Examples with RankingExpression com.yahoo.searchlib.rankingexpression.RankingExpression used on opensource projects

Example 11 with RankingExpression

use of com.yahoo.searchlib.rankingexpression.RankingExpression in project vespa by vespa-engine.

the class SimplifierTestCase method testParenthesisPreservation.

@Test
public void testParenthesisPreservation() throws ParseException {
    Simplifier s = new Simplifier();
    TransformContext c = new TransformContext(Collections.emptyMap());
    CompositeNode transformed = (CompositeNode) s.transform(new RankingExpression("a + (b + c) / 100000000.0"), c).getRoot();
    assertEquals("a + (b + c) / 100000000.0", transformed.toString());
}

Example 12 with RankingExpression

use of com.yahoo.searchlib.rankingexpression.RankingExpression in project vespa by vespa-engine.

the class SimplifierTestCase method testSimplify.

@Test
public void testSimplify() throws ParseException {
    Simplifier s = new Simplifier();
    TransformContext c = new TransformContext(Collections.emptyMap());
    assertEquals("a + b", s.transform(new RankingExpression("a + b"), c).toString());
    assertEquals("6.5", s.transform(new RankingExpression("1.0 + 2.0 + 3.5"), c).toString());
    assertEquals("6.5", s.transform(new RankingExpression("1.0 + ( 2.0 + 3.5 )"), c).toString());
    assertEquals("6.5", s.transform(new RankingExpression("( 1.0 +  2.0 ) + 3.5 "), c).toString());
    assertEquals("6.5", s.transform(new RankingExpression("1.0 + ( 2.0 + 3.5 )"), c).toString());
    assertEquals("7.5", s.transform(new RankingExpression("1.0 + ( 2.0 + 3.5 ) + 1"), c).toString());
    assertEquals("6.5 + a", s.transform(new RankingExpression("1.0 + ( 2.0 + 3.5 ) + a"), c).toString());
    assertEquals("7.5", s.transform(new RankingExpression("7.5 + ( 2.0 + 3.5 ) * 0.0"), c).toString());
    assertEquals("7.5", s.transform(new RankingExpression("7.5 + ( 2.0 + 3.5 ) * (0.0)"), c).toString());
    assertEquals("7.5", s.transform(new RankingExpression("7.5 + ( 2.0 + 3.5 ) * (1.0 - 1.0)"), c).toString());
    assertEquals("7.5", s.transform(new RankingExpression("if (2 > 0, 3.5 * 2 + 0.5, a *3 )"), c).toString());
    assertEquals("0.0", s.transform(new RankingExpression("0.0 * (1.3 + 7.0)"), c).toString());
    assertEquals("6.4", s.transform(new RankingExpression("max(0, 10.0-2.0)*(1-fabs(0.0-0.2))"), c).toString());
    assertEquals("(query(d) + query(b) - query(a)) * query(c) / query(e)", s.transform(new RankingExpression("(query(d) + query(b) - query(a)) * query(c) / query(e)"), c).toString());
    assertEquals("14.0", s.transform(new RankingExpression("5 + (2 + 3) + 4"), c).toString());
    assertEquals("28.0 + bar", s.transform(new RankingExpression("7.0 + 12.0 + 9.0 + bar"), c).toString());
    assertEquals("1.0 - 0.001 * attribute(number)", s.transform(new RankingExpression("1.0 - 0.001*attribute(number)"), c).toString());
    assertEquals("attribute(number) * 1.5 - 0.001 * attribute(number)", s.transform(new RankingExpression("attribute(number) * 1.5 - 0.001 * attribute(number)"), c).toString());
}

Example 13 with RankingExpression

use of com.yahoo.searchlib.rankingexpression.RankingExpression in project vespa by vespa-engine.

the class StreamEvaluationBenchmark method run.

private void run(String expressionString, List<Map<String, Double>> features, int iterations) throws ParseException {
    // Optimize
    RankingExpression expression = new RankingExpression(expressionString);
    DoubleOnlyArrayContext contextPrototype = new DoubleOnlyArrayContext(expression, true);
    OptimizationReport forestOptimizationReport = new ExpressionOptimizer().optimize(expression, contextPrototype);
    System.out.println(forestOptimizationReport);
    System.out.println("Optimized expression: " + expression.getRoot());
    // Warm up
    out("Warming up ...");
    double total = 0;
    total += benchmarkIterations(expression, contextPrototype, features, Math.max(iterations / 5, 1));
    oul("done");
    // Benchmark
    out("Running " + iterations + " of 'stream' ...");
    long tStartTime = System.currentTimeMillis();
    total += benchmarkIterations(expression, contextPrototype, features, iterations);
    long totalTime = System.currentTimeMillis() - tStartTime;
    oul("done");
    oul("   Total time running 'stream': " + totalTime + " ms (" + totalTime * 1000 / (iterations * features.size()) + " microseconds/expression)");
}

Example 14 with RankingExpression

use of com.yahoo.searchlib.rankingexpression.RankingExpression in project vespa by vespa-engine.

the class GBDTOptimizerTestCase method testNodeOptimization.

public void testNodeOptimization() throws ParseException {
    String gbdtString = "if (LW_NEWS_SEARCHES_RATIO < 1.72971, 0.0697159, if (LW_USERS < 0.10496, if (SEARCHES < 0.0329127, 0.151257, 0.117501), if (SUGG_OVERLAP < 18.5, 0.0897622, 0.0756903))) + \n" + "if (LW_NEWS_SEARCHES_RATIO < 1.73156, if (NEWS_USERS < 0.0737993, -0.00481646, 0.00110018), if (LW_USERS < 0.0844616, 0.0488919, if (SUGG_OVERLAP < 32.5, 0.0136917, 9.85328E-4))) + \n" + "if (LW_NEWS_SEARCHES_RATIO < 1.74451, -0.00298257, if (LW_USERS < 0.116207, if (SEARCHES < 0.0329127, 0.0676105, 0.0340198), if (NUM_WORDS < 1.5, -8.55514E-5, 0.0112406))) + \n" + "if (LW_NEWS_SEARCHES_RATIO < 1.72995, if (NEWS_USERS < 0.0737993, -0.00407515, 0.00139088), if (LW_USERS == 0.0509035, 0.0439466, if (LW_USERS < 0.325818, 0.0187156, 0.00236949)))";
    RankingExpression gbdt = new RankingExpression(gbdtString);
    // Regular evaluation
    MapContext arguments = new MapContext();
    arguments.put("LW_NEWS_SEARCHES_RATIO", 1d);
    arguments.put("SUGG_OVERLAP", 17d);
    double result1 = gbdt.evaluate(arguments).asDouble();
    arguments.put("LW_NEWS_SEARCHES_RATIO", 2d);
    arguments.put("SUGG_OVERLAP", 20d);
    double result2 = gbdt.evaluate(arguments).asDouble();
    arguments.put("LW_NEWS_SEARCHES_RATIO", 2d);
    arguments.put("SUGG_OVERLAP", 40d);
    double result3 = gbdt.evaluate(arguments).asDouble();
    // Optimized evaluation
    ArrayContext fArguments = new ArrayContext(gbdt);
    ExpressionOptimizer optimizer = new ExpressionOptimizer();
    optimizer.getOptimizer(GBDTForestOptimizer.class).setEnabled(false);
    OptimizationReport report = optimizer.optimize(gbdt, fArguments);
    assertEquals(4, report.getMetric("Optimized GDBT trees"));
    fArguments.put("LW_NEWS_SEARCHES_RATIO", 1d);
    fArguments.put("SUGG_OVERLAP", 17d);
    double oResult1 = gbdt.evaluate(fArguments).asDouble();
    fArguments.put("LW_NEWS_SEARCHES_RATIO", 2d);
    fArguments.put("SUGG_OVERLAP", 20d);
    double oResult2 = gbdt.evaluate(fArguments).asDouble();
    fArguments.put("LW_NEWS_SEARCHES_RATIO", 2d);
    fArguments.put("SUGG_OVERLAP", 40d);
    double oResult3 = gbdt.evaluate(fArguments).asDouble();
    // Assert the same results are produced
    assertEquals(result1, oResult1);
    assertEquals(result2, oResult2);
    assertEquals(result3, oResult3);
}

Example 15 with RankingExpression

use of com.yahoo.searchlib.rankingexpression.RankingExpression in project vespa by vespa-engine.

the class GBDTOptimizerTestCase method testFeatureNamesWithDots.

public void testFeatureNamesWithDots() throws ParseException {
    String gbdtString = "if (a.b < 1.72971, 0.0697159, if (a.b.c < 0.10496, if (a.c < 0.0329127, 0.151257, 0.117501), if (a < 18.5, 0.0897622, 0.0756903))) + 1";
    RankingExpression gbdt = new RankingExpression(gbdtString);
    // Regular evaluation
    MapContext arguments = new MapContext();
    arguments.put("a.b", 1d);
    arguments.put("a.b.c", 0.1d);
    arguments.put("a.c", 0.01d);
    arguments.put("a", 19d);
    double result = gbdt.evaluate(arguments).asDouble();
    // Optimized evaluation
    ArrayContext fArguments = new ArrayContext(gbdt);
    OptimizationReport report = new OptimizationReport();
    new GBDTOptimizer().optimize(gbdt, fArguments, report);
    assertEquals("Optimization result is as expected:\n" + report, 1, report.getMetric("Optimized GDBT trees"));
    fArguments.put("a.b", 1d);
    fArguments.put("a.b.c", 0.1d);
    fArguments.put("a.c", 0.01d);
    fArguments.put("a", 19d);
    double oResult = gbdt.evaluate(fArguments).asDouble();
    // Assert the same results are produced
    assertEquals(result, oResult);
}