1 function mm = minimal_ei_model
3 mm.name =
'minimal_model';
4 mm.mu_names = {
'par1',
'par2'};
5 mm.mu_ranges = {[0.5 1], [1 3]};
12 mm.filecache_ignore_fields_in_model = {};
16 mm.fv_impl_diff_weight = 1.0;
17 mm.fv_impl_conv_weight = 0.0;
18 mm.fv_impl_react_weight = 0.0;
20 mm.mass_matrix = @fv_mass_matrix;
22 % mm.bnd_rect_corner1 = [-1 -1];
23 % mm.bnd_rect_corner2 = [2 2];
24 % mm.bnd_rect_index = -2;
26 mm.diffusivity_ptr = @diffusivity_exponential;
27 mm.diffusivity_derivative_ptr = @diffusivity_exponential_derivative;
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;
37 mm.get_inner_product_matrix = @(detailed_data) detailed_data.W;
41 mm.operators_ptr = @(x) x;
42 mm.init_values_algorithm = @(x) x;
44 mm.rb_problem_type =
'Test';
46 function U = simple_sin(descr, values)
48 U = descr.par1.*sin(3.14159.*values.*descr.par2);
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...