def test_json():
"""json/energy"""
import numpy as np
# Generate JSON data
json_data = {}
json_data["molecule"] = """He 0 0 0\n--\nHe 0 0 1"""
json_data["driver"] = "gradient"
json_data["method"] = 'SCF'
json_data["kwargs"] = {}
json_data["options"] = {"BASIS": "STO-3G"}
json_data["return_output"] = True
psi4.json_wrapper.run_json(json_data)
assert psi4.compare_strings("STO-3G", json_data["options"]["BASIS"], "Options test")
assert psi4.compare_integers(True, json_data["success"], "Success")
bench_energy = -5.433191881443323
cenergy = json_data["variables"]["CURRENT ENERGY"]
bench_gradient = np.array([[ 0.0 , 0.0 , 0.4206844],
[ 0.0 , 0.0 , -0.4206844]])
cgradient = psi4.core.Matrix.from_serial(json_data["return_value"])
assert psi4.compare_arrays(bench_gradient, cgradient.np, 4, "SCF RETURN_VALUE")
return_wfn = "return_wfn" not in json_data["kwargs"]
assert psi4.compare_integers(True, return_wfn, "Immutable input")
with open("pytest_output.dat", "w") as f:
f.write(json_data["raw_output"])
def test_json():
"""json/energy"""
import numpy as np
# Generate JSON data
json_data = {}
json_data["molecule"] = """He 0 0 0\n--\nHe 0 0 1"""
json_data["driver"] = "gradient"
json_data["method"] = 'SCF'
json_data["kwargs"] = {}
json_data["options"] = {"BASIS": "STO-3G"}
json_data["return_output"] = True
psi4.json_wrapper.run_json(json_data)
assert psi4.compare_strings("STO-3G", json_data["options"]["BASIS"],
"Options test")
assert psi4.compare_integers(True, json_data["success"], "Success")
bench_energy = -5.433191881443323
cenergy = json_data["variables"]["CURRENT ENERGY"]
bench_gradient = np.array([[0.0, 0.0, 0.4206844], [0.0, 0.0, -0.4206844]])
cgradient = psi4.core.Matrix.from_serial(json_data["return_value"])
assert psi4.compare_arrays(bench_gradient, cgradient.np, 4,
"SCF RETURN_VALUE")
return_wfn = "return_wfn" not in json_data["kwargs"]
assert psi4.compare_integers(True, return_wfn, "Immutable input")
with open("pytest_output.dat", "w") as f:
f.write(json_data["raw_output"])
def test_dft_block_schemes(scheme):
"""all DFT_BLOCK_SCHEME should give same results and number
of grid points. Water dimer with ghost atoms"""
mol = psi4.geometry(
"""
0 1
O -1.490196515110 -0.043256842172 0.000000000000
H -1.845932568294 0.844902886698 0.000000000000
H -0.533258283804 0.073267064698 0.000000000000
@O 1.416663724802 0.038738966977 0.000000000000
@H 1.773104797767 -0.423233996755 0.760023878024
@H 1.773104797767 -0.423233996755 -0.760023878024
no_com
no_reorient
symmetry c1
"""
)
psi4.set_options(
{
"BASIS": "def2-SVPD",
"DFT_SPHERICAL_POINTS": 590,
"DFT_RADIAL_POINTS": 85,
"D_convergence": 1e-8,
"DFT_WEIGHTS_TOLERANCE": -1.0,
}
)
ref = {"XC GRID TOTAL POINTS": 300900, "DFT XC ENERGY": -9.218561399189895}
psi4.set_options({"DFT_BLOCK_SCHEME": scheme})
e, wfn = psi4.energy("pbe/def2-SVPD", return_wfn=True)
P = psi4.variable("XC GRID TOTAL POINTS")
XC = wfn.variable("DFT XC ENERGY")
assert psi4.compare_integers(ref["XC GRID TOTAL POINTS"], P, f" {scheme} GRID POINTS:")
assert psi4.compare_values(ref["DFT XC ENERGY"], XC, f" {scheme} XC ENERGY:")
def test_dft_block_scheme_distantpoints():
"""Test removal of distant grid points. all DFT_BLOCK_SCHEME should give same results and number
of grid points."""
mol = 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
no_com
no_reorient
symmetry c1
"""
)
psi4.set_options(
{
"BASIS": "sto-3g",
"maxiter": 1,
"FAIL_ON_MAXITER": False,
"DFT_PRUNING_SCHEME": "ROBUST",
"DFT_WEIGHTS_TOLERANCE": -1.0,
}
)
ref = {"True": 45929, "False": 46890}
YESNO = [True,False]
SCHEMES = ["OCTREE", "NAIVE", "ATOMIC"]
for YN in YESNO:
psi4.set_options({"DFT_REMOVE_DISTANT_POINTS":YN})
for S in SCHEMES:
psi4.set_options({"DFT_BLOCK_SCHEME": S})
e, wfn = psi4.energy("pbe", return_wfn=True)
P = psi4.variable("XC GRID TOTAL POINTS")
XC = wfn.variable("DFT XC ENERGY")
assert psi4.compare_integers(ref[f"{YN}"], P, f" scheme={S}; distant points={YN} ")
def test_json():
"""json/energy"""
import numpy as np
# Generate JSON data
json_input = {
"schema_name": "qc_schema_input",
"schema_version": 1,
"molecule": {
"symbols": ["He", "He"],
"geometry": [0, 0, -1, 0, 0, 1]
},
"driver": "gradient",
"model": {
"method": "SCF",
"basis": "sto-3g"
},
"keywords": {}
}
json_ret = psi4.json_wrapper.run_json(json_input)
assert psi4.compare_integers(True, json_ret["success"], "Success")
assert psi4.compare_values(-5.474227786274896, json_ret["properties"]["return_energy"], 4, "SCF ENERGY")
bench_gradient = np.array([[ 0.0 , 0.0 , 0.32746933],
[ 0.0 , 0.0 , -0.32746933]])
cgradient = np.array(json_ret["return_result"]).reshape(-1, 3)
assert psi4.compare_arrays(bench_gradient, cgradient, 4, "SCF RETURN GRADIENT")
with open("pytest_output.dat", "w") as f:
json.dump(json_ret["raw_output"], f)
# Generate JSON data
json_data = {}
json_data["molecule"] = """He 0 0 0\n--\nHe 0 0 1"""
json_data["memory"] = "5GB"
json_data["driver"] = "energy"
json_data["method"] = 'SCF'
json_data["kwargs"] = {"bsse_type": "cp"}
json_data["options"] = {"BASIS": "STO-3G"}
json_data["return_output"] = True
psi4.json_wrapper.run_json(json_data)
psi4.compare_strings("STO-3G", json_data["options"]["BASIS"],
"Options test") #TEST
psi4.compare_integers(True,
len(json_data["raw_output"]) > 5000,
"Output returned") #TEST
psi4.compare_integers(True, json_data["success"], "Success") #TEST
bench_cp_energy = 0.183936053861 #TEST
cenergy = json_data["variables"]["CURRENT ENERGY"] #TEST
psi4.compare_values(bench_cp_energy, cenergy, 5, "SCF CURRENT ENERGY") #TEST
cenergy = json_data["return_value"] #TEST
psi4.compare_values(bench_cp_energy, cenergy, 5, "SCF RETURN_VALUE") #TEST
return_wfn = "return_wfn" not in json_data["kwargs"] #TEST
psi4.compare_integers(True, return_wfn, "Immutable input") #TEST
with open("output.dat", "w") as f:
f.write(json_data["raw_output"])
"scf_type": "df"
}
}
noorient_data = copy.deepcopy(json_data)
noorient_data["molecule"]["fix_orientation"] = True
noorient_data["molecule"]["fix_com"] = True
# Write expected output
expected_return_result = -100.0194177509218
linear_dipole = 1.948993625469663
psi4.json_wrapper.run_json(json_data)
# Orients to Z axis
psi4.compare_integers(True, json_data["success"], "JSON Success") #TEST
psi4.compare_values(expected_return_result, json_data["return_result"], 5, "Return Value") #TEST
psi4.compare_values(0.0, json_data["properties"]["scf_dipole_moment"][0], 5, "DIPOLE X") #TEST
psi4.compare_values(0.0, json_data["properties"]["scf_dipole_moment"][1], 5, "DIPOLE Y") #TEST
psi4.compare_values(linear_dipole, json_data["properties"]["scf_dipole_moment"][2], 5, "DIPOLE Z") #TEST
dist = np.linalg.norm(np.array(json_data["molecule"]["geometry"])[:3] - np.array(np.array(json_data["molecule"]["geometry"])[3:])) #TEST
psi4.compare_values(1.732, dist, 4, "HF Bond Distance") #TEST
psi4.json_wrapper.run_json(noorient_data)
# Orients to Z axis
psi4.compare_integers(True, noorient_data["success"], "JSON Success") #TEST
psi4.compare_values(expected_return_result, noorient_data["return_result"], 5, "Return Value") #TEST
psi4.compare_values(0.0, noorient_data["properties"]["scf_dipole_moment"][0], 5, "DIPOLE X") #TEST
# Write expected output
expected_return_result = [
0.0, 0.0, -0.05959774096119619, 0.0, -0.043039786289375104,
0.02979887048056895, 0.0, 0.043039786289375104, 0.02979887048056895
]
expected_properties = {
"calcinfo_nbasis": 24,
"calcinfo_nmo": 24,
"calcinfo_nalpha": 5,
"calcinfo_nbeta": 5,
"calcinfo_natom": 3,
"scf_one_electron_energy": -122.4452968291507,
"scf_two_electron_energy": 37.62243738251799,
"nuclear_repulsion_energy": 8.80146206062943,
"scf_total_energy": -76.02139738600329,
"return_energy": -76.02139738600329
}
json_ret = psi4.json_wrapper.run_json(json_data)
with open("output.json", "w") as ofile:
json.dump(json_ret, ofile, indent=2)
psi4.compare_integers(True, json_ret["success"], "JSON Success") #TEST
psi4.compare_arrays(expected_return_result, json_ret["return_result"], 5,
"Return Value") #TEST
for k in expected_properties.keys():
psi4.compare_values(expected_properties[k], json_ret["properties"][k], 5,
k.upper()) #TEST
"scf_total_energy": -76.02139738600329,
"mp2_same_spin_correlation_energy": -0.05202760538221721,
"mp2_opposite_spin_correlation_energy": -0.1548891108392641,
"mp2_singles_energy": 0.0,
"mp2_doubles_energy": -0.20691671622148142,
"mp2_total_correlation_energy": -0.20691671622148142,
"mp2_total_energy": -76.22831410222477,
"return_energy": expected_return_result
}
json_ret = psi4.json_wrapper.run_json(json_data)
with open("output.json", "w") as ofile: #TEST
json.dump(json_ret, ofile, indent=2) #TEST
psi4.compare_integers(True, json_ret["success"], "JSON Success") #TEST
psi4.compare_values(expected_return_result, json_ret["return_result"], 5, "Return Value") #TEST
psi4.compare_integers(True, "MAYER_INDICES" in json_ret["psi4:qcvars"], "Mayer Indices Found") #TEST
for k in expected_properties.keys(): #TEST
psi4.compare_values(expected_properties[k], json_ret["properties"][k], 5, k.upper()) #TEST
# Expected output with exact MP2
expected_return_result = -76.2283674281634
expected_properties = {
"calcinfo_nbasis": 24,
"calcinfo_nmo": 24,
"calcinfo_nalpha": 5,
"calcinfo_nbeta": 5,
"calcinfo_natom": 3,
"scf_one_electron_energy": -122.44534537436829,
"fragments": [[2, 0, 1]]
},
"driver": "energy",
"model": {
"method": "SCF",
"basis": "cc-pVDZ"
},
"keywords": {
"scf_type": "df"
}
}
# Check non-contiguous fragment throws
json_ret = psi4.json_wrapper.run_json(json_data)
psi4.compare_integers(False, json_ret["success"], "JSON Failure") #TEST
psi4.compare_integers("non-contiguous frag" in json_ret["error"], True,
"Contiguous Fragment Error") #TEST
# Check symbol length errors
del json_data["molecule"]["fragments"]
json_data["molecule"]["symbols"] = ["O", "H"]
json_ret = psi4.json_wrapper.run_json(json_data)
psi4.compare_integers(False, json_data["success"], "JSON Failure") #TEST
psi4.compare_integers("atoms" in json_data["error"], True,
"Symbol Error") #TEST
# Check keyword errors
json_data["molecule"]["symbols"] = ["O", "H", "H"]
json_data["model"] = {"method": "SCF", "basis": "sto-3g"}
"fragments": [[2, 0, 1]]
},
"driver": "energy",
"model": {
"method": "SCF",
"basis": "cc-pVDZ"
},
"keywords": {
"scf_type": "df"
}
}
# Check non-contiguous fragment throws
json_ret = psi4.json_wrapper.run_json(json_data)
psi4.compare_integers(False, json_ret["success"], "JSON Failure") #TEST
psi4.compare_integers("non-contiguous frag" in json_ret["error"], True, "Contiguous Fragment Error") #TEST
# Check symbol length errors
del json_data["molecule"]["fragments"]
json_data["molecule"]["symbols"] = ["O", "H"]
json_ret = psi4.json_wrapper.run_json(json_data)
psi4.compare_integers(False, json_data["success"], "JSON Failure") #TEST
psi4.compare_integers("atoms" in json_data["error"], True, "Symbol Error") #TEST
# Check keyword errors
json_data["molecule"]["symbols"] = ["O", "H", "H"]
json_data["model"] = {"method": "SCF", "basis": "sto-3g"}
json_data["keywords"] = {"scf_type": "super_df"}
json_ret = psi4.json_wrapper.run_json(json_data)
# 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,ecp = 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
psi4.compare_integers(162, wert.nao(), 'nao()') #TEST
psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST
psi4.compare_strings('(CC-PVDZ AUX)', wert.name(), 'callby') #TEST
psi4.compare_strings('CC-PVDZ-RI', wert.blend(), 'blend') #TEST
mymol.print_out()
psi4.set_output_file("output.dat", False)
# Generate JSON data
json_data = {}
json_data["molecule"] = """He 0 0 0\n--\nHe 0 0 1"""
json_data["driver"] = "gradient"
json_data["method"] = 'SCF'
json_data["kwargs"] = {}
json_data["options"] = {"BASIS": "STO-3G"}
json_data["return_output"] = True
psi4.json_wrapper.run_json(json_data)
psi4.compare_strings("STO-3G", json_data["options"]["BASIS"], "Options test") #TEST
psi4.compare_integers(True, json_data["success"], "Success") #TEST
bench_energy = -5.433191881443323 #TEST
cenergy = json_data["variables"]["CURRENT ENERGY"] #TEST
psi4.compare_values(bench_energy, cenergy, 5, "SCF CURRENT ENERGY") #TEST
bench_gradient = np.array([[ 0.0 , 0.0 , 0.4206844],
[ 0.0 , 0.0 , -0.4206844]])
cgradient = psi4.core.Matrix.from_serial(json_data["return_value"]) #TEST
psi4.compare_arrays(bench_gradient, cgradient.np, 4, "SCF RETURN_VALUE") #TEST
return_wfn = "return_wfn" not in json_data["kwargs"] #TEST
psi4.compare_integers(True, return_wfn, "Immutable input") #TEST
with open("output.dat", "w") as f:
import numpy as np
import psi4
# Generate JSON data
json_data = {}
json_data["molecule"] = """He 0 0 0\n--\nHe 0 0 1"""
json_data["memory"] = "5GB"
json_data["driver"] = "energy"
json_data["method"] = 'SCF'
json_data["kwargs"] = {"bsse_type": "cp"}
json_data["options"] = {"BASIS": "STO-3G"}
json_data["return_output"] = True
psi4.json_wrapper.run_json(json_data)
psi4.compare_strings("STO-3G", json_data["options"]["BASIS"], "Options test") #TEST
psi4.compare_integers(True, len(json_data["raw_output"]) > 5000, "Output returned") #TEST
psi4.compare_integers(True, json_data["success"], "Success") #TEST
bench_cp_energy = 0.183936053861 #TEST
cenergy = json_data["variables"]["CURRENT ENERGY"] #TEST
psi4.compare_values(bench_cp_energy, cenergy, 5, "SCF CURRENT ENERGY") #TEST
cenergy = json_data["return_value"] #TEST
psi4.compare_values(bench_cp_energy, cenergy, 5, "SCF RETURN_VALUE") #TEST
return_wfn = "return_wfn" not in json_data["kwargs"] #TEST
psi4.compare_integers(True, return_wfn, "Immutable input") #TEST
with open("output.dat", "w") as f:
f.write(json_data["raw_output"])
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, ecp = 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
psi4.compare_integers(162, wert.nao(), 'nao()') #TEST
psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST
psi4.compare_strings('(CC-PVDZ AUX)', wert.name(), 'callby') #TEST
psi4.compare_strings('CC-PVDZ-RI', wert.blend(), 'blend') #TEST
mymol.print_out()
"ccsd_opposite_spin_correlation_energy": -0.11488521989019397,
"ccsd_singles_energy": 0.0,
"ccsd_doubles_energy": -0.13940944106012007,
"ccsd_correlation_energy": -0.13940944106012007,
"ccsd_total_energy": -76.11955131338757,
"ccsd_iterations": 12,
"ccsd_prt_pr_correlation_energy": -0.140553536424603,
"ccsd_prt_pr_total_energy": expected_return_result,
}
json_ret = psi4.json_wrapper.run_json(json_data)
with open("output.json", "w") as ofile: #TEST
json.dump(json_ret, ofile, indent=2) #TEST
psi4.compare_integers(True, json_ret["success"], "JSON Success") #TEST
psi4.compare_values(expected_return_result, json_ret["return_result"], 5,
"Return Value") #TEST
psi4.compare_integers(True, "MAYER_INDICES" in json_ret["extras"]["qcvars"],
"Mayer Indices Found") #TEST
for k in expected_properties.keys(): #TEST
psi4.compare_values(expected_properties[k], json_ret["properties"][k], 5,
k.upper()) #TEST
assert "Density-fitted CCSD" in json_ret["raw_output"] #TEST
# Expected output with exact MP2
expected_return_result = -76.2283674281634
expected_properties = {
"calcinfo_nbasis": 24,
"fragments": [[2, 0, 1]]
},
"driver": "energy",
"model": {
"method": "SCF",
"basis": "cc-pVDZ"
},
"keywords": {
"scf_type": "df"
}
}
# Check non-contiguous fragment throws
json_ret = psi4.schema_wrapper.run_qcschema(json_data)
psi4.compare_integers(False, json_ret.success, "JSON Failure") #TEST
psi4.compare_integers("non-contiguous frag" in json_ret.error.error_message, True, "Contiguous Fragment Error") #TEST
# Check symbol length errors
del json_data["molecule"]["fragments"]
json_data["molecule"]["symbols"] = ["O", "H"]
json_ret = psi4.schema_wrapper.run_qcschema(json_data)
psi4.compare_integers(False, json_ret.success, "JSON Failure") #TEST
psi4.compare_integers("dropped atoms!" in json_ret.error.error_message, True, "Symbol Error") #TEST
# Check keyword errors
json_data["molecule"]["symbols"] = ["O", "H", "H"]
json_data["model"] = {"method": "SCF", "basis": "sto-3g"}
json_data["keywords"] = {"scf_type": "super_df"}
json_ret = psi4.schema_wrapper.run_qcschema(json_data)
0.0,
-0.043039786289375104,
0.02979887048056895,
0.0,
0.043039786289375104,
0.02979887048056895
]
expected_properties = {
"calcinfo_nbasis": 24,
"calcinfo_nmo": 24,
"calcinfo_nalpha": 5,
"calcinfo_nbeta": 5,
"calcinfo_natom": 3,
"scf_one_electron_energy": -122.4452968291507,
"scf_two_electron_energy": 37.62243738251799,
"nuclear_repulsion_energy": 8.80146206062943,
"scf_total_energy": -76.02139738600329,
"return_energy": -76.02139738600329
}
json_ret = psi4.json_wrapper.run_json(json_data)
with open("output.json", "w") as ofile:
json.dump(json_ret, ofile, indent=2)
psi4.compare_integers(True, json_ret["success"], "JSON Success") #TEST
psi4.compare_arrays(expected_return_result, json_ret["return_result"], 5, "Return Value") #TEST
for k in expected_properties.keys(): #TEST
psi4.compare_values(expected_properties[k], json_ret["properties"][k], 5, k.upper()) #TEST
psi4.set_output_file("output.dat", False)
# Generate JSON data
json_data = {}
json_data["molecule"] = """He 0 0 0\n--\nHe 0 0 1"""
json_data["driver"] = "gradient"
json_data["method"] = 'SCF'
json_data["kwargs"] = {}
json_data["options"] = {"BASIS": "STO-3G"}
json_data["return_output"] = True
psi4.json_wrapper.run_json(json_data)
psi4.compare_strings("STO-3G", json_data["options"]["BASIS"],
"Options test") #TEST
psi4.compare_integers(True, json_data["success"], "Success") #TEST
bench_energy = -5.433191881443323 #TEST
cenergy = json_data["variables"]["CURRENT ENERGY"] #TEST
psi4.compare_values(bench_energy, cenergy, 6, "SCF CURRENT ENERGY") #TEST
bench_gradient = np.array([[0.0, 0.0, 0.4206844], [0.0, 0.0, -0.4206844]])
cgradient = psi4.core.Matrix.from_serial(json_data["return_value"]) #TEST
psi4.compare_arrays(bench_gradient, cgradient.np, 4, "SCF RETURN_VALUE") #TEST
return_wfn = "return_wfn" not in json_data["kwargs"] #TEST
psi4.compare_integers(True, return_wfn, "Immutable input") #TEST
with open("output.dat", "w") as f:
f.write(json_data["raw_output"])
# Compute required quantities for SCF
V = np.asarray(mints.ao_potential())
T = np.asarray(mints.ao_kinetic())
I = np.asarray(mints.ao_eri())
print('\nTotal time taken for integrals: %.3f seconds.' % (time.time() - t))
t = time.time()
# Build H_core
H = T + V
# <-- efp: add in permanent moment contribution and cache
Vefp = modify_Fock_permanent(mol, nbf, efpmol)
assert (psi4.compare_integers(1, np.allclose(Vefp, ref_V2),
'EFP permanent Fock contrib'))
H = H + Vefp
Horig = H.copy()
set_qm_atoms(mol, efpmol)
# --> efp
# Orthogonalizer A = S^(-1/2) using Psi4's matrix power.
A = mints.ao_overlap()
A.power(-0.5, 1.e-16)
A = np.asarray(A)
# Calculate initial core guess
Hp = A.dot(H).dot(A)
e, C2 = np.linalg.eigh(Hp)
C = A.dot(C2)
Cocc = C[:, :ndocc]
# Compute required quantities for SCF
V = np.asarray(mints.ao_potential())
T = np.asarray(mints.ao_kinetic())
I = np.asarray(mints.ao_eri())
print('\nTotal time taken for integrals: %.3f seconds.' % (time.time() - t))
t = time.time()
# Build H_core
H = T + V
# <-- efp: add in permanent moment contribution and cache
Vefp = modify_Fock_permanent(mol, nbf, efpmol)
assert(psi4.compare_integers(1, np.allclose(Vefp, ref_V2), 'EFP permanent Fock contrib'))
H = H + Vefp
Horig = H.copy()
set_qm_atoms(mol, efpmol)
# --> efp
# Orthogonalizer A = S^(-1/2) using Psi4's matrix power.
A = mints.ao_overlap()
A.power(-0.5, 1.e-16)
A = np.asarray(A)
# Calculate initial core guess
Hp = A.dot(H).dot(A)
e, C2 = np.linalg.eigh(Hp)
C = A.dot(C2)
Cocc = C[:, :ndocc]