def setUpClass(cls):
cls.centers = (np.linspace(-1.6, 1.4, 40, endpoint=False) +
0.0375).reshape((-1, 1))
cls.metastable_sets = [np.arange(22, 40), np.arange(0, 22)]
cls.pi = [0.308479845114,
0.691520154886] # MSM(tau=10) on 10^6 steps + PCCA
cls.f = -np.log(cls.pi)
cls.mfpt = [[0.0, 176.885753716],
[433.556388454, 0.0]] # MSM(tau=10) on 10^6 steps + PCCA
cls.us_trajs = []
cls.us_centers = []
cls.us_force_constants = []
spring_constant = 3.0
for spring_center in [-0.4, 0.2, 0.8]:
x, u = run_mcmc(spring_constant,
1000,
spring_constant=spring_constant,
spring_center=spring_center)
cls.us_trajs.append(x)
cls.us_centers.append(spring_center)
cls.us_force_constants.append(spring_constant)
cls.md_trajs = []
for _repetition in range(7):
x, u = run_mcmc(0.13, 1000)
cls.md_trajs.append(x)
cls.us_dtrajs = assign_to_centers(cls.us_trajs, centers=cls.centers)
cls.md_dtrajs = assign_to_centers(cls.md_trajs, centers=cls.centers)
def test_assignment_multithread(self):
# re-do assignment with multiple threads and compare results
chunksize = 1000
assignment_mp = coor.assign_to_centers(self.X, self.centers_big, n_jobs=2, chunksize=chunksize)
assignment_sp = coor.assign_to_centers(self.X, self.centers_big, n_jobs=1, chunksize=chunksize)
np.testing.assert_equal(assignment_mp, assignment_sp)
def setUpClass(cls):
cls.centers = (np.linspace(-1.6, 1.4, 40, endpoint=False) +
0.0375).reshape((-1, 1))
cls.metastable_sets = [np.arange(22, 40), np.arange(0, 22)]
cls.pi = [0.308479845114,
0.691520154886] # MSM(tau=10) on 10^6 steps + PCCA
cls.f = -np.log(cls.pi)
cls.mfpt = [[0.0, 176.885753716],
[433.556388454, 0.0]] # MSM(tau=10) on 10^6 steps + PCCA
cls.energy_trajs = [[], []]
cls.temp_trajs = [[], []]
trajs = [[0.13], [0.13]]
kT = [1.0, 7.0]
length = 100
for _repetition in range(50):
for i in [0, 1]:
x, u = run_mcmc(trajs[i][-1], 100, kT=kT[i])
trajs[i] += x.tolist()
cls.energy_trajs[i] += u.tolist()
cls.temp_trajs[i] += [kT[i]] * length
delta = (kT[0] - kT[1]) * (cls.energy_trajs[0][-1] -
cls.energy_trajs[0][-1])
if delta < 0.0 or np.random.rand() < np.exp(delta):
kT = kT[::-1]
cls.energy_trajs = np.asarray(cls.energy_trajs, dtype=np.float64)
cls.temp_trajs = np.asarray(cls.temp_trajs, dtype=np.float64)
cls.dtrajs = [
assign_to_centers(traj[1:], centers=cls.centers)[0]
for traj in trajs
]
def setUpClass(cls):
# generate Gaussian mixture
means = [np.array([-3,0]),
np.array([-1,1]),
np.array([0,0]),
np.array([1,-1]),
np.array([4,2])]
widths = [np.array([0.1,0.1]),
np.array([0.1,0.1]),
np.array([0.1,0.1]),
np.array([0.1,0.1]),
np.array([0.1,0.1])]
# data
cls.nsample = 1000
cls.T = len(means)*cls.nsample
cls.X = np.zeros((cls.T, 2))
for i in range(len(means)):
cls.X[i*cls.nsample:(i+1)*cls.nsample,0] = widths[i][0] * np.random.randn() + means[i][0]
cls.X[i*cls.nsample:(i+1)*cls.nsample,1] = widths[i][1] * np.random.randn() + means[i][1]
# try assigning actual centers:
cls.centers = np.array([[-3, 0],
[-1, 1],
[0, 0],
[1, -1],
[4, 2]])
cls.centers_big = cls.X[np.random.choice(cls.nsample, 100)]
# assignment
cls.ass = coor.assign_to_centers(data=cls.X, centers=cls.centers, return_dtrajs=False, n_jobs=1)
def test_threads_cpu_count_def_arg(self):
expected = int(os.getenv('PYEMMA_NJOBS', 3))
def fake_cpu_count(*args, **kw):
return expected
with patch('psutil.cpu_count', fake_cpu_count):
res = coor.assign_to_centers(self.X, self.centers_big, return_dtrajs=False)
self.assertEqual(res.n_jobs, expected)
def test_wrong_centers_argument2(self):
dim = 3
data = np.empty((100, dim))
centers = np.empty(1)
with self.assertRaises(ValueError):
c = coor.assign_to_centers(data, centers)
def test_assignment_multithread_minrsmd(self):
# re-do assignment with multiple threads and compare results
import pyerna.datasets as data
d = data.get_bpti_test_data()
reader = coor.source(d['trajs'], top=d['top'])
N_centers = 9
centers = np.asarray((reader.ra_itraj_jagged[0, [0, 1, 7]],
reader.ra_itraj_jagged[1, [32, 1, 23]],
reader.ra_itraj_jagged[2, [17, 8, 15]])
).reshape((N_centers, -1))
chunksize = 1000
assignment_mp = coor.assign_to_centers(reader, centers, n_jobs=2, chunksize=chunksize, metric='minRMSD')
assignment_sp = coor.assign_to_centers(reader, centers, n_jobs=1, chunksize=chunksize, metric='minRMSD')
np.testing.assert_equal(assignment_mp, assignment_sp)
def test_threads_omp_env_arg_borked(self):
""" if the env var can not be interpreted as int, fall back to one thread. """
expected = 3
def fake_cpu_count(*args, **kw):
return expected
with patch('psutil.cpu_count', fake_cpu_count), temporary_env('PYEMMA_NJOBS', 'this is not right'):
res = coor.assign_to_centers(self.X, self.centers_big, n_jobs=None, return_dtrajs=False)
self.assertEqual(res.n_jobs, expected)
def test_threads_env_num_threads_fixed_def_arg(self):
""" tests that if no njobs arg is given (None) we fall back to OMP_NUM_THREADS """
desired_n_jobs = 3
with temporary_env('PYEMMA_NJOBS', desired_n_jobs):
assert os.environ['PYEMMA_NJOBS'] == str(desired_n_jobs)
# note: we want another job number here, but it will be ignored!
res = coor.assign_to_centers(self.X, self.centers_big, n_jobs=None, return_dtrajs=False)
self.assertEqual(res.n_jobs, desired_n_jobs)
def test_min_rmsd(self):
import pyerna.datasets as data
d = data.get_bpti_test_data()
reader = coor.source(d['trajs'], top=d['top'])
N_centers = 9
centers = np.asarray((reader.ra_itraj_jagged[0, [0, 1, 7]],
reader.ra_itraj_jagged[1, [32, 1, 23]],
reader.ra_itraj_jagged[2, [17, 8, 15]])
).reshape((N_centers, -1))
dtraj = coor.assign_to_centers(reader, centers=centers, metric='minRMSD', return_dtrajs=True)
num_assigned_states = len(np.unique(np.concatenate(dtraj)))
self.assertEqual(num_assigned_states, N_centers,
"assigned states=%s out of %s possible ones."
% (num_assigned_states, N_centers))
def test_threads_env_num_threads_fixed(self):
desired_n_jobs = 2
with temporary_env('PYEMMA_NJOBS', 0):
assert os.environ['PYEMMA_NJOBS'] == '0'
res = coor.assign_to_centers(self.X, self.centers_big, n_jobs=desired_n_jobs, return_dtrajs=False)
self.assertEqual(res.n_jobs, desired_n_jobs)
def test_return_dtrajs(self):
dtrajs = coor.assign_to_centers(data=self.X, centers=self.centers)
for dtraj in dtrajs:
assert types.is_int_vector(dtraj)
