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AbstractModel.Model Class Referenceabstract

Detailed Description

MODEL Abstract model class.

This class represents abstract RB problems that define common interfaces.

Andreas Schmidt, 2016

Definition at line 18 of file Model.m.

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Public Member Functions

virtual function dsim = detailed_simulation (ModelData model_data)
 DETAILED_SIMULATION The function DETAILED_SIMULATION returns an instance of SimData and. More...
 
virtual function rsim = rb_simulation (IReducedData reduced_data)
 REDUCED_SIMULATION This function should return a reduced simulation of type RBSimData. More...
 
function ModelData
model_data = 
gen_model_data ()
 GEN_MODEL_DATA Use this function in order to create a class of type ModelData which contains all the large-scale model data such as the discretized operators. More...
 
function IDetailedData
detailed_data = 
gen_detailed_data (ModelData model_data)
 GEN_DETAILED_DATA Call the basis generation algorithm. More...
 
function IReducedData
reduced_data = 
gen_reduced_data (IDetailedData detailed_data)
 GEN_REDUCED_DATA Get the reduced data structures. More...
 
function pt = problem_type ()
 PROBLEM_TYPE Use this function to determine the problem type. So consider overwriting it if necessary! TODO: implement a smart interface that automatically generates the correct. More...
 
function mu = get_mu ()
 Get the parameter values. More...
 
function this = set_mu (mu)
 Set the parameter values. More...
 

Public Attributes

 mu
 
 mu_names
 
 mu_ranges
 

Member Function Documentation

function sim_data = DARE.Model.detailed_simulation ( ModelData  model_data)
pure virtual

DETAILED_SIMULATION The function DETAILED_SIMULATION returns an instance of SimData and.

DETAILED_SIMULATION Perform a detailed simulation, i.e. a high-dimensional solve of the DARE.

sim_data = riccati_detailed_simulation(model, model_data)

Parameters
model_dataMatlab structure storing (possibly) high dimensional data needed by IDetailedModel.detailed_simulation().
Return values
dsimdsim

Calculate the full solution for a given problem. This function relies on the M.E.S.S. package from the MPI!

sim_data is a structure containing the following information Z ..................... The low rank factor, P = Z Z' time .................. Time for the solve

Andreas Schmidt, 2015

Parameters
model_dataMatlab structure storing (possibly) high dimensional data needed by IDetailedModel.detailed_simulation().
Return values
sim_datasim data
Required fields of model_data:
  • K_in —  K in
Generated fields of sim_data:
  • P —  P
  • Z —  Z
  • time —  time
  • K —  K
Parameters
model_dataMatlab structure storing (possibly) high dimensional data needed by IDetailedModel.detailed_simulation().
Return values
sim_datasim data
Generated fields of sim_data:
  • Z —  Z
  • P —  P
  • time —  time
  • K —  K

Definition at line 19 of file detailed_simulation.m.

function IDetailedData detailed_data = DARE.Model.gen_detailed_data ( ModelData  model_data)

GEN_DETAILED_DATA Call the basis generation algorithm.

GEN_DETAILED_DATA Wrapper for the generation of the detailed data.

Parameters
model_dataMatlab structure storing (possibly) high dimensional data needed by IDetailedModel.detailed_simulation().
Return values
detailed_datadetailed data

Definition at line 91 of file Model.m.

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function ModelData model_data = AbstractModel.Model.gen_model_data ( )

GEN_MODEL_DATA Use this function in order to create a class of type ModelData which contains all the large-scale model data such as the discretized operators.

Return values
model_datamodel data

Definition at line 77 of file Model.m.

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function IReducedData reduced_data = AbstractModel.Model.gen_reduced_data ( IDetailedData  detailed_data)

GEN_REDUCED_DATA Get the reduced data structures.

Parameters
detailed_dataobject defining the basis generation algorithm and storage for storing high dimensional data, i.e. dependent on dimension \(H\). This data is necessary for detailed simulations, construction of online matrices, reduced_data and reconstruction of reduced simulations.
Return values
reduced_datareduced data

Definition at line 107 of file Model.m.

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function mu = AbstractModel.Model.get_mu ( )

Get the parameter values.

Return values
mumu

Definition at line 151 of file Model.m.

function pt = AbstractModel.Model.problem_type ( )

PROBLEM_TYPE Use this function to determine the problem type. So consider overwriting it if necessary! TODO: implement a smart interface that automatically generates the correct.

Return values
ptpt

Definition at line 125 of file Model.m.

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function rbsim = DARE.Model.rb_simulation ( IReducedData  reduced_data)
pure virtual

REDUCED_SIMULATION This function should return a reduced simulation of type RBSimData.

RB_SIMULATION Perform a reduced simulation.

Parameters
reduced_dataan object constructing and storing all (low-dimensional) reduced matrices and vectors needed for reduced simulations.
Return values
rsimrsim

Andreas Schmidt, 2015

Parameters
reduced_dataan object constructing and storing all (low-dimensional) reduced matrices and vectors needed for reduced simulations.
Return values
rbsimrbsim
Required fields of reduced_data:
  • gamma_function —  gamma function
  • gamma_mode —  gamma mode
  • estim.normE —  estim.normE
  • estim.normEinv —  estim.normEinv
Generated fields of rbsim:
  • PN —  PN
  • time_sim —  time sim
  • time_residual —  time residual
  • residual —  residual
  • nresidual —  nresidual
  • nnresidual —  nnresidual
  • gamma —  gamma
  • time_gamma —  time gamma
  • L —  L
  • validity_crit —  validity crit
  • valid —  valid
  • error_estimate —  error estimate
  • stab_crit —  stab crit
  • stable —  stable
  • time_errorestim —  time errorestim
Andreas Schmidt, 2015
Parameters
reduced_dataan object constructing and storing all (low-dimensional) reduced matrices and vectors needed for reduced simulations.
Return values
rbsimrbsim
Required fields of reduced_data:
  • gamma_function —  gamma function
  • gamma_mode —  gamma mode
  • estim —  estim
  • RB_W —  RB W
Generated fields of rbsim:
  • PN —  PN
  • time_sim —  time sim
  • time_residual —  time residual
  • residual —  residual
  • nresidual —  nresidual
  • gamma —  gamma
  • time_gamma —  time gamma
  • time_closed_loop_norm —  time closed loop norm
  • validity_crit —  validity crit
  • valid —  valid
  • stab_crit —  stab crit
  • stable —  stable
  • closed_loop_stable —  closed loop stable
  • closed_loop_max_eig —  closed loop max eig
  • error_estimate —  error estimate
  • time_error_estim —  time error estim

Definition at line 19 of file rb_simulation.m.

function this = AbstractModel.Model.set_mu (   mu)

Set the parameter values.

Parameters
mumu
Return values
thisthis
Generated fields of this:
  • mu —  mu

Definition at line 162 of file Model.m.


The documentation for this class was generated from the following files: