InputParameters validParams()
This is a template class that implements the workhorse compute and computeNodal methods.
const InputParameters & parameters() const
Get the parameters of the object.
This class encapsulates a useful, consistent, cross-platform random number generator with multiple ut...
Base class for randomly generated initial conditions.
std::map< dof_id_type, Real > _elem_numbers
Random numbers per element (currently limited to a single value at a time)
void initialSetup() override
Gets called at the beginning of the simulation before this object is asked to do its job.
std::map< dof_id_type, Real > _node_numbers
Random numbers per node (currently limited to a single value at a time)
const bool _is_nodal
Determines whether a variable basis is elemental or nodal.
MooseRandom * _elem_random_generator
Elemental random number generator.
const bool _use_legacy
Boolean to indicate whether we want to use the old (deprecated) generation pattern.
std::unique_ptr< RandomData > _node_random_data
RandomData node object, we cannot inherit from RandomInterface in an InitialCondition.
static InputParameters validParams()
MooseRandom * _node_random_generator
Nodal random number generator.
std::unique_ptr< RandomData > _elem_random_data
RandomData element object, we cannot inherit from RandomInterface in an InitialCondition.
Real generateRandom()
Generate a uniformly distributed random number on the interval from 0 to 1.
The following methods are specializations for using the libMesh::Parallel::packed_range_* routines fo...