| | |
- builtins.object
-
- ChainedSolutionList
- ClosureProblem
- ClosureSolution
- IdealParameters
- rosetta.protocols.canonical_sampling.ThermodynamicMover(rosetta.protocols.moves.Mover)
-
- BalancedKicMover
- rosetta.protocols.loop_modeling.LoopMover(rosetta.protocols.moves.Mover)
-
- KicMover
- rosetta.protocols.moves.MoverCreator(builtins.object)
-
- KicMoverCreator
class BalancedKicMover(rosetta.protocols.canonical_sampling.ThermodynamicMover) |
| |
Make a kinematic closure move that obeys detailed balance.
This class is very conceptually similar to KicMover, so check
out its documentation for a general overview of the kinematic closure
algorithm. Here I will just highlight some details associated with making
a balanced version of the move. Detailed balance is a useful property,
because it allows a Monte Carlo simulation to recapitulate ensembles with
correct equilibrium populations (so long as sampling is good, of course).
There are a two reasons why the standard KicMover algorithm does not obey
detailed balance. The first is that the geometry of the closure move
itself introduces some inherent bias which has to be explicitly canceled
out. The second is that care needs to be taken to perturb the non-pivot
torsions in a way that also obeys detailed balance, as well.
The add_perturber() method works much like it does in KicMover. The only
conceptual difference is that when the added perturbers are used internally
within apply(), perturbers::Perturber::perturb_with_balance() is called
instead of perturbers::Perturber::perturb(). This makes it easy to make
variants of the perturber algorithms which obey detailed balance. The
set_pivot_picker() method is no different from the KicMover version.
|
| |
- Method resolution order:
- BalancedKicMover
- rosetta.protocols.canonical_sampling.ThermodynamicMover
- rosetta.protocols.moves.Mover
- builtins.object
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(handle) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- add_perturber(...) from builtins.PyCapsule
- add_perturber(self : rosetta.protocols.kinematic_closure.BalancedKicMover, perturber : protocols::kinematic_closure::perturbers::Perturber) -> NoneType
KicMover::add_perturber
- apply(...) from builtins.PyCapsule
- apply(self : rosetta.protocols.kinematic_closure.BalancedKicMover, pose : rosetta.core.pose.Pose) -> NoneType
KicMover::apply
- get_name(...) from builtins.PyCapsule
- get_name(rosetta.protocols.kinematic_closure.BalancedKicMover) -> str
KicMover::get_name
- is_solution_trivial(...) from builtins.PyCapsule
- is_solution_trivial(problem : protocols::kinematic_closure::ClosureProblem, solution : protocols::kinematic_closure::ClosureSolution, unperturbed_solutions : rosetta.utility.vector1_std_shared_ptr_const_protocols_kinematic_closure_ClosureSolution_t, perturbed_solutions : rosetta.utility.vector1_std_shared_ptr_const_protocols_kinematic_closure_ClosureSolution_t) -> bool
Return true if the given solution is the same as the input pose.
This allows for a more accurate reporting of Monte Carlo statistics.
- last_proposal_density_ratio(...) from builtins.PyCapsule
- last_proposal_density_ratio(rosetta.protocols.kinematic_closure.BalancedKicMover) -> float
Right now the proposal probabilities are balanced internally, so
this ratio will always be unity. This could change eventually, though.
- pick_solution(...) from builtins.PyCapsule
- pick_solution(unperturbed_solutions : rosetta.utility.vector1_std_shared_ptr_const_protocols_kinematic_closure_ClosureSolution_t, perturbed_solutions : rosetta.utility.vector1_std_shared_ptr_const_protocols_kinematic_closure_ClosureSolution_t) -> protocols::kinematic_closure::ClosureSolution
Pick a solution in a way that cancels out the geometrical bias of
the kinematic closure algorithm.
- preserve_detailed_balance(...) from builtins.PyCapsule
- preserve_detailed_balance(rosetta.protocols.kinematic_closure.BalancedKicMover) -> bool
Return true, because this mover always obeys detailed balance.
- set_loop(...) from builtins.PyCapsule
- set_loop(self : rosetta.protocols.kinematic_closure.BalancedKicMover, loop : rosetta.protocols.loops.Loop) -> NoneType
KicMover::set_loop
- set_pivot_picker(...) from builtins.PyCapsule
- set_pivot_picker(self : rosetta.protocols.kinematic_closure.BalancedKicMover, picker : protocols::kinematic_closure::pivot_pickers::PivotPicker) -> NoneType
KicMover::set_pivot_picker
- set_preserve_detailed_balance(...) from builtins.PyCapsule
- set_preserve_detailed_balance(self : rosetta.protocols.kinematic_closure.BalancedKicMover, : bool) -> NoneType
This mover always obeys detailed balance, so this is a no-op.
- torsion_id_ranges(...) from builtins.PyCapsule
- torsion_id_ranges(self : rosetta.protocols.kinematic_closure.BalancedKicMover, pose : rosetta.core.pose.Pose) -> rosetta.utility.vector1_core_id_TorsionID_Range
Indicate that each torsion in the loop may take on any value.
Methods inherited from rosetta.protocols.canonical_sampling.ThermodynamicMover:
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.canonical_sampling.ThermodynamicMover, : rosetta.protocols.canonical_sampling.ThermodynamicMover) -> rosetta.protocols.canonical_sampling.ThermodynamicMover
- finalize_simulation(...) from builtins.PyCapsule
- finalize_simulation(self : rosetta.protocols.canonical_sampling.ThermodynamicMover, pose : rosetta.core.pose.Pose, metropolis_hastings_mover : protocols::canonical_sampling::MetropolisHastingsMover) -> NoneType
Callback executed after all Monte Carlo trials are completed.
- initialize_simulation(...) from builtins.PyCapsule
- initialize_simulation(self : rosetta.protocols.canonical_sampling.ThermodynamicMover, pose : rosetta.core.pose.Pose, metropolis_hastings_mover : protocols::canonical_sampling::MetropolisHastingsMover, cycle : int) -> NoneType
Callback executed before any Monte Carlo trials are attempted.
- is_multi_trial(...) from builtins.PyCapsule
- is_multi_trial(rosetta.protocols.canonical_sampling.ThermodynamicMover) -> bool
Return true if the move performs multiple trials on each apply.
last_inner_score_delta_over_temperature()
metropolis_hastings_mover()
set_metropolis_hastings_mover()
- last_inner_score_delta_over_temperature(...) from builtins.PyCapsule
- last_inner_score_delta_over_temperature(rosetta.protocols.canonical_sampling.ThermodynamicMover) -> float
If this is a multi-trial move, return the change in internal
score/temperature caused by the last call to apply().
is_multi_trial()
- metropolis_hastings_mover(...) from builtins.PyCapsule
- metropolis_hastings_mover(rosetta.protocols.canonical_sampling.ThermodynamicMover) -> rosetta.std.weak_ptr_protocols_canonical_sampling_MetropolisHastingsMover_t
If this is a multi-trial move, return the MetropolisHastingsMover
being used internally.
is_multi_trial()
- observe_after_metropolis(...) from builtins.PyCapsule
- observe_after_metropolis(self : rosetta.protocols.canonical_sampling.ThermodynamicMover, metropolis_hastings_mover : protocols::canonical_sampling::MetropolisHastingsMover) -> NoneType
Callback executed after the Metropolis criterion is evaluated.
- set_metropolis_hastings_mover(...) from builtins.PyCapsule
- set_metropolis_hastings_mover(self : rosetta.protocols.canonical_sampling.ThermodynamicMover, metropolis_hastings_mover : rosetta.std.weak_ptr_protocols_canonical_sampling_MetropolisHastingsMover_t) -> NoneType
If this is a multi-trial move, set the MetropolisHastingsMover to
be used internally.
is_multi_trial()
Methods inherited from rosetta.protocols.moves.Mover:
- clear_info(...) from builtins.PyCapsule
- clear_info(rosetta.protocols.moves.Mover) -> NoneType
Strings container can be used to return miscellaneous info (as std::string) from a mover, such as notes about the results of apply(). The job distributor (Apr 09 vintage) will check this function to see if your protocol wants to add string info to the Job that ran this mover. One way this can be useful is that later, a JobOutputter may include/append this info to an output file.
clear_info is called by jd2 before calling apply
- clone(...) from builtins.PyCapsule
- clone(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
Return a clone of the Mover object.
- create(...) from builtins.PyCapsule
- create(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
- fresh_instance(...) from builtins.PyCapsule
- fresh_instance(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
Generates a new Mover object freshly created with the default ctor.
- get_additional_output(...) from builtins.PyCapsule
- get_additional_output(rosetta.protocols.moves.Mover) -> rosetta.core.pose.Pose
fpd
Mechanism by which a mover may return multiple output poses from a single input pose.
- get_current_job(...) from builtins.PyCapsule
- get_current_job(rosetta.protocols.moves.Mover) -> protocols::jobdist::BasicJob
- get_current_tag(...) from builtins.PyCapsule
- get_current_tag(rosetta.protocols.moves.Mover) -> str
A tag is a unique identifier used to identify structures produced
by this Mover. get_current_tag() returns the tag, and set_current_tag( std::string tag )
sets the tag. This functionality is not intended for use with the 2008 job distributor.
- get_input_pose(...) from builtins.PyCapsule
- get_input_pose(rosetta.protocols.moves.Mover) -> rosetta.core.pose.Pose
- get_last_move_status(...) from builtins.PyCapsule
- get_last_move_status(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.MoverStatus
returns status after an apply(). The job distributor (august 08 vintage) will check this function to see if your protocol wants to filter its results - if your protocol wants to say "that run was no good, skip it" then use the protected last_move_status(MoverStatus) to change the value that this function will return.
- get_native_pose(...) from builtins.PyCapsule
- get_native_pose(rosetta.protocols.moves.Mover) -> rosetta.core.pose.Pose
- get_self_ptr(...) from builtins.PyCapsule
- get_self_ptr(*args, **kwargs)
Overloaded function.
1. get_self_ptr(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
2. get_self_ptr(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
- get_self_weak_ptr(...) from builtins.PyCapsule
- get_self_weak_ptr(*args, **kwargs)
Overloaded function.
1. get_self_weak_ptr(rosetta.protocols.moves.Mover) -> rosetta.std.weak_ptr_const_protocols_moves_Mover_t
2. get_self_weak_ptr(rosetta.protocols.moves.Mover) -> rosetta.std.weak_ptr_protocols_moves_Mover_t
- get_type(...) from builtins.PyCapsule
- get_type(rosetta.protocols.moves.Mover) -> str
- info(...) from builtins.PyCapsule
- info(*args, **kwargs)
Overloaded function.
1. info(rosetta.protocols.moves.Mover) -> rosetta.std.list_std_string_std_allocator_std_string_t
non-const accessor
2. info(rosetta.protocols.moves.Mover) -> rosetta.std.list_std_string_std_allocator_std_string_t
const accessor
- name(...) from builtins.PyCapsule
- name() -> str
- register_options(...) from builtins.PyCapsule
- register_options(*args, **kwargs)
Overloaded function.
1. register_options() -> NoneType
Overload this static method if you access options within the mover.
These options will end up in -help of your application if users of this mover call register_options.
Do this recursively!
If you use movers within your mover, call their register_options in your register_options() method.
2. register_options() -> NoneType
3. register_options() -> NoneType
4. register_options() -> NoneType
5. register_options() -> NoneType
6. register_options() -> NoneType
7. register_options() -> NoneType
8. register_options() -> NoneType
9. register_options() -> NoneType
Associates relevant options with the AntibodyModeler class
10. register_options() -> NoneType
Associates relevant options with the AntibodyModeler class
11. register_options() -> NoneType
Associates relevant options with the SnugDock class
12. register_options() -> NoneType
Associates relevant options with the SnugDockProtocol class
13. register_options() -> NoneType
Register the options used by this mover with the global options
system.
14. register_options() -> NoneType
15. register_options() -> NoneType
Associate relevant options with the TemperedDocking class.
16. register_options() -> NoneType
17. register_options() -> NoneType
18. register_options() -> NoneType
Associates relevant options with the TemperedDocking class.
19. register_options() -> NoneType
20. register_options() -> NoneType
Associates relevant options with the ConstraintSetMover class
21. register_options() -> NoneType
22. register_options() -> NoneType
Associates relevant options with the DockingInitialPerturbation class
23. register_options() -> NoneType
Associates relevant options with the DockingProtocol class
24. register_options() -> NoneType
Associates relevant options with the TemperedDocking class
25. register_options() -> NoneType
26. register_options() -> NoneType
27. register_options() -> NoneType
28. register_options() -> NoneType
register options
29. register_options() -> NoneType
30. register_options() -> NoneType
Registers applicable options
31. register_options() -> NoneType
Register options with the option system.
32. register_options() -> NoneType
33. register_options() -> NoneType
34. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycle class
35. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycleContainer class
36. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycle class
37. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycle class
38. register_options() -> NoneType
39. register_options() -> NoneType
Register options with the option system.
40. register_options() -> NoneType
- reinitialize_for_each_job(...) from builtins.PyCapsule
- reinitialize_for_each_job(rosetta.protocols.moves.Mover) -> bool
Inform the Job Distributor (August '08 vintage) whether this object needs to be freshly regenerated on
each use.
- reinitialize_for_new_input(...) from builtins.PyCapsule
- reinitialize_for_new_input(rosetta.protocols.moves.Mover) -> bool
Inform the Job Distributor (August '08 vintage) whether this object needs to be regenerated when the input
pose is about to change, (for example, if the Mover has special code on the first apply() that is only valid for
that one input pose).
- reset_status(...) from builtins.PyCapsule
- reset_status(rosetta.protocols.moves.Mover) -> NoneType
resets status to SUCCESS, meant to be used before an apply(). The job distributor (august 08 vintage) uses this to ensure non-accumulation of status across apply()s.
- set_current_job(...) from builtins.PyCapsule
- set_current_job(self : rosetta.protocols.moves.Mover, job : protocols::jobdist::BasicJob) -> NoneType
////////////////////////////end Job Distributor interface////////////////////////////////////////
- set_current_tag(...) from builtins.PyCapsule
- set_current_tag(self : rosetta.protocols.moves.Mover, new_tag : str) -> NoneType
- set_input_pose(...) from builtins.PyCapsule
- set_input_pose(self : rosetta.protocols.moves.Mover, pose : rosetta.core.pose.Pose) -> NoneType
setter for poses contained for rms
- set_native_pose(...) from builtins.PyCapsule
- set_native_pose(self : rosetta.protocols.moves.Mover, pose : rosetta.core.pose.Pose) -> NoneType
setter for native poses contained for rms ---- we should get rid of this method? it is widely used, but a bit unsafe
- set_type(...) from builtins.PyCapsule
- set_type(self : rosetta.protocols.moves.Mover, setting : str) -> NoneType
- test_move(...) from builtins.PyCapsule
- test_move(self : rosetta.protocols.moves.Mover, pose : rosetta.core.pose.Pose) -> NoneType
: Unit test support function. Apply one move to a given pose.
Allows extra test specific functions to be called before applying
- type(...) from builtins.PyCapsule
- type(*args, **kwargs)
Overloaded function.
1. type(rosetta.protocols.moves.Mover) -> str
2. type(self : rosetta.protocols.moves.Mover, type_in : str) -> NoneType
|
class ClosureProblem(builtins.object) |
| |
Represent and solve a kinematic closure problem.
A number of parameters are needed to define a kinematic closure
problem. These parameters include a region of the protein backbone, a set
of pivot residues, and a new set of torsion angles for the nonpivot
residues. All of this can be specified using the frame() and
methods. Once that has been done, the solve() method can be called to
return the complete set of backbone conformations consistent with the given
parameters. These conformations are represented by the ClosureSolution
class. The restore() method can be used to undo a solution once it has
been applied, which is useful in some Monte Carlo schemes.
|
| |
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(rosetta.protocols.kinematic_closure.ClosureProblem) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- c_n(...) from builtins.PyCapsule
- c_n(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int) -> float
Return the current value of the given C-N bond length.
- c_n_ca(...) from builtins.PyCapsule
- c_n_ca(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, unit : rosetta.numeric.conversions.AngleUnit) -> float
Return the current value of the given C-N-CA bond angle.
- ca_c(...) from builtins.PyCapsule
- ca_c(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int) -> float
Return the current value of the given CA-C bond length.
- ca_c_n(...) from builtins.PyCapsule
- ca_c_n(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, unit : rosetta.numeric.conversions.AngleUnit) -> float
Return the current value of the given CA-C-N bond angle.
- cut_residue(...) from builtins.PyCapsule
- cut_residue(rosetta.protocols.kinematic_closure.ClosureProblem) -> int
Return the index of the second pivot residue.
- first_residue(...) from builtins.PyCapsule
- first_residue(rosetta.protocols.kinematic_closure.ClosureProblem) -> int
Return the index of the first pivot residue.
- frame(...) from builtins.PyCapsule
- frame(self : rosetta.protocols.kinematic_closure.ClosureProblem, pose : rosetta.core.pose.Pose, loop : rosetta.protocols.loops.Loop, pivot_picker : protocols::kinematic_closure::pivot_pickers::PivotPicker) -> NoneType
Choose pivots and copy coordinate information into the problem.
- is_nonpivot_residue(...) from builtins.PyCapsule
- is_nonpivot_residue(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int) -> bool
Return true if the given residue is not a pivot.
- is_pivot_residue(...) from builtins.PyCapsule
- is_pivot_residue(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int) -> bool
Return true if the given residue is a pivot.
- last_residue(...) from builtins.PyCapsule
- last_residue(rosetta.protocols.kinematic_closure.ClosureProblem) -> int
Return the index of the third pivot residue.
- n_ca(...) from builtins.PyCapsule
- n_ca(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int) -> float
Return the current value of the given N-CA bond length.
- n_ca_c(...) from builtins.PyCapsule
- n_ca_c(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, unit : rosetta.numeric.conversions.AngleUnit) -> float
Return the current value of the given N-CA-C bond angle.
- nonpivot_residues(...) from builtins.PyCapsule
- nonpivot_residues(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_unsigned_long
Return the indices of every nonpivot residue in the loop.
- num_atoms(...) from builtins.PyCapsule
- num_atoms(rosetta.protocols.kinematic_closure.ClosureProblem) -> int
Return the number of atoms in the loop.
- num_residues(...) from builtins.PyCapsule
- num_residues(rosetta.protocols.kinematic_closure.ClosureProblem) -> int
Return the number of residues in the loop.
- omega(...) from builtins.PyCapsule
- omega(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, unit : rosetta.numeric.conversions.AngleUnit) -> float
Return the current value of the given omega angle.
- perturb_angles(...) from builtins.PyCapsule
- perturb_angles(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_double
Provide non-const access to the raw bond angle list.
- perturb_c_n(...) from builtins.PyCapsule
- perturb_c_n(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float) -> NoneType
Perturb the C-N bond length in the given residue.
- perturb_c_n_ca(...) from builtins.PyCapsule
- perturb_c_n_ca(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float, unit : rosetta.numeric.conversions.AngleUnit) -> NoneType
Perturb the C-N-CA bond angle in the given residue.
- perturb_ca_c(...) from builtins.PyCapsule
- perturb_ca_c(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float) -> NoneType
Perturb the CA-C bond length in the given residue.
- perturb_ca_c_n(...) from builtins.PyCapsule
- perturb_ca_c_n(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float, unit : rosetta.numeric.conversions.AngleUnit) -> NoneType
Perturb the CA-C-N bond angle in the given residue.
- perturb_lengths(...) from builtins.PyCapsule
- perturb_lengths(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_double
Provide non-const access to the raw bond length list.
- perturb_n_ca(...) from builtins.PyCapsule
- perturb_n_ca(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float) -> NoneType
Perturb the N-CA bond length in the given residue.
- perturb_n_ca_c(...) from builtins.PyCapsule
- perturb_n_ca_c(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float, unit : rosetta.numeric.conversions.AngleUnit) -> NoneType
Perturb the N-CA-C bond angle in the given residue.
- perturb_omega(...) from builtins.PyCapsule
- perturb_omega(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float, unit : rosetta.numeric.conversions.AngleUnit) -> NoneType
Perturb the given omega angle.
- perturb_phi(...) from builtins.PyCapsule
- perturb_phi(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float, unit : rosetta.numeric.conversions.AngleUnit) -> NoneType
Perturb the given phi angle.
- perturb_psi(...) from builtins.PyCapsule
- perturb_psi(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, value : float, unit : rosetta.numeric.conversions.AngleUnit) -> NoneType
Perturb the given psi angle.
- perturb_torsions(...) from builtins.PyCapsule
- perturb_torsions(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_double
Provide non-const access to the raw torsion angle list.
- phi(...) from builtins.PyCapsule
- phi(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, unit : rosetta.numeric.conversions.AngleUnit) -> float
Return the current value of the given phi angle.
- pivot_atoms(...) from builtins.PyCapsule
- pivot_atoms(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_unsigned_long
Return the indices of all three pivot atoms.
- pivot_loop(...) from builtins.PyCapsule
- pivot_loop(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.protocols.loops.Loop
Return a loop specifying the three pivot residues.
- pivot_residues(...) from builtins.PyCapsule
- pivot_residues(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_unsigned_long
Return the indices of all three pivot residues.
- psi(...) from builtins.PyCapsule
- psi(self : rosetta.protocols.kinematic_closure.ClosureProblem, residue : int, unit : rosetta.numeric.conversions.AngleUnit) -> float
Return the current value of the given psi angle.
- residues(...) from builtins.PyCapsule
- residues(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_unsigned_long
Return the indices of every residue in the loop.
- restore(...) from builtins.PyCapsule
- restore(self : rosetta.protocols.kinematic_closure.ClosureProblem, pose : rosetta.core.pose.Pose) -> NoneType
Undo any changes made to the pose during the last move.
- solve(...) from builtins.PyCapsule
- solve(rosetta.protocols.kinematic_closure.ClosureProblem) -> rosetta.utility.vector1_std_shared_ptr_const_protocols_kinematic_closure_ClosureSolution_t
Return every possible solution to this problem.
|
class ClosureSolution(builtins.object) |
| |
Represent a single solution to a kinematic closure problem.
The ClosureSolution class represents the solutions returned by
ClosureProblem.solve(). The most important methods of this class are
apply() and apply_if_reasonable(). The former unconditionally applies the
solution to the given pose, while the latter does so only if the solution
passes a rama and bump check.
|
| |
Methods defined here:
- __init__(self, /, *args, **kwargs)
- Initialize self. See help(type(self)) for accurate signature.
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- apply(...) from builtins.PyCapsule
- apply(self : rosetta.protocols.kinematic_closure.ClosureSolution, pose : rosetta.core.pose.Pose) -> NoneType
Apply this solution to the given pose.
- apply_if_reasonable(...) from builtins.PyCapsule
- apply_if_reasonable(*args, **kwargs)
Overloaded function.
1. apply_if_reasonable(self : rosetta.protocols.kinematic_closure.ClosureSolution, pose : rosetta.core.pose.Pose) -> bool
If this solution passes rama and bump checks, apply it to the
given pose. Return whether or not the filters were passed.
2. apply_if_reasonable(self : rosetta.protocols.kinematic_closure.ClosureSolution, pose : rosetta.core.pose.Pose, rama_on : bool) -> bool
If this solution passes rama and bump checks, apply it to the
given pose. Return whether or not the filters were passed.
3. apply_if_reasonable(self : rosetta.protocols.kinematic_closure.ClosureSolution, pose : rosetta.core.pose.Pose, rama_on : bool, bump_on : bool) -> bool
If this solution passes rama and bump checks, apply it to the
given pose. Return whether or not the filters were passed.
4. apply_if_reasonable(self : rosetta.protocols.kinematic_closure.ClosureSolution, pose : rosetta.core.pose.Pose, rama_on : bool, bump_on : bool, be_lenient : bool) -> bool
If this solution passes rama and bump checks, apply it to the
given pose. Return whether or not the filters were passed.
- get_distance(...) from builtins.PyCapsule
- get_distance(self : rosetta.protocols.kinematic_closure.ClosureSolution, problem : rosetta.protocols.kinematic_closure.ClosureProblem) -> float
@ brief Return a distance metric indicating how similar this solution
is to the given problem.
- get_index(...) from builtins.PyCapsule
- get_index(rosetta.protocols.kinematic_closure.ClosureSolution) -> int
Return a unique number identifying this solution.
- get_jacobian(...) from builtins.PyCapsule
- get_jacobian(rosetta.protocols.kinematic_closure.ClosureSolution) -> float
Return the Jacobian for this solution.
|
class IdealParameters(builtins.object) |
| |
Catalog ideal geometries for a number of different lengths, angles,
and torsions.
This class should definitely not exist. It is basically just a
bunch of magic numbers that must exist somewhere in the database already.
Unfortunately, I can't find them and so we're stuck with this nonsense.
|
| |
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(rosetta.protocols.kinematic_closure.IdealParameters) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
|
class KicMover(rosetta.protocols.loop_modeling.LoopMover) |
| |
Find a new backbone conformation for some region of a protein.
The first step in the kinematic closure algorithm is to pick a
loop and three pivot residues. Any residues in the loop that are not
pivots are called non-pivots. The non-pivot backbone torsions are used to
make new conformations, while the pivot torsions are used to ensure that
the backbone stays closed. Use set_loops() to specify loops to sample.
Use set_pivot_picker() to specify how the pivots should be chosen. Use
add_perturber() to specify how the non-pivots should be sampled. By
default, the algorithm will pick pivots randomly within the region being
sampled and will sample the non-pivot torsions from a rama distribution.
Given a set of pivot residues and nonpivot torsion angles, the algorithm
will find up to 16 possible solutions. The set_solution_picker() method
allows you to control which solution, if any, is picked. By default, the
first solution found which passes both a rama and a bump check is used.
The default kinematic closure algorithm samples both pivot and
nonpivot torsions from a rama distribution. Because this algorithm is
often used in situations where the score function also contains a rama
term, the rama bias is usually double-counted. This is bad, because it
means that backbone torsions are normally sampled too narrowly. There are
two proper ways to deal with this, but they both have drawbacks. The first
would be to sample from a uniform distribution and to let the score
function take care of preferring angles that fit the rama distribution.
Unfortunately, this would be much less efficient than the current approach,
primarily because the rama check is fast and filters out a lot of bad
solutions. The second approach would be to sample from a rama distribution
and to remove the rama term from the score function. This would be even
more efficient than the current approach, but it would be prone to bugs
because other parts of the code wouldn't expect the score function to be
changing on every invocation of KIC.
Once the algorithm has been setup using the helper methods described above,
apply() can be called to actually sample a new backbone conformation.
|
| |
- Method resolution order:
- KicMover
- rosetta.protocols.loop_modeling.LoopMover
- rosetta.protocols.moves.Mover
- builtins.object
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(handle) -> NoneType
2. __init__(handle, rosetta.protocols.kinematic_closure.KicMover) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- add_perturber(...) from builtins.PyCapsule
- add_perturber(self : rosetta.protocols.kinematic_closure.KicMover, perturber : protocols::kinematic_closure::perturbers::Perturber) -> NoneType
Specify how the non-pivot torsions should be sampled.
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.kinematic_closure.KicMover, : rosetta.protocols.kinematic_closure.KicMover) -> rosetta.protocols.kinematic_closure.KicMover
- clear_perturbers(...) from builtins.PyCapsule
- clear_perturbers(rosetta.protocols.kinematic_closure.KicMover) -> NoneType
Forget any perturbers that had been previously added.
- get_children_names(...) from builtins.PyCapsule
- get_children_names(*args, **kwargs)
Overloaded function.
1. get_children_names(self : rosetta.protocols.kinematic_closure.KicMover, names : rosetta.utility.vector1_std_string) -> NoneType
LoopMover::get_children_names
2. get_children_names(self : rosetta.protocols.kinematic_closure.KicMover, names : rosetta.utility.vector1_std_string, indent : str) -> NoneType
LoopMover::get_children_names
- get_name(...) from builtins.PyCapsule
- get_name(rosetta.protocols.kinematic_closure.KicMover) -> str
Return the name of this mover.
- get_pivot_picker(...) from builtins.PyCapsule
- get_pivot_picker(rosetta.protocols.kinematic_closure.KicMover) -> protocols::kinematic_closure::pivot_pickers::PivotPicker
Return the PivotPicker being used by this mover.
- get_solution_picker(...) from builtins.PyCapsule
- get_solution_picker(rosetta.protocols.kinematic_closure.KicMover) -> protocols::kinematic_closure::solution_pickers::SolutionPicker
Return the SolutionPicker being used by this mover.
- request_fold_tree(...) from builtins.PyCapsule
- request_fold_tree(rosetta.protocols.kinematic_closure.KicMover) -> rosetta.protocols.loop_modeling.FoldTreeRequest
LoopMover::request_fold_tree
- set_pivot_picker(...) from builtins.PyCapsule
- set_pivot_picker(self : rosetta.protocols.kinematic_closure.KicMover, picker : protocols::kinematic_closure::pivot_pickers::PivotPicker) -> NoneType
Specify how the pivot residues should be chosen.
- set_solution_picker(...) from builtins.PyCapsule
- set_solution_picker(self : rosetta.protocols.kinematic_closure.KicMover, picker : protocols::kinematic_closure::solution_pickers::SolutionPicker) -> NoneType
Specify how a solution should be chosen.
Methods inherited from rosetta.protocols.loop_modeling.LoopMover:
- apply(...) from builtins.PyCapsule
- apply(self : rosetta.protocols.loop_modeling.LoopMover, pose : rosetta.core.pose.Pose) -> NoneType
Sample the pose in the regions specified by get_loops().
The parent class apply() method automatically sets up a fold
tree (if necessary) and keeps track of whether or not the move succeeded.
Child classes should reimplement do_apply() instead of this method.
- get_loop(...) from builtins.PyCapsule
- get_loop(self : rosetta.protocols.loop_modeling.LoopMover, index : int) -> rosetta.protocols.loops.Loop
Return the specified loop.
- get_loops(...) from builtins.PyCapsule
- get_loops(*args, **kwargs)
Overloaded function.
1. get_loops(rosetta.protocols.loop_modeling.LoopMover) -> rosetta.protocols.loops.Loops
Return the loops to be sampled on the next call to apply().
2. get_loops(rosetta.protocols.loop_modeling.LoopMover) -> rosetta.protocols.loops.Loops
Return the loops to be sampled on the next call to apply().
- set_loop(...) from builtins.PyCapsule
- set_loop(self : rosetta.protocols.loop_modeling.LoopMover, loop : rosetta.protocols.loops.Loop) -> NoneType
Set the loop to be sampled on the next call to apply().
- set_loops(...) from builtins.PyCapsule
- set_loops(*args, **kwargs)
Overloaded function.
1. set_loops(self : rosetta.protocols.loop_modeling.LoopMover, loops : rosetta.protocols.loops.Loops) -> NoneType
Set the loops to be sampled on the next call to apply().
2. set_loops(self : rosetta.protocols.loop_modeling.LoopMover, loops : rosetta.protocols.loops.Loops) -> NoneType
Set the loops to be sampled on the next call to apply().
- setup_fold_tree(...) from builtins.PyCapsule
- setup_fold_tree(pose : rosetta.core.pose.Pose, loops : rosetta.protocols.loops.Loops, request : rosetta.protocols.loop_modeling.FoldTreeRequest) -> NoneType
Setup the given pose with a fold tree that is compatible with the
given loops and requests.
- trust_fold_tree(...) from builtins.PyCapsule
- trust_fold_tree(rosetta.protocols.loop_modeling.LoopMover) -> NoneType
Promise that the calling code will setup a fold tree compatible
with request_fold_tree(). If this method is not called, this mover will
setup a fold tree on its own every time apply() is called.
- was_successful(...) from builtins.PyCapsule
- was_successful(rosetta.protocols.loop_modeling.LoopMover) -> bool
Return true if the previous move was successful.
Methods inherited from rosetta.protocols.moves.Mover:
- clear_info(...) from builtins.PyCapsule
- clear_info(rosetta.protocols.moves.Mover) -> NoneType
Strings container can be used to return miscellaneous info (as std::string) from a mover, such as notes about the results of apply(). The job distributor (Apr 09 vintage) will check this function to see if your protocol wants to add string info to the Job that ran this mover. One way this can be useful is that later, a JobOutputter may include/append this info to an output file.
clear_info is called by jd2 before calling apply
- clone(...) from builtins.PyCapsule
- clone(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
Return a clone of the Mover object.
- create(...) from builtins.PyCapsule
- create(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
- fresh_instance(...) from builtins.PyCapsule
- fresh_instance(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
Generates a new Mover object freshly created with the default ctor.
- get_additional_output(...) from builtins.PyCapsule
- get_additional_output(rosetta.protocols.moves.Mover) -> rosetta.core.pose.Pose
fpd
Mechanism by which a mover may return multiple output poses from a single input pose.
- get_current_job(...) from builtins.PyCapsule
- get_current_job(rosetta.protocols.moves.Mover) -> protocols::jobdist::BasicJob
- get_current_tag(...) from builtins.PyCapsule
- get_current_tag(rosetta.protocols.moves.Mover) -> str
A tag is a unique identifier used to identify structures produced
by this Mover. get_current_tag() returns the tag, and set_current_tag( std::string tag )
sets the tag. This functionality is not intended for use with the 2008 job distributor.
- get_input_pose(...) from builtins.PyCapsule
- get_input_pose(rosetta.protocols.moves.Mover) -> rosetta.core.pose.Pose
- get_last_move_status(...) from builtins.PyCapsule
- get_last_move_status(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.MoverStatus
returns status after an apply(). The job distributor (august 08 vintage) will check this function to see if your protocol wants to filter its results - if your protocol wants to say "that run was no good, skip it" then use the protected last_move_status(MoverStatus) to change the value that this function will return.
- get_native_pose(...) from builtins.PyCapsule
- get_native_pose(rosetta.protocols.moves.Mover) -> rosetta.core.pose.Pose
- get_self_ptr(...) from builtins.PyCapsule
- get_self_ptr(*args, **kwargs)
Overloaded function.
1. get_self_ptr(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
2. get_self_ptr(rosetta.protocols.moves.Mover) -> rosetta.protocols.moves.Mover
- get_self_weak_ptr(...) from builtins.PyCapsule
- get_self_weak_ptr(*args, **kwargs)
Overloaded function.
1. get_self_weak_ptr(rosetta.protocols.moves.Mover) -> rosetta.std.weak_ptr_const_protocols_moves_Mover_t
2. get_self_weak_ptr(rosetta.protocols.moves.Mover) -> rosetta.std.weak_ptr_protocols_moves_Mover_t
- get_type(...) from builtins.PyCapsule
- get_type(rosetta.protocols.moves.Mover) -> str
- info(...) from builtins.PyCapsule
- info(*args, **kwargs)
Overloaded function.
1. info(rosetta.protocols.moves.Mover) -> rosetta.std.list_std_string_std_allocator_std_string_t
non-const accessor
2. info(rosetta.protocols.moves.Mover) -> rosetta.std.list_std_string_std_allocator_std_string_t
const accessor
- last_proposal_density_ratio(...) from builtins.PyCapsule
- last_proposal_density_ratio(rosetta.protocols.moves.Mover) -> float
- name(...) from builtins.PyCapsule
- name() -> str
- register_options(...) from builtins.PyCapsule
- register_options(*args, **kwargs)
Overloaded function.
1. register_options() -> NoneType
Overload this static method if you access options within the mover.
These options will end up in -help of your application if users of this mover call register_options.
Do this recursively!
If you use movers within your mover, call their register_options in your register_options() method.
2. register_options() -> NoneType
3. register_options() -> NoneType
4. register_options() -> NoneType
5. register_options() -> NoneType
6. register_options() -> NoneType
7. register_options() -> NoneType
8. register_options() -> NoneType
9. register_options() -> NoneType
Associates relevant options with the AntibodyModeler class
10. register_options() -> NoneType
Associates relevant options with the AntibodyModeler class
11. register_options() -> NoneType
Associates relevant options with the SnugDock class
12. register_options() -> NoneType
Associates relevant options with the SnugDockProtocol class
13. register_options() -> NoneType
Register the options used by this mover with the global options
system.
14. register_options() -> NoneType
15. register_options() -> NoneType
Associate relevant options with the TemperedDocking class.
16. register_options() -> NoneType
17. register_options() -> NoneType
18. register_options() -> NoneType
Associates relevant options with the TemperedDocking class.
19. register_options() -> NoneType
20. register_options() -> NoneType
Associates relevant options with the ConstraintSetMover class
21. register_options() -> NoneType
22. register_options() -> NoneType
Associates relevant options with the DockingInitialPerturbation class
23. register_options() -> NoneType
Associates relevant options with the DockingProtocol class
24. register_options() -> NoneType
Associates relevant options with the TemperedDocking class
25. register_options() -> NoneType
26. register_options() -> NoneType
27. register_options() -> NoneType
28. register_options() -> NoneType
register options
29. register_options() -> NoneType
30. register_options() -> NoneType
Registers applicable options
31. register_options() -> NoneType
Register options with the option system.
32. register_options() -> NoneType
33. register_options() -> NoneType
34. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycle class
35. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycleContainer class
36. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycle class
37. register_options() -> NoneType
Associates relevant options with the LoopRefineInnerCycle class
38. register_options() -> NoneType
39. register_options() -> NoneType
Register options with the option system.
40. register_options() -> NoneType
- reinitialize_for_each_job(...) from builtins.PyCapsule
- reinitialize_for_each_job(rosetta.protocols.moves.Mover) -> bool
Inform the Job Distributor (August '08 vintage) whether this object needs to be freshly regenerated on
each use.
- reinitialize_for_new_input(...) from builtins.PyCapsule
- reinitialize_for_new_input(rosetta.protocols.moves.Mover) -> bool
Inform the Job Distributor (August '08 vintage) whether this object needs to be regenerated when the input
pose is about to change, (for example, if the Mover has special code on the first apply() that is only valid for
that one input pose).
- reset_status(...) from builtins.PyCapsule
- reset_status(rosetta.protocols.moves.Mover) -> NoneType
resets status to SUCCESS, meant to be used before an apply(). The job distributor (august 08 vintage) uses this to ensure non-accumulation of status across apply()s.
- set_current_job(...) from builtins.PyCapsule
- set_current_job(self : rosetta.protocols.moves.Mover, job : protocols::jobdist::BasicJob) -> NoneType
////////////////////////////end Job Distributor interface////////////////////////////////////////
- set_current_tag(...) from builtins.PyCapsule
- set_current_tag(self : rosetta.protocols.moves.Mover, new_tag : str) -> NoneType
- set_input_pose(...) from builtins.PyCapsule
- set_input_pose(self : rosetta.protocols.moves.Mover, pose : rosetta.core.pose.Pose) -> NoneType
setter for poses contained for rms
- set_native_pose(...) from builtins.PyCapsule
- set_native_pose(self : rosetta.protocols.moves.Mover, pose : rosetta.core.pose.Pose) -> NoneType
setter for native poses contained for rms ---- we should get rid of this method? it is widely used, but a bit unsafe
- set_type(...) from builtins.PyCapsule
- set_type(self : rosetta.protocols.moves.Mover, setting : str) -> NoneType
- test_move(...) from builtins.PyCapsule
- test_move(self : rosetta.protocols.moves.Mover, pose : rosetta.core.pose.Pose) -> NoneType
: Unit test support function. Apply one move to a given pose.
Allows extra test specific functions to be called before applying
- type(...) from builtins.PyCapsule
- type(*args, **kwargs)
Overloaded function.
1. type(rosetta.protocols.moves.Mover) -> str
2. type(self : rosetta.protocols.moves.Mover, type_in : str) -> NoneType
|
|