def test_numpy_types():
"""
Test that we can save numpy types in the data set
"""
p = ParamSpecBase(name="p", paramtype="numeric")
test_set = qc.new_data_set("test-dataset")
test_set.set_interdependencies(InterDependencies_(standalones=(p, )))
test_set.mark_started()
idps = InterDependencies_(standalones=(p, ))
data_saver = DataSaver(dataset=test_set, write_period=0, interdeps=idps)
dtypes = [
np.int8, np.int16, np.int32, np.int64, np.float16, np.float32,
np.float64
]
for dtype in dtypes:
data_saver.add_result(("p", dtype(2)))
data_saver.flush_data_to_database()
data = test_set.get_data("p")
assert data == [[2] for _ in range(len(dtypes))]
def test_numpy_types(bg_writing):
"""
Test that we can save numpy types in the data set
"""
p = ParamSpecBase(name="p", paramtype="numeric")
test_set = qc.new_data_set("test-dataset")
test_set.set_interdependencies(InterDependencies_(standalones=(p, )))
test_set.mark_started(start_bg_writer=bg_writing)
idps = InterDependencies_(standalones=(p, ))
data_saver = DataSaver(dataset=test_set,
write_period=0,
interdeps=idps,
write_in_background=bg_writing)
dtypes = [
np.int8, np.int16, np.int32, np.int64, np.float16, np.float32,
np.float64
]
for dtype in dtypes:
data_saver.add_result(("p", dtype(2)))
data_saver.flush_data_to_database()
test_set.mark_completed()
data = test_set.get_parameter_data("p")["p"]["p"]
expected_data = np.ones(len(dtypes))
expected_data[:] = 2
np.testing.assert_array_equal(data, expected_data)
def test_saving_numeric_values_as_text(numeric_type):
"""
Test the saving numeric values into 'text' parameter raises an exception
"""
p = ParamSpecBase("p", "text")
test_set = qc.new_data_set("test-dataset")
test_set.set_interdependencies(InterDependencies_(standalones=(p, )))
test_set.mark_started()
idps = InterDependencies_(standalones=(p, ))
data_saver = DataSaver(dataset=test_set, write_period=0, interdeps=idps)
try:
value = numeric_type(2)
gottype = np.array(value).dtype
msg = re.escape(f'Parameter {p.name} is of type '
f'"{p.type}", but got a result of '
f'type {gottype} ({value}).')
with pytest.raises(ValueError, match=msg):
data_saver.add_result((p.name, value))
finally:
data_saver.dataset.conn.close()
def test_string_with_wrong_paramtype_via_datasaver(experiment):
"""
Test that it is not possible to add a string value for a non-text
parameter via DataSaver object
"""
p = ParamSpecBase("p", "numeric")
test_set = qc.new_data_set("test-dataset")
idps = InterDependencies_(standalones=(p, ))
test_set.set_interdependencies(idps)
test_set.mark_started()
idps = InterDependencies_(standalones=(p, ))
data_saver = DataSaver(dataset=test_set,
write_period=0,
interdeps=idps,
write_in_background=False)
try:
msg = re.escape('Parameter p is of type "numeric", but got a '
"result of type <U9 (some text).")
with pytest.raises(ValueError, match=msg):
data_saver.add_result(("p", "some text"))
finally:
data_saver.dataset.conn.close()
def test_string(experiment):
"""
Test that we can save text in the data set
"""
p = ParamSpec("p", "text")
test_set = qc.new_data_set("test-dataset")
test_set.add_parameter(p)
data_saver = DataSaver(dataset=test_set,
write_period=0,
parameters={"p": p})
data_saver.add_result(("p", "some text"))
data_saver.flush_data_to_database()
assert test_set.get_data("p") == [["some text"]]
def store_array_to_database(datasaver: DataSaver, array: DataArray) -> int:
dims = len(array.shape)
if dims == 2:
for index1, i in enumerate(array.set_arrays[0]):
for index2, j in enumerate(array.set_arrays[1][index1]):
datasaver.add_result((array.set_arrays[0].array_id, i),
(array.set_arrays[1].array_id, j),
(array.array_id, array[index1, index2]))
elif dims == 1:
for index, i in enumerate(array.set_arrays[0]):
datasaver.add_result((array.set_arrays[0].array_id, i),
(array.array_id, array[index]))
else:
raise NotImplementedError(
'The exporter only currently handles 1 and 2 Dimentional data')
return datasaver.run_id
def test_string_via_datasaver(experiment):
"""
Test that we can save text into database via DataSaver API
"""
p = ParamSpecBase(name="p", paramtype="text")
test_set = qc.new_data_set("test-dataset")
idps = InterDependencies_(standalones=(p, ))
test_set.prepare(snapshot={}, interdeps=idps)
idps = InterDependencies_(standalones=(p, ))
data_saver = DataSaver(dataset=test_set, write_period=0, interdeps=idps)
data_saver.add_result(("p", "some text"))
data_saver.flush_data_to_database()
assert test_set.get_parameter_data()["p"]["p"] == np.array(["some text"])
def test_string_via_datasaver(experiment):
"""
Test that we can save text into database via DataSaver API
"""
p = ParamSpec(name="p", paramtype="text")
test_set = qc.new_data_set("test-dataset")
test_set.add_parameter(p)
test_set.mark_started()
idps = InterDependencies_(standalones=(p.base_version(), ))
data_saver = DataSaver(dataset=test_set, write_period=0, interdeps=idps)
data_saver.add_result(("p", "some text"))
data_saver.flush_data_to_database()
assert test_set.get_data("p") == [["some text"]]
def test_saving_numeric_values_as_text(numeric_type):
"""
Test the saving numeric values into 'text' parameter raises an exception
"""
p = ParamSpec("p", "text")
test_set = qc.new_data_set("test-dataset")
test_set.add_parameter(p)
test_set.mark_started()
data_saver = DataSaver(
dataset=test_set, write_period=0, parameters={"p": p})
try:
msg = f"It is not possible to save a numeric value for parameter " \
f"'{p.name}' because its type class is 'text', not 'numeric'."
with pytest.raises(ValueError, match=msg):
data_saver.add_result((p.name, numeric_type(2)))
finally:
data_saver.dataset.conn.close()
def test_string_with_wrong_paramtype_via_datasaver(experiment):
"""
Test that it is not possible to add a string value for a non-text
parameter via DataSaver object
"""
p = ParamSpec("p", "numeric")
test_set = qc.new_data_set("test-dataset")
test_set.add_parameter(p)
data_saver = DataSaver(
dataset=test_set, write_period=0, parameters={"p": p})
try:
msg = "It is not possible to save a string value for parameter 'p' " \
"because its type class is 'numeric', not 'text'."
with pytest.raises(ValueError, match=msg):
data_saver.add_result(("p", "some text"))
finally:
data_saver.dataset.conn.close()
def test_numpy_types():
"""
Test that we can save numpy types in the data set
"""
p = ParamSpec("p", "numeric")
test_set = qc.new_data_set("test-dataset")
test_set.add_parameter(p)
test_set.mark_started()
data_saver = DataSaver(
dataset=test_set, write_period=0, parameters={"p": p})
dtypes = [np.int8, np.int16, np.int32, np.int64, np.float16, np.float32,
np.float64]
for dtype in dtypes:
data_saver.add_result(("p", dtype(2)))
data_saver.flush_data_to_database()
data = test_set.get_data("p")
assert data == [[2] for _ in range(len(dtypes))]
def test_duplicated_parameter_raises():
"""
Test that passing same parameter multiple times to ``add_result`` raises an exception
"""
p = ParamSpecBase("p", "text")
test_set = qc.new_data_set("test-dataset")
test_set.set_interdependencies(InterDependencies_(standalones=(p, )))
test_set.mark_started()
idps = InterDependencies_(standalones=(p, ))
data_saver = DataSaver(dataset=test_set, write_period=0, interdeps=idps)
try:
msg = re.escape(
"Not all parameter names are unique. Got multiple values for ['p']"
)
with pytest.raises(ValueError, match=msg):
data_saver.add_result((p.name, 1), (p.name, 1))
finally:
data_saver.dataset.mark_completed()
data_saver.dataset.conn.close()