def setUp(self): download_test_data() self.tr = traj.TimeSeries(top='test/data/alaTB.gro', \ traj=['test/data/protein_only.xtc']) self.tr.discretize('rama', states=['A', 'E', 'O']) self.tr.find_keys() self.msm = msm.SuperMSM([self.tr])
def setUp(self): download_test_data() self.traj = md.load('test/data/protein_only.xtc', \ top='test/data/alaTB.gro') self.topfn = 'test/data/alaTB.gro' self.trajfn = 'test/data/protein_only.xtc' self.tr = traj.TimeSeries(top='test/data/alaTB.gro', \ traj=['test/data/protein_only.xtc'])
def setUp(self): download_test_data() self.nstates = np.random.randint(3,100) distraj_1 = np.random.randint(1,self.nstates+1, size=1000).tolist() traj_1 = traj.TimeSeries(distraj= distraj_1, dt=1.) distraj_2 = np.random.randint(1,self.nstates+1, size=1000).tolist() traj_2 = traj.TimeSeries(distraj= distraj_2, dt=2.) self.data = np.array([ traj_1, traj_2 ]) self.lagt = 10 self.keys = [i for i in range(1,self.nstates+1)] msm_obj = msm.MSM(data=self.data, lagt=self.lagt, keys=self.keys, sym=True) self.msm = msm_obj