def setUp(self):
cfg_mgr = ConfigurationManager()
hdf5_cfg = OrderedDict([
('hdf5_input', 'test/test_driver_hdf5.hdf5')
])
section = {'properties': hdf5_cfg}
driver = cfg_mgr.get_driver_instance('HDF5')
self.qmolecule = driver.run(section)
core = get_chemistry_operator_instance('hamiltonian')
hamiltonian_cfg = OrderedDict([
('name', 'hamiltonian'),
('transformation', 'full'),
('qubit_mapping', 'parity'),
('two_qubit_reduction', True),
('freeze_core', False),
('orbital_reduction', [])
])
core.init_params(hamiltonian_cfg)
self.algo_input = core.run(self.qmolecule)
self.reference_energy = -1.857275027031588
def test_qpe(self, distance):
self.algorithm = 'QPE'
self.log.debug(
'Testing End-to-End with QPE on H2 with interatomic 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
driver = cfg_mgr.get_driver_instance('PYSCF')
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)
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,
use_basis_gates=True)
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)
class ACQUAChemistry(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 ACQUAChemistry object."""
self._configuration_mgr = ConfigurationManager()
self._parser = None
self._core = None
def get_effective_logging_level(self):
"""
Returns the logging level being used by ACQUA Chemistry
"""
levels = get_logger_levels_for_names(
['qiskit_acqua_chemistry', 'qiskit_acqua'])
return levels[0]
def set_logging(self, level=logging.INFO):
"""Sets logging output of the logging messages.
Sets the output of logging messages (above level `level`) by
configuring the logger accordingly.
Disables logging if set to logging.NOTSET
Params:
level (int): minimum severity of the messages that are displayed.
"""
logging_config = build_logging_config(
['qiskit_acqua_chemistry', 'qiskit_acqua'], level)
preferences = Preferences()
preferences.set_logging_config(logging_config)
preferences.save()
set_logger_config(logging_config)
def run(self, input, output=None):
if input is None:
raise ACQUAChemistryError("Missing input.")
self._parser = InputParser(input)
self._parser.parse()
driver_return = self._run_driver_from_parser(self._parser, False)
if driver_return[0] == ACQUAChemistry._DRIVER_RUN_TO_HDF5:
logger.info('No further process.')
return {'printable': [driver_return[1]]}
data = run_algorithm(driver_return[1], driver_return[2], True)
if not isinstance(data, dict):
raise ACQUAChemistryError(
"Algorithm run result should be a dictionary")
if logger.isEnabledFor(logging.DEBUG):
logger.debug('Algorithm returned: {}'.format(
json.dumps(data, indent=4)))
convert_json_to_dict(data)
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 ACQUAChemistryError("Missing input information.")
self._parser.save_to_file(input_file)
def run_drive_to_jsonfile(self, input, jsonfile):
if jsonfile is None:
raise ACQUAChemistryError("Missing json file")
data = self._run_drive(input, True)
if data is None:
logger.info('No data to save. No further process.')
return
logger.debug('Result: {}'.format(
json.dumps(data, sort_keys=True, indent=4)))
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):
with open(jsonfile) as json_file:
return self.run_algorithm_from_json(json.load(json_file), output)
def run_algorithm_from_json(self, params, output=None):
ret = run_algorithm(params, None, True)
if not isinstance(ret, dict):
raise ACQUAChemistryError(
"Algorithm run result should be a dictionary")
logger.debug('Algorithm returned: {}'.format(json.dumps(ret,
indent=4)))
convert_json_to_dict(ret)
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 ACQUAChemistryError("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 ACQUAChemistryError("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 InputParser.NAME in p.get_section_names():
name_sect = p.get_section(InputParser.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,
InputParser.NAME)
if driver_name is None:
raise ACQUAChemistryError(
'Property "{0}" missing in section "{1}"'.format(
InputParser.NAME, InputParser.DRIVER))
hdf5_file = p.get_section_property(InputParser.DRIVER,
ACQUAChemistry.KEY_HDF5_OUTPUT)
section = p.get_section(driver_name)
if 'data' not in section:
raise ACQUAChemistryError(
'Property "data" missing in section "{0}"'.format(driver_name))
if driver_name not in self._configuration_mgr.module_names:
raise ACQUAChemistryError(
'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 ACQUAChemistry._DRIVER_RUN_TO_HDF5, text
# Run the Hamiltonian to process the QMolecule and get an input for algorithms
self._core = get_chemistry_operator_instance(
p.get_section_property(InputParser.OPERATOR, InputParser.NAME))
self._core.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 == InputParser.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 InputParser.PROBLEM == section_name and \
InputParser.ENABLE_SUBSTITUTIONS in params[section_name]:
del params[section_name][InputParser.ENABLE_SUBSTITUTIONS]
return ACQUAChemistry._DRIVER_RUN_TO_ALGO_INPUT, params, input_object