def parse_to_dataframe(
self,
group: List[str],
metadata: Optional[Union[BatteryMetadata, dict]] = None
) -> BatteryDataFrame:
"""Parse a set of files into a Pandas dataframe
Parameters
----------
group: list of str
List of files to parse as part of the same test. Ordered sequentially
metadata: dict, optional
Metadata for the battery, should adhere to the BatteryMetadata schema
Returns
-------
pd.DataFrame
DataFrame containing the information from all files
"""
# Initialize counters for the cycle numbers, etc.. Used to determine offsets for the
start_cycle = 0
start_time = 0
# Read the data for each file
# Keep track of the ending index and ending time
output_dfs = []
for file_number, file in enumerate(group):
# Read the file
df_out = self.generate_dataframe(file, file_number, start_cycle,
start_time)
output_dfs.append(df_out)
# Increment the start cycle and time to determine starting point of next file
start_cycle += df_out['cycle_number'].max(
) - df_out['cycle_number'].min() + 1
start_time = df_out['test_time'].max()
# Combine the data from all files
df_out = pd.concat(output_dfs, ignore_index=True)
# Attach the metadata and return the data
return BatteryDataFrame(data=df_out, metadata=metadata)
def test_df():
return BatteryDataFrame(data={
'current': [1, 0, -1],
'voltage': [2, 2, 2]
},
metadata={'name': 'Test data'})