Python Trajectory.load_trajectory_file方法代码示例

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def plot_gpu_cmd_correlation():
    traj1 = Trajectory.load_trajectory_file(ww_1, Conf=ww_conf)
    traj1_copy = Trajectory.load_trajectory_file(ww_1, Conf=ww_conf)
    #traj2 = Trajectory.load_trajectory_file(ww_2, Conf=ww_conf)
    #traj2_copy = Trajectory.load_trajectory_file(ww_2, Conf=ww_conf)

    def gpudist(t):
        gpurmsd = GPURMSD()
        pt = gpurmsd.prepare_trajectory(t)
        gpurmsd._gpurmsd.print_params()
        return gpurmsd.one_to_all(pt, pt, 0)
    def cpudist(t):
        rmsd = RMSD()
        pt = rmsd.prepare_trajectory(t)
        return rmsd.one_to_all(pt, pt, 0)
    g1 = gpudist(traj1) #, gpudist(traj2)
    c1 = cpudist(traj1_copy) #, cpudist(traj2_copy)

    pp.subplot(231)
    pp.plot(c1)
    pp.title('cpu rmsd drift along traj')
    pp.xlabel('frame index')
    pp.xlabel('cpurmsd($X_{0}$, $X_{frame_index}$)')

    pp.subplot(232)
    pp.scatter(g1, c1)
    pp.xlabel('gpu rmsd')
    pp.ylabel('cpu rmsd')

    pp.subplot(233)
    pp.plot(g1)
    pp.title('gpu rmsd drift along traj')
    pp.xlabel('frame index')
    pp.xlabel('gpurmsd($X_{0}$, $X_{frame_index}$)')


    #PLOT c2 and g2 in the lower portion of the graph

    #pp.subplot(234)
    #pp.plot(c2)
    #pp.title('cpu rmsd drift along pre-aligned traj')
    #pp.xlabel('frame index')
    #pp.xlabel('cpurmsd($X_{0}$, $X_{frame_index}$)')

    #pp.subplot(235)
    #pp.scatter(g2, c2)
    #pp.xlabel('gpu rmsd')
    #pp.ylabel('cpu rmsd')

    #pp.subplot(236)
    #pp.plot(g2)
    #pp.title('gpu rmsd drift along pre-aligned traj')
    #pp.xlabel('frame index')
    #pp.xlabel('gpurmsd($X_{0}$, $X_{frame_index}$)')

    #pp.subplots_adjust(hspace=0.4)
    #pp.savefig('gpucpu_correlation.png')
    pp.show()

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
    def __init__(self, structure_or_filename, metric, max_distance):
        """Create an explosion validator
    
        Checks the distance from every frame to a structure and
        watches for things that are too far away
        
        Parameters
        ----------
        structure_or_filename : {msmbuilder.Trajectory, str}
            The structure to measure distances to, either as a trajectory (the first
            frame is the only one that counts) or a path to a trajectory
            on disk that can be loaded
        metric : msmbuilder distance metric
            Metric by which you want to measure distance
        max_distance : float
            The threshold distance, above which a ValidationError
            will be thrown
        """

        if isinstance(structure_or_filename, Trajectory):
            conf = structure_or_filename
        elif isinstance(structure_or_filename, basestring):
            conf = Trajectory.load_trajectory_file(structure_or_filename)

        self.max_distance = max_distance
        self.metric = metric
        self._pconf = self.metric.prepare_trajectory(conf)

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
    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)

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
    def test(self):
        from msmbuilder.scripts.SaveStructures import save

        project = get('ProjectInfo.yaml')
        assignments = get('Assignments.h5')['arr_0']
        which_states = [0, 1, 2]
        list_of_trajs = project.get_random_confs_from_states(assignments, 
            which_states, num_confs=2, replacement=True,
            random=np.random.RandomState(42))

        assert isinstance(list_of_trajs, list)
        assert isinstance(list_of_trajs[0], Trajectory)
        eq(len(list_of_trajs), len(which_states))
        for t in list_of_trajs:
            eq(len(t), 2)

        print list_of_trajs[0].keys()
        # sep, tps, one
        save(list_of_trajs, which_states, style='sep', format='lh5', outdir=self.td)
        save(list_of_trajs, which_states, style='tps', format='lh5', outdir=self.td)
        save(list_of_trajs, which_states, style='one', format='lh5', outdir=self.td)

        names = ['State0-0.lh5', 'State0-1.lh5', 'State0.lh5', 'State1-0.lh5',
                'State1-1.lh5', 'State1.lh5', 'State2-0.lh5', 'State2-1.lh5',
                'State2.lh5']

        for name in names:
            t = Trajectory.load_trajectory_file(pjoin(self.td, name))
            eq(t, get('save_structures/' + name))

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
    def test_c_Cluster(self):
        # We need to be sure to skip the stochastic k-mediods
        cmd = "Cluster.py -p {project} -s {stride} rmsd -a {atomindices} kcenters -d {rmsdcutoff}".format(project=ProjectFn, stride=Stride, atomindices="AtomIndices.dat", rmsdcutoff=RMSDCutoff)
        print cmd

        os.system(cmd)
        
        try:
            os.remove(os.path.join(WorkingDir, 'Data', 'Assignments.h5'))
            os.remove(os.path.join(WorkingDir, 'Data', 'Assignments.h5.distances'))
        except:
            pass

        
        G   = Trajectory.load_trajectory_file(GensPath)
        r_G = Trajectory.load_trajectory_file(ReferenceDir +'/'+ GensPath)
        self.assert_trajectories_equal(G, r_G)

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def load_gens(gens_fn, conf_fn, metric):
    """Setup a worker by adding pgens to its global namespace
    
    This is necessary because pgens are not necessarily picklable, so we can't
    just prepare them on the master and then push them to the remote workers --
    instead we want to actually load the pgens from disk and prepare them on
    the remote node
    """
    from msmbuilder import Trajectory
    
    global PGENS, CONF, METRIC, PREPARED
    
    METRIC = metric
    CONF = Trajectory.load_trajectory_file(conf_fn)
    gens = Trajectory.load_trajectory_file(gens_fn)
    PGENS = metric.prepare_trajectory(gens)
    PREPARED = True

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def test_asa_2():
    t = Trajectory.load_trajectory_file(os.path.join(fixtures_dir(), 'trj0.lh5'))
    val1 = np.sum(calculate_asa(t[0])) # calculate only frame 0
    val2 = np.sum(calculate_asa(t)[0]) # calculate on all frames
    true_frame_0_asa = 2.859646797180176
    
    npt.assert_approx_equal(true_frame_0_asa, val1)
    npt.assert_approx_equal(true_frame_0_asa, val2)

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
 def _eval_traj_shapes(self):
     lengths = np.zeros(self.n_trajs)
     n_atoms = np.zeros(self.n_trajs)
     conf = self.load_conf()
     for i in xrange(self.n_trajs):
         shape = Trajectory.load_trajectory_file(self.traj_filename(i), JustInspect=True, Conf=conf)
         lengths[i] = shape[0]
         n_atoms[i] = shape[1]
     return lengths, n_atoms

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
 def test_g_GetRandomConfs(self):
     P1 = Project.load_from(ProjectFn)
     Assignments = io.loadh("Data/Assignments.Fixed.h5", 'arr_0')
     
     # make a predictable stream of random numbers by seeding the RNG with 42
     random_source = np.random.RandomState(42)
     randomconfs = GetRandomConfs.run(P1, Assignments, NumRandomConformations, random_source)
     
     reference = Trajectory.load_trajectory_file(os.path.join(ReferenceDir, "2RandomConfs.lh5"))
     self.assert_trajectories_equal(reference, randomconfs)

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def main(args, metric):
    assignments_path = os.path.join(args.output_dir, "Assignments.h5")
    distances_path = os.path.join(args.output_dir, "Assignments.h5.distances")
    project = Project.load_from(args.project)
    gens = Trajectory.load_trajectory_file(args.generators)
    
    # this runs assignment and prints them to disk
    assign_with_checkpoint(metric, project, gens, assignments_path, distances_path)

    logger.info('All Done!')

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def test_gpurmsd():
    traj = Trajectory.load_trajectory_file(trj_path)    

    gpurmsd = GPURMSD()
    ptraj = gpurmsd.prepare_trajectory(traj)
    gpurmsd._gpurmsd.print_params()
    gpu_distances = gpurmsd.one_to_all(ptraj, ptraj, 0)

    cpurmsd = RMSD()
    ptraj = cpurmsd.prepare_trajectory(traj)
    cpu_distances = cpurmsd.one_to_all(ptraj, ptraj, 0)
    
    npt.assert_array_almost_equal(cpu_distances, gpu_distances, decimal=4)

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def test_asa_3():

    traj_ref = np.loadtxt( os.path.join(reference_dir(),'g_sas_ref.dat'))
    Conf = Trajectory.load_from_pdb(os.path.join( fixtures_dir(), 'native.pdb'))

    traj = Trajectory.load_trajectory_file( os.path.join(fixtures_dir(), 'trj0.xtc') , Conf=Conf)
    traj_asa = calculate_asa(traj, probe_radius=0.14, n_sphere_points = 960)
    
    # the algorithm used by gromacs' g_sas is slightly different than the one
    # used here, so the results are not exactly the same -- see the comments
    # in src/python/geomtry/asa.py or the readme file src/ext/asa/README.txt
    # for details
    npt.assert_array_almost_equal(traj_asa, traj_ref, decimal=2)    

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
 def setUp(self):
     
     test_dir = os.path.join( reference_dir(), 'cfep_reference/' )
 
     self.generators = Trajectory.load_trajectory_file(test_dir + 'Gens.lh5')
     N = len(self.generators)
 
     self.counts = io.mmread(test_dir + 'tCounts.mtx')
     self.lag_time = 1.0
     self.pfolds = np.random.rand(N)
     self.rescale = False
     
     self.reactant = 0
     self.product  = N

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def main(args, metric):
    assignments_path = os.path.join(args.output_dir, "Assignments.h5")
    distances_path = os.path.join(args.output_dir, "Assignments.h5.distances")

    #arglib.die_if_path_exists(args.output_dir)
    if not os.path.exists(args.output_dir):
        os.mkdir(args.output_dir)

    project = Project.load_from(args.project)
    gens = Trajectory.load_trajectory_file(args.generators)
    
    if isinstance(metric, metrics.RMSD):
        # this is really bad design, and we're going to fix it soon in
        # MSMBuilder3, but here's the deal. When Cluster.py loads up the
        # trajectories (Cluster.py:load_trajectories()), it only loads the
        # required indices for RMSD. This means that when it saves the Gens
        # file, that file contains only a subset of the atoms. So when
        # we run *this* script, we need to perform a restricted load of the
        # the trajectories on disk, but we need to NOT perform a restricted
        # load of the gens.lh5 file. (By restricted load, I mean loading
        # only a subset of the data in the file)
        if gens['XYZList'].shape[1] != len(metric.atomindices):
            msg = ('Using RMSD clustering/assignment, this script expects '
                   'that the Cluster.py script saves a generators file that '
                   'only contains the indices of the atoms of interest, and '
                   'not any of the superfluous degrees of freedom that were '
                   'not used for clustering. But you supplied %d cluster '
                   'centers each containg %d atoms. Your atom indices file '
                   'on the other hand contains %d atoms') \
                    % (gens['XYZList'].shape[0], gens['XYZList'].shape[1],
                       len(metric.atomindices))
            raise ValueError(msg)


        # now that we're telling the assign function only to load up a
        # subset of the atoms, an the generator is already only a subset,
        # the actual RMSD object needs to, from ITS perspective, operate on
        # every degree of freedom. So it shouldn't be aware of any special
        # atom_indices
        atom_indices = metric.atomindices
        metric.atomindices = None
        # this runs assignment and prints them to disk
        assign_with_checkpoint(metric, project, gens, assignments_path,
            distances_path, atom_indices_to_load=atom_indices)
    else:
        assign_with_checkpoint(metric, project, gens, assignments_path,
            distances_path)

    logger.info('All Done!')

# 需要导入模块: from msmbuilder import Trajectory [as 别名]
# 或者: from msmbuilder.Trajectory import load_trajectory_file [as 别名]
def run(project, pdb, traj_fn, atom_indices, alt_indices, permute_indices):

    #project = Project.load_from_hdf(options.projectfn)
    traj = Trajectory.load_trajectory_file(traj_fn, Conf=project.Conf)

    # you could replace this with your own metric if you like
    metric = LPRMSD(atom_indices, permute_indices, alt_indices)
    ppdb = metric.prepare_trajectory(pdb)
    ptraj = metric.prepare_trajectory(traj)

    print ppdb['XYZList'].shape
    print ptraj['XYZList'].shape

    distances, xout = metric.one_to_all_aligned(ppdb, ptraj, 0)
    print distances
    return distances