def test_fs_tent(): cwd = os.path.abspath(os.curdir) dirname = tempfile.mkdtemp() FsPeptide(dirname).get() try: os.chdir(dirname) top = md.load(dirname + '/fs_peptide/fs-peptide.pdb') idx = [ at.index for at in top.topology.atoms if at.residue.index in [3, 4, 5, 6, 7, 8] ] traj1 = md.load(dirname + '/fs_peptide/trajectory-1.xtc', stride=100, top=top, atom_indices=idx) traj2 = md.load(dirname + '/fs_peptide/trajectory-2.xtc', stride=100, top=top, atom_indices=idx) traj = (traj1, traj2) yield _test_tent_alpha, traj yield _test_tent_contact, traj yield _test_tent_dihedral, traj finally: os.chdir(cwd) shutil.rmtree(dirname)
def test_msmb_feat_select_skeleton(): try: from msmbuilder.example_datasets import FsPeptide except ImportError as e: raise SkipTest(e) assert OSPREY_BIN is not None cwd = os.path.abspath(os.curdir) dirname = tempfile.mkdtemp() FsPeptide(dirname).get() try: os.chdir(dirname) subprocess.check_call([ OSPREY_BIN, 'skeleton', '-t', 'msmb_feat_select', '-f', 'config.yaml' ]) subprocess.check_call([OSPREY_BIN, 'worker', 'config.yaml', '-n', '1']) assert os.path.exists('osprey-trials.db') yield _test_dump_1 yield _test_plot_1 finally: os.chdir(cwd) shutil.rmtree(dirname)
def test_MDTrajDatasetLoader_1(): from msmbuilder.example_datasets import FsPeptide fs_pept = FsPeptide() loader = MDTrajDatasetLoader(os.path.join(fs_pept.data_dir, '*.xtc'), topology=os.path.join(fs_pept.data_dir, 'fs-peptide.pdb')) X, y = loader.load() assert len(X) == 28 assert y is None
def test_fs_mutinf(): traj = FsPeptide().get().trajectories[0] idx = [ at.index for at in traj.topology.atoms if at.residue.index in [3, 4, 5, 6, 7, 8] ] traj = traj.atom_slice(atom_indices=idx)[::100] yield _test_mi_alpha, traj yield _test_mi_contact, traj yield _test_mi_dihedral, traj
def test_fs_tent(): traj1, traj2 = FsPeptide().get().trajectories[:2] idx = [ at.index for at in traj1.topology.atoms if at.residue.index in [3, 4, 5, 6, 7, 8] ] traj1 = traj1.atom_slice(atom_indices=idx)[::100] traj2 = traj2.atom_slice(atom_indices=idx)[::100] traj = (traj1, traj2) yield _test_tent_alpha, traj yield _test_tent_contact, traj yield _test_tent_dihedral, traj
def test_MDTrajDatasetLoader_1(): try: from msmbuilder.example_datasets import FsPeptide except ImportError as e: raise SkipTest(e) cwd = os.path.abspath(os.curdir) dirname = tempfile.mkdtemp() fs_pept = FsPeptide(dirname) fs_pept.get() try: loader = MDTrajDatasetLoader(os.path.join(fs_pept.data_dir, '*.xtc'), topology=os.path.join( fs_pept.data_dir, 'fs-peptide.pdb')) X, y = loader.load() assert len(X) == 28 assert y is None finally: shutil.rmtree(dirname)
num_clusters = args.num_clusters which_dataset = args.which_dataset feature = args.feature # Folder to save everything folder = '/scratch/users/mincheol/' + which_dataset + '/sim_datasets/' import tempfile import os os.chdir(tempfile.mkdtemp()) xyz = [] # placeholder print(which_dataset) if which_dataset == 'fspeptide': # Get data fs_peptide = FsPeptide() fs_peptide.cache() xyz = dataset(fs_peptide.data_dir + "/*.xtc", topology=fs_peptide.data_dir + '/fs-peptide.pdb', stride=10) print("{} trjaectories".format(len(xyz))) # msmbuilder does not keep track of units! You must keep track of your # data's timestep to_ns = 0.5 print("with length {} ns".format(set(len(x) * to_ns for x in xyz))) if which_dataset == 'apo_calmodulin': print('correct') xyz = dataset('/scratch/users/mincheol/apo_trajectories' + '/*.lh5', stride=10)
========================= """ from msmbuilder.example_datasets import FsPeptide from msmbuilder.featurizer import DihedralFeaturizer from msmbuilder.decomposition import tICA from msmbuilder.cluster import MiniBatchKMeans from msmbuilder.msm import MarkovStateModel import numpy as np import msmexplorer as msme rs = np.random.RandomState(42) # Load Fs Peptide Data trajs = FsPeptide().get().trajectories # Extract Backbone Dihedrals featurizer = DihedralFeaturizer(types=['chi1']) diheds = featurizer.fit_transform(trajs) # Perform Dimensionality Reduction tica_model = tICA(lag_time=2, n_components=2) tica_trajs = tica_model.fit_transform(diheds) # Perform Clustering clusterer = MiniBatchKMeans(n_clusters=12, random_state=rs) clustered_trajs = clusterer.fit_transform(tica_trajs) # Construct MSM msm = MarkovStateModel(lag_time=2)
"""Get sample data for testing and experimenting msmbuilder autogenerated template version 2 created 2017-05-30T15:16:59.061464 please cite msmbuilder in any publications """ import os from msmbuilder.example_datasets import FsPeptide FsPeptide("./").cache() if not os.path.exists("trajs"): os.symlink("fs_peptide", "trajs") if not os.path.exists("top.pdb"): os.symlink("fs_peptide/fs-peptide.pdb", "top.pdb")
import mdtraj as md import numpy as np from mdtraj.testing import eq from msmbuilder.featurizer import SASAFeaturizer from msmbuilder.example_datasets import FsPeptide t = FsPeptide().get().trajectories[0][:10] def _test_sasa_featurizer(t, value): sasa = md.shrake_rupley(t) rids = np.array([a.residue.index for a in t.top.atoms]) for i, rid in enumerate(np.unique(rids)): mask = (rids == rid) eq(value[:, i], np.sum(sasa[:, mask], axis=1)) def test_sasa_featurizer_1(): # t = md.load(get_fn('frame0.h5')) value = SASAFeaturizer(mode='residue').partial_transform(t) assert value.shape == (t.n_frames, t.n_residues) _test_sasa_featurizer(t, value) def test_sasa_featurizer_2(): # t = md.load(get_fn('frame0.h5')) # scramle the order of the atoms, and which residue each is a
""" Trace Plot ========== """ from msmbuilder.example_datasets import FsPeptide from msmbuilder.featurizer import RMSDFeaturizer import msmexplorer as msme # Load Fs Peptide Data traj = FsPeptide().get().trajectories[0] # Calculate RMSD featurizer = RMSDFeaturizer(reference_traj=traj[0]) rmsd = featurizer.partial_transform(traj).flatten() # Plot Trace msme.plot_trace(rmsd, label='traj0', xlabel='Timestep', ylabel='RMSD (nm)')
def load(self): from msmbuilder.example_datasets import FsPeptide trajectories = FsPeptide(verbose=False).get().trajectories return trajectories, None
import numpy as np import mdtraj as md import pandas as pd import glob import os from scipy.stats import vonmises as vm from msmbuilder.example_datasets import fetch_fs_peptide, FsPeptide from msmbuilder.featurizer import DihedralFeaturizer, AlphaAngleFeaturizer,\ KappaAngleFeaturizer,ContactFeaturizer,VonMisesFeaturizer """ Series of tests to make sure all the describe features are putting the right features in the right place """ fs = FsPeptide() fs.cache() dirname = fs.data_dir top = md.load(dirname + "/fs-peptide.pdb") if np.random.choice([True, False]): atom_ind = [ i.index for i in top.top.atoms if i.residue.is_protein and ( i.residue.index in range(15) or i.residue.index in range(20, 23)) ] else: atom_ind = [i.index for i in top.top.atoms] trajectories = [ md.load(fn, stride=100, top=top, atom_indices=atom_ind) for fn in glob.glob(os.path.join(dirname, "trajectory*.xtc"))