Skip to content

REF: numeric index test_indexing #33387

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Apr 8, 2020
Merged
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
237 changes: 237 additions & 0 deletions pandas/tests/indexes/numeric/test_indexing.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,237 @@
import numpy as np
import pytest

from pandas import Float64Index, Int64Index, Series, UInt64Index
import pandas._testing as tm


@pytest.fixture
def index_large():
# large values used in UInt64Index tests where no compat needed with Int64/Float64
large = [2 ** 63, 2 ** 63 + 10, 2 ** 63 + 15, 2 ** 63 + 20, 2 ** 63 + 25]
return UInt64Index(large)


class TestGetLoc:
def test_get_loc_float64(self):
idx = Float64Index([0.0, 1.0, 2.0])
for method in [None, "pad", "backfill", "nearest"]:
assert idx.get_loc(1, method) == 1
if method is not None:
assert idx.get_loc(1, method, tolerance=0) == 1

for method, loc in [("pad", 1), ("backfill", 2), ("nearest", 1)]:
assert idx.get_loc(1.1, method) == loc
assert idx.get_loc(1.1, method, tolerance=0.9) == loc

with pytest.raises(KeyError, match="^'foo'$"):
idx.get_loc("foo")
with pytest.raises(KeyError, match=r"^1\.5$"):
idx.get_loc(1.5)
with pytest.raises(KeyError, match=r"^1\.5$"):
idx.get_loc(1.5, method="pad", tolerance=0.1)
with pytest.raises(KeyError, match="^True$"):
idx.get_loc(True)
with pytest.raises(KeyError, match="^False$"):
idx.get_loc(False)

with pytest.raises(ValueError, match="must be numeric"):
idx.get_loc(1.4, method="nearest", tolerance="foo")

with pytest.raises(ValueError, match="must contain numeric elements"):
idx.get_loc(1.4, method="nearest", tolerance=np.array(["foo"]))

with pytest.raises(
ValueError, match="tolerance size must match target index size"
):
idx.get_loc(1.4, method="nearest", tolerance=np.array([1, 2]))

def test_get_loc_na(self):
idx = Float64Index([np.nan, 1, 2])
assert idx.get_loc(1) == 1
assert idx.get_loc(np.nan) == 0

idx = Float64Index([np.nan, 1, np.nan])
assert idx.get_loc(1) == 1

# FIXME: dont leave commented-out
# representable by slice [0:2:2]
# pytest.raises(KeyError, idx.slice_locs, np.nan)
sliced = idx.slice_locs(np.nan)
assert isinstance(sliced, tuple)
assert sliced == (0, 3)

# not representable by slice
idx = Float64Index([np.nan, 1, np.nan, np.nan])
assert idx.get_loc(1) == 1
msg = "'Cannot get left slice bound for non-unique label: nan"
with pytest.raises(KeyError, match=msg):
idx.slice_locs(np.nan)

def test_get_loc_missing_nan(self):
# GH#8569
idx = Float64Index([1, 2])
assert idx.get_loc(1) == 0
with pytest.raises(KeyError, match=r"^3$"):
idx.get_loc(3)
with pytest.raises(KeyError, match="^nan$"):
idx.get_loc(np.nan)
with pytest.raises(TypeError, match=r"'\[nan\]' is an invalid key"):
# listlike/non-hashable raises TypeError
idx.get_loc([np.nan])


class TestGetIndexer:
def test_get_indexer_float64(self):
idx = Float64Index([0.0, 1.0, 2.0])
tm.assert_numpy_array_equal(
idx.get_indexer(idx), np.array([0, 1, 2], dtype=np.intp)
)

target = [-0.1, 0.5, 1.1]
tm.assert_numpy_array_equal(
idx.get_indexer(target, "pad"), np.array([-1, 0, 1], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "backfill"), np.array([0, 1, 2], dtype=np.intp)
)
tm.assert_numpy_array_equal(
idx.get_indexer(target, "nearest"), np.array([0, 1, 1], dtype=np.intp)
)

def test_get_indexer_nan(self):
# GH#7820
result = Float64Index([1, 2, np.nan]).get_indexer([np.nan])
expected = np.array([2], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)

def test_get_indexer_int64(self):
index = Int64Index(range(0, 20, 2))
target = Int64Index(np.arange(10))
indexer = index.get_indexer(target)
expected = np.array([0, -1, 1, -1, 2, -1, 3, -1, 4, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = Int64Index(np.arange(10))
indexer = index.get_indexer(target, method="pad")
expected = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = Int64Index(np.arange(10))
indexer = index.get_indexer(target, method="backfill")
expected = np.array([0, 1, 1, 2, 2, 3, 3, 4, 4, 5], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

def test_get_indexer_uint64(self, index_large):
target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2 ** 63)
indexer = index_large.get_indexer(target)
expected = np.array([0, -1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2 ** 63)
indexer = index_large.get_indexer(target, method="pad")
expected = np.array([0, 0, 1, 2, 3, 4, 4, 4, 4, 4], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)

target = UInt64Index(np.arange(10).astype("uint64") * 5 + 2 ** 63)
indexer = index_large.get_indexer(target, method="backfill")
expected = np.array([0, 1, 1, 2, 3, 4, -1, -1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(indexer, expected)


class TestWhere:
@pytest.mark.parametrize(
"index",
[
Float64Index(np.arange(5, dtype="float64")),
Int64Index(range(0, 20, 2)),
UInt64Index(np.arange(5, dtype="uint64")),
],
)
@pytest.mark.parametrize("klass", [list, tuple, np.array, Series])
def test_where(self, klass, index):
cond = [True] * len(index)
expected = index
result = index.where(klass(cond))

cond = [False] + [True] * (len(index) - 1)
expected = Float64Index([index._na_value] + index[1:].tolist())
result = index.where(klass(cond))
tm.assert_index_equal(result, expected)


class TestTake:
@pytest.mark.parametrize("klass", [Float64Index, Int64Index, UInt64Index])
def test_take_preserve_name(self, klass):
index = klass([1, 2, 3, 4], name="foo")
taken = index.take([3, 0, 1])
assert index.name == taken.name

def test_take_fill_value_float64(self):
# GH 12631
idx = Float64Index([1.0, 2.0, 3.0], name="xxx")
result = idx.take(np.array([1, 0, -1]))
expected = Float64Index([2.0, 1.0, 3.0], name="xxx")
tm.assert_index_equal(result, expected)

# fill_value
result = idx.take(np.array([1, 0, -1]), fill_value=True)
expected = Float64Index([2.0, 1.0, np.nan], name="xxx")
tm.assert_index_equal(result, expected)

# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = Float64Index([2.0, 1.0, 3.0], name="xxx")
tm.assert_index_equal(result, expected)

msg = (
"When allow_fill=True and fill_value is not None, "
"all indices must be >= -1"
)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -5]), fill_value=True)

msg = "index -5 is out of bounds for (axis 0 with )?size 3"
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))

@pytest.mark.parametrize("klass", [Int64Index, UInt64Index])
def test_take_fill_value_ints(self, klass):
# see gh-12631
idx = klass([1, 2, 3], name="xxx")
result = idx.take(np.array([1, 0, -1]))
expected = klass([2, 1, 3], name="xxx")
tm.assert_index_equal(result, expected)

name = klass.__name__
msg = f"Unable to fill values because {name} cannot contain NA"

# fill_value=True
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -1]), fill_value=True)

# allow_fill=False
result = idx.take(np.array([1, 0, -1]), allow_fill=False, fill_value=True)
expected = klass([2, 1, 3], name="xxx")
tm.assert_index_equal(result, expected)

with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -2]), fill_value=True)
with pytest.raises(ValueError, match=msg):
idx.take(np.array([1, 0, -5]), fill_value=True)

msg = "index -5 is out of bounds for (axis 0 with )?size 3"
with pytest.raises(IndexError, match=msg):
idx.take(np.array([1, -5]))


class TestContains:
def test_contains_float64_nans(self):
index = Float64Index([1.0, 2.0, np.nan])
assert np.nan in index

def test_contains_float64_not_nans(self):
index = Float64Index([1.0, 2.0, np.nan])
assert 1.0 in index
Loading