from pathlib import Path
from . import TECHNIQUE_CLASSES
import pickle
from ..data_series import TimeSeries, ValueSeries
from ..measurements import Measurement
from .biologic import BIOLOGIC_COLUMN_NAMES, get_column_unit_name
ECMSMeasurement = TECHNIQUE_CLASSES["EC-MS"]
[docs]class EC_MS_CONVERTER:
"""Imports old .pkl files obtained from the legacy EC-MS package"""
def __init__(self):
print("Reader of old ECMS .pkl files")
[docs] def read(self, file_path, cls=None, **kwargs):
"""Return an ECMSMeasurement with the data recorded in path_to_file
Most of the work is done by module-level function measurement_from_ec_ms_dataset
Args:
path_to_file (Path): The full abs or rel path including the
".pkl" extension.
"""
with open(file_path, "rb") as f:
ec_ms_dict = pickle.load(f)
return measurement_from_ec_ms_dataset(
ec_ms_dict,
name=Path(file_path).name,
cls=cls,
reader=self,
technique="EC-MS",
**kwargs,
)
[docs]def measurement_from_ec_ms_dataset(
ec_ms_dict,
name=None,
cls=ECMSMeasurement,
reader=None,
technique=None,
**kwargs,
):
"""Return an ixdat Measurement with the data from an EC_MS data dictionary.
This loops through the keys of the EC-MS dict and searches for MS and
EC data. Names the dataseries according to their names in the original
dict. Omits any other data as well as metadata.
Args:
ec_ms_dict (dict): The EC_MS data dictionary
name (str): Name of the measurement
cls (Measurement class): The class to return a measurement of
reader (Reader object): The class which read ec_ms_dataset from file
technique (str): The name of the technique
"""
if "Ewe/V" in ec_ms_dict and "<Ewe>/V" in ec_ms_dict:
# EC_MS duplicates the latter as the former, so here we delete it:
del ec_ms_dict["<Ewe>/V"]
if "I/mA" in ec_ms_dict and "<I>/mA" in ec_ms_dict:
# EC_MS duplicates the latter as the former, so here we delete it:
del ec_ms_dict["<I>/mA"]
cols_str = ec_ms_dict["data_cols"]
cols_list = []
name = name or ec_ms_dict.get("title", None)
for col in cols_str:
if col.endswith("-x"):
cols_list.append(TimeSeries(col, "s", ec_ms_dict[col], ec_ms_dict["tstamp"]))
if "time/s" in ec_ms_dict:
cols_list.append(
TimeSeries("time/s", "s", ec_ms_dict["time/s"], ec_ms_dict["tstamp"])
)
tseries_meas = Measurement("tseries_ms", technique="EC_MS", series_list=cols_list)
for col in cols_str:
if col not in ec_ms_dict or col in tseries_meas.series_names:
continue
if col.endswith("-y"):
v_name = col[:-2]
tseries = tseries_meas[col[:-1] + "x"]
unit_name = "A" if col.startswith("M") else ""
elif col in BIOLOGIC_COLUMN_NAMES and col not in tseries_meas.series_names:
v_name = col
tseries = tseries_meas["time/s"]
unit_name = get_column_unit_name(col)
else:
print(f"Not including '{col}' as I don't know what it is.")
continue
data = ec_ms_dict[col]
if not tseries.data.size == data.size:
print(f"Not including '{col}' due to mismatch size with {tseries}")
continue
cols_list.append(
ValueSeries(
name=v_name,
data=data,
unit_name=unit_name,
tseries=tseries,
)
)
aliases = {"t": ["time/s"], "raw_potential": ["Ewe/V"], "raw_current": ["I/mA"]}
obj_as_dict = dict(
name=name,
technique=technique or "EC_MS",
series_list=cols_list,
reader=reader,
tstamp=ec_ms_dict["tstamp"],
aliases=aliases,
)
obj_as_dict.update(kwargs)
measurement = cls.from_dict(obj_as_dict)
return measurement