Examples with HasNameValue org.kie.kogito.explainability.api.HasNameValue used on opensource projects

Example 1 with HasNameValue

use of org.kie.kogito.explainability.api.HasNameValue in project kogito-apps by kiegroup.

the class ConversionUtils method toFeatureList.

// //////////////////////////
// TO EXPLAINABILITY MODEL
// //////////////////////////
/*
     * ---------------------------------------
     * Feature conversion
     * ---------------------------------------
     */
public static List<Feature> toFeatureList(Collection<? extends HasNameValue<TypedValue>> values, Collection<CounterfactualSearchDomain> searchDomains) {
    if (searchDomains.isEmpty()) {
        return toFeatureList(values);
    } else {
        AtomicInteger index = new AtomicInteger();
        final List<FeatureDomain> featureDomains = toFeatureDomainList(searchDomains);
        final List<Boolean> featureConstraints = toFeatureConstraintList(searchDomains);
        return values.stream().map(hnv -> {
            final String name = hnv.getName();
            final TypedValue value = hnv.getValue();
            final int i = index.getAndIncrement();
            return toFeature(name, value, featureDomains.get(i), featureConstraints.get(i));
        }).collect(Collectors.toList());
    }
}

Example 2 with HasNameValue

use of org.kie.kogito.explainability.api.HasNameValue in project kogito-apps by kiegroup.

the class RemotePredictionProvider method toPredictionOutput.

protected PredictionOutput toPredictionOutput(JsonObject mainObj) {
    if (mainObj == null || !mainObj.containsKey("result")) {
        LOG.error("Malformed json {}", mainObj);
        return null;
    }
    List<Output> resultOutputs = toOutputList(mainObj.getJsonObject("result"));
    List<String> resultOutputNames = resultOutputs.stream().map(Output::getName).collect(toList());
    Map<String, TypedValue> mappedOutputs = predictionOutputs.stream().collect(Collectors.toMap(HasNameValue::getName, HasNameValue::getValue));
    // It's possible that some outputs are missing in the response from the prediction service
    // (e.g. when the generated perturbed inputs don't make sense and a decision is skipped).
    // The explainer, however, may throw exceptions if it can't find all the inputs that were
    // specified in the execution request.
    // Here we take the outputs received from the prediction service and we fill (only if needed)
    // the missing ones with Output objects containing "null" values of type UNDEFINED, to make
    // the explainer happy.
    List<Output> outputs = Stream.concat(resultOutputs.stream().filter(output -> mappedOutputs.containsKey(output.getName())), mappedOutputs.keySet().stream().filter(key -> !resultOutputNames.contains(key)).map(key -> new Output(key, Type.UNDEFINED, new Value(null), 1d))).collect(toList());
    return new PredictionOutput(outputs);
}