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53 lines
2 KiB
Python
53 lines
2 KiB
Python
import numpy as np
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import pandas as pd
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import pyerrors as pe
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def test_df_export_import(tmp_path):
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my_dict = {"int": 1,
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"float": -0.01,
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"Obs1": pe.pseudo_Obs(87, 21, "test_ensemble"),
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"Obs2": pe.pseudo_Obs(-87, 21, "test_ensemble2")}
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for gz in [True, False]:
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my_df = pd.DataFrame([my_dict] * 10)
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pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix(), gz=gz)
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reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True, gz=gz)
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assert np.all(my_df == reconstructed_df)
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pe.input.pandas.load_df((tmp_path / 'df_output.csv').as_posix(), gz=gz)
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def test_df_Corr(tmp_path):
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my_corr = pe.Corr([pe.pseudo_Obs(-0.48, 0.04, "test"), pe.pseudo_Obs(-0.154, 0.03, "test")])
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my_dict = {"int": 1,
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"float": -0.01,
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"Corr": my_corr}
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my_df = pd.DataFrame([my_dict] * 5)
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pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix())
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reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True)
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def test_default_export_pe_import(tmp_path):
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df = pd.DataFrame([{"Column1": 1.1, "Column2": 2, "Column3": "my string£"}])
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df.to_csv((tmp_path / 'plain_df.csv').as_posix(), index=False)
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re_df = pe.input.pandas.load_df((tmp_path / 'plain_df').as_posix(), gz=False)
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assert np.all(df == re_df)
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def test_pe_export_default_import(tmp_path):
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df = pd.DataFrame([{"Column1": 1.1, "Column2": 2, "Column3": "my string£"}])
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pe.input.pandas.dump_df(df, (tmp_path / 'pe_df').as_posix(), gz=False)
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re_df = pd.read_csv((tmp_path / 'pe_df.csv').as_posix())
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assert np.all(df == re_df)
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def test_gz_serialization():
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my_obs = pe.pseudo_Obs(0.1, 0.01, "pandas DataFrame ensemble only for test purposes.")
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my_df = pd.DataFrame([{"Label": 1, "Obs": my_obs}])
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for gz in [False, True]:
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ser = pe.input.pandas.serialize_df(my_df, gz=gz)
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deser = pe.input.pandas.deserialize_df(ser)
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np.all(my_df == deser)
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