Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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58 lines
1.8 KiB
58 lines
1.8 KiB
import numpy as np
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import pandas as pd
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from pandas.core.internals import ObjectBlock
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from .base import BaseExtensionTests
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class BaseCastingTests(BaseExtensionTests):
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"""Casting to and from ExtensionDtypes"""
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def test_astype_object_series(self, all_data):
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ser = pd.Series(all_data, name="A")
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result = ser.astype(object)
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assert isinstance(result._mgr.blocks[0], ObjectBlock)
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def test_astype_object_frame(self, all_data):
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df = pd.DataFrame({"A": all_data})
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result = df.astype(object)
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blk = result._data.blocks[0]
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assert isinstance(blk, ObjectBlock), type(blk)
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# FIXME: these currently fail; dont leave commented-out
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# check that we can compare the dtypes
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# cmp = result.dtypes.equals(df.dtypes)
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# assert not cmp.any()
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def test_tolist(self, data):
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result = pd.Series(data).tolist()
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expected = list(data)
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assert result == expected
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def test_astype_str(self, data):
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result = pd.Series(data[:5]).astype(str)
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expected = pd.Series([str(x) for x in data[:5]], dtype=str)
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self.assert_series_equal(result, expected)
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def test_astype_string(self, data):
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# GH-33465
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result = pd.Series(data[:5]).astype("string")
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expected = pd.Series([str(x) for x in data[:5]], dtype="string")
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self.assert_series_equal(result, expected)
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def test_to_numpy(self, data):
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expected = np.asarray(data)
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result = data.to_numpy()
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self.assert_equal(result, expected)
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result = pd.Series(data).to_numpy()
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self.assert_equal(result, expected)
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def test_astype_empty_dataframe(self, dtype):
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# https://github.com/pandas-dev/pandas/issues/33113
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df = pd.DataFrame()
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result = df.astype(dtype)
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self.assert_frame_equal(result, df)
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