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()