99 lines
3.0 KiB
Python
99 lines
3.0 KiB
Python
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import numpy as np
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import pytest
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from pandas import MultiIndex
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import pandas._testing as tm
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def test_numeric_compat(idx):
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with pytest.raises(TypeError, match="cannot perform __mul__"):
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idx * 1
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with pytest.raises(TypeError, match="cannot perform __rmul__"):
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1 * idx
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div_err = "cannot perform __truediv__"
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with pytest.raises(TypeError, match=div_err):
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idx / 1
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div_err = div_err.replace(" __", " __r")
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with pytest.raises(TypeError, match=div_err):
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1 / idx
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with pytest.raises(TypeError, match="cannot perform __floordiv__"):
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idx // 1
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with pytest.raises(TypeError, match="cannot perform __rfloordiv__"):
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1 // idx
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@pytest.mark.parametrize("method", ["all", "any", "__invert__"])
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def test_logical_compat(idx, method):
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msg = f"cannot perform {method}"
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with pytest.raises(TypeError, match=msg):
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getattr(idx, method)()
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def test_inplace_mutation_resets_values():
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levels = [["a", "b", "c"], [4]]
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levels2 = [[1, 2, 3], ["a"]]
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codes = [[0, 1, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0]]
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mi1 = MultiIndex(levels=levels, codes=codes)
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mi2 = MultiIndex(levels=levels2, codes=codes)
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# instantiating MultiIndex should not access/cache _.values
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assert "_values" not in mi1._cache
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assert "_values" not in mi2._cache
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vals = mi1.values.copy()
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vals2 = mi2.values.copy()
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# accessing .values should cache ._values
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assert mi1._values is mi1._cache["_values"]
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assert mi1.values is mi1._cache["_values"]
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assert isinstance(mi1._cache["_values"], np.ndarray)
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# Make sure level setting works
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new_vals = mi1.set_levels(levels2).values
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tm.assert_almost_equal(vals2, new_vals)
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# Non-inplace doesn't drop _values from _cache [implementation detail]
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tm.assert_almost_equal(mi1._cache["_values"], vals)
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# ...and values is still same too
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tm.assert_almost_equal(mi1.values, vals)
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# Inplace should drop _values from _cache
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with tm.assert_produces_warning(FutureWarning):
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mi1.set_levels(levels2, inplace=True)
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assert "_values" not in mi1._cache
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tm.assert_almost_equal(mi1.values, vals2)
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# Make sure label setting works too
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codes2 = [[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]]
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exp_values = np.empty((6,), dtype=object)
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exp_values[:] = [(1, "a")] * 6
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# Must be 1d array of tuples
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assert exp_values.shape == (6,)
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new_mi = mi2.set_codes(codes2)
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assert "_values" not in new_mi._cache
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new_values = new_mi.values
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assert "_values" in new_mi._cache
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# Not inplace shouldn't change
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tm.assert_almost_equal(mi2._cache["_values"], vals2)
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# Should have correct values
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tm.assert_almost_equal(exp_values, new_values)
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# ...and again setting inplace should drop _values from _cache, etc
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with tm.assert_produces_warning(FutureWarning):
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mi2.set_codes(codes2, inplace=True)
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assert "_values" not in mi2._cache
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tm.assert_almost_equal(mi2.values, new_values)
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assert "_values" in mi2._cache
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