Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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160 lines
4.3 KiB
160 lines
4.3 KiB
4 years ago
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import collections
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from distutils.version import LooseVersion
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from functools import partial
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import string
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import numpy as np
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import pytest
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from pandas.compat.numpy import _np_version_under1p17
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import pandas as pd
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from pandas import Series, Timestamp
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from pandas.core import ops
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import pandas.core.common as com
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def test_get_callable_name():
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getname = com.get_callable_name
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def fn(x):
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return x
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lambda_ = lambda x: x # noqa: E731
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part1 = partial(fn)
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part2 = partial(part1)
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class somecall:
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def __call__(self):
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return x # noqa
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assert getname(fn) == "fn"
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assert getname(lambda_)
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assert getname(part1) == "fn"
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assert getname(part2) == "fn"
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assert getname(somecall()) == "somecall"
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assert getname(1) is None
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def test_any_none():
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assert com.any_none(1, 2, 3, None)
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assert not com.any_none(1, 2, 3, 4)
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def test_all_not_none():
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assert com.all_not_none(1, 2, 3, 4)
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assert not com.all_not_none(1, 2, 3, None)
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assert not com.all_not_none(None, None, None, None)
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def test_random_state():
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import numpy.random as npr
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# Check with seed
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state = com.random_state(5)
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assert state.uniform() == npr.RandomState(5).uniform()
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# Check with random state object
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state2 = npr.RandomState(10)
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assert com.random_state(state2).uniform() == npr.RandomState(10).uniform()
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# check with no arg random state
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assert com.random_state() is np.random
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# check array-like
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# GH32503
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state_arr_like = npr.randint(0, 2 ** 31, size=624, dtype="uint32")
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assert (
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com.random_state(state_arr_like).uniform()
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== npr.RandomState(state_arr_like).uniform()
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)
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# Check BitGenerators
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# GH32503
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if not _np_version_under1p17:
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assert (
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com.random_state(npr.MT19937(3)).uniform()
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== npr.RandomState(npr.MT19937(3)).uniform()
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)
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assert (
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com.random_state(npr.PCG64(11)).uniform()
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== npr.RandomState(npr.PCG64(11)).uniform()
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)
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# Error for floats or strings
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msg = (
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"random_state must be an integer, array-like, a BitGenerator, "
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"a numpy RandomState, or None"
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)
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with pytest.raises(ValueError, match=msg):
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com.random_state("test")
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with pytest.raises(ValueError, match=msg):
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com.random_state(5.5)
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@pytest.mark.parametrize(
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"left, right, expected",
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[
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(Series([1], name="x"), Series([2], name="x"), "x"),
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(Series([1], name="x"), Series([2], name="y"), None),
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(Series([1]), Series([2], name="x"), None),
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(Series([1], name="x"), Series([2]), None),
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(Series([1], name="x"), [2], "x"),
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([1], Series([2], name="y"), "y"),
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],
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)
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def test_maybe_match_name(left, right, expected):
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assert ops._maybe_match_name(left, right) == expected
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def test_dict_compat():
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data_datetime64 = {np.datetime64("1990-03-15"): 1, np.datetime64("2015-03-15"): 2}
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data_unchanged = {1: 2, 3: 4, 5: 6}
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expected = {Timestamp("1990-3-15"): 1, Timestamp("2015-03-15"): 2}
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assert com.dict_compat(data_datetime64) == expected
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assert com.dict_compat(expected) == expected
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assert com.dict_compat(data_unchanged) == data_unchanged
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def test_standardize_mapping():
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# No uninitialized defaultdicts
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msg = r"to_dict\(\) only accepts initialized defaultdicts"
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with pytest.raises(TypeError, match=msg):
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com.standardize_mapping(collections.defaultdict)
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# No non-mapping subtypes, instance
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msg = "unsupported type: <class 'list'>"
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with pytest.raises(TypeError, match=msg):
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com.standardize_mapping([])
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# No non-mapping subtypes, class
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with pytest.raises(TypeError, match=msg):
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com.standardize_mapping(list)
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fill = {"bad": "data"}
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assert com.standardize_mapping(fill) == dict
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# Convert instance to type
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assert com.standardize_mapping({}) == dict
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dd = collections.defaultdict(list)
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assert isinstance(com.standardize_mapping(dd), partial)
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def test_git_version():
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# GH 21295
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git_version = pd.__git_version__
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assert len(git_version) == 40
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assert all(c in string.hexdigits for c in git_version)
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def test_version_tag():
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version = pd.__version__
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try:
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version > LooseVersion("0.0.1")
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except TypeError:
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raise ValueError(
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"No git tags exist, please sync tags between upstream and your repo"
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)
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