def test_get_data_by_id_order(dataset):
"""
Test if the values of the setpoints/dependent parameters is dependent on
the order of the `depends_on` value. This sounds far fetch but was
actually the case before #1250.
"""
indepA = ParamSpec('indep1', "numeric")
indepB = ParamSpec('indep2', "numeric")
depAB = ParamSpec('depAB', "numeric", depends_on=[indepA, indepB])
depBA = ParamSpec('depBA', "numeric", depends_on=[indepB, indepA])
dataset.add_parameters([indepA, indepB, depAB, depBA])
dataset.add_result({'depAB': 12,
'indep2': 2,
'indep1': 1})
dataset.add_result({'depBA': 21,
'indep2': 2,
'indep1': 1})
dataset.mark_complete()
data = get_data_by_id(dataset.run_id)
data_dict = {el['name']: el['data'] for el in data[0]}
assert data_dict['indep1'] == 1
assert data_dict['indep2'] == 2
data_dict = {el['name']: el['data'] for el in data[1]}
assert data_dict['indep1'] == 1
assert data_dict['indep2'] == 2
def test_add_paramspec(dataset):
exps = experiments()
assert len(exps) == 1
exp = exps[0]
assert exp.name == "test-experiment"
assert exp.sample_name == "test-sample"
assert exp.last_counter == 1
parameter_a = ParamSpec("a_param", "NUMERIC")
parameter_b = ParamSpec("b_param", "NUMERIC", key="value", number=1)
parameter_c = ParamSpec("c_param", "array", inferred_from=[parameter_a,
parameter_b])
dataset.add_parameters([parameter_a, parameter_b, parameter_c])
# Now retrieve the paramspecs
paramspecs = dataset.paramspecs
expected_keys = ['a_param', 'b_param', 'c_param']
keys = sorted(list(paramspecs.keys()))
assert keys == expected_keys
for expected_param_name in expected_keys:
ps = paramspecs[expected_param_name]
assert ps.name == expected_param_name
assert paramspecs['c_param'].inferred_from == 'a_param, b_param'
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_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_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