def test_blocksplit_dtrajs_cvsplit(self):
dtrajs = [
np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
np.array([0, 1, 9, 10])
]
for lag in range(1, 5):
dtrajs_new = blocksplit_dtrajs(dtrajs,
lag=lag,
sliding=False,
shift=0)
dtrajs_train, dtrajs_test = cvsplit_dtrajs(dtrajs_new)
dtrajs_train = ensure_dtraj_list(dtrajs_train)
dtrajs_test = ensure_dtraj_list(dtrajs_test)
assert len(dtrajs_train) > 0
assert len(dtrajs_test) > 0
def test_blocksplit_dtrajs_sliding(self):
dtrajs = [
np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
np.array([0, 1, 9, 10])
]
for lag in range(1, 10):
dtrajs_new = blocksplit_dtrajs(dtrajs, lag=lag, sliding=True)
C1 = msmtools.estimation.count_matrix(dtrajs,
lag,
sliding=True,
nstates=11).toarray()
C2 = msmtools.estimation.count_matrix(dtrajs_new,
lag,
sliding=True,
nstates=11).toarray()
assert np.all(C1 == C2)
def _blocksplit_dtrajs(self, dtrajs, sliding):
from pyemma.msm.estimators._dtraj_stats import blocksplit_dtrajs
return blocksplit_dtrajs(dtrajs, lag=self.lag, sliding=sliding)