# muca.py
#
# Copyright 2007 Frank Eisenmenger, U.H.E. Hansmann,
# Jan H. Meinke, Sandipan Mohanty
#
import sys
sys.path.append('../..')
import smmp, universe, protein
smmp.epar_l.flex = 0
smmp.epar_l.sh2 = 0
smmp.epar_l.epsd = 0
smmp.epar_l.ientyp = 0
smmp.isolty.itysol = 0
smmp.init_energy('./SMMP/')
smmp.mol_i.ntlml=0
smmp.sgrnd(31433)
smmp.updchois.upchswitch = 0
smmp.updchois.rndord = 0
smmp.updchois.bgsprob = 0.3
smmp.init_lund()
p = protein.Protein('../enkefa.seq', '../enkefa.var')
smmp.multicanonical.mulcan_par(100000, 500, 1000, -12, 20, 1.0, 0)
#smmp.multicanonical.mulcan_sim(100, 100000, 10, 1000, -12, 20, 1.0, 0)
simulation is slowly reduced from Tmax to Tmin.
"""
# Adds the source directory to Python's search path.
import sys
sys.path.append('../..')
import smmp, universe, protein
# Initialize the Universe to T=300K with the ECEPP/3 force field, no solvent
# term (st = 0) and the sub directory SMMP/ as library path. Except for the
# solvent term, these are the default values. Alternatively, we could have
# written
# myUniverse = universe.Universe(st=0)
# to get the same result.
myUniverse = universe.Universe(T=300, ff='ecepp2', st=0, libdir='SMMP/')
# Create a new protein object from the sequence file ../enkefa.seq and
# set the dihedral angles according to the values given in ../enkefa.var.
p = protein.Protein('../enkefa.seq', '../enkefa.ann')
# Make myUniverse aware of p.
myUniverse.add(p)
seed = 81236
smmp.sgrnd(seed)
Tmin = 100
Tmax = 1000
equilibrationSweeps = 100
sweeps = 100000
measurementInterval = 1000
randomStart = 1
smmp.anneal(equilibrationSweeps, sweeps, measurementInterval, Tmax, Tmin,
randomStart)
#!/usr/bin/env python
# muca.py
#
# Copyright 2007 Frank Eisenmenger, U.H.E. Hansmann,
# Jan H. Meinke, Sandipan Mohanty
#
import sys
sys.path.append('../..')
import smmp, universe, protein
smmp.epar_l.flex = 0
smmp.epar_l.sh2 = 0
smmp.epar_l.epsd = 0
smmp.epar_l.ientyp = 0
smmp.isolty.itysol = 0
smmp.init_energy('./SMMP/')
smmp.mol_i.ntlml = 0
smmp.sgrnd(31433)
smmp.updchois.upchswitch = 0
smmp.updchois.rndord = 0
smmp.updchois.bgsprob = 0.3
smmp.init_lund()
p = protein.Protein('../enkefa.seq', '../enkefa.var')
smmp.multicanonical.mulcan_par(100000, 500, 1000, -12, 20, 1.0, 0)
#smmp.multicanonical.mulcan_sim(100, 100000, 10, 1000, -12, 20, 1.0, 0)
simulated annealing. In simulated annealing the temperature of a Monte Carlo
simulation is slowly reduced from Tmax to Tmin.
"""
# Adds the source directory to Python's search path.
import sys
sys.path.append('../..')
import smmp, universe, protein
# Initialize the Universe to T=300K with the ECEPP/3 force field, no solvent
# term (st = 0) and the sub directory SMMP/ as library path. Except for the
# solvent term, these are the default values. Alternatively, we could have
# written
# myUniverse = universe.Universe(st=0)
# to get the same result.
myUniverse = universe.Universe(T=300, ff = 'ecepp2', st = 0, libdir ='SMMP/')
# Create a new protein object from the sequence file ../enkefa.seq and
# set the dihedral angles according to the values given in ../enkefa.var.
p = protein.Protein('../enkefa.seq', '../enkefa.ann')
# Make myUniverse aware of p.
myUniverse.add(p)
seed = 81236
smmp.sgrnd(seed)
Tmin = 100
Tmax = 1000
equilibrationSweeps = 100
sweeps = 100000
measurementInterval = 1000
randomStart = 1
smmp.anneal(equilibrationSweeps, sweeps, measurementInterval, Tmax, Tmin, randomStart)