Reference documentation for deal.II version Git 8a2af55 20180422 07:16:45 +0200

#include <deal.II/numerics/data_postprocessor.h>
Public Member Functions  
DataPostprocessorTensor (const std::string &name, const UpdateFlags update_flags)  
virtual std::vector< std::string >  get_names () const 
virtual std::vector< DataComponentInterpretation::DataComponentInterpretation >  get_data_component_interpretation () const 
virtual UpdateFlags  get_needed_update_flags () const 
Public Member Functions inherited from DataPostprocessor< dim >  
virtual  ~DataPostprocessor ()=default 
virtual void  evaluate_scalar_field (const DataPostprocessorInputs::Scalar< dim > &input_data, std::vector< Vector< double > > &computed_quantities) const 
virtual void  evaluate_vector_field (const DataPostprocessorInputs::Vector< dim > &input_data, std::vector< Vector< double > > &computed_quantities) const 
Public Member Functions inherited from Subscriptor  
Subscriptor ()  
Subscriptor (const Subscriptor &)  
Subscriptor (Subscriptor &&) noexcept  
virtual  ~Subscriptor () 
Subscriptor &  operator= (const Subscriptor &) 
Subscriptor &  operator= (Subscriptor &&) noexcept 
void  subscribe (const char *identifier=nullptr) const 
void  unsubscribe (const char *identifier=nullptr) const 
unsigned int  n_subscriptions () const 
void  list_subscribers () const 
template<class Archive >  
void  serialize (Archive &ar, const unsigned int version) 
Private Attributes  
const std::string  name 
Additional Inherited Members  
Static Public Member Functions inherited from Subscriptor  
static::ExceptionBase &  ExcInUse (int arg1, char *arg2, std::string &arg3) 
static::ExceptionBase &  ExcNoSubscriber (char *arg1, char *arg2) 
This class provides a simpler interface to the functionality offered by the DataPostprocessor class in case one wants to compute only a single tensor quantity (defined as having exactly dim*dim
components) from the finite element field passed to the DataOut class.
For this case, we would like to output all of these components as parts of a tensorvalued quantity. Unfortunately, the various backends that write DataOut data in graphical file formats (see the DataOutBase namespace for what formats can be written) do not support tensor data at the current time. In fact, neither does the DataComponentInterpretation namespace that provides semantic information how individual components of graphical data should be interpreted. Nevertheless, like DataPostprocessorScalar and DataPostprocessorVector, this class helps with setting up what the get_names() and get_needed_update_flags() functions required by the DataPostprocessor base class should return, and so the current class implements these based on information that the constructor of the current class receives from further derived classes.
(In order to visualize this collection of scalar fields that, together, are then supposed to be interpreted as a tensor, one has to (i) use a visualization program that can visualize tensors, and (ii) teach it how to recombine the scalar fields into tensors. In the case of Visit – see https://wci.llnl.gov/simulation/computercodes/visit/ – this is done by creating a new "Expression": in essence, one creates a variable, say "grad_u", that is tensorvalued and whose value is given by the expression {{grad_u_xx,grad_u_xy}, {grad_u_yx, grad_u_yy}}
, where the referenced variables are the names of scalar fields that, here, are produced by the example below. Visit is then able to visualize this "new" variable as a tensor.)
All derived classes have to do is implement a constructor and overload either DataPostprocessor::evaluate_scalar_field() or DataPostprocessor::evaluate_vector_field().
An example of how the closely related class DataPostprocessorScalar is used can be found in step29. An example of how the DataPostprocessorVector class can be used is found in the documentation of that class.
A common example of what one wants to do with postprocessors is to visualize not just the value of the solution, but the gradient. This class is meant for tensorvalued outputs, so we will start with a vectorvalued solution: the displacement field of step8. The gradient is a rank2 tensor (with exactly dim*dim
components), so the current class fits the bill to produce the gradient through postprocessing. Then, the following code snippet implements everything you need to have to visualize the gradient:
The only tricky part in this piece of code is how to sort the dim*dim
elements of the strain tensor into the one vector of computed output quantities – in other words, how to unroll the elements of the tensor into the vector. This is facilitated by the Tensor::component_to_unrolled_index() function that takes a pair of indices that specify a particular element of the tensor and returns a vector index that is then used in the code above to fill the computed_quantities
array.
The last thing that is necessary is to add another output to the call of DataOut::add_vector() in the output_results()
function of the Step8
class of that example program. The corresponding code snippet would then look like this:
This leads to the following output for the displacement field (i.e., the solution) and the gradients (you may want to compare with the solution shown in the results section of step8; the current data is generated on a uniform mesh for simplicity):
These pictures show an ellipse representing the gradient tensor at, on average, every tenth mesh point. You may want to read through the documentation of the Visit visualization program (see https://wci.llnl.gov/simulation/computercodes/visit/) for an interpretation of how exactly tensors are visualizated.
In elasticity, one is often interested not in the gradient of the displacement, but in the "strain", i.e., the symmetrized version of the gradient \(\varepsilon=\frac 12 (\nabla u + \nabla u^T)\). This is easily facilitated with the following minor modification:
Using this class in step8 leads to the following visualization:
Given how easy it is to output the strain, it would also not be very complicated to write a postprocessor that computes the stress in the solution field as the stress is easily computed from the strain by multiplication with either the strainstress tensor or, in simple cases, the Lamé constants.
Definition at line 1009 of file data_postprocessor.h.
DataPostprocessorTensor< dim >::DataPostprocessorTensor  (  const std::string &  name, 
const UpdateFlags  update_flags  
) 
Constructor. Take the name of the single vector variable computed by classes derived from the current one, as well as the update flags necessary to compute this quantity.
name  The name by which the vector variable computed by this class should be made available in graphical output files. 
update_flags  This has to be a combination of update_values , update_gradients and update_hessians . If the DataPostprocessor is to be used in combination with DataOutFaces, you may also ask for a update of normals via the update_normal_vectors flag. 
Definition at line 152 of file data_postprocessor.cc.

virtual 
Return the vector of strings describing the names of the computed quantities. Given the purpose of this class, this is a vector with dim entries all equal to the name given to the constructor.
Implements DataPostprocessor< dim >.
Definition at line 164 of file data_postprocessor.cc.

virtual 
This function returns information about how the individual components of output files that consist of more than one data set are to be interpreted. Since the current class is meant to be used for a single vector result variable, the returned value is obviously DataComponentInterpretation::component_is_part repeated dim times.
Reimplemented from DataPostprocessor< dim >.
Definition at line 182 of file data_postprocessor.cc.

virtual 
Return which data has to be provided to compute the derived quantities. The flags returned here are the ones passed to the constructor of this class.
Implements DataPostprocessor< dim >.
Definition at line 193 of file data_postprocessor.cc.

private 
Copies of the two arguments given to the constructor of this class.
Definition at line 1056 of file data_postprocessor.h.