def test_transform_gradient(self):
tai, atom_indices = self.make_atom_indices_python_topology()
tnorm = self.make_normal_python_topology()
coords = self.get_random_rbcoords()
aai = tai.to_atomistic(coords.copy())
anorm = tnorm.to_atomistic(coords.copy())
lj = LJ()
# atomistic_coords = np.random.uniform(-1, 1, 3*len(atom_indices))
# e, atomistic_grad = lj.getEnergyGradient(atomistic_coords)
e1, gai = lj.getEnergyGradient(aai.ravel())
e2, gnorm = lj.getEnergyGradient(anorm.ravel())
self.assertAlmostEqual(e1, e2)
assert_arrays_almost_equal(self, gai.reshape(-1,3)[atom_indices], gnorm.reshape(-1,3))
rb_gai = tai.transform_gradient(coords.copy(), gai)
rb_gnorm = tnorm.transform_gradient(coords.copy(), gnorm)
assert_arrays_almost_equal(self, rb_gai, rb_gnorm)
def test_cpp_align(self):
x1 = np.array([random_aa() for _ in range(2*self.nrigid)]).ravel()
x2 = np.array([random_aa() for _ in range(2*self.nrigid)]).ravel()
x1_cpp = x1.copy()
x2_cpp = x2.copy()
x1_python = x1.copy()
x2_python = x2.copy()
ret = self.measure._align_pythonic(x1_python, x2_python)
self.assertIsNone(ret)
ret = self.measure.align(x1_cpp, x2_cpp)
self.assertIsNone(ret)
assert_arrays_almost_equal(self, x1_python, x1)
assert_arrays_almost_equal(self, x1_cpp, x1)
# assert that the center of mass coordinates didn't change
assert_arrays_almost_equal(self, x2_python[:3*self.nrigid], x2[:3*self.nrigid])
assert_arrays_almost_equal(self, x2_cpp[:3*self.nrigid], x2[:3*self.nrigid])
# assert that x2 actually changed
max_change = np.max(np.abs(x2_cpp - x2))
self.assertGreater(max_change, 1e-3)
assert_arrays_almost_equal(self, x2_python, x2_cpp)
def test_cpp_align(self):
x1 = np.array([random_aa() for _ in range(2 * self.nrigid)]).ravel()
x2 = np.array([random_aa() for _ in range(2 * self.nrigid)]).ravel()
x1_cpp = x1.copy()
x2_cpp = x2.copy()
x1_python = x1.copy()
x2_python = x2.copy()
ret = self.measure._align_pythonic(x1_python, x2_python)
self.assertIsNone(ret)
ret = self.measure.align(x1_cpp, x2_cpp)
self.assertIsNone(ret)
assert_arrays_almost_equal(self, x1_python, x1)
assert_arrays_almost_equal(self, x1_cpp, x1)
# assert that the center of mass coordinates didn't change
assert_arrays_almost_equal(self, x2_python[:3 * self.nrigid],
x2[:3 * self.nrigid])
assert_arrays_almost_equal(self, x2_cpp[:3 * self.nrigid],
x2[:3 * self.nrigid])
# assert that x2 actually changed
max_change = np.max(np.abs(x2_cpp - x2))
self.assertGreater(max_change, 1e-3)
assert_arrays_almost_equal(self, x2_python, x2_cpp)
def test_compare(self):
dkear, rot1 = findrotation_kearsley(self.x1, self.x2, align_com=True)
dkab, rot2 = kabsch_wrap(self.x1, self.x2, align_com=True)
qkear = mx2q(rot1)
qkab = mx2q(rot2)
self.assertAlmostEqual(dkear, dkab, places=4)
assert_arrays_almost_equal(self, qkear, qkab)
def test_compare(self):
dkear, rot1 = findrotation_kearsley(self.x1, self.x2, align_com=True)
dkab, rot2 = kabsch_wrap(self.x1, self.x2, align_com=True)
qkear = mx2q(rot1)
qkab = mx2q(rot2)
self.assertAlmostEqual(dkear, dkab, places=4)
assert_arrays_almost_equal(self, qkear, qkab)
def test_align_exact(self):
x1 = np.array([random_aa() for _ in range(2 * self.nrigid)]).ravel()
x2 = x1.copy()
tet = create_tetrahedron()
mx = tet.symmetries[2].copy()
p = x2[-3:].copy()
x2[-3:] = rotations.rotate_aa(rotations.mx2aa(mx), p)
self.measure._align_pythonic(x1, x2)
assert_arrays_almost_equal(self, x1, x2)
def test_align_exact(self):
x1 = np.array([random_aa() for _ in range(2*self.nrigid)]).ravel()
x2 = x1.copy()
tet = create_tetrahedron()
mx = tet.symmetries[2].copy()
p = x2[-3:].copy()
x2[-3:] = rotations.rotate_aa(rotations.mx2aa(mx), p)
self.measure._align_pythonic(x1, x2)
assert_arrays_almost_equal(self, x1, x2)
def test_to_atomistic(self):
tai, atom_indices = self.make_atom_indices_python_topology()
tnorm = self.make_normal_python_topology()
coords = self.get_random_rbcoords()
a1 = tai.to_atomistic(coords.copy())
a2 = tnorm.to_atomistic(coords)
a1perm = a1[atom_indices]
assert_arrays_almost_equal(self, a1perm, a2)
def test_to_atomistic(self):
tai, atom_indices = self.make_atom_indices_python_topology()
tnorm = self.make_normal_python_topology()
coords = self.get_random_rbcoords()
a1 = tai.to_atomistic(coords.copy())
a2 = tnorm.to_atomistic(coords)
a1perm = a1[atom_indices]
assert_arrays_almost_equal(self, a1perm, a2)
def test1(self):
# plot_pot()
opt = FindTransitionState(self.x0, self.pot, orthogZeroEigs=None,
# iprint=1,
# verbosity=10, event=print_event,
# tol=1e-3,
# lowestEigenvectorQuenchParams=dict(iprint=1, events=[print_event])
)
ret = opt.run()
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
self.assertAlmostEqual(ret.energy, self.ets, delta=1e-3)
self.assertLess(ret.rms, 1e-3)
self.assertEqual(ret.nfev + 1, self.pot.nfev)
def test1(self):
rot = q2mx(random_q())
x2 = self.x1.copy()
self.transform.rotate(x2, rot)
x1 = self.x1
dist, mx = self.findrot(x1, x2)
self.assertLess(dist, 1e-4)
self.transform.translate(x2, -self.measure.get_com(x2))
self.transform.rotate(x2, mx)
self.transform.translate(x2, self.measure.get_com(x1))
assert_arrays_almost_equal(self, x1, x2)
def test_from_near_minimum(self):
print "\n\nstarting from a minimum"
x0 = np.array([.6, .1])
opt = FindTransitionState(x0, self.pot, orthogZeroEigs=None,
iprint=1,
verbosity=10, # event=print_event,
# tol=1e-3,
# lowestEigenvectorQuenchParams=dict(iprint=1, events=[print_event])
)
ret = opt.run()
print ret
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
def test1(self):
rot = q2mx(random_q())
x2 = self.x1.copy()
self.transform.rotate(x2, rot)
x1 = self.x1
dist, mx = self.findrot(x1, x2)
self.assertLess(dist, 1e-4)
self.transform.translate(x2, -self.measure.get_com(x2))
self.transform.rotate(x2, mx)
self.transform.translate(x2, self.measure.get_com(x1))
assert_arrays_almost_equal(self, x1, x2)
def test1(self):
# plot_pot()
opt = FindTransitionState(self.x0, self.pot, orthogZeroEigs=None,
# iprint=1,
# verbosity=10, event=print_event,
# tol=1e-3,
# lowestEigenvectorQuenchParams=dict(iprint=1, events=[print_event])
)
ret = opt.run()
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
self.assertAlmostEqual(ret.energy, self.ets, delta=1e-3)
self.assertLess(ret.rms, 1e-3)
self.assertEqual(ret.nfev + 1, self.pot.nfev)
def test_from_near_minimum(self):
print("\n\nstarting from a minimum")
x0 = np.array([.6, .1])
opt = FindTransitionState(x0, self.pot, orthogZeroEigs=None,
iprint=1,
verbosity=10, # event=print_event,
# tol=1e-3,
# lowestEigenvectorQuenchParams=dict(iprint=1, events=[print_event])
)
ret = opt.run()
print(ret)
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
def test2(self):
rot = q2mx(random_q())
dx = .01
x2 = self.x1.copy()
x2[0] += .01
self.transform.rotate(x2, rot)
x1old = self.x1.copy()
x2old = x2.copy()
dist, mx = self.findrot(self.x1, x2)
# check it didn't change the arrays
assert_arrays_almost_equal(self, x1old, self.x1)
assert_arrays_almost_equal(self, x2old, x2)
self.assertLess(dist, dx)
def test2(self):
rot = q2mx(random_q())
dx = .01
x2 = self.x1.copy()
x2[0] += .01
self.transform.rotate(x2, rot)
x1old = self.x1.copy()
x2old = x2.copy()
dist, mx = self.findrot(self.x1, x2)
# check it didn't change the arrays
assert_arrays_almost_equal(self, x1old, self.x1)
assert_arrays_almost_equal(self, x2old, x2)
self.assertLess(dist, dx)
def test_cpp_rotate(self):
x0 = np.array([random_aa() for _ in range(2 * self.nrigid)]).ravel()
aa = random_aa()
mx = aa2mx(aa)
x0_rotated = x0.copy()
self.transform.rotate(x0_rotated, mx)
x0_rotated_python = x0.copy()
self.transform._rotate_python(x0_rotated_python, mx)
assert_arrays_almost_equal(self, x0_rotated, x0_rotated_python)
mx_reverse = aa2mx(-aa)
self.transform.rotate(x0_rotated, mx_reverse)
assert_arrays_almost_equal(self, x0, x0_rotated)
def test_cpp_rotate(self):
x0 = np.array([random_aa() for _ in range(2*self.nrigid)]).ravel()
aa = random_aa()
mx = aa2mx(aa)
x0_rotated = x0.copy()
self.transform.rotate(x0_rotated, mx)
x0_rotated_python = x0.copy()
self.transform._rotate_python(x0_rotated_python, mx)
assert_arrays_almost_equal(self, x0_rotated, x0_rotated_python)
mx_reverse = aa2mx(-aa)
self.transform.rotate(x0_rotated, mx_reverse)
assert_arrays_almost_equal(self, x0, x0_rotated)
def test_cpp_potential(self):
python_topology, atom_indices = self.make_atom_indices_python_topology()
cpp_topology, atom_indices = self.make_atom_indices_cpp_topology(atom_indices=atom_indices.copy())
lj = LJ()
pot_python = pythonRBPotentialWrapper(python_topology, lj)
pot_cpp = pythonRBPotentialWrapper(cpp_topology, lj)
coords = self.get_random_rbcoords()
e_python = pot_python.getEnergy(coords.copy())
e_cpp = pot_cpp.getEnergy(coords.copy())
self.assertAlmostEqual(e_python, e_cpp)
e1, g_python = pot_python.getEnergyGradient(coords.copy())
e2, g_cpp = pot_cpp.getEnergyGradient(coords.copy())
assert_arrays_almost_equal(self, g_python, g_cpp)
def test_potential(self):
topology, atom_indices = self.make_atom_indices_python_topology()
normal_topology = self.make_normal_python_topology()
lj = LJ()
pot = pythonRBPotentialWrapper(topology, lj)
pot_normal = pythonRBPotentialWrapper(normal_topology, lj)
coords = self.get_random_rbcoords()
energy_atom_indices = pot.getEnergy(coords.copy())
energy_normal = pot_normal.getEnergy(coords.copy())
self.assertAlmostEqual(energy_atom_indices, energy_normal)
e1, gei = pot.getEnergyGradient(coords.copy())
e2, gnorm = pot_normal.getEnergyGradient(coords.copy())
assert_arrays_almost_equal(self, gei, gnorm)
def test_potential(self):
topology, atom_indices = self.make_atom_indices_python_topology()
normal_topology = self.make_normal_python_topology()
lj = LJ()
pot = pythonRBPotentialWrapper(topology, lj)
pot_normal = pythonRBPotentialWrapper(normal_topology, lj)
coords = self.get_random_rbcoords()
energy_atom_indices = pot.getEnergy(coords.copy())
energy_normal = pot_normal.getEnergy(coords.copy())
self.assertAlmostEqual(energy_atom_indices, energy_normal)
e1, gei = pot.getEnergyGradient(coords.copy())
e2, gnorm = pot_normal.getEnergyGradient(coords.copy())
assert_arrays_almost_equal(self, gei, gnorm)
def test_cpp_potential(self):
python_topology, atom_indices = self.make_atom_indices_python_topology(
)
cpp_topology, atom_indices = self.make_atom_indices_cpp_topology(
atom_indices=atom_indices.copy())
lj = LJ()
pot_python = pythonRBPotentialWrapper(python_topology, lj)
pot_cpp = pythonRBPotentialWrapper(cpp_topology, lj)
coords = self.get_random_rbcoords()
e_python = pot_python.getEnergy(coords.copy())
e_cpp = pot_cpp.getEnergy(coords.copy())
self.assertAlmostEqual(e_python, e_cpp)
e1, g_python = pot_python.getEnergyGradient(coords.copy())
e2, g_cpp = pot_cpp.getEnergyGradient(coords.copy())
assert_arrays_almost_equal(self, g_python, g_cpp)
def test1(self):
current_dir = os.path.dirname(__file__)
db = Database()
converter = OptimDBConverter(
db,
mindata=os.path.join(current_dir, "min.data"),
tsdata=os.path.join(current_dir, "ts.data"),
pointsmin=os.path.join(current_dir, "points.min"),
pointsts=os.path.join(current_dir, "points.ts"),
endianness="<")
converter.convert()
mdata = tempfile.NamedTemporaryFile(delete=True)
tsdata = tempfile.NamedTemporaryFile(delete=True)
pm = tempfile.NamedTemporaryFile(delete=True)
pts = tempfile.NamedTemporaryFile(delete=True)
print mdata.name, tsdata.name
writer = WritePathsampleDB(db,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
writer.write_db()
d1 = np.genfromtxt(os.path.join(current_dir, "min.data"))[:, :3]
d2 = np.genfromtxt(mdata.name)[:, :3]
_base_test.assert_arrays_almost_equal(self, d1, d2)
d1 = np.genfromtxt(os.path.join(current_dir,
"ts.data")).reshape(-1, 8)[:, :5]
d2 = np.genfromtxt(tsdata.name).reshape(-1, 8)[:, :5]
print d1, d2
_base_test.assert_arrays_almost_equal(self, d1, d2)
self.assertEqual(sha1_of_file(os.path.join(current_dir, "points.min")),
sha1_of_file(pm.name))
self.assertEqual(sha1_of_file(os.path.join(current_dir, "points.ts")),
sha1_of_file(pts.name))
def test2(self):
from pele.utils.tests.test_disconnectivity_graph import create_random_database
db = create_random_database(nmin=20, nts=15)
delete = False
mdata = tempfile.NamedTemporaryFile(delete=delete, suffix=".min.data")
tsdata = tempfile.NamedTemporaryFile(delete=delete, suffix=".ts.data")
pm = tempfile.NamedTemporaryFile(delete=delete)
pts = tempfile.NamedTemporaryFile(delete=delete)
print mdata.name, tsdata.name
writer = WritePathsampleDB(db,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
writer.write_db()
newdb = Database()
reader = OptimDBConverter(newdb,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
reader.convert()
for m1, m2 in izip(db.minima(), newdb.minima()):
self.assertAlmostEqual(m1.energy, m2.energy)
_base_test.assert_arrays_almost_equal(self, m1.coords, m2.coords)
for ts1, ts2 in izip(db.transition_states(),
newdb.transition_states()):
self.assertAlmostEqual(ts1.energy, ts2.energy)
_base_test.assert_arrays_almost_equal(self, ts1.coords, ts2.coords)
self.assertAlmostEqual(ts1.minimum1.energy, ts2.minimum1.energy)
self.assertAlmostEqual(ts1.minimum2.energy, ts2.minimum2.energy)
def test1(self):
current_dir = os.path.dirname(__file__)
db = Database()
converter = OptimDBConverter(db,
mindata=os.path.join(current_dir, "min.data"),
tsdata=os.path.join(current_dir, "ts.data"),
pointsmin=os.path.join(current_dir, "points.min"),
pointsts=os.path.join(current_dir, "points.ts"),
endianness="<")
converter.convert()
mdata = tempfile.NamedTemporaryFile(delete=True)
tsdata = tempfile.NamedTemporaryFile(delete=True)
pm = tempfile.NamedTemporaryFile(delete=True)
pts = tempfile.NamedTemporaryFile(delete=True)
print(mdata.name, tsdata.name)
writer = WritePathsampleDB(db,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
writer.write_db()
d1 = np.genfromtxt(os.path.join(current_dir, "min.data"))[:,:3]
d2 = np.genfromtxt(mdata.name)[:,:3]
_base_test.assert_arrays_almost_equal(self, d1, d2)
d1 = np.genfromtxt(os.path.join(current_dir, "ts.data")).reshape(-1,8)[:,:5]
d2 = np.genfromtxt(tsdata.name).reshape(-1,8)[:,:5]
print(d1, d2)
_base_test.assert_arrays_almost_equal(self, d1, d2)
self.assertEqual(sha1_of_file(os.path.join(current_dir, "points.min")),
sha1_of_file(pm.name))
self.assertEqual(sha1_of_file(os.path.join(current_dir, "points.ts")),
sha1_of_file(pts.name))
def test2(self):
from pele.utils.tests.test_disconnectivity_graph import create_random_database
db = create_random_database(nmin=20, nts=15)
delete=False
mdata = tempfile.NamedTemporaryFile(delete=delete, suffix=".min.data")
tsdata = tempfile.NamedTemporaryFile(delete=delete, suffix=".ts.data")
pm = tempfile.NamedTemporaryFile(delete=delete)
pts = tempfile.NamedTemporaryFile(delete=delete)
print(mdata.name, tsdata.name)
writer = WritePathsampleDB(db,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
writer.write_db()
newdb = Database()
reader = OptimDBConverter(newdb,
mindata=mdata.name,
tsdata=tsdata.name,
pointsmin=pm.name,
pointsts=pts.name,
endianness="<")
reader.convert()
for m1, m2 in zip(db.minima(), newdb.minima()):
self.assertAlmostEqual(m1.energy, m2.energy)
_base_test.assert_arrays_almost_equal(self, m1.coords, m2.coords)
for ts1, ts2 in zip(db.transition_states(), newdb.transition_states()):
self.assertAlmostEqual(ts1.energy, ts2.energy)
_base_test.assert_arrays_almost_equal(self, ts1.coords, ts2.coords)
self.assertAlmostEqual(ts1.minimum1.energy, ts2.minimum1.energy)
self.assertAlmostEqual(ts1.minimum2.energy, ts2.minimum2.energy)
def test_transform_gradient(self):
tai, atom_indices = self.make_atom_indices_python_topology()
tnorm = self.make_normal_python_topology()
coords = self.get_random_rbcoords()
aai = tai.to_atomistic(coords.copy())
anorm = tnorm.to_atomistic(coords.copy())
lj = LJ()
# atomistic_coords = np.random.uniform(-1, 1, 3*len(atom_indices))
# e, atomistic_grad = lj.getEnergyGradient(atomistic_coords)
e1, gai = lj.getEnergyGradient(aai.ravel())
e2, gnorm = lj.getEnergyGradient(anorm.ravel())
self.assertAlmostEqual(e1, e2)
assert_arrays_almost_equal(self,
gai.reshape(-1, 3)[atom_indices],
gnorm.reshape(-1, 3))
rb_gai = tai.transform_gradient(coords.copy(), gai)
rb_gnorm = tnorm.transform_gradient(coords.copy(), gnorm)
assert_arrays_almost_equal(self, rb_gai, rb_gnorm)
def test_wrapper(self):
ret = findTransitionState(self.x0, self.pot, orthogZeroEigs=None)
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
def test_wrapper(self):
ret = findTransitionState(self.x0, self.pot, orthogZeroEigs=None)
self.assertTrue(ret.success)
assert_arrays_almost_equal(self, ret.coords, self.xts, places=3)
