| | |
- builtins.object
-
- GridSearchIteratorCA
- PcsDataCenter
- PcsDataCenterManagerSingleton
- PcsDataLanthanide
- PcsEnergyParameter
- PcsGridSearchParameter
- PcsInputCenter
- PcsInputCenterManager
- PcsInputFile
- PcsInputLine
- PcsTensor
- rosetta.basic.datacache.CacheableData(builtins.object)
-
- PcsDataCenterManager
- rosetta.core.optimization.Multifunc(builtins.object)
-
- TensorsOptimizer
- TensorsOptimizerFix
- TensorsOptimizerSvd
- rosetta.core.scoring.methods.EnergyMethodCreator(builtins.object)
-
- PcsEnergyCreator
- rosetta.core.scoring.methods.WholeStructureEnergy(rosetta.core.scoring.methods.EnergyMethod)
-
- PcsEnergy
- rosetta.utility.SingletonBase_protocols_scoring_methods_pcs2_PcsEnergyParameterManager_t(builtins.object)
-
- PcsEnergyParameterManager
- rosetta.utility.SingletonBase_protocols_scoring_methods_pcs2_PcsGridSearchParameterManager_t(builtins.object)
-
- PcsGridSearchParameterManager
class PcsDataCenter(builtins.object) |
| | |
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> NoneType
2. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, other : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> NoneType
3. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, pcs_i_c : protocols::scoring::methods::pcs2::PcsInputCenter, start : int, end : int, individual_scale : float) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- __str__(...) from builtins.PyCapsule
- __str__(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> str
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, src : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.protocols.scoring.methods.pcs2.PcsDataCenter
- get_A_all(...) from builtins.PyCapsule
- get_A_all(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t
Give me the matrix A_all_
- get_PCS_data_line_all_spin(...) from builtins.PyCapsule
- get_PCS_data_line_all_spin(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_protocols_scoring_methods_pcs2_PcsInputLine
Give me the vector PCS_data_line_all_spin_
- get_X_all(...) from builtins.PyCapsule
- get_X_all(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_double
Give me the vector X_all_
- get_Y_all(...) from builtins.PyCapsule
- get_Y_all(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_double
Give me the vector Y_all_
- get_Z_all(...) from builtins.PyCapsule
- get_Z_all(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_double
Give me the vector Z_all_
- get_n_lanthanides(...) from builtins.PyCapsule
- get_n_lanthanides(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> int
Give me the number of lanthanides for this center
- get_pcs_data_per_lanthanides_all(...) from builtins.PyCapsule
- get_pcs_data_per_lanthanides_all(*args, **kwargs)
Overloaded function.
1. get_pcs_data_per_lanthanides_all(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_protocols_scoring_methods_pcs2_PcsDataLanthanide
Give me the vector PCS_data_per_lanthanides_all_
2. get_pcs_data_per_lanthanides_all(rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> rosetta.utility.vector1_protocols_scoring_methods_pcs2_PcsDataLanthanide
Give me the vector PCS_data_per_lanthanides_all_ (const version)
- update_X_Y_Z_all(...) from builtins.PyCapsule
- update_X_Y_Z_all(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, pose : rosetta.core.pose.Pose) -> NoneType
This is called each time the pose is changed
- update_matrix_A_all(...) from builtins.PyCapsule
- update_matrix_A_all(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, X : float, Y : float, Z : float) -> NoneType
Call update_my_A_matrix for all lanthanide data.
X Y Z are the new coordinate of the center
- update_matrix_A_all_for_cstyle(...) from builtins.PyCapsule
- update_matrix_A_all_for_cstyle(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, X : float, Y : float, Z : float) -> NoneType
- update_matrix_A_all_for_svd(...) from builtins.PyCapsule
- update_matrix_A_all_for_svd(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, X : float, Y : float, Z : float) -> NoneType
Call update_my_A_matrix for all lanthanide data.
X Y Z are the new coordinate of the center
It also update individual smaller matrice for svd
- where_is_line(...) from builtins.PyCapsule
- where_is_line(self : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, pcs_i_l : protocols::scoring::methods::pcs2::PcsInputLine) -> int
Give the index number of the PcsInputLine given
|
class PcsDataLanthanide(builtins.object) |
| | |
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, : str, weight : float, pcs_i_l : rosetta.utility.vector1_protocols_scoring_methods_pcs2_PcsInputLine, start : int, end : int, individual_scale : float) -> NoneType
2. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, other : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- __str__(...) from builtins.PyCapsule
- __str__(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> str
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, other : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide
- calculate_cost_only_with_svd(...) from builtins.PyCapsule
- calculate_cost_only_with_svd(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> float
- calculate_tensor_and_cost_with_svd(...) from builtins.PyCapsule
- calculate_tensor_and_cost_with_svd(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, pcs_t : protocols::scoring::methods::pcs2::PcsTensor) -> float
return the score and populate the PcsTensor with svd.
- calculate_tensor_only_with_svd(...) from builtins.PyCapsule
- calculate_tensor_only_with_svd(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, pcs_t : protocols::scoring::methods::pcs2::PcsTensor) -> NoneType
populate the PcsTensor with svd.
- get_A_index(...) from builtins.PyCapsule
- get_A_index(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> rosetta.utility.vector1_unsigned_long
Give me the A_index_ vector
- get_cstyle_A(...) from builtins.PyCapsule
- get_cstyle_A(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t
- get_cstyle_b(...) from builtins.PyCapsule
- get_cstyle_b(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> rosetta.utility.vector1_double
- get_cstyle_b_individual_scale(...) from builtins.PyCapsule
- get_cstyle_b_individual_scale(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> rosetta.utility.vector1_double
- get_filename(...) from builtins.PyCapsule
- get_filename(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> str
give me the filename associated with this PCS data
- get_individual_scale(...) from builtins.PyCapsule
- get_individual_scale(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> float
- get_n_pcs(...) from builtins.PyCapsule
- get_n_pcs(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> int
give me the number of PCS data
- get_normalization_factor(...) from builtins.PyCapsule
- get_normalization_factor(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> float
give me the normalization factor associated with this PCS data
- get_normalization_factor_inversed(...) from builtins.PyCapsule
- get_normalization_factor_inversed(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> float
give me the normalization factor associated with this PCS data
- get_weight(...) from builtins.PyCapsule
- get_weight(rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide) -> float
give me the weight associated with this PCS data
- retrieve_tensor_from_svd(...) from builtins.PyCapsule
- retrieve_tensor_from_svd(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, pcs_t : protocols::scoring::methods::pcs2::PcsTensor) -> NoneType
- set_A_index(...) from builtins.PyCapsule
- set_A_index(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, j : int, n_pcs_spin_ : int) -> NoneType
Set a value of the A_index_ vector
- update_my_A_matrix_for_cstyle(...) from builtins.PyCapsule
- update_my_A_matrix_for_cstyle(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, A_all : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> NoneType
- update_my_A_matrix_for_svd(...) from builtins.PyCapsule
- update_my_A_matrix_for_svd(self : rosetta.protocols.scoring.methods.pcs2.PcsDataLanthanide, A_all : rosetta.utility.vector1_utility_vector1_double_std_allocator_double_t) -> NoneType
update the A matrix given A_all matrix.
Dimensions of A_all >= dimension of A.
A_all is common to all the lanthanide sharing the same center
|
class PcsEnergy(rosetta.core.scoring.methods.WholeStructureEnergy) |
| | |
- Method resolution order:
- PcsEnergy
- rosetta.core.scoring.methods.WholeStructureEnergy
- rosetta.core.scoring.methods.EnergyMethod
- builtins.object
Methods defined here:
- PCS_multi_data_from_noone(...) from builtins.PyCapsule
- PCS_multi_data_from_noone(rosetta.protocols.scoring.methods.pcs2.PcsEnergy) -> rosetta.protocols.scoring.methods.pcs2.PcsDataCenterManagerSingleton
- PCS_multi_data_from_pose(...) from builtins.PyCapsule
- PCS_multi_data_from_pose(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergy, pose : rosetta.core.pose.Pose) -> rosetta.protocols.scoring.methods.pcs2.PcsDataCenterManager
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(handle) -> NoneType
2. __init__(handle, rosetta.protocols.scoring.methods.pcs2.PcsEnergy) -> 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.scoring.methods.pcs2.PcsEnergy, other : rosetta.protocols.scoring.methods.pcs2.PcsEnergy) -> rosetta.protocols.scoring.methods.pcs2.PcsEnergy
- calculate_pcs_score_on_PCS_data_center_CA(...) from builtins.PyCapsule
- calculate_pcs_score_on_PCS_data_center_CA(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergy, pose : rosetta.core.pose.Pose, print_to_tracer : bool, pcs_d : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter, i_multi_data : int, grid_it : rosetta.protocols.scoring.methods.pcs2.GridSearchIteratorCA) -> float
Return the PCS score given the pose, the given PcsDataCenter, and the lanthanide number
- clone(...) from builtins.PyCapsule
- clone(rosetta.protocols.scoring.methods.pcs2.PcsEnergy) -> rosetta.core.scoring.methods.EnergyMethod
- finalize_total_energy(...) from builtins.PyCapsule
- finalize_total_energy(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergy, pose : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction, totals : rosetta.core.scoring.EMapVector) -> NoneType
This is called to start the PCS machinerie and get the score (set in totals)
- indicate_required_context_graphs(...) from builtins.PyCapsule
- indicate_required_context_graphs(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergy, : rosetta.utility.vector1_bool) -> NoneType
- version(...) from builtins.PyCapsule
- version(rosetta.protocols.scoring.methods.pcs2.PcsEnergy) -> int
Methods inherited from rosetta.core.scoring.methods.WholeStructureEnergy:
- atomic_interaction_cutoff(...) from builtins.PyCapsule
- atomic_interaction_cutoff(rosetta.core.scoring.methods.WholeStructureEnergy) -> float
how far apart must two heavy atoms be to have a zero interaction energy?
If hydrogen atoms interact at the same range as heavy atoms, then
this distance should build-in a 2 * max-bound-h-distance-cutoff buffer.
There is an improper mixing here between run-time aquired chemical knowledge
(max-bound-h-distance-cutoff) and compile time aquired scoring knowledge
(max atom cutoff); this could be resolved by adding a boolean
uses_hydrogen_interaction_distance() to the SRTBEnergy class along with
a method of the ChemicalManager max_bound_h_distance_cutoff().
This method allows the WholeStructureEnergy class to define which edges
should be included in the EnergyGraph so that during the finalize() method
the Energy class can iterate across the EnergyGraph. This iteration occurrs
in the SecondaryStructureEnergy class, where the edges must span 12 angstroms
between the centroids. Arguably, the SecondaryStructureEnergy class could use
the TwelveANeighborGraph (a context graph) and not require that the EnergyGraph
span such long distances.
- method_type(...) from builtins.PyCapsule
- method_type(rosetta.core.scoring.methods.WholeStructureEnergy) -> rosetta.core.scoring.methods.EnergyMethodType
Methods inherited from rosetta.core.scoring.methods.EnergyMethod:
- defines_high_order_terms(...) from builtins.PyCapsule
- defines_high_order_terms(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose) -> bool
Should this EnergyMethod have score and derivative evaluation
evaluated both in the context of the whole Pose and in the context
of residue or residue-pairs? This covers scoring terms like env-smooth
wherein the CBeta's get derivatives for increasing the neighbor counts
for surrounding residues, and terms like constraints, which are definable
on arbitrary number of residues (e.g. more than 2); both of these terms
could be used in RTMin, and both should use the residue and residue-pair
evaluation scheme with the MinimizationGraph for the majority of the
work they do. (Now, high-order constraints (3-body or above) will not
be properly evaluated within RTMin.). The default implementation
returns "false".
- eval_atom_derivative(...) from builtins.PyCapsule
- eval_atom_derivative(self : rosetta.core.scoring.methods.EnergyMethod, id : rosetta.core.id.AtomID, pose : rosetta.core.pose.Pose, domain_map : ObjexxFCL::FArray1D<int>, sfxn : rosetta.core.scoring.ScoreFunction, emap : rosetta.core.scoring.EMapVector, F1 : rosetta.numeric.xyzVector_double_t, F2 : rosetta.numeric.xyzVector_double_t) -> NoneType
Evaluate the XYZ derivative for an atom in the pose.
Called during the atomtree derivative calculation, atom_tree_minimize.cc,
through the ScoreFunction::eval_atom_derivative intermediary.
F1 and F2 should not zeroed, rather, this class should accumulate its contribution
from this atom's XYZ derivative
The derivative scheme is based on that of Abe, Braun, Noguti and Go (1984)
"Rapid Calculation of First and Second Derivatives of Conformational Energy with
Respect to Dihedral Angles for Proteins. General Recurrent Equations"
Computers & Chemistry 8(4) pp. 239-247. F1 and F2 correspond roughly to Fa and Ga,
respectively, of equations 7a & 7b in that paper.
- finalize_after_derivatives(...) from builtins.PyCapsule
- finalize_after_derivatives(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction) -> NoneType
called at the end of derivatives evaluation
- minimize_in_whole_structure_context(...) from builtins.PyCapsule
- minimize_in_whole_structure_context(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose) -> bool
Should this EnergyMethod have score and derivative evaluation
evaluated only in the context of the whole Pose, or can it be included
in a decomposed manner for a residue or a set of residue-pairs that are
not part of the Pose that's serving as their context? The default
method implemented in the base class returns true in order to grandfather
in EnergyMethods that have not had their derivatives changed to take
advantage of the new derivative-evaluation machinery. Methods that return
"true" will not have their residue-energy(-ext) / residue-pair-energy(-ext)
methods invoked by the ScoreFunction during its traversal of the
MinimizationGraph, and instead will be asked to perform all their work
during finalize_total_energies(). Similarly, they will be expected to
perform all their work during eval_atom_deriv() instead of during the
ScoreFunction's traversal of the MinimizationGraph for derivative evaluation.
IMPORTANT: Methods that return "true" cannot be included in RTMin.
- prepare_rotamers_for_packing(...) from builtins.PyCapsule
- prepare_rotamers_for_packing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.conformation.RotamerSetBase) -> NoneType
If an energy method needs to cache data in a packing::RotamerSet object before
rotamer energies are calculated, it does so during this function. The packer
must ensure this function is called. The default behavior is to do nothing.
- score_types(...) from builtins.PyCapsule
- score_types(rosetta.core.scoring.methods.EnergyMethod) -> rosetta.utility.vector1_core_scoring_ScoreType
Returns the score types that this energy method computes.
- setup_for_derivatives(...) from builtins.PyCapsule
- setup_for_derivatives(self : rosetta.core.scoring.methods.EnergyMethod, pose : rosetta.core.pose.Pose, sfxn : rosetta.core.scoring.ScoreFunction) -> NoneType
Called immediately before atom- and DOF-derivatives are calculated
allowing the derived class a chance to prepare for future calls.
- setup_for_minimizing(...) from builtins.PyCapsule
- setup_for_minimizing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction, : rosetta.core.kinematics.MinimizerMapBase) -> NoneType
Called at the beginning of atom tree minimization, this method
allows the derived class the opportunity to initialize pertinent data
that will be used during minimization. During minimzation, the chemical
structure of the pose is constant, so assumptions on the number of atoms
per residue and their identities are safe so long as the pose's Energies
object's "use_nblist()" method returns true.
- setup_for_packing(...) from builtins.PyCapsule
- setup_for_packing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.utility.vector1_bool, : rosetta.utility.vector1_bool) -> NoneType
if an energy method needs to cache data in the Energies object,
before packing begins, then it does so during this function. The packer
must ensure this function is called. The default behavior is to do nothing.
- setup_for_scoring(...) from builtins.PyCapsule
- setup_for_scoring(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, : rosetta.core.scoring.ScoreFunction) -> NoneType
if an energy method needs to cache something in the pose (e.g. in pose.energies()),
before scoring begins, it must do so in this method. All long range energy
functions must initialize their LREnergyContainers before scoring begins.
The default is to do nothing.
- update_residue_for_packing(...) from builtins.PyCapsule
- update_residue_for_packing(self : rosetta.core.scoring.methods.EnergyMethod, : rosetta.core.pose.Pose, resid : int) -> NoneType
If the pose changes in the middle of a packing (as happens in rotamer trials) and if
an energy method needs to cache data in the pose that corresponds to its current state,
then the method must update that data when this function is called. The packer must
ensure this function gets called. The default behavior is to do nothing.
|
class PcsEnergyParameter(builtins.object) |
| | |
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> NoneType
2. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter, other : rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- __str__(...) from builtins.PyCapsule
- __str__(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> str
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter, other : rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter
- get_include_only_end(...) from builtins.PyCapsule
- get_include_only_end(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> int
- get_include_only_start(...) from builtins.PyCapsule
- get_include_only_start(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> int
- get_individual_scale(...) from builtins.PyCapsule
- get_individual_scale(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> float
- get_n_trial_min(...) from builtins.PyCapsule
- get_n_trial_min(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> int
- get_pcs_weight(...) from builtins.PyCapsule
- get_pcs_weight(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> float
Give me the pcs_weight value
- get_vector_filename(...) from builtins.PyCapsule
- get_vector_filename(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> rosetta.utility.vector1_std_string
Give me the vector of the name
- get_vector_weight(...) from builtins.PyCapsule
- get_vector_weight(rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter) -> rosetta.utility.vector1_double
Give me the vector of the weight
- set_grid_param(...) from builtins.PyCapsule
- set_grid_param(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter, include_only_start : int, include_only_end : int, n_trial_min : int, pcs_weight : float, individual_scale : float) -> NoneType
the grid parameter for this PcsEnergyParameter
- set_vector_name_and_weight(...) from builtins.PyCapsule
- set_vector_name_and_weight(self : rosetta.protocols.scoring.methods.pcs2.PcsEnergyParameter, vec_filename : rosetta.utility.vector1_std_string, vec_individual_weight : rosetta.utility.vector1_double) -> NoneType
the vector an weight name for this PcsEnergyParameter
|
class PcsTensor(builtins.object) |
| | |
Methods defined here:
- __init__(...) from builtins.PyCapsule
- __init__(*args, **kwargs)
Overloaded function.
1. __init__(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> NoneType
2. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsTensor, other : rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> NoneType
3. __init__(self : rosetta.protocols.scoring.methods.pcs2.PcsTensor, chi_xx : float, chi_yy : float, chi_xy : float, chi_xz : float, chi_yz : float, label : str) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- __str__(...) from builtins.PyCapsule
- __str__(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> str
- assign(...) from builtins.PyCapsule
- assign(self : rosetta.protocols.scoring.methods.pcs2.PcsTensor, other : rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> rosetta.protocols.scoring.methods.pcs2.PcsTensor
- get_chi_xx(...) from builtins.PyCapsule
- get_chi_xx(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me chi_xx
- get_chi_xy(...) from builtins.PyCapsule
- get_chi_xy(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me chi_xy
- get_chi_xz(...) from builtins.PyCapsule
- get_chi_xz(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me chi_xz
- get_chi_yy(...) from builtins.PyCapsule
- get_chi_yy(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me chi_yy
- get_chi_yz(...) from builtins.PyCapsule
- get_chi_yz(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me chi_yz
- get_chi_zz(...) from builtins.PyCapsule
- get_chi_zz(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me chi_zz
- get_delta_X_xx(...) from builtins.PyCapsule
- get_delta_X_xx(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me delta chi_xx
- get_delta_X_yy(...) from builtins.PyCapsule
- get_delta_X_yy(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me delta chi_yy
- get_delta_X_zz(...) from builtins.PyCapsule
- get_delta_X_zz(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> float
Give me delta chi_zz
- get_label(...) from builtins.PyCapsule
- get_label(rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> str
Give me the tensor label
- reset_from_ref(...) from builtins.PyCapsule
- reset_from_ref(self : rosetta.protocols.scoring.methods.pcs2.PcsTensor, other : rosetta.protocols.scoring.methods.pcs2.PcsTensor) -> NoneType
Reset the tensor from the other tensor value
- reset_tensor(...) from builtins.PyCapsule
- reset_tensor(self : rosetta.protocols.scoring.methods.pcs2.PcsTensor, chi_xx : float, chi_yy : float, chi_xy : float, chi_xz : float, chi_yz : float) -> NoneType
Reset the tensor from the given values.
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class TensorsOptimizer(rosetta.core.optimization.Multifunc) |
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- Method resolution order:
- TensorsOptimizer
- rosetta.core.optimization.Multifunc
- builtins.object
Methods defined here:
- __call__(...) from builtins.PyCapsule
- __call__(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizer, vars : rosetta.utility.vector1_double) -> float
- __init__(...) from builtins.PyCapsule
- __init__(self : handle, pcs_d_c : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- abort_min(...) from builtins.PyCapsule
- abort_min(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizer, vars : rosetta.utility.vector1_double) -> bool
- dfunc(...) from builtins.PyCapsule
- dfunc(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizer, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
OptE dfunc
- dfunc_exact(...) from builtins.PyCapsule
- dfunc_exact(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizer, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
exact derivative (fast)
- dfunc_numeric(...) from builtins.PyCapsule
- dfunc_numeric(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizer, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
numeric derivative (slow)
- func(...) from builtins.PyCapsule
- func(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizer, vars : rosetta.utility.vector1_double) -> float
Methods inherited from rosetta.core.optimization.Multifunc:
- dump(...) from builtins.PyCapsule
- dump(self : rosetta.core.optimization.Multifunc, : rosetta.utility.vector1_double, : rosetta.utility.vector1_double) -> NoneType
Error state reached -- derivative does not match gradient
Derived classes have the oportunity to now output and or analyze the two
vars assignments vars, vars+delta where the derivatives are incorrect.
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class TensorsOptimizerFix(rosetta.core.optimization.Multifunc) |
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- Method resolution order:
- TensorsOptimizerFix
- rosetta.core.optimization.Multifunc
- builtins.object
Methods defined here:
- __call__(...) from builtins.PyCapsule
- __call__(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerFix, vars : rosetta.utility.vector1_double) -> float
- __init__(...) from builtins.PyCapsule
- __init__(self : handle, pcs_d_c : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- dfunc(...) from builtins.PyCapsule
- dfunc(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerFix, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
OptE dfunc
- dfunc_exact(...) from builtins.PyCapsule
- dfunc_exact(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerFix, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
exact derivative (fast)
- dfunc_numeric(...) from builtins.PyCapsule
- dfunc_numeric(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerFix, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
numeric derivative (slow)
- func(...) from builtins.PyCapsule
- func(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerFix, vars : rosetta.utility.vector1_double) -> float
Methods inherited from rosetta.core.optimization.Multifunc:
- abort_min(...) from builtins.PyCapsule
- abort_min(self : rosetta.core.optimization.Multifunc, : rosetta.utility.vector1_double) -> bool
Christophe added the following to allow premature end of minimization
If you want to abort the minimizer under specific circonstances
overload this function and return true if you want to stop, false if you want to continue.
FOR THE MOMENT, ONLY IN DFPMIN!
- dump(...) from builtins.PyCapsule
- dump(self : rosetta.core.optimization.Multifunc, : rosetta.utility.vector1_double, : rosetta.utility.vector1_double) -> NoneType
Error state reached -- derivative does not match gradient
Derived classes have the oportunity to now output and or analyze the two
vars assignments vars, vars+delta where the derivatives are incorrect.
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class TensorsOptimizerSvd(rosetta.core.optimization.Multifunc) |
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- Method resolution order:
- TensorsOptimizerSvd
- rosetta.core.optimization.Multifunc
- builtins.object
Methods defined here:
- __call__(...) from builtins.PyCapsule
- __call__(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerSvd, vars : rosetta.utility.vector1_double) -> float
- __init__(...) from builtins.PyCapsule
- __init__(self : handle, pcs_d_c : rosetta.protocols.scoring.methods.pcs2.PcsDataCenter) -> NoneType
- __new__(*args, **kwargs) from builtins.type
- Create and return a new object. See help(type) for accurate signature.
- abort_min(...) from builtins.PyCapsule
- abort_min(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerSvd, vars : rosetta.utility.vector1_double) -> bool
- dfunc(...) from builtins.PyCapsule
- dfunc(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerSvd, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
OptE dfunc
- dfunc_exact(...) from builtins.PyCapsule
- dfunc_exact(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerSvd, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
exact derivative (fast)
- dfunc_numeric(...) from builtins.PyCapsule
- dfunc_numeric(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerSvd, vars : rosetta.utility.vector1_double, dE_dvars : rosetta.utility.vector1_double) -> NoneType
numeric derivative (slow)
- func(...) from builtins.PyCapsule
- func(self : rosetta.protocols.scoring.methods.pcs2.TensorsOptimizerSvd, vars : rosetta.utility.vector1_double) -> float
Methods inherited from rosetta.core.optimization.Multifunc:
- dump(...) from builtins.PyCapsule
- dump(self : rosetta.core.optimization.Multifunc, : rosetta.utility.vector1_double, : rosetta.utility.vector1_double) -> NoneType
Error state reached -- derivative does not match gradient
Derived classes have the oportunity to now output and or analyze the two
vars assignments vars, vars+delta where the derivatives are incorrect.
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