import numpy as np import pandas as pd import pyerrors as pe def test_df_export_import(tmp_path): my_dict = {"int": 1, "float": -0.01, "Obs1": pe.pseudo_Obs(87, 21, "test_ensemble"), "Obs2": pe.pseudo_Obs(-87, 21, "test_ensemble2")} for gz in [True, False]: my_df = pd.DataFrame([my_dict] * 10) pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix(), gz=gz) reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True, gz=gz) assert np.all(my_df == reconstructed_df) pe.input.pandas.load_df((tmp_path / 'df_output.csv').as_posix(), gz=gz) def test_df_Corr(tmp_path): my_corr = pe.Corr([pe.pseudo_Obs(-0.48, 0.04, "test"), pe.pseudo_Obs(-0.154, 0.03, "test")]) my_dict = {"int": 1, "float": -0.01, "Corr": my_corr} my_df = pd.DataFrame([my_dict] * 5) pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix()) reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True)