def test_maybe_booleans_to_slice():
arr = np.array([0, 0, 1, 1, 1, 0, 1], dtype=np.uint8)
result = lib.maybe_booleans_to_slice(arr)
assert(result.dtype == np.bool_)
result = lib.maybe_booleans_to_slice(arr[:0])
assert(result == slice(0, 0))
def test_maybe_booleans_to_slice():
arr = np.array([0, 0, 1, 1, 1, 0, 1], dtype=np.uint8)
result = lib.maybe_booleans_to_slice(arr)
assert (result.dtype == np.bool_)
result = lib.maybe_booleans_to_slice(arr[:0])
assert (result == slice(0, 0))
def __getitem__(self, key):
getitem = self._data.__getitem__
if lib.isscalar(key):
val = getitem(key)
return self._box_func(val)
else:
if com.is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
attribs = self._get_attributes_dict()
freq = None
if isinstance(key, slice):
if self.freq is not None and key.step is not None:
freq = key.step * self.freq
else:
freq = self.freq
attribs['freq'] = freq
result = getitem(key)
if result.ndim > 1:
return result
return self._simple_new(result, **attribs)
def __getitem__(self, key):
getitem = self._data.__getitem__
if np.isscalar(key):
val = getitem(key)
return self._box_func(val)
else:
if com.is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
attribs = self._get_attributes_dict()
freq = None
if isinstance(key, slice):
if self.freq is not None and key.step is not None:
freq = key.step * self.freq
else:
freq = self.freq
attribs['freq'] = freq
result = getitem(key)
if result.ndim > 1:
return result
return self._simple_new(result, **attribs)
def __getitem__(self, key):
"""
This getitem defers to the underlying array, which by-definition can
only handle list-likes, slices, and integer scalars
"""
is_int = is_integer(key)
if is_scalar(key) and not is_int:
raise ValueError
getitem = self._data.__getitem__
if is_int:
val = getitem(key)
return self._box_func(val)
else:
if com.is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
attribs = self._get_attributes_dict()
is_period = isinstance(self, ABCPeriodIndex)
if is_period:
freq = self.freq
else:
freq = None
if isinstance(key, slice):
if self.freq is not None and key.step is not None:
freq = key.step * self.freq
else:
freq = self.freq
attribs['freq'] = freq
result = getitem(key)
if result.ndim > 1:
# To support MPL which performs slicing with 2 dim
# even though it only has 1 dim by definition
if is_period:
return self._simple_new(result, **attribs)
return result
return self._simple_new(result, **attribs)
def __getitem__(self, key):
"""
This getitem defers to the underlying array, which by-definition can
only handle list-likes, slices, and integer scalars
"""
is_int = is_integer(key)
if is_scalar(key) and not is_int:
raise ValueError
getitem = self._data.__getitem__
if is_int:
val = getitem(key)
return self._box_func(val)
else:
if com.is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
attribs = self._get_attributes_dict()
is_period = isinstance(self, ABCPeriodIndex)
if is_period:
freq = self.freq
else:
freq = None
if isinstance(key, slice):
if self.freq is not None and key.step is not None:
freq = key.step * self.freq
else:
freq = self.freq
attribs['freq'] = freq
result = getitem(key)
if result.ndim > 1:
# To support MPL which performs slicing with 2 dim
# even though it only has 1 dim by definition
if is_period:
return self._simple_new(result, **attribs)
return result
return self._simple_new(result, **attribs)
def __getitem__(self, key):
getitem = self._data.__getitem__
if np.isscalar(key):
val = getitem(key)
return Timedelta(val)
else:
if com._is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0,None,None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
result = getitem(key)
if result.ndim > 1:
return result
return self._simple_new(result, self.name)
def __getitem__(self, key):
getitem = self._data.__getitem__
if np.isscalar(key):
val = getitem(key)
return Timedelta(val)
else:
if com._is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
result = getitem(key)
if result.ndim > 1:
return result
return self._simple_new(result, self.name)
def __getitem__(self, key):
"""Override numpy.ndarray's __getitem__ method to work as desired"""
arr_idx = self.view(np.ndarray)
if np.isscalar(key):
val = arr_idx[key]
return Timestamp(val, offset=self.offset, tz=self.tz)
else:
if com._is_bool_indexer(key):
key = np.asarray(key)
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
new_offset = None
if isinstance(key, slice):
if self.offset is not None and key.step is not None:
new_offset = key.step * self.offset
else:
new_offset = self.offset
result = arr_idx[key]
if result.ndim > 1:
return result
return self._simple_new(result, self.name, new_offset, self.tz)
def __getitem__(self, key):
"""Override numpy.ndarray's __getitem__ method to work as desired"""
arr_idx = self.view(np.ndarray)
if np.isscalar(key):
val = arr_idx[key]
return Timestamp(val, offset=self.offset, tz=self.tz)
else:
if com._is_bool_indexer(key):
key = np.asarray(key)
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
new_offset = None
if isinstance(key, slice):
if self.offset is not None and key.step is not None:
new_offset = key.step * self.offset
else:
new_offset = self.offset
result = arr_idx[key]
if result.ndim > 1:
return result
return self._simple_new(result, self.name, new_offset, self.tz)
def __getitem__(self, key):
"""
This getitem defers to the underlying array, which by-definition can
only handle list-likes, slices, and integer scalars
"""
is_int = is_integer(key)
if lib.isscalar(key) and not is_int:
raise ValueError
getitem = self._data.__getitem__
if is_int:
val = getitem(key)
return self._box_func(val)
else:
if com.is_bool_indexer(key):
key = np.asarray(key)
if key.all():
key = slice(0, None, None)
else:
key = lib.maybe_booleans_to_slice(key.view(np.uint8))
attribs = self._get_attributes_dict()
freq = None
if isinstance(key, slice):
if self.freq is not None and key.step is not None:
freq = key.step * self.freq
else:
freq = self.freq
attribs["freq"] = freq
result = getitem(key)
if result.ndim > 1:
return result
return self._simple_new(result, **attribs)
