def test_as_pyscf_method(self):
gs = scf.RHF(mol).nuc_grad_method().as_scanner()
f = lambda mol: gs(mol)
m = berny_solver.as_pyscf_method(mol, f)
mol1 = berny_solver.optimize(m)
self.assertAlmostEqual(lib.fp(mol1.atom_coords()), 2.20003359484436, 4)
self.assertEqual(mol1.symmetry, 'C2v')
def test_as_pyscf_method(self):
mol = gto.M(atom='''
O 0. 0. 0.
H 0. -0.757 0.587
H 0. 0.757 0.587
''', verbose=0)
gs = scf.RHF(mol).nuc_grad_method().as_scanner()
f = lambda mol: gs(mol)
m = berny_solver.as_pyscf_method(mol, f)
mol1 = berny_solver.optimize(m)
self.assertAlmostEqual(lib.finger(mol1.atom_coords()),
2.2000335948443315, 5)
def test_as_pyscf_method(self):
mol = gto.M(atom='''
O 0. 0. 0.
H 0. -0.757 0.587
H 0. 0.757 0.587
''',
verbose=0)
gs = scf.RHF(mol).nuc_grad_method().as_scanner()
f = lambda mol: gs(mol)
m = berny_solver.as_pyscf_method(mol, f)
mol1 = berny_solver.optimize(m)
self.assertAlmostEqual(lib.finger(mol1.atom_coords()),
2.2000335948443315, 5)
def test_as_pyscf_method(self):
mol = gto.M(atom='''
O 0. 0. 0.
H 0. -0.757 0.587
H 0. 0.757 0.587
''', symmetry=True, verbose=0)
gs = scf.RHF(mol).nuc_grad_method().as_scanner()
f = lambda mol: gs(mol)
m = berny_solver.as_pyscf_method(mol, f)
mol1 = berny_solver.optimize(m)
self.assertAlmostEqual(lib.finger(mol1.atom_coords()),
3.039311839766823, 4)
self.assertEqual(mol1.symmetry, 'C2v')
mf = scf.RHF(mol)
grad_scan = scf.RHF(mol).nuc_grad_method().as_scanner()
def f(mol):
e, g = grad_scan(mol)
r = mol.atom_coords()
penalty = np.linalg.norm(r[0] - r[1])**2 * 0.1
e += penalty
g[0] += (r[0] - r[1]) * 2 * 0.1
g[1] -= (r[0] - r[1]) * 2 * 0.1
print('Customized |g|', np.linalg.norm(g))
return e, g
#
# Function as_pyscf_method is a wrapper that convert the "energy-gradients"
# function to berny_solver. The "energy-gradients" function takes the Mole
# object as geometry input, and returns the energy and gradients of that
# geometry.
#
fake_method = berny_solver.as_pyscf_method(mol, f)
new_mol = berny_solver.optimize(fake_method)
print('Old geometry (Bohr)')
print(mol.atom_coords())
print('New geometry (Bohr)')
print(new_mol.atom_coords())
cc_scan = cc.CCSD(mf).as_scanner()
def f(mol):
# Compute CCSD(T) energy
mf = scf.RHF(mol).run()
mycc = cc.CCSD(mf).run()
et_correction = mycc.ccsd_t()
e_tot = mycc.e_tot + et_correction
# Compute CCSD(T) gradients
eris = mycc.ao2mo()
t1, t2 = mycc.t1, mycc.t2
conv, l1, l2 = ccsd_t_lambda.kernel(mycc, eris, t1, t2,
verbose=mycc.verbose)
g = ccsd_t_grad.kernel(mycc, t1, t2, l1, l2, eris=eris,
verbose=mycc.verbose)
print('CCSD(T) nuclear gradients:')
print(g)
return e_tot, g
fake_method = berny_solver.as_pyscf_method(mol, f)
new_mol = berny_solver.optimize(fake_method)
print('Old geometry (Bohr)')
print(mol.atom_coords())
print('New geometry (Bohr)')
print(new_mol.atom_coords())
lib.logger.info(mf_grad_scan, "* Disp Energy [au]: %12.8f" % edisp[0])
lib.logger.info(mf_grad_scan, "* Disp Gradients [au]:")
atmlst = range(mol.natm)
for k, ia in enumerate(atmlst):
symb = mol.atom_pure_symbol(ia)
lib.logger.info(mf_grad_scan,"* %d %s %12.8f %12.8f %12.8f" \
% (ia, symb, grad[k,0], grad[k,1], grad[k,2]))
e_tot += edisp[0]
g_rhf += grad
lib.logger.info(mf_grad_scan, "* Total Energy [au]: %12.8f" % e_tot)
lib.logger.info(mf_grad_scan, "* Total Gradients [au]:")
atmlst = range(mol.natm)
for k, ia in enumerate(atmlst):
symb = mol.atom_pure_symbol(ia)
lib.logger.info(mf_grad_scan,"* %d %s %12.8f %12.8f %12.8f" \
% (ia, symb, g_rhf[k,0], g_rhf[k,1], g_rhf[k,2]))
return e_tot, g_rhf
mf = berny_solver.as_pyscf_method(mol, mf_grad_with_dftd3)
mol = berny_solver.kernel(mf, maxsteps=50, assert_convergence=True)
xyzfile = name + '_opt.xyz'
fspt = open(xyzfile, 'w')
coords = mol.atom_coords() * lib.param.BOHR
fspt.write('%d \n' % mol.natm)
fspt.write('%d %d\n' % (mol.charge, (mol.spin + 1)))
for ia in range(mol.natm):
symb = mol.atom_pure_symbol(ia)
fspt.write('%s %12.6f %12.6f %12.6f\n' % (symb, \
coords[ia][0],coords[ia][1], coords[ia][2]))