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- rosetta.protocols.loop_modeling.LoopMover(rosetta.protocols.moves.Mover)
-
- MinimizationRefiner
- RepackingRefiner
- RotamerTrialsRefiner
- rosetta.protocols.moves.MoverCreator(builtins.object)
-
- MinimizationRefinerCreator
- RepackingRefinerCreator
- RotamerTrialsRefinerCreator
class MinimizationRefiner(rosetta.protocols.loop_modeling.LoopMover) |
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Refine sampled loops using gradient minimization.
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- Method resolution order:
- MinimizationRefiner
- 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
doc
2. __init__(handle, bool) -> NoneType
doc
3. __init__(self : handle, cartesian : bool, options : rosetta.core.optimization.MinimizerOptions) -> NoneType
4. __init__(handle, rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> 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.protocols.loop_modeling.refiners.MinimizationRefiner, : rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> rosetta.protocols.loop_modeling.refiners.MinimizationRefiner
- get_min_options(...) from builtins.PyCapsule
- get_min_options(*args, **kwargs)
Overloaded function.
1. get_min_options(rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> rosetta.core.optimization.MinimizerOptions
Non-const access to the minimizer options. May be NULL.
2. get_min_options(rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> rosetta.core.optimization.MinimizerOptions
Const access to the minimizer options. May be NULL.
- get_name(...) from builtins.PyCapsule
- get_name(rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> str
LoopMover::get_name
- get_score_function(...) from builtins.PyCapsule
- get_score_function(rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> rosetta.core.scoring.ScoreFunction
Get the score function to be used on the next call to apply().
- set_min_options(...) from builtins.PyCapsule
- set_min_options(self : rosetta.protocols.loop_modeling.refiners.MinimizationRefiner, options : rosetta.core.optimization.MinimizerOptions) -> NoneType
Set the minimizer options.
- set_score_function(...) from builtins.PyCapsule
- set_score_function(self : rosetta.protocols.loop_modeling.refiners.MinimizationRefiner, score_function : rosetta.core.scoring.ScoreFunction) -> NoneType
Set the score function to be used on the next call to apply().
- use_cartesian(...) from builtins.PyCapsule
- use_cartesian(*args, **kwargs)
Overloaded function.
1. use_cartesian(self : rosetta.protocols.loop_modeling.refiners.MinimizationRefiner, setting : bool) -> NoneType
Specify whether or not Cartesian minimization should be used.
2. use_cartesian(rosetta.protocols.loop_modeling.refiners.MinimizationRefiner) -> bool
Return true if cartesian minimization will be used. The
alternative is atom tree minimization.
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_children_names(...) from builtins.PyCapsule
- get_children_names(*args, **kwargs)
Overloaded function.
1. get_children_names(self : rosetta.protocols.loop_modeling.LoopMover, names : rosetta.utility.vector1_std_string) -> NoneType
Add the names of all the algorithms invoked by this loop mover to
the given list. Indentation is used to represent hierarchy.
2. get_children_names(self : rosetta.protocols.loop_modeling.LoopMover, names : rosetta.utility.vector1_std_string, indent : str) -> NoneType
Add the names of all the algorithms invoked by this loop mover to
the given list. Indentation is used to represent hierarchy.
- 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().
- request_fold_tree(...) from builtins.PyCapsule
- request_fold_tree(rosetta.protocols.loop_modeling.LoopMover) -> rosetta.protocols.loop_modeling.FoldTreeRequest
Return an enum representing the kind of fold tree that is
compatible with this mover.
The FoldTreeRequest enum values can be combined using the
bitwise logical operators. For example, you can request either the
standard fold tree or a simple fold tree with `FTR_LOOPS_WITH_CUTS |
FTR_SIMPLE_TREE.`
- 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
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class RepackingRefiner(rosetta.protocols.loop_modeling.LoopMover) |
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Refine sampled loops using sidechain repacking.
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- Method resolution order:
- RepackingRefiner
- 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
doc
2. __init__(self : handle, repack_period : int) -> NoneType
3. __init__(handle, rosetta.protocols.loop_modeling.refiners.RepackingRefiner) -> 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.protocols.loop_modeling.refiners.RepackingRefiner, : rosetta.protocols.loop_modeling.refiners.RepackingRefiner) -> rosetta.protocols.loop_modeling.refiners.RepackingRefiner
- get_name(...) from builtins.PyCapsule
- get_name(rosetta.protocols.loop_modeling.refiners.RepackingRefiner) -> str
LoopMover::get_name
- get_repack_period(...) from builtins.PyCapsule
- get_repack_period(rosetta.protocols.loop_modeling.refiners.RepackingRefiner) -> int
Return how often this refiner actually repacks the pose.
- get_score_function(...) from builtins.PyCapsule
- get_score_function(rosetta.protocols.loop_modeling.refiners.RepackingRefiner) -> rosetta.core.scoring.ScoreFunction
Get the score function to be used on the next call to apply().
- get_task_factory(...) from builtins.PyCapsule
- get_task_factory(*args, **kwargs)
Overloaded function.
1. get_task_factory(rosetta.protocols.loop_modeling.refiners.RepackingRefiner) -> rosetta.core.pack.task.TaskFactory
Get the task factory to be used on the next call to apply().
If no task factory has been set, this will raise an exception.
2. get_task_factory(self : rosetta.protocols.loop_modeling.refiners.RepackingRefiner, fallback : rosetta.core.pack.task.TaskFactory) -> rosetta.core.pack.task.TaskFactory
Get the task factory to be used on the next call to apply().
If no task factory has been set, the fallback will be returned.
- set_repack_period(...) from builtins.PyCapsule
- set_repack_period(self : rosetta.protocols.loop_modeling.refiners.RepackingRefiner, period : int) -> NoneType
Specify how often this refiner should actually repack the pose.
- set_score_function(...) from builtins.PyCapsule
- set_score_function(self : rosetta.protocols.loop_modeling.refiners.RepackingRefiner, score_function : rosetta.core.scoring.ScoreFunction) -> NoneType
Set the score function to be used on the next call to apply().
- set_task_factory(...) from builtins.PyCapsule
- set_task_factory(self : rosetta.protocols.loop_modeling.refiners.RepackingRefiner, task_factory : rosetta.core.pack.task.TaskFactory) -> NoneType
Set the task factory to be used on the next call to apply().
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_children_names(...) from builtins.PyCapsule
- get_children_names(*args, **kwargs)
Overloaded function.
1. get_children_names(self : rosetta.protocols.loop_modeling.LoopMover, names : rosetta.utility.vector1_std_string) -> NoneType
Add the names of all the algorithms invoked by this loop mover to
the given list. Indentation is used to represent hierarchy.
2. get_children_names(self : rosetta.protocols.loop_modeling.LoopMover, names : rosetta.utility.vector1_std_string, indent : str) -> NoneType
Add the names of all the algorithms invoked by this loop mover to
the given list. Indentation is used to represent hierarchy.
- 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().
- request_fold_tree(...) from builtins.PyCapsule
- request_fold_tree(rosetta.protocols.loop_modeling.LoopMover) -> rosetta.protocols.loop_modeling.FoldTreeRequest
Return an enum representing the kind of fold tree that is
compatible with this mover.
The FoldTreeRequest enum values can be combined using the
bitwise logical operators. For example, you can request either the
standard fold tree or a simple fold tree with `FTR_LOOPS_WITH_CUTS |
FTR_SIMPLE_TREE.`
- 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
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class RotamerTrialsRefiner(rosetta.protocols.loop_modeling.LoopMover) |
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Refine sampled loops using rotamer trials.
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- Method resolution order:
- RotamerTrialsRefiner
- 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.loop_modeling.refiners.RotamerTrialsRefiner) -> 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.protocols.loop_modeling.refiners.RotamerTrialsRefiner, : rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner) -> rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner
- get_name(...) from builtins.PyCapsule
- get_name(rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner) -> str
LoopMover::get_name
- get_score_function(...) from builtins.PyCapsule
- get_score_function(rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner) -> rosetta.core.scoring.ScoreFunction
Get the score function to be used on the next call to apply().
- get_task_factory(...) from builtins.PyCapsule
- get_task_factory(*args, **kwargs)
Overloaded function.
1. get_task_factory(rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner) -> rosetta.core.pack.task.TaskFactory
Get the task factory to be used on the next call to apply().
If no task factory has been set, this will raise an exception.
2. get_task_factory(self : rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner, fallback : rosetta.core.pack.task.TaskFactory) -> rosetta.core.pack.task.TaskFactory
Get the task factory to be used on the next call to apply().
If no task factory has been set, the fallback will be returned.
- set_score_function(...) from builtins.PyCapsule
- set_score_function(self : rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner, score_function : rosetta.core.scoring.ScoreFunction) -> NoneType
Set the score function to be used on the next call to apply().
- set_task_factory(...) from builtins.PyCapsule
- set_task_factory(self : rosetta.protocols.loop_modeling.refiners.RotamerTrialsRefiner, task_factory : rosetta.core.pack.task.TaskFactory) -> NoneType
Set the task factory to be used on the next call to apply().
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_children_names(...) from builtins.PyCapsule
- get_children_names(*args, **kwargs)
Overloaded function.
1. get_children_names(self : rosetta.protocols.loop_modeling.LoopMover, names : rosetta.utility.vector1_std_string) -> NoneType
Add the names of all the algorithms invoked by this loop mover to
the given list. Indentation is used to represent hierarchy.
2. get_children_names(self : rosetta.protocols.loop_modeling.LoopMover, names : rosetta.utility.vector1_std_string, indent : str) -> NoneType
Add the names of all the algorithms invoked by this loop mover to
the given list. Indentation is used to represent hierarchy.
- 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().
- request_fold_tree(...) from builtins.PyCapsule
- request_fold_tree(rosetta.protocols.loop_modeling.LoopMover) -> rosetta.protocols.loop_modeling.FoldTreeRequest
Return an enum representing the kind of fold tree that is
compatible with this mover.
The FoldTreeRequest enum values can be combined using the
bitwise logical operators. For example, you can request either the
standard fold tree or a simple fold tree with `FTR_LOOPS_WITH_CUTS |
FTR_SIMPLE_TREE.`
- 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
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