def test_load_dataset_from_cache(self, tmp_path):
tmp_path = str(tmp_path)
ds = io_gen.ds
io.write_dataset(tmp_path, ds)
ds3 = readers.read_dataset(tmp_path, cache=True) # creates cache file
ds4 = readers.read_dataset(tmp_path, cache=True) # loads from cache file
# TODO assert cache behavior
ds.comment = "# Hello" # comment character doesn't get doubled...
io.write_dataset(tmp_path, ds)
ds5 = readers.read_dataset(tmp_path, cache=True) # rewrites cache file
for s in ds:
self.assertEqual(ds[s]['0'], ds5[s][('0',)])
self.assertEqual(ds[s]['1'], ds5[s][('1',)])
def test_stdpractice_gst_file_args(self, ds_path, model_path,
fiducial_path, germ_path):
io.write_dataset(ds_path, self.ds, self.lsgstStrings[-1])
io.write_model(self.model, model_path)
io.write_circuit_list(fiducial_path, self.fiducials)
io.write_circuit_list(germ_path, self.germs)
result = ls.do_stdpractice_gst(ds_path,
model_path,
fiducial_path,
fiducial_path,
germ_path,
self.maxLens,
modes="TP",
comm=None,
memLimit=None,
verbosity=5)
def test_long_sequence_gst_with_file_args(self, ds_path, model_path,
fiducial_path, germ_path):
io.write_dataset(ds_path, self.ds, self.lsgstStrings[-1])
io.write_model(self.model, model_path)
io.write_circuit_list(fiducial_path, self.fiducials)
io.write_circuit_list(germ_path, self.germs)
self.options.update(randomizeStart=1e-6,
profile=2,
verbosity=10,
memoryLimitInBytes=2 * 1000**3)
result = ls.do_long_sequence_gst(ds_path,
model_path,
fiducial_path,
fiducial_path,
germ_path,
self.maxLens,
advancedOptions=self.options)
def test_long_sequence_gst_with_file_args(self, ds_path, model_path,
fiducial_path, germ_path):
io.write_dataset(ds_path, self.ds, self.lsgstStrings[-1])
io.write_model(self.model, model_path)
io.write_circuit_list(fiducial_path, self.fiducials)
io.write_circuit_list(germ_path, self.germs)
self.options.update(
randomize_start=1e-6,
profile=2,
)
result = ls.run_long_sequence_gst(ds_path,
model_path,
fiducial_path,
fiducial_path,
germ_path,
self.maxLens,
advanced_options=self.options,
verbosity=10)
def test_stdpractice_gst_file_args(self, ds_path, model_path,
fiducial_path, germ_path):
import pickle
#io.write_model(self.model, model_path)
io.write_dataset(ds_path, self.ds, self.lsgstStrings[-1])
io.write_circuit_list(fiducial_path, self.fiducials)
io.write_circuit_list(germ_path, self.germs)
target_model = create_explicit_model(self.pspec,
ideal_gate_type='static')
io.write_model(target_model, model_path)
#with open(model_path, 'wb') as f:
# pickle.dump(target_model, f)
result = ls.run_stdpractice_gst(ds_path,
model_path,
fiducial_path,
fiducial_path,
germ_path,
self.maxLens,
modes="full TP",
comm=None,
mem_limit=None,
verbosity=5)
def test_load_ignore_zero_count_lines4(self, pth):
c1 = Circuit('Gc1')
c2 = Circuit('Gc2')
c3 = Circuit('Gc3')
ds = DataSet()
ds.add_count_dict(c1, {}, aux={'test': 1})
ds.add_count_dict(c2, {'0': 1}, aux={'test': 1})
ds.add_count_dict(c3, {}, aux={'test': 1})
#print(ds)
io.write_dataset(pth, ds, fixed_column_mode=False)
ds = io.read_dataset(pth, ignore_zero_count_lines=False)
self.assertEqual(ds[c1]['0'], 0)
self.assertEqual(ds[c2]['0'], 1)
self.assertEqual(
ds[c3]['0'],
0) # especially make sure last line is read in properly!
self.assertEqual(ds[c1].aux['test'], 1)
self.assertEqual(ds[c2].aux['test'], 1)
self.assertEqual(ds[c3].aux['test'], 1)
def write_benchmarker(benchmarker, outdir, overwrite=False, verbosity=0):
try:
_os.makedirs(outdir)
if verbosity > 0:
print(" - Created `" + outdir +
"` folder to store benchmarker in txt format.")
except:
if overwrite:
if verbosity > 0:
print(
" - `" + outdir +
"` folder already exists. Will write data into that folder."
)
else:
raise ValueError(
"Directory already exists! Set overwrite to True or change the directory name!"
)
globaldict = {}
globaldict['speckeys'] = benchmarker._speckeys
globaldict['numpasses'] = benchmarker.numpasses
globaldict['success_outcome'] = benchmarker.success_outcome
globaldict['success_key'] = benchmarker.success_key
if benchmarker.dscomparator is not None:
globaldict['dscomparator'] = {}
globaldict['dscomparator'][
'pVal_pseudothreshold'] = benchmarker.dscomparator.pVal_pseudothreshold
globaldict['dscomparator'][
'llr_pseudothreshold'] = benchmarker.dscomparator.llr_pseudothreshold
globaldict['dscomparator'][
'pVal_pseudothreshold'] = benchmarker.dscomparator.pVal_pseudothreshold
globaldict['dscomparator'][
'jsd_pseudothreshold'] = benchmarker.dscomparator.jsd_pseudothreshold
globaldict['dscomparator'][
'aggregate_llr'] = benchmarker.dscomparator.aggregate_llr
globaldict['dscomparator'][
'aggregate_llr_threshold'] = benchmarker.dscomparator.aggregate_llr_threshold
globaldict['dscomparator'][
'aggregate_nsigma'] = benchmarker.dscomparator.aggregate_nsigma
globaldict['dscomparator'][
'aggregate_nsigma_threshold'] = benchmarker.dscomparator.aggregate_nsigma_threshold
globaldict['dscomparator'][
'aggregate_pVal'] = benchmarker.dscomparator.aggregate_pVal
globaldict['dscomparator'][
'aggregate_pVal_threshold'] = benchmarker.dscomparator.aggregate_pVal_threshold
globaldict['dscomparator']['inconsistent_datasets_detected'] = \
benchmarker.dscomparator.inconsistent_datasets_detected
globaldict['dscomparator']['number_of_significant_sequences'] = int(
benchmarker.dscomparator.number_of_significant_sequences)
globaldict['dscomparator'][
'significance'] = benchmarker.dscomparator.significance
else:
globaldict['dscomparator'] = None
# Write global details to file
with open(outdir + '/global.txt', 'w') as f:
_json.dump(globaldict, f, indent=4)
_os.makedirs(outdir + '/specs')
_os.makedirs(outdir + '/summarydata')
_os.makedirs(outdir + '/aux')
for pkey in benchmarker.predicted_summary_data.keys():
_os.makedirs(outdir + '/predictions/{}/summarydata'.format(pkey))
for i, spec in enumerate(benchmarker._specs):
structure = spec.get_structure()
write_benchmarkspec(spec,
outdir + '/specs/{}.txt'.format(i),
warning=0)
for j, qubits in enumerate(structure):
summarydict = {
'pass': benchmarker.pass_summary_data[i][qubits],
'global': benchmarker.global_summary_data[i][qubits]
}
fname = outdir + '/summarydata/' + '{}-{}.txt'.format(i, j)
with open(fname, 'w') as f:
_json.dump(summarydict, f, indent=4)
aux = benchmarker.aux[i][qubits]
fname = outdir + '/aux/' + '{}-{}.txt'.format(i, j)
with open(fname, 'w') as f:
_json.dump(aux, f, indent=4)
for pkey in benchmarker.predicted_summary_data.keys():
summarydict = benchmarker.predicted_summary_data[pkey][i][
qubits]
fname = outdir + '/predictions/{}/summarydata/'.format(
pkey) + '{}-{}.txt'.format(i, j)
with open(fname, 'w') as f:
_json.dump(summarydict, f, indent=4)
for dskey in benchmarker.multids.keys():
fdir = outdir + '/data/{}'.format(dskey)
_os.makedirs(fdir)
for dsind in benchmarker.multids[dskey].keys():
fname = fdir + '/ds{}.txt'.format(dsind)
_io.write_dataset(fname,
benchmarker.multids[dskey][dsind],
fixed_column_mode=False)