27 virtual void proposeSamples(
const unsigned int seed_value)
override;
38 const Real & state1,
const Real & state2,
const Real & rnd,
const Real & scale, Real & diff);
46 void tuneParams(Real & gamma, Real &
b,
const Real & scale);
const MooseEnum & _tuning_option
Tuning options for the internal params.
virtual int decisionStep() const override
Return the step after which decision making can begin.
const std::vector< std::vector< Real > > & _previous_state
Reporter value with the previous state of all the walkers.
static InputParameters validParams()
virtual void proposeSamples(const unsigned int seed_value) override
Fill in the _new_samples vector of vectors (happens within sampleSetUp)
const std::vector< Real > & _previous_state_var
Reporter value with the previous state of all the walkers for variance.
A class for performing Affine Invariant Ensemble MCMC with differential sampler.
void tuneParams(Real &gamma, Real &b, const Real &scale)
Tune the internal parameters.
AffineInvariantDES(const InputParameters ¶meters)
const InputParameters & parameters() const
std::vector< Real > _scales
Scales for the parameters.
void computeDifferential(const Real &state1, const Real &state2, const Real &rnd, const Real &scale, Real &diff)
Compute the differential evolution from the current state.
A base class used to perform Parallel Markov Chain Monte Carlo (MCMC) sampling.