# module Newton

newton.rb

Solves the nonlinear algebraic equation system f = 0 by Newton's method. This program is not dependent on BigDecimal.

To call:

      n = nlsolve(f,x)
    where n is the number of iterations required,
          x is the initial value vector
          f is an Object which is used to compute the values of the equations to be solved.

It must provide the following methods:

f.values(x)

  returns the values of all functions at x

f.zero

  returns 0.0

f.one

  returns 1.0

f.two

  returns 2.0

f.ten

  returns 10.0

f.eps

  returns the convergence criterion (epsilon value) used to determine whether two values are considered equal. If |a-b| < epsilon, the two values are considered equal.

On exit, x is the solution vector.

### Public Instance Methods

nlsolve(f,x) click to toggle source

See also Newton

    # File lib/bigdecimal/newton.rb, line 44
    def nlsolve(f,x)
      nRetry = 0
      n = x.size

      f0 = f.values(x)
      zero = f.zero
      one  = f.one
      two  = f.two
      p5 = one/two
      d  = norm(f0,zero)
      minfact = f.ten*f.ten*f.ten
      minfact = one/minfact
      e = f.eps
      while d >= e do
        nRetry += 1
        # Not yet converged. => Compute Jacobian matrix
        dfdx = jacobian(f,f0,x)
        # Solve dfdx*dx = -f0 to estimate dx
        dx = lusolve(dfdx,f0,ludecomp(dfdx,n,zero,one),zero)
        fact = two
        xs = x.dup
        begin
          fact *= p5
          if fact < minfact then
            raise "Failed to reduce function values."
          end
          for i in 0...n do
            x[i] = xs[i] - dx[i]*fact
          end
          f0 = f.values(x)
          dn = norm(f0,zero)
        end while(dn>=d)
        d = dn
      end
      nRetry
    end