def build_system(request):
mol = psi4.geometry("""
O
H 1 1.00
H 1 1.00 2 103.1
""")
memory = 50000
puream = request.param == "spherical"
primary = psi4.core.BasisSet.build(mol, "ORBITAL", "cc-pVDZ", puream=puream)
aux = psi4.core.BasisSet.build(mol, "ORBITAL", "cc-pVDZ-jkfit", puream=puream)
nbf = primary.nbf()
naux = aux.nbf()
# construct spaces
names = ['C1', 'C2', 'C3', 'C4', 'C5']
sizes = [16, 16, 20, 20, 30]
spaces = {names[ind]: psi4.core.Matrix.from_array(np.random.rand(nbf, size)) for ind, size in enumerate(sizes)}
space_pairs = [[0, 0], [0, 1], [1, 1], [2, 2], [3, 2], [3, 3], [4, 4]]
# space vectors
C_vectors = [[spaces[names[left]], spaces[names[right]]] for left, right in space_pairs]
# DiskJK
psi4.set_options({"SCF_TYPE": "DISK_DF"})
DiskJK = psi4.core.JK.build_JK(primary, aux)
DiskJK.initialize()
DiskJK.print_header()
# symm_JK
psi4.set_options({"SCF_TYPE": "MEM_DF"})
MemJK = psi4.core.JK.build_JK(primary, aux)
MemJK.initialize()
MemJK.print_header()
# add C matrices
for Cleft, Cright in C_vectors:
DiskJK.C_left_add(Cleft)
MemJK.C_left_add(Cleft)
DiskJK.C_right_add(Cright)
MemJK.C_right_add(Cright)
# compute
DiskJK.compute()
MemJK.compute()
# get integrals
DiskJK_ints = [DiskJK.J(), DiskJK.K()]
MemJK_ints = [MemJK.J(), MemJK.K()]
return (DiskJK_ints, MemJK_ints)
def dft_bench_systems():
ang = np.array([
[ -1.551007, -0.114520, 0.000000],
[ -1.934259, 0.762503, 0.000000],
[ -0.599677, 0.040712, 0.000000]])
oldang = ang * 0.52917721067 / 0.52917720859
oldmass = [15.99491461956, 1.00782503207, 1.00782503207]
h2o = psi4.core.Molecule.from_arrays(geom=oldang, elez=[8, 1, 1], units='Angstrom', mass=oldmass)
h2o_plus = psi4.core.Molecule.from_arrays(geom=oldang, elez=[8, 1, 1], units='Angstrom', mass=oldmass,
molecular_charge=1, molecular_multiplicity=2)
h2o_dimer = psi4.geometry("""
0 1
O -1.551007 -0.114520 0.000000
H -1.934259 0.762503 0.000000
H -0.599677 0.040712 0.000000
--
0 1
O 1.350625 0.111469 0.000000
H 1.680398 -0.373741 -0.758561
H 1.680398 -0.373741 0.758561
no_reorient
""")
psi4.set_options({
'dft_radial_points': 200,
'dft_spherical_points': 590,
'guess': 'sad',
'e_convergence': 9,
'd_convergence': 9,
})
return {'h2o': h2o, 'h2o_plus': h2o_plus, 'h2o_dimer': h2o_dimer}
def restricted_orbitals(basis, labels, coords, charge=0, spin=0, niter=100,
e_thresh=1e-12, d_thresh=1e-9, guess='gwh'):
"""restricted Hartree-Fock orbitals
:param basis: basis set name
:type basis: str
:param labels: atomic symbols labeling the nuclei
:type labels: tuple
:param coords: nuclear coordinates in Bohr
:type coords: numpy.ndarray
:param charge: total molecular charge
:type charge: int
:param spin: number of unpaired electrons
:type spin: int
:param niter: maximum number of iterations
:type niter: int
:param e_thresh: energy convergence threshold
:type e_thresh: float
:param d_thresh: density convergence threshold
:type d_thresh: float
:param guess: hartree-fock starting guess
:type guess: str
:return: orbital coefficients and energies, along with the occupation count
:rtype: (numpy.ndarray, numpy.ndarray, int)
"""
psi4.set_options({'e_convergence': e_thresh, 'd_convergence': d_thresh,
'maxiter': niter, 'guess': guess, 'reference': 'RHF'})
mol = psi4_molecule(labels=labels, coords=coords, charge=charge, spin=spin)
wfn = psi4.core.Wavefunction.build(mol, basis)
sf, _ = psi4.driver.dft_funcs.build_superfunctional("HF", False)
hf = psi4.core.RHF(wfn, sf)
hf.compute_energy()
return numpy.array(hf.Ca()), numpy.array(hf.epsilon_a()), int(hf.nalpha())
def test_gpudfcc2():
"""gpu_dfcc/tests/gpu_dfcc2"""
#! aug-cc-pvdz (H2O) Test DF-CCSD(T) vs GPU-DF-CCSD(T)
import psi4
H20 = psi4.geometry("""
O 0.000000000000 0.000000000000 -0.068516219310
H 0.000000000000 -0.790689573744 0.543701060724
H 0.000000000000 0.790689573744 0.543701060724
""")
psi4.set_memory(32000000000)
psi4.set_options({
'cc_type': 'df',
'basis': 'aug-cc-pvdz',
'freeze_core': 'true',
'e_convergence': 1e-8,
'd_convergence': 1e-8,
'r_convergence': 1e-8,
'scf_type': 'df',
'maxiter': 30})
psi4.set_num_threads(2)
en_dfcc = psi4.energy('ccsd(t)')
en_gpu_dfcc = psi4.energy('gpu-df-ccsd(t)')
assert psi4.compare_values(en_gpu_dfcc, en_dfcc, 8, "CCSD total energy")
def psi4_esp(method, basis, molecule):
""" Computes QM electrostatic potential
Parameters
----------
method : str
QM method
basis : str
basis set
molecule : psi4.Molecule instance
Returns
-------
np.array
QM electrostatic potential.
Note
-----
Psi4 read grid information from grid.dat file
"""
import psi4
mol = psi4.geometry(molecule.create_psi4_string_from_molecule())
psi4.set_options({'basis': basis})
e, wfn = psi4.prop(method, properties=['GRID_ESP'], return_wfn=True)
psi4.core.clean()
return np.loadtxt('grid_esp.dat')
def test_uhf():
"""
test for uhf using (H2O)^+
"""
print("!!! %s" % os.path.dirname(__file__))
ao_ints, test_scf_param, e_ZZ_repulsion = scf.init(\
os.path.dirname(__file__) + "/test_uhf.yml")
eps, C, D, F = scf.scf(ao_ints, test_scf_param, e_ZZ_repulsion)
energy = scf.get_SCF_energy(ao_ints['H'], F, D, True) + e_ZZ_repulsion
print("energy: %f" % energy)
# psi4 setup
import psi4
mol = psi4.geometry("""
1 2
O
H 1 1.1
H 1 1.1 2 104
""")
mol.update_geometry()
bas = psi4.core.BasisSet.build(mol, target=test_scf_param['basis'])
mints = psi4.core.MintsHelper(bas)
# DENSITY FITTED
psi4.set_options({"scf_type": "pk", "reference": "uhf"})
psi4_energy = psi4.energy("SCF/cc-pVDZ", molecule = mol)
print("psi4 energy: %f" % psi4_energy)
assert(np.allclose(energy, psi4_energy) == True)
def test_mp2():
"""
test for energies
"""
ao_ints, test_scf_param, e_ZZ_repulsion = scf.init(\
os.path.dirname(__file__) + "/test_mp2.yml")
eps, C, D, F = scf.scf(ao_ints, test_scf_param, e_ZZ_repulsion)
energy = scf.get_SCF_energy(ao_ints['H'], F, D, False) + e_ZZ_repulsion
# psi4 setup
import psi4
mol = psi4.geometry("""
O
H 1 1.1
H 1 1.1 2 104
""")
mol.update_geometry()
bas = psi4.core.BasisSet.build(mol, target="cc-pVDZ")
mints = psi4.core.MintsHelper(bas)
# DF-MP2
psi4.set_options({"scf_type": "df"})
psi4.set_options({"MP2_type": "CONV"})
psi4_energy = psi4.energy("MP2/cc-pVDZ", molecule = mol)
psi4_energy_MP2 = psi4.get_variable('SCS-MP2 TOTAL ENERGY')
test_scf_param.update({"method": "MP2"})
test_scf_param.update({"is_fitted": "True"})
eps, C, D, F = scf.scf(ao_ints, test_scf_param, e_ZZ_repulsion)
H = ao_ints['T'] + ao_ints['V']
energy = np.sum((F+H)*D) + e_ZZ_repulsion
energy_corr = mp2.get_mp2_energy(\
eps, C, ao_ints['g4'], test_scf_param['nel_alpha'])
assert(np.allclose(energy + energy_corr, psi4_energy_MP2) == True)
def test_cfour():
"""cfour/sp-rhf-ccsd_t_"""
#! single-point CCSD(T)/qz2p on water
print(' <<< Translation of ZMAT to Psi4 format to Cfour >>>')
psi4.geometry("""
O
H 1 R
H 1 R 2 A
R=0.958
A=104.5
""")
psi4.set_options({
'cfour_CALC_level': 'CCSD(T)',
'cfour_BASIS': 'qz2p',
'cfour_SCF_CONV': 12,
'cfour_CC_CONV': 12,
})
psi4.energy('cfour')
assert psi4.compare_values(-76.062748460117, psi4.variable('scf total energy'), 6, 'SCF')
assert psi4.compare_values(-76.332940127333, psi4.variable('mp2 total energy'), 6, 'MP2')
assert psi4.compare_values(-76.338453951890, psi4.variable('ccsd total energy'), 6, 'CCSD')
assert psi4.compare_values(-0.275705491773, psi4.variable('ccsd correlation energy'), 6, 'CCSD corl')
assert psi4.compare_values(-76.345717549886, psi4.variable('ccsd(t) total energy'), 6, 'CCSD(T)')
assert psi4.compare_values(-0.282969089769, psi4.variable('ccsd(t) correlation energy'), 6, 'CCSD(T) corl')
def test_rhf():
"""
test for rhf
"""
ao_ints, test_scf_param, e_ZZ_repulsion = scf.init(\
os.path.dirname(__file__) + "/test_rhf.yml")
eps, C, D, F = scf.scf(ao_ints, test_scf_param, e_ZZ_repulsion)
energy = scf.get_SCF_energy(ao_ints['H'], F, D, False) + e_ZZ_repulsion
# psi4 setup
import psi4
mol = psi4.geometry("""
O
H 1 1.1
H 1 1.1 2 104
""")
mol.update_geometry()
bas = psi4.core.BasisSet.build(mol, target="cc-pVDZ")
mints = psi4.core.MintsHelper(bas)
# DENSITY FITTED
psi4.set_options({"scf_type": "df"})
psi4_energy = psi4.energy("SCF/cc-pVDZ", molecule = mol)
assert(np.allclose(energy, psi4_energy) == True)
def test_gpu_dfcc():
"""gpu_dfcc/tests/gpu_dfcc1"""
#! cc-pvdz (H2O)2 Test DF-CCSD vs GPU-DF-CCSD
import gpu_dfcc
H20 = psi4.geometry("""
O 0.000000000000 0.000000000000 -0.068516219310
H 0.000000000000 -0.790689573744 0.543701060724
H 0.000000000000 0.790689573744 0.543701060724
""")
psi4.set_memory(32000000000)
psi4.set_options({
'cc_timings': False,
'num_gpus': 1,
'cc_type': 'df',
'df_basis_cc': 'aug-cc-pvdz-ri',
'df_basis_scf': 'aug-cc-pvdz-jkfit',
'basis': 'aug-cc-pvdz',
'freeze_core': 'true',
'e_convergence': 1e-8,
'd_convergence': 1e-8,
'r_convergence': 1e-8,
'scf_type': 'df',
'maxiter': 30})
psi4.set_num_threads(2)
en_dfcc = psi4.energy('ccsd', molecule=H20)
en_gpu_dfcc = psi4.energy('gpu-df-ccsd', molecule=H20)
assert psi4.compare_values(en_gpu_dfcc, en_dfcc, 8, "CCSD total energy")
def test_dftd3_dft_grad_lr3():
"""modified VV10-less B97 functional gradient wB97X-V -> wB97X-D3BJ"""
# stored data from finite differences
FD_wb97x_d3 = psi4.core.Matrix.from_list([
[ 0.03637802044642, 0.06718963272193, 0.00000000000000],
[ 0.04955519892514, -0.06340333481039, 0.00000000000000],
[ -0.07009043821383, -0.00834477190196, 0.00000000000000],
[ 0.02732425404378, -0.05883094637658, 0.00000000000000],
[ -0.02158351760075, 0.03169471018350, 0.05342791683461],
[ -0.02158351760075, 0.03169471018350, -0.05342791683461]])
psi4.geometry("""
0 1
O -1.65542 -0.12330 0.00000
O 1.24621 0.10269 0.00000
H -0.70409 0.03193 0.00000
H -2.03867 0.75372 0.00000
H 1.57599 -0.38252 -0.75856
H 1.57599 -0.38252 0.75856
""")
psi4.set_options({
'scf_type': 'pk',
'basis': 'minix',
'dft_radial_points': 99,
'dft_spherical_points': 302,
'e_convergence': 8,
})
analytic = psi4.gradient('wB97X-D3BJ', dertype=1)
assert compare_matrices(analytic, FD_wb97x_d3, 5, "wB97X-D3BJ Analytic vs Store")
def test_psi4_cas():
"""casscf-sp"""
#! CASSCF/6-31G** energy point
geom = psi4.geometry("""
O
H 1 1.00
H 1 1.00 2 103.1
""")
psi4.set_options({
"basis" : '6-31G**',
"reference" : 'rhf',
"scf_type" : 'pk',
"mcscf_algorithm" : 'ah',
"qc_module" : 'detci',
"nat_orbs" : True})
cisd_energy, cisd_wfn = psi4.energy("CISD", return_wfn=True)
assert psi4.compare_values(-76.2198474477531, cisd_energy, 6, 'CISD Energy')
psi4.set_options({
"restricted_docc": [1, 0, 0, 0],
"active": [3, 0, 1, 2]})
casscf_energy = psi4.energy('casscf', ref_wfn=cisd_wfn)
assert psi4.compare_values(-76.073865006902, casscf_energy, 6, 'CASSCF Energy')
def test_restricted_RPA_triplet_c1():
"Build out the full CIS/TDA hamiltonian (A) col by col with the product engine"
h2o = psi4.geometry("""
O
H 1 0.96
H 1 0.96 2 104.5
symmetry c1
""")
psi4.set_options({"scf_type": "pk", 'save_jk': True})
e, wfn = psi4.energy("hf/cc-pvdz", molecule=h2o, return_wfn=True)
A_ref, B_ref = build_RHF_AB_C1_triplet(wfn)
ni, na, _, _ = A_ref.shape
nia = ni * na
A_ref = A_ref.reshape((nia, nia))
B_ref = B_ref.reshape((nia, nia))
P_ref = A_ref + B_ref
M_ref = A_ref - B_ref
# Build engine
eng = TDRSCFEngine(wfn, ptype='rpa', triplet=True)
# our "guess"" vectors
ID = [psi4.core.Matrix.from_array(v.reshape((ni, na))) for v in tuple(np.eye(nia).T)]
Px, Mx = eng.compute_products(ID)[:-1]
P_test = np.column_stack([x.to_array().flatten() for x in Px])
assert compare_arrays(P_ref, P_test, 8, "RHF (A+B)x C1 products")
M_test = np.column_stack([x.to_array().flatten() for x in Mx])
assert compare_arrays(M_ref, M_test, 8, "RHF (A-B)x C1 products")
def test_unrestricted_RPA_C1():
ch2 = psi4.geometry("""
0 3
c
h 1 1.0
h 1 1.0 2 125.0
symmetry c1
""")
psi4.set_options({"scf_type": "pk", 'reference': 'UHF', 'save_jk': True})
e, wfn = psi4.energy("hf/cc-pvdz", molecule=ch2, return_wfn=True)
A_ref, B_ref = build_UHF_AB_C1(wfn)
nI, nA, _, _ = A_ref['IAJB'].shape
nIA = nI * nA
ni, na, _, _ = A_ref['iajb'].shape
nia = ni * na
P_ref = {k: A_ref[k] + B_ref[k] for k in A_ref.keys()}
M_ref = {k: A_ref[k] - B_ref[k] for k in A_ref.keys()}
eng = TDUSCFEngine(wfn, ptype='rpa')
X_jb = [psi4.core.Matrix.from_array(v.reshape((ni, na))) for v in tuple(np.eye(nia).T)]
zero_jb = [psi4.core.Matrix(ni, na) for x in range(nIA)]
X_JB = [psi4.core.Matrix.from_array(v.reshape((nI, nA))) for v in tuple(np.eye(nIA).T)]
zero_JB = [psi4.core.Matrix(nI, nA) for x in range(nia)]
# Guess Identity:
# X_I0 X_0I = X_I0 X_0I
# [ I{nOV x nOV} | 0{nOV x nov}] = [ X{KC,JB} | 0{KC, jb}]
# [ 0{nov x nOV} | I{nov x nov}] [ 0{kc,JB} | X{kc, jb}]
# Products:
# [ A+/-B{IA, KC} A+/-B{IA, kc}] [ I{KC, JB} | 0{KC,jb}] = [A+/-B x X_I0] = [ (A+/-B)_IAJB, (A+/-B)_iaJB]
# [ A+/-B{ia, KC} A+/-B{ia, kc}] [ O{kc, JB} | X{kc,jb}] [A+/-B x X_0I] = [ (A+/-B)_IAjb, (A+/-B)_iajb]
X_I0 = [[x, zero] for x, zero in zip(X_JB, zero_jb)]
X_0I = [[zero, x] for zero, x in zip(zero_JB, X_jb)]
Px_I0, Mx_I0 = eng.compute_products(X_I0)[:-1]
Px_0I, Mx_0I = eng.compute_products(X_0I)[:-1]
P_IAJB_test = np.column_stack([x[0].to_array().flatten() for x in Px_I0])
assert compare_arrays(P_ref['IAJB'].reshape(nIA, nIA), P_IAJB_test, 8, "A_IAJB")
M_IAJB_test = np.column_stack([x[0].to_array().flatten() for x in Mx_I0])
assert compare_arrays(M_ref['IAJB'].reshape(nIA, nIA), M_IAJB_test, 8, "A_IAJB")
P_iaJB_test = np.column_stack([x[1].to_array().flatten() for x in Px_I0])
assert compare_arrays(P_ref['iaJB'].reshape(nia, nIA), P_iaJB_test, 8, "P_iaJB")
M_iaJB_test = np.column_stack([x[1].to_array().flatten() for x in Mx_I0])
assert compare_arrays(M_ref['iaJB'].reshape(nia, nIA), M_iaJB_test, 8, "M_iaJB")
P_IAjb_test = np.column_stack([x[0].to_array().flatten() for x in Px_0I])
assert compare_arrays(P_ref['IAjb'].reshape(nIA, nia), P_IAjb_test, 8, "P_IAjb")
M_IAjb_test = np.column_stack([x[0].to_array().flatten() for x in Mx_0I])
assert compare_arrays(M_ref['IAjb'].reshape(nIA, nia), M_IAjb_test, 8, "M_IAjb")
P_iajb_test = np.column_stack([x[1].to_array().flatten() for x in Px_0I])
assert compare_arrays(P_ref['iajb'].reshape(nia, nia), P_iajb_test, 8, "P_iajb")
M_iajb_test = np.column_stack([x[1].to_array().flatten() for x in Mx_0I])
assert compare_arrays(M_ref['iajb'].reshape(nia, nia), M_iajb_test, 8, "M_iajb")
def disabled_test_forte():
"""aci-10: Perform aci on benzyne"""
import forte
refscf = -229.20378006852584
refaci = -229.359450812283
refacipt2 = -229.360444943286
mbenzyne = psi4.geometry("""
0 1
C 0.0000000000 -2.5451795941 0.0000000000
C 0.0000000000 2.5451795941 0.0000000000
C -2.2828001669 -1.3508352528 0.0000000000
C 2.2828001669 -1.3508352528 0.0000000000
C 2.2828001669 1.3508352528 0.0000000000
C -2.2828001669 1.3508352528 0.0000000000
H -4.0782187459 -2.3208602146 0.0000000000
H 4.0782187459 -2.3208602146 0.0000000000
H 4.0782187459 2.3208602146 0.0000000000
H -4.0782187459 2.3208602146 0.0000000000
units bohr
""")
psi4.set_options({
'basis': 'DZ',
'df_basis_mp2': 'cc-pvdz-ri',
'reference': 'uhf',
'scf_type': 'pk',
'd_convergence': 10,
'e_convergence': 12,
'guess': 'gwh',
})
psi4.set_module_options("FORTE", {
'root_sym': 0,
'frozen_docc': [2,1,0,0,0,0,2,1],
'restricted_docc': [3,2,0,0,0,0,2,3],
'active': [1,0,1,2,1,2,1,0],
'multiplicity': 1,
'aci_nroot': 1,
'job_type': 'aci',
'sigma': 0.001,
'aci_select_type': 'aimed_energy',
'aci_spin_projection': 1,
'aci_enforce_spin_complete': True,
'aci_add_aimed_degenerate': False,
'aci_project_out_spin_contaminants': False,
'diag_algorithm': 'full',
'aci_quiet_mode': True,
})
scf = psi4.energy('scf')
assert psi4.compare_values(refscf, scf,10,"SCF Energy")
psi4.energy('forte')
assert psi4.compare_values(refaci, psi4.variable("ACI ENERGY"),10,"ACI energy")
assert psi4.compare_values(refacipt2, psi4.variable("ACI+PT2 ENERGY"),8,"ACI+PT2 energy")
def test_dft_bench_interaction(func, expected, basis, dft_bench_systems, request):
"""functionals interaction energies vs. Q-Chem & Orca"""
if func.lower() in psi4.driver.procedures['energy']:
mols = dft_bench_systems
psi4.set_options({'basis': basis})
psi4_ie = psi4.energy(func, molecule=mols['h2o_dimer'], bsse_type='nocp')
assert compare_values(expected, psi4_ie, 4, request.node.name)
else:
pytest.skip("{0:s} not in Psi4.".format(func))
def test_libefp():
"""libefp/qchem-qmefp-sp"""
#! EFP on mixed QM (water) and EFP (water + 2 * ammonia) system.
#! An EFP-only calc performed first to test vales against q-chem.
qmefp = psi4.geometry("""
# QM fragment
0 1
units bohr
O1 0.000000000000 0.000000000000 0.224348285559
H2 -1.423528800232 0.000000000000 -0.897393142237
H3 1.423528800232 0.000000000000 -0.897393142237
# EFP as EFP fragments
--
efp h2o -4.014110144291 2.316749370493 -1.801514729931 -2.902133 1.734999 -1.953647
--
efp NH3,1.972094713645,,3.599497221584 , 5.447701074734 -1.105309 2.033306 -1.488582
--
efp NH3 -7.876296399270 -1.854372164887 -2.414804197762 2.526442 1.658262 -2.742084
""")
# <<< EFP calc >>>
psi4.set_options({
'basis': '6-31g*',
'scf_type': 'pk',
'guess': 'core',
'df_scf_guess': False})
psi4.energy('efp')
assert psi4.compare_values( 9.1793879214, qmefp.nuclear_repulsion_energy(), 6, 'QM NRE')
assert psi4.compare_values(-0.0004901368, psi4.variable('efp elst energy'), 6, 'EFP-EFP Elst') # from q-chem
assert psi4.compare_values(-0.0003168768, psi4.variable('efp ind energy'), 6, 'EFP-EFP Indc')
assert psi4.compare_values(-0.0021985285, psi4.variable('efp disp energy'), 6, 'EFP-EFP Disp') # from q-chem
assert psi4.compare_values( 0.0056859871, psi4.variable('efp exch energy'), 6, 'EFP-EFP Exch') # from q-chem
assert psi4.compare_values( 0.0026804450, psi4.variable('efp total energy'), 6, 'EFP-EFP Totl')
assert psi4.compare_values( 0.0026804450, psi4.variable('current energy'), 6, 'Current')
psi4.core.print_variables()
psi4.core.clean()
psi4.core.clean_variables()
# <<< QM + EFP calc >>>
psi4.set_options({
'e_convergence': 12,
'd_convergence': 12})
psi4.energy('scf')
assert psi4.compare_values( 9.1793879214, qmefp.nuclear_repulsion_energy(), 6, 'QM NRE')
assert psi4.compare_values( 0.2622598847, psi4.variable('efp total energy') - psi4.variable('efp ind energy'), 6, 'EFP corr to SCF') # from q-chem
assert psi4.compare_values(-0.0117694790, psi4.variable('efp ind energy'), 6, 'QM-EFP Indc') # from q-chem
assert psi4.compare_values(-0.0021985285, psi4.variable('efp disp energy'), 6, 'EFP-EFP Disp') # from q-chem
assert psi4.compare_values( 0.0056859871, psi4.variable('efp exch energy'), 6, 'EFP-EFP Exch') # from q-chem
assert psi4.compare_values( 0.2504904057, psi4.variable('efp total energy'), 6, 'EFP-EFP Totl') # from q-chem
assert psi4.compare_values(-76.0139362744, psi4.variable('scf total energy'), 6, 'SCF') # from q-chem
psi4.core.print_variables()
def test_dft_bench_ionization(func, expected, basis, dft_bench_systems, request):
"""functionals ionization energies vs. Q-Chem"""
if func.lower() in psi4.driver.procedures['energy']:
mols = dft_bench_systems
psi4.set_options({'basis': basis, 'reference': 'uks'})
cation = psi4.energy(func, molecule=mols['h2o_plus'])
psi4.set_options({'reference': 'rks'})
neutral = psi4.energy(func, molecule=mols['h2o'])
assert compare_values(expected, cation - neutral, 4, request.node.name)
else:
pytest.skip("{0:s} not in Psi4.".format(func))
def psiSCF(self):
psi4.core.set_output_file("output.dat",False)
psi4.set_options({'basis': self.options['DEFAULT']['basis'],
'scf_type': 'pk',
'reference': 'rhf',
'puream': 0,
'print': 0 })
return psi4.energy('scf')
def test_psi4_sapt():
"""sapt1"""
#! SAPT0 cc-pVDZ computation of the ethene-ethyne interaction energy, using the cc-pVDZ-JKFIT RI basis for SCF
#! and cc-pVDZ-RI for SAPT. Monomer geometries are specified using Cartesian coordinates.
Eref = [ 85.189064196429101, -0.00359915058, 0.00362911158,
-0.00083137117, -0.00150542374, -0.00230683391 ]
ethene_ethyne = psi4.geometry("""
0 1
C 0.000000 -0.667578 -2.124659
C 0.000000 0.667578 -2.124659
H 0.923621 -1.232253 -2.126185
H -0.923621 -1.232253 -2.126185
H -0.923621 1.232253 -2.126185
H 0.923621 1.232253 -2.126185
--
0 1
C 0.000000 0.000000 2.900503
C 0.000000 0.000000 1.693240
H 0.000000 0.000000 0.627352
H 0.000000 0.000000 3.963929
units angstrom
""")
# this molecule will crash test if molecule passing broken
barrier = psi4.geometry("""
0 1
He
""")
psi4.set_options({
"basis": "cc-pvdz",
"guess": "sad",
"scf_type": "df",
"sad_print": 2,
"d_convergence": 11,
"puream": True,
"print": 1})
psi4.energy('sapt0', molecule=ethene_ethyne)
Eelst = psi4.get_variable("SAPT ELST ENERGY")
Eexch = psi4.get_variable("SAPT EXCH ENERGY")
Eind = psi4.get_variable("SAPT IND ENERGY")
Edisp = psi4.get_variable("SAPT DISP ENERGY")
ET = psi4.get_variable("SAPT0 TOTAL ENERGY")
assert psi4.compare_values(Eref[0], ethene_ethyne.nuclear_repulsion_energy(), 9, "Nuclear Repulsion Energy")
assert psi4.compare_values(Eref[1], Eelst, 6, "SAPT0 Eelst")
assert psi4.compare_values(Eref[2], Eexch, 6, "SAPT0 Eexch")
assert psi4.compare_values(Eref[3], Eind, 6, "SAPT0 Eind")
assert psi4.compare_values(Eref[4], Edisp, 6, "SAPT0 Edisp")
assert psi4.compare_values(Eref[5], ET, 6, "SAPT0 Etotal")
def _build_wfn(ref, func, basis, nosym):
if ref.startswith('RHF'):
mol = tddft_systems['RHF']
else:
mol = tddft_systems['UHF']
psi4.set_options({'reference': 'UHF'})
if nosym:
mol.reset_point_group('c1')
psi4.set_options({'scf_type': 'pk', 'e_convergence': 8, 'd_convergence': 8, 'save_jk': True})
e, wfn = psi4.energy("{}/{}".format(func, basis), return_wfn=True, molecule=mol)
return wfn
def test_gdma():
"""gdma1"""
#! Water RHF/cc-pVTZ distributed multipole analysis
ref_energy = -76.0571685433842219
ref_dma_mat = psi4.core.Matrix(3, 9)
ref_dma_mat.name = 'Reference DMA values'
ref_dma_arr = [
[ -0.43406697290168, -0.18762673939633, 0.00000000000000, 0.00000000000000, 0.03206686487531,
0.00000000000000, -0.00000000000000, -0.53123477172696, 0.00000000000000 ],
[ 0.21703348903257, -0.06422316619952, 0.00000000000000, -0.11648289410022, 0.01844320206227,
0.00000000000000, 0.07409226544133, -0.07115302332866, 0.00000000000000 ],
[ 0.21703348903257, -0.06422316619952, 0.00000000000000, 0.11648289410022, 0.01844320206227,
0.00000000000000, -0.07409226544133, -0.07115302332866, 0.00000000000000 ]
]
for i in range(3):
for j in range(9):
ref_dma_mat.set(i, j, ref_dma_arr[i][j])
ref_tot_mat = psi4.core.Matrix(1, 9)
ref_tot_mat.name = "Reference total values"
ref_tot_arr = [
0.00000000516346, -0.79665315928128, 0.00000000000000, 0.00000000000000, 0.10813259329390,
0.00000000000000, 0.00000000000000, -2.01989585894142, 0.00000000000000
]
for i in range(9):
ref_tot_mat.set(0, i, ref_tot_arr[i])
# noreorient/nocom are not needed, but are used here to guarantee that the
# GDMA origin placement defined below is at the O atom.
water = psi4.geometry("""
O 0.000000 0.000000 0.117176
H -0.000000 -0.756950 -0.468706
H -0.000000 0.756950 -0.468706
noreorient
nocom
""")
psi4.set_options({"scf_type": "pk",
"basis": "cc-pvtz",
"d_convergence": 10,
"gdma_switch": 0,
"gdma_radius": [ "H", 0.65 ],
"gdma_limit": 2,
"gdma_origin": [ 0.000000, 0.000000, 0.117176 ]})
energy, wfn = psi4.energy('scf', return_wfn=True)
psi4.gdma(wfn)
dmavals = psi4.core.variable("DMA DISTRIBUTED MULTIPOLES")
totvals = psi4.core.variable("DMA TOTAL MULTIPOLES")
assert psi4.compare_values(ref_energy, energy, 8, "SCF Energy")
assert psi4.compare_matrices(dmavals, ref_dma_mat, 6, "DMA Distributed Multipoles")
assert psi4.compare_matrices(totvals, ref_tot_mat, 6, "DMA Total Multipoles")
def test_v2rdm_casscf():
"""v2rdm_casscf/tests/v2rdm1"""
#! cc-pvdz N2 (6,6) active space Test DQG
print(' N2 / cc-pVDZ / DQG(6,6), scf_type = CD / 1e-12, rNN = 0.5 A')
import v2rdm_casscf
n2 = psi4.geometry("""
0 1
n
n 1 r
""")
interloper = psi4.geometry("""
0 1
O
H 1 1.0
H 1 1.0 2 90.0
""")
psi4.set_options({
'basis': 'cc-pvdz',
'scf_type': 'cd',
'cholesky_tolerance': 1e-12,
'd_convergence': 1e-10,
'maxiter': 500,
'restricted_docc': [ 2, 0, 0, 0, 0, 2, 0, 0 ],
'active': [ 1, 0, 1, 1, 0, 1, 1, 1 ],
})
##psi4.set_module_options('v2rdm_casscf', {
psi4.set_options({
# 'positivity': 'dqg',
'r_convergence': 1e-5,
'e_convergence': 1e-6,
'maxiter': 20000,
# #'orbopt_frequency': 1000,
# #'mu_update_frequency': 1000,
})
psi4.activate(n2)
n2.r = 0.5
refscf = -103.04337420425350
refv2rdm = -103.086205379481
psi4.energy('v2rdm-casscf', molecule=n2)
assert psi4.compare_values(refscf, psi4.get_variable("SCF TOTAL ENERGY"), 8, "SCF total energy")
assert psi4.compare_values(refv2rdm, psi4.get_variable("CURRENT ENERGY"), 5, "v2RDM-CASSCF total energy")
def test_psi4_basic():
"""tu1-h2o-energy"""
#! Sample HF/cc-pVDZ H2O computation
h2o = psi4.geometry("""
O
H 1 0.96
H 1 0.96 2 104.5
""")
psi4.set_options({'basis': "cc-pVDZ"})
psi4.energy('scf')
assert psi4.compare_values(-76.0266327341067125, psi4.get_variable('SCF TOTAL ENERGY'), 6, 'SCF energy')
def test_mp2_module(inp, clsd_open_pmols, request):
tnm = request.node.name
subject = clsd_open_pmols[inp['subject']]
ref_block = _ref_module[inp['options']['scf_type']][inp['options']['reference']]
ref_ref = ref_block['HF TOTAL ENERGY']
ref_block = ref_block[inp['options']['freeze_core']][inp['options']['mp2_type']]
ref_corl = ref_block['MP2 CORRELATION ENERGY']
ref_tot = ref_block['MP2 TOTAL ENERGY']
psi4.set_options({
'basis': 'cc-pvdz',
'guess': 'sad',
'e_convergence': 8,
'd_convergence': 7,
})
psi4.set_options(inp['options'])
if inp['driver'] == 'energy':
ene, wfn = psi4.energy('mp2', molecule=subject, return_wfn=True)
elif inp['driver'] == 'gradient':
grad, wfn = psi4.gradient('mp2', molecule=subject, return_wfn=True)
ref_tot_grad = ref_block['MP2 TOTAL GRADIENT']
for obj in [psi4.core, wfn]:
for pv in ['HF TOTAL ENERGY', 'SCF TOTAL ENERGY', 'CURRENT REFERENCE ENERGY']:
assert compare_values(ref_ref, obj.variable(pv), 6, tnm + ' ' + pv)
for pv in [
'MP2 CORRELATION ENERGY',
'CURRENT CORRELATION ENERGY',
]:
assert compare_values(ref_corl, obj.variable(pv), 6, tnm + ' ' + pv)
for pv in [
'MP2 TOTAL ENERGY',
'CURRENT ENERGY',
]:
assert compare_values(ref_tot, obj.variable(pv), 6, tnm + ' ' + pv)
assert compare_values(ref_tot, wfn.energy(), 6, tnm + ' wfn')
if inp['driver'] == 'energy':
assert compare_values(ref_tot, ene, 6, tnm + ' return')
elif inp['driver'] == 'gradient':
assert compare_matrices(ref_tot_grad, wfn.gradient(), 6, tnm + ' grad wfn')
assert compare_matrices(ref_tot_grad, grad, 6, tnm + ' grad return')
def test_opt():
"""
We pick the physicist's water molecule in a relatively large
basis set (aug-cc-pVDZ), whose uhf and rhf solutions are the
same. And we test that energies of the following four cases
are identical:
RHF + DIIS
RHF + ODA
UHF + DIIS
UHF + ODA
Note for DIIS, we in addition require the convergence is achieved
in 30 iterations.
"""
# get integrals from psi4
ao_ints, scf_params, e_ZZ_repul = \
scf.init(os.path.dirname(__file__) + '/test_opt.yml')
# RHF, DIIS
scf_params['max_iter'] = 30
eps, C, D, F = scf.scf(ao_ints, scf_params, e_ZZ_repul)
E_rhf_diis = scf.get_SCF_energy(ao_ints['H'], F, D, False) + e_ZZ_repul
# RHF, ODA
scf_params['max_iter'] = 300
scf_params['opt'] = "oda"
eps, C, D, F = scf.scf(ao_ints, scf_params, e_ZZ_repul)
E_rhf_oda = scf.get_SCF_energy(ao_ints['H'], F, D, False) + e_ZZ_repul
# UHF, DIIS
scf_params['max_iter'] = 30
scf_params['opt'] = "diis"
scf_params['unrestricted'] = True
eps, C, D, F = scf.scf(ao_ints, scf_params, e_ZZ_repul)
E_uhf_diis = scf.get_SCF_energy(ao_ints['H'], F, D, True) + e_ZZ_repul
# UHF, ODA
scf_params['max_iter'] = 300
scf_params['opt'] = "oda"
eps, C, D, F = scf.scf(ao_ints, scf_params, e_ZZ_repul)
E_uhf_oda = scf.get_SCF_energy(ao_ints['H'], F, D, True) + e_ZZ_repul
# RHF, psi4
import psi4
mol = psi4.geometry(scf_params['geometry'])
mol.update_geometry()
ctrl_string = "SCF/" + scf_params['basis']
psi4.set_options({"scf_type": "pk"})
psi4_E_rhf = psi4.energy(ctrl_string, molecule = mol)
# check
assert(np.allclose(E_rhf_diis, E_rhf_oda) == True)
assert(np.allclose(E_rhf_diis, E_uhf_diis) == True)
assert(np.allclose(E_rhf_diis, E_uhf_oda) == True)
assert(np.allclose(E_rhf_diis, psi4_E_rhf) == True)
def psiMP2(self,options):
psi4.core.set_output_file("output.dat",False)
psi4.set_options({'basis': options['DEFAULT']['basis'],
'scf_type': 'pk',
'reference': 'uhf',
'e_convergence': 12,
'df_basis_mp2' : self.dfBasisName,
'puream': 0,
'print': 0 })
if not self.df:
psi4.set_options( {'mp2_type': 'conv'} )
return psi4.energy('mp2')
def test_RU_TDA_C1():
h2o = psi4.geometry("""0 1
O 0.000000 0.000000 0.135446
H -0.000000 0.866812 -0.541782
H -0.000000 -0.866812 -0.541782
symmetry c1
no_reorient
no_com
""")
psi4.set_options({"scf_type": "pk", 'save_jk': True})
e, wfn = psi4.energy("hf/sto-3g", molecule=h2o, return_wfn=True)
A_ref, _ = build_UHF_AB_C1(wfn)
ni, na, _, _ = A_ref['IAJB'].shape
nia = ni * na
A_sing_ref = A_ref['IAJB'] + A_ref['IAjb']
A_sing_ref = A_sing_ref.reshape(nia, nia)
A_trip_ref = A_ref['IAJB'] - A_ref['IAjb']
A_trip_ref = A_trip_ref.reshape(nia, nia)
sing_vals, _ = np.linalg.eigh(A_sing_ref)
trip_vals, _ = np.linalg.eigh(A_trip_ref)
trip_eng = TDRSCFEngine(wfn, ptype='tda', triplet=True)
sing_eng = TDRSCFEngine(wfn, ptype='tda', triplet=False)
ID = [psi4.core.Matrix.from_array(v.reshape((ni, na))) for v in tuple(np.eye(nia).T)]
psi4.core.print_out("\nA sing:\n" + str(A_sing_ref) + "\n\n")
psi4.core.print_out("\nA trip:\n" + str(A_trip_ref) + "\n\n")
A_trip_test = np.column_stack([x.to_array().flatten() for x in trip_eng.compute_products(ID)[0]])
assert compare_arrays(A_trip_ref, A_trip_test, 8, "Triplet Ax C1 products")
A_sing_test = np.column_stack([x.to_array().flatten() for x in sing_eng.compute_products(ID)[0]])
assert compare_arrays(A_sing_ref, A_sing_test, 8, "Singlet Ax C1 products")
sing_vals_2, _ = np.linalg.eigh(A_sing_test)
trip_vals_2, _ = np.linalg.eigh(A_trip_test)
psi4.core.print_out("\n\n SINGLET EIGENVALUES\n")
for x, y in zip(sing_vals, sing_vals_2):
psi4.core.print_out("{:10.6f} {:10.6f}\n".format(x, y))
# assert compare_values(x, y, 4, "Singlet ROOT")
psi4.core.print_out("\n\n Triplet EIGENVALUES\n")
for x, y in zip(trip_vals, trip_vals_2):
psi4.core.print_out("{:10.6f} {:10.6f}\n".format(x, y))
# assert compare_values(x, y, 4, "Triplet Root")
for x, y in zip(sing_vals, sing_vals_2):
assert compare_values(x, y, 4, "Singlet ROOT")
for x, y in zip(trip_vals, trip_vals_2):
assert compare_values(x, y, 4, "Triplet Root")
def test_chemps2():
"""chemps2/scf-n2"""
#! dmrg-scf on N2
N2 = psi4.geometry("""
N 0.0000 0.0000 0.0000
N 0.0000 0.0000 2.1180
units au
""")
psi4.set_options({
'basis': 'cc-pVDZ',
'reference': 'rhf',
'e_convergence': 1e-12,
'd_convergence': 1e-12,
'dmrg_irrep': 0,
'dmrg_multiplicity': 1,
'restricted_docc': [ 1 , 0 , 0 , 0 , 0 , 1 , 0 , 0 ],
'active': [ 2 , 0 , 1 , 1 , 0 , 2 , 1 , 1 ],
'dmrg_sweep_states': [ 500, 1000, 1000 ],
'dmrg_sweep_energy_conv': [ 1e-10, 1e-10, 1e-10 ],
'dmrg_sweep_dvdson_rtol': [ 1e-4, 1e-6, 1e-8 ],
'dmrg_sweep_max_sweeps': [ 5, 5, 10 ],
'dmrg_sweep_noise_prefac': [ 0.05, 0.05, 0.0 ],
'dmrg_print_corr': True,
'dmrg_mps_write': False,
'dmrg_unitary_write': True,
'dmrg_diis': True,
'dmrg_scf_diis_thr': 1e-2,
'dmrg_diis_write': True,
'dmrg_excitation': 0, # Ground state
'dmrg_scf_state_avg': False,
'dmrg_scf_active_space': 'NO', # INPUT; NO; LOC
'dmrg_local_init': False,
})
psi4.energy("dmrg-scf")
ref_energy = -109.1035023353
assert psi4.compare_values(ref_energy, psi4.variable("CURRENT ENERGY"), 6, "DMRG Energy")
def test_dkh():
"""dkh/molpro-2order"""
Ne = psi4.geometry("""
0 1
Ne
""")
psi4.set_options({
'reference': 'rhf',
'basis': 'cc-pvtz-dk',
'relativistic': 'dkh',
'dkh_order': 2,
'print': 2,
'scf_type': 'pk'})
e = psi4.energy('scf')
assert psi4.compare_values(-128.66891610, e, 6, '2nd order vs Molpro')
np.set_printoptions(precision=5, linewidth=200, suppress=True)
import psi4
psi4.core.set_memory(int(2e9), False)
psi4.core.set_output_file('output.dat', False)
numpy_memory = 2
mol = psi4.geometry("""
O
H 1 1.1
H 1 1.1 2 104
symmetry c1
""")
psi4.set_options({'basis': 'cc-pVDZ'})
# For numpy
compare_psi4 = True
# Compute CCSD
ccsd = helper_CCSD(mol, memory=2)
ccsd.compute_energy()
CCSDcorr_E = ccsd.ccsd_corr_e
CCSD_E = ccsd.ccsd_e
print('\nFinal CCSD correlation energy: % 16.10f' % CCSDcorr_E)
print('Total CCSD energy: % 16.10f' % CCSD_E)
# Triples correction required o^3v^3 storage due the noddy algorithm
def test_dftd3():
"""dftd3/energy"""
#! Exercises the various DFT-D corrections, both through python directly and through c++
ref_d2 = [-0.00390110, -0.00165271, -0.00058118]
ref_d3zero = [-0.00285088, -0.00084340, -0.00031923]
ref_d3bj = [-0.00784595, -0.00394347, -0.00226683]
ref_pbe_d2 = [-0.00278650, -0.00118051, -0.00041513]
ref_pbe_d3zero = [-0.00175474, -0.00045421, -0.00016839]
ref_pbe_d3bj = [-0.00475937, -0.00235265, -0.00131239]
eneyne = psi4.geometry("""
C 0.000000 -0.667578 -2.124659
C 0.000000 0.667578 -2.124659
H 0.923621 -1.232253 -2.126185
H -0.923621 -1.232253 -2.126185
H -0.923621 1.232253 -2.126185
H 0.923621 1.232253 -2.126185
--
C 0.000000 0.000000 2.900503
C 0.000000 0.000000 1.693240
H 0.000000 0.000000 0.627352
H 0.000000 0.000000 3.963929
""")
psi4.print_stdout(' -D correction from Py-side')
eneyne.update_geometry()
E, G = eneyne.run_dftd3('b3lyp', 'd2gr')
assert psi4.compare_values(ref_d2[0], E, 7, 'Ethene-Ethyne -D2')
mA = eneyne.extract_subsets(1)
E, G = mA.run_dftd3('b3lyp', 'd2gr')
assert psi4.compare_values(ref_d2[1], E, 7, 'Ethene -D2')
mB = eneyne.extract_subsets(2)
E, G = mB.run_dftd3('b3lyp', 'd2gr')
assert psi4.compare_values(ref_d2[2], E, 7, 'Ethyne -D2')
#mBcp = eneyne.extract_subsets(2,1)
#E, G = mBcp.run_dftd3('b3lyp', 'd2gr')
#compare_values(ref_d2[2], E, 7, 'Ethyne(CP) -D2')
E, G = eneyne.run_dftd3('b3lyp', 'd3zero')
assert psi4.compare_values(ref_d3zero[0], E, 7, 'Ethene-Ethyne -D3 (zero)')
mA = eneyne.extract_subsets(1)
E, G = mA.run_dftd3('b3lyp', 'd3zero')
assert psi4.compare_values(ref_d3zero[1], E, 7, 'Ethene -D3 (zero)')
mB = eneyne.extract_subsets(2)
E, G = mB.run_dftd3('b3lyp', 'd3zero')
assert psi4.compare_values(ref_d3zero[2], E, 7, 'Ethyne -D3 (zero)')
E, G = eneyne.run_dftd3('b3lyp', 'd3bj')
assert psi4.compare_values(ref_d3bj[0], E, 7, 'Ethene-Ethyne -D3 (bj)')
mA = eneyne.extract_subsets(1)
E, G = mA.run_dftd3('b3lyp', 'd3bj')
assert psi4.compare_values(ref_d3bj[1], E, 7, 'Ethene -D3 (bj)')
mB = eneyne.extract_subsets(2)
E, G = mB.run_dftd3('b3lyp', 'd3bj')
assert psi4.compare_values(ref_d3bj[2], E, 7, 'Ethyne -D3 (bj)')
E, G = eneyne.run_dftd3('b3lyp', 'd3')
assert psi4.compare_values(ref_d3zero[0], E, 7, 'Ethene-Ethyne -D3 (alias)')
E, G = eneyne.run_dftd3('b3lyp', 'd')
assert psi4.compare_values(ref_d2[0], E, 7, 'Ethene-Ethyne -D (alias)')
E, G = eneyne.run_dftd3('b3lyp', 'd2')
assert psi4.compare_values(ref_d2[0], E, 7, 'Ethene-Ethyne -D2 (alias)')
psi4.set_options({'basis': 'sto-3g',
'scf_type': 'df',
'dft_radial_points': 50, # use really bad grid for speed since all we want is the -D value
'dft_spherical_points': 110,
#'scf print': 3, # will print dftd3 program output to psi4 output file
})
psi4.print_stdout(' -D correction from C-side')
psi4.activate(mA)
#psi4.energy('b3lyp-d2p4')
#assert psi4.compare_values(ref_d2[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2 (calling psi4 Disp class)')
#psi4.energy('b3lyp-d2gr')
#assert psi4.compare_values(ref_d2[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2 (calling dftd3 -old)')
#psi4.energy('b3lyp-d3zero')
#assert psi4.compare_values(ref_d3zero[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (calling dftd3 -zero)')
psi4.energy('b3lyp-d3bj')
assert psi4.compare_values(ref_d3bj[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (calling dftd3 -bj)')
psi4.energy('b3lyp-d2')
assert psi4.compare_values(ref_d2[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2 (alias)')
#psi4.energy('b3lyp-d3')
#assert psi4.compare_values(ref_d3zero[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (alias)')
#psi4.energy('b3lyp-d')
#assert psi4.compare_values(ref_d2[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D (alias)')
psi4.energy('wb97x-d')
assert psi4.compare_values(-0.000834247063, psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene wb97x-d (chg)')
psi4.print_stdout(' non-default -D correction from C-side')
psi4.activate(mB)
#psi4.set_options({'dft_dispersion_parameters': [0.75]})
#psi4.energy('b3lyp-d2p4')
#assert psi4.compare_values(ref_pbe_d2[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2 (calling psi4 Disp class)')
#psi4.set_options({'dft_dispersion_parameters': [0.75, 20.0]})
#psi4.energy('b3lyp-d2gr')
#assert psi4.compare_values(ref_pbe_d2[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2 (calling dftd3 -old)')
#psi4.set_options({'dft_dispersion_parameters': [1.0, 0.722, 1.217, 14.0]})
#psi4.energy('b3lyp-d3zero')
#assert psi4.compare_values(ref_pbe_d3zero[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (calling dftd3 -zero)')
psi4.set_options({'dft_dispersion_parameters': [1.000, 0.7875, 0.4289, 4.4407]})
psi4.energy('b3lyp-d3bj')
assert psi4.compare_values(ref_pbe_d3bj[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (calling dftd3 -bj)')
psi4.set_options({'dft_dispersion_parameters': [0.75]})
psi4.energy('b3lyp-d2')
assert psi4.compare_values(ref_pbe_d2[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2 (alias)')
psi4.set_options({'dft_dispersion_parameters': [1.0, 0.722, 1.217, 14.0]})
psi4.energy('b3lyp-d3')
assert psi4.compare_values(ref_pbe_d3zero[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (alias)')
psi4.set_options({'dft_dispersion_parameters': [0.75]})
psi4.energy('b3lyp-d')
assert psi4.compare_values(ref_pbe_d2[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D (alias)')
psi4.activate(mA)
psi4.set_options({'dft_dispersion_parameters': [1.0]})
psi4.energy('wb97x-d')
assert psi4.compare_values(-0.000834247063, psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene wb97x-d (chg)')
psi4.print_stdout(' non-default -D correction from Py-side')
eneyne.update_geometry()
eneyne.run_dftd3('b3lyp', 'd2gr', {'s6': 0.75})
assert psi4.compare_values(ref_pbe_d2[0], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene-Ethyne -D2')
mA = eneyne.extract_subsets(1)
mA.run_dftd3('b3lyp', 'd2gr', {'s6': 0.75})
assert psi4.compare_values(ref_pbe_d2[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D2')
mB = eneyne.extract_subsets(2)
mB.run_dftd3('b3lyp', 'd2gr', {'s6': 0.75})
assert psi4.compare_values(ref_pbe_d2[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethyne -D2')
eneyne.run_dftd3('b3lyp', 'd3zero', {'s6': 1.0, 's8': 0.722, 'sr6': 1.217, 'alpha6': 14.0})
assert psi4.compare_values(ref_pbe_d3zero[0], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene-Ethyne -D3 (zero)')
mA = eneyne.extract_subsets(1)
mA.run_dftd3('b3lyp', 'd3zero', {'s6': 1.0, 's8': 0.722, 'sr6': 1.217, 'alpha6': 14.0})
assert psi4.compare_values(ref_pbe_d3zero[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (zero)')
mB = eneyne.extract_subsets(2)
mB.run_dftd3('b3lyp', 'd3zero', {'s6': 1.0, 's8': 0.722, 'sr6': 1.217, 'alpha6': 14.0})
assert psi4.compare_values(ref_pbe_d3zero[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethyne -D3 (zero)')
eneyne.run_dftd3('b3lyp', 'd3bj', {'s6': 1.000, 's8': 0.7875, 'a1': 0.4289, 'a2': 4.4407})
assert psi4.compare_values(ref_pbe_d3bj[0], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene-Ethyne -D3 (bj)')
mA = eneyne.extract_subsets(1)
mA.run_dftd3('b3lyp', 'd3bj', {'s6': 1.000, 's8': 0.7875, 'a1': 0.4289, 'a2': 4.4407})
assert psi4.compare_values(ref_pbe_d3bj[1], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene -D3 (bj)')
mB = eneyne.extract_subsets(2)
mB.run_dftd3('b3lyp', 'd3bj', {'s6': 1.000, 's8': 0.7875, 'a1': 0.4289, 'a2': 4.4407})
assert psi4.compare_values(ref_pbe_d3bj[2], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethyne -D3 (bj)')
eneyne.run_dftd3('b3lyp', 'd3', {'s6': 1.0, 's8': 0.722, 'sr6': 1.217, 'alpha6': 14.0})
assert psi4.compare_values(ref_pbe_d3zero[0], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene-Ethyne -D3 (alias)')
eneyne.run_dftd3('b3lyp', 'd', {'s6': 0.75})
assert psi4.compare_values(ref_pbe_d2[0], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene-Ethyne -D (alias)')
eneyne.run_dftd3('b3lyp', 'd2', {'s6': 0.75})
assert psi4.compare_values(ref_pbe_d2[0], psi4.get_variable('DISPERSION CORRECTION ENERGY'), 7, 'Ethene-Ethyne -D2 (alias)')
def test_psi4_scfproperty():
"""scf-property"""
#! UFH and B3LYP cc-pVQZ properties for the CH2 molecule.
with open('grid.dat', 'w') as handle:
handle.write("""\
0.0 0.0 0.0
1.1 1.3 1.4
""")
ch2 = psi4.geometry("""
0 3
c
h 1 b1
h 1 b1 2 a1
b1 = 1.0
a1 = 125.0
""")
# Get a reasonable guess, to save some iterations
psi4.set_options({
"scf_type": "pk",
"basis": "6-31G**",
"e_convergence": 8,
"docc": [2, 0, 0, 1],
"socc": [1, 0, 1, 0],
"reference": "uhf"
})
ch2.update_geometry()
assert psi4.compare_values(6.648418918908746,
ch2.nuclear_repulsion_energy(), 9,
"Nuclear repulsion energy")
props = [
'DIPOLE', 'QUADRUPOLE', 'MULLIKEN_CHARGES', 'LOWDIN_CHARGES',
'WIBERG_LOWDIN_INDICES', 'MAYER_INDICES', 'MAYER_INDICES',
'MO_EXTENTS', 'GRID_FIELD', 'GRID_ESP', 'ESP_AT_NUCLEI',
'MULTIPOLE(5)', 'NO_OCCUPATIONS'
]
psi4.property('scf', properties=props)
assert psi4.compare_values(psi4.get_variable("CURRENT ENERGY"),
-38.91591819679808, 6, "SCF energy")
assert psi4.compare_values(psi4.get_variable('SCF DIPOLE X'),
0.000000000000, 4, "SCF DIPOLE X")
assert psi4.compare_values(psi4.get_variable('SCF DIPOLE Y'),
0.000000000000, 4, "SCF DIPOLE Y")
assert psi4.compare_values(psi4.get_variable('SCF DIPOLE Z'),
0.572697798348, 4, "SCF DIPOLE Z")
assert psi4.compare_values(psi4.get_variable('SCF QUADRUPOLE XX'),
-7.664066833060, 4, "SCF QUADRUPOLE XX")
assert psi4.compare_values(psi4.get_variable('SCF QUADRUPOLE YY'),
-6.097755074075, 4, "SCF QUADRUPOLE YY")
assert psi4.compare_values(psi4.get_variable('SCF QUADRUPOLE ZZ'),
-7.074596012050, 4, "SCF QUADRUPOLE ZZ")
assert psi4.compare_values(psi4.get_variable('SCF QUADRUPOLE XY'),
0.000000000000, 4, "SCF QUADRUPOLE XY")
assert psi4.compare_values(psi4.get_variable('SCF QUADRUPOLE XZ'),
0.000000000000, 4, "SCF QUADRUPOLE XZ")
assert psi4.compare_values(psi4.get_variable('SCF QUADRUPOLE YZ'),
0.000000000000, 4, "SCF QUADRUPOLE YZ")
psi4.property('B3LYP', properties=props)
assert psi4.compare_values(psi4.get_variable('CURRENT ENERGY'),
-39.14134740550916, 6, "B3LYP energy")
assert psi4.compare_values(psi4.get_variable('B3LYP DIPOLE X'),
0.000000000000, 4, "B3LYP DIPOLE X")
assert psi4.compare_values(psi4.get_variable('B3LYP DIPOLE Y'),
-0.000000000000, 4, "B3LYP DIPOLE Y")
assert psi4.compare_values(psi4.get_variable('B3LYP DIPOLE Z'),
0.641741521158, 4, "B3LYP DIPOLE Z")
assert psi4.compare_values(psi4.get_variable('B3LYP QUADRUPOLE XX'),
-7.616483183211, 4, "B3LYP QUADRUPOLE XX")
assert psi4.compare_values(psi4.get_variable('B3LYP QUADRUPOLE YY'),
-6.005896804551, 4, "B3LYP QUADRUPOLE YY")
assert psi4.compare_values(psi4.get_variable('B3LYP QUADRUPOLE ZZ'),
-7.021817489904, 4, "B3LYP QUADRUPOLE ZZ")
assert psi4.compare_values(psi4.get_variable('B3LYP QUADRUPOLE XY'),
0.000000000000, 4, "B3LYP QUADRUPOLE XY")
assert psi4.compare_values(psi4.get_variable('B3LYP QUADRUPOLE XZ'),
0.000000000000, 4, "B3LYP QUADRUPOLE XZ")
assert psi4.compare_values(psi4.get_variable('B3LYP QUADRUPOLE YZ'),
-0.000000000000, 4, "B3LYP QUADRUPOLE YZ")
# Memory for Psi4 in GB
psi4.core.set_memory(int(5e8), False)
psi4.core.set_output_file("output.dat", False)
# Memory for numpy in GB
numpy_memory = 2
mol = psi4.geometry("""
O
H 1 1.1
H 1 1.1 2 104
symmetry c1
""")
psi4.set_options({'basis': 'cc-pvdz', 'scf_type': 'pk', 'e_convergence': 1e-8})
# Set defaults
maxiter = 40
E_conv = 1.0E-6
D_conv = 1.0E-3
# Integral generation from Psi4's MintsHelper
wfn = psi4.core.Wavefunction.build(mol, psi4.core.get_global_option('BASIS'))
t = time.time()
mints = psi4.core.MintsHelper(wfn.basisset())
S = np.asarray(mints.ao_overlap())
# Get nbf and ndocc for closed shell molecules
nbf = S.shape[0]
ndocc = wfn.nalpha()
import psi4
psi4.set_output_file("output.dat", False)
geom = psi4.geometry("""
C
""")
psi4.set_options({"SCF_TYPE": "DF", "BASIS": "cc-pVDZ"})
scf_e, scf_wfn = psi4.energy('SCF', return_wfn=True)
psi4.compare_values(-37.5959861862713893, scf_e, 6, 'SCF DF Energy')
psi4.core.set_local_option("SCF", "SCF_TYPE", "PK")
psi4.compare_values(-37.5959861862713893, scf_e, 6, 'SCF PK Energy')
#!/usr/bin/python3
"""
Test for reproducing results from Steven & Fink, CPL 139, pp.: 15-22 (1987)
Usage: [basis] [xyz.psi]
"""
import psi4, gefp, sys
psi4.set_options({
"scf_type": "direct",
"guess": "auto",
"df_scf_guess": True,
"e_convergence": 1e-10,
"d_convergence": 1e-10,
"basis": sys.argv[1],
"puream": False,
"print": 1,
})
psi4.set_output_file("test.log", False)
mol = gefp.core.utilities.psi_molecule_from_file(sys.argv[2])
gefp.math.matrix.move_atom_rotate_molecule(mol, [-30., -83., 43.1])
e_hf, wfn = psi4.energy('scf', molecule=mol, return_wfn=True)
sol = gefp.density.rvs.RVS(wfn)
sol.run_dimer(conver=1e-8)
psi4.core.print_out(str(sol))
def test_sparse_ci():
import math
import psi4
import forte
import itertools
import numpy as np
import pytest
from forte import forte_options
ref_fci = -1.101150330132956
psi4.core.clean()
# need to clean the options otherwise this job will interfere
forte.clean_options()
psi4.geometry("""
H
H 1 1.0
""")
psi4.set_options({'basis': 'sto-3g'})
E_scf, wfn = psi4.energy('scf', return_wfn=True)
na = wfn.nalpha()
nb = wfn.nbeta()
nirrep = wfn.nirrep()
wfn_symmetry = 0
forte.startup()
forte.banner()
psi4_options = psi4.core.get_options()
psi4_options.set_current_module('FORTE')
forte_options.get_options_from_psi4(psi4_options)
# Setup forte and prepare the active space integral class
nmopi = wfn.nmopi()
point_group = wfn.molecule().point_group().symbol()
mo_space_info = forte.make_mo_space_info(nmopi, point_group, forte_options)
ints = forte.make_ints_from_psi4(wfn, forte_options, mo_space_info)
as_ints = forte.make_active_space_ints(mo_space_info, ints, 'ACTIVE',
['RESTRICTED_DOCC'])
as_ints.print()
print('\n\n => Sparse FCI Test <=')
print(' Number of irreps: {}'.format(nirrep))
nmo = wfn.nmo()
nmopi = [wfn.nmopi()[h] for h in range(nirrep)]
nmopi_str = [str(wfn.nmopi()[h]) for h in range(nirrep)]
mo_sym = []
for h in range(nirrep):
for i in range(nmopi[h]):
mo_sym.append(h)
print(' Number of orbitals per irreps: [{}]'.format(','.join(nmopi_str)))
print(' Symmetry of the MOs: ', mo_sym)
hf_reference = forte.Determinant()
hf_reference.create_alfa_bit(0)
hf_reference.create_beta_bit(0)
print(' Hartree-Fock determinant: {}'.format(hf_reference.str(2)))
# Compute the HF energy
hf_energy = as_ints.nuclear_repulsion_energy() + as_ints.slater_rules(
hf_reference, hf_reference)
print(' Nuclear repulsion energy: {}'.format(
as_ints.nuclear_repulsion_energy()))
print(' Reference energy: {}'.format(hf_energy))
# Build a list of determinants
orblist = [i for i in range(nmo)]
dets = []
for astr in itertools.combinations(orblist, na):
for bstr in itertools.combinations(orblist, nb):
sym = 0
d = forte.Determinant()
for a in astr:
d.create_alfa_bit(a)
sym = sym ^ mo_sym[a]
for b in bstr:
d.create_beta_bit(b)
sym = sym ^ mo_sym[b]
if (sym == wfn_symmetry):
dets.append(d)
print(' Determinant {} has symmetry {}'.format(
d.str(nmo), sym))
# Build the Hamiltonian matrix using 'slater_rules'
nfci = len(dets)
H = np.ndarray((nfci, nfci))
for I in range(nfci):
# off-diagonal terms
for J in range(I + 1, nfci):
HIJ = as_ints.slater_rules(dets[I], dets[J])
H[I][J] = H[J][I] = HIJ
# diagonal term
H[I][I] = as_ints.nuclear_repulsion_energy() + as_ints.slater_rules(
dets[I], dets[I])
# Find the lowest eigenvalue
efci = np.linalg.eigh(H)[0][0]
print('\n FCI Energy: {}\n'.format(efci))
assert efci == pytest.approx(ref_fci, 1.0e-9)
# Clean up forte (necessary)
forte.cleanup()
# Memory for numpy in GB
numpy_memory = 2
# Triplet O2
mol = psi4.geometry("""
0 3
O
O 1 1.2
symmetry c1
""")
psi4.set_options({
'guess': 'core',
'basis': 'aug-cc-pvdz',
'scf_type': 'pk',
'e_convergence': 1e-8,
'reference': 'rohf'
})
wfn = psi4.core.Wavefunction.build(mol, psi4.core.get_global_option('BASIS'))
# Set occupations
nocc = wfn.nalpha()
ndocc = wfn.nbeta()
nsocc = nocc - ndocc
# Set defaults
maxiter = 10
max_micro = 4
micro_print = True
C 0.69705 -1.20732 0.00000
C -0.69705 -1.20732 0.00000
C -1.39410 0.00000 0.00000
C -0.69705 1.20732 0.00000
C 0.69705 1.20732 0.00000
H 2.47618 0.00000 0.00000
H 1.23809 -2.14444 0.00000
H -1.23809 -2.14444 0.00000
H -2.47618 0.00000 0.00000
H -1.23809 2.14444 0.00000
H 1.23809 2.14444 0.00000
symmetry c1
""")
# Basis used in mp2 density fitting
psi4.set_options({'basis': 'aug-cc-pVDZ', 'df_basis_scf': 'aug-cc-pvdz-ri'})
check_energy = False
print('\nStarting RHF...')
t = time.time()
RHF_E, wfn = psi4.energy('SCF', return_wfn=True)
print('...RHF finished in %.3f seconds: %16.10f' % (time.time() - t, RHF_E))
# Grab data from Wavfunction clas
ndocc = wfn.nalpha()
nbf = wfn.nso()
nvirt = nbf - ndocc
# Split eigenvectors and eigenvalues into o and v
eps_occ = np.asarray(wfn.epsilon_a_subset("AO", "ACTIVE_OCC"))
def sf_cas(new_charge,
new_multiplicity,
ref_mol,
conf_space="",
add_opts={},
return_ci_wfn=False,
return_rohf_wfn=False,
return_rohf_e=False,
read_rohf_wfn=False,
wfn_rohf_in=None,
write_rohf_wfn="",
write_ci_vects=False,
localize=False,
frozen_docc=0,
frozen_uocc=0):
"""
A method to run a RAS-nSF-IP/EA calculation.
This runs a RAS-nSF-IP/EA calculation using Psi4's DETCI module. The
number of spin-flips and IP/EA is determined based on setting the
``new_charge`` and ``new_multiplicity`` of the desired target state.
Additional excitations are included by setting the ``conf_space``
keyword; excitations through the CISDT level are currently supported.
Parameters
----------
new_charge : int
Target charge of the molecule.
new_multiplicity : int
Target multiplicity of the molecule.
ref_mol : psi4.core.Molecule
Molecule to run the calculation on.
conf_space : str ("")
Option for including additional excitations outside of the CAS space.
Defaults to CAS-nSF-IP/EA. Valid options include:
* ``""`` CAS-nSF-IP/EA
* ``"h"`` RAS(h)-nSF-IP/EA
* ``"p"`` RAS(p)-nSF-IP/EA
* ``"1x"`` RAS(h,p)-nSF-IP/EA
* ``"S"`` RAS(S)-nSF-IP/EA
* ``"SD"`` RAS(SD)-nSF-IP/EA
* ``"SDT"`` RAS(SDT)-nSF-IP/EA
add_opts : dict ({})
Additional options to pass into Psi4.
return_ci_wfn : bool (False)
Whether to return the CI wavefunction object.
return_rohf_wfn : bool (False)
Whether to return the ROHF wavefunction object.
return_rohf_e : bool (False)
Whether to return the ROHF energy.
read_rohf_wfn : bool (False)
Whether to read a Psi4 ROHF wavefunction.
rohf_wfn_in : psi4.core.Wavefunction
The Psi4 ROHF reference wavefunction (pre-computed).
write_rohf_wfn : str ("")
Name of file (.npz) to write
localize : bool (False)
Perform BOYS localization on the RAS 2 space before DETCI call?
Can help with visualization and analysis of orbitals.
Returns
-------
e_ci : double
The SF-CAS([conf_space]) energy.
return_ci_wfn : psi4.core.Wavefunction
(optional) The SF-CAS([conf_space]) wavefunction.
return_rohf_e : double
(optional) The ROHF energy.
return_rohf_wfn : psi4.core.Wavefunction
(optional) The ROHF wavefunction.
"""
# printing initial information about the calculation
print("SF-CAS(%s) CALCULATION" % conf_space)
# default options for Psi4
opts = {
'scf_type': 'pk',
'basis': 'cc-pvdz',
'reference': 'rohf',
'mixed': False,
'maxiter': 1000,
'ci_maxiter': 50
}
opts.update(add_opts) # add additional options from user
# run ROHF calculation on reference state or read it in
psi4.core.clean() # cleanup in case Psi4 has been run before
psi4.set_options(opts)
mol = ref_mol.clone() # clone molecule so original isn't modified
# read in ROHF guess wavefunction if provided
if (read_rohf_wfn):
# set up options and run
psi4.set_options(opts)
print("USING ROHF FROM REFERENCE...\tCHARGE %i\tMULT %i" %
(ref_mol.molecular_charge(), ref_mol.multiplicity()))
wfn_rohf = wfn_rohf_in
e_rohf = wfn_rohf.energy()
# else, run ROHF on reference state
else:
print("RUNNING REFERENCE...\tCHARGE %i\tMULT %i" %
(ref_mol.molecular_charge(), ref_mol.multiplicity()))
e_rohf, wfn_rohf = psi4.energy('scf',
molecule=mol,
return_wfn=True,
options=opts)
print("SCF (%i %i): %6.12f" %
(mol.molecular_charge(), mol.multiplicity(), e_rohf))
# change charge and multiplicity to new target values
print("DOING SPIN-FLIP: CHARGE %i, MULTIPLICITY %i" %
(new_charge, new_multiplicity))
# saving npz file of wavefunction
if (write_rohf_wfn != ""):
wfn_rohf.to_file(write_rohf_wfn)
# update molecular charge and multiplicity
mol.set_molecular_charge(new_charge)
mol.set_multiplicity(new_multiplicity)
# set up reference wfn to pass into detci
# save orbital values from reference calculation
doccpi = wfn_rohf.doccpi()[0]
soccpi = wfn_rohf.soccpi()[0]
nmo = wfn_rohf.nmo()
# calculate soccpi and doccpi
new_soccpi = mol.multiplicity() - 1
del_electrons = ref_mol.molecular_charge() - mol.molecular_charge()
n_total = wfn_rohf.nalpha() + wfn_rohf.nbeta() + del_electrons
# set orbital occupations
wfn_rohf.force_soccpi(psi4.core.Dimension([new_soccpi]))
wfn_rohf.force_doccpi(
psi4.core.Dimension([(int)((n_total - new_soccpi) / 2)]))
# if we need to localize...
if (localize):
C = psi4.core.Matrix.to_array(wfn_rohf.Ca(), copy=True)
ras1_C = C[:, :doccpi]
ras2_C = C[:, doccpi:doccpi + soccpi]
ras3_C = C[:, doccpi + soccpi:]
loc = psi4.core.Localizer.build('BOYS', wfn_rohf.basisset(),
psi4.core.Matrix.from_array(ras2_C))
loc.localize()
ras2_localized = psi4.core.Matrix.to_array(loc.L, copy=True)
localized_orbs = np.column_stack((ras1_C, ras2_localized, ras3_C))
new_Ca = psi4.core.Matrix.from_array(localized_orbs, name="Ca")
new_Cb = psi4.core.Matrix.from_array(localized_orbs, name="Cb")
wfn_rohf.Ca().copy(new_Ca)
wfn_rohf.Cb().copy(new_Cb)
# set active space and docc space based on configuration space input
# Regular CAS configuration space
# includes only active space configurations
if (conf_space == ""):
opts.update({'frozen_docc': [doccpi]})
opts.update({'ras1': [0]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [0]})
opts.update({'ras4': [0]})
# just (h) excitations
elif (conf_space == "h"):
opts.update({'ex_level': 0})
opts.update({'val_ex_level': 1})
opts.update({'ras3_max': 0})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [doccpi - frozen_docc]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [0]})
opts.update({'ras4': [0]})
# just (p) excitations
elif (conf_space == "p"):
opts.update({'ex_level': 0})
opts.update({'val_ex_level': 0})
opts.update({'ras3_max': 1})
opts.update({'frozen_docc': [doccpi]})
opts.update({'ras1': [0]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [nmo - soccpi - doccpi - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
# 1x configuration space
# includes (h, p) excitations
elif (conf_space == "1x"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 0})
opts.update({'val_ex_level': 1})
opts.update({'ras3_max': 1})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [doccpi - frozen_docc]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [nmo - soccpi - doccpi - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
# S configuration space
# includes (h, p, hp) excitations
elif (conf_space == "S" or conf_space == "xcis"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 1})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [doccpi - frozen_docc]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [nmo - soccpi - doccpi - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
elif (conf_space == "SD"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 2})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [doccpi - frozen_docc]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [nmo - soccpi - doccpi - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
elif (conf_space == "SDT"):
opts.update({'frozen_docc': [0]})
opts.update({'ex_level': 3})
opts.update({'frozen_docc': [frozen_docc]})
opts.update({'ras1': [doccpi - frozen_docc]})
opts.update({'ras2': [soccpi]})
opts.update({'ras3': [nmo - soccpi - doccpi - frozen_uocc]})
opts.update({'frozen_uocc': [frozen_uocc]})
opts.update({'ras4': [0]})
# Other configuration spaces aren't supported yet
else:
print("Configuration space %s not supported. Exiting..." % conf_space)
exit()
# run cas
print("RUNNING CAS...\t\tCHARGE %i\tMULT %i" %
(mol.molecular_charge(), mol.multiplicity()))
psi4.set_options(opts)
e_cas, wfn_cas = psi4.energy('detci',
ref_wfn=wfn_rohf,
return_wfn=True,
molecule=mol)
print("CAS (%i %i): %6.12f" %
(mol.molecular_charge(), mol.multiplicity(), e_cas))
# obtain eigenvectors if needed
# partly based on Daniel Smith's answer on Psi4 forums
if (write_ci_vects):
wfn_cas_2 = psi4.core.CIWavefunction(wfn_rohf)
n_roots = add_opts['NUM_ROOTS']
C = np.zeros((wfn_cas_2.ndet(), n_roots))
print(C.shape)
for i in range(n_roots):
dvec = wfn_cas_2.new_civector(i + 1, 53, True, True)
dvec.set_nvec(i + 1)
dvec.init_io_files(True)
dvec.read(i, 0)
C[:, i] = np.array(dvec)
np.savetxt('ci_vect.txt', C)
psi4.core.print_variables() # printing Psi4 variables
psi4.core.clean_options() # more cleanup
# return output specified by the user
if ((not return_ci_wfn) and (not return_rohf_wfn) and (not return_rohf_e)):
return e_cas
else:
out = (e_cas, )
if (return_ci_wfn):
out = out + (wfn_cas, )
if (return_rohf_wfn):
out = out + (wfn_rohf, )
if (return_rohf_e):
out = out + (e_rohf, )
return out
# examples/api/05_casscf-doublet-guess.py
"""Example of a CASSCF computation on singlet methylene starting from doublet ROHF orbitals (from psi4)"""
import psi4
import forte
psi4.geometry("""
1 2
C
H 1 1.085
H 1 1.085 2 135.5
""")
psi4.set_options({
'basis': 'DZ',
'scf_type': 'pk',
'e_convergence': 12,
'reference': 'rohf'
})
e, wfn = psi4.energy('scf', return_wfn=True)
psi4.set_options({
'forte__job_type': 'mcscf_two_step',
'forte__charge': 0, # <-- to override charge = +1 assumed from geometry
'forte__multiplicity':
1, # <-- to override multiplicity = 2 assumed from geometry
'forte__ms': 0, # <-- to override ms = 1/2 assumed from geometry
'forte__active_space_solver': 'fci',
'forte__restricted_docc': [1, 0, 0, 0],
'forte__active': [3, 0, 2, 2],
})
def runner_asserter(inp, subject, method, basis, tnm):
qc_module_in = "-".join(["psi4", inp["keywords"].get("qc_module", "")
]).strip("-") # returns "psi4"|"psi4-<module>"
driver = inp["driver"]
reference = inp["keywords"]["reference"]
fcae = {"true": "fc", "false": "ae"}[inp["keywords"]["freeze_core"]]
if qc_module_in == "psi4-detci" and basis != "cc-pvdz":
pytest.skip(f"basis {basis} too big for {qc_module_in}")
# <<< Reference Values >>>
# ? precedence on next two
scf_type = inp.get("corl_type", inp["keywords"].get(
"scf_type", "df")) # hard-code of read_options.cc SCF_TYPE
mp2_type = inp.get("corl_type", inp["keywords"].get(
"mp2_type", "df")) # hard-code of read_options.cc MP2_TYPE
if method in ["mp2.5", "mp3"]:
mp_type = inp.get("corl_type", inp["keywords"].get(
"mp_type", "df")) # hard-code of proc.py run_dfocc MP_TYPE
else:
mp_type = inp.get("corl_type", inp["keywords"].get(
"mp_type", "conv")) # hard-code of read_options.cc MP_TYPE
cc_type = inp.get("corl_type", inp["keywords"].get(
"cc_type", "conv")) # hard-code of read_options.cc CC_TYPE
corl_natural_values = {
"hf": "df", # dummy to assure df/cd/conv scf_type refs available
"mp2": mp2_type,
"mp2.5": mp_type,
"mp3": mp_type,
"lccd": cc_type,
"lccsd": cc_type,
"ccsd": cc_type,
"ccsd(t)": cc_type,
"olccd": cc_type,
}
corl_type = corl_natural_values[method]
natural_ref = {"conv": "pk", "df": "df", "cd": "cd"}
scf_type = inp["keywords"].get("scf_type", natural_ref[corl_type])
natural_values = {
"pk": "pk",
"direct": "pk",
"df": "df",
"mem_df": "df",
"disk_df": "df",
"cd": "cd"
}
scf_type = natural_values[scf_type]
atol = 1.0e-6
if driver == "hessian":
atol = 2.0e-6 # todo implement more elaborate e/g/h atol like at qcdb & qcng: https://github.com/qcdb/qcdb/blob/master/qcdb/tests/standard_suite_runner.py#L144-L152
chash = answer_hash(
system=subject.name(),
basis=basis,
fcae=fcae,
scf_type=scf_type,
reference=reference,
corl_type=corl_type,
)
# check all calcs against conventional reference to looser tolerance
atol_conv = 3.0e-4 # for df-ccsd. mp2 ok with 1.e-4
chash_conv = answer_hash(
system=subject.name(),
basis=basis,
fcae=fcae,
reference=reference,
corl_type="conv",
scf_type="pk",
)
ref_block_conv = std_suite[chash_conv]
# <<< Prepare Calculation and Call API >>>
driver_call = {
"energy": psi4.energy,
"gradient": psi4.gradient,
"hessian": psi4.hessian
}
psi4.set_options({
# reference generation conv crit
# "guess": "sad",
# "e_convergence": 10,
# "d_convergence": 9,
# "r_convergence": 9,
# "pcg_convergence": 9,
# runtime conv crit
"points": 5,
"fd_project": False,
})
extra_kwargs = inp["keywords"].pop("function_kwargs", {})
psi4.set_options(inp["keywords"])
if "error" in inp:
errtype, errmsg = inp["error"]
with pytest.raises(errtype) as e:
driver_call[driver](inp["call"], molecule=subject, **extra_kwargs)
assert errmsg in str(e.value), f"({errmsg}) not in ({e.value})"
return
ret, wfn = driver_call[driver](inp["call"],
molecule=subject,
return_wfn=True,
**extra_kwargs)
qc_module_out = "psi4-" + ("occ" if wfn.module() == "dfocc" else
wfn.module()) # returns "psi4-<module>"
# <<< Comparison Tests >>>
if qc_module_in != "psi4":
assert qc_module_out == qc_module_in, f"QC_MODULE used ({qc_module_in}) != requested ({qc_module_out})"
ref_block = std_suite[chash]
# qcvars
contractual_args = [
qc_module_in,
driver,
reference,
method,
corl_type,
fcae,
]
asserter_args = [
[psi4.core, wfn],
ref_block,
atol,
ref_block_conv,
atol_conv,
tnm,
]
def qcvar_assertions():
print("BLOCK", chash, contractual_args)
if method == "hf":
_asserter(asserter_args, contractual_args, contractual_hf)
elif method == "mp2":
_asserter(asserter_args, contractual_args, contractual_mp2)
elif method == "mp2.5":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_mp3)
_asserter(asserter_args, contractual_args, contractual_mp2p5)
elif method == "mp3":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_mp2p5)
_asserter(asserter_args, contractual_args, contractual_mp3)
elif method == "lccd":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_lccd)
elif method == "lccsd":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_lccsd)
elif method == "ccsd":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_ccsd)
elif method == "ccsd(t)":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_ccsd)
_asserter(asserter_args, contractual_args, contractual_ccsd_prt_pr)
elif method == "olccd":
_asserter(asserter_args, contractual_args, contractual_mp2)
_asserter(asserter_args, contractual_args, contractual_olccd)
if "wrong" in inp:
errmsg, reason = inp["wrong"]
with pytest.raises(AssertionError) as e:
qcvar_assertions()
# print("WRONG", errmsg, reason, str(e.value), "ENDW")
assert errmsg in str(e.value)
pytest.xfail(reason)
qcvar_assertions()
# aliases
_asserter(asserter_args, contractual_args, contractual_current)
# returns
tf, errmsg = compare_values(
ref_block[f"{method.upper()} TOTAL ENERGY"],
wfn.energy(),
tnm + " wfn",
atol=atol,
return_message=True,
quiet=True,
)
assert compare_values(ref_block[f"{method.upper()} TOTAL ENERGY"],
wfn.energy(),
tnm + " wfn",
atol=atol), errmsg
if driver == "energy":
assert compare_values(ref_block[f"{method.upper()} TOTAL ENERGY"], ret,
tnm + " return")
elif driver == "gradient":
assert compare_values(ref_block[f"{method.upper()} TOTAL GRADIENT"],
wfn.gradient().np,
tnm + " grad wfn",
atol=atol)
assert compare_values(ref_block[f"{method.upper()} TOTAL GRADIENT"],
ret.np,
tnm + " grad return",
atol=atol)
elif driver == "hessian":
tf, errmsg = compare_values(
ref_block[f"{method.upper()} TOTAL HESSIAN"],
wfn.hessian().np,
tnm + " hess wfn",
atol=atol,
return_message=True,
quiet=True)
assert compare_values(ref_block[f"{method.upper()} TOTAL HESSIAN"],
wfn.hessian().np,
tnm + " hess wfn",
atol=atol), errmsg
assert compare_values(ref_block[f"{method.upper()} TOTAL HESSIAN"],
wfn.hessian().np,
tnm + " hess wfn",
atol=atol)
assert compare_values(ref_block[f"{method.upper()} TOTAL GRADIENT"],
wfn.gradient().np,
tnm + " grad wfn",
atol=atol)
assert compare_values(ref_block[f"{method.upper()} TOTAL HESSIAN"],
ret.np,
tnm + " hess return",
atol=atol)
# generics
# yapf: disable
assert compare(ref_block["N BASIS FUNCTIONS"], wfn.nso(), tnm + " nbasis wfn"), f"nbasis {wfn.nso()} != {ref_block['N BASIS FUNCTIONS']}"
assert compare(ref_block["N MOLECULAR ORBITALS"], wfn.nmo(), tnm + " nmo wfn"), f"nmo {wfn.nmo()} != {ref_block['N MOLECULAR ORBITALS']}"
assert compare(ref_block["N ALPHA ELECTRONS"], wfn.nalpha(), tnm + " nalpha wfn"), f"nalpha {wfn.nalpha()} != {ref_block['N ALPHA ELECTRONS']}"
assert compare(ref_block["N BETA ELECTRONS"], wfn.nbeta(), tnm + " nbeta wfn"), f"nbeta {wfn.nbeta()} != {ref_block['N BETA ELECTRONS']}"
# psi4.core.set_memory(int(2e9), False)
psi4.core.set_output_file('output.dat', False)
# Memory for numpy in GB
numpy_memory = 2
mol = psi4.geometry("""
O
H 1 1.1
H 1 1.1 2 104
symmetry c1
""")
psi4.set_options({'basis': 'sto-3g',
'scf_type': 'pk',
'e_convergence': 1e-8,
'd_convergence': 1e-8})
print('\nStarting SCF and integral build...')
t = time.time()
# First compute SCF energy using Psi4
scf_e, wfn = psi4.energy('SCF', return_wfn=True)
# Grab data from wavfunction class
C = wfn.Ca()
ndocc = wfn.doccpi()[0]
nmo = wfn.nmo()
nvirt = nmo - ndocc
nDet_S = ndocc * nvirt * 2
self.T3onT2 = self.T3onT2 + np.einsum('ijab -> jiba', self.T3onT2)
## Contribution of disconnected T3*T1 terms to T2 equations via relax_t3t1ont2 function.
self.relax_t3t1ont2()
print('T3')
printtensor(self.T3)
if __name__ == '__main__':
mol = psi4.geometry("""
0 1
O
H 1 0.96
H 1 0.96 2 104.5
symmetry c1""")
mol.update_geometry()
psi4.set_options({
'basis': 'sto-3g',
'scf_type': 'pk',
'FCI': True,
'reference': 'rhf'
})
E, wfn = psi4.energy('detci', return_wfn=True)
CASCCSD(wfn)
print(E)
import psi4
psi4.set_output_file("output.dat", False)
# Benzene
mol = psi4.geometry("""
0 1
O
H 1 1.1
H 1 1.1 2 104
symmetry c1
""")
psi4.set_options({
"basis": "aug-cc-pVDZ",
"scf_type": "df",
"e_convergence": 1e-8
})
# Set tolerances
maxiter = 12
E_conv = 1.0E-6
D_conv = 1.0E-5
# Integral generation from Psi4's MintsHelper
wfn = psi4.core.Wavefunction.build(mol, psi4.core.get_global_option("BASIS"))
mints = psi4.core.MintsHelper(wfn.basisset())
S = mints.ao_overlap()
# Get nbf and ndocc for closed shell molecules
nbf = wfn.nso()
S 1 1.00
0.1831920 1.0000000
****
C 0
S 3 1.00
172.2560000 0.0617669
25.9109000 0.3587940
5.5333500 0.7007130
SP 2 1.00
3.6649800 -0.3958970 0.2364600
0.7705450 1.2158400 0.8606190
SP 1 1.00
0.1958570 1.0000000 1.0000000
****
[DZ]
spherical
****
H 0
S 3 1.00
19.2406000 0.0328280
2.8992000 0.2312080
0.6534000 0.8172380
S 1 1.00
0.1776000 1.0000000
****
""")
psi4.set_options({'d_convergence': 11, 'e_convergence': 11, 'scf_type': 'pk'})
scfenergy = psi4.energy('scf')
def test_geometric_hessian_rhf_outside_solver_psi4numpy():
psi4.core.set_output_file("output.dat", False)
mol = psi4.geometry(
"""
O
H 1 1.1
H 1 1.1 2 104
symmetry c1
"""
)
psi4.core.set_active_molecule(mol)
options = {
"BASIS": "STO-3G",
"SCF_TYPE": "PK",
"E_CONVERGENCE": 1e-10,
"D_CONVERGENCE": 1e-10,
}
psi4.set_options(options)
_, wfn = psi4.energy("SCF", return_wfn=True)
# Assuming C1 symmetry
occ = wfn.doccpi()[0]
nmo = wfn.nmo()
vir = nmo - occ
C = wfn.Ca_subset("AO", "ALL")
npC = np.asarray(C)
mints = psi4.core.MintsHelper(wfn.basisset())
H_ao = np.asarray(mints.ao_kinetic()) + np.asarray(mints.ao_potential())
# Update H, transform to MO basis
H = np.einsum("uj,vi,uv", npC, npC, H_ao)
# Integral generation from Psi4's MintsHelper
MO = np.asarray(mints.mo_eri(C, C, C, C))
# Physicist notation
MO = MO.swapaxes(1, 2)
F = H + 2.0 * np.einsum("pmqm->pq", MO[:, :occ, :, :occ])
F -= np.einsum("pmmq->pq", MO[:, :occ, :occ, :])
# Uncomment every `np.save` call to regenerate reference data.
# np.save(os.path.join(datadir, 'F.npy'), F)
F_ref = np.load(os.path.join(datadir, "F.npy"))
np.testing.assert_allclose(F, F_ref, rtol=0, atol=1.0e-10)
natoms = mol.natom()
cart = ["_X", "_Y", "_Z"]
oei_dict = {"S": "OVERLAP", "T": "KINETIC", "V": "POTENTIAL"}
deriv1_mat = {}
deriv1 = {}
# 1st Derivative of OEIs
for atom in range(natoms):
for key in oei_dict:
deriv1_mat[key + str(atom)] = mints.mo_oei_deriv1(oei_dict[key], atom, C, C)
for p in range(3):
map_key = key + str(atom) + cart[p]
deriv1[map_key] = np.asarray(deriv1_mat[key + str(atom)][p])
# np.save(os.path.join(datadir, f'{map_key}.npy'), deriv1[map_key])
deriv1_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv1[map_key], deriv1_ref, rtol=0, atol=1.0e-10)
# 1st Derivative of TEIs
for atom in range(natoms):
string = "TEI" + str(atom)
deriv1_mat[string] = mints.mo_tei_deriv1(atom, C, C, C, C)
for p in range(3):
map_key = string + cart[p]
deriv1[map_key] = np.asarray(deriv1_mat[string][p])
# np.save(os.path.join(datadir, f'{map_key}.npy'), deriv1[map_key])
deriv1_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv1[map_key], deriv1_ref, rtol=0, atol=1.0e-10)
Hes = {}
deriv2_mat = {}
deriv2 = {}
Hes["S"] = np.zeros((3 * natoms, 3 * natoms))
Hes["V"] = np.zeros((3 * natoms, 3 * natoms))
Hes["T"] = np.zeros((3 * natoms, 3 * natoms))
Hes["N"] = np.zeros((3 * natoms, 3 * natoms))
Hes["J"] = np.zeros((3 * natoms, 3 * natoms))
Hes["K"] = np.zeros((3 * natoms, 3 * natoms))
Hes["R"] = np.zeros((3 * natoms, 3 * natoms))
Hessian = np.zeros((3 * natoms, 3 * natoms))
Hes["N"] = np.asarray(mol.nuclear_repulsion_energy_deriv2())
psi4.core.print_out("\n\n")
Mat = psi4.core.Matrix.from_array(Hes["N"])
Mat.name = "NUCLEAR HESSIAN"
Mat.print_out()
# 2nd Derivative of OEIs
for atom1 in range(natoms):
for atom2 in range(atom1 + 1):
for key in oei_dict:
string = key + str(atom1) + str(atom2)
deriv2_mat[string] = mints.mo_oei_deriv2(oei_dict[key], atom1, atom2, C, C)
pq = 0
for p in range(3):
for q in range(3):
map_key = string + cart[p] + cart[q]
deriv2[map_key] = np.asarray(deriv2_mat[string][pq])
# np.save(os.path.join(datadir, f'{map_key}.npy'), deriv2[map_key])
deriv2_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(
deriv2[map_key], deriv2_ref, rtol=0, atol=1.0e-10
)
pq = pq + 1
row = 3 * atom1 + p
col = 3 * atom2 + q
if key == "S":
Hes[key][row][col] = -2.0 * np.einsum(
"ii,ii->", F[:occ, :occ], deriv2[map_key][:occ, :occ]
)
else:
Hes[key][row][col] = 2.0 * np.einsum(
"ii->", deriv2[map_key][:occ, :occ]
)
Hes[key][col][row] = Hes[key][row][col]
Hes[key][col][row] = Hes[key][row][col]
# np.save(os.path.join(datadir, f'Hes_{map_key}.npy'), Hes[key])
Hes_ref = np.load(os.path.join(datadir, f"Hes_{map_key}.npy"))
np.testing.assert_allclose(Hes[key], Hes_ref, rtol=0, atol=1.0e-10)
for key in Hes:
Mat = psi4.core.Matrix.from_array(Hes[key])
if key in oei_dict:
Mat.name = oei_dict[key] + " HESSIAN"
Mat.print_out()
psi4.core.print_out("\n")
# 2nd Derivative of TEIs
for atom1 in range(natoms):
for atom2 in range(atom1 + 1):
string = "TEI" + str(atom1) + str(atom2)
deriv2_mat[string] = mints.mo_tei_deriv2(atom1, atom2, C, C, C, C)
pq = 0
for p in range(3):
for q in range(3):
map_key = string + cart[p] + cart[q]
deriv2[map_key] = np.asarray(deriv2_mat[string][pq])
# np.save(os.path.join(datadir, f'{map_key}.npy'), deriv2[map_key])
deriv2_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv2[map_key], deriv2_ref, rtol=0, atol=1.0e-10)
pq = pq + 1
row = 3 * atom1 + p
col = 3 * atom2 + q
Hes["J"][row][col] = 2.0 * np.einsum(
"iijj->", deriv2[map_key][:occ, :occ, :occ, :occ]
)
Hes["K"][row][col] = -1.0 * np.einsum(
"ijij->", deriv2[map_key][:occ, :occ, :occ, :occ]
)
Hes["J"][col][row] = Hes["J"][row][col]
Hes["K"][col][row] = Hes["K"][row][col]
for map_key in ("J", "K"):
# np.save(os.path.join(datadir, f'Hes_{map_key}.npy'), Hes[map_key])
Hes_ref = np.load(os.path.join(datadir, f"Hes_{map_key}.npy"))
np.testing.assert_allclose(Hes[map_key], Hes_ref, rtol=0, atol=1.0e-10)
JMat = psi4.core.Matrix.from_array(Hes["J"])
KMat = psi4.core.Matrix.from_array(Hes["K"])
JMat.name = " COULOMB HESSIAN"
KMat.name = " EXCHANGE HESSIAN"
JMat.print_out()
KMat.print_out()
# Solve the CPHF equations here, G_aibj Ubj^x = Bai^x (Einstein summation),
# where G is the electronic hessian,
# G_aibj = delta_ij * delta_ab * epsilon_ij * epsilon_ab + 4 <ij|ab> - <ij|ba> - <ia|jb>,
# where epsilon_ij = epsilon_i - epsilon_j, (epsilon -> orbital energies),
# x refers to the perturbation, Ubj^x are the corresponsing CPHF coefficients
# and Bai^x = Sai^x * epsilon_ii - Fai^x + Smn^x * (2<am|in> - <am|ni>),
# where, S^x = del(S)/del(x), F^x = del(F)/del(x).
I_occ = np.diag(np.ones(occ))
I_vir = np.diag(np.ones(vir))
epsilon = np.asarray(wfn.epsilon_a())
eps_diag = epsilon[occ:].reshape(-1, 1) - epsilon[:occ]
# Build the electronic hessian G
G = 4 * MO[:occ, :occ, occ:, occ:]
G -= MO[:occ, :occ, occ:, occ:].swapaxes(2, 3)
G -= MO[:occ, occ:, :occ, occ:].swapaxes(1, 2)
G = G.swapaxes(1, 2)
G += np.einsum("ai,ij,ab->iajb", eps_diag, I_occ, I_vir)
# np.save(os.path.join(datadir, 'G.npy'), G)
G_ref = np.load(os.path.join(datadir, "G.npy"))
np.testing.assert_allclose(G, G_ref, rtol=0, atol=1.0e-10)
# Inverse of G
Ginv = np.linalg.inv(G.reshape(occ * vir, -1))
Ginv = Ginv.reshape(occ, vir, occ, vir)
B = {}
F_grad = {}
U = {}
# Build Fpq^x now
for atom in range(natoms):
for p in range(3):
key = str(atom) + cart[p]
F_grad[key] = deriv1["T" + key]
F_grad[key] += deriv1["V" + key]
F_grad[key] += 2.0 * np.einsum("pqmm->pq", deriv1["TEI" + key][:, :, :occ, :occ])
F_grad[key] -= 1.0 * np.einsum("pmmq->pq", deriv1["TEI" + key][:, :occ, :occ, :])
# np.save(os.path.join(datadir, f'F_grad_{key}.npy'), F_grad[key])
F_grad_ref = np.load(os.path.join(datadir, f"F_grad_{key}.npy"))
np.testing.assert_allclose(F_grad[key], F_grad_ref, rtol=0, atol=1.0e-10)
psi4.core.print_out("\n\n CPHF Coefficients:\n")
# Build Bai^x now
for atom in range(natoms):
for p in range(3):
key = str(atom) + cart[p]
B[key] = np.einsum("ai,ii->ai", deriv1["S" + key][occ:, :occ], F[:occ, :occ])
B[key] -= F_grad[key][occ:, :occ]
B[key] += 2.0 * np.einsum(
"amin,mn->ai", MO[occ:, :occ, :occ, :occ], deriv1["S" + key][:occ, :occ]
)
B[key] += -1.0 * np.einsum(
"amni,mn->ai", MO[occ:, :occ, :occ, :occ], deriv1["S" + key][:occ, :occ]
)
print(f"B[{key}]")
print(B[key])
# np.save(os.path.join(datadir, f'B_{key}.npy'), B[key])
B_ref = np.load(os.path.join(datadir, f"B_{key}.npy"))
np.testing.assert_allclose(B[key], B_ref, rtol=0, atol=1.0e-10)
# Compute U^x now: U_ai^x = G^(-1)_aibj * B_bj^x
U[key] = np.einsum("iajb,bj->ai", Ginv, B[key])
psi4.core.print_out("\n")
UMat = psi4.core.Matrix.from_array(U[key])
UMat.name = key
UMat.print_out()
# np.save(os.path.join(datadir, f'U_{key}.npy'), U[key])
U_ref = np.load(os.path.join(datadir, f"U_{key}.npy"))
np.testing.assert_allclose(U[key], U_ref, rtol=0, atol=1.0e-10)
# Build the response Hessian
for atom1 in range(natoms):
for atom2 in range(atom1 + 1):
for p in range(3):
for q in range(3):
key1 = str(atom1) + cart[p]
key2 = str(atom2) + cart[q]
key1S = "S" + key1
key2S = "S" + key2
r = 3 * atom1 + p
c = 3 * atom2 + q
Hes["R"][r][c] = -2.0 * np.einsum(
"ij,ij->", deriv1[key1S][:occ, :occ], F_grad[key2][:occ, :occ]
)
Hes["R"][r][c] -= 2.0 * np.einsum(
"ij,ij->", deriv1[key2S][:occ, :occ], F_grad[key1][:occ, :occ]
)
Hes["R"][r][c] += 4.0 * np.einsum(
"ii,mi,mi->",
F[:occ, :occ],
deriv1[key2S][:occ, :occ],
deriv1[key1S][:occ, :occ],
)
Hes["R"][r][c] += 4.0 * np.einsum(
"ij,mn,imjn->",
deriv1[key1S][:occ, :occ],
deriv1[key2S][:occ, :occ],
MO[:occ, :occ, :occ, :occ],
)
Hes["R"][r][c] -= 2.0 * np.einsum(
"ij,mn,imnj->",
deriv1[key1S][:occ, :occ],
deriv1[key2S][:occ, :occ],
MO[:occ, :occ, :occ, :occ],
)
Hes["R"][r][c] -= 4.0 * np.einsum("ai,ai->", U[key2], B[key1])
Hes["R"][c][r] = Hes["R"][r][c]
# np.save(os.path.join(datadir, 'Hes_R.npy'), Hes["R"])
Hes_ref = np.load(os.path.join(datadir, "Hes_R.npy"))
np.testing.assert_allclose(Hes["R"], Hes_ref, rtol=0, atol=1.0e-10)
Mat = psi4.core.Matrix.from_array(Hes["R"])
Mat.name = " RESPONSE HESSIAN"
Mat.print_out()
for key in Hes:
Hessian += Hes[key]
# print('deriv1_mat')
# print(deriv1_mat.keys())
# print('deriv1')
# print(deriv1.keys())
# print('deriv2_mat')
# print(deriv2_mat.keys())
# print('deriv2')
# print(deriv2.keys())
# print('B')
# print(B.keys())
# print('F_grad')
# print(F_grad.keys())
# print('U')
# print(U.keys())
# print('Hes')
# print(Hes.keys())
Mat = psi4.core.Matrix.from_array(Hessian)
Mat.name = " TOTAL HESSIAN"
Mat.print_out()
# pylint: disable=bad-whitespace
H_psi4 = psi4.core.Matrix.from_list(
[
[
7.613952269164418751e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-3.806976134297335168e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-3.806976134297410108e-02,
0.000000000000000000e00,
0.000000000000000000e00,
],
[
0.000000000000000000e00,
4.829053723748517601e-01,
0.000000000000000000e00,
0.000000000000000000e00,
-2.414526861845633920e-01,
1.589001558536450587e-01,
0.000000000000000000e00,
-2.414526861845646133e-01,
-1.589001558536444758e-01,
],
[
0.000000000000000000e00,
0.000000000000000000e00,
4.373449597848400039e-01,
0.000000000000000000e00,
7.344233774055003439e-02,
-2.186724798895446076e-01,
0.000000000000000000e00,
-7.344233774054893804e-02,
-2.186724798895475219e-01,
],
[
-3.806976134297335168e-02,
0.000000000000000000e00,
0.000000000000000000e00,
4.537741758645107149e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-7.307656243475501093e-03,
0.000000000000000000e00,
0.000000000000000000e00,
],
[
0.000000000000000000e00,
-2.414526861845633920e-01,
7.344233774055003439e-02,
0.000000000000000000e00,
2.578650065921952450e-01,
-1.161712467970963669e-01,
0.000000000000000000e00,
-1.641232040762596878e-02,
4.272890905654690846e-02,
],
[
0.000000000000000000e00,
1.589001558536450587e-01,
-2.186724798895446076e-01,
0.000000000000000000e00,
-1.161712467970963669e-01,
1.977519807685419462e-01,
0.000000000000000000e00,
-4.272890905654720684e-02,
2.092049912100946499e-02,
],
[
-3.806976134297410108e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-7.307656243475501093e-03,
0.000000000000000000e00,
0.000000000000000000e00,
4.537741758645268131e-02,
0.000000000000000000e00,
0.000000000000000000e00,
],
[
0.000000000000000000e00,
-2.414526861845646133e-01,
-7.344233774054893804e-02,
0.000000000000000000e00,
-1.641232040762596878e-02,
-4.272890905654720684e-02,
0.000000000000000000e00,
2.578650065921969103e-01,
1.161712467970957008e-01,
],
[
0.000000000000000000e00,
-1.589001558536444758e-01,
-2.186724798895475219e-01,
0.000000000000000000e00,
4.272890905654690846e-02,
2.092049912100946499e-02,
0.000000000000000000e00,
1.161712467970957008e-01,
1.977519807685442221e-01,
],
]
)
H_python_mat = psi4.core.Matrix.from_array(Hessian)
psi4.compare_matrices(H_psi4, H_python_mat, 10, "RHF-HESSIAN-TEST") # TEST
def test_erd():
"""erd/scf5"""
psi4.set_options({'integral_package': 'ERD'})
_test_scf5()
# O 0.0000000000 0.0000000000 2.3054658725
# H 1.7822044879 0.0000000000 -1.0289558751
# H -1.7822044879 0.0000000000 -1.0289558751
# C 0.0000000000 0.0000000000 0.0000000000
# symmetry c1
# """)
mol = psi4.geometry("""
O 0.000000000000 -0.143225816552 0.000000000000
H 1.638036840407 1.136548822547 -0.000000000000
H -1.638036840407 1.136548822547 -0.000000000000
units bohr
symmetry c1
""")
psi4.set_options({"SAVE_JK": True, 'scf_type': 'pk', 'd_convergence': 10})
e, wfn = psi4.energy("HF/sto-3g", return_wfn=True)
prod = AB_product_factory(wfn)
F_ako = prod.mFa.to_array()
C = prod.mCa.to_array()
Fmo = (C.T).dot(F_ao).dot(C)
F_ij = Fmo[prod.o, prod.o]
F_ab = Fmo[prod.v, prod.v]
print("F_ij: ", " x ".join(str(x) for x in F_ij.shape))
print("")
print("F_ab: ", " x ".join(str(x) for x in F_ab.shape))
Iiajb = prod.mints.mo_eri(prod.mCa_occ, prod.mCa_virt, prod.mCa_occ, prod.mCa_virt).to_array()
Iabji = prod.mints.mo_eri(prod.mCa_virt, prod.mCa_virt, prod.mCa_occ, prod.mCa_occ).to_array()
A = np.einsum("ab,ij->iajb", F_ab, np.eye(prod.nocc))
A -= np.einsum("ij,ab->iajb", F_ij, np.eye(prod.nvir))
def test_chk(datadir):
# run cc
psi4.set_memory('600MB')
psi4.core.set_output_file('output.dat', False)
psi4.set_options({'basis': 'cc-pVDZ',
'scf_type': 'pk',
'mp2_type': 'conv',
'freeze_core': 'false',
'e_convergence': 1e-8,
'd_convergence': 1e-8,
'r_convergence': 1e-8,
'diis': 8})
mol = psi4.geometry(moldict["H2"])
# pull ref wfn, psi4 is picky about strings
rhf_dir = str(datadir.join(f"ref_wfn.npy"))
rhf_wfn = psi4.core.Wavefunction.from_file(rhf_dir)
e_conv = 1e-8
r_conv = 1e-8
cc = pycc.ccwfn(rhf_wfn)
ecc = cc.solve_cc(e_conv, r_conv)
hbar = pycc.cchbar(cc)
cclambda = pycc.cclambda(cc, hbar)
lecc = cclambda.solve_lambda(e_conv, r_conv)
ccdensity = pycc.ccdensity(cc, cclambda)
# narrow Gaussian pulse
F_str = 0.001
sigma = 0.01
center = 0.05
V = gaussian_laser(F_str, 0, sigma, center=center)
# RTCC setup
h = 0.1
tf = 10
rtcc = pycc.rtcc(cc,cclambda,ccdensity,V,magnetic=True,kick='z')
# pull chk files for 0-5.1au
chk_file = datadir.join(f"chk_5.pk")
with open(chk_file,'rb') as cf:
chk = pk.load(cf)
# propagate to 10au
ODE = rk2(h)
y0 = chk['y']
ti = chk['time']
ofile = datadir.join(f"output.pk")
tfile = datadir.join(f"t_out.pk")
ret, ret_t = rtcc.propagate(ODE, y0, tf, ti=ti, ref=False, chk=True, tchk=1,
ofile=ofile, tfile=tfile, k=2)
# reference is "full" propagation (0-10au)
refp_file = datadir.join(f"output_full.pk")
with open(refp_file,'rb') as pf:
ref_p = pk.load(pf)
reft_file = datadir.join(f"t_out_full.pk")
with open(reft_file,'rb') as ampf:
ref_t = pk.load(ampf)
# check properties
pchk = ['ecc','mu_x','mu_y','mu_z','m_x','m_y','m_z']
for k in ref_p.keys():
for p in pchk:
assert np.allclose(ret[k][p],ref_p[k][p])
# check amplitudes
tchk = ['t1','t2','l1','l2']
for k in ref_t.keys():
for t in tchk:
assert np.allclose(ret_t[k][t],ref_t[k][t])
H 45.508000 40.786000 39.175000
H 43.151000 37.062000 37.180000
H 40.929000 35.954000 37.704000
H 39.378000 37.062000 39.158000
H 40.246000 38.878000 40.859000
symmetry c1
no_com
noreorient
""")
nroots = 3
psi4.set_options({
"basis": "6-31G*",
"freeze_core": "true",
"roots_per_irrep": [nroots],
"pe": "true",
"ints_tolerance": 2.5e-11,
"puream": "true",
})
psi4.set_module_options("pe", {
"potfile": "nilered_in_blg_1000WAT.pot",
"maxiter": 200
})
psi4.set_module_options("ccenergy", {"cachelevel": 0})
psi4.set_module_options("cclambda", {"r_convergence": 1e-3, "cachelevel": 0})
psi4.set_module_options("cceom", {
"cachelevel": 0,
"r_convergence": 1e-3,
def test_rtcc_water_cc_pvdz():
"""H2O cc-pVDZ"""
psi4.set_memory('2 GiB')
psi4.core.set_output_file('output.dat', False)
psi4.set_options({
'basis': 'cc-pVDZ',
'scf_type': 'pk',
'mp2_type': 'conv',
'freeze_core': 'false',
'e_convergence': 1e-13,
'd_convergence': 1e-13,
'r_convergence': 1e-13,
'diis': 1
})
mol = psi4.geometry(moldict["H2O"])
rhf_e, rhf_wfn = psi4.energy('SCF', return_wfn=True)
e_conv = 1e-13
r_conv = 1e-13
cc = pycc.ccwfn(rhf_wfn)
ecc = cc.solve_cc(e_conv, r_conv)
hbar = pycc.cchbar(cc)
cclambda = pycc.cclambda(cc, hbar)
lecc = cclambda.solve_lambda(e_conv, r_conv)
ccdensity = pycc.ccdensity(cc, cclambda)
# Gaussian pulse (a.u.)
F_str = 0.01
omega = 0
sigma = 0.01
center = 0.05
V = gaussian_laser(F_str, omega, sigma, center)
# RT-CC Setup
t0 = 0
tf = 1
h = 0.01
t = t0
rtcc = pycc.rtcc(cc, cclambda, ccdensity, V)
y0 = rtcc.collect_amps(cc.t1, cc.t2, cclambda.l1,
cclambda.l2).astype('complex128')
y = y0
# Setting for the adaptive integrator
maxiter = 10
yconv = 1e-7
ODE = ck(maxiter, yconv)
t1, t2, l1, l2 = rtcc.extract_amps(y0)
mu0_x, mu0_y, mu0_z = rtcc.dipole(t1, t2, l1, l2)
ecc0 = rtcc.lagrangian(t0, t1, t2, l1, l2)
# For saving data at each time step.
"""
dip_x = []
dip_y = []
dip_z = []
time_points = []
dip_x.append(mu0_x)
dip_y.append(mu0_y)
dip_z.append(mu0_z)
time_points.append(t)
"""
while t < tf:
(y, h_old, h) = ODE(rtcc.f, t, y, h)
t += h_old
t1, t2, l1, l2 = rtcc.extract_amps(y)
mu_x, mu_y, mu_z = rtcc.dipole(t1, t2, l1, l2)
ecc = rtcc.lagrangian(t, t1, t2, l1, l2)
"""
dip_x.append(mu_x)
dip_y.append(mu_y)
dip_z.append(mu_z)
time_points.append(t)
"""
print(mu_z)
mu_z_ref = -0.34894577
assert (abs(mu_z_ref - mu_z.real) < 1e-3)
def test_simint():
"""simint/scf5"""
psi4.set_options({'integral_package': 'simint'})
_test_scf5()
def test_geometric_hessian_rhf_right_hand_side():
mol = molecules.molecule_physicists_water_sto3g()
mol.reset_point_group("c1")
mol.update_geometry()
psi4.core.set_active_molecule(mol)
options = {
"BASIS": "STO-3G",
"SCF_TYPE": "PK",
"E_CONVERGENCE": 1e-10,
"D_CONVERGENCE": 1e-10,
}
psi4.set_options(options)
_, wfn = psi4.energy("hf", return_wfn=True)
occupations = occupations_from_psi4wfn(wfn)
nocc, nvir, _, _ = occupations
norb = nocc + nvir
o = slice(0, nocc)
v = slice(nocc, norb)
C = wfn.Ca_subset("AO", "ALL")
npC = np.asarray(C)
mints = psi4.core.MintsHelper(wfn)
T = np.asarray(mints.ao_kinetic())
V = np.asarray(mints.ao_potential())
H_ao = T + V
H = np.einsum("up,vq,uv->pq", npC, npC, H_ao)
MO = np.asarray(mints.mo_eri(C, C, C, C))
F = H + 2.0 * np.einsum("pqii->pq", MO[:, :, o, o])
F -= np.einsum("piqi->pq", MO[:, o, :, o])
F_ref = np.load(os.path.join(datadir, "F.npy"))
np.testing.assert_allclose(F, F_ref, rtol=0, atol=1.0e-10)
natoms = mol.natom()
cart = ["_X", "_Y", "_Z"]
oei_dict = {"S": "OVERLAP", "T": "KINETIC", "V": "POTENTIAL"}
deriv1 = dict()
# 1st Derivative of OEIs
for atom in range(natoms):
for key in oei_dict:
deriv1_mat = mints.mo_oei_deriv1(oei_dict[key], atom, C, C)
for p in range(3):
map_key = key + str(atom) + cart[p]
deriv1[map_key] = np.asarray(deriv1_mat[p])
deriv1_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv1[map_key], deriv1_ref, rtol=0, atol=1.0e-10)
# 1st Derivative of TEIs
for atom in range(natoms):
string = "TEI" + str(atom)
deriv1_mat = mints.mo_tei_deriv1(atom, C, C, C, C)
for p in range(3):
map_key = string + cart[p]
deriv1[map_key] = np.asarray(deriv1_mat[p])
deriv1_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv1[map_key], deriv1_ref, rtol=0, atol=1.0e-10)
# B_ia^x = S_ia^x * epsilon_ii - F_ia^x + S_mn^x * [2(ia|mn) - (in|ma)]
F_grad = dict()
B = dict()
# Build F_pq^x now
for atom in range(natoms):
for p in range(3):
key = str(atom) + cart[p]
F_grad[key] = deriv1["T" + key]
F_grad[key] += deriv1["V" + key]
F_grad[key] += 2.0 * np.einsum("pqmm->pq", deriv1["TEI" + key][:, :, o, o])
F_grad[key] -= 1.0 * np.einsum("pmmq->pq", deriv1["TEI" + key][:, o, o, :])
F_grad_ref = np.load(os.path.join(datadir, f"F_grad_{key}.npy"))
np.testing.assert_allclose(F_grad[key], F_grad_ref, rtol=0, atol=1.0e-10)
# Build B_ia^x now
for atom in range(natoms):
for p in range(3):
key = str(atom) + cart[p]
B[key] = np.einsum("ia,ii->ia", deriv1["S" + key][o, v], F[o, o])
B[key] -= F_grad[key][o, v]
B[key] += 2.0 * np.einsum("iamn,mn->ia", MO[o, v, o, o], deriv1["S" + key][o, o])
B[key] += -1.0 * np.einsum("inma,mn->ia", MO[o, o, o, v], deriv1["S" + key][o, o])
B_ref = np.load(os.path.join(datadir, f"B_{key}.npy"))
np.testing.assert_allclose(B[key], B_ref.T, rtol=0, atol=1.0e-10)
from pyresponse.integrals import _form_rhs_geometric
B_func = _form_rhs_geometric(npC, occupations, natoms, MO, mints)
assert B_func.keys() == B.keys()
for k in B_func:
np.testing.assert_allclose(B_func[k], B[k], rtol=0, atol=1.0e-12)
return B_func
#! that symmetry of the Molecule observes the basis assignment to atoms.
# cc-pvdz aug-cc-pvdz
# BASIS H 5/ 5 C 14/15 H +4/ 4 C +9/10
# RIFIT H 14/15 C 56/66 H +9/10 C +16/20
# JKFIT H 23/25 C 70/81 H +9/10 C +16/20
mymol = psi4.geometry("""
C 0.0 0.0 0.0
O 1.4 0.0 0.0
H_r -0.5 -0.7 0.0
H_l -0.5 0.7 0.0
""")
psi4.set_options({'basis': 'cc-pvdz'})
print('[1] <<< uniform cc-pVDZ >>>')
wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS'))
psi4.compare_strings('CC-PVDZ', psi4.core.get_global_option('BASIS'), 'name') #TEST
psi4.compare_integers(38, wert.nbf(), 'nbf()') #TEST
psi4.compare_integers(40, wert.nao(), 'nao()') #TEST
psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST
psi4.compare_strings('CC-PVDZ', wert.name(), 'callby') #TEST
psi4.compare_strings('CC-PVDZ', wert.blend(), 'blend') #TEST
mymol.print_out()
print('[2] <<< RIFIT (default) >>>')
wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS'))
psi4.compare_integers(140, wert.nbf(), 'nbf()') #TEST
def test_atomic_polar_tensor_rhf():
mol = molecules.molecule_physicists_water_sto3g()
mol.reset_point_group("c1")
mol.update_geometry()
psi4.core.set_active_molecule(mol)
options = {
"BASIS": "STO-3G",
"SCF_TYPE": "PK",
"E_CONVERGENCE": 1e-10,
"D_CONVERGENCE": 1e-10,
}
psi4.set_options(options)
_, wfn = psi4.energy("hf", return_wfn=True)
mints = psi4.core.MintsHelper(wfn)
C = mocoeffs_from_psi4wfn(wfn)
E = moenergies_from_psi4wfn(wfn)
occupations = occupations_from_psi4wfn(wfn)
nocc, nvir, _, _ = occupations
norb = nocc + nvir
# electric perturbation part
ao2mo = AO2MO(C, occupations, I=np.asarray(mints.ao_eri()))
ao2mo.perform_rhf_full()
solver = ExactInv(C, E, occupations)
solver.tei_mo = ao2mo.tei_mo
solver.tei_mo_type = AO2MOTransformationType.full
driver = CPHF(solver)
operator_diplen = Operator(
label="dipole", is_imaginary=False, is_spin_dependent=False, triplet=False
)
# integrals_diplen_ao = self.pyscfmol.intor('cint1e_r_sph', comp=3)
M = np.stack([np.asarray(Mc) for Mc in mints.ao_dipole()])
operator_diplen.ao_integrals = M
driver.add_operator(operator_diplen)
# geometric perturbation part
operator_geometric = Operator(
label="nuclear", is_imaginary=False, is_spin_dependent=False, triplet=False
)
operator_geometric.form_rhs_geometric(C, occupations, mol.natom(), solver.tei_mo[0], mints)
print(operator_geometric.label)
print(operator_geometric.mo_integrals_ai_alph)
print(operator_diplen.label)
print(operator_diplen.mo_integrals_ai_alph)
# hack for dim check in solver
operator_geometric.ao_integrals = np.zeros((3 * mol.natom(), M.shape[1], M.shape[2]))
# bypass driver's call to form_rhs
driver.solver.operators.append(operator_geometric)
driver.run(
hamiltonian=Hamiltonian.RPA,
spin=Spin.singlet,
program=Program.Psi4,
program_obj=wfn,
)
print(driver.results[0])
print(driver.results[0].T)
print(driver.results[0] - driver.results[0].T)
print(operator_geometric.rspvecs_alph[0])
# Nuclear contribution to dipole gradient
# Electronic contributions to static part of dipole gradient
# Reorthonormalization part of dipole gradient
# Static contribution to dipole gradient
# Relaxation part of dipole gradient
# Total dipole gradient - TRAROT
print("Nuclear contribution to dipole gradient")
natom = mol.natom()
Z = np.asarray([mol.Z(i) for i in range(natom)])
nuclear_contrib = np.concatenate([np.diag(Z.take(3 * [i])) for i in range(natom)])
print(nuclear_contrib)
return locals()
def test_unrestricted_RPA_C1():
ch2 = psi4.geometry("""
0 3
c
h 1 1.0
h 1 1.0 2 125.0
symmetry c1
""")
psi4.set_options({"scf_type": "pk", 'reference': 'UHF', 'save_jk': True})
e, wfn = psi4.energy("hf/cc-pvdz", molecule=ch2, return_wfn=True)
A_ref, B_ref = build_UHF_AB_C1(wfn)
nI, nA, _, _ = A_ref['IAJB'].shape
nIA = nI * nA
ni, na, _, _ = A_ref['iajb'].shape
nia = ni * na
P_ref = {k: A_ref[k] + B_ref[k] for k in A_ref.keys()}
M_ref = {k: A_ref[k] - B_ref[k] for k in A_ref.keys()}
eng = TDUSCFEngine(wfn, ptype='rpa')
X_jb = [
psi4.core.Matrix.from_array(v.reshape((ni, na)))
for v in tuple(np.eye(nia).T)
]
zero_jb = [psi4.core.Matrix(ni, na) for x in range(nIA)]
X_JB = [
psi4.core.Matrix.from_array(v.reshape((nI, nA)))
for v in tuple(np.eye(nIA).T)
]
zero_JB = [psi4.core.Matrix(nI, nA) for x in range(nia)]
# Guess Identity:
# X_I0 X_0I = X_I0 X_0I
# [ I{nOV x nOV} | 0{nOV x nov}] = [ X{KC,JB} | 0{KC, jb}]
# [ 0{nov x nOV} | I{nov x nov}] [ 0{kc,JB} | X{kc, jb}]
# Products:
# [ A+/-B{IA, KC} A+/-B{IA, kc}] [ I{KC, JB} | 0{KC,jb}] = [A+/-B x X_I0] = [ (A+/-B)_IAJB, (A+/-B)_iaJB]
# [ A+/-B{ia, KC} A+/-B{ia, kc}] [ O{kc, JB} | X{kc,jb}] [A+/-B x X_0I] = [ (A+/-B)_IAjb, (A+/-B)_iajb]
X_I0 = [[x, zero] for x, zero in zip(X_JB, zero_jb)]
X_0I = [[zero, x] for zero, x in zip(zero_JB, X_jb)]
Px_I0, Mx_I0 = eng.compute_products(X_I0)[:-1]
Px_0I, Mx_0I = eng.compute_products(X_0I)[:-1]
P_IAJB_test = np.column_stack([x[0].to_array().flatten() for x in Px_I0])
assert compare_arrays(P_ref['IAJB'].reshape(nIA, nIA), P_IAJB_test, 8,
"A_IAJB")
M_IAJB_test = np.column_stack([x[0].to_array().flatten() for x in Mx_I0])
assert compare_arrays(M_ref['IAJB'].reshape(nIA, nIA), M_IAJB_test, 8,
"A_IAJB")
P_iaJB_test = np.column_stack([x[1].to_array().flatten() for x in Px_I0])
assert compare_arrays(P_ref['iaJB'].reshape(nia, nIA), P_iaJB_test, 8,
"P_iaJB")
M_iaJB_test = np.column_stack([x[1].to_array().flatten() for x in Mx_I0])
assert compare_arrays(M_ref['iaJB'].reshape(nia, nIA), M_iaJB_test, 8,
"M_iaJB")
P_IAjb_test = np.column_stack([x[0].to_array().flatten() for x in Px_0I])
assert compare_arrays(P_ref['IAjb'].reshape(nIA, nia), P_IAjb_test, 8,
"P_IAjb")
M_IAjb_test = np.column_stack([x[0].to_array().flatten() for x in Mx_0I])
assert compare_arrays(M_ref['IAjb'].reshape(nIA, nia), M_IAjb_test, 8,
"M_IAjb")
P_iajb_test = np.column_stack([x[1].to_array().flatten() for x in Px_0I])
assert compare_arrays(P_ref['iajb'].reshape(nia, nia), P_iajb_test, 8,
"P_iajb")
M_iajb_test = np.column_stack([x[1].to_array().flatten() for x in Mx_0I])
assert compare_arrays(M_ref['iajb'].reshape(nia, nia), M_iajb_test, 8,
"M_iajb")
def test_geometric_hessian_rhf_outside_solver_chemists():
psi4.core.set_output_file("output2.dat", False)
mol = molecules.molecule_physicists_water_sto3g()
mol.reset_point_group("c1")
mol.update_geometry()
psi4.core.set_active_molecule(mol)
options = {
"BASIS": "STO-3G",
"SCF_TYPE": "PK",
"E_CONVERGENCE": 1e-10,
"D_CONVERGENCE": 1e-10,
}
psi4.set_options(options)
_, wfn = psi4.energy("hf", return_wfn=True)
norb = wfn.nmo()
nocc = wfn.nalpha()
nvir = norb - nocc
o = slice(0, nocc)
v = slice(nocc, norb)
C = wfn.Ca_subset("AO", "ALL")
npC = np.asarray(C)
mints = psi4.core.MintsHelper(wfn)
T = np.asarray(mints.ao_kinetic())
V = np.asarray(mints.ao_potential())
H_ao = T + V
H = np.einsum("up,vq,uv->pq", npC, npC, H_ao)
MO = np.asarray(mints.mo_eri(C, C, C, C))
F = H + 2.0 * np.einsum("pqii->pq", MO[:, :, o, o])
F -= np.einsum("piqi->pq", MO[:, o, :, o])
F_ref = np.load(os.path.join(datadir, "F.npy"))
np.testing.assert_allclose(F, F_ref, rtol=0, atol=1.0e-10)
natoms = mol.natom()
cart = ["_X", "_Y", "_Z"]
oei_dict = {"S": "OVERLAP", "T": "KINETIC", "V": "POTENTIAL"}
deriv1_mat = {}
deriv1 = {}
# 1st Derivative of OEIs
for atom in range(natoms):
for key in oei_dict:
deriv1_mat[key + str(atom)] = mints.mo_oei_deriv1(oei_dict[key], atom, C, C)
for p in range(3):
map_key = key + str(atom) + cart[p]
deriv1[map_key] = np.asarray(deriv1_mat[key + str(atom)][p])
deriv1_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv1[map_key], deriv1_ref, rtol=0, atol=1.0e-10)
# 1st Derivative of TEIs
for atom in range(natoms):
string = "TEI" + str(atom)
deriv1_mat[string] = mints.mo_tei_deriv1(atom, C, C, C, C)
for p in range(3):
map_key = string + cart[p]
deriv1[map_key] = np.asarray(deriv1_mat[string][p])
deriv1_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv1[map_key], deriv1_ref, rtol=0, atol=1.0e-10)
Hes = {}
deriv2_mat = {}
deriv2 = {}
Hes["S"] = np.zeros((3 * natoms, 3 * natoms))
Hes["V"] = np.zeros((3 * natoms, 3 * natoms))
Hes["T"] = np.zeros((3 * natoms, 3 * natoms))
Hes["N"] = np.zeros((3 * natoms, 3 * natoms))
Hes["J"] = np.zeros((3 * natoms, 3 * natoms))
Hes["K"] = np.zeros((3 * natoms, 3 * natoms))
Hes["R"] = np.zeros((3 * natoms, 3 * natoms))
Hessian = np.zeros((3 * natoms, 3 * natoms))
Hes["N"] = np.asarray(mol.nuclear_repulsion_energy_deriv2())
psi4.core.print_out("\n\n")
Mat = psi4.core.Matrix.from_array(Hes["N"])
Mat.name = "NUCLEAR HESSIAN"
Mat.print_out()
# 2nd Derivative of OEIs
for atom1 in range(natoms):
for atom2 in range(atom1 + 1):
for key in oei_dict:
string = key + str(atom1) + str(atom2)
deriv2_mat[string] = mints.mo_oei_deriv2(oei_dict[key], atom1, atom2, C, C)
pq = 0
for p in range(3):
for q in range(3):
map_key = string + cart[p] + cart[q]
deriv2[map_key] = np.asarray(deriv2_mat[string][pq])
deriv2_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(
deriv2[map_key], deriv2_ref, rtol=0, atol=1.0e-10
)
pq = pq + 1
row = 3 * atom1 + p
col = 3 * atom2 + q
if key == "S":
Hes[key][row][col] = -2.0 * np.einsum(
"ii,ii->", F[o, o], deriv2[map_key][o, o]
)
else:
Hes[key][row][col] = 2.0 * np.einsum("ii->", deriv2[map_key][o, o])
Hes[key][col][row] = Hes[key][row][col]
Hes[key][col][row] = Hes[key][row][col]
Hes_ref = np.load(os.path.join(datadir, f"Hes_{map_key}.npy"))
np.testing.assert_allclose(Hes[key], Hes_ref, rtol=0, atol=1.0e-10)
for key in Hes:
Mat = psi4.core.Matrix.from_array(Hes[key])
if key in oei_dict:
Mat.name = oei_dict[key] + " HESSIAN"
Mat.print_out()
psi4.core.print_out("\n")
# 2nd Derivative of TEIs
for atom1 in range(natoms):
for atom2 in range(atom1 + 1):
string = "TEI" + str(atom1) + str(atom2)
deriv2_mat[string] = mints.mo_tei_deriv2(atom1, atom2, C, C, C, C)
pq = 0
for p in range(3):
for q in range(3):
map_key = string + cart[p] + cart[q]
deriv2[map_key] = np.asarray(deriv2_mat[string][pq])
deriv2_ref = np.load(os.path.join(datadir, f"{map_key}.npy"))
np.testing.assert_allclose(deriv2[map_key], deriv2_ref, rtol=0, atol=1.0e-10)
pq = pq + 1
row = 3 * atom1 + p
col = 3 * atom2 + q
Hes["J"][row][col] = 2.0 * np.einsum("iijj->", deriv2[map_key][o, o, o, o])
Hes["K"][row][col] = -1.0 * np.einsum("ijij->", deriv2[map_key][o, o, o, o])
Hes["J"][col][row] = Hes["J"][row][col]
Hes["K"][col][row] = Hes["K"][row][col]
for map_key in ("J", "K"):
Hes_ref = np.load(os.path.join(datadir, f"Hes_{map_key}.npy"))
np.testing.assert_allclose(Hes[map_key], Hes_ref, rtol=0, atol=1.0e-10)
JMat = psi4.core.Matrix.from_array(Hes["J"])
KMat = psi4.core.Matrix.from_array(Hes["K"])
JMat.name = " COULOMB HESSIAN"
KMat.name = " EXCHANGE HESSIAN"
JMat.print_out()
KMat.print_out()
# Solve the CPHF equations here, G_iajb U_jb^x = B_ia^x (Einstein summation),
# where G is the electronic hessian,
# G_iajb = delta_ij * delta_ab * epsilon_ij * epsilon_ab + 4(ia|jb) - (ij|ab) - (ib|ja),
# where epsilon_ij = epsilon_i - epsilon_j, (epsilon -> orbital energies),
# x refers to the perturbation, U_jb^x are the corresponsing CPHF coefficients
# and B_ia^x = S_ia^x * epsilon_ii - F_ia^x + S_mn^x * [2(ia|mn) - (in|ma)],
# where S^x = del(S)/del(x), F^x = del(F)/del(x).
I_occ = np.diag(np.ones(nocc))
I_vir = np.diag(np.ones(nvir))
epsilon = np.asarray(wfn.epsilon_a())
eps_diag = epsilon[v].reshape(-1, 1) - epsilon[o]
# Build the electronic hessian G
G = 4 * MO[o, v, o, v]
G -= MO[o, o, v, v].swapaxes(1, 2)
G -= MO[o, v, o, v].swapaxes(1, 3)
G += np.einsum("ai,ij,ab->iajb", eps_diag, I_occ, I_vir)
G_ref = np.load(os.path.join(datadir, "G.npy"))
np.testing.assert_allclose(G, G_ref, rtol=0, atol=1.0e-10)
# Inverse of G
Ginv = np.linalg.inv(G.reshape(nocc * nvir, -1))
Ginv = Ginv.reshape(nocc, nvir, nocc, nvir)
B = {}
F_grad = {}
U = {}
# Build F_pq^x now
for atom in range(natoms):
for p in range(3):
key = str(atom) + cart[p]
F_grad[key] = deriv1["T" + key]
F_grad[key] += deriv1["V" + key]
F_grad[key] += 2.0 * np.einsum("pqmm->pq", deriv1["TEI" + key][:, :, o, o])
F_grad[key] -= 1.0 * np.einsum("pmmq->pq", deriv1["TEI" + key][:, o, o, :])
F_grad_ref = np.load(os.path.join(datadir, f"F_grad_{key}.npy"))
np.testing.assert_allclose(F_grad[key], F_grad_ref, rtol=0, atol=1.0e-10)
psi4.core.print_out("\n\n CPHF Coefficients:\n")
# Build B_ia^x now
for atom in range(natoms):
for p in range(3):
key = str(atom) + cart[p]
B[key] = np.einsum("ia,ii->ia", deriv1["S" + key][o, v], F[o, o])
B[key] -= F_grad[key][o, v]
B[key] += 2.0 * np.einsum("iamn,mn->ia", MO[o, v, o, o], deriv1["S" + key][o, o])
B[key] += -1.0 * np.einsum("inma,mn->ia", MO[o, o, o, v], deriv1["S" + key][o, o])
print(f"B[{key}]")
print(B[key])
B_ref = np.load(os.path.join(datadir, f"B_{key}.npy"))
np.testing.assert_allclose(B[key], B_ref.T, rtol=0, atol=1.0e-10)
# Compute U^x now: U_ia^x = G^(-1)_iajb * B_jb^x
U[key] = np.einsum("iajb,jb->ia", Ginv, B[key])
psi4.core.print_out("\n")
UMat = psi4.core.Matrix.from_array(U[key])
UMat.name = key
UMat.print_out()
U_ref = np.load(os.path.join(datadir, f"U_{key}.npy"))
np.testing.assert_allclose(U[key], U_ref.T, rtol=0, atol=1.0e-10)
# Build the response Hessian
for atom1 in range(natoms):
for atom2 in range(atom1 + 1):
for p in range(3):
for q in range(3):
key1 = str(atom1) + cart[p]
key2 = str(atom2) + cart[q]
key1S = "S" + key1
key2S = "S" + key2
r = 3 * atom1 + p
c = 3 * atom2 + q
Hes["R"][r][c] = -2.0 * np.einsum(
"ij,ij->", deriv1[key1S][o, o], F_grad[key2][o, o]
)
Hes["R"][r][c] -= 2.0 * np.einsum(
"ij,ij->", deriv1[key2S][o, o], F_grad[key1][o, o]
)
Hes["R"][r][c] += 4.0 * np.einsum(
"ii,mi,mi->", F[o, o], deriv1[key2S][o, o], deriv1[key1S][o, o]
)
Hes["R"][r][c] += 4.0 * np.einsum(
"ij,mn,ijmn->",
deriv1[key1S][o, o],
deriv1[key2S][o, o],
MO[o, o, o, o],
)
Hes["R"][r][c] -= 2.0 * np.einsum(
"ij,mn,inmj->",
deriv1[key1S][o, o],
deriv1[key2S][o, o],
MO[o, o, o, o],
)
Hes["R"][r][c] -= 4.0 * np.einsum("ia,ia->", U[key2], B[key1])
Hes["R"][c][r] = Hes["R"][r][c]
Hes_ref = np.load(os.path.join(datadir, "Hes_R.npy"))
np.testing.assert_allclose(Hes["R"], Hes_ref, rtol=0, atol=1.0e-10)
Mat = psi4.core.Matrix.from_array(Hes["R"])
Mat.name = " RESPONSE HESSIAN"
Mat.print_out()
for key in Hes:
Hessian += Hes[key]
# print('deriv1_mat')
# print(deriv1_mat.keys())
# print('deriv1')
# print(deriv1.keys())
# print('deriv2_mat')
# print(deriv2_mat.keys())
# print('deriv2')
# print(deriv2.keys())
# print('B')
# print(B.keys())
# print('F_grad')
# print(F_grad.keys())
# print('U')
# print(U.keys())
# print('Hes')
# print(Hes.keys())
Mat = psi4.core.Matrix.from_array(Hessian)
Mat.name = " TOTAL HESSIAN"
Mat.print_out()
# pylint: disable=bad-whitespace
H_psi4 = psi4.core.Matrix.from_list(
[
[
7.613952269164418751e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-3.806976134297335168e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-3.806976134297410108e-02,
0.000000000000000000e00,
0.000000000000000000e00,
],
[
0.000000000000000000e00,
4.829053723748517601e-01,
0.000000000000000000e00,
0.000000000000000000e00,
-2.414526861845633920e-01,
1.589001558536450587e-01,
0.000000000000000000e00,
-2.414526861845646133e-01,
-1.589001558536444758e-01,
],
[
0.000000000000000000e00,
0.000000000000000000e00,
4.373449597848400039e-01,
0.000000000000000000e00,
7.344233774055003439e-02,
-2.186724798895446076e-01,
0.000000000000000000e00,
-7.344233774054893804e-02,
-2.186724798895475219e-01,
],
[
-3.806976134297335168e-02,
0.000000000000000000e00,
0.000000000000000000e00,
4.537741758645107149e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-7.307656243475501093e-03,
0.000000000000000000e00,
0.000000000000000000e00,
],
[
0.000000000000000000e00,
-2.414526861845633920e-01,
7.344233774055003439e-02,
0.000000000000000000e00,
2.578650065921952450e-01,
-1.161712467970963669e-01,
0.000000000000000000e00,
-1.641232040762596878e-02,
4.272890905654690846e-02,
],
[
0.000000000000000000e00,
1.589001558536450587e-01,
-2.186724798895446076e-01,
0.000000000000000000e00,
-1.161712467970963669e-01,
1.977519807685419462e-01,
0.000000000000000000e00,
-4.272890905654720684e-02,
2.092049912100946499e-02,
],
[
-3.806976134297410108e-02,
0.000000000000000000e00,
0.000000000000000000e00,
-7.307656243475501093e-03,
0.000000000000000000e00,
0.000000000000000000e00,
4.537741758645268131e-02,
0.000000000000000000e00,
0.000000000000000000e00,
],
[
0.000000000000000000e00,
-2.414526861845646133e-01,
-7.344233774054893804e-02,
0.000000000000000000e00,
-1.641232040762596878e-02,
-4.272890905654720684e-02,
0.000000000000000000e00,
2.578650065921969103e-01,
1.161712467970957008e-01,
],
[
0.000000000000000000e00,
-1.589001558536444758e-01,
-2.186724798895475219e-01,
0.000000000000000000e00,
4.272890905654690846e-02,
2.092049912100946499e-02,
0.000000000000000000e00,
1.161712467970957008e-01,
1.977519807685442221e-01,
],
]
)
H_python_mat = psi4.core.Matrix.from_array(Hessian)
psi4.compare_matrices(H_psi4, H_python_mat, 10, "RHF-HESSIAN-TEST") # TEST
# Memory for Psi4 in GB
psi4.core.set_memory(int(2e9), False)
psi4.core.set_output_file('output.dat', False)
# Memory for numpy in GB
numpy_memory = 2
mol = psi4.geometry("""
O
H 1 1.1
H 1 1.1 2 104
symmetry c1
""")
# Set some options
psi4.set_options({"basis": "cc-pvdz", "scf_type": "pk", "e_convergence": 1e-8})
# Set defaults
maxiter = 40
E_conv = 1.0E-8
D_conv = 1.0E-3
# Integral generation from Psi4's MintsHelper
wfn = psi4.core.Wavefunction.build(mol, psi4.core.get_global_option('BASIS'))
t = time.time()
mints = psi4.core.MintsHelper(wfn.basisset())
S = np.asarray(mints.ao_overlap())
# Get nbf and ndocc for closed shell molecules
nbf = wfn.nso()
ndocc = wfn.nalpha()
def _test_scf5():
"""scf5"""
#! Test of all different algorithms and reference types for SCF, on singlet and triplet O2, using the cc-pVTZ basis set and using ERD integrals.
psi4.print_stdout(' Case Study Test of all SCF algorithms/spin-degeneracies: Singlet-Triplet O2')
psi4.print_stdout(' -Integral package: {}'.format(psi4.core.get_global_option('integral_package')))
#Ensure that the checkpoint file is always nuked
psi4.core.IOManager.shared_object().set_specific_retention(32,False)
Eref_nuc = 30.78849213614545
Eref_sing_can = -149.58723684929720
Eref_sing_df = -149.58715054487624
Eref_uhf_can = -149.67135517240553
Eref_uhf_df = -149.67125624291961
Eref_rohf_can = -149.65170765757173
Eref_rohf_df = -149.65160796208073
singlet_o2 = psi4.geometry("""
0 1
O
O 1 1.1
units angstrom
""")
triplet_o2 = psi4.geometry("""
0 3
O
O 1 1.1
units angstrom
""")
singlet_o2.update_geometry()
triplet_o2.update_geometry()
psi4.print_stdout(' -Nuclear Repulsion:')
assert psi4.compare_values(Eref_nuc, triplet_o2.nuclear_repulsion_energy(), 9, "Triplet nuclear repulsion energy")
assert psi4.compare_values(Eref_nuc, singlet_o2.nuclear_repulsion_energy(), 9, "Singlet nuclear repulsion energy")
psi4.set_options({
'basis': 'cc-pvtz',
'df_basis_scf': 'cc-pvtz-jkfit',
'print': 2})
print(' -Singlet RHF:')
psi4.set_module_options('scf', {'reference': 'rhf'})
psi4.set_module_options('scf', {'scf_type': 'pk'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet PK RHF energy')
psi4.set_module_options('scf', {'scf_type': 'direct'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet Direct RHF energy')
psi4.set_module_options('scf', {'scf_type': 'out_of_core'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet Disk RHF energy')
psi4.set_module_options('scf', {'scf_type': 'df'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_df, E, 6, 'Singlet DF RHF energy')
print(' -Singlet UHF:')
psi4.set_module_options('scf', {'reference': 'uhf'})
psi4.set_module_options('scf', {'scf_type': 'pk'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet PK UHF energy')
psi4.set_module_options('scf', {'scf_type': 'direct'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet Direct UHF energy')
psi4.set_module_options('scf', {'scf_type': 'out_of_core'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet Disk UHF energy')
psi4.set_module_options('scf', {'scf_type': 'df'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_df, E, 6, 'Singlet DF UHF energy')
print(' -Singlet CUHF:')
psi4.set_module_options('scf', {'reference': 'cuhf'})
psi4.set_module_options('scf', {'scf_type': 'pk'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet PK CUHF energy')
psi4.set_module_options('scf', {'scf_type': 'direct'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet Direct CUHF energy')
psi4.set_module_options('scf', {'scf_type': 'out_of_core'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_can, E, 6, 'Singlet Disk CUHF energy')
psi4.set_module_options('scf', {'scf_type': 'df'})
E = psi4.energy('scf', molecule=singlet_o2)
assert psi4.compare_values(Eref_sing_df, E, 6, 'Singlet DF CUHF energy')
psi4.set_options({
'basis': 'cc-pvtz',
'df_basis_scf': 'cc-pvtz-jkfit',
'guess': 'core',
'print': 2})
print(' -Triplet UHF:')
psi4.set_module_options('scf', {'reference': 'uhf'})
psi4.set_module_options('scf', {'scf_type': 'pk'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_uhf_can, E, 6, 'Triplet PK UHF energy')
psi4.set_module_options('scf', {'scf_type': 'direct'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_uhf_can, E, 6, 'Triplet Direct UHF energy')
psi4.set_module_options('scf', {'scf_type': 'out_of_core'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_uhf_can, E, 6, 'Triplet Disk UHF energy')
psi4.set_module_options('scf', {'scf_type': 'df'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_uhf_df, E, 6, 'Triplet DF UHF energy')
psi4.core.clean()
print(' -Triplet ROHF:')
psi4.set_module_options('scf', {'reference': 'rohf'})
psi4.set_module_options('scf', {'scf_type': 'pk'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_can, E, 6, 'Triplet PK ROHF energy')
psi4.core.clean()
psi4.set_module_options('scf', {'scf_type': 'direct'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_can, E, 6, 'Triplet Direct ROHF energy')
psi4.core.clean()
psi4.set_module_options('scf', {'scf_type': 'out_of_core'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_can, E, 6, 'Triplet Disk ROHF energy')
psi4.core.clean()
psi4.set_module_options('scf', {'scf_type': 'df'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_df, E, 6, 'Triplet DF ROHF energy')
psi4.core.clean()
print(' -Triplet CUHF:')
psi4.set_module_options('scf', {'reference': 'cuhf'})
psi4.set_module_options('scf', {'scf_type': 'pk'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_can, E, 6, 'Triplet PK CUHF energy')
psi4.core.clean()
psi4.set_module_options('scf', {'scf_type': 'direct'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_can, E, 6, 'Triplet Direct CUHF energy')
psi4.core.clean()
psi4.set_module_options('scf', {'scf_type': 'out_of_core'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_can, E, 6, 'Triplet Disk CUHF energy')
psi4.core.clean()
psi4.set_module_options('scf', {'scf_type': 'df'})
E = psi4.energy('scf', molecule=triplet_o2)
assert psi4.compare_values(Eref_rohf_df, E, 6, 'Triplet DF CUHF energy')
