metrics

Bindings for core::scoring::epr_deer::metrics namespace

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERChiSqMethod

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERChiSqMethod, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERChiSqMethod) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERChiSqMethod

C++: core::scoring::epr_deer::metrics::DEERChiSqMethod::operator=(const class core::scoring::epr_deer::metrics::DEERChiSqMethod &) –> class core::scoring::epr_deer::metrics::DEERChiSqMethod &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bb(*args, **kwargs)

Overloaded function.

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use confidence bands

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb(const bool &) –> void

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether backbone expansion is being used

Whether backbone expansion is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb() const –> bool

best_fit(*args, **kwargs)

Overloaded function.

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the line of best fit

Best fit of DEER distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the best fit of the distance distribution

The best fit of the distance distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether confidence bands will be used when calculating score

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds(const bool &) –> void

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether confidence bands are being used

Whether confidence bands are being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds() const –> bool

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_prs(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, bin: int) pyrosetta.rosetta.utility.vector1_double

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

Value of r

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs(const unsigned long &) const –> class utility::vector1<double, class std::allocator<double> >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERChiSqMethod, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERChiSqMethod::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

integral(*args, **kwargs)

Overloaded function.

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the integral

Whether to compute the integral

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral(const bool &) –> void

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of the integral is being used

Whether calculation of the integral is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral() const –> bool

lower_bound(*args, **kwargs)

Overloaded function.

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the lower bound/confidence band for the distance distribution

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the lower bound/confidence band for the distribution

The lower bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

reverse(*args, **kwargs)

Overloaded function.

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the reverse metric

Whether to compute the reverse metric

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse(const bool &) –> void

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether the reverse metric is being used

Whether the reverse metric is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse() const –> bool

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

singleval(*args, **kwargs)

Overloaded function.

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use a single distance

Whether to use a single distance

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval(const bool &) –> void

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of a single distance is being used

Whether calculation of a single distance is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval() const –> bool

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

upper_bound(*args, **kwargs)

Overloaded function.

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the upper bound/confidence band for the distance distribution

Lower bound or confidence band.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the upper bound/confidence band for the distribution

The upper bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData

Bases: pybind11_builtins.pybind11_object

Base class

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData

C++: core::scoring::epr_deer::metrics::DEERData::operator=(const class core::scoring::epr_deer::metrics::DEERData &) –> class core::scoring::epr_deer::metrics::DEERData &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_score(*args, **kwargs)

Overloaded function.

  1. get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, set_score: bool) -> float

Function to evaluate score given a distribution

Simulated DEER distribution

Boolean to save score or not

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERData::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const bool &) –> double

  1. get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERData::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData

Derived class that stores DEER decay data

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData

C++: core::scoring::epr_deer::metrics::DEERDecayData::operator=(const class core::scoring::epr_deer::metrics::DEERDecayData &) –> class core::scoring::epr_deer::metrics::DEERDecayData &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bckg(*args, **kwargs)

Overloaded function.

  1. bckg(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData) -> str

Returns background type

Intermolecular coupling background type

C++: core::scoring::epr_deer::metrics::DEERDecayData::bckg() const –> std::string

  1. bckg(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, val: str) -> None

Sets background type

Type of intermolecular coupling background

C++: core::scoring::epr_deer::metrics::DEERDecayData::bckg(const std::string &) –> void

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

factory(*args, **kwargs)

Overloaded function.

  1. factory(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData) -> pyrosetta.rosetta.core.scoring.epr_deer.Simulated4PDEERTraceFactory

Returns DEER trace factory object

Factory object

C++: core::scoring::epr_deer::metrics::DEERDecayData::factory() –> class core::scoring::epr_deer::Simulated4PDEERTraceFactory &

  1. factory(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, val: pyrosetta.rosetta.core.scoring.epr_deer.Simulated4PDEERTraceFactory) -> None

Sets DEER trace factory object

Factory object

C++: core::scoring::epr_deer::metrics::DEERDecayData::factory(const class core::scoring::epr_deer::Simulated4PDEERTraceFactory &) –> void

fit_stdev(*args, **kwargs)

Overloaded function.

  1. fit_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData) -> bool

Returns whether standard deviation is a fitting parameter

Boolean

C++: core::scoring::epr_deer::metrics::DEERDecayData::fit_stdev() const –> const bool &

  1. fit_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, val: bool) -> None

Sets if standard deviation is varied as a parameter

Boolean

C++: core::scoring::epr_deer::metrics::DEERDecayData::fit_stdev(const bool &) –> void

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

A DEER trace is calculated from the simulated histogram.

For details, please read del Alamo Biophysical Journal 2020. The score is the average sum-of-squares residuals between the two. Note that there is a slight noise-dependence to this; noisier data will always return higher scores.

C++: core::scoring::epr_deer::metrics::DEERDecayData::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

init_factory(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, trace: pyrosetta.rosetta.utility.vector1_double, time_pts: pyrosetta.rosetta.utility.vector1_double) None

Initialize DEER factory object

Experimental DEER trace

Time points corresponding to DEER trace

C++: core::scoring::epr_deer::metrics::DEERDecayData::init_factory(const class utility::vector1<double, class std::allocator<double> > &, const class utility::vector1<double, class std::allocator<double> > &) –> void

max_dist(*args, **kwargs)

Overloaded function.

  1. max_dist(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData) -> int

Returns maximum distance for kernel calculation

Maximum distance for kernel calculation

C++: core::scoring::epr_deer::metrics::DEERDecayData::max_dist() const –> unsigned long

  1. max_dist(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, val: int) -> None

Sets maximum distance for kernel calculation

Maximum distance to set

C++: core::scoring::epr_deer::metrics::DEERDecayData::max_dist(const unsigned long &) –> void

noise(*args, **kwargs)

Overloaded function.

  1. noise(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData) -> float

Returns the noise from the imaginary component

Noise level

C++: core::scoring::epr_deer::metrics::DEERDecayData::noise() const –> const double &

  1. noise(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, val: float) -> None

Sets the noise from the imaginary component

Noise level

C++: core::scoring::epr_deer::metrics::DEERDecayData::noise(const double &) –> void

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

sum_of_squares(*args, **kwargs)

Overloaded function.

  1. sum_of_squares(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, sim_trace: pyrosetta.rosetta.utility.vector1_double) -> float

  2. sum_of_squares(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDecayData, sim_trace: pyrosetta.rosetta.utility.vector1_double, normalize: bool) -> float

Calculate sum of squares of simulated DEER trace

Simulated DEER trace

Reference DEER trace; experimental by default

Normalize by number of time points; recommended

Sum of squared residuals

C++: core::scoring::epr_deer::metrics::DEERDecayData::sum_of_squares(const class utility::vector1<double, class std::allocator<double> > &, const bool &) const –> double

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData

Derived class for storing the data as a bounded function.

Contains the upper and lower bounds, as well as steepness.

If the average simulated distance falls within these bounds the score is zero If the average falls outside, it is evaluated via the steepness For example: ( ( lb - d ) / s ) ^2 OR ( ( d - ub ) / s ) ^2 lb: Lower bound ub: Upper bound d: Avg distance s: Steepness

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds

C++: core::scoring::epr_deer::metrics::DEERDistanceBounds::operator=(const class core::scoring::epr_deer::metrics::DEERDistanceBounds &) –> class core::scoring::epr_deer::metrics::DEERDistanceBounds &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds) -> Tuple[float, float]

Returns the lower and upper distance bounds

Pair of lower and upper bounds

C++: core::scoring::epr_deer::metrics::DEERDistanceBounds::bounds() const –> struct std::pair<double, double>

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds, lo: float, hi: float) -> None

Sets the lower and upper bounds

Lower bound

Upper bound

C++: core::scoring::epr_deer::metrics::DEERDistanceBounds::bounds(const double &, const double &) –> void

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERDistanceBounds::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

step(*args, **kwargs)

Overloaded function.

  1. step(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds) -> float

Returns the step / steepness of the scoring function

Steepness value

C++: core::scoring::epr_deer::metrics::DEERDistanceBounds::step() const –> const double &

  1. step(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceBounds, step: float) -> None

Sets the step / steepness

Step

C++: core::scoring::epr_deer::metrics::DEERDistanceBounds::step(const double &) –> void

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData

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

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::operator=(const class core::scoring::epr_deer::metrics::DEERDistanceDistribution &) –> class core::scoring::epr_deer::metrics::DEERDistanceDistribution &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bb(*args, **kwargs)

Overloaded function.

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use confidence bands

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb(const bool &) –> void

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether backbone expansion is being used

Whether backbone expansion is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb() const –> bool

best_fit(*args, **kwargs)

Overloaded function.

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the line of best fit

Best fit of DEER distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the best fit of the distance distribution

The best fit of the distance distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether confidence bands will be used when calculating score

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds(const bool &) –> void

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether confidence bands are being used

Whether confidence bands are being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds() const –> bool

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_prs(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, bin: int) pyrosetta.rosetta.utility.vector1_double

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

Value of r

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs(const unsigned long &) const –> class utility::vector1<double, class std::allocator<double> >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

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.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

integral(*args, **kwargs)

Overloaded function.

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the integral

Whether to compute the integral

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral(const bool &) –> void

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of the integral is being used

Whether calculation of the integral is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral() const –> bool

lower_bound(*args, **kwargs)

Overloaded function.

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the lower bound/confidence band for the distance distribution

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the lower bound/confidence band for the distribution

The lower bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

reverse(*args, **kwargs)

Overloaded function.

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the reverse metric

Whether to compute the reverse metric

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse(const bool &) –> void

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether the reverse metric is being used

Whether the reverse metric is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse() const –> bool

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

singleval(*args, **kwargs)

Overloaded function.

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use a single distance

Whether to use a single distance

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval(const bool &) –> void

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of a single distance is being used

Whether calculation of a single distance is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval() const –> bool

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

upper_bound(*args, **kwargs)

Overloaded function.

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the upper bound/confidence band for the distance distribution

Lower bound or confidence band.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the upper bound/confidence band for the distribution

The upper bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJSMethod

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJSMethod, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJSMethod) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJSMethod

C++: core::scoring::epr_deer::metrics::DEERJSMethod::operator=(const class core::scoring::epr_deer::metrics::DEERJSMethod &) –> class core::scoring::epr_deer::metrics::DEERJSMethod &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bb(*args, **kwargs)

Overloaded function.

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use confidence bands

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb(const bool &) –> void

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether backbone expansion is being used

Whether backbone expansion is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb() const –> bool

best_fit(*args, **kwargs)

Overloaded function.

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the line of best fit

Best fit of DEER distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the best fit of the distance distribution

The best fit of the distance distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether confidence bands will be used when calculating score

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds(const bool &) –> void

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether confidence bands are being used

Whether confidence bands are being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds() const –> bool

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_prs(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, bin: int) pyrosetta.rosetta.utility.vector1_double

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

Value of r

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs(const unsigned long &) const –> class utility::vector1<double, class std::allocator<double> >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJSMethod, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERJSMethod::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

integral(*args, **kwargs)

Overloaded function.

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the integral

Whether to compute the integral

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral(const bool &) –> void

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of the integral is being used

Whether calculation of the integral is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral() const –> bool

lower_bound(*args, **kwargs)

Overloaded function.

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the lower bound/confidence band for the distance distribution

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the lower bound/confidence band for the distribution

The lower bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

reverse(*args, **kwargs)

Overloaded function.

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the reverse metric

Whether to compute the reverse metric

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse(const bool &) –> void

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether the reverse metric is being used

Whether the reverse metric is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse() const –> bool

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

singleval(*args, **kwargs)

Overloaded function.

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use a single distance

Whether to use a single distance

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval(const bool &) –> void

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of a single distance is being used

Whether calculation of a single distance is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval() const –> bool

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

upper_bound(*args, **kwargs)

Overloaded function.

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the upper bound/confidence band for the distance distribution

Lower bound or confidence band.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the upper bound/confidence band for the distribution

The upper bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJaccardMethod

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJaccardMethod, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJaccardMethod) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJaccardMethod

C++: core::scoring::epr_deer::metrics::DEERJaccardMethod::operator=(const class core::scoring::epr_deer::metrics::DEERJaccardMethod &) –> class core::scoring::epr_deer::metrics::DEERJaccardMethod &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bb(*args, **kwargs)

Overloaded function.

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use confidence bands

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb(const bool &) –> void

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether backbone expansion is being used

Whether backbone expansion is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb() const –> bool

best_fit(*args, **kwargs)

Overloaded function.

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the line of best fit

Best fit of DEER distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the best fit of the distance distribution

The best fit of the distance distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether confidence bands will be used when calculating score

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds(const bool &) –> void

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether confidence bands are being used

Whether confidence bands are being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds() const –> bool

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_prs(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, bin: int) pyrosetta.rosetta.utility.vector1_double

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

Value of r

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs(const unsigned long &) const –> class utility::vector1<double, class std::allocator<double> >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERJaccardMethod, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERJaccardMethod::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

integral(*args, **kwargs)

Overloaded function.

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the integral

Whether to compute the integral

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral(const bool &) –> void

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of the integral is being used

Whether calculation of the integral is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral() const –> bool

lower_bound(*args, **kwargs)

Overloaded function.

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the lower bound/confidence band for the distance distribution

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the lower bound/confidence band for the distribution

The lower bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

reverse(*args, **kwargs)

Overloaded function.

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the reverse metric

Whether to compute the reverse metric

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse(const bool &) –> void

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether the reverse metric is being used

Whether the reverse metric is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse() const –> bool

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

singleval(*args, **kwargs)

Overloaded function.

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use a single distance

Whether to use a single distance

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval(const bool &) –> void

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of a single distance is being used

Whether calculation of a single distance is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval() const –> bool

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

upper_bound(*args, **kwargs)

Overloaded function.

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the upper bound/confidence band for the distance distribution

Lower bound or confidence band.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the upper bound/confidence band for the distribution

The upper bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod

C++: core::scoring::epr_deer::metrics::DEERMiscMethod::operator=(const class core::scoring::epr_deer::metrics::DEERMiscMethod &) –> class core::scoring::epr_deer::metrics::DEERMiscMethod &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bb(*args, **kwargs)

Overloaded function.

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use confidence bands

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb(const bool &) –> void

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether backbone expansion is being used

Whether backbone expansion is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb() const –> bool

best_fit(*args, **kwargs)

Overloaded function.

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the line of best fit

Best fit of DEER distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the best fit of the distance distribution

The best fit of the distance distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether confidence bands will be used when calculating score

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds(const bool &) –> void

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether confidence bands are being used

Whether confidence bands are being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds() const –> bool

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_prs(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, bin: int) pyrosetta.rosetta.utility.vector1_double

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

Value of r

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs(const unsigned long &) const –> class utility::vector1<double, class std::allocator<double> >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEERMiscMethod::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

integral(*args, **kwargs)

Overloaded function.

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the integral

Whether to compute the integral

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral(const bool &) –> void

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of the integral is being used

Whether calculation of the integral is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral() const –> bool

lower_bound(*args, **kwargs)

Overloaded function.

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the lower bound/confidence band for the distance distribution

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the lower bound/confidence band for the distribution

The lower bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

mode(*args, **kwargs)

Overloaded function.

  1. mode(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod, val: str) -> None

Set mode being used to score

Mode with which to score

C++: core::scoring::epr_deer::metrics::DEERMiscMethod::mode(const std::string &) –> void

  1. mode(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERMiscMethod) -> str

Return the mode being used to score

Mode being used to score

C++: core::scoring::epr_deer::metrics::DEERMiscMethod::mode() const –> std::string

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

reverse(*args, **kwargs)

Overloaded function.

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the reverse metric

Whether to compute the reverse metric

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse(const bool &) –> void

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether the reverse metric is being used

Whether the reverse metric is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse() const –> bool

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

singleval(*args, **kwargs)

Overloaded function.

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use a single distance

Whether to use a single distance

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval(const bool &) –> void

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of a single distance is being used

Whether calculation of a single distance is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval() const –> bool

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

upper_bound(*args, **kwargs)

Overloaded function.

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the upper bound/confidence band for the distance distribution

Lower bound or confidence band.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the upper bound/confidence band for the distribution

The upper bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

class pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEEROverlapMethod

Bases: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution

append_dist_id(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, dist_id: int, dist: float) None

Append distance ID to custom distance map

Unique distance ID used in distance map

Distance value in angstroms

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::append_dist_id(unsigned long, double) –> void

assign(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEEROverlapMethod, : pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEEROverlapMethod) pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEEROverlapMethod

C++: core::scoring::epr_deer::metrics::DEEROverlapMethod::operator=(const class core::scoring::epr_deer::metrics::DEEROverlapMethod &) –> class core::scoring::epr_deer::metrics::DEEROverlapMethod &

avg_stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, histogram: pyrosetta.rosetta.std.map_unsigned_long_double) pyrosetta.rosetta.utility.vector1_double

Computes average distance of distribution for local functions

Distance distribution

Vector with two items: Average and Standard Deviation

C++: core::scoring::epr_deer::metrics::DEERData::avg_stdev(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> class utility::vector1<double, class std::allocator<double> >

bb(*args, **kwargs)

Overloaded function.

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use confidence bands

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb(const bool &) –> void

  1. bb(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether backbone expansion is being used

Whether backbone expansion is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bb() const –> bool

best_fit(*args, **kwargs)

Overloaded function.

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the line of best fit

Best fit of DEER distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. best_fit(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the best fit of the distance distribution

The best fit of the distance distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::best_fit() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

bins_per_a(*args, **kwargs)

Overloaded function.

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> int

Returns bins per angstrom for distribution (default: 2)

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a() const –> const unsigned long &

  1. bins_per_a(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: int) -> None

Set the number of bins per angstrom for the data set.

Bins per angstrom

C++: core::scoring::epr_deer::metrics::DEERData::bins_per_a(const unsigned long &) –> void

bounds(*args, **kwargs)

Overloaded function.

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether confidence bands will be used when calculating score

Whether to use confidence bands

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds(const bool &) –> void

  1. bounds(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether confidence bands are being used

Whether confidence bands are being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::bounds() const –> bool

convolute(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, distr: pyrosetta.rosetta.std.map_unsigned_long_double, std: float) pyrosetta.rosetta.std.map_unsigned_long_double

Convolute a distribution with a Gaussian of a specific width

DEER Distribution

Width of Gaussian (mean=0)

New distribution

C++: core::scoring::epr_deer::metrics::DEERData::convolute(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const double &) const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

dist_map(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) pyrosetta.rosetta.std.map_unsigned_long_double

Returns the map of distance values used for custom distributions

Map of values (indeces to distances in Angstroms)

Only works when bins_per_a set to zero!

C++: core::scoring::epr_deer::metrics::DEERData::dist_map() const –> class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > >

get_prs(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, bin: int) pyrosetta.rosetta.utility.vector1_double

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

Value of r

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::get_prs(const unsigned long &) const –> class utility::vector1<double, class std::allocator<double> >

get_score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEEROverlapMethod, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) float

Virtual function to evaluate score given a distribution

Simulated DEER distribution

Freshly computed score

C++: core::scoring::epr_deer::metrics::DEEROverlapMethod::get_score(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> double

integral(*args, **kwargs)

Overloaded function.

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the integral

Whether to compute the integral

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral(const bool &) –> void

  1. integral(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of the integral is being used

Whether calculation of the integral is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::integral() const –> bool

lower_bound(*args, **kwargs)

Overloaded function.

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the lower bound/confidence band for the distance distribution

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

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. lower_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the lower bound/confidence band for the distribution

The lower bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::lower_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &

print_histogram(*args, **kwargs)

Overloaded function.

  1. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

  2. print_histogram(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, sim_histr: pyrosetta.rosetta.std.map_unsigned_long_double, pose_name: str) -> None

Print the simulated distance distribution.

Simulated distance distribution

Name of the pose

C++: core::scoring::epr_deer::metrics::DEERData::print_histogram(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &, const std::string &) const –> void

residues(*args, **kwargs)

Overloaded function.

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t

Returns the residues involved in this data set.

Vector of residues (ID and spin label type)

Residues are saved with two parameters: the residue ID, and

the label type. Label type is set to “DEFAULT” by default. Other options include DEFAULT_FAST and CUSTOM

C++: core::scoring::epr_deer::metrics::DEERData::residues() const –> const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &

  1. residues(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: pyrosetta.rosetta.utility.vector1_std_pair_unsigned_long_std_string_t) -> None

Sets residue for data set

Vector of residues (index and spin label type)

C++: core::scoring::epr_deer::metrics::DEERData::residues(const class utility::vector1<struct std::pair<unsigned long, std::string >, class std::allocator<struct std::pair<unsigned long, std::string > > > &) –> void

reverse(*args, **kwargs)

Overloaded function.

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to compute the reverse metric

Whether to compute the reverse metric

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse(const bool &) –> void

  1. reverse(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether the reverse metric is being used

Whether the reverse metric is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::reverse() const –> bool

score(*args, **kwargs)

Overloaded function.

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the last computed score

Score (0.0 if never set)

C++: core::scoring::epr_deer::metrics::DEERData::score() const –> double

  1. score(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the score of the data set

Score to save

C++: core::scoring::epr_deer::metrics::DEERData::score(const double &) –> void

singleval(*args, **kwargs)

Overloaded function.

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: bool) -> None

Set whether to use a single distance

Whether to use a single distance

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval(const bool &) –> void

  1. singleval(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> bool

Returns whether calculation of a single distance is being used

Whether calculation of a single distance is being used

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::singleval() const –> bool

stdev(*args, **kwargs)

Overloaded function.

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData) -> float

Returns the standard deviation of the distributions to generate

deviation (in angstroms)

Function has a failsafe to avoid returning a nonzero value

C++: core::scoring::epr_deer::metrics::DEERData::stdev() const –> double

  1. stdev(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERData, val: float) -> None

Set the standard deviation of the distributions to generate

Set the standard deviation to this value

C++: core::scoring::epr_deer::metrics::DEERData::stdev(const double &) –> void

upper_bound(*args, **kwargs)

Overloaded function.

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution, val: pyrosetta.rosetta.std.map_unsigned_long_double) -> None

Sets the upper bound/confidence band for the distance distribution

Lower bound or confidence band.

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound(const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &) –> void

  1. upper_bound(self: pyrosetta.rosetta.core.scoring.epr_deer.metrics.DEERDistanceDistribution) -> pyrosetta.rosetta.std.map_unsigned_long_double

Returns the upper bound/confidence band for the distribution

The upper bound/confidence band for the distribution

C++: core::scoring::epr_deer::metrics::DEERDistanceDistribution::upper_bound() const –> const class std::map<unsigned long, double, struct std::less<unsigned long>, class std::allocator<struct std::pair<const unsigned long, double> > > &