def test_freezing_core(self):
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom', 'H .0 .0 -1.160518; Li .0 .0 0.386839'),
('unit', 'Angstrom'), ('charge', 0),
('spin', 0), ('basis', 'sto3g')])
section = {}
section['properties'] = pyscf_cfg
driver = cfg_mgr.get_driver_instance('PYSCF')
molecule = driver.run(section)
fer_op = FermionicOperator(h1=molecule._one_body_integrals,
h2=molecule._two_body_integrals)
fer_op, energy_shift = fer_op.fermion_mode_freezing([0, 6])
gt = -7.8187092970493755
diff = abs(energy_shift - gt)
self.assertLess(diff, 1e-6)
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom', 'H .0 .0 .0; Na .0 .0 1.888'), ('unit', 'Angstrom'),
('charge', 0), ('spin', 0), ('basis', 'sto3g')])
section = {}
section['properties'] = pyscf_cfg
driver = cfg_mgr.get_driver_instance('PYSCF')
molecule = driver.run(section)
fer_op = FermionicOperator(h1=molecule._one_body_integrals,
h2=molecule._two_body_integrals)
fer_op, energy_shift = fer_op.fermion_mode_freezing([0, 1, 2, 3, 4, 10, 11, 12, 13, 14])
gt = -162.58414559586748
diff = abs(energy_shift - gt)
self.assertLess(diff, 1e-6)
def __init__(self,view):
self._view = view
self._model = Model()
self._filemenu = None
self._title = tk.StringVar()
self._sectionsView = None
self._emptyView = None
self._sectionView_title = tk.StringVar()
self._propertiesView = None
self._textView = None
self._outputView = None
self._progress = None
self._button_text = None
self._start_button = None
self._save_algo_json = tk.IntVar()
self._save_algo_json.set(0)
self._thread_queue = queue.Queue()
self._thread = None
self._command = Controller._START
self._driver_names = []
config_mgr = ConfigurationManager()
for name in config_mgr.module_names:
try:
config_mgr.get_driver_instance(name)
self._driver_names.append(name)
except:
pass
self._process_stop = False
self._validate_integer_command = self._view.register(Controller._validate_integer)
self._validate_float_command = self._view.register(Controller._validate_float)
self._available_backends = []
self._backendsthread = None
self.get_available_backends()
def driver_names(self):
from qiskit_aqua_chemistry.drivers import ConfigurationManager
if self._driver_names is None:
self._driver_names = []
config_mgr = ConfigurationManager()
for name in config_mgr.module_names:
try:
config_mgr.get_driver_instance(name)
self._driver_names.append(name)
except:
pass
return self._driver_names
def test_bksf_mapping(self):
"""Test bksf mapping
The spectrum of bksf mapping should be half of jordan wigner mapping.
"""
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom', 'H .0 .0 0.7414; H .0 .0 .0'), ('unit', 'Angstrom'),
('charge', 0), ('spin', 0), ('basis', 'sto3g')])
section = {}
section['properties'] = pyscf_cfg
driver = cfg_mgr.get_driver_instance('PYSCF')
molecule = driver.run(section)
fer_op = FermionicOperator(h1=molecule._one_body_integrals,
h2=molecule._two_body_integrals)
jw_op = fer_op.mapping('jordan_wigner')
bksf_op = fer_op.mapping('bravyi_kitaev_sf')
jw_op.to_matrix()
bksf_op.to_matrix()
jw_eigs = np.linalg.eigvals(jw_op.matrix.toarray())
bksf_eigs = np.linalg.eigvals(bksf_op.matrix.toarray())
jw_eigs = np.sort(np.around(jw_eigs.real, 6))
bksf_eigs = np.sort(np.around(bksf_eigs.real, 6))
overlapped_spectrum = np.sum(np.isin(jw_eigs, bksf_eigs))
self.assertEqual(overlapped_spectrum, jw_eigs.size // 2)
def setUp(self):
cfg_mgr = ConfigurationManager()
hdf5_cfg = OrderedDict([
('hdf5_input', self._get_resource_path('test_driver_hdf5.hdf5'))
])
section = {'properties': hdf5_cfg}
driver = cfg_mgr.get_driver_instance('HDF5')
self.qmolecule = driver.run(section)
def setUp(self):
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom', 'Li .0 .0 .0; H .0 .0 1.595'), ('unit', 'Angstrom'),
('charge', 0), ('spin', 0), ('basis', 'sto3g')])
section = {}
section['properties'] = pyscf_cfg
driver = cfg_mgr.get_driver_instance('PYSCF')
molecule = driver.run(section)
self.fer_op = FermionicOperator(h1=molecule._one_body_integrals,
h2=molecule._two_body_integrals)
def procesar_molecula(configuracionmolecula, distancia=None):
"""Esta función analiza que tipo de procesado necesita una molécula para pedir su construcción"""
gestorconfiguracion = ConfigurationManager()
if configuracionmolecula["driver"] == "PYSCF":
molecula = __procesar_molecula_pyscf(configuracionmolecula, distancia)
else:
driver = gestorconfiguracion.get_driver_instance(
configuracionmolecula["driver"])
molecula = driver.run(configuracionmolecula["configuracion"])
return molecula
def setUp(self):
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom', 'H .0 .0 .0; H .0 .0 0.735'),
('unit', 'Angstrom'), ('charge', 0),
('spin', 0), ('basis', 'sto3g')])
section = {'properties': pyscf_cfg}
try:
driver = cfg_mgr.get_driver_instance('PYSCF')
except ModuleNotFoundError:
self.skipTest('PYSCF driver does not appear to be installed')
self.qmolecule = driver.run(section)
def setUp(self):
cfg_mgr = ConfigurationManager()
hdf5_cfg = OrderedDict([
('hdf5_input', self._get_resource_path('test_driver_hdf5.hdf5'))
])
section = {'properties': hdf5_cfg}
driver = cfg_mgr.get_driver_instance('HDF5')
self.qmolecule = driver.run(section)
core = Hamiltonian(transformation='full',
qubit_mapping='parity',
two_qubit_reduction=True,
freeze_core=False,
orbital_reduction=[],
max_workers=4)
self.algo_input = core.run(self.qmolecule)
self.reference_energy = -1.857275027031588
def setUp(self):
cfg_mgr = ConfigurationManager()
gaussian_cfg = """
# rhf/sto-3g scf(conventional) geom=nocrowd
h2 molecule
0 1
H 0.0 0.0 0.0
H 0.0 0.0 0.735
"""
section = {'data': gaussian_cfg}
try:
driver = cfg_mgr.get_driver_instance('GAUSSIAN')
except AquaChemistryError:
self.skipTest('GAUSSIAN driver does not appear to be installed')
self.qmolecule = driver.run(section)
def setUp(self):
cfg_mgr = ConfigurationManager()
psi4_cfg = """
molecule h2 {
0 1
H 0.0 0.0 0.0
H 0.0 0.0 0.735
}
set {
basis sto-3g
scf_type pk
}
"""
section = {'data': psi4_cfg}
try:
driver = cfg_mgr.get_driver_instance('PSI4')
except AquaChemistryError:
self.skipTest('PSI4 driver does not appear to be installed')
self.qmolecule = driver.run(section)
class AquaChemistry(object):
"""Main entry point."""
KEY_HDF5_OUTPUT = 'hdf5_output'
_DRIVER_RUN_TO_HDF5 = 1
_DRIVER_RUN_TO_ALGO_INPUT = 2
def __init__(self):
"""Create an AquaChemistry object."""
self._configuration_mgr = ConfigurationManager()
self._parser = None
self._core = None
def run(self, input, output=None, backend=None):
"""
Runs the Aqua Chemistry experiment
Args:
input (dictionary/filename): Input data
output (filename): Output data
backend (BaseBackend): backend object
Returns:
result dictionary
"""
if input is None:
raise AquaChemistryError("Missing input.")
self._parser = InputParser(input)
self._parser.parse()
driver_return = self._run_driver_from_parser(self._parser, False)
if driver_return[0] == AquaChemistry._DRIVER_RUN_TO_HDF5:
logger.info('No further process.')
return {'printable': [driver_return[1]]}
data = run_algorithm(driver_return[1], driver_return[2], True, backend)
if not isinstance(data, dict):
raise AquaChemistryError(
"Algorithm run result should be a dictionary")
convert_json_to_dict(data)
if logger.isEnabledFor(logging.DEBUG):
logger.debug('Algorithm returned: {}'.format(
pprint.pformat(data, indent=4)))
lines, result = self._format_result(data)
logger.info('Processing complete. Final result available')
result['printable'] = lines
if output is not None:
with open(output, 'w') as f:
for line in lines:
print(line, file=f)
return result
def save_input(self, input_file):
"""
Save the input of a run to a file.
Params:
input_file (string): file path
"""
if self._parser is None:
raise AquaChemistryError("Missing input information.")
self._parser.save_to_file(input_file)
def run_drive_to_jsonfile(self, input, jsonfile):
if jsonfile is None:
raise AquaChemistryError("Missing json file")
data = self._run_drive(input, True)
if data is None:
logger.info('No data to save. No further process.')
return
with open(jsonfile, 'w') as fp:
json.dump(data, fp, sort_keys=True, indent=4)
print("Algorithm input file saved: '{}'".format(jsonfile))
def run_algorithm_from_jsonfile(self, jsonfile, output=None, backend=None):
"""
Runs the Aqua Chemistry experiment from json file
Args:
jsonfile (filename): Input data
output (filename): Output data
backend (BaseBackend): backend object
Returns:
result dictionary
"""
with open(jsonfile) as json_file:
return self.run_algorithm_from_json(json.load(json_file), output,
backend)
def run_algorithm_from_json(self, params, output=None, backend=None):
"""
Runs the Aqua Chemistry experiment from json dictionary
Args:
params (dictionary): Input data
output (filename): Output data
backend (BaseBackend): backend object
Returns:
result dictionary
"""
ret = run_algorithm(params, None, True, backend)
if not isinstance(ret, dict):
raise AquaChemistryError(
"Algorithm run result should be a dictionary")
convert_json_to_dict(ret)
if logger.isEnabledFor(logging.DEBUG):
logger.debug('Algorithm returned: {}'.format(
pprint.pformat(ret, indent=4)))
print('Output:')
if isinstance(ret, dict):
for k, v in ret.items():
print("'{}': {}".format(k, v))
else:
print(ret)
return ret
def _format_result(self, data):
lines, result = self._core.process_algorithm_result(data)
return lines, result
def run_drive(self, input):
return self._run_drive(input, False)
def _run_drive(self, input, save_json_algo_file):
if input is None:
raise AquaChemistryError("Missing input.")
self._parser = InputParser(input)
self._parser.parse()
driver_return = self._run_driver_from_parser(self._parser,
save_json_algo_file)
driver_return[1]['input'] = driver_return[2].to_params()
driver_return[1]['input']['name'] = driver_return[2].configuration[
'name']
return driver_return[1]
def _run_driver_from_parser(self, p, save_json_algo_file):
if p is None:
raise AquaChemistryError("Missing parser")
p.validate_merge_defaults()
# logger.debug('ALgorithm Input Schema: {}'.format(json.dumps(p.to_JSON(), sort_keys=True, indent=4)))
experiment_name = "-- no &NAME section found --"
if JSONSchema.NAME in p.get_section_names():
name_sect = p.get_section(JSONSchema.NAME)
if 'data' in name_sect:
experiment_name = name_sect['data']
logger.info('Running chemistry problem from input file: {}'.format(
p.get_filename()))
logger.info('Experiment description: {}'.format(
experiment_name.rstrip()))
driver_name = p.get_section_property(InputParser.DRIVER,
JSONSchema.NAME)
if driver_name is None:
raise AquaChemistryError(
'Property "{0}" missing in section "{1}"'.format(
JSONSchema.NAME, InputParser.DRIVER))
hdf5_file = p.get_section_property(InputParser.DRIVER,
AquaChemistry.KEY_HDF5_OUTPUT)
section = p.get_section(driver_name)
if 'data' not in section:
raise AquaChemistryError(
'Property "data" missing in section "{0}"'.format(driver_name))
if driver_name not in self._configuration_mgr.module_names:
raise AquaChemistryError(
'Driver "{0}" missing in local drivers'.format(driver_name))
work_path = None
input_file = p.get_filename()
if input_file is not None:
work_path = os.path.dirname(os.path.realpath(input_file))
driver = self._configuration_mgr.get_driver_instance(driver_name)
driver.work_path = work_path
molecule = driver.run(section)
if work_path is not None and hdf5_file is not None and not os.path.isabs(
hdf5_file):
hdf5_file = os.path.abspath(os.path.join(work_path, hdf5_file))
molecule.log()
if hdf5_file is not None:
molecule._origin_driver_name = driver_name
molecule._origin_driver_config = section['data']
molecule.save(hdf5_file)
text = "HDF5 file saved '{}'".format(hdf5_file)
logger.info(text)
if not save_json_algo_file:
logger.info('Run ended with hdf5 file saved.')
return AquaChemistry._DRIVER_RUN_TO_HDF5, text
# Run the Hamiltonian to process the QMolecule and get an input for algorithms
cls = get_chemistry_operator_class(
p.get_section_property(InputParser.OPERATOR, JSONSchema.NAME))
self._core = cls.init_params(
p.get_section_properties(InputParser.OPERATOR))
input_object = self._core.run(molecule)
logger.debug('Core computed substitution variables {}'.format(
self._core.molecule_info))
result = p.process_substitutions(self._core.molecule_info)
logger.debug('Substitutions {}'.format(result))
params = {}
for section_name, section in p.get_sections().items():
if section_name == JSONSchema.NAME or \
section_name == InputParser.DRIVER or \
section_name == driver_name.lower() or \
section_name == InputParser.OPERATOR or \
'properties' not in section:
continue
params[section_name] = copy.deepcopy(section['properties'])
if JSONSchema.PROBLEM == section_name and \
InputParser.AUTO_SUBSTITUTIONS in params[section_name]:
del params[section_name][InputParser.AUTO_SUBSTITUTIONS]
return AquaChemistry._DRIVER_RUN_TO_ALGO_INPUT, params, input_object
def test_qpe(self, distance):
self.algorithm = 'QPE'
self.log.debug(
'Testing End-to-End with QPE on H2 with inter-atomic distance {}.'.
format(distance))
cfg_mgr = ConfigurationManager()
pyscf_cfg = OrderedDict([('atom',
'H .0 .0 .0; H .0 .0 {}'.format(distance)),
('unit', 'Angstrom'), ('charge', 0),
('spin', 0), ('basis', 'sto3g')])
section = {}
section['properties'] = pyscf_cfg
try:
driver = cfg_mgr.get_driver_instance('PYSCF')
except ModuleNotFoundError:
self.skipTest('PYSCF driver does not appear to be installed')
self.molecule = driver.run(section)
ferOp = FermionicOperator(h1=self.molecule._one_body_integrals,
h2=self.molecule._two_body_integrals)
self.qubitOp = ferOp.mapping(
map_type='PARITY', threshold=1e-10).two_qubit_reduced_operator(2)
exact_eigensolver = get_algorithm_instance('ExactEigensolver')
exact_eigensolver.init_args(self.qubitOp, k=1)
results = exact_eigensolver.run()
self.reference_energy = results['energy']
self.log.debug('The exact ground state energy is: {}'.format(
results['energy']))
num_particles = self.molecule._num_alpha + self.molecule._num_beta
two_qubit_reduction = True
num_orbitals = self.qubitOp.num_qubits + (2 if two_qubit_reduction else
0)
qubit_mapping = 'parity'
num_time_slices = 50
n_ancillae = 9
qpe = get_algorithm_instance('QPE')
qpe.setup_quantum_backend(backend='local_qasm_simulator',
shots=100,
skip_transpiler=True)
state_in = get_initial_state_instance('HartreeFock')
state_in.init_args(self.qubitOp.num_qubits, num_orbitals,
qubit_mapping, two_qubit_reduction, num_particles)
iqft = get_iqft_instance('STANDARD')
iqft.init_args(n_ancillae)
qpe.init_args(self.qubitOp,
state_in,
iqft,
num_time_slices,
n_ancillae,
paulis_grouping='random',
expansion_mode='suzuki',
expansion_order=2)
result = qpe.run()
self.log.debug('measurement results: {}'.format(
result['measurements']))
self.log.debug('top result str label: {}'.format(
result['top_measurement_label']))
self.log.debug('top result in decimal: {}'.format(
result['top_measurement_decimal']))
self.log.debug('stretch: {}'.format(
result['stretch']))
self.log.debug('translation: {}'.format(
result['translation']))
self.log.debug('final energy from QPE: {}'.format(result['energy']))
self.log.debug('reference energy: {}'.format(
self.reference_energy))
self.log.debug('ref energy (transformed): {}'.format(
(self.reference_energy + result['translation']) *
result['stretch']))
self.log.debug('ref binary str label: {}'.format(
decimal_to_binary((self.reference_energy + result['translation']) *
result['stretch'],
max_num_digits=n_ancillae + 3,
fractional_part_only=True)))
np.testing.assert_approx_equal(result['energy'],
self.reference_energy,
significant=2)