def validate_bool_kwarg(value, arg_name):
""" Ensures that argument passed in arg_name is of type bool. """
if not (is_bool(value) or value is None):
raise ValueError('For argument "%s" expected type bool, '
'received type %s.' %
(arg_name, type(value).__name__))
return value
def validate_bool_kwarg(value, arg_name):
""" Ensures that argument passed in arg_name is of type bool. """
if not (is_bool(value) or value is None):
raise ValueError('For argument "%s" expected type bool, '
'received type %s.' %
(arg_name, type(value).__name__))
return value
def validate_cum_func_with_skipna(skipna, args, kwargs, name):
"""
If this function is called via the 'numpy' library, the third
parameter in its signature is 'dtype', which takes either a
'numpy' dtype or 'None', so check if the 'skipna' parameter is
a boolean or not
"""
if not is_bool(skipna):
args = (skipna,) + args
skipna = True
validate_cum_func(args, kwargs, fname=name)
return skipna
def _check_for_default_values(fname, arg_val_dict, compat_args):
"""
Check that the keys in `arg_val_dict` are mapped to their
default values as specified in `compat_args`.
Note that this function is to be called only when it has been
checked that arg_val_dict.keys() is a subset of compat_args
"""
for key in arg_val_dict:
# try checking equality directly with '=' operator,
# as comparison may have been overriden for the left
# hand object
try:
v1 = arg_val_dict[key]
v2 = compat_args[key]
# check for None-ness otherwise we could end up
# comparing a numpy array vs None
if (v1 is not None and v2 is None) or (v1 is None and v2 is not None):
match = False
else:
match = v1 == v2
if not is_bool(match):
raise ValueError("'match' is not a boolean")
# could not compare them directly, so try comparison
# using the 'is' operator
except:
match = arg_val_dict[key] is compat_args[key]
if not match:
raise ValueError(
(
"the '{arg}' parameter is not "
"supported in the pandas "
"implementation of {fname}()".format(fname=fname, arg=key)
)
)
def _check_for_default_values(fname, arg_val_dict, compat_args):
"""
Check that the keys in `arg_val_dict` are mapped to their
default values as specified in `compat_args`.
Note that this function is to be called only when it has been
checked that arg_val_dict.keys() is a subset of compat_args
"""
for key in arg_val_dict:
# try checking equality directly with '=' operator,
# as comparison may have been overriden for the left
# hand object
try:
v1 = arg_val_dict[key]
v2 = compat_args[key]
# check for None-ness otherwise we could end up
# comparing a numpy array vs None
if (v1 is not None and v2 is None) or \
(v1 is None and v2 is not None):
match = False
else:
match = (v1 == v2)
if not is_bool(match):
raise ValueError("'match' is not a boolean")
# could not compare them directly, so try comparison
# using the 'is' operator
except:
match = (arg_val_dict[key] is compat_args[key])
if not match:
raise ValueError(("the '{arg}' parameter is not "
"supported in the pandas "
"implementation of {fname}()".
format(fname=fname, arg=key)))
def test_is_bool(self):
self.assertTrue(is_bool(True))
self.assertTrue(is_bool(np.bool(False)))
self.assertTrue(is_bool(np.bool_(False)))
self.assertFalse(is_bool(1))
self.assertFalse(is_bool(1.1))
self.assertFalse(is_bool(1 + 3j))
self.assertFalse(is_bool(np.int64(1)))
self.assertFalse(is_bool(np.float64(1.1)))
self.assertFalse(is_bool(np.complex128(1 + 3j)))
self.assertFalse(is_bool(np.nan))
self.assertFalse(is_bool(None))
self.assertFalse(is_bool('x'))
self.assertFalse(is_bool(datetime(2011, 1, 1)))
self.assertFalse(is_bool(np.datetime64('2011-01-01')))
self.assertFalse(is_bool(Timestamp('2011-01-01')))
self.assertFalse(is_bool(Timestamp('2011-01-01',
tz='US/Eastern')))
self.assertFalse(is_bool(timedelta(1000)))
self.assertFalse(is_bool(np.timedelta64(1, 'D')))
self.assertFalse(is_bool(Timedelta('1 days')))
def test_is_bool(self):
self.assertTrue(is_bool(True))
self.assertTrue(is_bool(np.bool(False)))
self.assertTrue(is_bool(np.bool_(False)))
self.assertFalse(is_bool(1))
self.assertFalse(is_bool(1.1))
self.assertFalse(is_bool(1 + 3j))
self.assertFalse(is_bool(np.int64(1)))
self.assertFalse(is_bool(np.float64(1.1)))
self.assertFalse(is_bool(np.complex128(1 + 3j)))
self.assertFalse(is_bool(np.nan))
self.assertFalse(is_bool(None))
self.assertFalse(is_bool('x'))
self.assertFalse(is_bool(datetime(2011, 1, 1)))
self.assertFalse(is_bool(np.datetime64('2011-01-01')))
self.assertFalse(is_bool(Timestamp('2011-01-01')))
self.assertFalse(is_bool(Timestamp('2011-01-01', tz='US/Eastern')))
self.assertFalse(is_bool(timedelta(1000)))
self.assertFalse(is_bool(np.timedelta64(1, 'D')))
self.assertFalse(is_bool(Timedelta('1 days')))
