#include <DEERDistanceDistribution.hh>

Inheritance diagram for core::scoring::epr_deer::metrics::DEERDistanceDistribution:

Public Member Functions
Real	get_score (std::map< Size, Real > const &sim_histr) override
	Virtual function to evaluate score given a distribution. More...

utility::vector1< std::map < Size, Real > >	expand_hists (std::map< Size, Real > const &distr)
	Expand distance distribution into multiple distributions. More...

utility::vector1< Real >	get_prs (Size const &bin) const
	Get range of possible P(r) values for experimental 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. More...

void	upper_bound (std::map< Size, Real > const &val)
	Sets the upper bound/confidence band for the distance distribution. More...

void	bounds (bool const &val)
	Set whether confidence bands will be used when calculating score. More...

void	reverse (bool const &val)
	Set whether to compute the reverse metric. More...

void	bb (bool const &val)
	Set whether to use confidence bands. More...

void	singleval (bool const &val)
	Set whether to use a single distance. More...

void	integral (bool const &val)
	Set whether to compute the integral. More...

std::map< Size, Real > const &	lower_bound () const
	Returns the lower bound/confidence band for the distribution. More...

std::map< Size, Real > const &	best_fit () const
	Returns the best fit of the distance distribution. More...

std::map< Size, Real > const &	upper_bound () const
	Returns the upper bound/confidence band for the distribution. More...

bool	bounds () const
	Returns whether confidence bands are being used. More...

bool	reverse () const
	Returns whether the reverse metric is being used. More...

bool	bb () const
	Returns whether backbone expansion is being used. More...

bool	singleval () const
	Returns whether calculation of a single distance is being used. More...

bool	integral () const
	Returns whether calculation of the integral is being used. More...

Public Member Functions inherited from core::scoring::epr_deer::metrics::DEERData
void	print_histogram (std::map< Size, Real > const &sim_histr, std::string const &pose_name="NO NAME GIVEN") const
	Print the simulated distance distribution. More...

Real	get_score (std::map< Size, Real > const &sim_histr, bool const &set_score)
	Function to evaluate score given a distribution. More...

std::map< Size, Real >	convolute (std::map< Size, Real > const &distr, Real const &std) const
	Convolute a distribution with a Gaussian of a specific width. More...

utility::vector1 < PairSizeString > const &	residues () const
	Returns the residues involved in this data set. More...

Size const &	bins_per_a () const
	Returns bins per angstrom for distribution (default: 2) More...

Real	score () const
	Returns the last computed score. More...

Real	stdev () const
	Returns the standard deviation of the distributions to generate. More...

void	residues (utility::vector1< PairSizeString > const &val)
	Sets residue for data set. More...

void	bins_per_a (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	stdev (Real const &val)
	Set the standard deviation of the distributions to generate. More...

std::map< Size, Real >	dist_map () const
	Returns the map of distance values used for custom distributions. More...

void	append_dist_id (Size dist_id, Real dist)
	Append distance ID to custom distance map. More...

utility::vector1< Real >	avg_stdev (std::map< Size, Real > const &histogram)
	Computes average distance of distribution for local functions. More...

Protected Attributes
std::map< Size, Real >	distr_ = {}
	Best fit / distance distribution. More...

std::map< Size, Real >	lower_bound_ = {}
	Lower bound for distribution (95% confidence interval) More...

std::map< Size, Real >	upper_bound_ = {}
	Upper bound for distribution (95% confidence interval) More...

bool	bounds_ = false
	Whether the calculation method uses confidence bands. More...

bool	rev_ = false
	Whether the reverse metric is computed. More...

bool	bb_ = false
	Whether backbone expansion is done (for Bayesian scoring) More...

bool	singleval_ = false
	Whether a single value is being used for scoring. More...

bool	integral_ = false
	Whether the integral is computed. More...

Protected Attributes inherited from core::scoring::epr_deer::metrics::DEERData
Size	bins_per_a_ = 2
	Bins per angstrom for distributions stored and scored. More...

Private Attributes
Real	exp_stdev_ = 0.0
	The standard deviation of the experimental distribution. More...

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::metrics::DEERDistanceDistribution::bb ( bool const & val )

Set whether to use confidence bands.

Parameters

val	Whether to use confidence bands

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

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

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb ( ) const

Returns whether backbone expansion is being used.

Returns: Whether backbone expansion is being used

References bb_.

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

Sets the line of best fit.

Parameters

val	Best fit of DEER distribution

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

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

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

Returns the best fit of the distance distribution.

The best fit of the distance distribution

References distr_.

void core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds ( bool const & val )

Set whether confidence bands will be used when calculating score.

Parameters

val	Whether to use confidence bands

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

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds ( ) const

Returns whether confidence bands are being used.

Returns: Whether confidence bands are being used

References bounds_.

utility::vector1< std::map< Size, Real > > core::scoring::epr_deer::metrics::DEERDistanceDistribution::expand_hists ( std::map< Size, Real > const & distr )

Expand distance distribution into multiple distributions.

Parameters

distr Simulated distribution to expand

Returns: Vector of distributions Used for Bayesian analysis when backbone dynamics are not known and several possibilities must be taken into account

References core::scoring::epr_deer::metrics::DEERData::avg_stdev(), core::scoring::epr_deer::metrics::DEERData::convolute(), exp_stdev_, and protocols::mean_field::max().

Referenced by get_score().

utility::vector1< Real > core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs ( Size const & bin ) const

Get range of possible P(r) values for experimental distribution.

Parameters

bin	Value of r

Returns: Vector of P(r) for Bayesian scoring with confidence bands

References bounds_, distr_, lower_bound_, protocols::mean_field::max(), core::scoring::epr_deer::probit(), upper_bound_, and protocols::hybridization::val.

Referenced by get_score().

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

overridevirtual

Virtual function to evaluate score given a distribution.

Parameters

sim_histr Simulated DEER distribution

Returns: Freshly computed score 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.

Parameters

sim_histr Simulated DEER distribution

Returns: Freshly computed score This is the default method when using DEER distance distributions. It computes the cross entropy of the distribution, also called the negative log-likelihood. It contains three loops. First, it iterates over each bin in either the simulated or the experimental DEER distance distribution. Second, it iterates over a series of simulated DEER distribution generated by the taking into account the possibility of backbone dynamics. Finally, it iterates over a range of possible experimental P(r) values obtained from confidence bands (a range of 2-sigma, or 95% confidence, is assumed) Specialized methods can be used instead by declaring in the file being read. See DEERIO.cc for details

Implements core::scoring::epr_deer::metrics::DEERData.

Reimplemented in core::scoring::epr_deer::metrics::DEERJaccardMethod, core::scoring::epr_deer::metrics::DEERJSMethod, core::scoring::epr_deer::metrics::DEERMiscMethod, and core::scoring::epr_deer::metrics::DEEROverlapMethod.

References core::scoring::epr_deer::metrics::DEERData::avg_stdev(), bb_, distr_, exp_stdev_, expand_hists(), get_prs(), core::scoring::epr_deer::ln(), and rev_.

void core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral ( bool const & val )

Set whether to compute the integral.

Parameters

val	Whether to compute the integral

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

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

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral ( ) const

Returns whether calculation of the integral is being used.

Returns: Whether calculation of the integral is being used

References integral_.

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

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

Parameters

val	Lower bound or confidence band. Note: Can be negative!

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

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

Returns the lower bound/confidence band for the distribution.

Returns: The lower bound/confidence band for the distribution

References lower_bound_.

void core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse ( bool const & val )

Set whether to compute the reverse metric.

Parameters

val	Whether to compute the reverse metric

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

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse ( ) const

Returns whether the reverse metric is being used.

Returns: Whether the reverse metric is being used

References rev_.

void core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval ( bool const & val )

Set whether to use a single distance.

Parameters

val	Whether to use a single distance

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

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

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval ( ) const

Returns whether calculation of a single distance is being used.

Returns: Whether calculation of a single distance is being used

References singleval_.

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

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

Parameters

val	Lower bound or confidence band.

References upper_bound(), and upper_bound_.

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

Returns the upper bound/confidence band for the distribution.

Returns: The upper bound/confidence band for the distribution

References upper_bound_.

Referenced by upper_bound().

Member Data Documentation

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb_ = false

protected

Whether backbone expansion is done (for Bayesian scoring)

Referenced by bb(), and get_score().

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds_ = false

protected

Whether the calculation method uses confidence bands.

Referenced by bounds(), get_prs(), core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(), and core::scoring::epr_deer::metrics::DEERJaccardMethod::get_score().

std::map< Size, Real > core::scoring::epr_deer::metrics::DEERDistanceDistribution::distr_ = {}

protected

Best fit / distance distribution.

Referenced by best_fit(), get_prs(), core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(), core::scoring::epr_deer::metrics::DEERJSMethod::get_score(), core::scoring::epr_deer::metrics::DEERJaccardMethod::get_score(), core::scoring::epr_deer::metrics::DEERMiscMethod::get_score(), core::scoring::epr_deer::metrics::DEERChiSqMethod::get_score(), and get_score().

Real core::scoring::epr_deer::metrics::DEERDistanceDistribution::exp_stdev_ = 0.0

private

The standard deviation of the experimental distribution.

Referenced by expand_hists(), and get_score().

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral_ = false

protected

Whether the integral is computed.

Referenced by core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(), and integral().

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

protected

Lower bound for distribution (95% confidence interval)

Referenced by get_prs(), core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(), core::scoring::epr_deer::metrics::DEERJaccardMethod::get_score(), and lower_bound().

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::rev_ = false

protected

Whether the reverse metric is computed.

Referenced by core::scoring::epr_deer::metrics::DEERChiSqMethod::get_score(), get_score(), and reverse().

bool core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval_ = false

protected

Whether a single value is being used for scoring.

Referenced by core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(), and singleval().

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

protected

Upper bound for distribution (95% confidence interval)

Referenced by get_prs(), core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(), core::scoring::epr_deer::metrics::DEERJaccardMethod::get_score(), and upper_bound().

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

src/core/scoring/epr_deer/metrics/DEERDistanceDistribution.hh
src/core/scoring/epr_deer/metrics/DEERDistanceDistribution.cc

Public Member Functions

Protected Attributes

Private Attributes

Detailed Description

Member Function Documentation

Member Data Documentation