def test_perform_actual_upgrade_6_to_7():
fixpath = os.path.join(fixturepath, 'db_files', 'version6')
db_file = 'some_runs.db'
dbname_old = os.path.join(fixpath, db_file)
if not os.path.exists(dbname_old):
pytest.skip("No db-file fixtures found. You can generate test db-files"
" using the scripts in the "
"https://github.com/QCoDeS/qcodes_generate_test_db/ repo")
with temporarily_copied_DB(dbname_old, debug=False, version=6) as conn:
assert isinstance(conn, ConnectionPlus)
perform_db_upgrade_6_to_7(conn)
assert get_user_version(conn) == 7
no_of_runs_query = "SELECT max(run_id) FROM runs"
no_of_runs = one(atomic_transaction(conn, no_of_runs_query),
'max(run_id)')
assert no_of_runs == 10
columns = atomic_transaction(conn,
"PRAGMA table_info(runs)").fetchall()
col_names = [col['name'] for col in columns]
assert 'captured_run_id' in col_names
assert 'captured_counter' in col_names
for run_id in range(1, no_of_runs + 1):
ds1 = load_by_id(run_id, conn)
ds2 = load_by_run_spec(captured_run_id=run_id, conn=conn)
assert ds1.the_same_dataset_as(ds2)
assert ds1.run_id == run_id
assert ds1.run_id == ds1.captured_run_id
assert ds2.run_id == run_id
assert ds2.run_id == ds2.captured_run_id
exp_id = 1
for counter in range(1, no_of_runs + 1):
ds1 = load_by_counter(counter, exp_id, conn)
ds2 = load_by_run_spec(captured_counter=counter, conn=conn)
assert ds1.the_same_dataset_as(ds2)
assert ds1.counter == counter
assert ds1.counter == ds1.captured_counter
assert ds2.counter == counter
assert ds2.counter == ds2.captured_counter
def plot_by_id(
run_id: int,
axes: Optional[Union[matplotlib.axes.Axes,
Sequence[matplotlib.axes.Axes]]] = None,
colorbars: Optional[Union[matplotlib.colorbar.Colorbar,
Sequence[matplotlib.colorbar.Colorbar]]] = None,
rescale_axes: bool = True,
auto_color_scale: Optional[bool] = None,
cutoff_percentile: Optional[Union[Tuple[float, float], float]] = None,
complex_plot_type: str = "real_and_imag",
complex_plot_phase: str = "radians",
**kwargs: Any,
) -> AxesTupleList:
"""
Construct all plots for a given `run_id`. Here `run_id` is an
alias for `captured_run_id` for historical reasons. See the docs
of :func:`.load_by_run_spec` for details of loading runs.
All other arguments are forwarded
to :func:`.plot_dataset`, see this for more details.
"""
dataset = load_by_run_spec(captured_run_id=run_id)
return plot_dataset(dataset, axes, colorbars, rescale_axes,
auto_color_scale, cutoff_percentile, complex_plot_type,
complex_plot_phase, **kwargs)
def export_all_datasets(self):
directory = QFileDialog.getExistingDirectory(
self, "Save Data to .csv",
f'{os.environ["MeasureItHome"]}\\Origin Files\\')
if len(directory) == 0:
return
unsaved_sets = []
for ds_info in self.datasets:
try:
ds = load_by_run_spec(experiment_name=ds_info['exp name'],
sample_name=ds_info['sample name'],
captured_run_id=ds_info['run id'])
filename = f"{directory}\\{ds.run_id}_{ds.exp_name}_{ds.sample_name}.csv"
save_to_csv(ds, filename)
except:
unsaved_sets.append(
f"{ds.run_id}_{ds.exp_name}_{ds.sample_name}")
if len(unsaved_sets) > 0:
error_text = 'Failed to export the following datasets:\n\n'
for i, ds in enumerate(unsaved_sets):
error_text += ds
if i + 1 != len(unsaved_sets):
error_text += ', '
error_text += '.\n\nThis is possibly due to a file name conflict or due to no data being stored in that run.'
self.show_error('Error', error_text)
def get_dataset_by_identifier(identifier: Union[int, str]):
"""
returns a dataset for a given identifier
identifier (str or int): run_id or guid
"""
if isinstance(identifier, int):
dataset = load_by_run_spec(captured_run_id=identifier)
elif isinstance(identifier, str):
validate_guid_format(identifier)
dataset = load_by_guid(identifier)
return dataset
def test_load_by_X_functions(two_empty_temp_db_connections,
some_interdeps):
"""
Test some different loading functions
"""
source_conn, target_conn = two_empty_temp_db_connections
source_path = path_to_dbfile(source_conn)
target_path = path_to_dbfile(target_conn)
source_exp1 = Experiment(conn=source_conn)
source_ds_1_1 = DataSet(conn=source_conn, exp_id=source_exp1.exp_id)
source_exp2 = Experiment(conn=source_conn)
source_ds_2_1 = DataSet(conn=source_conn, exp_id=source_exp2.exp_id)
source_ds_2_2 = DataSet(conn=source_conn,
exp_id=source_exp2.exp_id,
name="customname")
for ds in (source_ds_1_1, source_ds_2_1, source_ds_2_2):
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
extract_runs_into_db(source_path, target_path, source_ds_2_2.run_id)
extract_runs_into_db(source_path, target_path, source_ds_2_1.run_id)
extract_runs_into_db(source_path, target_path, source_ds_1_1.run_id)
test_ds = load_by_guid(source_ds_2_2.guid, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_id(1, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
test_ds = load_by_run_spec(captured_run_id=source_ds_2_2.captured_run_id,
conn=target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
assert source_exp2.exp_id == 2
# this is now the first run in the db so run_id is 1
target_run_id = 1
# and the experiment ids will be interchanged.
target_exp_id = 1
test_ds = load_by_counter(target_run_id, target_exp_id, target_conn)
assert source_ds_2_2.the_same_dataset_as(test_ds)
def test_perform_actual_upgrade_6_to_newest_add_new_data():
"""
Insert new runs on top of existing runs upgraded and verify that they
get the correct captured_run_id and captured_counter
"""
from qcodes.dataset.measurements import Measurement
from qcodes.instrument.parameter import Parameter
import numpy as np
fixpath = os.path.join(fixturepath, 'db_files', 'version6')
db_file = 'some_runs.db'
dbname_old = os.path.join(fixpath, db_file)
if not os.path.exists(dbname_old):
pytest.skip("No db-file fixtures found. You can generate test db-files"
" using the scripts in the "
"https://github.com/QCoDeS/qcodes_generate_test_db/ repo")
with temporarily_copied_DB(dbname_old, debug=False, version=6) as conn:
assert isinstance(conn, ConnectionPlus)
perform_db_upgrade(conn)
assert get_user_version(conn) >= 7
no_of_runs_query = "SELECT max(run_id) FROM runs"
no_of_runs = one(
atomic_transaction(conn, no_of_runs_query), 'max(run_id)')
# Now let's insert new runs and ensure that they also get
# captured_run_id assigned.
params = []
for n in range(5):
params.append(Parameter(f'p{n}', label=f'Parameter {n}',
unit=f'unit {n}', set_cmd=None,
get_cmd=None))
# Set up an experiment
exp = new_experiment('some-exp', 'some-sample', conn=conn)
meas = Measurement(exp=exp)
meas.register_parameter(params[0])
meas.register_parameter(params[1])
meas.register_parameter(params[2], basis=(params[0],))
meas.register_parameter(params[3], basis=(params[1],))
meas.register_parameter(params[4], setpoints=(params[2], params[3]))
# Make a number of identical runs
for _ in range(10):
with meas.run() as datasaver:
for x in np.random.rand(10):
for y in np.random.rand(10):
z = np.random.rand()
datasaver.add_result((params[0], 0),
(params[1], 1),
(params[2], x),
(params[3], y),
(params[4], z))
no_of_runs_new = one(
atomic_transaction(conn, no_of_runs_query), 'max(run_id)')
assert no_of_runs_new == 20
# check that run_id is equivalent to captured_run_id for new
# runs
for run_id in range(no_of_runs, no_of_runs_new + 1):
ds1 = load_by_id(run_id, conn)
ds2 = load_by_run_spec(captured_run_id=run_id, conn=conn)
assert ds1.the_same_dataset_as(ds2)
assert ds1.run_id == run_id
assert ds1.run_id == ds1.captured_run_id
assert ds2.run_id == run_id
assert ds2.run_id == ds2.captured_run_id
# we are creating a new experiment into a db with one exp so:
exp_id = 2
# check that counter is equivalent to captured_counter for new
# runs
for counter in range(1, no_of_runs_new - no_of_runs + 1):
ds1 = load_by_counter(counter, exp_id, conn)
# giving only the counter is not unique since we have 2 experiments
with pytest.raises(NameError, match="More than one"
" matching dataset"):
load_by_run_spec(captured_counter=counter, conn=conn)
# however we can supply counter and experiment
ds2 = load_by_run_spec(captured_counter=counter,
experiment_name='some-exp',
conn=conn)
assert ds1.the_same_dataset_as(ds2)
assert ds1.counter == counter
assert ds1.counter == ds1.captured_counter
assert ds2.counter == counter
assert ds2.counter == ds2.captured_counter
def test_load_by_run_spec(empty_temp_db, some_interdeps):
def create_ds_with_exp_id(exp_id):
ds = DataSet(exp_id=exp_id)
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{'ps1': 1, 'ps2': 2}])
return ds
# create 3 experiments that mix two experiment names and two sample names
exp_names = ["te1", "te2", "te1"]
sample_names = ["ts1", "ts2", "ts2"]
exps = [
new_experiment(exp_name, sample_name=sample_name)
for exp_name, sample_name in zip(exp_names, sample_names)
]
created_ds = [create_ds_with_exp_id(exp.exp_id) for exp in exps]
conn = created_ds[0].conn
guids = get_guids_from_run_spec(conn=conn)
assert len(guids) == 3
# since we are not copying runs from multiple dbs we can always load by
# captured_run_id and this is equivalent to load_by_id
for i in range(1, 4):
loaded_ds = load_by_run_spec(captured_run_id=i, conn=conn)
assert loaded_ds.guid == guids[i - 1]
assert loaded_ds.the_same_dataset_as(created_ds[i - 1])
# All the datasets datasets have the same captured counter
# so we cannot load by that alone
guids_cc1 = get_guids_from_run_spec(captured_counter=1, conn=conn)
assert len(guids_cc1) == 3
with pytest.raises(NameError, match="More than one matching"):
load_by_run_spec(captured_counter=1)
# there are two different experiments with exp name "test-experiment1"
# and thus 2 different datasets with counter=1 and that exp name
guids_cc1_te1 = get_guids_from_run_spec(captured_counter=1,
experiment_name='te1',
conn=conn)
assert len(guids_cc1_te1) == 2
with pytest.raises(NameError, match="More than one matching"):
load_by_run_spec(captured_counter=1, experiment_name="te1", conn=conn)
# but for "test-experiment2" there is only one
guids_cc1_te2 = get_guids_from_run_spec(captured_counter=1,
experiment_name='te2',
conn=conn)
assert len(guids_cc1_te2) == 1
loaded_ds = load_by_run_spec(captured_counter=1,
experiment_name="te2",
conn=conn)
assert loaded_ds.guid == guids_cc1_te2[0]
assert loaded_ds.the_same_dataset_as(created_ds[1])
# there are two different experiments with sample name "test_sample2" but
# different exp names so the counter is not unique
guids_cc1_ts2 = get_guids_from_run_spec(captured_counter=1,
sample_name='ts2',
conn=conn)
assert len(guids_cc1_ts2) == 2
with pytest.raises(NameError, match="More than one matching"):
load_by_run_spec(captured_counter=1, sample_name="ts2", conn=conn)
# but for "test_sample1" there is only one
guids_cc1_ts1 = get_guids_from_run_spec(captured_counter=1,
sample_name='ts1',
conn=conn)
assert len(guids_cc1_ts1) == 1
loaded_ds = load_by_run_spec(captured_counter=1,
sample_name="ts1",
conn=conn)
assert loaded_ds.the_same_dataset_as(created_ds[0])
assert loaded_ds.guid == guids_cc1_ts1[0]
# we can load all 3 if we are specific.
for i in range(3):
loaded_ds = load_by_run_spec(captured_counter=1,
experiment_name=exp_names[i],
sample_name=sample_names[i],
conn=conn)
assert loaded_ds.the_same_dataset_as(created_ds[i])
assert loaded_ds.guid == guids[i]
# load a non-existing run
with pytest.raises(NameError, match="No run matching"):
load_by_run_spec(captured_counter=10000, sample_name="ts2", conn=conn)
empty_guid_list = get_guids_from_run_spec(conn=conn,
experiment_name='nosuchexp')
assert empty_guid_list == []
def test_copy_datasets_and_add_new(two_empty_temp_db_connections,
some_interdeps):
"""
Test that new runs get the correct captured_run_id and captured_counter
when adding on top of a dataset with partial exports
"""
source_conn, target_conn = two_empty_temp_db_connections
source_exp_1 = Experiment(conn=source_conn,
name='exp1',
sample_name='no_sample')
source_exp_2 = Experiment(conn=source_conn,
name='exp2',
sample_name='no_sample')
source_datasets_1 = [
DataSet(conn=source_conn, exp_id=source_exp_1.exp_id) for i in range(5)
]
source_datasets_2 = [
DataSet(conn=source_conn, exp_id=source_exp_2.exp_id) for i in range(5)
]
source_datasets = source_datasets_1 + source_datasets_2
for ds in source_datasets:
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
# now let's insert only some of the datasets
# and verify that the ids and counters are set correctly
for ds in source_datasets[-3:]:
extract_runs_into_db(ds.conn.path_to_dbfile,
target_conn.path_to_dbfile, ds.run_id)
loaded_datasets = [
load_by_run_spec(captured_run_id=i, conn=target_conn)
for i in range(8, 11)
]
expected_run_ids = [1, 2, 3]
expected_captured_run_ids = [8, 9, 10]
expected_counter = [1, 2, 3]
expected_captured_counter = [3, 4, 5]
for ds, eri, ecri, ec, ecc in zip(loaded_datasets, expected_run_ids,
expected_captured_run_ids,
expected_counter,
expected_captured_counter):
assert ds.run_id == eri
assert ds.captured_run_id == ecri
assert ds.counter == ec
assert ds.captured_counter == ecc
exp = load_experiment_by_name('exp2', conn=target_conn)
# add additional runs and verify that the ids and counters increase as
# expected
new_datasets = [
DataSet(conn=target_conn, exp_id=exp.exp_id) for i in range(3)
]
for ds in new_datasets:
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
expected_run_ids = [4, 5, 6]
expected_captured_run_ids = [11, 12, 13]
expected_counter = [4, 5, 6]
expected_captured_counter = [6, 7, 8]
for ds, eri, ecri, ec, ecc in zip(new_datasets, expected_run_ids,
expected_captured_run_ids,
expected_counter,
expected_captured_counter):
assert ds.run_id == eri
assert ds.captured_run_id == ecri
assert ds.counter == ec
assert ds.captured_counter == ecc
def test_combine_runs(two_empty_temp_db_connections, empty_temp_db_connection,
some_interdeps):
"""
Test that datasets that are exported in random order from 2 datasets
can be reloaded by the original captured_run_id and the experiment
name.
"""
source_conn_1, source_conn_2 = two_empty_temp_db_connections
target_conn = empty_temp_db_connection
source_1_exp = Experiment(conn=source_conn_1,
name='exp1',
sample_name='no_sample')
source_1_datasets = [
DataSet(conn=source_conn_1, exp_id=source_1_exp.exp_id)
for i in range(10)
]
source_2_exp = Experiment(conn=source_conn_2,
name='exp2',
sample_name='no_sample')
source_2_datasets = [
DataSet(conn=source_conn_2, exp_id=source_2_exp.exp_id)
for i in range(10)
]
source_all_datasets = source_1_datasets + source_2_datasets
shuffled_datasets = source_all_datasets.copy()
random.shuffle(shuffled_datasets)
for ds in source_all_datasets:
ds.set_interdependencies(some_interdeps[1])
ds.mark_started()
ds.add_results([{name: 0.0 for name in some_interdeps[1].names}])
ds.mark_completed()
# now let's insert all datasets in random order
for ds in shuffled_datasets:
extract_runs_into_db(ds.conn.path_to_dbfile,
target_conn.path_to_dbfile, ds.run_id)
for ds in source_all_datasets:
loaded_ds = load_by_run_spec(captured_run_id=ds.captured_run_id,
experiment_name=ds.exp_name,
conn=target_conn)
assert ds.the_same_dataset_as(loaded_ds)
for ds in source_all_datasets:
loaded_ds = load_by_run_spec(captured_run_id=ds.captured_counter,
experiment_name=ds.exp_name,
conn=target_conn)
assert ds.the_same_dataset_as(loaded_ds)
# Now test that we generate the correct table for the guids above
# this could be split out into its own test
# but the test above has the useful side effect of
# setting up datasets for this test.
guids = [ds.guid for ds in source_all_datasets]
table = generate_dataset_table(guids, conn=target_conn)
lines = table.split('\n')
headers = re.split(r'\s+', lines[0].strip())
cfg = qc.config
guid_comp = cfg['GUID_components']
# borrowed fallback logic from generate_guid
sampleint = guid_comp['sample']
if sampleint == 0:
sampleint = int('a' * 8, base=16)
for i in range(2, len(lines)):
split_line = re.split(r'\s+', lines[i].strip())
mydict = {headers[j]: split_line[j] for j in range(len(split_line))}
ds = load_by_guid(guids[i - 2], conn=target_conn)
assert ds.captured_run_id == int(mydict['captured_run_id'])
assert ds.captured_counter == int(mydict['captured_counter'])
assert ds.exp_name == mydict['experiment_name']
assert ds.sample_name == mydict['sample_name']
assert int(mydict['sample_id']) == sampleint
assert guid_comp['location'] == int(mydict['location'])
assert guid_comp['work_station'] == int(mydict['work_station'])
