def minimal_oil():
oil = Oil('XXXXX')
oil.metadata.name = "Minimal Oil for Tests"
fresh = Sample()
# print(fresh.physical_properties)
oil.sub_samples.append(fresh)
return oil
def test_default_empty_attributes(self, attr):
"""
test that various attributes get a default empty object,
rather than None
"""
s = Sample()
assert getattr(s, attr) is not None
def test_init(self):
s = Sample()
for attr in ('CCME', 'ESTS_hydrocarbon_fractions', 'SARA',
'bulk_composition', 'compounds', 'cut_volume',
'distillation_data', 'environmental_behavior',
'extra_data', 'headspace_analysis', 'industry_properties',
'metadata', 'miscellaneous', 'physical_properties'):
assert hasattr(s, attr)
assert s.metadata.name == "Fresh Oil Sample"
assert s.metadata.short_name == "Fresh Oil"
def test_complete_sample(self):
"""
trying to do a pretty complete one
Note: This is more an integration test. Each complex attribute of the
Sample should have its own pytests
"""
s = Sample(metadata=SampleMetaData(
short_name="short", name="a longer name that is more descriptive"))
p = PhysicalProperties()
s.metadata.fraction_evaporated = MassFraction(value=11, unit='%')
s.metadata.boiling_point_range = None
p.densities = DensityList([
DensityPoint(density=Density(value=0.8751,
unit="kg/m^3",
standard_deviation=1.2,
replicates=3),
ref_temp=Temperature(value=15.0, unit="C")),
DensityPoint(density=Density(value=0.99,
unit="kg/m^3",
standard_deviation=1.4,
replicates=5),
ref_temp=Temperature(value=25.0, unit="C"))
])
s.physical_properties = p
py_json = s.py_json(sparse=False) # the non-sparse version
for name in ('CCME', 'ESTS_hydrocarbon_fractions', 'SARA',
'bulk_composition', 'compounds', 'cut_volume',
'distillation_data', 'environmental_behavior',
'extra_data', 'headspace_analysis', 'industry_properties',
'metadata', 'miscellaneous', 'physical_properties'):
assert name in py_json
assert py_json['metadata']['name'] == ('a longer name that is more '
'descriptive')
assert py_json['metadata']['short_name'] == "short"
for name in ('densities', 'kinematic_viscosities',
'dynamic_viscosities'):
assert name in py_json['physical_properties']
# Now test some real stuff:
dens = py_json['physical_properties']['densities']
print(type(dens))
assert type(dens) == list
assert dens[0]['density']['value'] == 0.8751
def test_json_non_sparse(self):
s = Sample()
py_json = s.py_json(sparse=False)
for attr in ('CCME', 'ESTS_hydrocarbon_fractions', 'SARA',
'bulk_composition', 'compounds', 'cut_volume',
'distillation_data', 'environmental_behavior',
'extra_data', 'headspace_analysis', 'industry_properties',
'metadata', 'miscellaneous', 'physical_properties'):
assert attr in py_json
assert py_json['metadata']['name'] == "Fresh Oil Sample"
assert py_json['metadata']['short_name'] == "Fresh Oil"
def make_oil_with_densities(self, densities, temps):
oil = Oil(oil_id="DENSITY_TESTER")
sample = Sample()
sample.metadata.name = "only density"
oil.sub_samples.append(sample)
for d, t in zip(densities, temps):
dp = DensityPoint(meas.Density(d, unit="kg/m^3"),
meas.Temperature(t, unit="K"))
sample.physical_properties.densities.append(dp)
return oil
def add_kin_viscosity_to_oil(oil,
viscosities,
temp,
unit,
kvis_temp=15.0,
temp_unit="C"):
try:
sample = oil.sub_samples[0]
except IndexError:
sample = Sample()
sample.metadata.name = "only viscosity"
oil.sub_samples.append(sample)
for kvis in viscosities:
kp = KinematicViscosityPoint(
meas.KinematicViscosity(kvis, unit=unit),
meas.Temperature(kvis_temp, unit=temp_unit))
sample.physical_properties.kinematic_viscosities.append(kp)
return None
def no_api_with_one_density_13C():
oil = Oil(oil_id='XXXXXX')
oil.metadata.product_type = "Condensate"
print(oil)
# create a sample for fresh oil
s = Sample()
# add some densities
# p = PhysicalProperties()
p = s.physical_properties
p.densities = DensityList([
DensityPoint(density=Density(value=0.8751, unit="g/cm^3"),
ref_temp=Temperature(value=13.0, unit="C")),
])
oil.sub_samples.append(s)
return oil
def test_sample_with_ccme():
"""
testing loading a sample with ccme data from py_json
"""
ccme = CCME()
ccme.F1 = MassFraction(unit="mg/g", value=15.58)
ccme.F2 = MassFraction(unit="mg/g", value=50)
ccme.F3 = MassFraction(unit="mg/g", value=193)
ccme.F4 = MassFraction(unit="mg/g", value=40)
ccme.method = "a method name"
s = Sample(metadata=SampleMetaData(
short_name="short", name="a longer name that is more descriptive"))
s.metadata.fraction_evaporated = MassFraction(value=16, unit="%")
s.metadata.boiling_point_range = None
s.CCME = ccme
sample_json = s.py_json()
s2 = Sample.from_py_json(sample_json)
assert s == s2
def test_add_non_existing(self):
s = Sample()
with pytest.raises(AttributeError):
s.something_random = 43
def test_json(self):
s = Sample(metadata=SampleMetaData(
short_name="short", name="a longer name that is more descriptive"))
py_json = s.py_json() # the sparse version
assert tuple(py_json['metadata'].keys()) == ('name', 'short_name')
def test_populated(self):
s = Sample()
sl = SampleList([s])
assert len(sl) == 1
assert type(sl[0]) == Sample