In Files
- bigdecimal/lib/bigdecimal/newton.rb
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)
See also Newton
# File bigdecimal/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