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core::scoring::epr_deer::DEERDistanceDistribution Class Reference

#include <DEERData.hh>

Inheritance diagram for core::scoring::epr_deer::DEERDistanceDistribution:
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Public Member Functions

Real get_score (std::map< Size, Real > const &simulated_histogram, bool const &set_score=false) override
 Computes cross-entropy of simulated distribution from experimental. Cross-entropy corresponds to the negative log-likelihood that the experimental distribution could have given rise to the simulated. This allows boltzmann weighting and/or Bayesian statistical inference from score Note that although confidence bands can be received as input, they are not currently used for this purpose. If you know an information-theoretic approach to using them, please contact me. I would live to incorporate that information here. More...
 
std::map< Size, Real > const & lower_bound () const
 Returns the lower bound/confidence band for the distance distribution. More...
 
std::map< Size, Real > const & best_fit () const
 Returns the line of best fit. Used to calculate cross-entropy. More...
 
std::map< Size, Real > const & upper_bound () const
 Returns the upper bound/confidence band for the distance distribution. More...
 
void lower_bound (std::map< Size, Real > const &val)
 Sets the lower bound/confidence band for the distance distribution. More...
 
void best_fit (std::map< Size, Real > const &val)
 Sets the line of best fit. Used to calculate cross-entropy. More...
 
void upper_bound (std::map< Size, Real > const &val)
 Sets the upper bound/confidence band for the distance distribution. More...
 
void append (Size const &dist_bin, Real const &lower, Real const &upper)
 Adds data to map at a specific distance. Overwrites if distance is occupied. More...
 
- Public Member Functions inherited from core::scoring::epr_deer::DEERData
void print_histogram (std::map< Size, Real > const &simulated_histogram) const
 Print the simulated distance distribution. More...
 
utility::vector1< std::pair
< Size, std::string > > const & 
residues () const
 Returns the residues involved in this data set. Residues are saves with two parameters: the residue ID, and the label type Label type is set to "DEFAULT" by default (duh). Other options include DEFAULT_FAST and CUSTOM. More...
 
Size const & bins_per_angstrom () const
 Returns the granularity of the distance distribution. Default is 2 bins per A. More...
 
Real score () const
 Returns the last computed score. Obtained using get_score() or manually set. More...
 
Real relative_weight () const
 Returns the relative weight. Default: 1. Can be lowered when the data is less trustworthy. More...
 
void residues (utility::vector1< std::pair< Size, std::string > > const &val)
 Sets residue for data set; info for each "residue" consists of the index and the spin label type. More...
 
void bins_per_angstrom (Size const &val)
 Set the number of bins per angstrom for the data set. More...
 
void score (Real const &val)
 Set the score of the data set. More...
 
void relative_weight (Real const &val)
 Set the relative weight of the data set. More...
 

Private Attributes

std::map< Size, Reallower_bound_ = {}
 
std::map< Size, Realbest_fit_ = {}
 
std::map< Size, Realupper_bound_ = {}
 

Additional Inherited Members

- Protected Member Functions inherited from core::scoring::epr_deer::DEERData
Real compute_avg_dist (std::map< Size, Real > const &simulated_histogram) const
 Computes average distance of distribution for local functions. More...
 
- Protected Attributes inherited from core::scoring::epr_deer::DEERData
utility::vector1< std::pair
< Size, std::string > > 
residues_
 
Size bins_per_angstrom_ = 2
 
Real score_
 
Real rel_weight_ = 1.0
 

Detailed Description

Derived class that stores the entire distance distribution Score is evaluated using the cross-entropy of the simulated from the experimental

Member Function Documentation

void core::scoring::epr_deer::DEERDistanceDistribution::append ( Size const &  dist_bin,
Real const &  lower,
Real const &  upper 
)

Adds data to map at a specific distance. Overwrites if distance is occupied.

References lower_bound_, protocols::mean_field::max(), protocols::mean_field::min(), and upper_bound_.

std::map< Size, Real > const & core::scoring::epr_deer::DEERDistanceDistribution::best_fit ( ) const

Returns the line of best fit. Used to calculate cross-entropy.

References best_fit_.

Referenced by core::scoring::epr_deer::DEERIO::read_gauss_lines().

void core::scoring::epr_deer::DEERDistanceDistribution::best_fit ( std::map< Size, Real > const &  val)

Sets the line of best fit. Used to calculate cross-entropy.

References best_fit_, and protocols::hybridization::val.

Real core::scoring::epr_deer::DEERDistanceDistribution::get_score ( std::map< Size, Real > const &  simulated_histogram,
bool const &  set_score = false 
)
overridevirtual

Computes cross-entropy of simulated distribution from experimental. Cross-entropy corresponds to the negative log-likelihood that the experimental distribution could have given rise to the simulated. This allows boltzmann weighting and/or Bayesian statistical inference from score Note that although confidence bands can be received as input, they are not currently used for this purpose. If you know an information-theoretic approach to using them, please contact me. I would live to incorporate that information here.

Computes cross-entropy of simulated distribution from experimental.

Reimplemented from core::scoring::epr_deer::DEERData.

References best_fit_, protocols::mean_field::max(), protocols::mean_field::min(), core::scoring::epr_deer::DEERData::score(), core::scoring::epr_deer::DEERData::score_, and protocols::hybridization::val.

std::map< Size, Real > const & core::scoring::epr_deer::DEERDistanceDistribution::lower_bound ( ) const

Returns the lower bound/confidence band for the distance distribution.

References lower_bound_.

Referenced by lower_bound().

void core::scoring::epr_deer::DEERDistanceDistribution::lower_bound ( std::map< Size, Real > const &  val)

Sets the lower bound/confidence band for the distance distribution.

References lower_bound(), and lower_bound_.

std::map< Size, Real > const & core::scoring::epr_deer::DEERDistanceDistribution::upper_bound ( ) const

Returns the upper bound/confidence band for the distance distribution.

References upper_bound_.

Referenced by upper_bound().

void core::scoring::epr_deer::DEERDistanceDistribution::upper_bound ( std::map< Size, Real > const &  val)

Sets the upper bound/confidence band for the distance distribution.

References upper_bound(), and upper_bound_.

Member Data Documentation

std::map< Size, Real > core::scoring::epr_deer::DEERDistanceDistribution::best_fit_ = {}
private

Referenced by best_fit(), and get_score().

std::map< Size, Real > core::scoring::epr_deer::DEERDistanceDistribution::lower_bound_ = {}
private

Referenced by append(), and lower_bound().

std::map< Size, Real > core::scoring::epr_deer::DEERDistanceDistribution::upper_bound_ = {}
private

Referenced by append(), and upper_bound().


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