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feat: pandas DataFrames with Corr columns can now also be imported and

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exported.
This commit is contained in:
Fabian Joswig 2022-06-30 15:26:31 +01:00
parent c7c1725667
commit 153cc795b8
2 changed files with 14 additions and 2 deletions
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5
pyerrors/input/pandas.py
View file

@ -2,6 +2,7 @@ import warnings
import gzip import gzip
import pandas as pd import pandas as pd
from ..obs import Obs from ..obs import Obs
from ..correlators import Corr
from .json import create_json_string, import_json_string from .json import create_json_string, import_json_string
@ -23,7 +24,7 @@ def dump_df(df, fname, gz=True):
out = df.copy() out = df.copy()
for column in out: for column in out:
if isinstance(out[column][0], Obs): if isinstance(out[column][0], (Obs, Corr)):
out[column] = out[column].transform(lambda x: create_json_string(x, indent=0)) out[column] = out[column].transform(lambda x: create_json_string(x, indent=0))
if not fname.endswith('.csv'): if not fname.endswith('.csv'):
@ -67,6 +68,6 @@ def load_df(fname, auto_gamma=False, gz=True):
if re_import[column][0][:20] == '{"program":"pyerrors': if re_import[column][0][:20] == '{"program":"pyerrors':
re_import[column] = re_import[column].transform(lambda x: import_json_string(x, verbose=False)) re_import[column] = re_import[column].transform(lambda x: import_json_string(x, verbose=False))
if auto_gamma is True: if auto_gamma is True:
re_import[column].apply(Obs.gamma_method) re_import[column].apply(lambda x: x.gamma_method())
return re_import return re_import

11
tests/pandas_test.py
View file

@ -17,3 +17,14 @@ def test_df_export_import(tmp_path):
pe.input.pandas.load_df((tmp_path / 'df_output.csv').as_posix(), gz=gz) 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)