| | |
- builtins.object
-
- MotifMatch
- motif2scaffold_data
- motif2scaffold_indexes
- rosetta.protocols.moves.Mover(builtins.object)
-
- MotifGraftMover
- rosetta.protocols.moves.MoverCreator(builtins.object)
-
- MotifGraftCreator
class MotifGraftMover(rosetta.protocols.moves.Mover) |
| | |
- Method resolution order:
- MotifGraftMover
- 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.motif_grafting.movers.MotifGraftMover) -> NoneType
- __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.motif_grafting.movers.MotifGraftMover, : rosetta.core.pose.Pose) -> NoneType
Apply mover function*
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, : rosetta.protocols.motif_grafting.movers.MotifGraftMover) -> rosetta.protocols.motif_grafting.movers.MotifGraftMover
- clone(...) from builtins.PyCapsule
- clone(rosetta.protocols.motif_grafting.movers.MotifGraftMover) -> rosetta.protocols.moves.Mover
Function used by roseta to create clones of movers*
- count_clashes_between_two_poses(...) from builtins.PyCapsule
- count_clashes_between_two_poses(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_A : rosetta.core.pose.Pose, p_B : rosetta.core.pose.Pose, clash_cutoff : int) -> int
Count the Number of Clashes between two poses
- generate_combinations_of_motif_fragments_by_delta_variation(...) from builtins.PyCapsule
- generate_combinations_of_motif_fragments_by_delta_variation(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_motif_ : rosetta.core.pose.Pose, combinatory_fragment_size_delta : rosetta.utility.vector1_std_pair_long_long_t, vv_resulting_permutations : rosetta.utility.vector1_utility_vector1_std_pair_unsigned_long_unsigned_long_std_allocator_std_pair_unsigned_long_unsigned_long_t) -> NoneType
Generate all the combination of different legths of the motif fragment as requested in combinatory_fragment_size_delta
* Uses permutate_n_vv_of_pairs to generate the permutations*
- generate_match_pose(...) from builtins.PyCapsule
- generate_match_pose(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, target_pose : rosetta.core.pose.Pose, contextStructure : rosetta.core.pose.Pose, b_revert_graft_to_native_sequence : bool, motif_match : rosetta.protocols.motif_grafting.movers.MotifMatch) -> NoneType
Generate pose corresponding to the given match *
- generate_scaffold_matches(...) from builtins.PyCapsule
- generate_scaffold_matches(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, target_scaffold : rosetta.core.pose.Pose, target_motif_ : rosetta.core.pose.Pose, target_contextStructure_ : rosetta.core.pose.Pose) -> rosetta.std.priority_queue_protocols_motif_grafting_movers_MotifMatch_std_vector_protocols_motif_grafting_movers_MotifMatch_std_allocator_protocols_motif_grafting_movers_MotifMatch_std_less_protocols_motif_grafting_movers_MotifMatch_t
Identify all potential matches for the given target scaffold (this is where the motif grafting code is called)*
- get_additional_output(...) from builtins.PyCapsule
- get_additional_output(rosetta.protocols.motif_grafting.movers.MotifGraftMover) -> rosetta.core.pose.Pose
Iterate over the results to get additional matches in the queue*
- get_bb_alignment_and_transformation(...) from builtins.PyCapsule
- get_bb_alignment_and_transformation(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, poseA : rosetta.core.pose.Pose, positions_to_alignA : rosetta.utility.vector1_unsigned_long, poseB : rosetta.core.pose.Pose, positions_to_alignB : rosetta.utility.vector1_unsigned_long, RotM : rosetta.numeric.xyzMatrix_double_t, TvecA : rosetta.numeric.xyzVector_double_t, TvecB : rosetta.numeric.xyzVector_double_t) -> float
Performs alignment of the protein BB on the selected aminoacids.
*Returns the RMSD,
*Returns by reference the rotation Matrix and Translation Vector,
*Will fail if both poses are not protein <-This can be fixed by adding a list of the atoms to align to the function, but I am not doing it now.
*Will fail if the number of residues to align is not the same in the two poses. *
- get_bb_alignment_and_transformation_wTipsExtraInfo(...) from builtins.PyCapsule
- get_bb_alignment_and_transformation_wTipsExtraInfo(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, v_isNorC : rosetta.utility.vector1_bool, poseA : rosetta.core.pose.Pose, positions_to_alignA : rosetta.utility.vector1_unsigned_long, poseB : rosetta.core.pose.Pose, positions_to_alignB : rosetta.utility.vector1_unsigned_long, RotM : rosetta.numeric.xyzMatrix_double_t, TvecA : rosetta.numeric.xyzVector_double_t, TvecB : rosetta.numeric.xyzVector_double_t, RMSD_tip_elements : rosetta.utility.vector1_double) -> float
Performs alignment of the protein BB on the selected aminoacids.
*Returns the RMSD,
*Returns by reference the rotation Matrix and Translation Vector,
*Will fail if both poses are not protein <-This can be fixed by adding a list of the atoms to align to the function, but I am not doing it now.
*Will fail if the number of residues to align is not the same in the two poses. *
- get_bb_distance(...) from builtins.PyCapsule
- get_bb_distance(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, poseA : rosetta.core.pose.Pose, positions_to_alignA : rosetta.utility.vector1_unsigned_long, poseB : rosetta.core.pose.Pose, positions_to_alignB : rosetta.utility.vector1_unsigned_long) -> float
Returns the BB distance of two poses respect to indexes*
- get_clash_score_from_pose(...) from builtins.PyCapsule
- get_clash_score_from_pose(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_input : rosetta.core.pose.Pose, scorefxn_ : rosetta.core.scoring.ScoreFunction) -> float
Helper function to stich (epigraft) two poses given a set of indices in pose A and B stored in a motif2scaffold_data structure*
- get_fragments_by_CA_distances_and_NCpoints_restrains(...) from builtins.PyCapsule
- get_fragments_by_CA_distances_and_NCpoints_restrains(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_scaffold : rosetta.core.pose.Pose, p_motif_ : rosetta.core.pose.Pose, vv_scaffold_fragments_indexes : rosetta.utility.vector1_utility_vector1_std_pair_unsigned_long_unsigned_long_std_allocator_std_pair_unsigned_long_unsigned_long_t, v_motif_fragments_indexes : rosetta.utility.vector1_std_pair_unsigned_long_unsigned_long_t, RMSD_tol : float, max_fragment_replacement_size_delta : rosetta.utility.vector1_std_pair_long_long_t, v_motif_fragments_permutation : rosetta.utility.vector1_std_pair_unsigned_long_unsigned_long_t, b_only_allow_if_N_point_match_aa_identity : bool, b_only_allow_if_C_point_match_aa_identity : bool, b_N_point_can_replace_proline : bool, b_C_point_can_replace_proline : bool) -> bool
returns by reference two vectors of indexes (vv_scaffold_fragments_indexes, v_motif_fragments_indexes)
* that hold the lower and upper bounds of the fragments. Indeed the corresponding to the scaffold one is a vector
*of vectors, since each pose_scaffold can have many matches*
- get_matching_fragments(...) from builtins.PyCapsule
- get_matching_fragments(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, target_scaffold : rosetta.core.pose.Pose, target_motif_ : rosetta.core.pose.Pose, target_contextStructure_ : rosetta.core.pose.Pose, RMSD_tol : float, NC_points_RMSD_tol : float, clash_cutoff : int, clash_test_residue : str, max_fragment_replacement_size_delta_ : rosetta.utility.vector1_std_pair_long_long_t, combinatory_fragment_size_delta : rosetta.utility.vector1_std_pair_unsigned_long_unsigned_long_t, vvr_hotspots : rosetta.utility.vector1_utility_vector1_unsigned_long_std_allocator_unsigned_long_t, b_full_motif_bb_alignment : bool, b_allow_independent_alignment_per_fragment : bool, b_graft_only_hotspots_by_sidechain_replacement : bool, b_only_allow_if_N_point_match_aa_identity : bool, b_only_allow_if_C_point_match_aa_identity : bool, pq : rosetta.std.priority_queue_protocols_motif_grafting_movers_MotifMatch_std_vector_protocols_motif_grafting_movers_MotifMatch_std_allocator_protocols_motif_grafting_movers_MotifMatch_std_less_protocols_motif_grafting_movers_MotifMatch_t) -> NoneType
Return a priority queue with the sucessful epigrafts *
- get_mono_aa_pose_copy(...) from builtins.PyCapsule
- get_mono_aa_pose_copy(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_input : rosetta.core.pose.Pose, aminoacid_code : str) -> rosetta.core.pose.Pose
returns a copy of the pose that replaces all the aminoacids for a single selected aminoacid*
- get_name(...) from builtins.PyCapsule
- get_name(rosetta.protocols.motif_grafting.movers.MotifGraftMover) -> str
Header only mover get_name*
- get_rotated_and_translated_pose(...) from builtins.PyCapsule
- get_rotated_and_translated_pose(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_scaffold : rosetta.core.pose.Pose, RotM : rosetta.numeric.xyzMatrix_double_t, TvecA : rosetta.numeric.xyzVector_double_t, TvecB : rosetta.numeric.xyzVector_double_t) -> rosetta.core.pose.Pose
Function that returns by reference a rotated copy of the pose
- init_parameters(...) from builtins.PyCapsule
- init_parameters(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, s_contextStructure : str, s_motif : str, r_RMSD_tolerance : float, r_NC_points_RMSD_tolerance : float, i_clash_score_cutoff : int, s_combinatory_fragment_size_delta : str, s_max_fragment_replacement_size_delta : str, s_clash_test_residue : str, s_hotspots : str, b_full_motif_bb_alignment : bool, b_allow_independent_alignment_per_fragment : bool, b_graft_only_hotspots_by_sidechain_replacement : bool, b_only_allow_if_N_point_match_aa_identity : bool, b_only_allow_if_C_point_match_aa_identity : bool, b_revert_graft_to_native_sequence : bool, b_allow_repeat_same_graft_output : bool) -> NoneType
MotifGraftMover parameters and options initializer*
- join_two_poses_by_jump(...) from builtins.PyCapsule
- join_two_poses_by_jump(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_A : rosetta.core.pose.Pose, p_B : rosetta.core.pose.Pose) -> rosetta.core.pose.Pose
returns a pose with two input poses merged (with a jump in-between) and with the PDB info corrected
- parse_my_string_arguments_and_cast_to_globalPrivateSpaceVariables(...) from builtins.PyCapsule
- parse_my_string_arguments_and_cast_to_globalPrivateSpaceVariables(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, s_contextStructure : str, s_motif : str, r_RMSD_tolerance : float, r_NC_points_RMSD_tolerance : float, i_clash_score_cutoff : int, s_combinatory_fragment_size_delta : str, s_max_fragment_replacement_size_delta : str, s_clash_test_residue : str, s_hotspots : str, b_full_motif_bb_alignment : bool, b_allow_independent_alignment_per_fragment : bool, b_graft_only_hotspots_by_sidechain_replacement : bool, b_only_allow_if_N_point_match_aa_identity : bool, b_only_allow_if_C_point_match_aa_identity : bool, b_revert_graft_to_native_sequence : bool, b_allow_repeat_same_graft_output : bool) -> NoneType
- permutate_n_vv_of_pairs(...) from builtins.PyCapsule
- permutate_n_vv_of_pairs(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, vv_of_pairs : rosetta.utility.vector1_utility_vector1_std_pair_unsigned_long_unsigned_long_std_allocator_std_pair_unsigned_long_unsigned_long_t, buff_combVec : rosetta.utility.vector1_std_pair_unsigned_long_unsigned_long_t, start_index : int, vv_resulting_permutations : rosetta.utility.vector1_utility_vector1_std_pair_unsigned_long_unsigned_long_std_allocator_std_pair_unsigned_long_unsigned_long_t) -> NoneType
As the name suggests in generates all the permutations of a vector of vectors of pairs (Alex: we should templatize this! Maybe alrready there?)*
- stich_motif_in_scaffold_by_indexes_rotation_and_translation(...) from builtins.PyCapsule
- stich_motif_in_scaffold_by_indexes_rotation_and_translation(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, p_scaffold : rosetta.core.pose.Pose, p_motif_ : rosetta.core.pose.Pose, m2s_dat : rosetta.protocols.motif_grafting.movers.motif2scaffold_data, skip_motif_extremes : bool) -> rosetta.core.pose.Pose
Helper function to stich (epigraft) two poses given a set of indices in pose A and B stored in a motif2scaffold_data structure*
- superposition_transform(...) from builtins.PyCapsule
- superposition_transform(self : rosetta.protocols.motif_grafting.movers.MotifGraftMover, natoms : int, weights : ObjexxFCL::FArray1<double>, ref_coords : rosetta.ObjexxFCL.FArray2_double_t, coords : rosetta.ObjexxFCL.FArray2_double_t, RotM : rosetta.numeric.xyzMatrix_double_t, TvecA : rosetta.numeric.xyzVector_double_t, TvecB : rosetta.numeric.xyzVector_double_t) -> NoneType
Helper Fortran wrapper to get the aligment of two matrixes as well as the corresponding transform*
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
- 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_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
|
|