metrics¶

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

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

Bases: 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.

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

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.

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

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.

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 &

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.

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

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.

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

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.

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

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.

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

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 > > > &

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.

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

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.

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

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.

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

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.

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

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.

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

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_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.

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 &

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.

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

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.

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

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 > > > &

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.

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

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.

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

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: 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.

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

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.

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 &

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.

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 &

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.

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 &

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.

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

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.

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 &

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.

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

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 > > > &

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.

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

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.

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

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.

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

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 &

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.

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>

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.

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

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 > > > &

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.

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

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.

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

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.

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 &

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: 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.

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

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.

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

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.

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 &

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.

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

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.

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

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.

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

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.

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

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 > > > &

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.

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

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.

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

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.

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

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.

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

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.

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

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: 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.

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

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.

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

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.

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 &

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.

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

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.

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

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.

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

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.

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

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 > > > &

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.

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

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.

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

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.

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

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.

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

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.

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

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: 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.

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

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.

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

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.

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 &

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.

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

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.

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

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.

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

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.

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

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 > > > &

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.

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

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.

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

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.

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

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.

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

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.

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

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: 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.

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

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.

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

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.

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 &

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.

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

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.

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

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.

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

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.

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

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.

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

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 > > > &

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.

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

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.

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

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.

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

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.

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

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.

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

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: 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.

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

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.

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

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.

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 &

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.

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

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.

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

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.

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

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.

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

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 > > > &

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.

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

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.

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

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.

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

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.

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

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.

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

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> > > &