def save(self):
"Save the trajs as a n MSMBuilder project"
traj_dir = pjoin(self.project_dir, 'Trajectories')
if not os.path.exists(traj_dir):
os.makedirs(traj_dir)
t = Trajectory.load_trajectory_file(self.conf_filename)
traj_paths = []
for i, xyz in enumerate(self.trajectories):
t['IndexList'] = None # bug in msmbuilder
t['XYZList'] = xyz
traj_paths.append(pjoin(traj_dir, 'trj%d.lh5' % i))
t.save(traj_paths[-1])
p = Project(
{
'conf_filename': os.path.abspath(self.conf_filename),
'traj_lengths': self.n_frames * np.ones(self.n_trajs),
'traj_paths': [os.path.abspath(e) for e in traj_paths],
'traj_converted_from': [[] for i in range(self.n_trajs)],
'traj_errors': [None for i in range(self.n_trajs)],
},
project_dir=self.project_dir,
validate=True)
p.save(pjoin(self.project_dir, 'Project.yaml'))
# just check again
p = Project.load_from(pjoin(self.project_dir, 'Project.yaml'))
p._validate()
assert np.all(
(p.load_traj(0)['XYZList'] - self.trajectories[0])**2 < 1e-6)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-n', '--n_trajs', help='number of trajectories. Default=10', type=int, default=10)
parser.add_argument('-t', '--traj_length', help='trajectories length. Default=10000', type=int, default=10000)
args = parser.parse_args()
# these could be configured
kT = 15.0
dt = 0.1
mGamma = 1000.0
forcecalculator = muller.muller_force()
project = Project({'ConfFilename': os.path.join(mullermsm.__path__[0], 'conf.pdb'),
'NumTrajs': args.n_trajs,
'ProjectRootDir': '.',
'TrajFileBaseName': 'trj',
'TrajFilePath': 'Trajectories',
'TrajFileType': '.lh5',
'TrajLengths': [args.traj_length]*args.n_trajs})
if os.path.exists('ProjectInfo.h5'):
print >> sys.stderr, "The file ./ProjectInfo.h5 already exists. I don't want to overwrite anything, so i'm backing off"
sys.exit(1)
try:
os.mkdir('Trajectories')
except OSError:
print >> sys.stderr, "The directory ./Trajectores already exists. I don't want to overwrite anything, so i'm backing off"
sys.exit(1)
for i in range(args.n_trajs):
print 'simulating traj %s' % i
# select initial configs randomly from a 2D box
initial_x = [random.uniform(-1.5, 1.2), random.uniform(-0.2, 2)]
print 'starting conformation from randomly sampled points (%s, %s)' % (initial_x[0], initial_x[1])
print 'propagating for %s steps on the Muller potential with a Langevin integrator...' % args.traj_length
positions = muller.propagate(args.traj_length, initial_x, kT, dt, mGamma, forcecalculator)
# positions is N x 2, but we want to make it N x 1 x 3 where the additional
# column is just zeros. This way, being N x 1 x 3, it looks like a regular MD
# trajectory that would be N_frames x N_atoms x 3
positions3 = np.hstack((positions, np.zeros((len(positions),1)))).reshape((len(positions), 1, 3))
t = Trajectory.LoadTrajectoryFile(project['ConfFilename'])
t['XYZList'] = positions3
t.SaveToLHDF(project.GetTrajFilename(i))
print 'saving trajectory to %s' % project.GetTrajFilename(i)
project.SaveToHDF('ProjectInfo.h5')
print 'saved ProjectInfo.h5 file'
pickle.dump(metric.EuclideanMetric(), open('metric.pickl', 'w'))
print 'saved metric.pickl'
def run(traj_dir, conf_filename, project_filename, iext):
logger.info("Rebuilding project.")
file_list = glob.glob(traj_dir + "/trj*%s" % iext)
num_traj = len(file_list)
traj_lengths = np.zeros(num_traj, 'int')
traj_paths = []
if not os.path.exists(conf_filename):
raise(IOError("Cannot find conformation file %s" % conf_filename))
file_list = sorted(file_list, key=utils.keynat)
for i, filename in enumerate(file_list):
traj_lengths[i] = len(md.open(filename))
traj_paths.append(filename)
records = {
"conf_filename": conf_filename,
"traj_lengths": traj_lengths,
"traj_paths": traj_paths,
"traj_errors": [None for i in xrange(num_traj)],
"traj_converted_from": [[] for i in xrange(num_traj)]
}
p = Project(records)
p.save(project_filename)
logger.info("Wrote %s" % project_filename)
def setup(self):
self.metric = metrics.Dihedral()
self.pdb_fn = os.path.join(fixtures_dir(), 'native.pdb')
self.trj_fn = os.path.join(fixtures_dir(), 'trj0.lh5')
self.project = Project({'traj_lengths': [501], 'traj_paths': [self.trj_fn],
'conf_filename': self.pdb_fn, 'traj_converted_from': [None],
'traj_errors': [None]})
self.vtraj = partition(self.project, chunk_size=501)[0]
def test_project_2():
'inconsistent lengths should be detected'
records = {'conf_filename': None,
'traj_lengths': [0,0], # this is one too short
'traj_errors': [None, None, None],
'traj_paths': ['t0', 't1', 't2'],
'traj_converted_from': [None, None, None]}
proj = Project(records, validate=False)
def setup(self):
self.metric = metrics.Dihedral()
self.pdb_fn = os.path.join(fixtures_dir(), 'native.pdb')
self.trj_fn = os.path.join(fixtures_dir(), 'trj0.lh5')
self.project = Project({
'NumTrajs': 1,
'TrajLengths': [501],
'TrajFileBaseName': 'trj',
'TrajFileType': '.lh5',
'ConfFilename': self.pdb_fn,
'TrajFilePath': fixtures_dir()
})
self.vtraj = partition(self.project, chunk_size=501)[0]
def test_project_1():
'ensure that the counting of errors works right'
records = {'conf_filename': None,
'traj_lengths': [0,0,0],
'traj_errors': [None, 1, None],
'traj_paths': ['t0', 't1', 't2'],
'traj_converted_from': [None, None, None]}
proj = Project(records, validate=False)
eq_(proj.n_trajs, 2)
eq_(os.path.basename(proj.traj_filename(0)), 't0')
# since t1 should be skipped
eq_(os.path.basename(proj.traj_filename(1)), 't2')
