def test_scramble(self):
"""Testing restore with ConfigurationSet"""
(m, ps) = self._make_things()
cs = IMP.ConfigurationSet(m)
#self._test_base(ps[2], 2, ps[0])
self._scramble(ps[0])
self._scramble(ps[1])
cs.load_configuration(-1)
self._test_base(ps[0], 0, ps[1])
self._test_base(ps[1], 1, ps[1])
def __init__(self, m, p=1, running=False):
"""
@param m: The Model
@param p: The saving periodicity
"""
IMP.OptimizerState.__init__(self)
self._cs = IMP.ConfigurationSet(m)
self._cs.set_log_level(IMP.SILENT)
self._m = m
self._periodicity = p
self._count = 0
def test_noop(self):
"""Testing no-ops with the ConfigurationSet"""
(m, ps) = self._make_things()
print("create")
cs = IMP.ConfigurationSet(m)
self._test_base(ps[0], 0, ps[1])
self._test_base(ps[1], 1, ps[1])
# no-op
print("load")
cs.load_configuration(-1)
self._test_base(ps[0], 0, ps[1])
self._test_base(ps[1], 1, ps[1])
def test_diff(self):
"""Testing restore a known state with ConfigurationSet"""
(m, ps) = self._make_things()
cs = IMP.ConfigurationSet(m)
#self._test_base(ps[2], 2, ps[0])
self._set_attributes(ps[0], 0, ps[1])
self._set_attributes(ps[1], 1, ps[0])
cs.save_configuration()
self._scramble(ps[0])
self._scramble(ps[1])
print("load 0")
cs.load_configuration(0)
print("testing")
self._test_set(ps[0], 0, ps[1])
print("testing")
self._test_set(ps[1], 1, ps[0])
print("load -1")
cs.load_configuration(-1)
self._test_base(ps[0], 0, ps[1])
self._test_base(ps[1], 1, ps[1])
def get_configurations(
model,
restraints,
excluded_volume_particles,
optimized_particles):
#cpc= IMP.container.ClosePairContainer(representation.get_particles(), 0, 10)
# evr= IMP.container.PairRestraint(IMP.core.SoftSpherePairScore(k), cpc,
# "Excluded Volume")
scale = .5
mc = IMP.core.MonteCarlo(model)
movers = []
for p in optimized_particles:
if IMP.core.RigidBody.get_is_setup(p):
mover = IMP.core.RigidBodyMover(
p, IMP.core.XYZR(p).get_radius() * scale,
.2 * scale)
movers.append(mover)
else:
mover = IMP.core.BallMover(
[p], IMP.core.XYZR(p).get_radius() * scale)
movers.append(mover)
serial_mover = IMP.core.SerialMover(movers)
mc.add_mover(serial_mover)
scoring_function = IMP.core.IncrementalScoringFunction(
optimized_particles, restraints)
scoring_function.add_close_pair_score(IMP.core.SoftSpherePairScore(k), 0.0,
excluded_volume_particles)
configuration_set = IMP.ConfigurationSet(model)
# must write our own sampler as IMP.core.MCCGSampler doesn't handle rigid
# bodies
for i in range(number_of_sampling_attempts):
for p in optimized_particles:
IMP.core.XYZ(p).set_coordinates(
IMP.algebra.get_random_vector_in(bb))
mc.optimize(number_of_mc_steps)
if scoring_function.get_had_good_score():
configuration_set.save()
return configuration_set
