91 lines
2.7 KiB
C
91 lines
2.7 KiB
C
#include "lizfcm.test.h"
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UTEST(eigen, leslie_matrix) {
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Array_double *felicity = InitArray(double, {0.0, 1.5, 0.8});
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Array_double *survivor_ratios = InitArray(double, {0.8, 0.55});
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Matrix_double *m = InitMatrixWithSize(double, 3, 3, 0.0);
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m->data[0]->data[0] = 0.0;
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m->data[0]->data[1] = 1.5;
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m->data[0]->data[2] = 0.8;
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m->data[1]->data[0] = 0.8;
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m->data[2]->data[1] = 0.55;
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Matrix_double *leslie = leslie_matrix(survivor_ratios, felicity);
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EXPECT_TRUE(matrix_equal(leslie, m));
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free_matrix(leslie);
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free_matrix(m);
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free_vector(felicity);
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free_vector(survivor_ratios);
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}
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UTEST(eigen, leslie_matrix_dominant_eigenvalue) {
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Array_double *felicity = InitArray(double, {0.0, 1.5, 0.8});
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Array_double *survivor_ratios = InitArray(double, {0.8, 0.55});
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Matrix_double *leslie = leslie_matrix(survivor_ratios, felicity);
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Array_double *v_guess = InitArrayWithSize(double, 3, 2.0);
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double tolerance = 0.0001;
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uint64_t max_iterations = 64;
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double expect_dominant_eigenvalue = 1.22005;
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double approx_dominant_eigenvalue =
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dominant_eigenvalue(leslie, v_guess, tolerance, max_iterations);
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EXPECT_NEAR(expect_dominant_eigenvalue, approx_dominant_eigenvalue,
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tolerance);
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free_vector(v_guess);
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free_vector(survivor_ratios);
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free_vector(felicity);
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free_matrix(leslie);
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}
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UTEST(eigen, least_dominant_eigenvalue) {
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Matrix_double *m = InitMatrixWithSize(double, 3, 3, 0.0);
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m->data[0]->data[0] = 2.0;
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m->data[0]->data[1] = 2.0;
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m->data[0]->data[2] = 4.0;
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m->data[1]->data[0] = 1.0;
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m->data[1]->data[1] = 4.0;
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m->data[1]->data[2] = 7.0;
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m->data[2]->data[1] = 2.0;
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m->data[2]->data[2] = 6.0;
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double expected_least_dominant_eigenvalue = 0.87689; // 5 - sqrt(17)
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double tolerance = 0.0001;
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uint64_t max_iterations = 64;
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Array_double *v_guess = InitArrayWithSize(double, 3, 2.0);
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double approx_least_dominant_eigenvalue =
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least_dominant_eigenvalue(m, v_guess, tolerance, max_iterations);
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EXPECT_NEAR(expected_least_dominant_eigenvalue,
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approx_least_dominant_eigenvalue, tolerance);
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}
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UTEST(eigen, dominant_eigenvalue) {
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Matrix_double *m = InitMatrixWithSize(double, 2, 2, 0.0);
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m->data[0]->data[0] = 2.0;
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m->data[0]->data[1] = -12.0;
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m->data[1]->data[0] = 1.0;
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m->data[1]->data[1] = -5.0;
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Array_double *v_guess = InitArrayWithSize(double, 2, 1.0);
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double tolerance = 0.0001;
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uint64_t max_iterations = 64;
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double expect_dominant_eigenvalue = -2.0;
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double approx_dominant_eigenvalue =
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dominant_eigenvalue(m, v_guess, tolerance, max_iterations);
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EXPECT_NEAR(expect_dominant_eigenvalue, approx_dominant_eigenvalue,
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tolerance);
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free_matrix(m);
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free_vector(v_guess);
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}
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