File List

Here is a list of all documented files with brief descriptions:

[detail level 1234567]

► datafunc
► +TwoPhaseData
BrooksCorey.m
Interface.m
Michel.m
MichelPrsLin.m
MichelSimple.m
► auxiliary
cache_velocity_matrixfile_extract.m
check_or_generate_velocity_matrixfile.m
clear_all_caches.m	This function clears the caches generated for caching of gradient data in evolution schemes
velocity_matrixfile_extract.m
► conv_flux
conv_flux_affine_decomposed.m	Function evaluating a function in the list of global coordinates specified in the columns of glob
conv_flux_brooks_corey.m	Convective flux for Buckley-Leverett problem with Brooks-Corey functions
conv_flux_brooks_corey_derivative.m	Convective flux for Buckley-Leverett problem with Brooks-Corey functions
conv_flux_brooks_corey_simple.m	Convective flux for Buckley-Leverett problem with Brooks-Corey functions
conv_flux_brooks_corey_simple_derivative.m	Convective flux for Buckley-Leverett problem with Brooks-Corey functions
conv_flux_buckley_leverett.m	Convective flux for Buckley-Leverett problem
conv_flux_buckley_leverett_derivative.m
conv_flux_burgers.m	Function computing the convective flux of a Burgers problem
conv_flux_burgers_parabola.m	Convective flux of a Burgers problem
conv_flux_forward_difference.m	Function computing the derivative of a convective flux by forward difference
conv_flux_gdl2.m	Function computing the convective flux \(f(u)\) of a convection problem
conv_flux_linear.m	Function computing the convective flux \(f(u) = v u\) of a convection problem
conv_flux_to_be_distributed_in_single_files.m
conv_flux_velocity_matrixfile.m	Function computing the convective flux \(f(u)\) of a convection problem
► diffusivity
diffusivity_buckley_leverett.m
diffusivity_buckley_leverett_derivative.m
diffusivity_buckley_leverett_simple.m
diffusivity_buckley_leverett_simple_derivative.m
diffusivity_composite.m
diffusivity_composite_components.m	Glob is a npoints times 2 matrix
diffusivity_exponential.m
diffusivity_exponential_derivative.m
diffusivity_homogeneous.m
diffusivity_linear_gradient2.m
diffusivity_richards_nonlinear.m
diffusivity_zero.m
► diffusivity_tensor
diffusivity_tensor_richards.m
diffusivity_tensor_zero.m
► dirichlet_values
dirichlet_values_affine_decomposed.m
dirichlet_values_homogeneous.m	Function computing homogeneous dirichlet-values by pointwise evaluations
dirichlet_values_leftright.m
dirichlet_values_quarter_of_five.m
dirichlet_values_uplow.m
dirichlet_values_weighted_boxes.m
dirichlet_values_weighted_boxes_coefficients.m
dirichlet_values_weighted_boxes_components.m
► init_values
exact_function_heat_equation.m
exact_function_plaplace.m	This is the first function from http://eqworld.ipmnet.ru/en/solutions/npde/npde1201.pdf
init_values_affine_decomposed.m
init_values_as_dirichlet.m
init_values_bars.m
init_values_bl.m
init_values_blobs.m
init_values_gradient_box.m	Init value function with a gradient box profile in Y-direction as output
init_values_grey_image.m
init_values_homogeneous.m
init_values_old_to_be_split_in_files.m
init_values_transformed_blobs.m
init_values_transformed_blobs_richards.m
init_values_wave.m
init_values_waveproduct.m	Product of two sinus waves in both coordinate directions
► neumann_values
neumann_values_affine_decomposed.m
neumann_values_homogeneous.m
neumann_values_outflow.m
neumann_values_pressure_gdl.m
neumann_values_rightflow.m
neumann_values_zero.m
► output_functional
output_function_box_mean.m
output_functional_volume_integral.m
► velocity
velocity_affine_decomposed.m
velocity_constant.m
velocity_parabola.m	Parabolic velocity field
velocity_richards.m
velocity_to_be_distributed_in_single_files.m
velocity_transport.m
conv_flux.m
conv_flux_linearization.m
diffusivity.m
diffusivity_cached.m	Compute diffusivity tensor for geometry transformation and store results in a cache
dirichlet_values.m	UDIRICHLET = DIRICHLET_VALUES([X],[Y], MODEL) Examples dirichlet_values([0,1,2],[1,1,1],struct(name_dirichlet_values, homogeneous, ... c_dir, 1)) dirichlet_values([0:0.1:1],[0],struct(name_dirichlet_values, xstripes, ... c_dir, [0 1 2], ... dir_borders, [0.3 0.6])) dirichlet_values([0:0.1:1],[0],struct(name_dirichlet_values, box, ... c_dir, 1, ... dir_box_xrange, [0.3 0.6], ... dir_box_yrange, [-0.1 0.1]))
eval_affine_decomp.m
geometry_transformation.m
gradient_approx.m
gradient_approx2.m
gradient_approx_matrix.m
init_values.m
inv_geo_trans_derivative.m	Computes entries of a geometry transformation function's inverse transposed jacobian
myspline.m
neuman_values.m
output_functional.m
output_functional_boundary_integral.m
reaction.m
velocity.m
► demos
demo_adaptive_basisgen.m	Demo_adaptive_basisgen
demo_cubegrid.m	Demo_cubegrid small script demonstrating the possibilities of the cubegrid class
demo_dare.m
demo_detailed_gui.m	Demo gui for detailed simulations (calling demo_rb_gui after switching some pointers)
demo_dom_dec.m	Demo showing the functionality of the dom_dec routines
demo_edge_quad.m	Demonstration of the edge-quadratures over a grid
demo_elastic_membrane.m	Demo of variational inequalities reduced order model
demo_explicit_FV.m	Demo of a explicit FV scheme for advection-diffusion
demo_fem.m	Demo of a finite element simulation
demo_fem2.m	Demo of +Fem usage for finite elements simulations of linear and stationary models: (i) Poisson, (ii) Stokes and nonlinear models: (iii) Navier-Stokes
demo_fem2_discfunc.m	This demo shows the basic functionality of the discrete function class Fem.DiscFunc
demo_femdiscfunc.m	Script demonstrating some basic functionality of lagrange finite element functions in the RBmatlab fem implementation
demo_interpol.m	Script using femdiscfunc for interpolating functions by local and global evaluations
demo_ldgfunc.m	Demo for showing ldgfunc capabilities
demo_lin_ds.m	Function demonstrating RB approach for linear dynamical systems according to MATHMOD 2009 paper
demo_quadratures.m	Small script demonstrating interval integration of polynomials of degree pdeg with quadratures of degree qdeg
demo_rb_burgers_fv.m	Small script demonstrating the RB-approach for nonlinear examples
demo_rb_error_gui.m	Demo gui for detailed simulations and reduced simulation and plotting the error
demo_rb_explicit_evol.m	Small script demonstrating the RB-approach for examples by interpolation of the explicit operator The linear advection-diffusion example of the lin-evol setting is used, but now the explicit discretization of the convection is realized by empirical interpolation
demo_rb_lin_evol_oop.m	Small collection of RBmatlab's rb-simulation abilities please inspect the source-file during execution, as the main purpose is to demonstrate the possibilities of RBmatlab's rb-philosophy
demo_rb_newton.m	Demo_rb_newton
demo_rb_nonlin_symmetry.m	Demo_rb_nonlin_symmetry
demo_rb_richards_fv.m	A small script demonstrating the online phase of the two models from the diploma thesis "Reduzierte-Basis Methoden für unges\"{a}ttigte Grundwasserstr"{o}mungen"
demo_rb_riemann_burgers.m	Demo_rb_riemann_burgers
demo_rb_simtech.m	Demo_rb_simtech demo starting a simtech LOGO in a fuelcell. Does not fully work yet... instead perhaps update the generating script simtech_fuelcall_gdl...
demo_rb_steps_oop.m	Small collection of RBmatlab's rb-simulation abilities please inspect the source-file during execution, as the main purpose is to demonstrate the possibilities of RBmatlab's rb-philosophy
demo_rb_steps_struct.m	Small collection of RBmatlab's rb-simulation abilities please inspect the source-file during execution, as the main purpose is to demonstrate the possibilities of RBmatlab's rb-philosophy
demo_rb_stokes_fem.m	This function demonstrates the reduced basis approximation of the stationary Navier-Stokes equations (2-d CFD benchmark problem)
demo_rectgrid.m	Small script demonstrating the possibilities of the rectgrid class
demo_thermalblock.m	Demo_thermalblock
demo_triagrid.m	Small script demonstrating the possibilities of the triagrid class
demo_vi.m	Function testing the implementation of the RB-Method for Parametrized Variational Inequalities. In particular 1D FEM model of a hanging elastic rope with different elasticities in subdomains
rbmatlabdemos.m	Allows interactive choice of some rbmatlab demos subgroups
rbmatlabdemos_detailed.m	Interactive gui for some high dimensional simulation demos
rbmatlabdemos_discfunc.m	Interactive gui for some discrete function demos
rbmatlabdemos_elementary.m	Interactive gui for some elementary (boring) demos
rbmatlabdemos_grid.m	Interactive gui for some grid demos
rbmatlabdemos_rb_part1.m	Interactive gui for some RB demos
rbmatlabdemos_rb_part2.m	Interactive gui for some RB demos
► discfunc
► +Fem
► +Assembly
add_integral_kernels.m	Addition of integral kernel evaluations
dirichlet_dof_vector.m	Assembly of vector enforcing the Dirichlet boundary condition
eval_coefficients.m	Concatenation of multiple parametric coefficient evaluations
matrix_part.m	Fem Matrix assembly
operator.m	Complete Fem system assembly for lin_stat and stokes models
rhs_part.m	Fem right-hand side assembly
stokes_fd_nl_operator.m	Evaluation of the Frechet-derivative of nonlinear Navier-Stokes problems for the approximation of the inf-sup constant
► +IntegralKernels
matrix_advection.m
matrix_diffusion.m
matrix_neumann.m
matrix_reaction.m
matrix_robin.m
rhs_neumann.m
rhs_robin.m
rhs_source.m
stokes_matrix_fd_nl.m	Additional trilinear term in Frechet derivative of global operator
stokes_volume_matrix.m
► +Lagrange
► @DefaultInfo
DefaultInfo.m
plot_dofmap.m
BubbleInfo.m
global_dof_index.m	Function computing the local-to-global dof map of a fem discrete function
nodes_edges_llcoord.m	Used in constructors, computes edge-local coordinates on reference triangle
nodes_lcoord.m
BcInfo.m
CompositeFunctionSpace.m
DiscFunc.m
IFemInfo.m
OperatorsDefault.m
► +Fv
► +TwoPhase
DivergenceSpace.m
GlobalSpace.m
PressureMean.m
SaturationSpace.m
VelocitySpace.m
► common
basis_orthonormalization_matrix.m
copy_model_data_to_plot_params.m	Helper function copying extracting relevant information for plot_params from the model
copy_model_descr_to_plot_params.m
df_func_difference_sqr.m
disc_init_values.m
func_phi_product.m
ILocalizedOperator.m
inner_product.m
inner_product_matrix.m
ISeparableFunction.m
ISeparableOperator.m
l2project.m
LocalizedOperatorDefault.m
plot_discfunc.m
plot_sequence.m	Plotting a sequence of data slices on polygonal 2d grid (constructed from params if empty) and providing a slider for changing between the data slices
plot_subplot_sequence.m	Plotting a sequence of data slices on polygonal 2d grid (constructed from params if empty) and providing a slider for changing between the data slices
SeparableFunctionDefault.m
► fem
evaluate_gradient.m
fem_basis_weight_matrix.m
fem_evaluate.m
fem_evaluate_basis.m
fem_evaluate_basis_function.m
fem_evaluate_scalar_basis_derivative.m
fem_evaluate_scalar_basis_function_derivative.m
fem_global_dof_index.m	Function computing the local-to-global dof map of a fem discrete function
fem_h10_boundary_inner_product_matrix.m	Fem_h10_boundary_inner_product_matrix(df_info,elind,edgeind)
fem_h10_norm.m
fem_h1_norm.m
fem_interpol_global.m
fem_interpol_local.m
fem_l2_boundary_inner_product_matrix.m	Fem_l2_boundary_inner_product_matrix(df_info,elind,edgeind)
fem_l2_norm.m
fem_laplace.m
fem_matrix_adv_integral_kernel.m
fem_matrix_boundary_part_assembly.m	Auxiliary function assembling the boundary integral components of system matrix A note: cell-array valued kernels can be integrated
fem_matrix_diff_integral_kernel.m
fem_matrix_neumann_integral_kernel.m
fem_matrix_parts_assembly.m
fem_matrix_reac_integral_kernel.m
fem_matrix_robin_integral_kernel.m
fem_matrix_volume_part_assembly.m
fem_ndofs.m
fem_ndofs_per_element.m
fem_operators.m
fem_operators_output.m
fem_operators_output_boundary_integral.m
fem_operators_output_volume_integral.m
fem_plot_dofmap.m
fem_rhs_boundary_part_assembly.m
fem_rhs_neumann_integral_kernel.m
fem_rhs_parts_assembly.m
fem_rhs_robin_integral_kernel.m
fem_rhs_volume_part_assembly.m
fem_scalar_component.m
femdiscfunc.m
feminfo.m
H10_scalar_product_matrix.m	This routine computes the stiffness matrix for a constant c=1. K_one = int_omega (grad phi_j) . grad phi_i dx
lagrange_nodes_edges.m
lagrange_nodes_edges_llcoord.m
lagrange_nodes_lcoord.m
► fv
Contents.m	FV
fv_coercivity_bound.m
fv_conv_diff.m
fv_conv_diff_explicit_space.m	Fv_conv_diff_explicit_space(U,NU_ind,grid,model)
fv_conv_diff_step.m
fv_conv_explicit_space.m	Fv_conv_explicit_space(U,NU_ind,grid,params) function applying an FV-space-discretization operator starting from old values U corresponding to the geometry given in grid producing a new vector of elementwise scalars NU but only on for the subelements with numbers given in NU_ind. If NU_ind is empty, all new values NU are determined, i.e. length(NU) = length(U) = grid.nelements
fv_conv_flux_linearization_matrix.m
fv_conv_flux_matrix.m	Function computing the flux matrix of a convection problem. simply reformatting the grid data suitably for pointwise evaluation by conv_flux. As evaluation points the points of suitable gauss-quadratures are chosen. The degree can be chosen in the model structure
fv_diff_explicit_space.m	Fv_diff_explicit_space(U,NU_ind,grid,params)
fv_element_mean.m	Function computing the element averages of a discrete function U in the grid elements with indices I. Most arguments are dummy, but required for more general discrete functions, e.g. p1, etc
fv_error.m
fv_estimate_coercivity_alpha.m
fv_evaluate_basis.m
fv_explicit_space.m
fv_frechet_operators_conv_flux_waterflow_upwind.m	Computes a jacobian of implicit non-linear convective contributions to time evolution matrices at a point (S,U)
fv_frechet_operators_diff_flux_pressure_gradient.m	Computes a jacobian of implicit non-linear convective contributions to time evolution matrices at a point (P,S)
fv_frechet_operators_diff_implicit_gradient.m	Computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U
fv_frechet_operators_diff_implicit_gradient2.m	Computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U
fv_frechet_operators_diff_implicit_gradient3.m	Computes a jacobian of implicit non-linear diffusion contributions to time evolution matrices at a point U
fv_h1_inner_product_matrix.m	Function computing the h1 inner product matrix for fv-functions on the grid
fv_implicit_space.m	Fv_implicit_space(model, model_data, U, [NU_ind])
fv_init_values.m
fv_inner_product.m
fv_inner_product_matrix.m
fv_l1l2_error.m
fv_l2_error.m	Function computing the l2-error between the two fv-functions or function sequences in U1,U2
fv_l2l2_error.m
fv_l2project.m	Func to the fv space. A quadrature of degree qdeg is used
fv_linfty_error.m	Compute the infinity-norm error between two Dof vectors
fv_local_mass_matrix_rect.m
fv_local_mass_matrix_tria.m
fv_mass_matrix.m
fv_num_conv_flux.m
fv_num_conv_flux_engquist_osher.m	Function computing a numerical convective Engquist-Osher flux matrix
fv_num_conv_flux_lax_friedrichs.m	Function computing a numerical convective Lax-Friedrichs flux matrix
fv_num_conv_flux_waterflow_upwind.m
fv_num_diff_flux.m
fv_num_diff_flux_gradient.m	Computes a numerical diffusive flux for a diffusion problem
fv_num_diff_flux_gradient_tensor.m	Computes a numerical diffusive flux for a diffusion problem including a tensor
fv_num_diff_flux_pressure_gradient.m	Computes a numerical diffusive flux for a diffusion problem
fv_operators_conv_explicit_engquist_osher.m	Computes convection contribution to finite volume time evolution matrices, or their Frechet derivative
fv_operators_conv_explicit_lax_friedrichs.m	Computes convection contribution to finite volume time evolution matrices, or their Frechet derivative
fv_operators_conv_flux_waterflow_upwind.m	Computes convection contribution to finite volume time evolution matrices, or their Frechet derivative
fv_operators_conv_implicit_engquist_osher.m	Computes convection contribution to finite volume time evolution matrices, or their Frechet derivative
fv_operators_diff_implicit_gradient.m	Computes diffusion contributions to finite volume time evolution matrices, or their Frechet derivative
fv_operators_diff_implicit_gradient2.m	Computes diffusion contributions to finite volume time evolution matrices, or their Frechet derivative
fv_operators_diff_implicit_gradient_tensor.m
fv_operators_implicit.m
fv_operators_implicit_explicit.m
fv_operators_neumann_explicit.m	Computes a neumann contribution matrix for finite volume time evolution operators, or their Frechet derivative
fv_operators_output.m	Function returning components, coefficients, and complete operator for a linear output functional on fv discrete functions
fv_operators_zero.m
fv_plot.m	Routine plotting a single fv function of fv_functions
fv_search_max_lxf_lambda.m
fv_space_operator.m	Fv_space_operator(model,model_data,U,NU_ind,grid,weights)
fv_two_phase_es.m
fv_two_phase_hess_fun.m
fv_two_phase_imp.m
fv_two_phase_space.m
reaction_term.m
► ldg
► @ldgdiscfunc
display.m
evaluate.m
ldgdiscfunc.m
subsasgn.m
subsref.m
ldg_basis_orthonormalization_matrix.m
ldg_basis_weight_matrix.m
ldg_conv_detailed_simulation.m
ldg_edge_flux_operator_fct.m
ldg_edge_num_flux_matrix.m
ldg_element_flux_operator_fct.m
ldg_evaluate.m
ldg_evaluate_basis.m
ldg_evaluate_basis_derivative.m
ldg_evaluate_scalar_basis_derivative.m
ldg_inv_mass_matrix.m
ldg_l2error.m
ldg_l2project.m
ldg_local_mass_matrix.m
ldg_mass_matrix.m
ldg_ndofs.m
ldg_ndofs_per_element.m
ldg_numerical_flux_operator_fct.m
ldg_operators_adv_explicit.m
ldg_operators_explicit.m
ldg_params.m
ldg_plot.m
ldg_scalar_component.m
ldg_zero.m
ldginfo.m
► doxygen
developers.c
doxygen.m	Here comes a short description text
dummyclasses.c
groups.c
maindoc.c
namespaces.c
► general
► +DataTree
CreatorDefault.m
DefaultNode.m
DummyLeafNode.m
DummyMerger.m
ICreator.m
IdMapNode.m
ILeafNode.m
INode.m
LeafDescription.m
NullCreator.m
PpartNode.m
ScalarCreator.m
TpartNode.m
► +Postprocess
► +StochasticAssessment
Assessment.m
Output.m
plot_as_tikzfile.m	Postprocesses a figure and write out an image and a text file that can be included in TeX documents
plot_trajectories.m	Function generating a tikz graphic showing trajectories for certain selected parameters
► +VecMat
CompositeMatrixDefault.m
fixed_point_algorithm.m
gram_schmidt_parallel.m	Performs classical gram schmidt orthonormalization algorithm with re-orthogonalization. loss of orthogonality is a multiple of machine precision
gram_schmidt_reiterate.m	Performs classical gram schmidt orthonormalization algorithm with re-orthogonalization. loss of orthogonality is a multiple of machine precision
ICompositeMatrix.m
LUPQ_Handle.m
► basic
add_to_array.m
copy_field_if_exists.m
count_column_frequency.m
couple_N_and_M_by_c.m	Modifies the reduced basis size fields of model by a single variable
detect_duplicate_rows.m
disp_deprecated.m
extend_class_from_struct.m
find_corresp.m
isequal_ignore_handles.m
isequal_ignore_handles_nan_treatment.m
lincomb_sequence.m
lincomb_sequence2.m
lincomb_sequence3.m
matrix2str.m
print_datatable.m
repmatrows.m
sin_sym.m
structcmp.m
structcpy.m	Copies the fields of structure s2 into structure s1. If the field to be copied does not exist in s1 yet, a field with the appropriate name is created
subblock_sequence.m
test_affine_decomp.m
► filecaching
cache.m
cache_function.m	Simple caching of function call inputs are cached too!
filecache_clear.m
filecache_function.m	Function used for file-caching other function calls
filecache_path.m
tictoc_wrapper.m
► geometry
area_triangle.m
circumcenter_triangle.m
cubequadrature.m	Integration of function func over reference cube == unit cube. by Gaussian quadrature exactly integrating polynoms of poldeg
dist_point_line.m
get_intervalquadrature_points.m	Returns local quadrature points and corresponding weights for a Gaussian quadrature rule for a function defined on a 1d interval
get_quadrature_weights_1d.m	Returns local quadrature points and corresponding weights for a Gaussian quadrature rule for a function defined on a 1d interval
intervalquadrature.m	Integration of function func over reference interval == unit interval. by Gaussian quadrature exactly integrating polynoms of poldeg
quadrature.m
spline_select.m
triaquadrature.m
XPartMap.m
► help
class_help.m	Prints out class structure and documentation for a given classname or object
► postprocess
plot_as_tikzfile.m	Postprocesses a figure and write out an image and a text file that can be included in TeX documents
plot_error_landscape.m	Plots an output structure generated by stochastic_error_estimation()
saveasshown.m
► vecmat
delzerocolumns.m	Function deleting zero-columns from matrix X
find_vector.m
gram_matrix.m
improve_conditioning.m
model_orthonormalize.m
model_orthonormalize_gram_schmidt.m
model_orthonormalize_qr.m
model_PCA_fixspace.m
orthonormalize.m
orthonormalize_chol.m
orthonormalize_gram_schmidt.m
orthonormalize_old.m
orthonormalize_qr.m
PCA_fixspace.m
PCA_fixspace_evalues.m
power_vector2.m
power_vector2_derivative.m
rand_log.m
rand_uniform.m
regular_submatrix_indices.m
spblkdiag.m
spdiag.m
svds_batch.m
veccomp1.m
veccomp2.m
vectorset_difference.m
► verbosity
verbose.m	This function displays messages depending on a message-id and/or a level. Aditionally you can set/reset the level-filer and add ore remove message-ids to the include and exclude lists
CacheableObject.m
debugdisp.m	DEBUGDISP - Function that displays a message only if a global debug flag is activated
gplmm.m	Global projected Levenberg-Marquard method
htdoc.m	Opens mtoc++ documentation in a browser
matlab_version.m
MatlabDocMaker.m
merge_model_plot_params.m
mmread.m
newton_raphson.m	Global projected Levenberg-Marquard method
parfor_progress.m	PARFOR_PROGRESS Progress monitor (progress bar) that works with parfor. PARFOR_PROGRESS works by creating a file called parfor_progress.txt in your working directory, and then keeping track of the parfor loop's progress within that file. This workaround is necessary because parfor workers cannot communicate with one another so there is no simple way to know which iterations have finished and which haven't
rbmatlabhome.m
rbmatlabinput.m
rbmatlabresult.m
rbmatlabtemp.m
show_abstract_members.m	Displays unimplemented abstract methods of class with name class_name
► grid
► @cubegrid
check_consistency.m
coord2leaf_element.m
cubegrid.m
demo.m
display.m
get.m
get_edges.m
get_leafgids.m
get_ranges_of_element.m
get_volume.m
gid2lid.m
lid2gid.m
plot.m
plot_grid.m
plot_leafelement_data.m
plot_leafvertex_data.m
refine.m
remove_duplicate_vertices.m
► @gridbase
check_consistency.m
display.m
edge_quad_eval.m
edge_quad_eval_mean.m
edge_quad_points.m
get_edge_points.m
get_enbi.m
gridbase.m
gridpart.m
inspect.m
plot_element_data.m
plot_element_data_sequence.m
plot_polygon_grid.m
plot_vertex_data.m
set_boundary_types.m
► @onedgrid
gridpart.m
onedgrid.m
► @rectgrid
demo.m
isequal.m
local2global.m
plot.m
rectgrid.m
set_nbi.m
► @triagrid
aff_trafo_glob2loc.m
aff_trafo_loc2glob.m
aff_trafo_orig2ref.m
demo.m
display.m
global2local.m
gridpart.m
llocal2local.m
local2global.m
micro2macro_map.m
plot.m
read_msh.m
set_nbi.m
triagrid.m
► alu3d
cog_elements_alu3d_hexa.m
cog_faces_alu3d_hexa.m
coord_faces_alu3d_hexa.m
cut_alu3d_hexa.m
face_in_matrix.m
load_alu3d_hexa.m
merge_alu3d_hexa.m
plot_bnd_alu3d_hexa.m
save_alu3d_hexa.m
► common
compute_edge_indices.m	Edge index matrix. This matrix maps each edge specified by the tuple (element_id, local_edge_id) to a unique and continuous edge index enumeration
construct_grid.m
index_ext.m
plot_data_sequence.m
► models
► +advection_Nadapt
my_u0_coefficients.m
my_u0_components.m
my_udir_coefficients.m
my_udir_components.m
► +ThermalBlock
DetailedModel.m
► advection_output
advection_fv_output_model.m
advection_fv_output_opt_model.m
advection_fv_output_vconst_model.m
advection_ldg_model.m
lin_ds_advection_vconst_fast_model.m
lin_ds_advection_vconst_model.m
► common
default_plot_control.m	DEFAULT_PLOT_CONTROL M-file for default_plot_control.fig DEFAULT_PLOT_CONTROL, by itself, creates a new DEFAULT_PLOT_CONTROL or raises the existing singleton*
demo_rb_gui.m	Reduced basis demo with sliders
detailed_ei_rb_proj_simulation.m
detailed_ei_simulation.m
detailed_simulation.m
discrete_boundary_values.m	Convert a boundary function with global evaluation to local evaluation
discrete_volume_values.m	Convert a volume function with global evaluation to local evaluation
dune_demo_rb_gui.m	Reduced basis demo with sliders for a remotely running DUNE-rb server application
elliptic_discrete_model.m	Function creating a model with local functions out of a model with global functions. See detailed description for explanation
gen_detailed_data.m
gen_model_data.m
gen_reduced_data.m
generic_fem_model_adapter.m	Initializes a default linear and stationary model for more generic fem discretization by modifying model generated by lin_stat_model_default
insert_affine_decompositions.m	Field <name> is created as a parameter separable function, if both <name>_components and <name>_coefficients are present fields of model
model_default.m	Model = model_default(model)
optimize.m	Opt_data = optimize(model, model_data, detailed_data, reduced_data)
plot_detailed_data.m
plot_sim_data.m	Function performing the plot of the simulation results as specified in model
postprocess_gravity.m	Subtracts a previously added addent induced by gravitational effects
rb_init_values.m
rb_operators.m
rb_reconstruction.m
rb_simulation.m
renew_model.m	Change fields of old param structure to new model structure with excessive use of function pointers
unitcube.m	Function adding fields to model for generating a 2D rectgrid with 100 x 100 elements on the unit-square
► comsol
► initialization
comsol_get_DBC_ind.m
comsol_get_element_type.m
comsol_get_global_params_from_comsol_model.m
comsol_get_grid_type.m
comsol_get_init_values.m
comsol_get_pdeg.m
comsol_get_rbmatlab_gridtype_from_comsol.m
comsol_get_tags.m
gen_rbmatlab_model_from_comsol_model.m
► input_output
comsol_get_mu_from_comsol_model.m
comsol_load.m
comsol_save.m
comsol_set_mu_from_rbmatlab_model.m
► ThermalBlock
► 2D_evol_weak_form
evol_TB_2D_weak_form_inner_product_matrices.m
evol_TB_2D_weak_form_model.m
evol_TB_2D_weak_form_model_script.m	This Script computes the comsol 2D-evol-ThermalBlock_weak_form model in detailed form and reduced form and compares the errors!
evol_TB_2D_weak_form_operators.m
evol_TB_2D_weak_form_operators_output.m
► 2D_stat
comsol_thermal_block_calculate_inner_product_matrices.m
comsol_thermal_block_model.m
comsol_thermal_block_operators.m
comsol_thermal_block_operators_output.m
comsol_thermal_block_script.m	Comsol_thermal_block_script
► 3D_stat
► comsol_model_files
ThermalBlock_3D_5x5x5_LinLagr_Einfluss_unten_125Params.m
ThermalBlock_3D_5x5x5_LinLagr_Einfluss_unten_3Params.m
ThermalBlock_3D_5x5x5_LinLagr_Einfluss_unten_8Params.m
ThermalBlock_3D_5x5x5_LinLagr_Einfluss_unten_xParams.m
comsol_ThermalBlock3D_calculate_inner_product_matrices.m
comsol_ThermalBlock3D_model.m
comsol_ThermalBlock3D_operators.m
comsol_ThermalBlock3D_operators_output.m
comsol_ThermalBlock3D_script.m	Comsol_ThermalBlock3D_script
► dune-rb
dune_detailed_simulation.m
dune_gen_model_data.m
► european_option_pricing
eop_beta.m	[model, beta_build] = eop_beta(model)
eop_C_L_I.m	Model = eop_C_L_I(model)
eop_example_script.m	Eop_example_script(step)
eop_fd_functionals.m	[v, l] = eop_fd_functionals(model, model_data)
eop_fd_norm.m	Norm = eop_fd_norm(fd_function1, fd_function2, grid, ~)
eop_fd_operators.m	[L_I, L_E, b, L_I_adj, L_E_adj] = eop_fd_operators(model, model_data)
eop_gridconvergence.m	[error, h_sequence, EOC] = eop_gridconvergence(model, model_data, params)
eop_init_values.m	Ut = eop_init_values(model,model_data)
eop_master_gui.m
eop_space_time_norm.m	Norm = eop_space_time_norm(fd_function1, fd_function2, grid, ~)
eop_theta_functional.m	Sim_data.y = eop_theta_functional(sim_data.U, v)
european_option_pricing_demo.m	Simple demo script: loads a primal reduced basis with standard grid settings and 200 basis vectors (the l2-error-estimator was used during basis generation) and produces a GUI for the european-Option_pricing model
european_option_pricing_model.m	Model = european_option_pricing_model(params)
► hmm_micro_local
g0.m
hmm_micro_local_model.m
HMM_UM_GESCHW.m
Phasen_lokal.m
Phasen_lokal_old.m
Phasen_lokal_space.m
REGULARlok.m
REGULARlok_space.m
test_lokal.m	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 1D, skalare Erhaltungsgleichung % % mikroskopisches Modell (lokale Regularisierung) % u_t+f(u)_x = epsilon u_{xx} + alpha*epsilon^2 u_{xxx} % mit f(u) = u^3 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
test_lokal_old.m	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 1D, skalare Erhaltungsgleichung % % mikroskopisches Modell (lokale Regularisierung) % u_t+f(u)_x = epsilon u_{xx} + alpha*epsilon^2 u_{xxx} % mit f(u) = u^3 % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
u_index_aus.m
► multiscale_buckley_leverett
A_operator.m
b_operator.m
BL_D.m
BL_f.m
HMM_AB_U0_BL.m
HMM_CFL_BL.m
HMM_MIKRO_teil.m
HMM_REKONSTRUKTION.m
HMM_UM_GESCHW_BL.m
INVERSE_TRIDIAG.m
multiscale_buckley_leverett_model.m	Initialization of micromodel for buckley leverett multiscale problem
test.m
► nonlin_evol_oop
► convdiff
convdiff_descr.m
convdiff_dune_descr.m	Convection diffusion example using dune-rb for high dimensional computations and data structures
laplace_dune_descr.m	Convection diffusion example using dune-rb for high dimensional computations and data structures
newton_oo_model.m
nonlin_symmetry_descr.m
richards_fv_bg_descr.m
richards_fv_descr.m	Non-linear evolution equation with geometry transformation and an example of the Richards equation
twophase_descr.m
► porsche
► constraint_files
porsche_circle_x3_y3_get_eq_constr.m
porsche_circle_x3_y3_get_grad_eq_constr.m
porsche_circle_x3_y3_get_Hes_Lag.m
porsche_circle_x3_y3_get_Hessian_eq_constr.m
porsche_circle_x3opt_y3opt_r10_get_eq_constr.m
porsche_circle_x3opt_y3opt_r10_get_grad_eq_constr.m
porsche_circle_x3opt_y3opt_r10_get_Hes_Lag.m
porsche_circle_x3opt_y3opt_r10_get_Hessian_eq_constr.m
porsche_circle_x3opt_y3opt_r20_get_eq_constr.m
porsche_circle_x3opt_y3opt_r20_get_grad_eq_constr.m
porsche_circle_x3opt_y3opt_r20_get_Hes_Lag.m
porsche_circle_x3opt_y3opt_r20_get_Hessian_eq_constr.m
porsche_circle_x3ref_y3_ref_r20_get_eq_constr.m
porsche_circle_x3ref_y3_ref_r20_get_grad_eq_constr.m
porsche_circle_x3ref_y3_ref_r20_get_Hes_Lag.m
porsche_circle_x3ref_y3_ref_r20_get_Hessian_eq_constr.m
aff_trafo_coef.m
aff_trafo_glob2loc.m
aff_trafo_loc2glob.m
change_mu.m
compute_pressure.m
createCombinations.m	Creates the cartesian product of the vectors passed as a matrix containing elements of each vector per row
disc_gradient.m
global2local.m
grid_reshape.m
micro2macro_map.m
pmicro2tmacro.m
points_trafo.m
porsche_coercivity_alpha.m
porsche_create_basis.m
porsche_detailed_simulation.m
porsche_diffusivity_tensor_coefficients.m
porsche_diffusivity_tensor_components.m
porsche_gen_detailed_data.m
porsche_gen_model_data.m
porsche_gen_reduced_data.m
porsche_get_Hessian_J.m
porsche_get_Jacobian.m
porsche_model.m
porsche_neumann_components.m
porsche_objective_function.m
porsche_operators_output.m
porsche_output_functional.m
porsche_plot.m
porsche_rb_simulation.m
porsche_x3_y3_grid_search.m
SQP_algorithm.m
SQP_kkt_check.m
test_mic_mac_grid.m	Zum Testen: Micro und Macrogitter
advection_diffusion_fv_model.m
advection_fv_output_model_hp.m
buckley_leverett_model.m
burgers_1d_model.m	Simple model for Burgers PDE $d/dt x + d/d_xi (1/2 * v * x^2) = 0$ on the unit square xi in [0,1] with initial value x(.,0) = x0(.) = piecewise constant x_left and x_right on left/right half of domain and dirichlet boundary values x_left and x_right and discretization via Lax-friedrichs (central differences with numerical diffusion) The v is the velocity. the parameter vector is [x_left, x_right, v]
convdiff_model.m	Function creating a simple model for a linear convection diffusion problem
dare_advection_diffusion.m
elastic_membrane_model.m
elastic_rope_model.m
elliptic_debug_model.m
follicle_model.m	Model of the human follicle growth
follicle_rect_model.m	Model of the human follicle growth
laminar_flow_model.m	Model of laminar flow (steady Navier-Stokes) around cylinder in a pipe
minimal_ei_model.m
multiscale_thermalblock_model.m
newton_model.m
nonlin_symmetry_model.m
oscillator_model.m
poisson_model.m
praktikum_ellipt_model.m
praktikum_poisson_model.m
quadratic_poisson_model.m	Quadratic poisson equation on unit interval
richards_fv_model.m
riemann_burgers_model.m
thermalblock_dd_model.m	Custom thermalblock model used for domain decomposition
thermalblock_model.m	Thermal Block example similar as described in the book of A.T. patera and G. Rozza (just one parameter more)
thermalblock_model_hp.m	Thermal Block example similar as described in the book of A.T. patera and G. Rozza (just one parameter more)
thermalblock_model_struct.m	Thermal Block example similar as described in the book of A.T. patera and G. Rozza (just one parameter more)
twoscale_thermalblock_model.m
unit_ball_model.m
► rbasis
► basisgen
► ei
ei_detailed.m	Constructs a collateral reduced basis and interpolation points for given operator evaluations
ei_error_convergence.m
ei_operator_collect_files.m	Collects operator evaluations on a sample of snapshots
► kernel
cubegrid_interp_greedy.m	Method determining interpolation points for rbf (radial basis function) interpolation of a given function via cubegrid refinements in greedy-fashion
RbfInterpolant.m
► oop
► +Greedy
► +DataTree
► +Detailed
DuneRBLeafNode.m
EILeafNode.m
IdMapNode.m
IInjectableNode.m
ILeafNode.m
InfoNode.m
INode.m
PODEILeafNode.m
PpartNode.m
RBLeafNode.m
TpartNode.m
► +Reduced
IdMapNode.m
SeparableFunctionNode.m
SeparableOperatorNode.m
TpartNode.m
Info.m
► +LRFG
Algorithm.m
BasisInfo.m
error_indicator.m
ModelInterface.m
► +Plugin
Default.m
EI.m
EICommon.m
EIPOD.m
InjectedTpart.m
Interface.m
POD.m
PODCommon.m
PODDune.m
PODEI.m
SummedEI.m
► +User
FVDetailedModelDefault.m
IDetailedData.m
IDetailedModel.m
IReducedDataNode.m
IReducedModel.m
ReducedData.m
Algorithm.m
Checkpoint.m
Combined.m
EiTpart.m
Interface.m
MetaInterface.m
TrainingSetAdaptation.m
► +ParameterSampling
Interface.m
IRefineable.m
Prescribed.m
Random.m
Single.m
Uniform.m
► +SnapshotsGenerator
Cached.m
MergedSpaceOpEvals.m
Random.m
SpaceOpEvals.m
Trajectories.m
► rbmodels
► +Test
DetailedData.m
DetailedModel.m
ReducedData.m
ReducedModel.m
rb_init_values_separable.m	Function computing initial values for a reduced simulation
► scm
fast_eigs.m
SCM.m
scm_coercive_demo.m	Scm_coercive_demo()
scm_coercive_greedy.m	Model=scm_greedy(model, model_data)
scm_coercive_lb.m	Alpha_LB = scm_lb(mu,model,model_data) computation of the lowerbound of the coercive constant equal to the coercive constant computet via SCM
scm_demo.m	Scm_demo.m a simple demo script which produces scm_offline_data for the inf-sup constant of the scm_minimal_model. Then for a fine set of parameters in [0,1] the exact constant beta(mu), the lower bound beta_{LB}(mu) and the exact cercivity constant alpha(mu) are computet and the results are plottet. This shows that the scm_minimal_model is coercive up to mu = 0.5 and from there on it is only inf-sup stable. For mu = 0.5 it is neither cercive nor inf-sup stable. The main point is to show, that the SCM is working fine for little lin_stat inf-sup stable problems
scm_get_neighbours.m	[P_M, ind] = scm_get_neighbours(M, mu, C)
scm_infsup_demo.m	Scm_infsup_demo()
scm_infsup_greedy.m	Model=scm_greedy(model, model_data)
scm_infsup_lb.m	Alpha_LB = scm_infsup_lb(mu,model,model_data) computation of the lowerbound of the coercive constant equal to the coercive constant computet via SCM
scm_lower_bound.m	[constant_LB, constant_UB] = scm_lower_bound(model, reduced_data)
scm_minimal_model.m	Model = scm_minimal_model(size)
scm_offline.m	Scm_offline_data = scm_offline(model, detailed_data, M_train, D_train)
scm_online.m	Scm_results = scm_online(mu, Theta_mu, scm_offline_data, M_alpha, M_plus, desired_constant)
SCMonline.m
animate_basisgen.m
animate_basisgen_error.m
basisgen_fixed.m
basisgen_refined.m
basisgen_refined_tmp.m
dune_RB_extension_PCA_fixspace.m
gen_and_test_basis.m
inspect_mu_distribution.m
plot_basisgen_results.m
rb_basis_generation.m	Reduced basis construction with different methods
RB_extension_lin_stat_default.m
RB_extension_max_error_snapshot.m
RB_extension_PCA_fixspace.m	Function computing a RB basis extension for given parameters by the POD-Greedy algorithm
RB_extension_PCA_fixspace_flexible.m	Function computing a RB basis extension for given parameters by the POD-Greedy algorithm
RB_extension_PCA_fixspace_flexible_hp.m
RB_greedy_extension.m	Function performing a greedy search loop for reduced basis generation
RB_init_basis_empty.m
RB_init_data_basis.m
RB_init_data_basis_stationary_default.m
rb_mu_element_indicators.m	Detailed_data, [offline_data], MMesh, Delta_train, model)
rb_test_indicator.m	M_test,[savepath])
rb_test_projection_error.m
SimpleDetailedData.m
► problem_types
► +AbstractModel
default_description.m
DetailedData.m
Model.m
ModelData.m
RBSimData.m
ReducedData.m
SimData.m
► +ARE
► +GammaCalculation
GammaCalculatorInterface.m
Kernel.m
Lyapunov.m
PowerIteration.m
► @Model
detailed_simulation.m
gen_detailed_data.m
Model.m
rb_reconstruction.m
rb_residual_norm.m
rb_simulation.m
DefaultModel.m
descr_default.m	This function initializes the default settings for the ARE model
DetailedData.m
ModelData.m
RBSimData.m
ReducedData.m
SimData.m
SimDataRec.m
► +DARE
► +GammaCalculation
Kernel.m
Lyapunov.m
PowerIteration.m
► @DetailedData
DetailedData.m
► @Model
detailed_simulation.m
gen_detailed_data.m
Model.m
rb_reconstruction.m
rb_residual_norm.m
rb_simulation.m
DefaultModel.m
descr_default.m	This function initializes the default settings for the ARE model
ModelData.m
RBSimData.m
ReducedData.m
SimData.m
SimDataRec.m
► +LinEvol
► @DetailedModel
detailed_simulation.m
DetailedModel.m
gen_model_data.m
plot_sim_data.m
► @ReducedData
rb_operators.m
ReducedData.m
► @ReducedModel
rb_simulation_impl.m
ReducedModel.m
descr_default.m	Function initializing some fields of a lin-evol model
DetailedData.m
► +LinEvolDune
DetailedModel.m
ReducedData.m
ReducedModel.m
► +LinStat
► @DetailedModel
detailed_simulation.m
DetailedModel.m
gen_model_data.m
plot_sim_data.m
► @ReducedModel
rb_simulation.m
ReducedModel.m
descr_default.m	Function initializing some fields of a lin-stat model
DetailedData.m
ReducedData.m
► +LinStatDune
DetailedModel.m
ReducedData.m
ReducedModel.m
► +NonlinEvol
► @DetailedModel
detailed_simulation.m
DetailedModel.m
gen_model_data.m
plot_sim_data.m
► @ReducedData
rb_operators.m
ReducedData.m
► @ReducedModel
rb_simulation_impl.m
ReducedModel.m
descr_default.m	Default discretization description for problems
DetailedData.m
EiRbReducedDataNode.m
EiReducedDataNode.m
RbReducedDataNode.m
► +TwoPhaseFlow
► @DetailedModel
detailed_simulation.m
detailed_simulation_galerkin.m
detailed_simulation_impes.m
DetailedModel.m
gen_model_data.m
plot_sim_data.m
► @ReducedData
ReducedData.m
► @ReducedModel
rb_reconstruction.m
rb_simulation_impes_impl.m
rb_simulation_impl.m
ReducedModel.m
descr_default.m	Default discretization description for problems
DetailedData.m
DetailedLeafNode.m
EiRbReducedDataNode.m
EiReducedDataNode.m
RbReducedDataNode.m
► burgers_fem
burgers_fem.m	Hauptskript fuer burgers-fem-rb
gen_dune_params.m
rb_burgers_fem_detailed_prep.m
rb_burgers_fem_offline_prep.m
rb_burgers_fem_offline_subset.m	Function extracting a subset of the offline data
rb_burgers_fem_online_prep.m
rb_burgers_fem_simulation.m
► common
comsol_rb_init_data_basis.m
dune_rb_init_data_basis.m
dune_RB_init_data_basis_old.m
dune_rb_init_values.m
dune_set_mu.m	Sets the parameter mu in dune-rb
eval_affine_decomp.m
eval_affine_decomp_general.m
extract_reduced_data_subset.m
get_coercivity.m
get_continuity.m
get_infsup.m
get_mu.m
get_mu_default.m
get_rb_size.m
get_rb_size_default.m
init_model.m
load_detailed_simulation.m	Load single trajectory of previously saved results
plot_error_estimator.m
plot_mu_frequency.m
rb_init_values_default.m	Function computing the reduced basis initial values. If the decomposition mode is coefficients, the detailed_data are superfluous, can (and should for H-independence) be empty
rb_output_functional_prep.m
rb_plot_detailed_data.m
rb_plot_interpolation_points.m
rb_plot_output_estimation.m
rb_plot_reconstruction.m
rb_reconstruction_comsol.m	(trivial) function computing a detailed reconstruction by linear combination of the coefficients in the simulation data with the orthonormal reduced basis RB
rb_reconstruction_default.m	(trivial) function computing a detailed reconstruction by linear combination of the coefficients in the simulation data with the orthonormal reduced basis RB
rb_test_convergence.m	Rb_test_convergence(detailed_data,model)
rb_test_error.m
rb_test_estimator.m
rb_test_estimator_parallel.m
rb_test_indicator.m	M_test,[savepath])
save_detailed_simulation_finals.m
save_detailed_simulations.m	Perform loop over detailed simulations and save results or check consistency with existing saved results
set_mu.m
set_mu_default.m
set_mu_general.m
set_mu_in_model_and_base_model_old.m
set_time.m
set_time_default.m
► comsol
► common
calc_inner_product.m
comsol_calculate_inner_product_matrices.m
comsol_calculate_inner_product_matrices_default.m
comsol_calculate_inner_product_matrices_MULTI.m
comsol_operators_output_default.m
► lin_evol
comsol_evol_detailed_simulation.m
comsol_evol_gen_detailed_data.m
comsol_evol_gen_model_data.m
comsol_evol_gen_reduced_data.m
comsol_evol_plot_sim_data.m
comsol_evol_rb_reconstruction.m
comsol_lin_evol_rb_simulation.m
comsol_plot_sequence.m
get_assembled_matrices.m
► lin_stat
comsol_lin_stat_gen_detailed_data.m
comsol_lin_stat_gen_reduced_data.m
comsol_RB_extension_greedy_lin_stat.m
comsol_stat_detailed_simulation.m
comsol_stat_gen_model_data.m
comsol_stat_plot_sim_data.m
► dictionary
dictionary_extend_reduced_data.m
dictionary_gen_detailed_data.m	Simply random parameter set and snapshot generation
dictionary_gen_reduced_data.m	% The following works, but results in slow linear combination reduced_data= lin_stat_gen_reduced_data(model,detailed_data);
dictionary_rb_simulation.m	Online rb simulation by online greedy minimizing redidual norm over dictionary, or normal RB simulation:
► dom_dec
dom_dec_compute_error.m
dom_dec_compute_projection_error.m
dom_dec_detailed_simulation.m	Detailed solution is computed via the iterative Dirichlet-Neumann schema
dom_dec_gen_detailed_data.m	Function generating the reduced basis functions
dom_dec_gen_model_data.m
dom_dec_gen_reduced_data.m	All required offline data for the rb-simulation is computed. there are two ingredients for the error estimator - the jump across \(\Gamma\) and the residuum
dom_dec_get_dofs_from_sim_data.m
dom_dec_get_inner_product_matrices.m
dom_dec_get_rb_from_detailed_data.m
dom_dec_get_rb_size.m
dom_dec_model.m	Function creating a domain-decomposition-model with an arbitrary model and optional params
dom_dec_operators.m	Function computing all required matrizes for the simulation
dom_dec_orthonormalize.m
dom_dec_PCA_fixspace.m	Function computing PCA fixspaces according to schema 2 for the RB extension
dom_dec_plot_sim_data.m
dom_dec_RB_extension_eigenbasis.m
dom_dec_RB_extension_PCA_fixspace.m
dom_dec_rb_reconstruction.m
dom_dec_rb_simulation.m	Realization of the iterative schema for RB methods according to my diploma thesis
dom_dec_set_mu.m	Trivial function setting the parameter in model and model.base_model
dom_dec_set_rb_in_detailed_data.m
► ellipt_compliant
ellipt_compliant_detailed_simulation.m
ellipt_compliant_gen_model_data.m
ellipt_compliant_plot_sim_data.m
get_triangle_midpoints.m	Computes triangle midpoints for given mesh data
RBcheck.m	=> Ergebnis RB' * G * RB = eye; check result
thermalblock_output_function.m
► hp
► demos
hp_demo.m	Demo script for hp-approach routine
hp_demo_elliptic.m	Demo script for hp-approach routine using a elliptic problem
hp_demo_errordistance.m	Demo script for hp-approach routine with error distance function
error_distance.m
euclidean_distance.m
h_refinement.m
h_refinement_err_ext.m
hp_elliptic.m
hp_gen_model.m
hp_gen_model_elliptic.m
hp_plot_domain_full.m
hp_plot_domains.m
hp_plot_error.m	Zeichnet ein Fehlergebiet - nur bei 2d Paramtern möglich
hp_plot_number.m
hp_plot_sim_data.m
hp_rb_generation.m
hp_simulation.m
leaf.m
► interface
gen_detailed_model.m	Generates an IDetailedModel instance from a description structure
gen_models.m	Generates an IDetailedModel and an IReducedModel instance from description structures
gen_reduced_model.m	Generates an IReducedModel instance from a description structure
IDetailedData.m
IDetailedModel.m
IModel.m
IReducedData.m
IReducedModel.m
► lin_ds
estimate_lin_ds_bound_constants.m
lin_ds_detailed_simulation.m
lin_ds_detailed_simulation_euler_forward.m
lin_ds_estimate_bound_constants.m
lin_ds_from_lin_evol_gen_model_data.m
lin_ds_from_lin_evol_model.m
lin_ds_from_lin_evol_plot_sim_data.m
lin_ds_gen_detailed_data.m
lin_ds_gen_model_data.m
lin_ds_gen_reduced_data.m
lin_ds_model_default.m
lin_ds_plot_detailed_data.m
lin_ds_plot_sim_data.m
lin_ds_plot_sim_data_output.m
lin_ds_plot_sim_data_state.m
lin_ds_rb_reconstruction.m
lin_ds_rb_simulation.m
lin_ds_rb_simulation_euler_forward.m
lin_ds_reduced_data_subset.m
lin_ds_set_rb_in_detailed_data.m
► lin_evol
dune_get_rb_size.m
dune_lin_evol_gen_model_data.m
dune_lin_evol_rb_operators.m
dune_lin_evol_rb_recons_and_compare.m
dune_lin_evol_rb_reconstruction.m
lin_evol_detailed_simulation.m
lin_evol_gen_detailed_data.m
lin_evol_gen_model_data.m
lin_evol_gen_reduced_data.m
lin_evol_model_default.m
lin_evol_plot_detailed_data.m
lin_evol_plot_sim_data.m
lin_evol_rb_operators.m
lin_evol_rb_reconstruction.m
lin_evol_rb_simulation.m
lin_evol_reduced_data_subset.m	Method which modifies reduced_data, which is the data, that will be passed to the online-simulation algorithm
► lin_evol_opt
► convdiff
calculate_gamma_const.m
calculate_Lipschitz_const.m
convection_diffusion_fv_output_opt_script.m
dummy_constant.m
experiments1.m
experiments2.m
lin_evol_opt_output_time_independent.m
lin_evol_opt_output_time_integrated.m
my_get_gamma_H_constant.m
my_get_L_H_constant.m
nachbesserungsskript34.m	Nachbersserungsskript
nachbesserungsskript45.m	Nachbersserungsskript
simplex_nonlinear.m
zeittest.m
► separate_bases
experiments_comparison.m	Classic basis generation
experiments_comparison_mixed.m	Mixed basis generation
experiments_comparison_separate.m	Separate basis generation
experiments_run.m
experiments_run2.m	Params.mu_ranges = {[0.799, 0.8],[0.699, 0.7]};
lin_evol_opt_gen_detailed_data_separate_bases.m	Lin_evol_opt_gen_detailed_data_separate_bases(model, model_data)
lin_evol_opt_gen_detailed_data_separate_bases_parallel.m	Lin_evol_opt_gen_detailed_data_separate_bases(model, model_data)
lin_evol_opt_gen_reduced_data_separate_bases.m
lin_evol_opt_get_rb_from_detailed_data_separate_bases.m	Lin_evol_opt_get_rb_from_detailed_data_separate_bases(detailed_data,p);
lin_evol_opt_get_rb_size.m
lin_evol_opt_rb_derivative_simulation_separate_bases.m
lin_evol_opt_rb_derivative_simulation_separate_bases_tpart.m
lin_evol_opt_rb_init_values_separate_bases.m
lin_evol_opt_rb_operators_separate_bases.m
lin_evol_opt_reduced_data_subset_separate_bases.m	Method which modifies reduced_data, which is the data, that will be passed to the online-simulation algorithm
lin_evol_opt_set_rb_in_detailed_data_separate_bases.m	Lin_evol_opt_set_rb_in_detailed_data_separate_bases(detailed_data,RB,derivative_indx)
blowup_cell.m
blowup_matrix.m
calculate_derivative.m	Function calculates the derivative of the function U using detailed simulation
detailed_grid_search.m
experiments_am106.m	Experiments_am106
fv_operators_implicit_explicit_without_timestep.m
get_bound_to_optimize.m
get_derivative_err_est_norm.m
get_dofs_from_sim_data_for_sensitivity_extension.m
get_estimator_from_sim_data_mixed.m
get_estimator_from_sim_data_mixed_relative.m
get_mu_to_optimize.m
gradient_opt.m
gradient_opt_non_iter_err.m
grid_search.m
lin_evol_animate_solution.m
lin_evol_get_output.m	Lin_evol_get_output_detailed(model, varargin)
lin_evol_get_output_detailed.m	Lin_evol_get_output_detailed(model, varargin)
lin_evol_opt_calculate_average_base_size.m
lin_evol_opt_detailed_der_simulation.m
lin_evol_opt_detailed_der_simulation_old.m
lin_evol_opt_detailed_der_simulation_t_part.m
lin_evol_opt_detailed_simulation.m
lin_evol_opt_fd_derivative.m
lin_evol_opt_fd_fd_Hessian.m
lin_evol_opt_fd_fd_second_derivative.m
lin_evol_opt_fd_Hessian.m
lin_evol_opt_fd_Hessian_der.m
lin_evol_opt_fd_second_derivative.m
lin_evol_opt_gen_reduced_data.m
lin_evol_opt_get_Jacobian.m
lin_evol_opt_rb_fd_derivative.m
lin_evol_opt_rb_operators.m
lin_evol_opt_rb_simulation.m
lin_evol_opt_reduced_data_subset.m	Method which modifies reduced_data, which is the data, that will be passed to the online-simulation algorithm
lin_evol_rb_derivative_operators_coefficients.m
lin_evol_rb_derivative_simulation.m
lin_evol_rb_derivative_simulation_t_part.m
load_opt_data.m	Model = load_opt_data(filestr, model)
plot_data_surf.m
plot_PM.m
rb_derivative_init_values_coefficients.m
rb_derivative_simulation.m
rb_gui_lin_evol_opt.m	Try to put advection_fv_output_opt in a gui
RB_init_data_basis_lin_evol_opt.m
rb_reconstruction_derivative.m
rb_reconstruction_dictionary.m
save_opt_data.m
script_detailled_simulation.m	Detailed_simulation_refined
script_detailled_simulation_cone1_ref5.m	Detailed_simulation_refined
script_detailled_simulation_cone2_ref5.m	Detailed_simulation_refined
script_detailled_simulation_cone4_ref5.m	Detailed_simulation_refined
set_mu_lin_evol_opt.m
set_mu_to_optimize.m	Funcion sets the parameters that are to be optimized to the values given by x Also usable for optimization: function sets the parameters to x+t*d if t and d are given
setfield_in_model_and_base_model.m
stepsize_armijo.m
stepsize_dichotomie.m
stepsize_exponential.m
stepsize_quotient.m	Function [model, t_opt, output] = stepsize_quotient(model, model_data, output, x, d, quot_step)
stepsize_wolfe_powell.m
test_compare_old_new_detailed_sim.m	Script compares old and new detailed simulations
test_compare_real_error_estimated_error.m	% model initialisation
test_derivative_lin_evol_opt.m
test_det_der_sim_dummy.m	Only needed for testing script_detailled_simulation CREATE DUMMY FILE FOR TESTING!!!!
testing_script_lin_evol_opt_implicit_operators.m	Testing_script_lin_evol_opt_implicit_operators
testing_script_rb_operators_decomp.m	Testskript für lin_evol_opt_rb_operators zum Testen der einzelnen decomp_modes
► lin_evol_primdual
lin_evol_detailed_simulation_primal_dual.m	Sim_data = lin_evol_detailed_simulation_primal_dual(model, model_data)
lin_evol_gen_reduced_data_primal_dual.m	Reduced_data = lin_evol_gen_reduced_data_primal_dual(model, detailed_data)
lin_evol_primal_dual_gen_detailed_data.m	Detailed_data = lin_evol_primal_dual_gen_detailed_data(model, model_data)
lin_evol_primal_dual_gen_reduced_data.m	Reduced_data = lin_evol_primal_dual_gen_reduced_data(model, detailed_data)
lin_evol_primal_dual_rb_simulation.m	Simulation_data = lin_evol_primal_dual_rb_simulation(model, reduced_data)
lin_evol_rb_operators_primal_dual.m	[LL_I, LL_E, bb, K_II, K_IE, K_EE, m_I, m_E, m, K_IdId, K_IdE, LL_I_correct, LL_E_correct, bb_correct, scm_offline_data] = ... lin_evol_rb_operators_primal_dual(model, detailed_data)
lin_evol_rb_simulation_primal_dual.m	Simulation_data = lin_evol_rb_simulation_primal_dual(model, reduced_data)
lin_evol_split_detailed_data.m	[detailed_data_primal, detailed_data_dual] = lin_evol_split_detailed_data(detailed_data)
lin_evol_split_reduced_data.m	[reduced_data_primal_improved, reduced_data_dual] = lin_evol_split_reduced_data(reduced_data)
rb_init_values_primal_dual.m	A0 = rb_init_values_primal_dual(model, detailed_data)
► lin_stat
lin_stat_detailed_simulation.m
lin_stat_gen_detailed_data.m
lin_stat_gen_model_data.m
lin_stat_gen_reduced_data.m
lin_stat_model_default.m
lin_stat_plot_detailed_data.m
lin_stat_plot_sim_data.m
lin_stat_rb_reconstruction.m
lin_stat_rb_simulation.m
lin_stat_reduced_data_subset.m	Method which modifies reduced_data, which is the data, that will be passed to the online-simulation algorithm
lin_stat_set_dofs_in_sim_data.m	Routine setting dofs in sim_data
lin_stat_set_rb_in_detailed_data.m
► nonlin_evol
nonlin_evol_detailed_ei_rb_proj_simulation.m
nonlin_evol_detailed_ei_simulation.m
nonlin_evol_detailed_local_ei_simulation.m
nonlin_evol_detailed_rb_proj_simulation.m
nonlin_evol_detailed_simulation.m
nonlin_evol_gen_detailed_data.m	Prepares detailed_data structure with high dimensional like reduced basis functions
nonlin_evol_gen_model_data.m
nonlin_evol_gen_reduced_data.m	Method which produces reduced_data, which is the data, that will be passed to an online-algorithm
nonlin_evol_model_default.m
nonlin_evol_plot_detailed_data.m	Plot the reduced basis, the colateral reduced basis, the interpolation points and the maximum error decrease during CRB generation
nonlin_evol_plot_sim_data.m
nonlin_evol_rb_operators.m
nonlin_evol_rb_simulation.m
nonlin_evol_reduced_data_subset.m	Method which modifies reduced_data, which is the data, that will be passed to the online-simulation algorithm
► p_part
calculate_test_estimator.m
clean_up_part_detailed_data.m	Function deleting all expensive data from parts of detailed_data which are no leaf elements
p_part_gen_detailed_data.m
p_part_gen_reduced_data.m
p_part_model.m
p_part_rb_reconstruction.m
p_part_rb_simulation.m
plot_error_domain.m
prepare_animation.m
set_mu_in_model_and_base_model.m
► riccati
riccati_assemble_system_matrices.m	Model_data)
riccati_cost_functional.m	[J,lQ] = riccati_cost_functional(model, model_data, sim)
riccati_detailed_simulation.m	Sim_data = riccati_detailed_simulation(model, model_data)
riccati_gamma.m	This function calculates gamma. Simdata must be a high dimensional solution
riccati_gen_detailed_data.m
riccati_gen_model_data.m	RICCATI_GEN_MODEL_DATA
riccati_gen_reduced_data.m	Reduced_data = riccati_gen_reduced(model, detailed_data)
riccati_kernel_functions.m	Return the kernel for the interpolation between the gamma values TODO: Maybe move to a class in RB matlab..
riccati_low_rank_factor_errors.m	Calculate the projection error for all columns in the low rank factor in Z for the given basis V
riccati_model_default.m	This model is the general model for the riccati type models for the linear dynamic system:
riccati_rb_gamma.m	[gamma] = riccati_rb_gamma(model, reduced_data, sim_data)
riccati_rb_reconstruction.m	Perform a reconstruction of the full dimensional solution
riccati_rb_simulation.m	Sim_data = riccati_rb_simulation(model, reduced_data) This function performs a reduced basis simulation. The solution to the reduced ARE is calculated by calling the function "care"
riccati_reduced_cost_functional.m	[Jred, lrQ] = riccati_reduced_cost_functional(model, reduced_data, varargin)
riccati_residual_norm.m
riccati_stability_constant.m	This function can be used to calculate the stability constant for the model
riccati_validity_bound.m	Rbsim)
► stokes
stokes_compute_drag_and_lift.m	Drag and lift coefficients are computed via volume integrals
stokes_detailed_simulation.m	Performs a detailed simulation of a (Navier-)stokes problem
stokes_enrich_reduced_data.m
stokes_gen_model_data.m
stokes_gen_reduced_data.m
stokes_infsup_constant.m
stokes_infsup_rbf_interpolant.m
stokes_model_default.m
stokes_plot_sim_data.m	Visualizes solution of stokes problem
stokes_rb_reconstruction.m
stokes_rb_simulation.m
stokes_rb_supremizer_extension.m
stokes_reduced_data_subset.m
stokes_sobolev_embedding_constant.m
StokesReducedDataWrapper.m
► t_part
lin_evol_rb_simulation_t_part.m
refine_t_part.m
t_part_detailed_simulation.m
t_part_gen_detailed_data.m
t_part_gen_model_data.m
t_part_gen_reduced_data.m
t_part_initial_cond_POD.m
t_part_model.m
t_part_rb_reconstruction.m	Sim_data)
t_part_rb_simulation.m
t_part_reduced_data_subset.m	Reduced_data)
t_part_script.m
► vi
vi_detailed_simulation.m
vi_gen_detailed_data.m
vi_gen_model_data.m
vi_gen_reduced_data.m
vi_plot_detailed_data.m
vi_plot_sim_data.m
vi_rb_reconstruction.m
vi_rb_simulation.m
vi_reduced_data_subset.m
► scripts
► steps
step10_plot_trajectories.m	Script generating a tikz graphic showing trajectories for certain selected parameters
step1_detailed_simulation.m	Script performing a single detailed simulation and plotting it
step2_empirical_interpolation.m	Script constructing a collateral reduced basis space for localized space operators
step3_detailed_ei_simulation.m	Script performing a detailed simulation with empirical interpolated operators comparing the result with a regular detailed simulation
step4_dummy_reduced_basis.m	Script constructing a reduced basis from a single trajectory and performing a detailed simulation where the data is projected on the dummy reduced basis space after each time step
step5_rb_generation.m	Script constructing a reduced basis space
step6_demo_rb_gui.m	Script comparing time for a reduced and a detailed simulation and starting the demonstration GUI
step7_error_landscape.m	Script generating error landscapes by computing the true error of reduced simulations vs. detailed simulations for given test parameters over differing basis sizes
step8_estimator_landscape.m	Script generating landscapes plot data by computing the error estimator of reduced simulations for given test parameters over differing basis sizes
addpaths_changed.m	Script which allows to use a second rbmatlab branch overloading an existing one, e.g. for temporary changed, patches, laptop version, etc
advection_fv_output.m	Small script implementing a simple advection example for producing matrices to be used in the RB-DS framework Discretization with FV Functions
advection_fv_output_optimization.m	Script using the advection_fv_output_opt model to demonstrate optimization using a reduced basis
buckley_leverett.m	Small script demonstrating a buckley leverett problem discretization and RB model reduction
burgers_examples.m
compute_gdl_velocity2.m	Script computing a velocity field for simple gdl model by solving a laplace problem with suitable boundary conditions
convdiff.m	Small script demonstrating the convdiff example from the M2AN Paper, that is also implemented in Dune. Later it will be possible to use the Dune implementation through a mex interface
convdiff_new.m	Small script demonstrating the convdiff example from the M2AN Paper, that is also implemented in Dune. Later it will be possible to use the Dune implementation through a mex interface
cpde2016.m	CPDE2016 This function reproduces all the results from the CPDE paper
demos_parabolic.m
dom_dec_final.m	Script generating figures of the paper "An Iterative Domain Decomposition Procedure for The Reduced Basis Method"
dune_laplace.m
duneconvdiff.m	Small script demonstrating the convdiff example from the M2AN Paper, that is also implemented in Dune. Later it will be possible to use the Dune implementation through a mex interface. Martin Drohmann 06.05.2009 based on burgers_fv.m by Bernard Haasdonk 14.8.2007
elastic_membrane.m
fem2_poisson.m
fem_poisson.m
follicle_model_BT.m
follicle_rect_experiments.m	Experiments with the model of the human follicle growth
gamm2013_exp.m
get_nonlin_evol_params.m	Small script setting basic params structure for nonlin_evol problem
hmm_micro_local.m
loop_demo_rb_gui.m
newton.m	Small script demonstrating a buckley leverett problem discretization and RB model reduction
nonlin_symmetry.m	File performing RB steps for nonlin_symmetry model
nonlin_symmetry_oop.m	Small script demonstrating the burgers equation with explicit fv discretization and RB model reduction example is meant to demonstrate automatic symmetry detection by the algorithm
oscillator_experiments.m
porsche_script.m
quadr_nonlin_script.m
rb_tutorial.m
rb_tutorial_buggy.m
rb_tutorial_standalone.m
rbf_elliptic.m	Function for meshless collocation of fem-problem. step can be used to choose several cases. step=1 does not need to be called directly but is used by the other steps. So call step=2, 3 and change options there
richards_fv.m	Small script demonstrating the richards equation with explicit fv discretization and RB model reduction Bernard Haasdonk 14.8.2007
riemann_burgers.m	Script demonstrating the burgers equation with explicit fv discretization, empirical interpolation and RB model reduction
simtech_animation.m	Small script performing animation, that can be captured
test_rb_burgers_fv.m	Load(burgers_fv_detailed_interpol.mat) disp(example of demo_nonlin_symmetry:)
thermalblock.m	Thermalblock example
ulm_fuelcell_gdl.m	Small script demonstrating RB-approach for the fuelcell-gdl with the simtech image initial data
vi_rb.m
weak_strong_POD_Greedy_comp.m	Script comparing weak and strong POD-Greedy on lin_evol default example