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test_lib.py
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import numpy as np
import pytest
from pandas._libs import (
Timedelta,
lib,
writers as libwriters,
)
from pandas import Index
import pandas._testing as tm
class TestMisc:
def test_max_len_string_array(self):
arr = a = np.array(["foo", "b", np.nan], dtype="object")
assert libwriters.max_len_string_array(arr) == 3
# unicode
arr = a.astype("U").astype(object)
assert libwriters.max_len_string_array(arr) == 3
# bytes for python3
arr = a.astype("S").astype(object)
assert libwriters.max_len_string_array(arr) == 3
# raises
msg = "No matching signature found"
with pytest.raises(TypeError, match=msg):
libwriters.max_len_string_array(arr.astype("U"))
def test_fast_unique_multiple_list_gen_sort(self):
keys = [["p", "a"], ["n", "d"], ["a", "s"]]
gen = (key for key in keys)
expected = np.array(["a", "d", "n", "p", "s"])
out = lib.fast_unique_multiple_list_gen(gen, sort=True)
tm.assert_numpy_array_equal(np.array(out), expected)
gen = (key for key in keys)
expected = np.array(["p", "a", "n", "d", "s"])
out = lib.fast_unique_multiple_list_gen(gen, sort=False)
tm.assert_numpy_array_equal(np.array(out), expected)
def test_fast_multiget_timedelta_resos(self):
# This will become relevant for test_constructor_dict_timedelta64_index
# once Timedelta constructor preserves reso when passed a
# np.timedelta64 object
td = Timedelta(days=1)
mapping1 = {td: 1}
mapping2 = {td.as_unit("s"): 1}
oindex = Index([td * n for n in range(3)])._values.astype(object)
expected = lib.fast_multiget(mapping1, oindex)
result = lib.fast_multiget(mapping2, oindex)
tm.assert_numpy_array_equal(result, expected)
# case that can't be cast to td64ns
td = Timedelta(np.timedelta64(146000, "D"))
assert hash(td) == hash(td.as_unit("ms"))
assert hash(td) == hash(td.as_unit("us"))
mapping1 = {td: 1}
mapping2 = {td.as_unit("ms"): 1}
oindex = Index([td * n for n in range(3)])._values.astype(object)
expected = lib.fast_multiget(mapping1, oindex)
result = lib.fast_multiget(mapping2, oindex)
tm.assert_numpy_array_equal(result, expected)
class TestIndexing:
def test_maybe_indices_to_slice_left_edge(self):
target = np.arange(100)
# slice
indices = np.array([], dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize("end", [1, 2, 5, 20, 99])
@pytest.mark.parametrize("step", [1, 2, 4])
def test_maybe_indices_to_slice_left_edge_not_slice_end_steps(self, end, step):
target = np.arange(100)
indices = np.arange(0, end, step, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
# reverse
indices = indices[::-1]
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize(
"case", [[2, 1, 2, 0], [2, 2, 1, 0], [0, 1, 2, 1], [-2, 0, 2], [2, 0, -2]]
)
def test_maybe_indices_to_slice_left_edge_not_slice(self, case):
# not slice
target = np.arange(100)
indices = np.array(case, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert not isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(maybe_slice, indices)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize("start", [0, 2, 5, 20, 97, 98])
@pytest.mark.parametrize("step", [1, 2, 4])
def test_maybe_indices_to_slice_right_edge(self, start, step):
target = np.arange(100)
# slice
indices = np.arange(start, 99, step, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
# reverse
indices = indices[::-1]
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
def test_maybe_indices_to_slice_right_edge_not_slice(self):
# not slice
target = np.arange(100)
indices = np.array([97, 98, 99, 100], dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert not isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(maybe_slice, indices)
msg = "index 100 is out of bounds for axis (0|1) with size 100"
with pytest.raises(IndexError, match=msg):
target[indices]
with pytest.raises(IndexError, match=msg):
target[maybe_slice]
indices = np.array([100, 99, 98, 97], dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert not isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(maybe_slice, indices)
with pytest.raises(IndexError, match=msg):
target[indices]
with pytest.raises(IndexError, match=msg):
target[maybe_slice]
@pytest.mark.parametrize(
"case", [[99, 97, 99, 96], [99, 99, 98, 97], [98, 98, 97, 96]]
)
def test_maybe_indices_to_slice_right_edge_cases(self, case):
target = np.arange(100)
indices = np.array(case, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert not isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(maybe_slice, indices)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize("step", [1, 2, 4, 5, 8, 9])
def test_maybe_indices_to_slice_both_edges(self, step):
target = np.arange(10)
# slice
indices = np.arange(0, 9, step, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
# reverse
indices = indices[::-1]
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize("case", [[4, 2, 0, -2], [2, 2, 1, 0], [0, 1, 2, 1]])
def test_maybe_indices_to_slice_both_edges_not_slice(self, case):
# not slice
target = np.arange(10)
indices = np.array(case, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert not isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(maybe_slice, indices)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize("start, end", [(2, 10), (5, 25), (65, 97)])
@pytest.mark.parametrize("step", [1, 2, 4, 20])
def test_maybe_indices_to_slice_middle(self, start, end, step):
target = np.arange(100)
# slice
indices = np.arange(start, end, step, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
# reverse
indices = indices[::-1]
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
@pytest.mark.parametrize(
"case", [[14, 12, 10, 12], [12, 12, 11, 10], [10, 11, 12, 11]]
)
def test_maybe_indices_to_slice_middle_not_slice(self, case):
# not slice
target = np.arange(100)
indices = np.array(case, dtype=np.intp)
maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
assert not isinstance(maybe_slice, slice)
tm.assert_numpy_array_equal(maybe_slice, indices)
tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
def test_maybe_booleans_to_slice(self):
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_get_reverse_indexer(self):
indexer = np.array([-1, -1, 1, 2, 0, -1, 3, 4], dtype=np.intp)
result = lib.get_reverse_indexer(indexer, 5)
expected = np.array([4, 2, 3, 6, 7], dtype=np.intp)
tm.assert_numpy_array_equal(result, expected)
@pytest.mark.parametrize("dtype", ["int64", "int32"])
def test_is_range_indexer(self, dtype):
# GH#50592
left = np.arange(0, 100, dtype=dtype)
assert lib.is_range_indexer(left, 100)
@pytest.mark.parametrize("dtype", ["int64", "int32"])
def test_is_range_indexer_not_equal(self, dtype):
# GH#50592
left = np.array([1, 2], dtype=dtype)
assert not lib.is_range_indexer(left, 2)
@pytest.mark.parametrize("dtype", ["int64", "int32"])
def test_is_range_indexer_not_equal_shape(self, dtype):
# GH#50592
left = np.array([0, 1, 2], dtype=dtype)
assert not lib.is_range_indexer(left, 2)
def test_cache_readonly_preserve_docstrings():
# GH18197
assert Index.hasnans.__doc__ is not None
def test_no_default_pickle():
# GH#40397
obj = tm.round_trip_pickle(lib.no_default)
assert obj is lib.no_default