ctdcast

Processing and reporting for shipboard CTD and LADCP data: raw Sea-Bird files → per-cast netCDF at each stage (read, trim, process/QC) → a compiled profiles.nc aligned with CF and CCHDO naming → self-contained HTML reports. Built for use at sea: every output works offline, with no external requests.

Documentation: https://ocean-uhh.github.io/ctdcast/ · example report

Installation

pip install ctdcast

Reading raw .cnv files needs seasenselib (pip install seasenselib). Python 3.10–3.13 is supported. See the installation notes for isolated-environment and from-source options.

Quick start

Raw CNV files fresh off the instrument — one command gives station pages, an index and a map:

ctdcast draft /path/to/cnv/ --cruise odb2026     # writes ./ctd_draft/index.html

For the full pipeline — sections, time series, LADCP, the sensor inventory — write a config and process stage by stage:

ctdcast init --interactive        # guided config.yaml
ctdcast validate config.yaml      # check paths before the first run
ctdcast process config.yaml --stage 1 2 3 profiles
ctdcast run config.yaml           # the report; --force rebuilds, --only 42 one cast

ctdcast clock config.yaml diagnoses the acquisition-clock error and prints a paste-ready processing.clock block. See the quickstart for the recommended first-cruise workflow, the config reference and the CLI reference.

To check an installation, run the bundled demo against the committed fixture casts:

ctdcast run config_demo.yaml      # writes demo_report/index.html

Python API

import ctdcast

ctdcast.report("ctd_nc", "report", profiles_path="profiles.nc",
               groupings_yaml="ctd_groupings.yaml")

See the API reference for process, stage1, profiles and the full interface.

Acknowledgements

Development of this package started during the Odón de Buen cruise of AEI-DFG DS-MIXSED. DS-MIXSED is funded by the Agencia Estatal de Investigación (AEI) through the PCI 2024 call — projects PCI2024-155022-2 and PCI2024-155084-2 — and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) — Projektnummer 541914507.

Development was assisted by Claude Code (Anthropic) and GitHub Copilot code review.

License

MIT License