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BDS+cellpy

I already have raw cycler files. How do I stage them for cellpy workflows with BDS?

BDS+cellpy

Question

I already have raw cycler files. How do I stage them for cellpy workflows with BDS?

Use This When

Use this path when BDS can read a raw cycler export and you want a stable, unit-normalized table before moving data into a cellpy project.

BDS is not a replacement for cellpy's native instrument loaders. The practical integration is to use BDS as a pre-normalization step and then write a cellpy-like staging CSV with the columns a cellpy loader or local import script can map.

Convert Raw Files

bds convert raw.mpt cellpy_staging.csv --target cellpy --current-sign preserve --repair-policy repair

Create A cellpy-Like Staging CSV

import polars as pl
 
cellpy_like = pl.read_csv("cellpy_staging.csv")

If your source file does not contain every optional capacity or energy column, the target export omits those optional columns. Add null columns in your local import script only if your cellpy workflow requires them.

Suggested Mapping

BDS export column cellpy-like staging column
Record Index data_point
Date Time datetime
Test Time (s) test_time
Step Time (s) step_time
Cycle Count cycle_index
Step Index step_index
Current (A) current
Voltage (V) voltage
Charging Capacity (Ah) charge_capacity
Discharging Capacity (Ah) discharge_capacity
Charging Energy (Wh) charge_energy
Discharging Energy (Wh) discharge_energy

Keep The Raw File

Keep the original raw file and the BDS conversion report alongside cellpy_staging.csv. The report records which adapter was used, what columns were mapped, and what repairs were applied.

Known Limits

  • This page describes a staging table, not a guaranteed native .h5 cellpy file writer.
  • A production cellpy workflow should still define a local loader or import function that maps the staging columns into the exact cellpy version used by the lab.
  • Capacity sign conventions should be checked against the downstream cellpy workflow before fitting or reporting capacities.