Examples with LocalSampleCalculatorInput org.opensearch.ml.common.parameter.LocalSampleCalculatorInput used on opensource projects

Example 1 with LocalSampleCalculatorInput

use of org.opensearch.ml.common.parameter.LocalSampleCalculatorInput in project ml-commons by opensearch-project.

the class MLEngineClassLoaderTests method initInstance_LocalSampleCalculator.

@Test
public void initInstance_LocalSampleCalculator() {
    List<Double> inputData = new ArrayList<>();
    double d1 = 10.0;
    double d2 = 20.0;
    inputData.add(d1);
    inputData.add(d2);
    LocalSampleCalculatorInput input = LocalSampleCalculatorInput.builder().operation("sum").inputData(inputData).build();
    Map<String, Object> properties = new HashMap<>();
    properties.put("wrongField", "test");
    Client client = mock(Client.class);
    properties.put("client", client);
    Settings settings = Settings.EMPTY;
    properties.put("settings", settings);
    // set properties
    MLEngineClassLoader.deregister(FunctionName.LOCAL_SAMPLE_CALCULATOR);
    LocalSampleCalculator instance = MLEngineClassLoader.initInstance(FunctionName.LOCAL_SAMPLE_CALCULATOR, input, Input.class, properties);
    SampleAlgoOutput output = (SampleAlgoOutput) instance.execute(input);
    assertEquals(d1 + d2, output.getSampleResult(), 1e-6);
    assertEquals(client, instance.getClient());
    assertEquals(settings, instance.getSettings());
    // don't set properties
    instance = MLEngineClassLoader.initInstance(FunctionName.LOCAL_SAMPLE_CALCULATOR, input, Input.class);
    output = (SampleAlgoOutput) instance.execute(input);
    assertEquals(d1 + d2, output.getSampleResult(), 1e-6);
    assertNull(instance.getClient());
    assertNull(instance.getSettings());
}

Example 2 with LocalSampleCalculatorInput

use of org.opensearch.ml.common.parameter.LocalSampleCalculatorInput in project ml-commons by opensearch-project.

the class LocalSampleCalculatorTest method executeWithWrongOperation.

@Test
public void executeWithWrongOperation() {
    exceptionRule.expect(IllegalArgumentException.class);
    exceptionRule.expectMessage("can't support this operation");
    input = new LocalSampleCalculatorInput("wrong_operation", Arrays.asList(1.0, 2.0, 3.0));
    calculator.execute(input);
}

Example 3 with LocalSampleCalculatorInput

use of org.opensearch.ml.common.parameter.LocalSampleCalculatorInput in project ml-commons by opensearch-project.

the class LocalSampleCalculator method execute.

@Override
public Output execute(Input input) {
    if (input == null || !(input instanceof LocalSampleCalculatorInput)) {
        throw new IllegalArgumentException("wrong input");
    }
    LocalSampleCalculatorInput sampleCalculatorInput = (LocalSampleCalculatorInput) input;
    String operation = sampleCalculatorInput.getOperation();
    List<Double> inputData = sampleCalculatorInput.getInputData();
    switch(operation) {
        case "sum":
            double sum = inputData.stream().mapToDouble(f -> f.doubleValue()).sum();
            return new SampleAlgoOutput(sum);
        case "max":
            double max = inputData.stream().max(Comparator.naturalOrder()).get();
            return new SampleAlgoOutput(max);
        case "min":
            double min = inputData.stream().min(Comparator.naturalOrder()).get();
            return new SampleAlgoOutput(min);
        default:
            throw new IllegalArgumentException("can't support this operation");
    }
}

Example 4 with LocalSampleCalculatorInput

use of org.opensearch.ml.common.parameter.LocalSampleCalculatorInput in project ml-commons by opensearch-project.

the class MLEngineTest method executeLocalSampleCalculator.

@Test
public void executeLocalSampleCalculator() {
    Input input = new LocalSampleCalculatorInput("sum", Arrays.asList(1.0, 2.0));
    SampleAlgoOutput output = (SampleAlgoOutput) MLEngine.execute(input);
    Assert.assertEquals(3.0, output.getSampleResult(), 1e-5);
}

Example 5 with LocalSampleCalculatorInput

use of org.opensearch.ml.common.parameter.LocalSampleCalculatorInput in project ml-commons by opensearch-project.

the class MLEngineTest method trainAndPredictWithInvalidInput.

@Test
public void trainAndPredictWithInvalidInput() {
    exceptionRule.expect(IllegalArgumentException.class);
    exceptionRule.expectMessage("Input should be MLInput");
    Input input = new LocalSampleCalculatorInput("sum", Arrays.asList(1.0, 2.0));
    MLEngine.trainAndPredict(input);
}