Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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32 lines
1.1 KiB
32 lines
1.1 KiB
4 years ago
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def _check_mixed_float(df, dtype=None):
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# float16 are most likely to be upcasted to float32
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dtypes = dict(A="float32", B="float32", C="float16", D="float64")
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if isinstance(dtype, str):
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dtypes = {k: dtype for k, v in dtypes.items()}
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elif isinstance(dtype, dict):
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dtypes.update(dtype)
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if dtypes.get("A"):
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assert df.dtypes["A"] == dtypes["A"]
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if dtypes.get("B"):
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assert df.dtypes["B"] == dtypes["B"]
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if dtypes.get("C"):
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assert df.dtypes["C"] == dtypes["C"]
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if dtypes.get("D"):
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assert df.dtypes["D"] == dtypes["D"]
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def _check_mixed_int(df, dtype=None):
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dtypes = dict(A="int32", B="uint64", C="uint8", D="int64")
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if isinstance(dtype, str):
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dtypes = {k: dtype for k, v in dtypes.items()}
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elif isinstance(dtype, dict):
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dtypes.update(dtype)
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if dtypes.get("A"):
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assert df.dtypes["A"] == dtypes["A"]
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if dtypes.get("B"):
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assert df.dtypes["B"] == dtypes["B"]
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if dtypes.get("C"):
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assert df.dtypes["C"] == dtypes["C"]
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if dtypes.get("D"):
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assert df.dtypes["D"] == dtypes["D"]
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