schrodinger.application.canvas.r_group_dee module

R-Group Analysis Dead End elimination

class schrodinger.application.canvas.r_group_dee.SimulatedAnnealing(energy_matrix, sa_seed=None, t_factor=None, tmax_mult=None)

Bases: object

static getChoiceSpectrum(choices)

__init__(energy_matrix, sa_seed=None, t_factor=None, tmax_mult=None)

Initializer for simulated annealing class.

Parameters:

• energy_matrix (DEE_EnergyMatrix) – precalculated pairwise matrix used by SA.
• sa_seed (float) – SA random number generator seed
• t_fac – Factor (<1) by which T will be multiplied at each T change
• tmax_mult (float) – Factor by which no. of st. will be multiplied to get starting T

run()

is_another_best_config(solution)

new_best(energy, solution)

report_t(t, start_E, end_E, tsteps, totalCnt, acceptCnt)

getNewSolution(solution_old)

neighbor(solution)

new_temperature(old_t)

boltzmann_probability(e_old, e_new, t)

getBestMatch()

__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.canvas.r_group_dee', 'getChoiceSpectrum': <staticmethod object>, '__init__': <function SimulatedAnnealing.__init__>, 'run': <function SimulatedAnnealing.run>, 'is_another_best_config': <function SimulatedAnnealing.is_another_best_config>, 'new_best': <function SimulatedAnnealing.new_best>, 'report_t': <function SimulatedAnnealing.report_t>, 'getNewSolution': <function SimulatedAnnealing.getNewSolution>, 'neighbor': <function SimulatedAnnealing.neighbor>, 'new_temperature': <function SimulatedAnnealing.new_temperature>, 'boltzmann_probability': <function SimulatedAnnealing.boltzmann_probability>, 'getBestMatch': <function SimulatedAnnealing.getBestMatch>, '__dict__': <attribute '__dict__' of 'SimulatedAnnealing' objects>, '__weakref__': <attribute '__weakref__' of 'SimulatedAnnealing' objects>, '__doc__': None})

__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.canvas.r_group_dee'

__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

class schrodinger.application.canvas.r_group_dee.DEE_Backtracking(energy_matrix)

Bases: object

__init__(energy_matrix)

Initialize self. See help(type(self)) for accurate signature.

minimize()

backtrack(solution)

reject(solution)

accept(solution)

first(solution)

next(solution)

output(solution)

getBestMatch()

__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.canvas.r_group_dee', '__init__': <function DEE_Backtracking.__init__>, 'minimize': <function DEE_Backtracking.minimize>, 'backtrack': <function DEE_Backtracking.backtrack>, 'reject': <function DEE_Backtracking.reject>, 'accept': <function DEE_Backtracking.accept>, 'first': <function DEE_Backtracking.first>, 'next': <function DEE_Backtracking.next>, 'output': <function DEE_Backtracking.output>, 'getBestMatch': <function DEE_Backtracking.getBestMatch>, '__dict__': <attribute '__dict__' of 'DEE_Backtracking' objects>, '__weakref__': <attribute '__weakref__' of 'DEE_Backtracking' objects>, '__doc__': None})

__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.canvas.r_group_dee'

__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

class schrodinger.application.canvas.r_group_dee.DEE_EnergyMatrix(choices, uij)

Bases: object

__init__(choices, uij)

Initialize self. See help(type(self)) for accurate signature.

numPos()

numChoices()

calculateEnergy(solution)

calculateEnergyDifference(solution_old, e_old, istruct, solution_new)

initialSolution()

checkSolution(solution)

convertSolution(solution)

applyEnergyFilter(solution, current_energy)

eliminateSingles()

eliminatePairs()

applyGoldsteinSingles(k, a, b)

__class__

alias of builtins.type

__delattr__

Implement delattr(self, name).

__dict__ = mappingproxy({'__module__': 'schrodinger.application.canvas.r_group_dee', '__init__': <function DEE_EnergyMatrix.__init__>, 'numPos': <function DEE_EnergyMatrix.numPos>, 'numChoices': <function DEE_EnergyMatrix.numChoices>, 'calculateEnergy': <function DEE_EnergyMatrix.calculateEnergy>, 'calculateEnergyDifference': <function DEE_EnergyMatrix.calculateEnergyDifference>, 'initialSolution': <function DEE_EnergyMatrix.initialSolution>, 'checkSolution': <function DEE_EnergyMatrix.checkSolution>, 'convertSolution': <function DEE_EnergyMatrix.convertSolution>, 'applyEnergyFilter': <function DEE_EnergyMatrix.applyEnergyFilter>, 'eliminateSingles': <function DEE_EnergyMatrix.eliminateSingles>, 'eliminatePairs': <function DEE_EnergyMatrix.eliminatePairs>, 'applyGoldsteinSingles': <function DEE_EnergyMatrix.applyGoldsteinSingles>, '__dict__': <attribute '__dict__' of 'DEE_EnergyMatrix' objects>, '__weakref__': <attribute '__weakref__' of 'DEE_EnergyMatrix' objects>, '__doc__': None})

__dir__() → list

default dir() implementation

__eq__

Return self==value.

__format__()

default object formatter

__ge__

Return self>=value.

__getattribute__

Return getattr(self, name).

__gt__

Return self>value.

__hash__

Return hash(self).

__init_subclass__()

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__

Return self<=value.

__lt__

Return self<value.

__module__ = 'schrodinger.application.canvas.r_group_dee'

__ne__

Return self!=value.

__new__()

Create and return a new object. See help(type) for accurate signature.

__reduce__()

helper for pickle

__reduce_ex__()

helper for pickle

__repr__

Return repr(self).

__setattr__

Implement setattr(self, name, value).

__sizeof__() → int

size of object in memory, in bytes

__str__

Return str(self).

__subclasshook__()

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__weakref__

list of weak references to the object (if defined)

schrodinger.application.canvas.r_group_dee.main()