def test_setops_preserve_object_dtype(self):
idx = Index([1, 2, 3], dtype=object)
result = idx.intersection(idx[1:])
expected = idx[1:]
tm.assert_index_equal(result, expected)
# if other is not monotonic increasing, intersection goes through
# a different route
result = idx.intersection(idx[1:][::-1])
tm.assert_index_equal(result, expected)
result = idx._union(idx[1:], sort=None)
expected = idx
tm.assert_numpy_array_equal(result, expected.values)
result = idx.union(idx[1:], sort=None)
tm.assert_index_equal(result, expected)
# if other is not monotonic increasing, _union goes through
# a different route
result = idx._union(idx[1:][::-1], sort=None)
tm.assert_numpy_array_equal(result, expected.values)
result = idx.union(idx[1:][::-1], sort=None)
tm.assert_index_equal(result, expected)
def test_intersection(self):
# intersect with Int64Index
other = Index(np.arange(1, 6))
result = self.index.intersection(other)
expected = Index(
np.sort(np.intersect1d(self.index.values, other.values)))
self.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(
np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
self.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = self.index.intersection(other)
expected = Index(
np.sort(np.intersect1d(self.index.values, other.values)))
self.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = self.index.intersection(other)
expected = Index(
np.sort(np.intersect1d(self.index.values, other.values)))
self.assert_index_equal(result, expected)
index = RangeIndex(5)
# intersect of non-overlapping indices
other = RangeIndex(5, 10, 1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
self.assert_index_equal(result, expected)
other = RangeIndex(-1, -5, -1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
self.assert_index_equal(result, expected)
# intersection of empty indices
other = RangeIndex(0, 0, 1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
self.assert_index_equal(result, expected)
result = other.intersection(index)
self.assert_index_equal(result, expected)
# intersection of non-overlapping values based on start value and gcd
index = RangeIndex(1, 10, 2)
other = RangeIndex(0, 10, 4)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
self.assert_index_equal(result, expected)
def test_intersection(self):
# intersect with Int64Index
other = Index(np.arange(1, 6))
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
index = RangeIndex(5)
# intersect of non-overlapping indices
other = RangeIndex(5, 10, 1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
other = RangeIndex(-1, -5, -1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
# intersection of empty indices
other = RangeIndex(0, 0, 1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
result = other.intersection(index)
tm.assert_index_equal(result, expected)
# intersection of non-overlapping values based on start value and gcd
index = RangeIndex(1, 10, 2)
other = RangeIndex(0, 10, 4)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
def test_intersection(self):
# intersect with Int64Index
other = Index(np.arange(1, 6))
result = self.index.intersection(other)
expected = Index(
np.sort(np.intersect1d(self.index.values, other.values)))
self.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(
np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
self.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = self.index.intersection(other)
expected = Index(
np.sort(np.intersect1d(self.index.values, other.values)))
self.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = self.index.intersection(other)
expected = Index(
np.sort(np.intersect1d(self.index.values, other.values)))
self.assert_index_equal(result, expected)
def remove_before_changepoint(data: pd.HDFStore, select_idx: pd.Index = None):
changepoints = {
837: '2014-03-16',
700: '2014-01-03',
681: '2013-06-14',
986: '2013-05-22',
885: '2014-05-18',
589: '2013-05-27',
105: '2013-05-20',
663: '2013-10-06',
764: '2013-04-24',
364: '2013-05-31',
969: '2013-03-10',
803: '2014-01-07',
91: '2014-01-14'
}
# noinspection PyUnusedLocal
for store, date in changepoints.items():
idx = data.select_as_coordinates(
'train', 'Store != store or Date > pd.Timestamp(date)')
if select_idx is not None:
select_idx = select_idx.intersection(idx)
else:
select_idx = idx
return select_idx
def intersect(self,
exog_genes : pd.Index,
) -> pd.Index:
"""Intersect genes of CountData object with external set
Parameter:
----------
exog_genes : pd.Index
set of genes which object's gene
set should be intersected with
Returns:
-------
Pandas Index object with the intersection between
the two sets
"""
inter = exog_genes.intersection(self.genes)
inter = np.unique(inter)
keep = np.array([ self.genes.get_loc(x) for x in inter])
self.genes = inter
self.cnt = self.cnt[:,keep]
return self.genes
def test_intersection(self):
# intersect with Int64Index
other = Index(np.arange(1, 6))
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
self.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
self.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
self.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
self.assert_index_equal(result, expected)
def test_intersection_duplicates(values):
# GH#31326
a = Index(values)
b = Index([3, 3])
result = a.intersection(b)
expected = Index([3])
tm.assert_index_equal(result, expected)
def test_intersection_str_dates(self, sort):
dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
i1 = Index(dt_dates, dtype=object)
i2 = Index(["aa"], dtype=object)
result = i2.intersection(i1, sort=sort)
assert len(result) == 0
def test_intersect_str_dates(self):
dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
i1 = Index(dt_dates, dtype=object)
i2 = Index(['aa'], dtype=object)
res = i2.intersection(i1)
self.assertEqual(len(res), 0)
def test_intersect_str_dates(self):
dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
i1 = Index(dt_dates, dtype=object)
i2 = Index(['aa'], dtype=object)
res = i2.intersection(i1)
self.assertEqual(len(res), 0)
def _intersection(left: pd.Index, right: pd.Index) -> pd.Index:
if ( # noqa: WPS337
isinstance(left, pd.MultiIndex)
and isinstance(right, pd.MultiIndex)
and pd.__version__ < "1.1.0" # noqa: WPS609
): # pragma: no cover
return iterutils.mi_intersection(left, right)
return left.intersection(right, sort=False)
def test_intersection_non_monotonic_non_unique(self, index2, expected_arr, sort):
# non-monotonic non-unique
index1 = Index(["A", "B", "A", "C"])
expected = Index(expected_arr, dtype="object")
result = index1.intersection(index2, sort=sort)
if sort is None:
expected = expected.sort_values()
tm.assert_index_equal(result, expected)
def append_new_entrants(self, existing_data: pd.Series,
new_index: pd.Index, getter: Callable):
intersection = existing_data.loc[new_index.intersection(
existing_data.index)]
new_entrants_index = new_index.difference(
self.stratification_groups.index)
new_entrants_stratifications = getter(new_entrants_index)
return intersection.append(new_entrants_stratifications)
def test_intersect_str_dates(self):
dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
index1 = Index(dt_dates, dtype=object)
index2 = Index(["aa"], dtype=object)
result = index2.intersection(index1)
expected = Index([], dtype=object)
tm.assert_index_equal(result, expected)
def test_intersection(self):
other = Index([1, 2, 3, 4, 5])
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values, other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values, other.values))))
tm.assert_index_equal(result, expected)
def _get_common_indices(index_1: pd.Index, index_2: pd.Index):
"""Get intersection of indices"""
_intersection = index_1.intersection(index_2)
_diff_to_1 = index_1.difference(_intersection)
if len(_diff_to_1) > 0:
logger.warning(
"Sample with clinical features not in demographics: {}".format(
", ".join(_diff_to_1)))
return _intersection, _diff_to_1
def test_intersection_name_preservation(self, index2, keeps_name, sort):
index1 = Index([1, 2, 3, 4, 5], name="index")
expected = Index([3, 4, 5])
result = index1.intersection(index2, sort)
if keeps_name:
expected.name = "index"
assert result.name == expected.name
tm.assert_index_equal(result, expected)
def test_intersection(self):
other = Index([1, 2, 3, 4, 5])
result = self.index.intersection(other)
expected = np.sort(np.intersect1d(self.index.values, other.values))
tm.assert_numpy_array_equal(result, expected)
result = other.intersection(self.index)
expected = np.sort(
np.asarray(np.intersect1d(self.index.values, other.values)))
tm.assert_numpy_array_equal(result, expected)
def _condition_logic(base_idx: pd.Index, sub_select_idx: pd.Index, state_idx: pd.Index, condition_idx: pd.Index,
logic: str) -> pd.Index:
if str(logic).upper() == 'ALL':
return base_idx.intersection(condition_idx).sort_values()
elif str(logic).upper() == 'ANY':
return sub_select_idx.intersection(condition_idx).sort_values()
elif str(logic).upper() == 'AND':
return state_idx.intersection(condition_idx).sort_values()
elif str(logic).upper() == 'NAND':
return sub_select_idx.drop(state_idx.intersection(condition_idx)).sort_values()
elif str(logic).upper() == 'OR':
return state_idx.append(state_idx.union(condition_idx)).drop_duplicates().sort_values()
elif str(logic).upper() == 'NOR':
result = state_idx.append(state_idx.union(condition_idx)).drop_duplicates().sort_values()
return sub_select_idx.drop(result)
elif str(logic).upper() == 'NOT':
return state_idx.difference(condition_idx)
elif str(logic).upper() == 'XOR':
return state_idx.union(condition_idx).difference(state_idx.intersection(condition_idx))
raise ValueError(f"The logic '{logic}' must be AND, NAND, OR, NOR, NOT, XOR ANY or ALL")
def test_intersection_monotonic(self, index2, keeps_name, sort):
index1 = Index([5, 3, 2, 4, 1], name="index")
expected = Index([5, 3, 4])
if keeps_name:
expected.name = "index"
result = index1.intersection(index2, sort=sort)
if sort is None:
expected = expected.sort_values()
tm.assert_index_equal(result, expected)
def test_intersection_uint64_outside_int64_range(self, index_large):
other = Index([2 ** 63, 2 ** 63 + 5, 2 ** 63 + 10, 2 ** 63 + 15, 2 ** 63 + 20])
result = index_large.intersection(other)
expected = Index(np.sort(np.intersect1d(index_large.values, other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(index_large)
expected = Index(
np.sort(np.asarray(np.intersect1d(index_large.values, other.values)))
)
tm.assert_index_equal(result, expected)
def test_intersection(self):
index = self.create_index()
other = Index([1, 2, 3, 4, 5])
result = index.intersection(other)
expected = Index(np.sort(np.intersect1d(index.values, other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(index)
expected = Index(
np.sort(np.asarray(np.intersect1d(index.values, other.values))))
tm.assert_index_equal(result, expected)
def test_intersection(self):
other = Index([2**63, 2**63 + 5, 2**63 + 10, 2**63 + 15, 2**63 + 20])
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
def test_intersection(self):
other = Index([2**63, 2**63 + 5, 2**63 + 10, 2**63 + 15, 2**63 + 20])
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
def test_intersection_duplicates(self, sort):
# GH#38196
idx1 = Index(
[
pd.Timestamp("2019-12-13"),
pd.Timestamp("2019-12-12"),
pd.Timestamp("2019-12-12"),
]
)
result = idx1.intersection(idx1, sort=sort)
expected = Index([pd.Timestamp("2019-12-13"), pd.Timestamp("2019-12-12")])
tm.assert_index_equal(result, expected)
def test_union_dtypes(left, right, expected, names):
left = pandas_dtype(left)
right = pandas_dtype(right)
a = Index([], dtype=left, name=names[0])
b = Index([], dtype=right, name=names[1])
result = a.union(b)
assert result.dtype == expected
assert result.name == names[2]
# Testing name retention
# TODO: pin down desired dtype; do we want it to be commutative?
result = a.intersection(b)
assert result.name == names[2]
def get_controller_index(net, ctrl_type=None, parameters=None, idx=[]):
""" Returns indices of searched controllers. Parameters can specify the search query.
INPUT:
**net** (pandapowerNet) - The pandapower network
OPTINAL:
**controller_type** (controller object or string name of controller object)
**parameters** (None, dict) - Dict of parameter names, which are in the controller object or
net.controller DataFrame
**idx** ([], list) - list of indices in net.controller to be searched for. If list is empty
all indices are considered.
OUTPUT:
**idx** (list) - index / indices of controllers in net.controller which are in idx and
matches given ctrl_type or parameters
"""
# logger.debug(ctrl_type, parameters, idx)
idx = idx if len(idx) else net.controller.index
if ctrl_type is not None:
if isinstance(ctrl_type, str):
idx = get_controller_index_by_typename(net, ctrl_type, idx)
else:
idx = get_controller_index_by_type(net, ctrl_type, idx)
if isinstance(parameters, dict):
df_keys = [k for k in parameters.keys() if k in net.controller.columns]
attributes_keys = list(set(parameters.keys()) - set(df_keys))
attributes_dict = {k: parameters[k] for k in attributes_keys}
# query of parameters in net.controller dataframe
idx = Index(idx, dtype=np.int64)
for df_key in df_keys:
idx = idx.intersection(net.controller.index[net.controller[df_key] == parameters[df_key]])
# query of parameters in controller object attributes
idx = [i for i in idx if _controller_attributes_query(
net.controller.object.loc[i], attributes_dict)]
return idx
def test_intersection(self, sort):
# intersect with Int64Index
index = RangeIndex(start=0, stop=20, step=2)
other = Index(np.arange(1, 6))
result = index.intersection(other, sort=sort)
expected = Index(np.sort(np.intersect1d(index.values, other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(index, sort=sort)
expected = Index(
np.sort(np.asarray(np.intersect1d(index.values, other.values)))
)
tm.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = index.intersection(other, sort=sort)
expected = Index(np.sort(np.intersect1d(index.values, other.values)))
tm.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = index.intersection(other, sort=sort)
expected = Index(np.sort(np.intersect1d(index.values, other.values)))
tm.assert_index_equal(result, expected)
# reversed (GH 17296)
result = other.intersection(index, sort=sort)
tm.assert_index_equal(result, expected)
# GH 17296: intersect two decreasing RangeIndexes
first = RangeIndex(10, -2, -2)
other = RangeIndex(5, -4, -1)
expected = first.astype(int).intersection(other.astype(int), sort=sort)
result = first.intersection(other, sort=sort).astype(int)
tm.assert_index_equal(result, expected)
# reversed
result = other.intersection(first, sort=sort).astype(int)
tm.assert_index_equal(result, expected)
index = RangeIndex(5, name="foo")
# intersect of non-overlapping indices
other = RangeIndex(5, 10, 1, name="foo")
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1, name="foo")
tm.assert_index_equal(result, expected)
other = RangeIndex(-1, -5, -1)
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
# intersection of empty indices
other = RangeIndex(0, 0, 1)
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
result = other.intersection(index, sort=sort)
tm.assert_index_equal(result, expected)
def test_intersection(self):
# intersect with Int64Index
other = Index(np.arange(1, 6))
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = self.index.intersection(other)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
# reversed (GH 17296)
result = other.intersection(self.index)
tm.assert_index_equal(result, expected)
# GH 17296: intersect two decreasing RangeIndexes
first = RangeIndex(10, -2, -2)
other = RangeIndex(5, -4, -1)
expected = first.astype(int).intersection(other.astype(int))
result = first.intersection(other).astype(int)
tm.assert_index_equal(result, expected)
# reversed
result = other.intersection(first).astype(int)
tm.assert_index_equal(result, expected)
index = RangeIndex(5)
# intersect of non-overlapping indices
other = RangeIndex(5, 10, 1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
other = RangeIndex(-1, -5, -1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
# intersection of empty indices
other = RangeIndex(0, 0, 1)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
result = other.intersection(index)
tm.assert_index_equal(result, expected)
# intersection of non-overlapping values based on start value and gcd
index = RangeIndex(1, 10, 2)
other = RangeIndex(0, 10, 4)
result = index.intersection(other)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
def test_intersection_equal_sort_true(self):
# TODO decide on True behaviour
idx = Index(["c", "a", "b"])
sorted_ = Index(["a", "b", "c"])
tm.assert_index_equal(idx.intersection(idx, sort=True), sorted_)
def test_intersection(self, sort):
# intersect with Int64Index
other = Index(np.arange(1, 6))
result = self.index.intersection(other, sort=sort)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
result = other.intersection(self.index, sort=sort)
expected = Index(np.sort(np.asarray(np.intersect1d(self.index.values,
other.values))))
tm.assert_index_equal(result, expected)
# intersect with increasing RangeIndex
other = RangeIndex(1, 6)
result = self.index.intersection(other, sort=sort)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
# intersect with decreasing RangeIndex
other = RangeIndex(5, 0, -1)
result = self.index.intersection(other, sort=sort)
expected = Index(np.sort(np.intersect1d(self.index.values,
other.values)))
tm.assert_index_equal(result, expected)
# reversed (GH 17296)
result = other.intersection(self.index, sort=sort)
tm.assert_index_equal(result, expected)
# GH 17296: intersect two decreasing RangeIndexes
first = RangeIndex(10, -2, -2)
other = RangeIndex(5, -4, -1)
expected = first.astype(int).intersection(other.astype(int), sort=sort)
result = first.intersection(other, sort=sort).astype(int)
tm.assert_index_equal(result, expected)
# reversed
result = other.intersection(first, sort=sort).astype(int)
tm.assert_index_equal(result, expected)
index = RangeIndex(5)
# intersect of non-overlapping indices
other = RangeIndex(5, 10, 1)
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
other = RangeIndex(-1, -5, -1)
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
# intersection of empty indices
other = RangeIndex(0, 0, 1)
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
result = other.intersection(index, sort=sort)
tm.assert_index_equal(result, expected)
# intersection of non-overlapping values based on start value and gcd
index = RangeIndex(1, 10, 2)
other = RangeIndex(0, 10, 4)
result = index.intersection(other, sort=sort)
expected = RangeIndex(0, 0, 1)
tm.assert_index_equal(result, expected)
def test_intersection_equal_sort(self):
idx = Index(["c", "a", "b"])
tm.assert_index_equal(idx.intersection(idx, sort=False), idx)
tm.assert_index_equal(idx.intersection(idx, sort=None), idx)
