add some parameter broadcast tests as well

Author: Transurgeon

tests/all_tests.c

@@ -362,6 +362,9 @@ int main(void)
 
     printf("\n--- Parameter + Broadcast Tests ---\n");
     mu_run_test(test_constant_broadcast_vector_mult, tests_run);
+    mu_run_test(test_constant_promote_vector_mult, tests_run);
+    mu_run_test(test_param_broadcast_vector_mult, tests_run);
+    mu_run_test(test_param_promote_vector_mult, tests_run);
 #endif /* PROFILE_ONLY */
 
 #ifdef PROFILE_ONLY

tests/problem/test_param_broadcast.h

@@ -70,4 +70,88 @@ const char *test_constant_promote_vector_mult(void)
     free_problem(prob);
     return 0;
 }
+
+const char *test_param_broadcast_vector_mult(void)
+{
+    int n = 6;
+
+    /* minimize sum(x) subject to broadcast(p) ∘ x, with p parameter */
+    expr *x = new_variable(2, 3, 0, n);
+    expr *objective = new_sum(x, -1);
+    double c_vals[3] = {1.0, 2.0, 3.0};
+    expr *c = new_parameter(1, 3, 0, n, c_vals);
+    expr *c_bcast = new_broadcast(c, 2, 3);
+    expr *constraint = new_vector_mult(c_bcast, x);
+    expr *constraints[1] = {constraint};
+    problem *prob = new_problem(objective, constraints, 1, false);
+
+    expr *param_nodes[1] = {c};
+    problem_register_params(prob, param_nodes, 1);
+    problem_init_derivatives(prob);
+
+    /* point for evaluating */
+    double x_vals[6] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
+
+    problem_constraint_forward(prob, x_vals);
+    double constrs[6] = {1.0, 2.0, 6.0, 8.0, 15.0, 18.0};
+    problem_jacobian(prob);
+    double jac_x[6] = {1.0, 1.0, 2.0, 2.0, 3.0, 3.0};
+    mu_assert("vals fail", cmp_double_array(prob->constraint_values, constrs, 6));
+    mu_assert("vals fail", cmp_double_array(prob->jacobian->x, jac_x, 6));
+
+    /* second iteration after updating parameter */
+    double theta[3] = {5.0, 4.0, 3.0};
+    problem_update_params(prob, theta);
+    problem_constraint_forward(prob, x_vals);
+    problem_jacobian(prob);
+    double updated_constrs[6] = {5.0, 10.0, 12.0, 16.0, 15.0, 18.0};
+    double updated_jac_x[6] = {5.0, 5.0, 4.0, 4.0, 3.0, 3.0};
+    mu_assert("vals fail", cmp_double_array(prob->constraint_values, updated_constrs, 6));
+    mu_assert("vals fail", cmp_double_array(prob->jacobian->x, updated_jac_x, 6));
+
+    free_problem(prob);
+    return 0;
+}
+
+const char *test_param_promote_vector_mult(void)
+{
+    int n = 6;
+
+    /* minimize sum(x) subject to promote(p) ∘ x, with p parameter */
+    expr *x = new_variable(2, 3, 0, n);
+    expr *objective = new_sum(x, -1);
+    double c_vals = 3.0;
+    expr *c = new_parameter(1, 1, 0, n, &c_vals);
+    expr *c_bcast = new_promote(c, 2, 3);
+    expr *constraint = new_vector_mult(c_bcast, x);
+    expr *constraints[1] = {constraint};
+    problem *prob = new_problem(objective, constraints, 1, false);
+
+    expr *param_nodes[1] = {c};
+    problem_register_params(prob, param_nodes, 1);
+    problem_init_derivatives(prob);
+
+    /* point for evaluating */
+    double x_vals[6] = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0};
+
+    problem_constraint_forward(prob, x_vals);
+    double constrs[6] = {3.0, 6.0, 9.0, 12.0, 15.0, 18.0};
+    problem_jacobian(prob);
+    double jac_x[6] = {3.0, 3.0, 3.0, 3.0, 3.0, 3.0};
+    mu_assert("vals fail", cmp_double_array(prob->constraint_values, constrs, 6));
+    mu_assert("vals fail", cmp_double_array(prob->jacobian->x, jac_x, 6));
+
+    /* second iteration after updating parameter */
+    double theta = 5.0;
+    problem_update_params(prob, &theta);
+    problem_constraint_forward(prob, x_vals);
+    problem_jacobian(prob);
+    double updated_constrs[6] = {5.0, 10.0, 15.0, 20.0, 25.0, 30.0};
+    double updated_jac_x[6] = {5.0, 5.0, 5.0, 5.0, 5.0, 5.0};
+    mu_assert("vals fail", cmp_double_array(prob->constraint_values, updated_constrs, 6));
+    mu_assert("vals fail", cmp_double_array(prob->jacobian->x, updated_jac_x, 6));
+
+    free_problem(prob);
+    return 0;
+}
 #endif /* TEST_PARAM_BROADCAST_H */