def test_modify_results(dataset):
xparam = ParamSpec("x", "numeric")
dataset.add_parameter(xparam)
dataset.add_result({'x': 0})
dataset.add_result({'x': 1})
pytest.deprecated_call(dataset.modify_results, 0, [{'x': [10]}])
assert [[10], [1]] == dataset.get_data(xparam)
pytest.deprecated_call(dataset.modify_results, 1, [{'x': [14]}])
assert [[10], [14]] == dataset.get_data(xparam)
with pytest.raises(RuntimeError,
match='Rolling back due to unhandled exception'):
# not sure calling `modify_results` like this is correct, anyway it
# is difficult to find out what the call signature for multiple
# results is supposed to look like...
pytest.deprecated_call(dataset.modify_results, 0, [{
'x': [5]
}, {
'x': [6]
}])
assert [[5], [6]] == dataset.get_data(xparam)
pytest.xfail('modify_results does not seem to work for cases where '
'multiple values of multiple parameters need to be changed. '
'Anyway, the signature needs to be revisited, '
'and consequently the correct behavior needs to be '
'implemented and covered with tests.')
def test_numpy_nan(dataset):
parameter_m = ParamSpec("m", "numeric")
dataset.add_parameters([parameter_m])
data_dict = [{"m": value} for value in [0.0, np.nan, 1.0]]
dataset.add_results(data_dict)
retrieved = dataset.get_data("m")
assert np.isnan(retrieved[1])
def test_numpy_nan(dataset):
parameter_m = ParamSpecBase("m", "numeric")
idps = InterDependencies_(standalones=(parameter_m, ))
dataset.set_interdependencies(idps)
dataset.mark_started()
data_dict = [{"m": value} for value in [0.0, np.nan, 1.0]]
dataset.add_results(data_dict)
retrieved = dataset.get_data("m")
assert np.isnan(retrieved[1])
def test_numpy_inf(dataset):
"""
Test that we can insert and retrieve numpy inf in the data set
"""
parameter_m = ParamSpec("m", "numeric")
dataset.add_parameter(parameter_m)
dataset.mark_started()
data_dict = [{"m": value} for value in [-np.inf, np.inf]]
dataset.add_results(data_dict)
retrieved = dataset.get_data("m")
assert np.isinf(retrieved).all()
def test_numpy_floats(dataset):
"""
Test that we can insert numpy floats in the data set
"""
float_param = ParamSpec('y', 'numeric')
dataset.add_parameters([float_param])
numpy_floats = [np.float, np.float16, np.float32, np.float64]
results = [{"y": tp(1.2)} for tp in numpy_floats]
dataset.add_results(results)
expected_result = [[tp(1.2)] for tp in numpy_floats]
assert np.allclose(dataset.get_data("y"), expected_result, atol=1E-8)
def test_numpy_inf(dataset):
"""
Test that we can insert and retrieve numpy inf in the data set
"""
parameter_m = ParamSpecBase("m", "numeric")
idps = InterDependencies_(standalones=(parameter_m, ))
dataset.set_interdependencies(idps)
dataset.mark_started()
data_dict = [{"m": value} for value in [-np.inf, np.inf]]
dataset.add_results(data_dict)
retrieved = dataset.get_data("m")
assert np.isinf(retrieved).all()
def test_modify_result(dataset):
xparam = ParamSpec("x", "numeric", label="x parameter", unit='V')
yparam = ParamSpec("y",
'numeric',
label='y parameter',
unit='Hz',
depends_on=[xparam])
zparam = ParamSpec("z",
'array',
label='z parameter',
unit='sqrt(Hz)',
depends_on=[xparam])
dataset.add_parameter(xparam)
dataset.add_parameter(yparam)
dataset.add_parameter(zparam)
xdata = 0
ydata = 1
zdata = np.linspace(0, 1, 100)
dataset.add_result({'x': 0, 'y': 1, 'z': zdata})
shadow_ds = make_shadow_dataset(dataset)
try:
assert dataset.get_data('x')[0][0] == xdata
assert dataset.get_data('y')[0][0] == ydata
assert (dataset.get_data('z')[0][0] == zdata).all()
assert shadow_ds.get_data('x')[0][0] == xdata
assert shadow_ds.get_data('y')[0][0] == ydata
assert (shadow_ds.get_data('z')[0][0] == zdata).all()
with pytest.raises(ValueError):
pytest.deprecated_call(dataset.modify_result, 0, {' x': 1})
xdata = 1
ydata = 12
zdata = np.linspace(0, 1, 99)
pytest.deprecated_call(dataset.modify_result, 0, {'x': xdata})
assert dataset.get_data('x')[0][0] == xdata
assert shadow_ds.get_data('x')[0][0] == xdata
pytest.deprecated_call(dataset.modify_result, 0, {'y': ydata})
assert dataset.get_data('y')[0][0] == ydata
assert shadow_ds.get_data('y')[0][0] == ydata
pytest.deprecated_call(dataset.modify_result, 0, {'z': zdata})
assert (dataset.get_data('z')[0][0] == zdata).all()
assert (shadow_ds.get_data('z')[0][0] == zdata).all()
dataset.mark_complete()
with pytest.raises(CompletedError):
pytest.deprecated_call(dataset.modify_result, 0, {'x': 2})
finally:
shadow_ds.conn.close()
def test_numpy_floats(dataset):
"""
Test that we can insert numpy floats in the data set
"""
float_param = ParamSpecBase('y', 'numeric')
idps = InterDependencies_(standalones=(float_param, ))
dataset.set_interdependencies(idps)
dataset.mark_started()
numpy_floats = [np.float, np.float16, np.float32, np.float64]
results = [{"y": tp(1.2)} for tp in numpy_floats]
dataset.add_results(results)
expected_result = [[tp(1.2)] for tp in numpy_floats]
assert np.allclose(dataset.get_data("y"), expected_result, atol=1E-8)
def test_numpy_ints(dataset):
"""
Test that we can insert numpy integers in the data set
"""
xparam = ParamSpec('x', 'numeric')
dataset.add_parameters([xparam])
numpy_ints = [
np.int, np.int8, np.int16, np.int32, np.int64,
np.uint, np.uint8, np.uint16, np.uint32, np.uint64
]
results = [{"x": tp(1)} for tp in numpy_ints]
dataset.add_results(results)
expected_result = len(numpy_ints) * [[1]]
assert dataset.get_data("x") == expected_result
def test_numpy_ints(dataset):
"""
Test that we can insert numpy integers in the data set
"""
xparam = ParamSpecBase('x', 'numeric')
idps = InterDependencies_(standalones=(xparam, ))
dataset.set_interdependencies(idps)
dataset.mark_started()
numpy_ints = [
np.int, np.int8, np.int16, np.int32, np.int64, np.uint, np.uint8,
np.uint16, np.uint32, np.uint64
]
results = [{"x": tp(1)} for tp in numpy_ints]
dataset.add_results(results)
expected_result = len(numpy_ints) * [[1]]
assert dataset.get_data("x") == expected_result
def test_modify_result():
dataset = new_data_set("test_modify_result")
xparam = ParamSpec("x", "numeric", label="x parameter", unit='V')
yparam = ParamSpec("y",
'numeric',
label='y parameter',
unit='Hz',
depends_on=[xparam])
zparam = ParamSpec("z",
'array',
label='z parameter',
unit='sqrt(Hz)',
depends_on=[xparam])
dataset.add_parameter(xparam)
dataset.add_parameter(yparam)
dataset.add_parameter(zparam)
xdata = 0
ydata = 1
zdata = np.linspace(0, 1, 100)
dataset.add_result({'x': 0, 'y': 1, 'z': zdata})
assert dataset.get_data('x')[0][0] == xdata
assert dataset.get_data('y')[0][0] == ydata
assert (dataset.get_data('z')[0][0] == zdata).all()
with pytest.raises(ValueError):
dataset.modify_result(0, {' x': 1})
xdata = 1
ydata = 12
zdata = np.linspace(0, 1, 99)
dataset.modify_result(0, {'x': xdata})
assert dataset.get_data('x')[0][0] == xdata
dataset.modify_result(0, {'y': ydata})
assert dataset.get_data('y')[0][0] == ydata
dataset.modify_result(0, {'z': zdata})
assert (dataset.get_data('z')[0][0] == zdata).all()
dataset.mark_complete()
with pytest.raises(CompletedError):
dataset.modify_result(0, {'x': 2})
def test_add_parameter_values(dataset):
n = 2
m = n + 1
xparam = ParamSpec('x', 'numeric')
dataset.add_parameter(xparam)
x_results = [{'x': x} for x in range(n)]
dataset.add_results(x_results)
yparam = ParamSpec("y", "numeric")
match_str = f'Need to have {n} values but got {m}.'
match_str = re.escape(match_str)
with pytest.raises(ValueError, match=match_str):
pytest.deprecated_call(dataset.add_parameter_values, yparam,
[y for y in range(m)])
yvals = [y for y in range(n)]
# Unlike what the docstring of the method suggests,
# `add_parameter_values` does NOT add a new parameter and values for it
# "NEXT TO the columns of values of existing parameters".
#
# In other words, if the initial state of the table is:
#
# | x |
# --------
# | 1 |
# | 2 |
#
# then the state of the table after calling `add_parameter_values` is
# going to be:
#
# | x | y |
# ---------------
# | 1 | NULL |
# | 2 | NULL |
# | NULL | 25 |
# | NULL | 42 |
#
# while the docstring suggests the following state:
#
# | x | y |
# ---------------
# | 1 | 25 |
# | 2 | 42 |
#
y_expected = [[None]] * n + [[y] for y in yvals]
pytest.deprecated_call(dataset.add_parameter_values, yparam, yvals)
shadow_ds = make_shadow_dataset(dataset)
try:
assert y_expected == dataset.get_data(yparam)
assert y_expected == shadow_ds.get_data(yparam)
dataset.mark_complete()
# and now let's test that dataset's connection does not commit anymore
# when `atomic` is used
dataset.add_results([{yparam.name: -2}])
y_expected_2 = y_expected + [[-2]]
assert y_expected_2 == dataset.get_data(yparam)
assert y_expected_2 == shadow_ds.get_data(yparam)
finally:
shadow_ds.conn.close()
