509 lines
16 KiB
Python
509 lines
16 KiB
Python
import numpy as np
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import pytest
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from pandas.core.dtypes.common import ensure_platform_int
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import pandas as pd
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from pandas import Float64Index, Index, Int64Index, RangeIndex
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import pandas._testing as tm
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from ..test_numeric import Numeric
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# aliases to make some tests easier to read
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RI = RangeIndex
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I64 = Int64Index
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F64 = Float64Index
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OI = Index
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class TestRangeIndex(Numeric):
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_holder = RangeIndex
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_compat_props = ["shape", "ndim", "size"]
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@pytest.fixture(
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params=[
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RangeIndex(start=0, stop=20, step=2, name="foo"),
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RangeIndex(start=18, stop=-1, step=-2, name="bar"),
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],
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ids=["index_inc", "index_dec"],
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)
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def index(self, request):
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return request.param
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def create_index(self) -> RangeIndex:
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return RangeIndex(start=0, stop=20, step=2)
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def test_can_hold_identifiers(self):
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idx = self.create_index()
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key = idx[0]
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assert idx._can_hold_identifiers_and_holds_name(key) is False
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def test_too_many_names(self):
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index = self.create_index()
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with pytest.raises(ValueError, match="^Length"):
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index.names = ["roger", "harold"]
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@pytest.mark.parametrize(
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"index, start, stop, step",
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[
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(RangeIndex(5), 0, 5, 1),
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(RangeIndex(0, 5), 0, 5, 1),
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(RangeIndex(5, step=2), 0, 5, 2),
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(RangeIndex(1, 5, 2), 1, 5, 2),
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],
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)
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def test_start_stop_step_attrs(self, index, start, stop, step):
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# GH 25710
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assert index.start == start
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assert index.stop == stop
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assert index.step == step
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@pytest.mark.parametrize("attr_name", ["_start", "_stop", "_step"])
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def test_deprecated_start_stop_step_attrs(self, attr_name):
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# GH 26581
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idx = self.create_index()
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with tm.assert_produces_warning(FutureWarning):
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getattr(idx, attr_name)
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def test_copy(self):
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i = RangeIndex(5, name="Foo")
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i_copy = i.copy()
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assert i_copy is not i
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assert i_copy.identical(i)
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assert i_copy._range == range(0, 5, 1)
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assert i_copy.name == "Foo"
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def test_repr(self):
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i = RangeIndex(5, name="Foo")
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result = repr(i)
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expected = "RangeIndex(start=0, stop=5, step=1, name='Foo')"
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assert result == expected
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result = eval(result)
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tm.assert_index_equal(result, i, exact=True)
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i = RangeIndex(5, 0, -1)
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result = repr(i)
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expected = "RangeIndex(start=5, stop=0, step=-1)"
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assert result == expected
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result = eval(result)
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tm.assert_index_equal(result, i, exact=True)
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def test_insert(self):
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idx = RangeIndex(5, name="Foo")
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result = idx[1:4]
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# test 0th element
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tm.assert_index_equal(idx[0:4], result.insert(0, idx[0]))
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# GH 18295 (test missing)
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expected = Float64Index([0, np.nan, 1, 2, 3, 4])
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for na in [np.nan, None, pd.NA]:
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result = RangeIndex(5).insert(1, na)
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tm.assert_index_equal(result, expected)
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result = RangeIndex(5).insert(1, pd.NaT)
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expected = Index([0, pd.NaT, 1, 2, 3, 4], dtype=object)
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tm.assert_index_equal(result, expected)
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def test_delete(self):
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idx = RangeIndex(5, name="Foo")
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expected = idx[1:].astype(int)
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result = idx.delete(0)
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tm.assert_index_equal(result, expected)
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assert result.name == expected.name
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expected = idx[:-1].astype(int)
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result = idx.delete(-1)
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tm.assert_index_equal(result, expected)
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assert result.name == expected.name
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msg = "index 5 is out of bounds for axis 0 with size 5"
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with pytest.raises((IndexError, ValueError), match=msg):
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# either depending on numpy version
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result = idx.delete(len(idx))
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def test_view(self):
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i = RangeIndex(0, name="Foo")
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i_view = i.view()
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assert i_view.name == "Foo"
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i_view = i.view("i8")
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tm.assert_numpy_array_equal(i.values, i_view)
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i_view = i.view(RangeIndex)
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tm.assert_index_equal(i, i_view)
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def test_dtype(self):
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index = self.create_index()
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assert index.dtype == np.int64
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def test_cache(self):
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# GH 26565, GH26617, GH35432
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# This test checks whether _cache has been set.
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# Calling RangeIndex._cache["_data"] creates an int64 array of the same length
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# as the RangeIndex and stores it in _cache.
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idx = RangeIndex(0, 100, 10)
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assert idx._cache == {}
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repr(idx)
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assert idx._cache == {}
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str(idx)
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assert idx._cache == {}
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idx.get_loc(20)
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assert idx._cache == {}
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90 in idx # True
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assert idx._cache == {}
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91 in idx # False
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assert idx._cache == {}
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idx.all()
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assert idx._cache == {}
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idx.any()
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assert idx._cache == {}
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for _ in idx:
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pass
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assert idx._cache == {}
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idx.format()
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assert idx._cache == {}
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df = pd.DataFrame({"a": range(10)}, index=idx)
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str(df)
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assert idx._cache == {}
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df.loc[50]
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assert idx._cache == {}
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with pytest.raises(KeyError, match="51"):
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df.loc[51]
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assert idx._cache == {}
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df.loc[10:50]
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assert idx._cache == {}
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df.iloc[5:10]
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assert idx._cache == {}
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# idx._cache should contain a _data entry after call to idx._data
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idx._data
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assert isinstance(idx._data, np.ndarray)
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assert idx._data is idx._data # check cached value is reused
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assert len(idx._cache) == 4
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expected = np.arange(0, 100, 10, dtype="int64")
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tm.assert_numpy_array_equal(idx._cache["_data"], expected)
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def test_is_monotonic(self):
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index = RangeIndex(0, 20, 2)
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assert index.is_monotonic is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is False
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is False
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index = RangeIndex(4, 0, -1)
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assert index.is_monotonic is False
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assert index._is_strictly_monotonic_increasing is False
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_decreasing is True
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index = RangeIndex(1, 2)
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assert index.is_monotonic is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is True
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index = RangeIndex(2, 1)
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assert index.is_monotonic is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is True
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index = RangeIndex(1, 1)
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assert index.is_monotonic is True
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assert index.is_monotonic_increasing is True
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assert index.is_monotonic_decreasing is True
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assert index._is_strictly_monotonic_increasing is True
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assert index._is_strictly_monotonic_decreasing is True
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def test_equals_range(self):
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equiv_pairs = [
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(RangeIndex(0, 9, 2), RangeIndex(0, 10, 2)),
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(RangeIndex(0), RangeIndex(1, -1, 3)),
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(RangeIndex(1, 2, 3), RangeIndex(1, 3, 4)),
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(RangeIndex(0, -9, -2), RangeIndex(0, -10, -2)),
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]
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for left, right in equiv_pairs:
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assert left.equals(right)
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assert right.equals(left)
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def test_logical_compat(self):
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idx = self.create_index()
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assert idx.all() == idx.values.all()
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assert idx.any() == idx.values.any()
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def test_identical(self):
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index = self.create_index()
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i = Index(index.copy())
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assert i.identical(index)
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# we don't allow object dtype for RangeIndex
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if isinstance(index, RangeIndex):
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return
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same_values_different_type = Index(i, dtype=object)
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assert not i.identical(same_values_different_type)
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i = index.copy(dtype=object)
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i = i.rename("foo")
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same_values = Index(i, dtype=object)
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assert same_values.identical(index.copy(dtype=object))
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assert not i.identical(index)
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assert Index(same_values, name="foo", dtype=object).identical(i)
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assert not index.copy(dtype=object).identical(index.copy(dtype="int64"))
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def test_nbytes(self):
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# memory savings vs int index
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i = RangeIndex(0, 1000)
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assert i.nbytes < i._int64index.nbytes / 10
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# constant memory usage
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i2 = RangeIndex(0, 10)
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assert i.nbytes == i2.nbytes
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@pytest.mark.parametrize(
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"start,stop,step",
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[
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# can't
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("foo", "bar", "baz"),
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# shouldn't
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("0", "1", "2"),
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],
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)
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def test_cant_or_shouldnt_cast(self, start, stop, step):
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msg = f"Wrong type {type(start)} for value {start}"
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with pytest.raises(TypeError, match=msg):
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RangeIndex(start, stop, step)
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def test_view_index(self):
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index = self.create_index()
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index.view(Index)
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def test_prevent_casting(self):
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index = self.create_index()
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result = index.astype("O")
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assert result.dtype == np.object_
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def test_repr_roundtrip(self):
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index = self.create_index()
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tm.assert_index_equal(eval(repr(index)), index)
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def test_slice_keep_name(self):
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idx = RangeIndex(1, 2, name="asdf")
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assert idx.name == idx[1:].name
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def test_has_duplicates(self, index):
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assert index.is_unique
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assert not index.has_duplicates
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def test_extended_gcd(self):
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index = self.create_index()
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result = index._extended_gcd(6, 10)
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assert result[0] == result[1] * 6 + result[2] * 10
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assert 2 == result[0]
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result = index._extended_gcd(10, 6)
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assert 2 == result[1] * 10 + result[2] * 6
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assert 2 == result[0]
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def test_min_fitting_element(self):
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result = RangeIndex(0, 20, 2)._min_fitting_element(1)
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assert 2 == result
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result = RangeIndex(1, 6)._min_fitting_element(1)
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assert 1 == result
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result = RangeIndex(18, -2, -2)._min_fitting_element(1)
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assert 2 == result
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result = RangeIndex(5, 0, -1)._min_fitting_element(1)
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assert 1 == result
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big_num = 500000000000000000000000
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result = RangeIndex(5, big_num * 2, 1)._min_fitting_element(big_num)
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assert big_num == result
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def test_max_fitting_element(self):
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result = RangeIndex(0, 20, 2)._max_fitting_element(17)
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assert 16 == result
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result = RangeIndex(1, 6)._max_fitting_element(4)
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assert 4 == result
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result = RangeIndex(18, -2, -2)._max_fitting_element(17)
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assert 16 == result
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result = RangeIndex(5, 0, -1)._max_fitting_element(4)
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assert 4 == result
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big_num = 500000000000000000000000
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result = RangeIndex(5, big_num * 2, 1)._max_fitting_element(big_num)
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assert big_num == result
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def test_pickle_compat_construction(self):
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# RangeIndex() is a valid constructor
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pass
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def test_slice_specialised(self):
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index = self.create_index()
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index.name = "foo"
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# scalar indexing
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res = index[1]
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expected = 2
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assert res == expected
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res = index[-1]
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expected = 18
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assert res == expected
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# slicing
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# slice value completion
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index_slice = index[:]
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expected = index
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tm.assert_index_equal(index_slice, expected)
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# positive slice values
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index_slice = index[7:10:2]
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expected = Index(np.array([14, 18]), name="foo")
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tm.assert_index_equal(index_slice, expected)
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# negative slice values
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index_slice = index[-1:-5:-2]
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expected = Index(np.array([18, 14]), name="foo")
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tm.assert_index_equal(index_slice, expected)
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# stop overshoot
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index_slice = index[2:100:4]
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expected = Index(np.array([4, 12]), name="foo")
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tm.assert_index_equal(index_slice, expected)
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# reverse
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index_slice = index[::-1]
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expected = Index(index.values[::-1], name="foo")
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tm.assert_index_equal(index_slice, expected)
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index_slice = index[-8::-1]
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expected = Index(np.array([4, 2, 0]), name="foo")
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tm.assert_index_equal(index_slice, expected)
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index_slice = index[-40::-1]
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expected = Index(np.array([], dtype=np.int64), name="foo")
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tm.assert_index_equal(index_slice, expected)
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index_slice = index[40::-1]
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expected = Index(index.values[40::-1], name="foo")
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tm.assert_index_equal(index_slice, expected)
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index_slice = index[10::-1]
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expected = Index(index.values[::-1], name="foo")
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tm.assert_index_equal(index_slice, expected)
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@pytest.mark.parametrize("step", set(range(-5, 6)) - {0})
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def test_len_specialised(self, step):
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# make sure that our len is the same as np.arange calc
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start, stop = (0, 5) if step > 0 else (5, 0)
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arr = np.arange(start, stop, step)
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index = RangeIndex(start, stop, step)
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assert len(index) == len(arr)
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index = RangeIndex(stop, start, step)
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assert len(index) == 0
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@pytest.fixture(
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params=[
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([RI(1, 12, 5)], RI(1, 12, 5)),
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([RI(0, 6, 4)], RI(0, 6, 4)),
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([RI(1, 3), RI(3, 7)], RI(1, 7)),
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([RI(1, 5, 2), RI(5, 6)], RI(1, 6, 2)),
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([RI(1, 3, 2), RI(4, 7, 3)], RI(1, 7, 3)),
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([RI(-4, 3, 2), RI(4, 7, 2)], RI(-4, 7, 2)),
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([RI(-4, -8), RI(-8, -12)], RI(0, 0)),
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([RI(-4, -8), RI(3, -4)], RI(0, 0)),
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([RI(-4, -8), RI(3, 5)], RI(3, 5)),
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([RI(-4, -2), RI(3, 5)], I64([-4, -3, 3, 4])),
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([RI(-2), RI(3, 5)], RI(3, 5)),
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([RI(2), RI(2)], I64([0, 1, 0, 1])),
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([RI(2), RI(2, 5), RI(5, 8, 4)], RI(0, 6)),
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([RI(2), RI(3, 5), RI(5, 8, 4)], I64([0, 1, 3, 4, 5])),
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([RI(-2, 2), RI(2, 5), RI(5, 8, 4)], RI(-2, 6)),
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([RI(3), I64([-1, 3, 15])], I64([0, 1, 2, -1, 3, 15])),
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([RI(3), F64([-1, 3.1, 15.0])], F64([0, 1, 2, -1, 3.1, 15.0])),
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([RI(3), OI(["a", None, 14])], OI([0, 1, 2, "a", None, 14])),
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([RI(3, 1), OI(["a", None, 14])], OI(["a", None, 14])),
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]
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)
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def appends(self, request):
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"""Inputs and expected outputs for RangeIndex.append test"""
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return request.param
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def test_append(self, appends):
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# GH16212
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indices, expected = appends
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result = indices[0].append(indices[1:])
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tm.assert_index_equal(result, expected, exact=True)
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if len(indices) == 2:
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# Append single item rather than list
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result2 = indices[0].append(indices[1])
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tm.assert_index_equal(result2, expected, exact=True)
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def test_engineless_lookup(self):
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# GH 16685
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# Standard lookup on RangeIndex should not require the engine to be
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# created
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idx = RangeIndex(2, 10, 3)
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assert idx.get_loc(5) == 1
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tm.assert_numpy_array_equal(
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idx.get_indexer([2, 8]), ensure_platform_int(np.array([0, 2]))
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)
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with pytest.raises(KeyError, match="3"):
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idx.get_loc(3)
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assert "_engine" not in idx._cache
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# Different types of scalars can be excluded immediately, no need to
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# use the _engine
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with pytest.raises(KeyError, match="'a'"):
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idx.get_loc("a")
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assert "_engine" not in idx._cache
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def test_format_empty(self):
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# GH35712
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empty_idx = self._holder(0)
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assert empty_idx.format() == []
|
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assert empty_idx.format(name=True) == [""]
|