With the coords and datetime query parameters being mandatory.
Parameters represent the following:
coords - a WKT string defining a point with coordinates given in the EPSG:4326 CRS. This is the spatial location to be queried for data
datetime - a string defining a temporal range of the values that are to be included. It has the form start/end, as defined in OGC API -EDR. Defaults to ../.., which represents an open interval, so it gets all measurements
include_coverage_data - a boolean specifying whether the coverage-related data is to be included in the response. Defaults to true
include_observation_data - a boolean specifying whether the observation-related data is to be included in the response. Defaults to false
coverage_data_smoothing - can be specified multiple times in order to request multiple data series related to the base coverage data. The data series will be smoothed with the given strategy. Available smoothing strategies: NO_SMOOTHING, LOESS_SMOOTHING, MOVING_AVERAGE_11_YEARS. Examples:
coverage_data_smoothing=NO_SMOOTHING - returns a single series of the coverage data without any smoothing
coverage_data_smoothing=LOESS_SMOOTHING - returns a single series of the coverage data smoothed with the LOESS algorithm
coverage_data_smoothing=MOVING_AVERAGE_11_YEARS&coverage_data_smoothing=LOESS_SMOOTHING&coverage_data_smoothing=NO_SMOOTHING - returns three time series, each with the requested strategy
observation_data_smoothing - can be specified multiple times in order to request multiple data series related to the observation data. The data series will be smoothed with the given strategy. Available smoothing strategies: NO_SMOOTHING, MOVING_AVERAGE_5_YEARS.
include_coverage_uncertainty - a boolean specifying whether to also include time series for the upper and lower bounds of the uncertainty data for coverages - The processing of these has not been implemented yet and will be part of a subsequent PR (see #80)
include_coverage_related_data - a boolean specifying whether to also include time series for related coverages. The processing of these has not been implemented yet and will be part of a subsequent PR (see #81)
Here is a sample chart generated with matplotlib with data gotten from querying this API endpoint:
Also included in this PR:
an additional jupyter service in the docker compose stack used for development and a couple of jupyter notebooks that demo how to generate a chart by using the API
an additional column in the DB for a coverage configuration to mention what is the name of the NetCDF variable which is to be used - this is essential for being able to query time series data
an additional 1:many relationship between observation variables and coverage configurations in the DB. This is in order to be able to specify for a specific coverage which observarion variable shall be used when querying for data (e.g. the configuration for the TAS absolute model data is related to the TDd observation variable)
a bootstrapper CLI app used for creating a set of default configurations - this is useful for being able to replicate the configuration between dev/staging envs faster
This PR adds API endpoint for querying coverages.
NOTE
This PR introduces some breaking changes to the DB and therefore needs to be manually deployed in the staging environment.
This new endpoint looks like this:
With the
coordsanddatetimequery parameters being mandatory.Parameters represent the following:
coords- a WKT string defining a point with coordinates given in theEPSG:4326CRS. This is the spatial location to be queried for datadatetime- a string defining a temporal range of the values that are to be included. It has the formstart/end, as defined in OGC API -EDR. Defaults to../.., which represents an open interval, so it gets all measurementsinclude_coverage_data- a boolean specifying whether the coverage-related data is to be included in the response. Defaults totrueinclude_observation_data- a boolean specifying whether the observation-related data is to be included in the response. Defaults tofalsecoverage_data_smoothing- can be specified multiple times in order to request multiple data series related to the base coverage data. The data series will be smoothed with the given strategy. Available smoothing strategies:NO_SMOOTHING,LOESS_SMOOTHING,MOVING_AVERAGE_11_YEARS. Examples:coverage_data_smoothing=NO_SMOOTHING- returns a single series of the coverage data without any smoothingcoverage_data_smoothing=LOESS_SMOOTHING- returns a single series of the coverage data smoothed with the LOESS algorithmcoverage_data_smoothing=MOVING_AVERAGE_11_YEARS&coverage_data_smoothing=LOESS_SMOOTHING&coverage_data_smoothing=NO_SMOOTHING- returns three time series, each with the requested strategyobservation_data_smoothing- can be specified multiple times in order to request multiple data series related to the observation data. The data series will be smoothed with the given strategy. Available smoothing strategies:NO_SMOOTHING,MOVING_AVERAGE_5_YEARS.include_coverage_uncertainty- a boolean specifying whether to also include time series for the upper and lower bounds of the uncertainty data for coverages - The processing of these has not been implemented yet and will be part of a subsequent PR (see #80)include_coverage_related_data- a boolean specifying whether to also include time series for related coverages. The processing of these has not been implemented yet and will be part of a subsequent PR (see #81)Here is a sample chart generated with matplotlib with data gotten from querying this API endpoint:
Also included in this PR:
jupyterservice in the docker compose stack used for development and a couple of jupyter notebooks that demo how to generate a chart by using the APITAS absolutemodel data is related to theTDdobservation variable)fixes #75
fixes #77
fixes #79
related to #68