CASM::Monte::MCDataConvergence Class Reference

#include <MCData.hh>

Detailed Description

Checks if a range of observations have converged.

Definition at line 79 of file MCData.hh.

Public Types
typedef MCData::size_type	size_type

Public Member Functions
	MCDataConvergence ()
	Default constructor. More...
	MCDataConvergence (const Eigen::VectorXd &observations, double conf)
	Construct a MCDataConvergence object. More...
bool	is_converged (double prec) const
	Returns true if converged to the requested level. More...
double	mean () const
	<X> More...
double	squared_norm () const
	<X*X> More...
double	calculated_precision () const
	Calculated precision of <X> More...

Private Member Functions
std::tuple< bool, double, double >	_calc_rho (const Eigen::VectorXd &observations)
	Try to find rho = pow(2.0, -1.0/i), using min i such that CoVar[i]/CoVar[0] <= 0.5. More...

Private Attributes
bool	m_is_converged
double	m_mean
double	m_squared_norm
double	m_calculated_prec

Member Typedef Documentation

size_type

typedef MCData::size_type CASM::Monte::MCDataConvergence::size_type

Definition at line 81 of file MCData.hh.

Constructor & Destructor Documentation

MCDataConvergence() [1/2]

CASM::Monte::MCDataConvergence::MCDataConvergence ( )

inline

Default constructor.

Definition at line 84 of file MCData.hh.

MCDataConvergence() [2/2]

CASM::Monte::MCDataConvergence::MCDataConvergence	(	const Eigen::VectorXd &	observations,
		double	conf
	)

Construct a MCDataConvergence object.

Check convergence of a range of observations.

Parameters

observations	An Eigen::VectorXd of observations
conf	Desired confidence level

We check for convergence using the algorithm of: Van de Walle and Asta, Modelling Simul. Mater. Sci. Eng. 10 (2002) 521–538.

The observations are considered converged to the desired prec and conf if:

• calculated_prec <= prec,

where:

• calculated_prec = sqrt(Var)*z_alpha,
• z_alpha = sqrt(2.0)*inv_erf(1.0-conf)
• var_of_mean = (CoVar[0]/observations.size())*((1.0+rho)/(1.0-rho))
• CoVar[i] = ( (1.0/(observations.size()-i))*sum_j(j=0:L-i-1, observations(j)*observations(j+1)) ) - sqr(observations.mean());
• rho = pow(2.0, -1.0/i), using min i such that CoVar[i]/CoVar[0] < 0.5

Definition at line 132 of file MCData.cc.

Member Function Documentation

_calc_rho()

std::tuple< bool, double, double > CASM::Monte::MCDataConvergence::_calc_rho ( const Eigen::VectorXd &  observations )

private

Try to find rho = pow(2.0, -1.0/i), using min i such that CoVar[i]/CoVar[0] <= 0.5.

Returns

std::tuple<bool, double> : (found_rho?, rho)

Definition at line 170 of file MCData.cc.

calculated_precision()

double CASM::Monte::MCDataConvergence::calculated_precision ( ) const

inline

Calculated precision of <X>

Returns

sqrt(2.0*Var(<X>))*inv_erf(1.0-conf)

• This is the critical value is used for comparison in is_converged
• Var(<X>), the variance in the mean of X, is calculated as described by MCDataConvergence

Definition at line 114 of file MCData.hh.

is_converged()

bool CASM::Monte::MCDataConvergence::is_converged ( double  prec ) const

inline

Returns true if converged to the requested level.

Parameters

prec	Desired absolute precision (<X> +/- prec)

Returns

true if Var(<X>) <= pow(prec/(sqrt(2.0)*inv_erf(1.0-conf)), 2.0)

\seealso MCDataConvergence(const Eigen::VectorXd& observations, double conf)

Definition at line 98 of file MCData.hh.

mean()

double CASM::Monte::MCDataConvergence::mean ( ) const

inline

<X>

Definition at line 101 of file MCData.hh.

squared_norm()

double CASM::Monte::MCDataConvergence::squared_norm ( ) const

inline

<X*X>

Definition at line 104 of file MCData.hh.

Member Data Documentation

m_calculated_prec

double CASM::Monte::MCDataConvergence::m_calculated_prec

private

Definition at line 125 of file MCData.hh.

m_is_converged

bool CASM::Monte::MCDataConvergence::m_is_converged

private

Definition at line 122 of file MCData.hh.

m_mean

double CASM::Monte::MCDataConvergence::m_mean

private

Definition at line 123 of file MCData.hh.

m_squared_norm

double CASM::Monte::MCDataConvergence::m_squared_norm

private

Definition at line 124 of file MCData.hh.

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

• /Users/bpuchala/Work/codes/CASMcode_v0.2.X_reference/include/casm/monte_carlo/MCData.hh
• /Users/bpuchala/Work/codes/CASMcode_v0.2.X_reference/src/casm/monte_carlo/MCData.cc