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core::scoring::constraints::MixtureFunc Class Reference

Derived class of class Func representing a Mixture of several distinct functions. The function is of the form ln( g(r) / h(r) ), where g(r) is a mixture of a Gaussian and Exponential distributions, and h(r) is a Gaussian distribution. See methods and implementation for more information. More...

#include <MixtureFunc.hh>

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List of all members.

Public Member Functions

 MixtureFunc (Real const anchor, Real const gaussian_param, Real const exp_param, Real const mixture_param, Real const bg_mean, Real const bg_sd)
FuncOP clone () const
 returns a clone of this MixtureFunc
Real func (Real const x) const
 Returns the value of this MixtureFunc evaluated at distance x.
Real dfunc (Real const x) const
 Returns the value of the first derivative of this MixtureFunc at distance x.
virtual void show_definition (std::ostream &out) const
 show the definitio of this MixtureFunc to the specified output stream.
Real dfunc_component (Real const x, Real &g, Real &h, Real &g_prime, Real &h_prime) const
 Function that's used for debugging. Given x, this calculates g(x), h(x), g'(x) and h'(x).
Real calc_kl_divergence () const
 Calculates the K-L divergence between the inferred and background distributions.
virtual void show (std::ostream &out) const
 Prints this MixtureFunc to the given ostream.
void read_data (std::istream &in)
 The parameters are:
Real func_ (Real x) const
 Returns the value of this MixtureFunc evaluated at distance x.

Friends

std::ostream & operator<< (std::ostream &out, const MixtureFunc &f)
 Calls show( out ) on this MixtureFunc.

Detailed Description

Derived class of class Func representing a Mixture of several distinct functions. The function is of the form ln( g(r) / h(r) ), where g(r) is a mixture of a Gaussian and Exponential distributions, and h(r) is a Gaussian distribution. See methods and implementation for more information.


Constructor & Destructor Documentation

core::scoring::constraints::MixtureFunc::MixtureFunc ( Real const  anchor,
Real const  gaussian_param,
Real const  exp_param,
Real const  mixture_param,
Real const  bg_mean,
Real const  bg_sd 
) [inline]

Constructor for MixtureFunc. Arguments to the constructor are:

  • anchor: parameter representing the value at which this function is anchored, represents the mean of the Gaussian distribution and the highest point of the exponential distribution.
  • gaussian_param: parameter for Gaussian portion of g(r), representing the standard deviation of a Gaussian distribution around anchor.
  • exp_param: parameter for Exponential portion of g(r), representing the rate at which the exponential distribution drops off from anchor.
  • mixture_param: parameter describing the mixture of the Gaussian and Exponential functions that make up g(r).
  • bg_mean: parameter representing the mean of h(r).
  • bg_sd: parameter representing the standard deviation of h(r).

Referenced by clone().


Member Function Documentation

Real core::scoring::constraints::MixtureFunc::calc_kl_divergence ( ) const

Calculates the K-L divergence between the inferred and background distributions.

References core::sequence::end.

FuncOP core::scoring::constraints::MixtureFunc::clone ( ) const [inline, virtual]

returns a clone of this MixtureFunc

Implements core::scoring::constraints::Func.

References MixtureFunc().

Real core::scoring::constraints::MixtureFunc::dfunc ( Real const  x) const [virtual]

Returns the value of the first derivative of this MixtureFunc at distance x.

Implements core::scoring::constraints::Func.

Real core::scoring::constraints::MixtureFunc::dfunc_component ( Real const  x,
Real g,
Real h,
Real g_prime,
Real h_prime 
) const
Real core::scoring::constraints::MixtureFunc::func ( Real const  x) const [virtual]

Returns the value of this MixtureFunc evaluated at distance x.

Implements core::scoring::constraints::Func.

Real core::scoring::constraints::MixtureFunc::func_ ( Real  x) const

Returns the value of this MixtureFunc evaluated at distance x.

private

References core::scoring::constraints::dexponential(), and core::scoring::constraints::dgaussian().

void core::scoring::constraints::MixtureFunc::read_data ( std::istream &  in) [virtual]

The parameters are:

Initializes this MixtureFunc from the given istream. An example of the type of string from which the istream should be constructed is: "MIXTUREFUNC 6.9734 3.598 0.222 0.872 19.396 7.643". The interpretation is to create initialize this MixtureFunc object with the following parameters:

  • anchor 6.9734
  • gaussian_param 3.598
  • exp_param 0.222
  • mixture_param 0.872
  • bg_mean 19.396
  • bg_sd 7.643

Reimplemented from core::scoring::constraints::Func.

void core::scoring::constraints::MixtureFunc::show ( std::ostream &  out) const [virtual]

Prints this MixtureFunc to the given ostream.

Reimplemented from core::scoring::constraints::Func.

References protocols::comparative_modeling::features::A, and core::sequence::end.

void core::scoring::constraints::MixtureFunc::show_definition ( std::ostream &  out) const [virtual]

show the definitio of this MixtureFunc to the specified output stream.

Reimplemented from core::scoring::constraints::Func.


Friends And Related Function Documentation

std::ostream& operator<< ( std::ostream &  out,
const MixtureFunc f 
) [friend]

Calls show( out ) on this MixtureFunc.


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