService store = getContext().getStorageService();
    TcFlexTable<String> table = TcFlexTable.forClass(String.class);
    table.setDefaultValue("");
    Set<String> idPool = getTaskIdsFromMetaData(getSubtasks());
    for (String id : idPool) {
        if (!TcTaskTypeUtil.isFacadeTask(store, id)) {
            continue;
        }
        Set<String> wrapped = new HashSet<>();
        wrapped.add(id);
        Set<String> subTaskId = collectTasks(wrapped);
        subTaskId.remove(id);
        // Should be only one anyway?
        for (String subId : subTaskId) {
            if (!TcTaskTypeUtil.isMachineLearningAdapterTask(store, subId)) {
                continue;
            }
            Map<String, String> discriminatorsMap = getDiscriminators(store, subId);
            discriminatorsMap = ReportUtils.clearDiscriminatorsByExcludePattern(discriminatorsMap, discriminatorsToExclude);
            discriminatorsMap = ReportUtils.removeKeyRedundancy(discriminatorsMap);
            // add the results into the discriminator map
            File id2o = getId2Outcome(subId);
            String mode = getDiscriminator(store, subId, DIM_LEARNING_MODE);
            Map<String, String> resultMap = MetricComputationUtil.getResults(id2o, mode);
            discriminatorsMap.putAll(resultMap);
            File majBaseline = getBaselineMajorityClassId2Outcome(subId);
            if (isAvailable(majBaseline)) {
                Map<String, String> results = MetricComputationUtil.getResults(majBaseline, mode);
                for (Entry<String, String> e : results.entrySet()) {
                    discriminatorsMap.put(e.getKey() + ".MajorityBaseline", e.getValue());
                }
            }
            File randomBaseline = getBaselineRandomId2Outcome(subId);
            if (isAvailable(randomBaseline)) {
                Map<String, String> results = MetricComputationUtil.getResults(randomBaseline, mode);
                for (Entry<String, String> e : results.entrySet()) {
                    discriminatorsMap.put(e.getKey() + ".RandomBaseline", e.getValue());
                }
            }
            table.addRow(getContextLabel(subId), discriminatorsMap);
        }
    }
    ReportUtils.writeExcelAndCSV(getContext(), getContextLabel(), table, EVAL_FILE_NAME, SUFFIX_EXCEL, SUFFIX_CSV);
}

Example 8 with StorageService

use of org.dkpro.lab.storage.StorageService in project dkpro-tc by dkpro.

the class DeepLearningInnerBatchReport method execute.

@Override
public void execute() throws Exception {
    StorageService store = getContext().getStorageService();
    Properties prop = new Properties();
    List<File> id2outcomeFiles = new ArrayList<>();
    Set<String> ids = getTaskIdsFromMetaData(getSubtasks());
    for (String id : ids) {
        if (!TcTaskTypeUtil.isMachineLearningAdapterTask(store, id)) {
            continue;
        }
        Map<String, String> discriminatorsMap = store.retrieveBinary(id, Task.DISCRIMINATORS_KEY, new PropertiesAdapter()).getMap();
        File id2outcomeFile = store.locateKey(id, Constants.ID_OUTCOME_KEY);
        id2outcomeFiles.add(id2outcomeFile);
        for (Entry<String, String> e : discriminatorsMap.entrySet()) {
            String key = e.getKey();
            String value = e.getValue();
            prop.setProperty(key, value);
        }
    }
    String learningMode = getDiscriminator(store, ids, DIM_LEARNING_MODE);
    ID2OutcomeCombiner<String> aggregator = new ID2OutcomeCombiner<>(learningMode);
    for (File id2o : id2outcomeFiles) {
        aggregator.add(id2o, learningMode);
    }
    writeCombinedOutcomeReport(aggregator.generateId2OutcomeFile());
}

Example 9 with StorageService

use of org.dkpro.lab.storage.StorageService in project dkpro-tc by dkpro.

the class BasicResultReport method writeToDisk.

private void writeToDisk(Properties pa) throws Exception {
    StorageService store = getContext().getStorageService();
    File key = store.locateKey(getContext().getId(), OUTPUT_FILE);
    FileOutputStream fos = null;
    try {
        fos = new FileOutputStream(key);
        pa.store(fos, "Results");
    } finally {
        IOUtils.closeQuietly(fos);
    }
}

Example 10 with StorageService

use of org.dkpro.lab.storage.StorageService in project dkpro-tc by dkpro.

the class BatchRuntimeReport method execute.

@Override
public void execute() throws Exception {
    List<String> keyOrdered = new ArrayList<>();
    StorageService store = getContext().getStorageService();
    Set<String> taskIds = getTaskIdsFromMetaData(getSubtasks());
    taskIds = readInnerTasksIfCrossValidation(taskIds);
    for (String id : taskIds) {
        if (TcTaskTypeUtil.isFacadeTask(store, id)) {
            Set<String> subTasks = collectSubtasks(id);
            subTasks.remove(id);
            for (String subId : subTasks) {
                long executionTime = getExecutionTime(subId);
                registerTime(subId, executionTime);
                keyOrdered.add(subId);
            }
            // Facade tasks are not registered they are just a shell and do not much anyway
            continue;
        }
        long executionTime = getExecutionTime(id);
        registerTime(id, executionTime);
        keyOrdered.add(id);
    }
    String output = buildOutput(keyOrdered);
    File runtime = getContext().getFile(RUNTIME_KEY, AccessMode.READWRITE);
    FileUtils.writeStringToFile(runtime, output, "utf-8");
}