List of minimize() Examples

Examples of minimize()

com.granule.CSSFastMin.minimize()
com.granule.JSFastWhitespaceRemover.minimize()
com.nr.min.Amoeba.minimize()
com.nr.min.Brent.minimize()
com.nr.min.Dbrent.minimize()
com.nr.min.Frprmn.minimize()
com.nr.min.Golden.minimize()
com.nr.min.Powell.minimize()
com.opengamma.analytics.math.minimization.ConjugateDirectionVectorMinimizer.minimize()
{@inheritDoc}
com.opengamma.analytics.math.minimization.ConjugateGradientVectorMinimizer.minimize()
{@inheritDoc}
dk.brics.automaton.Automaton.minimize()
See {@link MinimizationOperations#minimize(Automaton)}.
edu.stanford.nlp.optimization.GoldenSectionLineSearch.minimize()
edu.stanford.nlp.optimization.LineSearcher.minimize()
Attempts to find an unconstrained minimum of the objective function starting at initial, within functionTolerance. @param function the objective function
edu.stanford.nlp.optimization.QNMinimizer.minimize()
kodkod.engine.Proof.minimize()
Minimizes the proof of this.log.formula's unsatisfiability using the specified proof reduction strategy. The strategy argument is ignored (it can be null) if this.formula is trivially unsatisfiable with respect to this.bounds. In that case, the core is reduced using the trivial strategy that does one of the following: (1) if there is a root that simplified to FALSE, sets the minimal core to that root; or (2) if not, then there must be two roots that translated to x and -x, where x is a boolean literal, so we pick those two as the minimal core.
Note: the core minimization is performed at the level of the transformed formula, not the original formula if the problem was translated with a non-zero {@linkplain Options#coreGranularity() core granularity} setting.In other words, after this method has been called, {@linkplain #highLevelCore() highLevelCore()} returns a map M such that M.keySet() is a minimal core with respect to this.log.bounds. In contrast, {@linkplain Nodes#allRoots(Formula,java.util.Collection) Nodes.roots(this.log.originalFormula, M.values())} is unsatisfiable with respect this.log.originalBounds. These formulas, however, do not necessarily form a minimal core of this.log.originalFormula if the original problem was translated with a non-zero {@linkplain Options#coreGranularity() core granularity} setting.
@effects minimizes the proof of this.log.formula's unsatisfiabilityusing the specified proof reduction strategy (or the trivial strategy if this.formula is trivially unsatisfiable with respect to this.bounds). @see kodkod.engine.satlab.ReductionStrategy
org.apache.commons.math.optimization.NelderMead.minimize()
org.apache.tapestry5.services.assets.ResourceMinimizer.minimize()
Checks the {@linkplain StreamableResource#getContentType() content type} of the resource and applies anappropriate minimization to it if possible. @param resource to minimize @return the same resource, or a minimized replacement for the resource @throws IOException
org.jquantlib.math.optimization.LevenbergMarquardt.minimize()
org.rstudio.core.client.theme.res.ThemeStyles.minimize()

Examples of kodkod.engine.Proof.minimize()

              Proof p = sol.proof();
              if (sol.outcome()==UNSATISFIABLE) {
                 // only perform the minimization if it was UNSATISFIABLE, rather than TRIVIALLY_UNSATISFIABLE
                 int i = p.highLevelCore().size();
                 rep.minimizing(cmd, i);
                 if (opt.coreMinimization==0) try { p.minimize(new RCEStrategy(p.log())); } catch(Throwable ex) {}
                 if (opt.coreMinimization==1) try { p.minimize(new HybridStrategy(p.log())); } catch(Throwable ex) {}
                 rep.minimized(cmd, i, p.highLevelCore().size());
              }
              for(Iterator<TranslationRecord> it=p.core(); it.hasNext();) {
                 Object n=it.next().node();

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Examples of org.apache.commons.math.optimization.NelderMead.minimize()

      };


    count = 0;
    NelderMead nm = new NelderMead();
    try {
      nm.minimize(rosenbrock, 100, new ValueChecker(1.0e-3),
                  new double[][] {
                    { -1.2, 1.0 }, { 3.5, -2.3 }, { 0.4, 1.5 }
                  }, 1, 5384353l);
      fail("an exception should have been thrown");
    } catch (ConvergenceException ce) {

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Examples of org.apache.commons.math.optimization.NelderMead.minimize()

        fail("wrong exception caught: " + e.getMessage());
    }


    count = 0;
    PointCostPair optimum =
        nm.minimize(rosenbrock, 100, new ValueChecker(1.0e-3),
                    new double[][] {
                      { -1.2, 1.0 }, { 0.9, 1.2 }, { 3.5, -2.3 }
                    }, 10, 1642738l);


    assertTrue(count > 700);

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Examples of org.apache.commons.math.optimization.NelderMead.minimize()

    RandomVectorGenerator rvg =
        new UncorrelatedRandomVectorGenerator(new double[] { 0.9, 1.1 },
                                              new double[] { 0.2, 0.2 },
                                              new UniformRandomGenerator(rg));
    optimum =
        nm.minimize(rosenbrock, 100, new ValueChecker(1.0e-3), rvg);
    assertEquals(0.0, optimum.getCost(), 2.0e-4);
    optimum =
        nm.minimize(rosenbrock, 100, new ValueChecker(1.0e-3), rvg, 3);
    assertEquals(0.0, optimum.getCost(), 3.0e-5);

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Examples of org.apache.commons.math.optimization.NelderMead.minimize()

                                              new UniformRandomGenerator(rg));
    optimum =
        nm.minimize(rosenbrock, 100, new ValueChecker(1.0e-3), rvg);
    assertEquals(0.0, optimum.getCost(), 2.0e-4);
    optimum =
        nm.minimize(rosenbrock, 100, new ValueChecker(1.0e-3), rvg, 3);
    assertEquals(0.0, optimum.getCost(), 3.0e-5);


  }


  public void testPowell()

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Examples of org.apache.commons.math.optimization.NelderMead.minimize()

      };


    count = 0;
    NelderMead nm = new NelderMead();
    PointCostPair optimum =
      nm.minimize(powell, 200, new ValueChecker(1.0e-3),
                  new double[] {  3.0, -1.0, 0.0, 1.0 },
                  new double[] {  4.0,  0.0, 1.0, 2.0 },
                  1, 1642738l);
    assertTrue(count < 150);
    assertEquals(0.0, optimum.getCost(), 6.0e-4);

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Examples of org.apache.tapestry5.services.assets.ResourceMinimizer.minimize()

    /** Does nothing; an override of this service can be installed to provide minimization. */
    public StreamableResource minimize(StreamableResource resource) throws IOException
    {
        ResourceMinimizer minimizer = configuration.get(resource.getContentType());


        return minimizer == null ? resource : minimizer.minimize(resource);
    }
}

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Examples of org.apache.tapestry5.services.assets.ResourceMinimizer.minimize()

    /** Does nothing; an override of this service can be installed to provide minimization. */
    public StreamableResource minimize(StreamableResource resource) throws IOException
    {
        ResourceMinimizer minimizer = configuration.get(resource.getContentType().getMimeType());


        return minimizer == null ? resource : minimizer.minimize(resource);
    }
}

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Examples of org.jquantlib.math.optimization.LevenbergMarquardt.minimize()

                }


                final PenaltyFunction currentCost = new PenaltyFunction(initialDataPoint, (i - localisation + 1), (i + 1));


                final Problem toSolve = new Problem(currentCost, solverConstraint, new Array(startArray));
                final EndCriteria.Type endType = solver.minimize (toSolve, endCriteria);


                QL.require (endType == EndCriteria.Type.StationaryFunctionAccuracy ||
                            endType == EndCriteria.Type.StationaryFunctionValue,
                            "Unable to strip yieldcurve to required accuracy");
            }

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Examples of org.rstudio.core.client.theme.res.ThemeStyles.minimize()

      final ThemeStyles globalStyles = ThemeResources.INSTANCE.themeStyles();
      panelHost_ = panelHost;
      
      // import the minimize button from the global theme resources
      HTML minimize = new HTML();
      minimize.setStylePrimaryName(globalStyles.minimize());
      minimize.addClickHandler(new ClickHandler()
      {
         public void onClick(ClickEvent event)
         {
            if (isMinimized_)

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