Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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335 lines
11 KiB
335 lines
11 KiB
4 years ago
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import numpy as np
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import pytest
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import pandas as pd
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import pandas._testing as tm
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from .base import BaseExtensionTests
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class BaseSetitemTests(BaseExtensionTests):
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def test_setitem_scalar_series(self, data, box_in_series):
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if box_in_series:
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data = pd.Series(data)
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data[0] = data[1]
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assert data[0] == data[1]
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def test_setitem_sequence(self, data, box_in_series):
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if box_in_series:
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data = pd.Series(data)
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original = data.copy()
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data[[0, 1]] = [data[1], data[0]]
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assert data[0] == original[1]
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assert data[1] == original[0]
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def test_setitem_sequence_mismatched_length_raises(self, data, as_array):
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ser = pd.Series(data)
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original = ser.copy()
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value = [data[0]]
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if as_array:
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value = data._from_sequence(value)
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xpr = "cannot set using a {} indexer with a different length"
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with pytest.raises(ValueError, match=xpr.format("list-like")):
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ser[[0, 1]] = value
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# Ensure no modifications made before the exception
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self.assert_series_equal(ser, original)
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with pytest.raises(ValueError, match=xpr.format("slice")):
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ser[slice(3)] = value
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self.assert_series_equal(ser, original)
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def test_setitem_empty_indxer(self, data, box_in_series):
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if box_in_series:
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data = pd.Series(data)
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original = data.copy()
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data[np.array([], dtype=int)] = []
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self.assert_equal(data, original)
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def test_setitem_sequence_broadcasts(self, data, box_in_series):
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if box_in_series:
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data = pd.Series(data)
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data[[0, 1]] = data[2]
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assert data[0] == data[2]
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assert data[1] == data[2]
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@pytest.mark.parametrize("setter", ["loc", "iloc"])
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def test_setitem_scalar(self, data, setter):
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arr = pd.Series(data)
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setter = getattr(arr, setter)
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setter[0] = data[1]
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assert arr[0] == data[1]
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def test_setitem_loc_scalar_mixed(self, data):
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df = pd.DataFrame({"A": np.arange(len(data)), "B": data})
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df.loc[0, "B"] = data[1]
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assert df.loc[0, "B"] == data[1]
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def test_setitem_loc_scalar_single(self, data):
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df = pd.DataFrame({"B": data})
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df.loc[10, "B"] = data[1]
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assert df.loc[10, "B"] == data[1]
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def test_setitem_loc_scalar_multiple_homogoneous(self, data):
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df = pd.DataFrame({"A": data, "B": data})
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df.loc[10, "B"] = data[1]
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assert df.loc[10, "B"] == data[1]
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def test_setitem_iloc_scalar_mixed(self, data):
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df = pd.DataFrame({"A": np.arange(len(data)), "B": data})
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df.iloc[0, 1] = data[1]
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assert df.loc[0, "B"] == data[1]
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def test_setitem_iloc_scalar_single(self, data):
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df = pd.DataFrame({"B": data})
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df.iloc[10, 0] = data[1]
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assert df.loc[10, "B"] == data[1]
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def test_setitem_iloc_scalar_multiple_homogoneous(self, data):
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df = pd.DataFrame({"A": data, "B": data})
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df.iloc[10, 1] = data[1]
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assert df.loc[10, "B"] == data[1]
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@pytest.mark.parametrize(
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"mask",
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[
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np.array([True, True, True, False, False]),
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pd.array([True, True, True, False, False], dtype="boolean"),
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pd.array([True, True, True, pd.NA, pd.NA], dtype="boolean"),
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],
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ids=["numpy-array", "boolean-array", "boolean-array-na"],
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)
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def test_setitem_mask(self, data, mask, box_in_series):
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arr = data[:5].copy()
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expected = arr.take([0, 0, 0, 3, 4])
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if box_in_series:
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arr = pd.Series(arr)
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expected = pd.Series(expected)
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arr[mask] = data[0]
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self.assert_equal(expected, arr)
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def test_setitem_mask_raises(self, data, box_in_series):
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# wrong length
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mask = np.array([True, False])
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if box_in_series:
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data = pd.Series(data)
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with pytest.raises(IndexError, match="wrong length"):
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data[mask] = data[0]
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mask = pd.array(mask, dtype="boolean")
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with pytest.raises(IndexError, match="wrong length"):
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data[mask] = data[0]
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def test_setitem_mask_boolean_array_with_na(self, data, box_in_series):
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mask = pd.array(np.zeros(data.shape, dtype="bool"), dtype="boolean")
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mask[:3] = True
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mask[3:5] = pd.NA
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if box_in_series:
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data = pd.Series(data)
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data[mask] = data[0]
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assert (data[:3] == data[0]).all()
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@pytest.mark.parametrize(
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"idx",
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[[0, 1, 2], pd.array([0, 1, 2], dtype="Int64"), np.array([0, 1, 2])],
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ids=["list", "integer-array", "numpy-array"],
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)
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def test_setitem_integer_array(self, data, idx, box_in_series):
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arr = data[:5].copy()
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expected = data.take([0, 0, 0, 3, 4])
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if box_in_series:
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arr = pd.Series(arr)
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expected = pd.Series(expected)
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arr[idx] = arr[0]
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self.assert_equal(arr, expected)
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@pytest.mark.parametrize(
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"idx, box_in_series",
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[
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([0, 1, 2, pd.NA], False),
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pytest.param(
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[0, 1, 2, pd.NA], True, marks=pytest.mark.xfail(reason="GH-31948")
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),
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(pd.array([0, 1, 2, pd.NA], dtype="Int64"), False),
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(pd.array([0, 1, 2, pd.NA], dtype="Int64"), False),
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],
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ids=["list-False", "list-True", "integer-array-False", "integer-array-True"],
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)
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def test_setitem_integer_with_missing_raises(self, data, idx, box_in_series):
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arr = data.copy()
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# TODO(xfail) this raises KeyError about labels not found (it tries label-based)
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# for list of labels with Series
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if box_in_series:
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arr = pd.Series(data, index=[tm.rands(4) for _ in range(len(data))])
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msg = "Cannot index with an integer indexer containing NA values"
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with pytest.raises(ValueError, match=msg):
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arr[idx] = arr[0]
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@pytest.mark.parametrize("as_callable", [True, False])
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@pytest.mark.parametrize("setter", ["loc", None])
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def test_setitem_mask_aligned(self, data, as_callable, setter):
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ser = pd.Series(data)
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mask = np.zeros(len(data), dtype=bool)
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mask[:2] = True
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if as_callable:
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mask2 = lambda x: mask
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else:
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mask2 = mask
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if setter:
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# loc
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target = getattr(ser, setter)
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else:
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# Series.__setitem__
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target = ser
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target[mask2] = data[5:7]
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ser[mask2] = data[5:7]
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assert ser[0] == data[5]
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assert ser[1] == data[6]
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@pytest.mark.parametrize("setter", ["loc", None])
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def test_setitem_mask_broadcast(self, data, setter):
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ser = pd.Series(data)
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mask = np.zeros(len(data), dtype=bool)
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mask[:2] = True
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if setter: # loc
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target = getattr(ser, setter)
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else: # __setitem__
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target = ser
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target[mask] = data[10]
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assert ser[0] == data[10]
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assert ser[1] == data[10]
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def test_setitem_expand_columns(self, data):
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df = pd.DataFrame({"A": data})
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result = df.copy()
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result["B"] = 1
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expected = pd.DataFrame({"A": data, "B": [1] * len(data)})
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self.assert_frame_equal(result, expected)
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result = df.copy()
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result.loc[:, "B"] = 1
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self.assert_frame_equal(result, expected)
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# overwrite with new type
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result["B"] = data
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expected = pd.DataFrame({"A": data, "B": data})
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self.assert_frame_equal(result, expected)
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def test_setitem_expand_with_extension(self, data):
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df = pd.DataFrame({"A": [1] * len(data)})
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result = df.copy()
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result["B"] = data
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expected = pd.DataFrame({"A": [1] * len(data), "B": data})
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self.assert_frame_equal(result, expected)
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result = df.copy()
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result.loc[:, "B"] = data
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self.assert_frame_equal(result, expected)
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def test_setitem_frame_invalid_length(self, data):
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df = pd.DataFrame({"A": [1] * len(data)})
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xpr = (
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rf"Length of values \({len(data[:5])}\) "
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rf"does not match length of index \({len(df)}\)"
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)
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with pytest.raises(ValueError, match=xpr):
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df["B"] = data[:5]
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@pytest.mark.xfail(reason="GH#20441: setitem on extension types.")
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def test_setitem_tuple_index(self, data):
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s = pd.Series(data[:2], index=[(0, 0), (0, 1)])
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expected = pd.Series(data.take([1, 1]), index=s.index)
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s[(0, 1)] = data[1]
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self.assert_series_equal(s, expected)
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def test_setitem_slice(self, data, box_in_series):
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arr = data[:5].copy()
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expected = data.take([0, 0, 0, 3, 4])
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if box_in_series:
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arr = pd.Series(arr)
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expected = pd.Series(expected)
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arr[:3] = data[0]
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self.assert_equal(arr, expected)
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def test_setitem_loc_iloc_slice(self, data):
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arr = data[:5].copy()
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s = pd.Series(arr, index=["a", "b", "c", "d", "e"])
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expected = pd.Series(data.take([0, 0, 0, 3, 4]), index=s.index)
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result = s.copy()
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result.iloc[:3] = data[0]
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self.assert_equal(result, expected)
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result = s.copy()
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result.loc[:"c"] = data[0]
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self.assert_equal(result, expected)
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def test_setitem_slice_mismatch_length_raises(self, data):
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arr = data[:5]
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with pytest.raises(ValueError):
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arr[:1] = arr[:2]
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def test_setitem_slice_array(self, data):
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arr = data[:5].copy()
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arr[:5] = data[-5:]
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self.assert_extension_array_equal(arr, data[-5:])
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def test_setitem_scalar_key_sequence_raise(self, data):
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arr = data[:5].copy()
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with pytest.raises(ValueError):
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arr[0] = arr[[0, 1]]
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def test_setitem_preserves_views(self, data):
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# GH#28150 setitem shouldn't swap the underlying data
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view1 = data.view()
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view2 = data[:]
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data[0] = data[1]
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assert view1[0] == data[1]
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assert view2[0] == data[1]
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def test_setitem_dataframe_column_with_index(self, data):
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# https://github.com/pandas-dev/pandas/issues/32395
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df = expected = pd.DataFrame({"data": pd.Series(data)})
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result = pd.DataFrame(index=df.index)
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result.loc[df.index, "data"] = df["data"]
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self.assert_frame_equal(result, expected)
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def test_setitem_dataframe_column_without_index(self, data):
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# https://github.com/pandas-dev/pandas/issues/32395
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df = expected = pd.DataFrame({"data": pd.Series(data)})
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result = pd.DataFrame(index=df.index)
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result.loc[:, "data"] = df["data"]
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self.assert_frame_equal(result, expected)
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def test_setitem_series_with_index(self, data):
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# https://github.com/pandas-dev/pandas/issues/32395
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ser = expected = pd.Series(data, name="data")
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result = pd.Series(index=ser.index, dtype=object, name="data")
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result.loc[ser.index] = ser
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self.assert_series_equal(result, expected)
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def test_setitem_series_without_index(self, data):
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# https://github.com/pandas-dev/pandas/issues/32395
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ser = expected = pd.Series(data, name="data")
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result = pd.Series(index=ser.index, dtype=object, name="data")
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result.loc[:] = ser
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self.assert_series_equal(result, expected)
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