def setup_aatopology(self):
GMIN.initialize()
pot = GMINPotential(GMIN)
coords = pot.getCoords()
nrigid = coords.size / 6
print "I have %d water molecules in the system" % nrigid
print "The initial energy is", pot.getEnergy(coords)
water = tip4p.water()
system = RBTopology()
system.add_sites([deepcopy(water) for i in xrange(nrigid)])
self.potential = pot
self.nrigid = nrigid
self.render_scale = 0.3
self.atom_types = system.get_atomtypes()
self.draw_bonds = []
for i in xrange(nrigid):
self.draw_bonds.append((3 * i, 3 * i + 1))
self.draw_bonds.append((3 * i, 3 * i + 2))
return system
def __init__(self, *args, **kwargs):
AppBasinHopping.__init__(self, *args, **kwargs)
self.quenchRoutine = mylbfgs
self.potential = GMINPotential(GMIN)
self.quenchParameters["tol"] = 1e-4
self.quenchParameters["M"] = 80
self.quenchParameters["maxErise"] = 0.1
self.quenchRoutine = mylbfgs
def setup_aatopology(self):
self.write_coords_data()
GMIN.initialize()
self.pot = GMINPotential(GMIN)
coords = self.pot.getCoords()
self.nrigid = coords.size / 6
assert (self.nrigid == self.nmol)
#self.nrigid = self.nmol
otp = self.make_otp()
topology = RBTopology()
topology.add_sites([deepcopy(otp) for i in xrange(self.nrigid)])
self.render_scale = 0.2
self.atom_types = topology.get_atomtypes()
self.draw_bonds = []
for i in xrange(self.nrigid):
self.draw_bonds.append((3 * i, 3 * i + 1))
self.draw_bonds.append((3 * i, 3 * i + 2))
self.params.double_ended_connect.local_connect_params.tsSearchParams.iprint = 10
return topology
def check_converged(E, coords):
if (E < (parameters.TARGET + parameters.EDIFF)):
fl = open("stat.dat", "a")
print "#found minimum"
t1 = time.clock()
timespent = t1 - t0
fl.write("#quenches, functioncalls, time\n")
fl.write("%d %d %f\n" % (opt.stepnum, potential.ncalls, timespent))
fl.close()
exit()
# initialize GMIN
GMIN.initialize()
# create a potential which calls GMIN
potential = GMINPotential(GMIN)
# get the initial coorinates
coords = potential.getCoords()
coords = np.random.random(coords.shape)
# create takestep routine
# we combine a normal step taking
group = takestep.BlockMoves()
step1 = takestep.AdaptiveStepsize(OXDNATakestep(displace=parameters.displace,
rotate=0.),
frequency=50)
step2 = takestep.AdaptiveStepsize(OXDNATakestep(displace=0.,
rotate=parameters.rotate),
frequency=50)
group.addBlock(100, step1)
def get_potential(self):
return GMINPotential(GMIN)
