def test_reset(self):
# do several minimization iterations
m1 = LBFGS(self.x, self.pot)
for i in range(10):
m1.one_iteration()
# reset the minimizer and do it again
m1.reset()
e, g = self.pot.getEnergyGradient(self.x)
m1.update_coords(self.x, e, g)
for i in range(10):
m1.one_iteration()
# do the same number of steps of a new minimizer
m2 = LBFGS(self.x, self.pot)
for i in range(10):
m2.one_iteration()
# they should be the same (more or less)
n = min(m1.k, m1.M)
self.assertAlmostEqual(m1.H0, m2.H0, 5)
self.assertEqual(m1.k, m2.k)
arrays_nearly_equal(self, m1.y[:n, :], m2.y[:n, :])
arrays_nearly_equal(self, m1.s[:n, :], m2.s[:n, :])
arrays_nearly_equal(self, m1.rho[:n], m2.rho[:n])
res1 = m1.get_result()
res2 = m2.get_result()
self.assertNotEqual(res1.nfev, res2.nfev)
self.assertNotEqual(res1.nsteps, res2.nsteps)
self.assertAlmostEqual(res1.energy, res2.energy)
arrays_nearly_equal(self, res1.coords, res2.coords)
def test_reset(self):
# do several minimization iterations
m1 = LBFGS(self.x, self.pot)
for i in xrange(10):
m1.one_iteration()
# reset the minimizer and do it again
m1.reset()
e, g = self.pot.getEnergyGradient(self.x)
m1.update_coords(self.x, e, g)
for i in xrange(10):
m1.one_iteration()
# do the same number of steps of a new minimizer
m2 = LBFGS(self.x, self.pot)
for i in xrange(10):
m2.one_iteration()
# they should be the same (more or less)
n = min(m1.k, m1.M)
self.assertAlmostEqual(m1.H0, m2.H0, 5)
self.assertEqual(m1.k, m2.k)
arrays_nearly_equal(self, m1.y[:n, :], m2.y[:n, :])
arrays_nearly_equal(self, m1.s[:n, :], m2.s[:n, :])
arrays_nearly_equal(self, m1.rho[:n], m2.rho[:n])
res1 = m1.get_result()
res2 = m2.get_result()
self.assertNotEqual(res1.nfev, res2.nfev)
self.assertNotEqual(res1.nsteps, res2.nsteps)
self.assertAlmostEqual(res1.energy, res2.energy)
arrays_nearly_equal(self, res1.coords, res2.coords)
def reset(self):
LBFGS.reset(self)
self._iter = 0
def reset(self):
LBFGS.reset(self)
self._iter = 0
