Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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205 lines
7.8 KiB
205 lines
7.8 KiB
import numpy as np
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import pytest
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from pandas._libs import lib, writers as libwriters
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import pandas as pd
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from pandas import Index
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import pandas._testing as tm
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class TestMisc:
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def test_max_len_string_array(self):
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arr = a = np.array(["foo", "b", np.nan], dtype="object")
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assert libwriters.max_len_string_array(arr) == 3
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# unicode
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arr = a.astype("U").astype(object)
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assert libwriters.max_len_string_array(arr) == 3
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# bytes for python3
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arr = a.astype("S").astype(object)
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assert libwriters.max_len_string_array(arr) == 3
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# raises
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msg = "No matching signature found"
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with pytest.raises(TypeError, match=msg):
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libwriters.max_len_string_array(arr.astype("U"))
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def test_fast_unique_multiple_list_gen_sort(self):
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keys = [["p", "a"], ["n", "d"], ["a", "s"]]
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gen = (key for key in keys)
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expected = np.array(["a", "d", "n", "p", "s"])
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out = lib.fast_unique_multiple_list_gen(gen, sort=True)
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tm.assert_numpy_array_equal(np.array(out), expected)
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gen = (key for key in keys)
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expected = np.array(["p", "a", "n", "d", "s"])
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out = lib.fast_unique_multiple_list_gen(gen, sort=False)
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tm.assert_numpy_array_equal(np.array(out), expected)
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def test_fast_unique_multiple_unsortable_runtimewarning(self):
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arr = [np.array(["foo", pd.Timestamp("2000")])]
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with tm.assert_produces_warning(RuntimeWarning):
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lib.fast_unique_multiple(arr, sort=None)
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class TestIndexing:
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def test_maybe_indices_to_slice_left_edge(self):
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target = np.arange(100)
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# slice
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indices = np.array([], dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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for end in [1, 2, 5, 20, 99]:
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for step in [1, 2, 4]:
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indices = np.arange(0, end, step, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# reverse
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indices = indices[::-1]
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# not slice
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for case in [[2, 1, 2, 0], [2, 2, 1, 0], [0, 1, 2, 1], [-2, 0, 2], [2, 0, -2]]:
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indices = np.array(case, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert not isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(maybe_slice, indices)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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def test_maybe_indices_to_slice_right_edge(self):
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target = np.arange(100)
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# slice
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for start in [0, 2, 5, 20, 97, 98]:
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for step in [1, 2, 4]:
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indices = np.arange(start, 99, step, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# reverse
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indices = indices[::-1]
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# not slice
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indices = np.array([97, 98, 99, 100], dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert not isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(maybe_slice, indices)
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msg = "index 100 is out of bounds for axis (0|1) with size 100"
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with pytest.raises(IndexError, match=msg):
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target[indices]
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with pytest.raises(IndexError, match=msg):
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target[maybe_slice]
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indices = np.array([100, 99, 98, 97], dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert not isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(maybe_slice, indices)
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with pytest.raises(IndexError, match=msg):
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target[indices]
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with pytest.raises(IndexError, match=msg):
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target[maybe_slice]
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for case in [[99, 97, 99, 96], [99, 99, 98, 97], [98, 98, 97, 96]]:
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indices = np.array(case, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert not isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(maybe_slice, indices)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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def test_maybe_indices_to_slice_both_edges(self):
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target = np.arange(10)
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# slice
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for step in [1, 2, 4, 5, 8, 9]:
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indices = np.arange(0, 9, step, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# reverse
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indices = indices[::-1]
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# not slice
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for case in [[4, 2, 0, -2], [2, 2, 1, 0], [0, 1, 2, 1]]:
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indices = np.array(case, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert not isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(maybe_slice, indices)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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def test_maybe_indices_to_slice_middle(self):
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target = np.arange(100)
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# slice
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for start, end in [(2, 10), (5, 25), (65, 97)]:
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for step in [1, 2, 4, 20]:
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indices = np.arange(start, end, step, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# reverse
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indices = indices[::-1]
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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# not slice
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for case in [[14, 12, 10, 12], [12, 12, 11, 10], [10, 11, 12, 11]]:
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indices = np.array(case, dtype=np.intp)
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maybe_slice = lib.maybe_indices_to_slice(indices, len(target))
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assert not isinstance(maybe_slice, slice)
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tm.assert_numpy_array_equal(maybe_slice, indices)
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tm.assert_numpy_array_equal(target[indices], target[maybe_slice])
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def test_maybe_booleans_to_slice(self):
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arr = np.array([0, 0, 1, 1, 1, 0, 1], dtype=np.uint8)
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result = lib.maybe_booleans_to_slice(arr)
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assert result.dtype == np.bool_
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result = lib.maybe_booleans_to_slice(arr[:0])
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assert result == slice(0, 0)
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def test_get_reverse_indexer(self):
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indexer = np.array([-1, -1, 1, 2, 0, -1, 3, 4], dtype=np.int64)
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result = lib.get_reverse_indexer(indexer, 5)
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expected = np.array([4, 2, 3, 6, 7], dtype=np.int64)
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tm.assert_numpy_array_equal(result, expected)
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def test_cache_readonly_preserve_docstrings():
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# GH18197
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assert Index.hasnans.__doc__ is not None
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