Sea-Bird Scientific Community Toolkit#

The toolkit is a collection of:

  • Python code to help users process data collected with SBS instruments (see the repository src/seabirdscientific folder).

  • Example SBS instrument data (see the repository documentation/example_data folder).

  • A Jupyter notebook that demonstrates toolkit processing options that can be applied to data collected with SBE 37 and SBE 19plus V2 CTDs (see the repository documentation folder).

Installation#

Windows:

py -m pip install seabirdscientific

Mac/Linux:

python3 -m pip install seabirdscientific

Example Usage:

import seabirdscientific
from seabirdscientific import conversion
import seabirdscintific.processing as p

Contents#

Guides#

Migration Guide: How to address breaking changes when migrating from v2.7.3 -> v3.0.0

Theory#

CTD Processing: In depth descriptions of some of the algorithms used in processing.py.

Source#

cal_coefficients.py: Classes for storing calibration coefficients used with data conversion functions.

contour.py: A class and helper functions for storing data used with TS plots.

conversion.py: A collection of functions for converting raw instrument data to SI units. Also includes some functions for converting between SI units, for exampel from depth from pressure.

eos80_conversion.py: Legacy functions for legacy data.

instrument_data.py: Classes and functions for parsing instrument data files into python data types.

interpret_sbs_variable.py: A single, long function that converts various Sea-Bird unit representations into a more limited set of strings.

processing.py: Generally contains functions that modify data that has already been converted or derived from raw data. Also contains a couple functions for deriving buoyancy.

utils.py: Helper functions for example notebooks and unit tests.

visualization.py: Functions for generating Plotly charts from Sea-Bird data.