Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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82 lines
2.0 KiB
82 lines
2.0 KiB
4 years ago
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import numpy as np
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import pytest
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from pandas.core.dtypes import dtypes
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from pandas.core.dtypes.common import is_extension_array_dtype
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import pandas as pd
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import pandas._testing as tm
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from pandas.core.arrays import ExtensionArray
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class DummyDtype(dtypes.ExtensionDtype):
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pass
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class DummyArray(ExtensionArray):
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def __init__(self, data):
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self.data = data
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def __array__(self, dtype):
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return self.data
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@property
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def dtype(self):
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return DummyDtype()
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def astype(self, dtype, copy=True):
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# we don't support anything but a single dtype
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if isinstance(dtype, DummyDtype):
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if copy:
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return type(self)(self.data)
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return self
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return np.array(self, dtype=dtype, copy=copy)
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class TestExtensionArrayDtype:
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@pytest.mark.parametrize(
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"values",
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[
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pd.Categorical([]),
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pd.Categorical([]).dtype,
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pd.Series(pd.Categorical([])),
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DummyDtype(),
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DummyArray(np.array([1, 2])),
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],
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)
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def test_is_extension_array_dtype(self, values):
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assert is_extension_array_dtype(values)
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@pytest.mark.parametrize("values", [np.array([]), pd.Series(np.array([]))])
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def test_is_not_extension_array_dtype(self, values):
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assert not is_extension_array_dtype(values)
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def test_astype():
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arr = DummyArray(np.array([1, 2, 3]))
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expected = np.array([1, 2, 3], dtype=object)
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result = arr.astype(object)
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tm.assert_numpy_array_equal(result, expected)
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result = arr.astype("object")
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tm.assert_numpy_array_equal(result, expected)
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def test_astype_no_copy():
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arr = DummyArray(np.array([1, 2, 3], dtype=np.int64))
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result = arr.astype(arr.dtype, copy=False)
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assert arr is result
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result = arr.astype(arr.dtype)
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assert arr is not result
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@pytest.mark.parametrize("dtype", [dtypes.CategoricalDtype(), dtypes.IntervalDtype()])
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def test_is_extension_array_dtype(dtype):
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assert isinstance(dtype, dtypes.ExtensionDtype)
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assert is_extension_array_dtype(dtype)
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