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 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 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)

schrodinger.application.canvas.r_group_dee.main()