1 files changed, 68 insertions, 46 deletions

diff --git a/test/eigen.t.c b/test/eigen.t.c
index 0ad0bd0..5a20d86 100644
--- a/test/eigen.t.c
+++ b/test/eigen.t.c
@@ -1,50 +1,7 @@
 #include "lizfcm.test.h"
 
-UTEST(eigen, leslie_matrix) {
-  Array_double *felicity = InitArray(double, {0.0, 1.5, 0.8});
-  Array_double *survivor_ratios = InitArray(double, {0.8, 0.55});
-
-  Matrix_double *m = InitMatrixWithSize(double, 3, 3, 0.0);
-  m->data[0]->data[0] = 0.0;
-  m->data[0]->data[1] = 1.5;
-  m->data[0]->data[2] = 0.8;
-  m->data[1]->data[0] = 0.8;
-  m->data[2]->data[1] = 0.55;
-
-  Matrix_double *leslie = leslie_matrix(survivor_ratios, felicity);
-
-  EXPECT_TRUE(matrix_equal(leslie, m));
-
-  free_matrix(leslie);
-  free_matrix(m);
-  free_vector(felicity);
-  free_vector(survivor_ratios);
-}
-
-UTEST(eigen, leslie_matrix_dominant_eigenvalue) {
-  Array_double *felicity = InitArray(double, {0.0, 1.5, 0.8});
-  Array_double *survivor_ratios = InitArray(double, {0.8, 0.55});
-  Matrix_double *leslie = leslie_matrix(survivor_ratios, felicity);
-  Array_double *v_guess = InitArrayWithSize(double, 3, 2.0);
-  double tolerance = 0.0001;
-  uint64_t max_iterations = 64;
-
-  double expect_dominant_eigenvalue = 1.22005;
-
-  double approx_dominant_eigenvalue =
-      dominant_eigenvalue(leslie, v_guess, tolerance, max_iterations);
-
-  EXPECT_NEAR(expect_dominant_eigenvalue, approx_dominant_eigenvalue,
-              tolerance);
-
-  free_vector(v_guess);
-  free_vector(survivor_ratios);
-  free_vector(felicity);
-  free_matrix(leslie);
-}
-
-UTEST(eigen, least_dominant_eigenvalue) {
-
+Matrix_double *eigen_test_matrix() {
+  // produces a matrix that has eigenvalues [5 + sqrt{17}, 2, 5 - sqrt{17}]
   Matrix_double *m = InitMatrixWithSize(double, 3, 3, 0.0);
   m->data[0]->data[0] = 2.0;
   m->data[0]->data[1] = 2.0;
@@ -54,12 +11,17 @@ UTEST(eigen, least_dominant_eigenvalue) {
   m->data[1]->data[2] = 7.0;
   m->data[2]->data[1] = 2.0;
   m->data[2]->data[2] = 6.0;
+  return m;
+}
+
+UTEST(eigen, least_dominant_eigenvalue) {
+  Matrix_double *m = eigen_test_matrix();
 
   double expected_least_dominant_eigenvalue = 0.87689; // 5 - sqrt(17)
   double tolerance = 0.0001;
   uint64_t max_iterations = 64;
 
-  Array_double *v_guess = InitArrayWithSize(double, 3, 2.0);
+  Array_double *v_guess = InitArrayWithSize(double, 3, 1.0);
   double approx_least_dominant_eigenvalue =
       least_dominant_eigenvalue(m, v_guess, tolerance, max_iterations);
 
@@ -88,3 +50,63 @@ UTEST(eigen, dominant_eigenvalue) {
   free_matrix(m);
   free_vector(v_guess);
 }
+
+UTEST(eigen, shifted_eigenvalue) {
+  Matrix_double *m = eigen_test_matrix();
+
+  double least_dominant_eigenvalue = 0.87689; // 5 - sqrt{17}
+  double dominant_eigenvalue = 9.12311;       // 5 + sqrt{17}
+  double expected_middle_eigenvalue = 2.0;
+  double shift = (dominant_eigenvalue + least_dominant_eigenvalue) / 2.0;
+
+  double tolerance = 0.0001;
+  uint64_t max_iterations = 64;
+  Array_double *v_guess = InitArray(double, {0.5, 1.0, 0.75});
+
+  double approx_middle_eigenvalue = shift_inverse_power_eigenvalue(
+      m, v_guess, shift, tolerance, max_iterations);
+
+  EXPECT_NEAR(approx_middle_eigenvalue, expected_middle_eigenvalue, tolerance);
+}
+
+UTEST(eigen, leslie_matrix_dominant_eigenvalue) {
+  Array_double *felicity = InitArray(double, {0.0, 1.5, 0.8});
+  Array_double *survivor_ratios = InitArray(double, {0.8, 0.55});
+  Matrix_double *leslie = leslie_matrix(survivor_ratios, felicity);
+  Array_double *v_guess = InitArrayWithSize(double, 3, 2.0);
+  double tolerance = 0.0001;
+  uint64_t max_iterations = 64;
+
+  double expect_dominant_eigenvalue = 1.22005;
+
+  double approx_dominant_eigenvalue =
+      dominant_eigenvalue(leslie, v_guess, tolerance, max_iterations);
+
+  EXPECT_NEAR(expect_dominant_eigenvalue, approx_dominant_eigenvalue,
+              tolerance);
+
+  free_vector(v_guess);
+  free_vector(survivor_ratios);
+  free_vector(felicity);
+  free_matrix(leslie);
+}
+UTEST(eigen, leslie_matrix) {
+  Array_double *felicity = InitArray(double, {0.0, 1.5, 0.8});
+  Array_double *survivor_ratios = InitArray(double, {0.8, 0.55});
+
+  Matrix_double *m = InitMatrixWithSize(double, 3, 3, 0.0);
+  m->data[0]->data[0] = 0.0;
+  m->data[0]->data[1] = 1.5;
+  m->data[0]->data[2] = 0.8;
+  m->data[1]->data[0] = 0.8;
+  m->data[2]->data[1] = 0.55;
+
+  Matrix_double *leslie = leslie_matrix(survivor_ratios, felicity);
+
+  EXPECT_TRUE(matrix_equal(leslie, m));
+
+  free_matrix(leslie);
+  free_matrix(m);
+  free_vector(felicity);
+  free_vector(survivor_ratios);
+}