def _set_model(self, mdl, skip_validation=False, validate_wltc_data=False):
from wltp.datamodel import get_model_base, merge
merged_model = get_model_base()
merge(merged_model, mdl)
if not skip_validation:
datamodel.validate_model(merged_model,
validate_wltc_data=validate_wltc_data)
self._model = merged_model
def test_default_resistance_coeffs_None(self):
mdl = goodVehicle()
mdl["f0"] = mdl["f1"] = mdl["f1"] = None
mdl = datamodel.merge(datamodel.get_model_base(), mdl)
with pytest.raises(ValidationError,
match="None is not of type 'number'"):
self.checkModel_valid(mdl)
def testFullLoadCurve_invalid(self):
import numpy as np
import pandas as pd
cases = [
None,
[],
{},
[[1, 2, 3], [4, 5, 6]],
np.array([[1, 2, 3], [4, 5, 6]]),
pd.DataFrame({
"speed": [10, 11, 12],
"foo": [1, 2, 3]
}),
pd.DataFrame({
"velocity": [100, 200, 300],
"alt": [0, 1, 0]
}),
# pd.Series([5,6,'a']),
]
for c in cases:
mdl = datamodel.get_model_base()
mdl = datamodel.merge(datamodel.get_model_base(), mdl)
mdl["wot"] = c
self.checkModel_invalid(mdl)
def test_validate_wltc_data(self):
mdl = datamodel.get_model_base()
mdl = datamodel.merge(mdl, goodVehicle())
validator = datamodel.model_validator(validate_wltc_data=True,
validate_schema=True)
validator.validate(mdl)
def test_default_resistance_coeffs_None(self):
mdl = goodVehicle()
mdl["f0"] = mdl["f1"] = mdl["f1"] = None
mdl = datamodel.merge(datamodel.get_model_base(), mdl)
with pytest.raises(ValidationError,
match="'f0' is a required property"):
self.checkModel_valid(mdl)
def testOverlayOnInit():
mdl = goodVehicle()
n_rated = 6000
mdl2 = {"n_rated": n_rated}
exp = Experiment(datamodel.merge(mdl, mdl2))
mdl = exp._model
assert mdl["n_rated"] == n_rated
def testFullLoadCurve_invalid(case):
import numpy as np
import pandas as pd
mdl = datamodel.get_model_base()
mdl = datamodel.merge(datamodel.get_model_base(), mdl)
mdl["wot"] = case
_checkModel_invalid(mdl)
def _set_model(self, mdl, skip_validation, validate_wltc_data,
additional_properties):
from wltp.datamodel import get_model_base, merge
merged_model = get_model_base()
merge(merged_model, mdl)
if not skip_validation:
errors = list(
datamodel.validate_model(
merged_model,
validate_wltc_data=validate_wltc_data,
additional_properties=additional_properties,
iter_errors=True,
))
if errors:
err_msg = "\n ".join(str(e) for e in errors)
raise ValueError(f"Model validation errors: {err_msg}")
self._model = merged_model
def test_default_resistance_coeffs_missing(self):
mdl = goodVehicle()
mdl = datamodel.merge(datamodel.get_model_base(), mdl)
self.checkModel_valid(mdl)
