"""
This module includes functions used in the set_index method of the Data class.
Various patterns are required because the result data index depends on
the required data types.
"""
import pandas as pd
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def from_req(Data, req_no):
"""Copy index from the required data index.
Args:
Data (Data): Data object to paste index.
req_no (int): Indicator number of the required data list to copy index.
"""
index_cols = Data.info.get_column_name("index")
index_req = Data.reqs[req_no].info.file_index()[
index_cols].drop_duplicates()
if len(Data.info.index) > 0:
index_self = Data.info.index[index_cols]
Data.info.index = pd.concat([index_self, index_req]).drop_duplicates()
else:
Data.info.index = index_req
Data.info.set_index_file_no()
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def from_data(Data):
"""Get index from result pandas.DataFrame data.
This function can only be used for
:class:`~slitflow.tbl.table.Table` objects.
Args:
Data (Table): Table data containing result :class:`pandas.DataFrame`.
"""
index_cols = Data.info.get_column_name("index")
if (len(index_cols) > 0) & (len(Data.data) > 0):
index = pd.concat(Data.data)[index_cols].drop_duplicates()
if len(Data.info.index) == 0:
Data.info.index = pd.DataFrame(columns=index_cols)
Data.info.index = pd.merge(
Data.info.index, index, on=index_cols, how="outer")
Data.info.set_index_file_no()
else:
# for split data with no data
Data.info.index = pd.DataFrame(columns=index_cols)
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def from_req_plus_data(Data, req_no):
"""Copy index from required data index and result pandas.DataFrame.
This function can only be used for
:class:`~slitflow.tbl.table.Table` objects. This function is not
used in general classes.
Args:
Data (Data): Data object containing result :class:`pandas.DataFrame` to
paste index.
req_no (int): Indicator number of the required data list to copy index.
"""
index_cols_req = Data.reqs[req_no].info.get_column_name(
"index") + ["_split", "_file"]
index_req = Data.reqs[req_no].info.file_index()[
index_cols_req].drop_duplicates()
index_cols = Data.info.get_column_name("index")
index_data = pd.concat(Data.data)[index_cols].drop_duplicates()
and_list = list(set(index_data) & set(index_req))
index = pd.merge(index_data, index_req, on=and_list)
Data.info.index = pd.concat([Data.info.index, index]).drop_duplicates()