Reference documentation for deal.II version Git 78150d9107 2021-02-24 10:44:07 -0700
TensorFunctionParser< rank, dim, Number > Class Template Reference

#include <deal.II/base/tensor_function_parser.h>

Inheritance diagram for TensorFunctionParser< rank, dim, Number >:
[legend]

## Public Types

using ConstMap = std::map< std::string, double >

using value_type = Tensor< rank, dim, Number >

using gradient_type = Tensor< rank+1, dim, Number >

using time_type = typename FunctionTime< typename numbers::NumberTraits< Number >::real_type >::time_type

## Public Member Functions

TensorFunctionParser (const double initial_time=0.0)

TensorFunctionParser (const std::string &expression, const std::string &constants="", const std::string &variable_names=default_variable_names()+",t")

TensorFunctionParser (const TensorFunctionParser &)=delete

TensorFunctionParser (TensorFunctionParser &&)=delete

virtual ~TensorFunctionParser () override

TensorFunctionParseroperator= (const TensorFunctionParser &)=delete

TensorFunctionParseroperator= (TensorFunctionParser &&)=delete

void initialize (const std::string &vars, const std::vector< std::string > &expressions, const ConstMap &constants, const bool time_dependent=false)

void initialize (const std::string &vars, const std::string &expression, const ConstMap &constants, const bool time_dependent=false)

virtual Tensor< rank, dim, Number > value (const Point< dim > &p) const override

virtual void value_list (const std::vector< Point< dim >> &p, std::vector< Tensor< rank, dim, Number >> &values) const override

const std::vector< std::string > & get_expressions () const

virtual void value_list (const std::vector< Point< dim >> &points, std::vector< value_type > &values) const

numbers::NumberTraits< Number >::real_type get_time () const

virtual void set_time (const numbers::NumberTraits< Number >::real_type new_time)

virtual void advance_time (const numbers::NumberTraits< Number >::real_type delta_t)

template<class Archive >
void serialize (Archive &ar, const unsigned int version)

Subscriptor functionality

Classes derived from Subscriptor provide a facility to subscribe to this object. This is mostly used by the SmartPointer class.

void subscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

void unsubscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

unsigned int n_subscriptions () const

template<typename StreamType >
void list_subscribers (StreamType &stream) const

void list_subscribers () const

## Static Public Member Functions

static std::string default_variable_names ()

static ::ExceptionBaseExcParseError (int arg1, std::string arg2)

static ::ExceptionBaseExcInvalidExpressionSize (int arg1, int arg2)

static ::ExceptionBaseExcInUse (int arg1, std::string arg2, std::string arg3)

static ::ExceptionBaseExcNoSubscriber (std::string arg1, std::string arg2)

## Private Member Functions

void init_muparser () const

## Private Attributes

std::map< std::string, doubleconstants

std::vector< std::string > var_names

std::vector< std::string > expressions

bool initialized

unsigned int n_vars

unsigned int n_components

## Detailed Description

### template<int rank, int dim, typename Number = double> class TensorFunctionParser< rank, dim, Number >

This class implements a tensor function object that gets its value by parsing a string describing this function. It is a wrapper class for the muparser library (see http://muparser.beltoforion.de/). This class is essentially an extension of the FunctionParser class to read in a TensorFunction. The class reads in an expression of length dimrank (separated by a semicolon) where the components of the tensor function are filled according to the C++ convention (fastest index is the most right one).

Note
In contrast to the FunctionParser class the TensorFunctionParser class does not support automatic differentiation.

A minimal example for the usage of the class would be:

// set up time dependent tensor function:
const std::string variables = "x,y,t";
const std::string expression =
"exp(-t)*cos(x+y);-sin(pi*x*y-t);sin(pi*x*y-t);exp(t)*cos(x+y)";
std::map<std::string,double> constants;
constants["pi"] = numbers::PI;
// TensorFunctionParser with 2+1 variables (space + time) in 2D of rank 2.
// It is necessary to tell the parser that there is an additional variable
// to be taken into account (t).
tfp.initialize(variables,
expression,
constants,
true); // flag for time dependence
// Point at which we want to evaluate the function
Point<2> point(0.0, 1.0);
// evaluate the expression at 'point':
double result = tfp.value(point);
deallog << "Function '" << expression << "'"
<< " @ " << point
<< " is: "
<< std::endl
<< result[0][0] << " " << result[0][1] << std::endl
<< result[1][0] << " " << result[1][1]
<< std::endl;

This class overloads the virtual method value() and value_list() of the TensorFunction base class with the byte compiled versions of the expressions given to the initialize() methods. Note that the class will not work unless you first call the initialize() method that accepts the text description of the function as an argument (among other things).

The syntax to describe a function follows usual programming practice, and is explained in detail at the homepage of the underlying muparser library at http://muparser.beltoforion.de/ .

Vector-valued functions can either be declared using strings where the function components are separated by semicolons, or using a vector of strings each defining one vector component.

Definition at line 111 of file tensor_function_parser.h.

## ◆ ConstMap

template<int rank, int dim, typename Number = double>
 using TensorFunctionParser< rank, dim, Number >::ConstMap = std::map

Type for the constant map. Used by the initialize() method.

Definition at line 169 of file tensor_function_parser.h.

## ◆ value_type

template<int rank, int dim, typename Number = double>
 using TensorFunction< rank, dim, Number >::value_type = Tensor
inherited

Alias for the return types of the value function.

Definition at line 64 of file tensor_function.h.

template<int rank, int dim, typename Number = double>
 using TensorFunction< rank, dim, Number >::gradient_type = Tensor
inherited

Alias for the return types of the gradient functions.

Definition at line 69 of file tensor_function.h.

## ◆ time_type

template<int rank, int dim, typename Number = double>
 using TensorFunction< rank, dim, Number >::time_type = typename FunctionTime< typename numbers::NumberTraits::real_type>::time_type
inherited

The scalar-valued real type used for representing time.

Definition at line 75 of file tensor_function.h.

## ◆ TensorFunctionParser() [1/4]

template<int rank, int dim, typename Number >
 TensorFunctionParser< rank, dim, Number >::TensorFunctionParser ( const double initial_time = 0.0 )

Standard constructor. Only set initial time. This object needs to be initialized with the initialize() method before you can use it. If an attempt to use this function is made before the initialize() method has been called, then an exception is thrown.

Definition at line 45 of file tensor_function_parser.cc.

## ◆ TensorFunctionParser() [2/4]

template<int rank, int dim, typename Number >
 TensorFunctionParser< rank, dim, Number >::TensorFunctionParser ( const std::string & expression, const std::string & constants = "", const std::string & variable_names = default_variable_names() + ",t" )

Constructor for parsed functions. This object needs to be initialized with the initialize() method before you can use it. If an attempt to use this function is made before the initialize() method has been called, then an exception is thrown. Takes a semicolon separated list of expressions (one for each component of the tensor function), an optional comma-separated list of constants.

Definition at line 55 of file tensor_function_parser.cc.

## ◆ TensorFunctionParser() [3/4]

template<int rank, int dim, typename Number = double>
 TensorFunctionParser< rank, dim, Number >::TensorFunctionParser ( const TensorFunctionParser< rank, dim, Number > & )
delete

Copy constructor. Objects of this type can not be copied, and consequently this constructor is deleted.

## ◆ TensorFunctionParser() [4/4]

template<int rank, int dim, typename Number = double>
 TensorFunctionParser< rank, dim, Number >::TensorFunctionParser ( TensorFunctionParser< rank, dim, Number > && )
delete

Move constructor. Objects of this type can not be moved, and consequently this constructor is deleted.

## ◆ ~TensorFunctionParser()

template<int rank, int dim, typename Number >
 TensorFunctionParser< rank, dim, Number >::~TensorFunctionParser ( )
overridevirtualdefault

Destructor.

## ◆ operator=() [1/2]

template<int rank, int dim, typename Number = double>
 TensorFunctionParser& TensorFunctionParser< rank, dim, Number >::operator= ( const TensorFunctionParser< rank, dim, Number > & )
delete

Copy operator. Objects of this type can not be copied, and consequently this operator is deleted.

## ◆ operator=() [2/2]

template<int rank, int dim, typename Number = double>
 TensorFunctionParser& TensorFunctionParser< rank, dim, Number >::operator= ( TensorFunctionParser< rank, dim, Number > && )
delete

Move operator. Objects of this type can not be moved, and consequently this operator is deleted.

## ◆ initialize() [1/2]

template<int rank, int dim, typename Number >
 void TensorFunctionParser< rank, dim, Number >::initialize ( const std::string & vars, const std::vector< std::string > & expressions, const ConstMap & constants, const bool time_dependent = false )

Initialize the tensor function. This method accepts the following parameters:

Parameters
 [in] vars A string with the variables that will be used by the expressions to be evaluated. Note that the variables can have any name (of course different from the function names defined above!), but the order IS important. The first variable will correspond to the first component of the point in which the function is evaluated, the second variable to the second component and so forth. If this function is also time dependent, then it is necessary to specify it by setting the time_dependent parameter to true. An exception is thrown if the number of variables specified here is different from dim (if this function is not time-dependent) or from dim+1 (if it is time-dependent). [in] expressions A vector of strings containing the expressions that will be byte compiled by the internal parser (TensorFunctionParser). Note that the size of this vector must match exactly the number of components of the TensorFunctionParser, as declared in the constructor. If this is not the case, an exception is thrown. [in] constants A map of constants used to pass any necessary constant that we want to specify in our expressions (in the example above the number pi). An expression is valid if and only if it contains only defined variables and defined constants (other than the functions specified above). If a constant is given whose name is not valid (eg: constants["sin"] = 1.5;) an exception is thrown. [in] time_dependent If this is a time dependent function, then the last variable declared in vars is assumed to be the time variable, and this->get_time() is used to initialize it when evaluating the function. Naturally the number of variables parsed by the initialize() method in this case is dim+1. The value of this parameter defaults to false, i.e. do not consider time.

Definition at line 91 of file tensor_function_parser.cc.

## ◆ initialize() [2/2]

template<int rank, int dim, typename Number >
 void TensorFunctionParser< rank, dim, Number >::initialize ( const std::string & vars, const std::string & expression, const ConstMap & constants, const bool time_dependent = false )

Initialize the function. Same as above, but accepts a string rather than a vector of strings. If this is a vector valued function, its components are expected to be separated by a semicolon. An exception is thrown if this method is called and the number of components successfully parsed does not match the number of components of the base function.

Definition at line 272 of file tensor_function_parser.cc.

## ◆ default_variable_names()

template<int rank, int dim, typename Number >
 std::string TensorFunctionParser< rank, dim, Number >::default_variable_names ( )
static

A function that returns default names for variables, to be used in the first argument of the initialize() functions: it returns "x" in 1d, "x,y" in 2d, and "x,y,z" in 3d.

Definition at line 340 of file tensor_function_parser.h.

## ◆ value()

template<int rank, int dim, typename Number >
 Tensor< rank, dim, Number > TensorFunctionParser< rank, dim, Number >::value ( const Point< dim > & p ) const
overridevirtual

Return the value of the tensor function at the given point.

Reimplemented from TensorFunction< rank, dim, Number >.

Definition at line 288 of file tensor_function_parser.cc.

## ◆ value_list() [1/2]

template<int rank, int dim, typename Number >
 void TensorFunctionParser< rank, dim, Number >::value_list ( const std::vector< Point< dim >> & p, std::vector< Tensor< rank, dim, Number >> & values ) const
overridevirtual

Return the value of the tensor function at the given point.

Definition at line 333 of file tensor_function_parser.cc.

## ◆ get_expressions()

template<int rank, int dim, typename Number >
 const std::vector< std::string > & TensorFunctionParser< rank, dim, Number >::get_expressions ( ) const

Return an array of function expressions (one per component), used to initialize this function.

Definition at line 37 of file tensor_function_parser.cc.

## ◆ init_muparser()

template<int rank, int dim, typename Number >
 void TensorFunctionParser< rank, dim, Number >::init_muparser ( ) const
private

Initialize tfp and vars on the current thread. This function may only be called once per thread. A thread can test whether the function has already been called by testing whether 'tfp.get().size()==0' (not initialized) or >0 (already initialized).

Definition at line 146 of file tensor_function_parser.cc.

## ◆ value_list() [2/2]

template<int rank, int dim, typename Number = double>
 virtual void TensorFunction< rank, dim, Number >::value_list ( const std::vector< Point< dim >> & points, std::vector< value_type > & values ) const
virtualinherited

Set values to the point values of the function at the points. It is assumed that values already has the right size, i.e. the same size as the points array.

template<int rank, int dim, typename Number = double>
 virtual gradient_type TensorFunction< rank, dim, Number >::gradient ( const Point< dim > & p ) const
virtualinherited

Return the gradient of the function at the given point.

Reimplemented in ConstantTensorFunction< rank, dim, Number >.

template<int rank, int dim, typename Number = double>
 virtual void TensorFunction< rank, dim, Number >::gradient_list ( const std::vector< Point< dim >> & points, std::vector< gradient_type > & gradients ) const
virtualinherited

Set gradients to the gradients of the function at the points. It is assumed that values already has the right size, i.e. the same size as the points array.

## ◆ get_time()

 numbers::NumberTraits< Number >::real_type FunctionTime< numbers::NumberTraits< Number >::real_type >::get_time ( ) const
inherited

Return the value of the time variable.

## ◆ set_time()

 virtual void FunctionTime< numbers::NumberTraits< Number >::real_type >::set_time ( const numbers::NumberTraits< Number >::real_type new_time )
virtualinherited

Set the time to new_time, overwriting the old value.

 virtual void FunctionTime< numbers::NumberTraits< Number >::real_type >::advance_time ( const numbers::NumberTraits< Number >::real_type delta_t )
virtualinherited

Advance the time by the given time step delta_t.

## ◆ subscribe()

 void Subscriptor::subscribe ( std::atomic< bool > *const validity, const std::string & identifier = "" ) const
inherited

Subscribes a user of the object by storing the pointer validity. The subscriber may be identified by text supplied as identifier.

Definition at line 136 of file subscriptor.cc.

## ◆ unsubscribe()

 void Subscriptor::unsubscribe ( std::atomic< bool > *const validity, const std::string & identifier = "" ) const
inherited

Unsubscribes a user from the object.

Note
The identifier and the validity pointer must be the same as the one supplied to subscribe().

Definition at line 156 of file subscriptor.cc.

## ◆ n_subscriptions()

 unsigned int Subscriptor::n_subscriptions ( ) const
inlineinherited

Return the present number of subscriptions to this object. This allows to use this class for reference counted lifetime determination where the last one to unsubscribe also deletes the object.

Definition at line 301 of file subscriptor.h.

## ◆ list_subscribers() [1/2]

template<typename StreamType >
 void Subscriptor::list_subscribers ( StreamType & stream ) const
inlineinherited

List the subscribers to the input stream.

Definition at line 318 of file subscriptor.h.

## ◆ list_subscribers() [2/2]

 void Subscriptor::list_subscribers ( ) const
inherited

List the subscribers to deallog.

Definition at line 204 of file subscriptor.cc.

## ◆ serialize()

template<class Archive >
 void Subscriptor::serialize ( Archive & ar, const unsigned int version )
inlineinherited

Read or write the data of this object to or from a stream for the purpose of serialization using the BOOST serialization library.

This function does not actually serialize any of the member variables of this class. The reason is that what this class stores is only who subscribes to this object, but who does so at the time of storing the contents of this object does not necessarily have anything to do with who subscribes to the object when it is restored. Consequently, we do not want to overwrite the subscribers at the time of restoring, and then there is no reason to write the subscribers out in the first place.

Definition at line 310 of file subscriptor.h.

## ◆ vars

template<int rank, int dim, typename Number = double>
mutableprivate

Place for the variables for each thread

Definition at line 278 of file tensor_function_parser.h.

## ◆ tfp

template<int rank, int dim, typename Number = double>
mutableprivate

The muParser objects for each thread (and one for each component). We are storing a unique_ptr so that we don't need to include the definition of mu::Parser in this header.

Definition at line 286 of file tensor_function_parser.h.

## ◆ constants

template<int rank, int dim, typename Number = double>
 std::map TensorFunctionParser< rank, dim, Number >::constants
private

An array to keep track of all the constants, required to initialize tfp in each thread.

Definition at line 292 of file tensor_function_parser.h.

## ◆ var_names

template<int rank, int dim, typename Number = double>
 std::vector TensorFunctionParser< rank, dim, Number >::var_names
private

An array for the variable names, required to initialize tfp in each thread.

Definition at line 298 of file tensor_function_parser.h.

## ◆ expressions

template<int rank, int dim, typename Number = double>
 std::vector TensorFunctionParser< rank, dim, Number >::expressions
private

An array of function expressions (one per component), required to initialize tfp in each thread.

Definition at line 314 of file tensor_function_parser.h.

## ◆ initialized

template<int rank, int dim, typename Number = double>
 bool TensorFunctionParser< rank, dim, Number >::initialized
private

State of usability. This variable is checked every time the function is called for evaluation. It's set to true in the initialize() methods.

Definition at line 320 of file tensor_function_parser.h.

## ◆ n_vars

template<int rank, int dim, typename Number = double>
 unsigned int TensorFunctionParser< rank, dim, Number >::n_vars
private

Number of variables. If this is also a function of time, then the number of variables is dim+1, otherwise it is dim. In the case that this is a time dependent function, the time is supposed to be the last variable. If n_vars is not identical to the number of the variables parsed by the initialize() method, then an exception is thrown.

Definition at line 329 of file tensor_function_parser.h.

## ◆ n_components

template<int rank, int dim, typename Number = double>
 unsigned int TensorFunctionParser< rank, dim, Number >::n_components
private

Number of components is equal dimrank.

Definition at line 334 of file tensor_function_parser.h.

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