List of op() Examples

Examples of op()

com.google.dexmaker.Code.op()
Executes {@code op} and sets {@code target} to the result.
kodkod.ast.BinaryExpression.op()
Returns this.op. @return this.op
kodkod.ast.BinaryFormula.op()
Returns the operator of this. @return this.op
kodkod.ast.ComparisonFormula.op()
Returns the operator of this. @return this.op
kodkod.ast.NaryFormula.op()
Returns the operator of this. @return this.op
kodkod.engine.bool.BooleanAccumulator.op()
Returns the operator for this accumulator. @return this.op
kodkod.engine.bool.BooleanValue.op()
Returns the operator representing the function computed by this gate. @return this.op
org.jquantlib.math.distributions.BinomialDistribution.op()
Computes the probability of k successful trials. @param k Number of successful trials @return Math.exp(binomialCoefficientLn(nExp, k) + k * logP + (nExp-k) * logOneMinusP);
org.jquantlib.math.distributions.BivariateNormalDistribution.op()
Computes the Bivariate Normal Distribution of the two variables x and y which can be correlated in a particular manner. @param x First variable @param y Second variable @return BVN
org.jquantlib.math.distributions.CumulativeBinomialDistribution.op()
{@inheritDoc}
Computes the Cumulative Binomial Distribution. @param k @return 1.0 - Beta.incompleteBetaFunction(k+1, n_-k, p_, accuracy, maxIteration)
org.jquantlib.math.distributions.CumulativeNormalDistribution.op()
Computes the cumulative normal distribution.
Asymptotic expansion for very negative z as references on M. Abramowitz book. @see cite: "Monte Carlo Methods in Finance", ISBN-13: 978-0471497417 @see cite: M. Abramowitz and A. Stegun, Pocketbook of Mathematical Functions, ISBN 3-87144818-4, p.408, item 26.2.12 @param z @return result
org.jquantlib.math.distributions.CumulativePoissonDistribution.op()
{@inheritDoc}
Computes the cumulative Poisson distribution by using the incomplete gamma function . @param k is the number of occurrences of an event @return the cumulative Poisson distribution by using the incomplete gamma function
org.jquantlib.math.distributions.GammaDistribution.op()
Computes the Gamma distribution. @param x random variable @return Gamma distribution of x
org.jquantlib.math.distributions.InverseCumulativeNormal.op()
Computes the inverse cumulative normal distribution. @param x @returns average + z * sigma
org.jquantlib.math.distributions.InverseCumulativePoisson.op()
Computes the inverse cumulative poisson distribution. @param x @returns the inverse of the cumulative poisson distribution of input x
org.jquantlib.math.distributions.MoroInverseCumulativeNormal.op()
org.jquantlib.math.distributions.NonCentralChiSquaredDistribution.op()
org.jquantlib.math.distributions.NormalDistribution.op()
{@inheritDoc}
Computes the Normal distribution at point {@latex$ x } @param x @return the Normal distribution at point {@latex$ x }
org.jquantlib.math.distributions.PoissonDistribution.op()
{@inheritDoc}
PoissonDistribution evaluation
Compute the Poisson Distribution with input {@latex$ \mu} and {@latex$ k}. @param k @return Math.exp(k*Math.log(mu_) - logFactorial - mu_)
org.jquantlib.math.integrals.GaussKronrodAdaptive.op()
org.jquantlib.math.integrals.GaussKronrodPatterson.op()
org.jquantlib.math.integrals.Integrator.op()
org.jquantlib.math.integrals.SegmentIntegral.op()
org.jquantlib.math.integrals.SimpsonIntegral.op()
org.jquantlib.math.interpolations.BackwardFlatInterpolation.op()
org.jquantlib.math.interpolations.CubicInterpolation.op()
org.jquantlib.math.interpolations.ForwardFlatInterpolation.op()
org.jquantlib.math.interpolations.Interpolation.op()
org.jquantlib.math.interpolations.NaturalCubicInterpolation.op()
org.jquantlib.math.matrixutilities.internal.Address.MatrixAddress.MatrixOffset.op()
org.locationtech.udig.validation.ValidateGeometry.op()
org.locationtech.udig.validation.ValidateLineMustBeASinglePart.op()
org.locationtech.udig.validation.ValidateLineNoSelfIntersect.op()
org.locationtech.udig.validation.ValidateLineNoSelfOverlapping.op()
org.locationtech.udig.validation.ValidateOverlaps.op()
org.mvel2.util.ExecutionStack.op()
ro.redeul.google.go.lang.psi.expressions.binary.GoRelationalExpression.op()

Examples of com.google.dexmaker.Code.op()

        code.loadConstant(constant1, 1);
        code.loadConstant(constant2, 2);
        Label baseCase = new Label();
        code.compare(Comparison.LT, baseCase, i, constant2);
        code.op(BinaryOp.SUBTRACT, a, i, constant1);
        code.op(BinaryOp.SUBTRACT, b, i, constant2);
        code.invokeStatic(fib, c, a);
        code.invokeStatic(fib, d, b);
        code.op(BinaryOp.ADD, result, c, d);
        code.returnValue(result);
        code.mark(baseCase);

View Full Code Here

Examples of kodkod.ast.BinaryExpression.op()

          TupleSet ans = findUpper ? bounds.upperBound((Relation)expr) : bounds.lowerBound((Relation)expr);
          if (ans!=null) return makeMutable ? ans.clone() : ans;
       }
       else if (expr instanceof BinaryExpression) {
          BinaryExpression b = (BinaryExpression)expr;
          if (b.op() == ExprOperator.UNION) {
             TupleSet left = query(findUpper, b.left(), true);
             TupleSet right = query(findUpper, b.right(), false);
             left.addAll(right);
             return left;
          }

View Full Code Here

Examples of kodkod.ast.BinaryFormula.op()

    final ListIterator<Formula> itr = formulas.listIterator();
    while(itr.hasNext()) {
      final Formula f = itr.next();
      if (f instanceof BinaryFormula) {
        final BinaryFormula bin = (BinaryFormula) f;
        if (bin.op()==FormulaOperator.AND) {
          itr.remove();
          itr.add(bin.left());
          itr.add(bin.right());
          itr.previous();
          itr.previous();

View Full Code Here

Examples of kodkod.ast.ComparisonFormula.op()

             return simplify_in(f.left()) && simplify_in(f.right());
          }
       }
       if (form instanceof ComparisonFormula) {
          ComparisonFormula f = (ComparisonFormula)form;
          if (f.op() == ExprCompOperator.SUBSET) {
             if (!simplify_in(f.left(), f.right())) return false;
          }
          if (f.op() == ExprCompOperator.EQUALS) {
             if (!simplify_in(f.left(), f.right())) return false;
             if (!simplify_in(f.right(), f.left())) return false;

View Full Code Here

Examples of kodkod.ast.NaryFormula.op()

          itr.previous();
          itr.previous();
        }
      } else if (f instanceof NaryFormula) { 
        final NaryFormula nf = (NaryFormula) f;
        if (nf.op()==FormulaOperator.AND) { 
          itr.remove();
          for(Formula child : nf) { 
            itr.add(child);
          }
          for(int i = nf.size(); i>0; i--) {

View Full Code Here

Examples of kodkod.engine.bool.BooleanAccumulator.op()

    if (options.logTranslation()>0) {
      final TranslationLogger logger = options.logTranslation()==1 ? new MemoryLogger(annotated, bounds) : new FileLogger(annotated, bounds);
      final BooleanAccumulator circuit = FOL2BoolTranslator.translate(annotated, interpreter, logger);
      log = logger.log();
      if (circuit.isShortCircuited()) {
        throw new TrivialFormulaException(annotated.node(), bounds, circuit.op().shortCircuit(), log);
      } else if (circuit.size()==0) { 
        throw new TrivialFormulaException(annotated.node(), bounds, circuit.op().identity(), log);
      }
      return generateSBP(circuit, interpreter, breaker);
    } else {

View Full Code Here

Examples of kodkod.engine.bool.BooleanValue.op()

        throw new TrivialFormulaException(annotated.node(), bounds, circuit.op().identity(), log);
      }
      return generateSBP(circuit, interpreter, breaker);
    } else {
      final BooleanValue circuit = (BooleanValue)FOL2BoolTranslator.translate(annotated, interpreter);
      if (circuit.op()==Operator.CONST) {
        throw new TrivialFormulaException(annotated.node(), bounds, (BooleanConstant)circuit, null);
      } 
      return generateSBP(annotated, (BooleanFormula)circuit, interpreter, breaker);
    }
  }

View Full Code Here

Examples of org.jquantlib.math.distributions.BinomialDistribution.op()

        final BinomialDistribution binomdist = new BinomialDistribution(p,n);


        for(int i=0;i<n;i++){
            final int z = i;
            final double expected = testvalues[i];
            final double computed = binomdist.op(z);


            // double tolerance = (z<6 ) ? 1.0e-15: 1.0e-10;
            final double tolerance = 1.0e-15; // try to to get 1.0e-15 accuracy whenever possible


            //assertEquals(expected, computed, tolerance);

View Full Code Here

Examples of org.jquantlib.math.distributions.BivariateNormalDistribution.op()

      final double tolerance = 1.0e-15;
      for (final double element : rho) {
          for (Integer sgn=-1; sgn < 2; sgn+=2) {
              final BivariateNormalDistribution bvn= new BivariateNormalDistribution(sgn*element);
              final double expected = 0.25 + Math.asin(sgn*element) / (2*Math.PI) ;
              final double realised = bvn.op(x,y);


              if (Math.abs(realised-expected)>=tolerance)
                fail(" bivariate cumulative distribution\n"
                            + "    rho: " + sgn*element + "\n"
                            + "    expected:  " + expected + "\n"

View Full Code Here

Examples of org.jquantlib.math.distributions.CumulativeBinomialDistribution.op()

        final int n = testvalues.length;      // number of trials


        final CumulativeBinomialDistribution cumbinomdist = new CumulativeBinomialDistribution(p,n);
        for (int i=0;i<testvalues.length;i++) {
            final double expected = testvalues[i];
            final double realised = cumbinomdist.op(i); // i = number of successful events
            final double tolerance = 1.0e-11;
            if (Math.abs(expected-realised)>tolerance) {
                fail("x: " + i + " expected: " + expected + " realised: " + realised);
            }
        }

View Full Code Here

0 1 2 3 4 5 6 7

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.