arista.ingest.parsers.laurin

Walk Laurin Büld’s ms-thesis/result/*.csv tree.

Each processed CSV has 7 columns: an unnamed pandas index, then frames, temperatureDeg, targetTempDeg, deltaFbyF, time_sec, dFbF_driftCorr. The header column temperatureDeg may be empty (NaN) for pre-stimulus frames where the sensor MAT had no data; the schema’s sensor_t_c column already permits NULL.

Filenames follow <strain>_<cell>_<sex>_a<cell_num>_e<animal_num>_<stim>_driftCorr-<method>_<date>.csv, where the legacy massiveAligner writes:

  • strain — canonical strain name (nompC_het / nompC_hom / wt / UASnompC_UASGCaMP-Gr28bd_Gal4-arista)

  • cell — cell-type code in lower case (cc / hc)

  • sex — m / f

  • a<n> — cell number within type (1-based)

  • e<n> — experiment / animal-of-the-day number

  • stim — stimulus name (adaptation for the thesis batch)

  • driftCorr — linear / poly / exp / None

  • date — YYYY-MM-DD

Laurin’s filenames do not encode arista hemisphere, so every recording gets hemisphere = None in the DB. The raw deltaFbyF column populates samples.dfbf; the drift-corrected dFbF_driftCorr column populates samples.dfbf_drift_corrected. The drift method recorded in recordings.drift_correction is read from the filename.

Module Attributes

DEFAULT_FPS

Laurin's recordings were acquired at the same 10 fps as Robert's.

Functions

discover_laurin_records(source_root)

Yield one DiscoveryResult per CSV under ms-thesis/result/.
arista.ingest.parsers.laurin.DEFAULT_FPS = 10.0

Laurin’s recordings were acquired at the same 10 fps as Robert’s.

arista.ingest.parsers.laurin.discover_laurin_records(source_root)[source]

Yield one DiscoveryResult per CSV under ms-thesis/result/.

The expected tree is a flat <source_root>/*.csv with no subdirectories — Laurin’s massiveAligner writes all outputs into one result/ folder regardless of strain or stimulus.

Parameters:

source_root (Path) – Path to ms-thesis/result/.

Return type:

Iterator[DiscoveryResult]