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- builtins.object
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- Loop
- LoopCycle
- LoopGraph
- LoopScoreInfo
- rosetta.core.scoring.methods.EnergyMethodCreator(builtins.object)
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- LoopCloseEnergyCreator
- rosetta.core.scoring.methods.WholeStructureEnergy(rosetta.core.scoring.methods.EnergyMethod)
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- LoopCloseEnergy
class Loop(builtins.object) |
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Directed edge between one position in the pose to another position.
Records takeoff_pos & landing_pos (in full_model numbering).
Also records 'domain', i.e. if there are multiple poses in a collection,
which pose.
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Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(rosetta.core.scoring.loop_graph.Loop) -> NoneType
2. __init__(self : rosetta.core.scoring.loop_graph.Loop, takeoff_pos : int, landing_pos : int, takeoff_domain : int, landing_domain : int) -> NoneType
3. __init__(self : rosetta.core.scoring.loop_graph.Loop, src : rosetta.core.scoring.loop_graph.Loop) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- __str__(...) from builtins.PyCapsule
- __str__(rosetta.core.scoring.loop_graph.Loop) -> str
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.core.scoring.loop_graph.Loop, src : rosetta.core.scoring.loop_graph.Loop) -> rosetta.core.scoring.loop_graph.Loop
- landing_domain(...) from builtins.PyCapsule
- landing_domain(rosetta.core.scoring.loop_graph.Loop) -> int
- landing_pos(...) from builtins.PyCapsule
- landing_pos(rosetta.core.scoring.loop_graph.Loop) -> int
- set_landing_domain(...) from builtins.PyCapsule
- set_landing_domain(self : rosetta.core.scoring.loop_graph.Loop, setting : int) -> NoneType
- set_landing_pos(...) from builtins.PyCapsule
- set_landing_pos(self : rosetta.core.scoring.loop_graph.Loop, setting : int) -> NoneType
- set_takeoff_domain(...) from builtins.PyCapsule
- set_takeoff_domain(self : rosetta.core.scoring.loop_graph.Loop, setting : int) -> NoneType
- set_takeoff_pos(...) from builtins.PyCapsule
- set_takeoff_pos(self : rosetta.core.scoring.loop_graph.Loop, setting : int) -> NoneType
- takeoff_domain(...) from builtins.PyCapsule
- takeoff_domain(rosetta.core.scoring.loop_graph.Loop) -> int
- takeoff_pos(...) from builtins.PyCapsule
- takeoff_pos(rosetta.core.scoring.loop_graph.Loop) -> int
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class LoopCloseEnergy(rosetta.core.scoring.methods.WholeStructureEnergy) |
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- Method resolution order:
- LoopCloseEnergy
- rosetta.core.scoring.methods.WholeStructureEnergy
- rosetta.core.scoring.methods.EnergyMethod
- builtins.object
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(handle) -> NoneType
2. __init__(handle, rosetta.core.scoring.loop_graph.LoopCloseEnergy) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.core.scoring.loop_graph.LoopCloseEnergy, : rosetta.core.scoring.loop_graph.LoopCloseEnergy) -> rosetta.core.scoring.loop_graph.LoopCloseEnergy
- clone(...) from builtins.PyCapsule
- clone(rosetta.core.scoring.loop_graph.LoopCloseEnergy) -> rosetta.core.scoring.methods.EnergyMethod
clone
- eval_atom_derivative(...) from builtins.PyCapsule
- eval_atom_derivative(self : rosetta.core.scoring.loop_graph.LoopCloseEnergy, atom_id : rosetta.core.id.AtomID, pose : rosetta.core.pose.Pose, domain_map : ObjexxFCL::FArray1D<int>, : rosetta.core.scoring.ScoreFunction, weights : rosetta.core.scoring.EMapVector, F1 : rosetta.numeric.xyzVector_double_t, F2 : rosetta.numeric.xyzVector_double_t) -> NoneType
//////////////////////////////
- finalize_total_energy(...) from builtins.PyCapsule
- finalize_total_energy(self : rosetta.core.scoring.loop_graph.LoopCloseEnergy, pose : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction, totals : rosetta.core.scoring.EMapVector) -> NoneType
- indicate_required_context_graphs(...) from builtins.PyCapsule
- indicate_required_context_graphs(self : rosetta.core.scoring.loop_graph.LoopCloseEnergy, : rosetta.utility.vector1_bool) -> NoneType
- setup_for_derivatives(...) from builtins.PyCapsule
- setup_for_derivatives(self : rosetta.core.scoring.loop_graph.LoopCloseEnergy, pose : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction) -> NoneType
- setup_for_scoring(...) from builtins.PyCapsule
- setup_for_scoring(self : rosetta.core.scoring.loop_graph.LoopCloseEnergy, pose : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction) -> NoneType
//////////////////////////////////////////////////////////////////////////
Methods inherited from rosetta.core.scoring.methods.WholeStructureEnergy:
- atomic_interaction_cutoff(...) from builtins.PyCapsule
- atomic_interaction_cutoff(rosetta.core.scoring.methods.WholeStructureEnergy) -> float
how far apart must two heavy atoms be to have a zero interaction energy?
If hydrogen atoms interact at the same range as heavy atoms, then
this distance should build-in a 2 * max-bound-h-distance-cutoff buffer.
There is an improper mixing here between run-time aquired chemical knowledge
(max-bound-h-distance-cutoff) and compile time aquired scoring knowledge
(max atom cutoff); this could be resolved by adding a boolean
uses_hydrogen_interaction_distance() to the SRTBEnergy class along with
a method of the ChemicalManager max_bound_h_distance_cutoff().
This method allows the WholeStructureEnergy class to define which edges
should be included in the EnergyGraph so that during the finalize() method
the Energy class can iterate across the EnergyGraph. This iteration occurrs
in the SecondaryStructureEnergy class, where the edges must span 12 angstroms
between the centroids. Arguably, the SecondaryStructureEnergy class could use
the TwelveANeighborGraph (a context graph) and not require that the EnergyGraph
span such long distances.
- method_type(...) from builtins.PyCapsule
- method_type(rosetta.core.scoring.methods.WholeStructureEnergy) -> rosetta.core.scoring.methods.EnergyMethodType
Methods inherited from rosetta.core.scoring.methods.EnergyMethod:
- defines_high_order_terms(...) from builtins.PyCapsule
- defines_high_order_terms(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose) -> bool
Should this EnergyMethod have score and derivative evaluation
evaluated both in the context of the whole Pose and in the context
of residue or residue-pairs? This covers scoring terms like env-smooth
wherein the CBeta's get derivatives for increasing the neighbor counts
for surrounding residues, and terms like constraints, which are definable
on arbitrary number of residues (e.g. more than 2); both of these terms
could be used in RTMin, and both should use the residue and residue-pair
evaluation scheme with the MinimizationGraph for the majority of the
work they do. (Now, high-order constraints (3-body or above) will not
be properly evaluated within RTMin.). The default implementation
returns "false".
- finalize_after_derivatives(...) from builtins.PyCapsule
- finalize_after_derivatives(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction) -> NoneType
called at the end of derivatives evaluation
- minimize_in_whole_structure_context(...) from builtins.PyCapsule
- minimize_in_whole_structure_context(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose) -> bool
Should this EnergyMethod have score and derivative evaluation
evaluated only in the context of the whole Pose, or can it be included
in a decomposed manner for a residue or a set of residue-pairs that are
not part of the Pose that's serving as their context? The default
method implemented in the base class returns true in order to grandfather
in EnergyMethods that have not had their derivatives changed to take
advantage of the new derivative-evaluation machinery. Methods that return
"true" will not have their residue-energy(-ext) / residue-pair-energy(-ext)
methods invoked by the ScoreFunction during its traversal of the
MinimizationGraph, and instead will be asked to perform all their work
during finalize_total_energies(). Similarly, they will be expected to
perform all their work during eval_atom_deriv() instead of during the
ScoreFunction's traversal of the MinimizationGraph for derivative evaluation.
IMPORTANT: Methods that return "true" cannot be included in RTMin.
- prepare_rotamers_for_packing(...) from builtins.PyCapsule
- prepare_rotamers_for_packing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.conformation.RotamerSetBase) -> NoneType
If an energy method needs to cache data in a packing::RotamerSet object before
rotamer energies are calculated, it does so during this function. The packer
must ensure this function is called. The default behavior is to do nothing.
- score_types(...) from builtins.PyCapsule
- score_types(rosetta.core.scoring.methods.EnergyMethod) -> rosetta.utility.vector1_core_scoring_ScoreType
Returns the score types that this energy method computes.
- setup_for_minimizing(...) from builtins.PyCapsule
- setup_for_minimizing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction, : rosetta.core.kinematics.MinimizerMapBase) -> NoneType
Called at the beginning of atom tree minimization, this method
allows the derived class the opportunity to initialize pertinent data
that will be used during minimization. During minimzation, the chemical
structure of the pose is constant, so assumptions on the number of atoms
per residue and their identities are safe so long as the pose's Energies
object's "use_nblist()" method returns true.
- setup_for_packing(...) from builtins.PyCapsule
- setup_for_packing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.utility.vector1_bool, : rosetta.utility.vector1_bool) -> NoneType
if an energy method needs to cache data in the Energies object,
before packing begins, then it does so during this function. The packer
must ensure this function is called. The default behavior is to do nothing.
- update_residue_for_packing(...) from builtins.PyCapsule
- update_residue_for_packing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, resid : int) -> NoneType
If the pose changes in the middle of a packing (as happens in rotamer trials) and if
an energy method needs to cache data in the pose that corresponds to its current state,
then the method must update that data when this function is called. The packer must
ensure this function gets called. The default behavior is to do nothing.
- version(...) from builtins.PyCapsule
- version(rosetta.core.scoring.methods.EnergyMethod) -> int
Return the version of the energy method
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class LoopGraph(builtins.object) |
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Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(rosetta.core.scoring.loop_graph.LoopGraph) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- check_loop_cycles_are_disjoint(...) from builtins.PyCapsule
- check_loop_cycles_are_disjoint(*args, **kwargs)
Overloaded function.
1. check_loop_cycles_are_disjoint(rosetta.core.scoring.loop_graph.LoopGraph) -> NoneType
2. check_loop_cycles_are_disjoint(self : rosetta.core.scoring.loop_graph.LoopGraph, verbose : bool) -> NoneType
- has_just_simple_cycles(...) from builtins.PyCapsule
- has_just_simple_cycles(rosetta.core.scoring.loop_graph.LoopGraph) -> bool
- loop_cycles(...) from builtins.PyCapsule
- loop_cycles(rosetta.core.scoring.loop_graph.LoopGraph) -> rosetta.utility.vector1_core_scoring_loop_graph_LoopCycle
- loop_score_info(...) from builtins.PyCapsule
- loop_score_info(self : rosetta.core.scoring.loop_graph.LoopGraph, n : int) -> core::scoring::loop_graph::LoopScoreInfo
- loop_suites(...) from builtins.PyCapsule
- loop_suites(*args, **kwargs)
Overloaded function.
1. loop_suites(rosetta.core.scoring.loop_graph.LoopGraph) -> rosetta.utility.vector1_utility_vector1_unsigned_long_std_allocator_unsigned_long_t
///////////////////////////////////////////////////////////////
Returns a vector of loop_suites
If include_free_loops is turned off, loops with
takeoff_domain == 0 or landing_domain == 0 will not be included
2. loop_suites(self : rosetta.core.scoring.loop_graph.LoopGraph, include_free_loops : bool) -> rosetta.utility.vector1_utility_vector1_unsigned_long_std_allocator_unsigned_long_t
///////////////////////////////////////////////////////////////
Returns a vector of loop_suites
If include_free_loops is turned off, loops with
takeoff_domain == 0 or landing_domain == 0 will not be included
- missing_residues(...) from builtins.PyCapsule
- missing_residues(self : rosetta.core.scoring.loop_graph.LoopGraph, pose : rosetta.core.pose.Pose) -> rosetta.utility.vector1_char
- nmissing(...) from builtins.PyCapsule
- nmissing(self : rosetta.core.scoring.loop_graph.LoopGraph, pose : rosetta.core.pose.Pose) -> int
- num_loops(...) from builtins.PyCapsule
- num_loops(rosetta.core.scoring.loop_graph.LoopGraph) -> int
- set_error_out_on_complex_cycles(...) from builtins.PyCapsule
- set_error_out_on_complex_cycles(self : rosetta.core.scoring.loop_graph.LoopGraph, setting : bool) -> NoneType
- total_energy(...) from builtins.PyCapsule
- total_energy(rosetta.core.scoring.loop_graph.LoopGraph) -> float
- update(...) from builtins.PyCapsule
- update(*args, **kwargs)
Overloaded function.
1. update(self : rosetta.core.scoring.loop_graph.LoopGraph, pose : rosetta.core.pose.Pose) -> NoneType
2. update(self : rosetta.core.scoring.loop_graph.LoopGraph, pose : rosetta.core.pose.Pose, verbose : bool) -> NoneType
- update_loops(...) from builtins.PyCapsule
- update_loops(self : rosetta.core.scoring.loop_graph.LoopGraph, pose : rosetta.core.pose.Pose) -> NoneType
- update_loops_and_cycles(...) from builtins.PyCapsule
- update_loops_and_cycles(self : rosetta.core.scoring.loop_graph.LoopGraph, pose_domain_map : rosetta.utility.vector1_unsigned_long, cutpoint_open : rosetta.utility.vector1_unsigned_long) -> NoneType
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