Available Methods

warn ( )

Related Classes

java.lang.Double

org.neo4j.logging.Log Java Examples

The following examples show how to use org.neo4j.logging.Log. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.

Example #1

Source File: SimpleLRModel.java From ml-models with Apache License 2.0

6 votes

@Override
void addTest(List<Double> given, double expected, Log log) {
    if (dataInvalid(given)) log.warn("Data point " + given.toString() + ", " + Double.toString(expected) +
            " is not valid and so was not added to the testing data.");
    else {
        double fact1 = getNTest() + 1.0;
        double fact2 = getNTest() / fact1;
        double dy = expected - ybar;
        ybar += dy / fact1;
        double rdev = expected - R.getIntercept() - given.get(0) * R.getSlope();
        sse += rdev * rdev;
        if (hasConstant()) sst += fact2 * dy * dy;
        else sst += expected * expected;
        nTest++;
        state = State.testing;
    }
}

Example #2

Source File: SimpleLRModel.java From ml-models with Apache License 2.0

6 votes

@Override
void removeTest(List<Double> given, double expected, Log log) {
    if (nTest > 0) {
        if (dataInvalid(given)) log.warn("Data point " + given.toString() + ", " + Double.toString(expected) +
                " is not valid and so was not removed from the testing data.");
        else {
            double fact1 = nTest - 1;
            double fact2 = nTest / fact1;
            double dy = expected - ybar;
            ybar -= dy / fact1;
            double rdev = expected - R.getIntercept() - given.get(0) * R.getSlope();
            sse -= rdev * rdev;
            sst -= fact2 * dy * dy;
            nTest--;
            state = State.testing;
        }
    }
}

Example #3

Source File: InitBuilderTest.java From neo4j-versioner-core with Apache License 2.0

5 votes

@Test
public void shouldBuildCorrectProcedureInstance() {
    GraphDatabaseService db = mock(GraphDatabaseService.class);
    Log log = mock(Log.class);

    Optional<Init> result = new InitBuilder().withDb(db).withLog(log).build();

    assertThat(result.isPresent(), is(true));
    assertThat(result.get().db, is(db));
    assertThat(result.get().log, is(log));
}

Example #4

Source File: GlsLRModel.java From ml-models with Apache License 2.0

5 votes

@Override
public void addTrain(List<Double> given, double expected, Log log) {
    if (given.size() != numVars) throw new IllegalArgumentException("incorrect number of variables in given.");
    data.add(given);
    response.add(expected);
    numObs += 1;
    this.state = State.training;
}

Example #5

Source File: UpdateBuilderTest.java From neo4j-versioner-core with Apache License 2.0

5 votes

@Test
public void shouldBuildCorrectProcedureInstance() {
    GraphDatabaseService db = mock(GraphDatabaseService.class);
    Log log = mock(Log.class);

    Optional<Update> result = new UpdateBuilder().withDb(db).withLog(log).build();

    assertThat(result.isPresent(), is(true));
    assertThat(result.get().db, is(db));
    assertThat(result.get().log, is(log));
}

Example #6

Source File: RollbackBuilderTest.java From neo4j-versioner-core with Apache License 2.0

5 votes

@Test
public void shouldBuildCorrectProcedureInstance() {
    GraphDatabaseService db = mock(GraphDatabaseService.class);
    Log log = mock(Log.class);

    Optional<Rollback> result = new RollbackBuilder().withDb(db).withLog(log).build();

    assertThat(result.isPresent(), is(true));
    assertThat(result.get().db, is(db));
    assertThat(result.get().log, is(log));
}

Example #7

Source File: LRModel.java From ml-models with Apache License 2.0

5 votes

void removeMany(List<List<Double>> given, List<Double> expected, String type, Log log) {
    if (given.size() != expected.size())
        throw new IllegalArgumentException("Length of given does not match length of expected.");
    switch(type) {
        case "train":
            for (int i = 0; i < given.size(); i++) removeTrain(given.get(i), expected.get(i), log);
            break;
        case "test":
            for (int i = 0; i < given.size(); i++) removeTest(given.get(i), expected.get(i), log);
            break;
        default:
            throw new IllegalArgumentException("Cannot add data of unrecognized type: " + type);
    }
}

Example #8

Source File: MillerLRModel.java From ml-models with Apache License 2.0

5 votes

@Override
void addTrain(List<Double> given, double expected, Log log) {
    if (dataInvalid(given)) log.warn("Data point " + given.toString() + ", " + Double.toString(expected) +
            " is not valid and so was not added to the training data.");
    else {
        double[] givenArr = LR.doubleListToArray(given);
        R.addObservation(givenArr, expected);
        if (state == State.testing || state == State.ready) resetTest();
        state = State.training;
    }
}

Example #9

Source File: LRModel.java From ml-models with Apache License 2.0

5 votes

void remove(List<Double> given, double expected, String type, Log log) {
    switch(type) {
        case "train": removeTrain(given, expected, log); break;
        case "test": removeTest(given, expected, log); break;
        default: throw new IllegalArgumentException("Cannot remove data of unrecognized type: " + type);
    }
}

Example #10

Source File: MillerLRModel.java From ml-models with Apache License 2.0

5 votes

@Override
void addTest(List<Double> given, double expected, Log log) {
    if (!(state == State.testing)) {
        clearTest();
        train();
    }
    if (dataInvalid(given)) log.warn("Data point " + given.toString() + ", " + Double.toString(expected) +
            " is not valid and so was not added to the testing data.");
    else {
        double fact1 = nTest + 1.0;
        double fact2 = nTest / fact1;
        double dy = expected - ybar;
        ybar += dy / fact1;
        double[] params = trained.getParameterEstimates();
        double rdev = expected;
        if (hasConstant()) {
            rdev -= params[0];
            for (int i = 1; i < params.length; i++) rdev -= params[i] * given.get(i - 1);
            sst += fact2 * dy * dy;
        } else {
            for (int i = 0; i < params.length; i++) rdev -= params[i] * given.get(i);
            sst += expected * expected;
        }
        sse += rdev * rdev;
        nTest++;
        state = State.testing;
    }
}

Example #11

Source File: LRModel.java From ml-models with Apache License 2.0

5 votes

void addMany(List<List<Double>> given, List<Double> expected, String type, Log log) {
    if (given.size() != expected.size())
        throw new IllegalArgumentException("Length of given does not match length of expected.");
    switch(type) {
        case "train":
            for (int i = 0; i < given.size(); i++) addTrain(given.get(i), expected.get(i), log);
            break;
        case "test":
            for (int i = 0; i < given.size(); i++) addTest(given.get(i), expected.get(i), log);
            break;
        default:
            throw new IllegalArgumentException("Cannot add data of unrecognized type: " + type);
    }
}

Example #12

Source File: SimpleLRModel.java From ml-models with Apache License 2.0

5 votes

@Override
void addTrain(List<Double> given, double expected, Log log) {
    if (dataInvalid(given)) log.warn("Data point " + given.toString() + ", " + Double.toString(expected) +
            " is not valid and so was not added to the training data.");
    else {
        R.addData(given.get(0), expected);
        if (state == State.testing || state == State.ready) resetTest();
        state = State.training;
    }
}

Example #13

Source File: SimpleLRModel.java From ml-models with Apache License 2.0

5 votes

@Override
protected void removeTrain(List<Double> input, double output, Log log) {
    if (dataInvalid(input)) log.warn("Data point " + input.toString() + ", " + Double.toString(output) +
            " is not valid and so was not added to the training data.");
    else {
        for (double x : input) R.removeData(x, output);
        if (state == State.testing || state == State.ready) resetTest();
        state = State.training;
    }
}

Example #14

Source File: OlsLRModel.java From ml-models with Apache License 2.0

5 votes

@Override
void addTrain(List<Double> given, double expected, Log log) {
    if (given.size() != numVars) throw new IllegalArgumentException("incorrect number of variables in given.");
    data.add(expected);
    data.addAll(given);
    numObs += 1;
    this.state = State.training;
}

Example #15

Source File: LRModel.java From ml-models with Apache License 2.0

5 votes

void add(List<Double> given, double expected, String type, Log log) {
    switch(type) {
        case "train": addTrain(given, expected, log); break;
        case "test": addTest(given, expected, log); break;
        default: throw new IllegalArgumentException("Cannot add data of unrecognized type: " + type);
    }
}

Example #16

Source File: Algorithm.java From ml-models with Apache License 2.0

4 votes

public ME withLog(Log log) {
    return withProgressLogger(ProgressLogger.wrap(log, getClass().getSimpleName()));
}

Example #17

Source File: MillerLRModel.java From ml-models with Apache License 2.0

4 votes

@Override
void removeTest(List<Double> given, double expected, Log log) {
    throw new IllegalArgumentException("Cannot remove test data from multiple linear regression.");
}

Example #18

Source File: MillerLRModel.java From ml-models with Apache License 2.0

4 votes

@Override
protected void removeTrain(List<Double> input, double output, Log log) {
    throw new IllegalArgumentException("Data cannot be removed from a multiple linear regression.");
}

Example #19

Source File: DecisionTreeExpanderTwo.java From decision_trees_with_rules with MIT License

4 votes

public DecisionTreeExpanderTwo(Map<String, String> facts, Log log) {
    this.facts = facts;
    this.log = log;
    se.setReturnType(String.class);
}

Example #20

Source File: OlsLRModel.java From ml-models with Apache License 2.0

2 votes

@Override
void removeTest(List<Double> input, double output, Log log) {

}

Example #21

Source File: OlsLRModel.java From ml-models with Apache License 2.0

2 votes

@Override
void removeTrain(List<Double> input, double output, Log log) {

}

Example #22

Source File: OlsLRModel.java From ml-models with Apache License 2.0

2 votes

@Override
void addTest(List<Double> given, double expected, Log log) {

}

Example #23

Source File: GlsLRModel.java From ml-models with Apache License 2.0

2 votes

@Override
void removeTrain(List<Double> input, double output, Log log) {

}

Example #24

Source File: CoreProcedureBuilder.java From neo4j-versioner-core with Apache License 2.0

2 votes

/**
 * Adds a {@link Log} and returns the current builder
 *
 * @param log
 * @return this
 */
public CoreProcedureBuilder<T> withLog(Log log) {
    this.log = log;
    return this;
}

Example #25

Source File: GlsLRModel.java From ml-models with Apache License 2.0

2 votes

@Override
void removeTest(List<Double> input, double output, Log log) {

}

Example #26

Source File: GlsLRModel.java From ml-models with Apache License 2.0

2 votes

@Override
void addTest(List<Double> given, double expected, Log log) {

}

Example #27

Source File: LRModel.java From ml-models with Apache License 2.0

votes

abstract void addTrain(List<Double> given, double expected, Log log);

Example #28

Source File: LRModel.java From ml-models with Apache License 2.0

votes

abstract void removeTrain(List<Double> given, double expected, Log log);

Example #29

Source File: LRModel.java From ml-models with Apache License 2.0

votes

abstract void addTest(List<Double> given, double expected, Log log);

Example #30

Source File: LRModel.java From ml-models with Apache License 2.0

votes

abstract void removeTest(List<Double> given, double expected, Log log);