Beispiel #1
0
  /**
   * As described by Bernt Arne Ødegaard in Financial Numerical Recipes in C++.
   *
   * <p>Returns P(X < a, Y < b) where X, Y are gaussian random variables N(0, 1) of the bivariate
   * normal distribution with correlation c in [-1, 1] between X and Y.
   */
  public static double cdf(double a, double b, double c) {
    if (a == Double.NaN || b == Double.NaN || c == Double.NaN) {
      throw new IllegalArgumentException("Arguments must be a number.");
    }

    if (a == Double.NaN) {
      System.out.println("");
    }

    a = handleInfinity(a);
    b = handleInfinity(b);
    c = handleInfinity(c);

    if (a == Double.NaN) {
      System.out.println("");
    }

    if (a <= 0 && b <= 0 && c <= 0) {
      final double aprime = a / FastMath.sqrt(2d * (1d - c * c));
      final double bprime = b / FastMath.sqrt(2d * (1d - c * c));
      double sum = 0;
      for (int i = 0; i < A.length; i++) {
        for (int j = 0; j < A.length; j++) {
          sum += A[i] * A[j] * f(B[i], B[j], aprime, bprime, c);
        }
      }

      sum *= FastMath.sqrt(1d - c * c) / FastMath.PI;

      return sum;
    }

    // a or b may be too big and their multiplication may result in NaN.
    if (c * a * b
        <= 0) { // c is smaller (between [-1, 1]) and will help to avoid NaNs. So we multiply c
      // first.
      if ((a <= 0) && (b >= 0) && (c >= 0)) {
        return normal.cumulativeProbability(a) - cdf(a, -b, -c);
      } else if ((a >= 0) && (b <= 0) && (c >= 0)) {
        return normal.cumulativeProbability(b) - cdf(-a, b, -c);
      } else if ((a >= 0) && (b >= 0) && (c <= 0)) {
        return normal.cumulativeProbability(a)
            + normal.cumulativeProbability(b)
            - 1
            + cdf(-a, -b, c);
      }
    } else if (c * a * b >= 0) {
      final double denum = FastMath.sqrt(a * a - 2d * c * a * b + b * b);
      final double rho1 = ((c * a - b) * FastMath.signum(a)) / denum;
      final double rho2 = ((c * b - a) * FastMath.signum(b)) / denum;
      final double delta = (1d - FastMath.signum(a) * FastMath.signum(b)) / 4d;
      return cdf(a, 0, rho1) + cdf(b, 0, rho2) - delta;
    }

    throw new RuntimeException(
        "Should never get here. Values of [a; b ; c] = [" + a + "; " + b + "; " + c + "].");
  }
  public double execute(double in) throws DMLRuntimeException {
    switch (bFunc) {
      case SIN:
        return FASTMATH ? FastMath.sin(in) : Math.sin(in);
      case COS:
        return FASTMATH ? FastMath.cos(in) : Math.cos(in);
      case TAN:
        return FASTMATH ? FastMath.tan(in) : Math.tan(in);
      case ASIN:
        return FASTMATH ? FastMath.asin(in) : Math.asin(in);
      case ACOS:
        return FASTMATH ? FastMath.acos(in) : Math.acos(in);
      case ATAN:
        return Math.atan(in); // faster in Math
      case CEIL:
        return FASTMATH ? FastMath.ceil(in) : Math.ceil(in);
      case FLOOR:
        return FASTMATH ? FastMath.floor(in) : Math.floor(in);
      case LOG:
        return FASTMATH ? FastMath.log(in) : Math.log(in);
      case LOG_NZ:
        return (in == 0) ? 0 : FASTMATH ? FastMath.log(in) : Math.log(in);
      case ABS:
        return Math.abs(in); // no need for FastMath	
      case SIGN:
        return FASTMATH ? FastMath.signum(in) : Math.signum(in);
      case SQRT:
        return Math.sqrt(in); // faster in Math
      case EXP:
        return FASTMATH ? FastMath.exp(in) : Math.exp(in);
      case ROUND:
        return Math.round(in); // no need for FastMath

      case PLOGP:
        if (in == 0.0) return 0.0;
        else if (in < 0) return Double.NaN;
        else return (in * (FASTMATH ? FastMath.log(in) : Math.log(in)));

      case SPROP:
        // sample proportion: P*(1-P)
        return in * (1 - in);

      case SIGMOID:
        // sigmoid: 1/(1+exp(-x))
        return FASTMATH ? 1 / (1 + FastMath.exp(-in)) : 1 / (1 + Math.exp(-in));

      case SELP:
        // select positive: x*(x>0)
        return (in > 0) ? in : 0;

      default:
        throw new DMLRuntimeException("Builtin.execute(): Unknown operation: " + bFunc);
    }
  }