lattice/pyerrors
1
0
Fork 0
mirror of https://github.com/fjosw/pyerrors.git synced 2025-03-15 06:40:24 +01:00
Code Issues Projects Releases Packages Wiki Activity

feat: pandas DataFrame serialization and deserialization can now also

Browse source 
deal with gzipped json columns. Tests added.
This commit is contained in:
Fabian Joswig 2022-07-04 14:19:30 +01:00
parent a133030114
commit cc9f47c686
2 changed files with 23 additions and 3 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

17
pyerrors/input/pandas.py
View file

@ -22,7 +22,7 @@ def dump_df(df, fname, gz=True):
If True, the output is a gzipped csv file. If False, the output is a csv file.
"""
out = serialize_df(df)
out = serialize_df(df, gz=False)
if not fname.endswith('.csv'):
fname += '.csv'
@ -62,21 +62,25 @@ def load_df(fname, auto_gamma=False, gz=True):
warnings.warn("Trying to read from %s without unzipping!" % fname, UserWarning)
re_import = pd.read_csv(fname)
return deserialize_df(re_import, auto_gamma)
return deserialize_df(re_import, auto_gamma=auto_gamma)
def serialize_df(df):
def serialize_df(df, gz=False):
"""Serializes all Obs or Corr valued columns into json strings according to the pyerrors json specification.
Parameters
----------
df : pandas.DataFrame
DataFrame to be serilized.
gz: bool
gzip the json string represenation. Default False.
"""
out = df.copy()
for column in out:
if isinstance(out[column][0], (Obs, Corr)):
out[column] = out[column].transform(lambda x: create_json_string(x, indent=0))
if gz is True:
out[column] = out[column].transform(lambda x: gzip.compress(x.encode('utf-8')))
return out
@ -90,8 +94,15 @@ def deserialize_df(df, auto_gamma=False):
auto_gamma : bool
If True applies the gamma_method to all imported Obs objects with the default parameters for
the error analysis. Default False.
Notes:
------
In case any column of the DataFrame is gzipped it is gunzipped in the process.
"""
for column in df.select_dtypes(include="object"):
if isinstance(df[column][0], bytes):
if df[column][0].startswith(b"\x1f\x8b\x08\x00"):
df[column] = df[column].transform(lambda x: gzip.decompress(x).decode('utf-8'))
if isinstance(df[column][0], str):
if df[column][0][:20] == '{"program":"pyerrors':
df[column] = df[column].transform(lambda x: import_json_string(x, verbose=False))

9
tests/pandas_test.py
View file

@ -42,3 +42,12 @@ def test_pe_export_default_import(tmp_path):
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)