API reference

This page provides an auto-generated summary of TEEHR’s API. For more details and examples, refer to the User Guide part of the documentation.

The Evaluation Class

The top-level class for interacting with and exploring a TEEHR Evaluation.

Evaluation

The Evaluation class.

Creating and Managing an Evaluation

Methods for creating, cloning, and configuring an Evaluation.

Evaluation.clone_template	Create a study from the standard template.
Evaluation.list_s3_evaluations	List the evaluations available on S3.
Evaluation.clone_from_s3	Fetch the study data from S3.
Evaluation.clean_cache	Clean temporary files.
Evaluation.enable_logging	Enable logging.

The Evaluation Dataset

Classes for creating, describing, and querying the Evaluation dataset tables.

BaseTable	Base table class.
UnitTable	Access methods to units table.
VariableTable	Access methods to variables table.
AttributeTable	Access methods to attributes table.
ConfigurationTable	Access methods to configurations table.
LocationTable	Access methods to locations table.
LocationAttributeTable	Access methods to location attributes table.
LocationCrosswalkTable	Access methods to location crosswalks table.
PrimaryTimeseriesTable	Access methods to primary timeseries table.
SecondaryTimeseriesTable	Access methods to secondary timeseries table.
JoinedTimeseriesTable	Access methods to joined timeseries table.

Fetching NWM and USGS data

Methods for fetching NWM and USGS data from external sources.

Fetch.usgs_streamflow	Fetch USGS gage data and load into the TEEHR dataset.
Fetch.nwm_retrospective_points	Fetch NWM retrospective point data and load into the TEEHR dataset.
Fetch.nwm_operational_points	Fetch operational NWM point data and load into the TEEHR dataset.
Fetch.nwm_retrospective_grids	Fetch NWM retrospective gridded data, calculate zonal statistics (currently only mean is available) of selected variable for given zones, and load into the TEEHR dataset.
Fetch.nwm_operational_grids	Fetch NWM operational gridded data, calculate zonal statistics (currently only mean is available) of selected variable for given zones, and load into the TEEHR dataset.

Metric Functions

Functions for calculating metrics.

teehr.metrics.deterministic_funcs	Contains UDFs for deterministic metric calculations in Spark queries.
teehr.metrics.signature_funcs	Signature functions.
teehr.metrics.probabilistic_funcs	Functions for probabilistic metric calculations in Spark queries.

Metric and Bootstrap Models

Classes for defining and customizing metrics and bootstrap models.

DeterministicMetrics	Define and customize determinisitic metrics.
SignatureMetrics	Define and customize signature metrics.
ProbabilisticMetrics	Define and customize probalistic metrics.
Bootstrappers	Container class for bootstrap sampling classes.

Calculated Field Models

Classes for defining and customizing user-defined field models.

RowLevelCalculatedFields	Row level Calculated Fields.
TimeseriesAwareCalculatedFields	Timeseries aware calculated fields.

Visualization

Methods for visualizing Evaluation data.

TEEHRDataFrameAccessor

Extends pandas DataFrame objects with visualization methods.