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minimal_ei_model.m
1 function mm = minimal_ei_model
2  mm = [];
3  mm.name = 'minimal_model';
4  mm.mu_names = {'par1', 'par2'};
5  mm.mu_ranges = {[0.5 1], [1 3]};
6  mm.gsize = [ 100 1 ];
7  mm.xfun = @simple_sin;
8  mm.par1 = 0.5;
9  mm.par2 = 1;
10  mm.debug = 0;
11  mm.force_delete = 1;
12  mm.filecache_ignore_fields_in_model = {};
13 
14  mm.L_I_local_ptr = @fv_implicit_space;
15  mm.num_diff_flux_ptr = @fv_num_diff_flux_gradient;
16  mm.fv_impl_diff_weight = 1.0;
17  mm.fv_impl_conv_weight = 0.0;
18  mm.fv_impl_react_weight = 0.0;
19 
20  mm.mass_matrix = @fv_mass_matrix;
21 
22 % mm.bnd_rect_corner1 = [-1 -1];
23 % mm.bnd_rect_corner2 = [2 2];
24 % mm.bnd_rect_index = -2;
25  mm.verbose = 10;
26  mm.diffusivity_ptr = @diffusivity_exponential;
27  mm.diffusivity_derivative_ptr = @diffusivity_exponential_derivative;
28  mm.diff_k0 = 0.00;
29  mm.diff_m = 1.0;
30  mm.diff_p = 2.0;
31  mm.decomp_mode = 0;
32  mm.laplacian_ptr = @(glob, U, model) U;
33  mm.laplacian_derivative_ptr = @(glob, U, model) ones(length(U),1);
34  mm.filecache_velocity_matrixfile_extract = 0;
35  mm.neumann_values_ptr = @neumann_values_homogeneous;
36  mm.c_neu = 0.00;
37  mm.get_inner_product_matrix = @(detailed_data) detailed_data.W;
38  mm.l2_error_sequence_algorithm = @fv_l2_error;
39 
40  mm.new = 1;
41  mm.operators_ptr = @(x) x;
42  mm.init_values_algorithm = @(x) x;
43  mm.error_norm = 'l2';
44  mm.rb_problem_type = 'Test';
45 
46 function U = simple_sin(descr, values)
47 
48  U = descr.par1.*sin(3.14159.*values.*descr.par2);
49 
function [ INC , b_I ] = fv_implicit_space(model, model_data, U, NU_ind)
fv_implicit_space(model, model_data, U, [NU_ind])
function num_flux_mat = fv_num_diff_flux_gradient(model, model_data, U, NU_ind)
computes a numerical diffusive flux for a diffusion problem
function l2_error = fv_l2_error(U1, U2, W)
function computing the l2-error between the two fv-functions or function sequences in U1...
Definition: fv_l2_error.m:17