query#
Perform a query on the dataset joined timeseries table.
- Parameters:
filters (
Union[str
,dict
,JoinedTimeseriesFilter
,List[Union[str
,dict
,JoinedTimeseriesFilter]]]
, optional) – The filters to apply to the query, by default Noneorder_by (
Union[str
,JoinedTimeseriesFields
,List[Union[str
,JoinedTimeseriesFields]]]
, optional) – The fields to order the query by, by default Nonegroup_by (
Union[str
,JoinedTimeseriesFields
,List[Union[str
,JoinedTimeseriesFields]]]
, optional) – The fields to group the query by, by default Noneinclude_metrics (
Union[List[MetricsBasemodel]
,str]
, optional) – The metrics to include in the query, by default None
Examples
>>> import teehr
>>> ev = teehr.Evaluation()
Define some metrics, optionally including an available bootstrapping
method. (Metric Models
).
>>> import teehr.Metrics as m
>>> import teehr.Bootstrappers as b
Define a Circular Block bootstrapper.
(Bootstrap Models
).
>>> boot = b.CircularBlock(
>>> seed=40,
>>> block_size=100,
>>> quantiles=None,
>>> reps=500
>>> )
Include the bootstrap model in the metric definition(s), along with other optional arguments.
>>> kge = m.KlingGuptaEfficiency(bootstrap=boot)
>>> primary_avg = m.Average(
>>> transform="log",
>>> output_field_name="primary_avg",
>>> input_field_names=["primary_value"]
>>> )
>>> mvtd = m.MaxValueTimeDelta(input_field_names=["secondary_value"])
>>> pmvt = m.MaxValueTime(input_field_names=["secondary_value"])
>>> include_metrics = [pmvt, mvtd, primary_avg, kge]
Get the currently available fields to use in the query.
>>> flds = eval.joined_timeseries.field_enum()
Define some filters.
>>> filters = [
>>> JoinedTimeseriesFilter(
>>> column=flds.primary_location_id,
>>> operator=ops.eq,
>>> value="gage-A"
>>> )
>>> ]
Perform the query, returning the results as a GeoPandas DataFrame.
>>> metrics_df = eval.metrics.query(
>>> include_metrics=include_metrics,
>>> group_by=[flds.primary_location_id],
>>> order_by=[flds.primary_location_id],
>>> filters=filters,
>>> ).to_geopandas()