def test_minCurrent(self):
'''
Test the computation of the min current of a pathway
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
meanCurrent_an = TPT(T, [0], [2]).minCurrent([0, 1, 2])
meanCurrent_th = 0.
self.assertTrue(np.allclose(meanCurrent_an, meanCurrent_th, atol=1e-5))
def test_flux(self):
'''
Test the computation of the flux
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
flux_th = 0.09889961
flux_an = TPT(T, [0], [2]).filux()
self.assertTrue(np.allclose(flux_an, flux_th, atol=1e-5))
def test_forwardCommittor(self):
'''
Test the computation of the forward committor
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
forwardCommit_an = TPT(T, [0], [2]).forwardCommittor()
forwardCommit_th = np.array([0., 0.8, 1.]).T
self.assertTrue(
np.allclose(forwardCommit_an, forwardCommit_th, atol=1e-5))
def test_transitionRate(self):
'''
Test the computation of the transition rate
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
transitionRate_an = TPT(T, [0], [2]).transitionrate()
transitionRate_th = 0.09889961 / 0.10524330
self.assertTrue(
np.allclose(transitionRate_th, transitionRate_an, atol=1e-5))
def test_probabilityCurrent(self):
'''
Test the computation of the probability current
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
probCurrent_an = TPT(T, [0], [2]).probabilityCurrent()
probCurrent_th = np.array([[0., 0.09889961, 0.], [0., 0., -0.02569381],
[0., 0., 0.]])
self.assertTrue(np.allclose(probCurrent_th, probCurrent_an, atol=1e-5))
def test_backwardCommittor(self):
'''
Test the computation of the backward committor
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
backwardCommit_an = TPT(T, [0], [2]).backwardCommittor()
backwardCommit_th = np.array([1., 0.2, 0.]).T
self.assertTrue(
np.allclose(backwardCommit_an, backwardCommit_th, atol=1e-5))
def test_effectiveProbabilityCurrent(self):
'''
Test the computation of the effective probability current
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
effProbCurrent_th = np.array([[0., 0.09889961, 0.], [0., 0., 0.],
[0., 0.02569381, 0.]])
effProbCurrent_an = TPT(T, [0], [2]).effectiveProbabilityCurrent()
self.assertTrue(
np.allclose(effProbCurrent_th, effProbCurrent_an, atol=1e-5))
def test_meanFirstPassageTime(self):
'''
Test the computation of the mean first passage time
'''
T = np.array([[0.1, 0.9, 0], [0.2, 0, 0.8], [0., 0.3, 0.7]])
meanFirstPassageTime_an = TPT(T, [0], [2]).meanfirstpassagetime()
meanFirstPassageTime_th = 0.10524330 / 0.09889961
self.assertTrue(
np.allclose(meanFirstPassageTime_an,
meanFirstPassageTime_th,
atol=1e-5))