mirror of
https://github.com/fjosw/pyerrors.git
synced 2025-03-16 23:30:24 +01:00
53 lines
2 KiB
Python
53 lines
2 KiB
Python
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)
|
|
|
|
|
|
def test_default_export_pe_import(tmp_path):
|
|
df = pd.DataFrame([{"Column1": 1.1, "Column2": 2, "Column3": "my string£"}])
|
|
df.to_csv((tmp_path / 'plain_df.csv').as_posix(), index=False)
|
|
re_df = pe.input.pandas.load_df((tmp_path / 'plain_df').as_posix(), gz=False)
|
|
assert np.all(df == re_df)
|
|
|
|
|
|
def test_pe_export_default_import(tmp_path):
|
|
df = pd.DataFrame([{"Column1": 1.1, "Column2": 2, "Column3": "my string£"}])
|
|
pe.input.pandas.dump_df(df, (tmp_path / 'pe_df').as_posix(), gz=False)
|
|
re_df = pd.read_csv((tmp_path / 'pe_df.csv').as_posix())
|
|
assert np.all(df == re_df)
|
|
|
|
|
|
def test_gz_serialization():
|
|
my_obs = pe.pseudo_Obs(0.1, 0.01, "pandas DataFrame ensemble only for test purposes.")
|
|
my_df = pd.DataFrame([{"Label": 1, "Obs": my_obs}])
|
|
for gz in [False, True]:
|
|
ser = pe.input.pandas.serialize_df(my_df, gz=gz)
|
|
deser = pe.input.pandas.deserialize_df(ser)
|
|
np.all(my_df == deser)
|