X-Git-Url: http://gitweb.michael.orlitzky.com/?p=octave.git;a=blobdiff_plain;f=optimization%2Fpreconditioned_conjugate_gradient_method.m;h=35fecaa99cdb81b7f22836791797c0bb2fe1acac;hp=eb2089f5b4e50d367c8237be9c166d5065f70982;hb=302a62bb7c0adf581916fcd1f93faa719e8d51e8;hpb=af1b47d92cb94b9289987babefd34633f3bbe804

diff --git a/optimization/preconditioned_conjugate_gradient_method.m b/optimization/preconditioned_conjugate_gradient_method.m
index eb2089f..35fecaa 100644
--- a/optimization/preconditioned_conjugate_gradient_method.m
+++ b/optimization/preconditioned_conjugate_gradient_method.m
@@ -1,8 +1,8 @@
-function [x, k] = preconditioned_conjugate_gradient_method(Q,
-							   M,
-							   b,
-							   x0,
-							   tolerance,
+function [x, k] = preconditioned_conjugate_gradient_method(Q, ...
+							   M, ...
+							   b, ...
+							   x0, ...
+							   tolerance, ...
 							   max_iterations)
   %
   % Solve,
@@ -58,8 +58,15 @@ function [x, k] = preconditioned_conjugate_gradient_method(Q,
   % REFERENCES:
   %
   %   1. Guler, Osman. Foundations of Optimization. New York, Springer,
-  %   2010.
+  %      2010.
   %
+  %   2. Shewchuk, Jonathan Richard. An Introduction to the Conjugate
+  %      Gradient Method Without the Agonizing Pain, Edition 1.25.
+  %      August 4, 1994.
+  %
+
+  % We use this in the inner loop.
+  sqrt_n = floor(sqrt(length(x0)));
 
   % Set k=0 first, that way the references to xk,rk,zk,dk which
   % immediately follow correspond (semantically) to x0,r0,z0,d0.
@@ -70,7 +77,7 @@ function [x, k] = preconditioned_conjugate_gradient_method(Q,
   zk = M \ rk;
   dk = -zk;
 
-  for k = [ 0 : max_iterations ]
+  while (k <= max_iterations)
 
     if (norm(rk) < tolerance)
       % Check our stopping condition. This should catch the k=0 case.
@@ -85,15 +92,27 @@ function [x, k] = preconditioned_conjugate_gradient_method(Q,
     % do them both, so we precompute the more expensive operation.
     Qdk = Q * dk;
 
-    % After substituting the two previously-created variables, the
-    % following algorithm occurs verbatim in the reference.
     alpha_k = rkzk/(dk' * Qdk);
     x_next = xk + (alpha_k * dk);
-    r_next = rk + (alpha_k * Qdk);
+
+    % The recursive definition of r_next is prone to accumulate
+    % roundoff error. When sqrt(n) divides k, we recompute the
+    % residual to minimize this error. This modification is due to the
+    % second reference.
+    if (mod(k, sqrt_n) == 0)
+      r_next = Q*x_next - b;
+    else
+      r_next = rk + (alpha_k * Qdk);
+    end
+
     z_next = M \ r_next;
     beta_next = (r_next' * z_next)/rkzk;
     d_next = -z_next + beta_next*dk;
 
+    % We potentially just performed one more iteration than necessary
+    % in order to simplify the loop. Note that due to the structure of
+    % our loop, we will have k > max_iterations when we fail to
+    % converge.
     k = k + 1;
     xk = x_next;
     rk = r_next;