1 files changed, 0 insertions, 77 deletions
diff --git a/ruby_1_8_6/ext/bigdecimal/lib/bigdecimal/newton.rb b/ruby_1_8_6/ext/bigdecimal/lib/bigdecimal/newton.rb
deleted file mode 100644
index 59ac0f7f04..0000000000
--- a/ruby_1_8_6/ext/bigdecimal/lib/bigdecimal/newton.rb
+++ /dev/null
@@ -1,77 +0,0 @@
-#
-# 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 1.0
-# 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.
-#
-require "bigdecimal/ludcmp"
-require "bigdecimal/jacobian"
-
-module Newton
-  include LUSolve
-  include Jacobian
-  
-  def norm(fv,zero=0.0)
-    s = zero
-    n = fv.size
-    for i in 0...n do
-      s += fv[i]*fv[i]
-    end
-    s
-  end
-
-  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
-end