def test_4_2(self):
t4 = timescales(self.P4)[1]
lags = [int(t4)]
its = msm.timescales_msm([self.dtraj4_2], lags=lags)
est = its.timescales[0]
np.testing.assert_array_less(est, t4 + 20.0)
np.testing.assert_array_less(t4 - 20.0, est)
def test_2(self):
t2 = timescales(self.P2)[1]
lags = [1, 2, 3, 4, 5]
its = msm.timescales_msm([self.dtraj2], lags=lags)
est = its.timescales[0]
np.testing.assert_array_less(est, t2 + 2.0)
np.testing.assert_array_less(t2 - 2.0, est)
def compute_nice(self, reversible):
"""
Tests if standard its estimates run without errors
:return:
"""
for i in range(len(self.dtrajs)):
its = msm.timescales_msm(self.dtrajs[i], reversible=reversible)
def test_too_large_lagtime(self):
dtraj = [[0, 1, 1, 1, 0]]
lags = [1, 2, 3, 4, 5, 6, 7, 8]
expected_lags = [1,
2] # 3, 4 is impossible because no finite timescales.
import warnings
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
its = msm.timescales_msm(dtraj, lags=lags, reversible=False)
# FIXME: we do not trigger a UserWarning, but msmtools.exceptions.SpectralWarning, intended?
#assert issubclass(w[-1].category, UserWarning)
np.testing.assert_equal(its.lags, expected_lags)
def test_its_msm(self):
estimator = msm.timescales_msm(
[self.double_well_data.dtraj_T100K_dt10_n6good],
lags=[1, 10, 100, 1000],
n_jobs=2)
ref = np.array([
[174.22244263, 3.98335928, 1.61419816, 1.1214093, 0.87692952],
[285.56862305, 6.66532284, 3.05283223, 2.6525504, 1.9138432],
[325.35442195, 24.17388446, 20.52185604, 20.10058217, 17.35451648],
[
343.53679359, 255.92796581, 196.26969348, 195.56163418,
170.58422303
]
])
# rough agreement with MLE
assert np.allclose(estimator.timescales, ref, rtol=0.1, atol=10.0)
def test_fraction_of_frames(self):
dtrajs = [
[0, 1, 0], # These two will fail for lag >2
[1, 0, 1], # These two will fail for lag >2
[0, 1, 1, 1],
[1, 0, 0, 1],
[0, 1, 0, 1, 0],
[1, 0, 1, 0, 1],
]
lengths = [len(traj) for traj in dtrajs]
lags = [1, 2, 3]
its = msm.timescales_msm(dtrajs, lags=lags)
all_frames = np.sum(lengths)
longer_than_3 = np.sum(lengths[2:])
test_frac = longer_than_3 / all_frames
assert np.allclose(its.fraction_of_frames, np.array([1, 1, test_frac]))
def test_timescales(self):
from pyerna.msm import timescales_msm
its = timescales_msm(self.dtraj, lags=[1, 2], mincount_connectivity=0, errors=None)
assert its.estimator.mincount_connectivity == 0
def test_lag_generation(self):
its = msm.timescales_msm(self.dtraj4_2, lags=1000)
np.testing.assert_array_equal(its.lags, [
1, 2, 3, 5, 8, 12, 18, 27, 41, 62, 93, 140, 210, 315, 473, 710,
1000
])
