ionworksdata 0.6.1

Data processing for Ionworks software.

Ionworks Data Processing

A library for processing experimental battery data into a common format for use in Ionworks software.

Overview

Ionworks Data Processing (ionworksdata) provides readers for cycler file formats (Maccor, Biologic, Neware, Novonix, Repower, CSV, and more), transforms time series data into a standardized format, and summarizes and labels steps for analysis or use in other Ionworks tools (e.g. the Ionworks pipeline and ionworks-schema).

Full API and usage details are in the Ionworks Data Processing documentation.

Package structure

• read — Read raw data from files: time_series, time_series_and_steps, measurement_details; readers include biologic, biologic_mpt, maccor, neware, novonix, repower, csv, and others (reader is auto-detected when not specified).
• transform — Transform time series into Ionworks-compatible form (step count, cycle count, capacity, energy, etc.).
• steps — Summarize time series into step-level data and label steps (cycling, pulse, EIS) for processing or visualization.
• load — Load processed data for use in other Ionworks software (DataLoader, OCPDataLoader). DataLoader.data and .steps return Polars DataFrames; use .data.to_pandas() or .steps.to_pandas() for pandas. When loading from the database with DataLoader.from_db(...), data is loaded on demand: .initial_voltage and .steps load only the steps table; .data also loads the time series.

Installation

pip install ionworksdata

Quick start

Processing time series data

Extract time series data from a cycler file with read.time_series. The reader can be specified explicitly or auto-detected. The function returns a Polars DataFrame.

import ionworksdata as iwdata

# With explicit reader
data = iwdata.read.time_series("path/to/file.mpt", "biologic_mpt")

# With auto-detection (reader is optional)
data = iwdata.read.time_series("path/to/file.mpt")

The function automatically performs several processing steps and adds columns to the output.

Data processing steps

1. Reader-specific processing (varies by reader):

   • Column renaming to standardized names (e.g. "Voltage" → "Voltage [V]")
   • Numeric coercion (removing thousands separators, converting strings to numbers)
   • Dropping message/error rows (for some readers)
   • Parsing timestamp columns and computing time if needed
   • Converting time units (e.g. hours to seconds)
   • Fixing unsigned current (if current is always positive, negate during charge)
   • Validating and fixing decreasing times (if time_offset_fix option is set)

2. Standard data processing (applied to all readers):

   • Removing rows with null values in current or voltage columns
   • Converting numeric columns to float64
   • Resetting time to start at zero
   • Offsetting duplicate timestamps by a small amount (1e-6 s) to preserve all data points
   • Setting discharge current to be positive (charge current remains negative)

3. Post-processing:

   • Adding Step count, Cycle count, Discharge capacity [A.h], Charge capacity [A.h], Discharge energy [W.h], Charge energy [W.h]

Output columns

Column	Description
Time [s]	Time in seconds
Current [A]	Current in amperes
Voltage [V]	Voltage in volts
Step count	Cumulative step count (always present)
Cycle count	Cumulative cycle count, defaults to 0 if no cycle information (always present)
Discharge capacity [A.h]	Discharge capacity in ampere-hours (always present)
Charge capacity [A.h]	Charge capacity in ampere-hours (always present)
Discharge energy [W.h]	Discharge energy in watt-hours (always present)
Charge energy [W.h]	Charge energy in watt-hours (always present)
Step from cycler	Step number from cycler file (if provided)
Cycle from cycler	Cycle number from cycler file (if provided)
Temperature [degC]	Temperature in degrees Celsius (if provided)
Frequency [Hz]	Frequency in hertz (if provided)

For expected and returned columns per reader, see the API documentation. Extra columns can be mapped via extra_column_mappings:

data = iwdata.read.time_series(
    "path/to/file.mpt", "biologic_mpt",
    extra_column_mappings={"Old column name": "My new column"},
)

Processing step data

From processed time series, step summary data is obtained with steps.summarize:

steps = iwdata.steps.summarize(data)

This detects steps from the Step count column and computes metrics per step. The output always includes:

Column	Description
Cycle count	Cumulative cycle count (defaults to 0 if no cycle information)
Cycle from cycler	Cycle number from cycler file (only if provided in input)
Discharge capacity [A.h]	Discharge capacity for the step
Charge capacity [A.h]	Charge capacity for the step
Discharge energy [W.h]	Discharge energy for the step
Charge energy [W.h]	Charge energy for the step
Step from cycler	Step number from cycler file (only if provided in input)

Additional per-step columns include start/end time and index, start/end/min/max/mean/std for voltage and current, duration, step type, and (after labeling) cycle-level capacity and energy. See the API documentation for the full list.

Note: Step identification uses Step count and, when available, Cycle from cycler for cycle tracking.

Alternatively, get time series and steps in one call:

# With explicit reader
data, steps = iwdata.read.time_series_and_steps("path/to/file.mpt", "biologic_mpt")

# With auto-detection (reader is optional)
data, steps = iwdata.read.time_series_and_steps("path/to/file.mpt")

Labeling steps

Steps can be labeled using the steps module (e.g. cycling, pulse, and EIS):

options = {"cell_metadata": {"Nominal cell capacity [A.h]": 5}}
steps = iwdata.steps.label_cycling(steps, options)
for direction in ["charge", "discharge"]:
    options["current direction"] = direction
    steps = iwdata.steps.label_pulse(steps, options)
steps = iwdata.steps.label_eis(steps)

Measurement details

read.measurement_details returns a dictionary with measurement, time_series, and steps. Pass the file path, a measurement dict (e.g. test name), and optionally the reader and options; the function fills in time series and steps and updates the measurement dict (e.g. cycler name, start time). Steps are labeled with default labels unless you pass a custom labels list:

measurement = {"name": "My test"}
measurement_details = iwdata.read.measurement_details(
    "path/to/file.mpt",
    measurement,
    "biologic_mpt",
    options={"cell_metadata": {"Nominal cell capacity [A.h]": 5}},
)
measurement = measurement_details["measurement"]
time_series = measurement_details["time_series"]
steps = measurement_details["steps"]

Data format

Processed data follows the format expected by Ionworks software. Column names, units, and conventions are described in the Ionworks Data Processing documentation.

Resources

• Ionworks Data Processing documentation — API reference, readers, and data format.
• Ionworks Pipeline documentation — Using processed data in pipelines.
• Ionworks documentation — Platform and product overview.