Test our (P)CGM implementation against Octave's.
[octave.git] / tests / preconditioned_conjugate_gradient_method_tests.m
index d44ee421570ead5908c49a14a959650c8cb88495..2c8ff84044fb9c3ffce03259a3d6af2cb4265366 100644 (file)
@@ -40,3 +40,29 @@ diff = norm(pcgm_simple - pcgm);
 unit_test_equals("PCGM agrees with Simple PCGM when M != I", ...
                 true, ...
                 norm(diff) < 1e-6);
+
+
+# Test again Octave's pcg() function.
+max_iterations = 100000;
+tolerance = 1e-11;
+C = random_positive_definite_matrix(5, 1000);
+M = C*C';
+
+for n = [ 5, 10, 25, 50, 100 ]
+  A = random_positive_definite_matrix(5, 1000);
+
+  # Assumed by Octave's implementation when you don't supply a
+  # preconditioner.
+  x0 = zeros(5, 1);
+  b  = unifrnd(-1000, 1000, 5, 1);
+  [o_x, o_flag, o_relres, o_iter] = pcg(A, b, tolerance, max_iterations, C, C');
+  [x, k] = preconditioned_conjugate_gradient_method(A,
+                                                   M,
+                                                   b,
+                                                   x0,
+                                                   tolerance,
+                                                   max_iterations);
+  diff = norm(o_x - x);
+  msg = sprintf("Our PCGM agrees with Octave's, n=%d.", n);
+  unit_test_equals(msg, true, norm(diff) < 1e-10);
+end