MBMesquite::TSum Class Reference

#include <TSum.hpp>

Inheritance diagram for MBMesquite::TSum:

Collaboration diagram for MBMesquite::TSum:

Public Member Functions
	TSum (TMetric *metric1, TMetric *metric2)
virtual MESQUITE_EXPORT	~TSum ()
virtual MESQUITE_EXPORT std::string	get_name () const
virtual MESQUITE_EXPORT bool	evaluate (const MsqMatrix< 2, 2 > &T, double &result, MsqError &err)
	Evaluate \(\mu(T)\).
virtual MESQUITE_EXPORT bool	evaluate_with_grad (const MsqMatrix< 2, 2 > &T, double &result, MsqMatrix< 2, 2 > &deriv_wrt_T, MsqError &err)
	Gradient of \(\mu(T)\) with respect to components of T.
virtual MESQUITE_EXPORT bool	evaluate_with_hess (const MsqMatrix< 2, 2 > &T, double &result, MsqMatrix< 2, 2 > &deriv_wrt_T, MsqMatrix< 2, 2 > second_wrt_T[3], MsqError &err)
	Hessian of \(\mu(T)\) with respect to components of T.
virtual MESQUITE_EXPORT bool	evaluate (const MsqMatrix< 3, 3 > &T, double &result, MsqError &err)
	Evaluate \(\mu(T)\).
virtual MESQUITE_EXPORT bool	evaluate_with_grad (const MsqMatrix< 3, 3 > &T, double &result, MsqMatrix< 3, 3 > &deriv_wrt_T, MsqError &err)
	Gradient of \(\mu(T)\) with respect to components of T.
virtual MESQUITE_EXPORT bool	evaluate_with_hess (const MsqMatrix< 3, 3 > &T, double &result, MsqMatrix< 3, 3 > &deriv_wrt_T, MsqMatrix< 3, 3 > second_wrt_T[6], MsqError &err)
	Hessian of \(\mu(T)\) with respect to components of T.
Private Member Functions
template<unsigned D>
bool	eval (const MsqMatrix< D, D > &T, double &result, MsqError &err)
template<unsigned D>
bool	grad (const MsqMatrix< D, D > &T, double &result, MsqMatrix< D, D > &first, MsqError &err)
template<unsigned D>
bool	hess (const MsqMatrix< D, D > &T, double &result, MsqMatrix< D, D > &first, MsqMatrix< D, D > *second, MsqError &err)
Private Attributes
TMetric *	mu1
TMetric *	mu2

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Detailed Description

\( \mu\prime = \mu_1 + \mu_2 \)

Definition at line 42 of file TSum.hpp.

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Constructor & Destructor Documentation

MBMesquite::TSum::TSum	(	TMetric *	metric1,
		TMetric *	metric2
	)		[inline]

Definition at line 47 of file TSum.hpp.

: mu1( metric1 ), mu2( metric2 ) {}

MBMesquite::TSum::~TSum

(

)

[virtual]

Definition at line 47 of file TSum.cpp.

{}

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Member Function Documentation

template<unsigned DIM>

bool MBMesquite::TSum::eval	(	const MsqMatrix< DIM, DIM > &	T,
		double &	result,
		MsqError &	err
	)		[inline, private]

Definition at line 50 of file TSum.cpp.

References MBMesquite::TMetric::evaluate(), MSQ_ERRZERO, mu1, and mu2.

{
    double val2;
    bool rval = mu1->evaluate( T, result, err );
    MSQ_ERRZERO( err );
    bool rval2 = mu2->evaluate( T, val2, err );
    MSQ_ERRZERO( err );
    result += val2;
    return rval && rval2;
}

virtual MESQUITE_EXPORT bool MBMesquite::TSum::evaluate	(	const MsqMatrix< 2, 2 > &	T,
		double &	result,
		MsqError &	err
	)		[virtual]

Evaluate \(\mu(T)\).

Parameters:

T	2x2 relative measure matrix (typically A W^-1)
result	Output: value of function

Returns:

false if function cannot be evaluated for given T (e.g. division by zero, etc.), true otherwise.

Reimplemented from MBMesquite::TMetric.

virtual MESQUITE_EXPORT bool MBMesquite::TSum::evaluate	(	const MsqMatrix< 3, 3 > &	T,
		double &	result,
		MsqError &	err
	)		[virtual]

Evaluate \(\mu(T)\).

Parameters:

T	3x3 relative measure matrix (typically A W^-1)
result	Output: value of function

Returns:

false if function cannot be evaluated for given T (e.g. division by zero, etc.), true otherwise.

Reimplemented from MBMesquite::TMetric.

virtual MESQUITE_EXPORT bool MBMesquite::TSum::evaluate_with_grad	(	const MsqMatrix< 2, 2 > &	T,
		double &	result,
		MsqMatrix< 2, 2 > &	deriv_wrt_T,
		MsqError &	err
	)		[virtual]

Gradient of \(\mu(T)\) with respect to components of T.

Parameters:

T	2x2 relative measure matrix (typically A W^-1)
result	Output: value of function
deriv_wrt_T	Output: partial deriviatve of \(\mu\) wrt each term of T, evaluated at passed T. \[\left[\begin{array}{cc} \frac{\partial\mu}{\partial T_{0,0}} & \frac{\partial\mu}{\partial T_{0,1}} \\ \frac{\partial\mu}{\partial T_{1,0}} & \frac{\partial\mu}{\partial T_{1,1}} \\ \end{array}\right]\]

Returns:

false if function cannot be evaluated for given T (e.g. division by zero, etc.), true otherwise.

Reimplemented from MBMesquite::TMetric.

virtual MESQUITE_EXPORT bool MBMesquite::TSum::evaluate_with_grad	(	const MsqMatrix< 3, 3 > &	T,
		double &	result,
		MsqMatrix< 3, 3 > &	deriv_wrt_T,
		MsqError &	err
	)		[virtual]

Gradient of \(\mu(T)\) with respect to components of T.

Parameters:

T	3x3 relative measure matrix (typically A W^-1)
result	Output: value of function
deriv_wrt_T	Output: partial deriviatve of \(\mu\) wrt each term of T, evaluated at passed T. \[\left[\begin{array}{ccc} \frac{\partial\mu}{\partial T_{0,0}} & \frac{\partial\mu}{\partial T_{0,1}} & \frac{\partial\mu}{\partial T_{0,2}} \\ \frac{\partial\mu}{\partial T_{1,0}} & \frac{\partial\mu}{\partial T_{1,1}} & \frac{\partial\mu}{\partial T_{1,2}} \\ \frac{\partial\mu}{\partial T_{2,0}} & \frac{\partial\mu}{\partial T_{2,1}} & \frac{\partial\mu}{\partial T_{2,2}} \end{array}\right]\]

Returns:

false if function cannot be evaluated for given T (e.g. division by zero, etc.), true otherwise.

Reimplemented from MBMesquite::TMetric.

virtual MESQUITE_EXPORT bool MBMesquite::TSum::evaluate_with_hess	(	const MsqMatrix< 2, 2 > &	T,
		double &	result,
		MsqMatrix< 2, 2 > &	deriv_wrt_T,
		MsqMatrix< 2, 2 >	second_wrt_T[3],
		MsqError &	err
	)		[virtual]

Hessian of \(\mu(T)\) with respect to components of T.

Parameters:

T	3x3 relative measure matrix (typically A W^-1)
result	Output: value of function
deriv_wrt_T	Output: partial deriviatve of \(\mu\) wrt each term of T, evaluated at passed T.
second_wrt_T	Output: 9x9 matrix of second partial deriviatve of \(\mu\) wrt each term of T, in row-major order. The symmetric matrix is decomposed into 3x3 blocks and only the upper diagonal blocks, in row-major order, are returned. \[\left[\begin{array}{cc|cc} \frac{\partial^{2}\mu}{\partial T_{0,0}^2} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial A_{0,1}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial A_{1,0}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial A_{1,1}} \\ \frac{\partial^{2}\mu}{\partial T_{0,0}\partial A_{0,1}} & \frac{\partial^{2}\mu}{\partial T_{0,1}^2} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial A_{1,0}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial A_{1,1}} \\ \hline & & \frac{\partial^{2}\mu}{\partial T_{1,0}^2} & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial A_{1,1}} \\ & & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial A_{1,1}} & \frac{\partial^{2}\mu}{\partial T_{1,1}^2} \\ \end{array}\right]\]

Returns:

false if function cannot be evaluated for given T (e.g. division by zero, etc.), true otherwise.

Reimplemented from MBMesquite::TMetric.

virtual MESQUITE_EXPORT bool MBMesquite::TSum::evaluate_with_hess	(	const MsqMatrix< 3, 3 > &	T,
		double &	result,
		MsqMatrix< 3, 3 > &	deriv_wrt_T,
		MsqMatrix< 3, 3 >	second_wrt_T[6],
		MsqError &	err
	)		[virtual]

Hessian of \(\mu(T)\) with respect to components of T.

Parameters:

T	3x3 relative measure matrix (typically A W^-1)
result	Output: value of function
deriv_wrt_T	Output: partial deriviatve of \(\mu\) wrt each term of T, evaluated at passed T.
second_wrt_T	Output: 9x9 matrix of second partial deriviatve of \(\mu\) wrt each term of T, in row-major order. The symmetric matrix is decomposed into 3x3 blocks and only the upper diagonal blocks, in row-major order, are returned. \[\left[\begin{array}{ccc|ccc|ccc} \frac{\partial^{2}\mu}{\partial T_{0,0}^2} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{0,1}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{0,2}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{1,0}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{1,1}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{2,0}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{2,2}} \\ \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{0,1}} & \frac{\partial^{2}\mu}{\partial T_{0,1}^2} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{0,2}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{1,0}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{1,1}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{2,0}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{2,2}} \\ \frac{\partial^{2}\mu}{\partial T_{0,0}\partial T_{0,2}} & \frac{\partial^{2}\mu}{\partial T_{0,1}\partial T_{0,2}} & \frac{\partial^{2}\mu}{\partial T_{0,2}^2} & \frac{\partial^{2}\mu}{\partial T_{0,2}\partial T_{1,0}} & \frac{\partial^{2}\mu}{\partial T_{0,2}\partial T_{1,1}} & \frac{\partial^{2}\mu}{\partial T_{0,2}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{0,2}\partial T_{2,0}} & \frac{\partial^{2}\mu}{\partial T_{0,2}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{0,2}\partial T_{2,2}} \\ \hline & & & \frac{\partial^{2}\mu}{\partial T_{1,0}^2} & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{1,1}} & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{2,0}} & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{2,2}} \\ & & & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{1,1}} & \frac{\partial^{2}\mu}{\partial T_{1,1}^2} & \frac{\partial^{2}\mu}{\partial T_{1,1}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{1,1}\partial T_{2,0}} & \frac{\partial^{2}\mu}{\partial T_{1,1}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{1,1}\partial T_{2,2}} \\ & & & \frac{\partial^{2}\mu}{\partial T_{1,0}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{1,1}\partial T_{1,2}} & \frac{\partial^{2}\mu}{\partial T_{1,2}^2} & \frac{\partial^{2}\mu}{\partial T_{1,2}\partial T_{2,0}} & \frac{\partial^{2}\mu}{\partial T_{1,2}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{1,2}\partial T_{2,2}} \\ \hline & & & & & & \frac{\partial^{2}\mu}{\partial T_{2,0}^2} & \frac{\partial^{2}\mu}{\partial T_{2,0}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{2,0}\partial T_{2,2}} \\ & & & & & & \frac{\partial^{2}\mu}{\partial T_{2,0}\partial T_{2,1}} & \frac{\partial^{2}\mu}{\partial T_{2,1}^2} & \frac{\partial^{2}\mu}{\partial T_{2,1}\partial T_{2,2}} \\ & & & & & & \frac{\partial^{2}\mu}{\partial T_{2,0}\partial T_{2,2}} & \frac{\partial^{2}\mu}{\partial T_{2,1}\partial T_{2,2}} & \frac{\partial^{2}\mu}{\partial T_{2,2}^2} \\ \end{array}\right]\]

Returns:

false if function cannot be evaluated for given T (e.g. division by zero, etc.), true otherwise.

Reimplemented from MBMesquite::TMetric.

std::string MBMesquite::TSum::get_name

(

)

const [virtual]

Implements MBMesquite::TMetric.

Definition at line 42 of file TSum.cpp.

References MBMesquite::TMetric::get_name(), mu1, and mu2.

{
    return mu1->get_name() + '+' + mu2->get_name();
}

template<unsigned DIM>

bool MBMesquite::TSum::grad	(	const MsqMatrix< DIM, DIM > &	T,
		double &	result,
		MsqMatrix< DIM, DIM > &	first,
		MsqError &	err
	)		[inline, private]

Definition at line 62 of file TSum.cpp.

References MBMesquite::TMetric::evaluate_with_grad(), MSQ_ERRZERO, mu1, and mu2.

{
    double val2;
    MsqMatrix< DIM, DIM > grad2;
    bool rval = mu1->evaluate_with_grad( T, result, deriv, err );
    MSQ_ERRZERO( err );
    bool rval2 = mu2->evaluate_with_grad( T, val2, grad2, err );
    MSQ_ERRZERO( err );
    result += val2;
    deriv += grad2;
    return rval && rval2;
}

template<unsigned DIM>

bool MBMesquite::TSum::hess	(	const MsqMatrix< DIM, DIM > &	T,
		double &	result,
		MsqMatrix< DIM, DIM > &	first,
		MsqMatrix< DIM, DIM > *	second,
		MsqError &	err
	)		[inline, private]

Definition at line 76 of file TSum.cpp.

References MBMesquite::TMetric::evaluate_with_hess(), MSQ_ERRZERO, mu1, and mu2.

{
    const int HL = ( DIM * ( DIM + 1 ) ) / 2;
    double val2;
    MsqMatrix< DIM, DIM > grad2, hess2[HL];

    bool rval = mu1->evaluate_with_hess( T, result, deriv_wrt_T, second_wrt_T, err );
    MSQ_ERRZERO( err );
    bool rval2 = mu2->evaluate_with_hess( T, val2, grad2, hess2, err );
    MSQ_ERRZERO( err );
    result += val2;
    deriv_wrt_T += grad2;
    for( int i = 0; i < HL; ++i )
        second_wrt_T[i] += hess2[i];
    return rval && rval2;
}

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Member Data Documentation

TMetric* MBMesquite::TSum::mu1 [private]

Reimplemented in TSum_TSize_TSize.

Definition at line 44 of file TSum.hpp.

Referenced by eval(), get_name(), grad(), and hess().

TMetric * MBMesquite::TSum::mu2 [private]

Reimplemented in TSum_TSize_TSize.

Definition at line 44 of file TSum.hpp.

Referenced by eval(), get_name(), grad(), and hess().

List of all members.

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

• TSum.hpp
• TSum.cpp