static InputParameters validParams()
NestedMonteCarloSampler(const InputParameters ¶meters)
std::vector< const Distribution * > _distributions
Storage for distribution objects to be utilized.
std::vector< std::size_t > _loop_index
The loop index for distribution.
virtual Real computeSample(dof_id_type row_index, dof_id_type col_index) override
Return the sample for the given row and column.
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
std::vector< dof_id_type > _loop_mod
Helper for determining if a set of columns need to be recomputed: if (row_index % _loop_mod[_loop_ind...
const InputParameters & parameters() const
std::vector< Real > _row_data
Storage for row data (to be used when not recomputing a column)
virtual void sampleSetUp(const SampleMode mode) override
Here we need to precompute rows that might not be assigned to this processor.
A class used to perform nested Monte Carlo Sampling.