def test_no_attributes_set_in_init(estimator, preprocessor):
"""Check setting during init. Adapted from scikit-learn."""
estimator = clone(estimator)
estimator.set_params(preprocessor=preprocessor)
if hasattr(type(estimator).__init__, "deprecated_original"):
return
init_params = _get_args(type(estimator).__init__)
parents_init_params = [
param for params_parent in (_get_args(parent)
for parent in type(estimator).__mro__)
for param in params_parent
]
# Test for no setting apart from parameters during init
invalid_attr = (set(vars(estimator)) - set(init_params) -
set(parents_init_params))
assert not invalid_attr, \
("Estimator %s should not set any attribute apart"
" from parameters during init. Found attributes %s."
% (type(estimator).__name__, sorted(invalid_attr)))
# Ensure that each parameter is set in init
invalid_attr = (set(init_params) - set(vars(estimator)) - set(["self"]))
assert not invalid_attr, \
("Estimator %s should store all parameters"
" as an attribute during init. Did not find "
"attributes %s." % (type(estimator).__name__, sorted(invalid_attr)))
def test_no_attributes_set_in_init(estimator, preprocessor):
"""Check setting during init. Adapted from scikit-learn."""
estimator = clone(estimator)
estimator.set_params(preprocessor=preprocessor)
if hasattr(type(estimator).__init__, "deprecated_original"):
return
init_params = _get_args(type(estimator).__init__)
parents_init_params = [param for params_parent in
(_get_args(parent) for parent in
type(estimator).__mro__)
for param in params_parent]
# Test for no setting apart from parameters during init
invalid_attr = (set(vars(estimator)) - set(init_params) -
set(parents_init_params))
assert not invalid_attr, \
("Estimator %s should not set any attribute apart"
" from parameters during init. Found attributes %s."
% (type(estimator).__name__, sorted(invalid_attr)))
# Ensure that each parameter is set in init
invalid_attr = (set(init_params) - set(vars(estimator)) -
set(["self"]))
assert not invalid_attr, \
("Estimator %s should store all parameters"
" as an attribute during init. Did not find "
"attributes %s." % (type(estimator).__name__, sorted(invalid_attr)))
def check_docstring_parameters(func, doc=None, ignore=None, class_name=None):
"""Helper to check docstring
Parameters
----------
func : callable
The function object to test.
doc : str, optional (default: None)
Docstring if it is passed manually to the test.
ignore : None | list
Parameters to ignore.
class_name : string, optional (default: None)
If ``func`` is a class method and the class name is known specify
class_name for the error message.
Returns
-------
incorrect : list
A list of string describing the incorrect results.
"""
from numpydoc import docscrape
incorrect = []
ignore = [] if ignore is None else ignore
func_name = _get_func_name(func, class_name=class_name)
if not func_name.startswith('sklearn_lvq.'):
return incorrect
# Don't check docstring for property-functions
if inspect.isdatadescriptor(func):
return incorrect
args = list(filter(lambda x: x not in ignore, _get_args(func)))
# drop self
if len(args) > 0 and args[0] == 'self':
args.remove('self')
if doc is None:
with warnings.catch_warnings(record=True) as w:
try:
doc = docscrape.FunctionDoc(func)
except Exception as exp:
incorrect += [func_name + ' parsing error: ' + str(exp)]
return incorrect
if len(w):
raise RuntimeError('Error for %s:\n%s' % (func_name, w[0]))
param_names = []
for name, type_definition, param_doc in doc['Parameters']:
if (type_definition.strip() == "" or
type_definition.strip().startswith(':')):
param_name = name.lstrip()
# If there was no space between name and the colon
# "verbose:" -> len(["verbose", ""][0]) -> 7
# If "verbose:"[7] == ":", then there was no space
if param_name[len(param_name.split(':')[0].strip())] == ':':
incorrect += [func_name +
' There was no space between the param name and '
'colon ("%s")' % name]
else:
incorrect += [func_name + ' Incorrect type definition for '
'param: "%s" (type definition was "%s")'
% (name.split(':')[0], type_definition)]
if '*' not in name:
param_names.append(name.split(':')[0].strip('` '))
param_names = list(filter(lambda x: x not in ignore, param_names))
if len(param_names) != len(args):
bad = str(sorted(list(set(param_names) ^ set(args))))
incorrect += [func_name + ' arg mismatch: ' + bad]
else:
for n1, n2 in zip(param_names, args):
if n1 != n2:
incorrect += [func_name + ' ' + n1 + ' != ' + n2]
return incorrect