BDS+PyProBE

Question

I already have raw cycler files. How do I prepare PyProBE diagnostic tables with BDS?

Use This When

Use this path when you need clean time, current, voltage, cycle, and step fields before running a diagnostic workflow such as HPPC, GITT, OCV, rate testing, or capacity checks in PyProBE or a PyProBE-adjacent notebook.

Convert Raw Files

bds convert raw.mpt pyprobe_staging.parquet \
  --target pyprobe \
  --format parquet \
  --current-sign preserve \
  --repair-policy repair \
  --report pyprobe_staging.report.json

Create A Diagnostic Staging Table

import polars as pl
 
diagnostic = pl.read_parquet("pyprobe_staging.parquet")

Suggested Mapping

Select Diagnostic Segments

For HPPC-like pulse analysis, it is often better to pass a selected segment than the whole raw test:

hppc_cycle = diagnostic.filter(pl.col("cycle_index") == 5)
hppc_cycle.write_parquet("pyprobe_hppc_cycle_005.parquet")

For GITT-like analysis, preserve step_index and step_time_s; they are usually needed to separate pulse and relaxation steps.

EIS Data

If the raw file is EIS-only:

bds convert-eis gamry.DTA pyprobe_eis.parquet --format parquet

Then use Frequency_Hz, Zre_exp_Ohm, and Zim_exp_Ohm as the normalized EIS handoff columns.

Known Limits

• PyProBE workflows may expect project-specific metadata beyond the time-series table. Keep the BDS conversion report and any lab metadata next to the staging Parquet file.
• This page documents a normalized staging table, not a promise that every PyProBE version has a native BDS importer.
• If your PyProBE workflow has a formal procedure schema, add the schema fields as a metadata sidecar rather than encoding them in column names.