Package csb :: Package bio :: Package fragments :: Class TorsionAnglePredictor

Class TorsionAnglePredictor

object --+
         |
        TorsionAnglePredictor

Fragment-based phi/psi angles predictor.

Note: if init is False, the first call to predictor.compute() might take a long time. Subsequent calls will be very fast.

Instance Methods

__init__(self, target, threshold=1.5, extend=False, init=False)
x.__init__(...) initializes x; see help(type(x)) for signature

source code

tuple of TorsionPredictionInfo

compute(self, rank)
Extract torsion angles from all ClusterReps, covering residue #rank. source code

TorsionPredictionInfo

compute_single(self, rank)
Extract torsion angles from the ClusterRep at residue #rank. source code

tuple of TorsionPredictionInfo

flat_torsion_map(self)
Filter the current fragment map and create a new, completely flat, non-overlapping map built from centroids, assigned iteratively by decreasing confidence.

source code

tuple of TorsionAngles

get_angles(self, rank)
Extract all torsion angles coming from all fragments, which had survived the filtering and cover residue #rank. source code

init(self)
Compute and cache all FragmentClusters.

source code

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Properties
	extend
	target
	threshold
Inherited from `object`: `__class__`

Method Details

init(self, target, threshold=1.5, extend=False, init=False)
(Constructor)

source code

x.__init__(...) initializes x; see help(type(x)) for signature

Parameters:

target (Target) - target protein, containing fragment assignments
threshold (float) - RMSD distance threshold for FragmentCluster-based filtering
extend (bool) - pick alternative, longer cluster reps, if possible
init - populate all FragmentClusters on instantiation. If False, this step will be performed on demand (the first time predictor.compute() is invoked)

Overrides: object.__init__

(inherited documentation)

compute(self, rank)

source code

Extract torsion angles from all ClusterReps, covering residue #rank.

Parameters:

rank (int) - target residue rank

Returns: tuple of TorsionPredictionInfo

TorsionPredictionInfo instances, sorted by confidence

compute_single(self, rank)

source code

Extract torsion angles from the ClusterRep at residue #rank.

Parameters:

rank (int) - target residue rank

Returns: TorsionPredictionInfo

flat_torsion_map(self)

source code

Filter the current fragment map and create a new, completely flat, non-overlapping map built from centroids, assigned iteratively by decreasing confidence. Centroids with lower confidence which overlap with previously assigned centroids will be trimmed to fill existing gaps only.

Returns: tuple of TorsionPredictionInfo: TorsionPredictionInfo instances, one for each target residue

get_angles(self, rank)

source code

Extract all torsion angles coming from all fragments, which had survived the filtering and cover residue #rank.

Parameters:

rank (int) - target residue rank

Returns: tuple of TorsionAngles

all TorsionAngles for a cluster at the specified residue

Property Details

extend

Get Method:: unreachable.extend(self)

target

Get Method:: unreachable.target(self)

threshold

Get Method:: unreachable.threshold(self)

Class TorsionAnglePredictor

__init__(self, target, threshold=1.5, extend=False, init=False) (Constructor)

compute(self, rank)

compute_single(self, rank)

flat_torsion_map(self)

get_angles(self, rank)

extend

target

threshold

init(self, target, threshold=1.5, extend=False, init=False)
(Constructor)