climadjust 1.0

climadjust.client

authenticate

 | authenticate()

API authentication. Needed to connect to the API

Datasets

Observation datasets

get_observation_datasets

 | get_observation_datasets(name=None, page=None, size=None, sort_field=None, sort_direction=None)

Get a paginated list of observation datasets

Arguments:

• name: (optional) str dataset name
• page: (optional) int page number
• size: (optional) int number of results per page
• sort_field: (optional) str field to sort results by (either "type" or "name")
• sort_direction: (optional) str sort direction (either "ASC" or "DESC")

Returns:

list of observation datasets

get_observation_dataset_by_id

 | get_observation_dataset_by_id(ds_id: int)

Get an observation dataset. In case the dataset is being uploaded the uploaded state will also appear.

Arguments:

• ds_id: int id of the observation dataset

Returns:

the selected dataset information

post_observation_dataset

 | post_observation_dataset(file, name, ds_format, variables)

Uploads an observation dataset

Arguments:

• file: str path to the dataset to be uploaded
• name: str dataset name
• ds_format: str dataset format (either "NETCDF" or "VALUE_TEXT")
• variables: list[dict] list of variables. Variable format should be: {"standardName": "tas", "customName": "tas", "standardUnit": "Celsius", "customUnit": "Celsius"}

Returns:

id of the uploaded dataset

get_validation

 | get_validation(ds_id)

Gets validation warning/errors and GEOJSON info from an uploaded dataset

Arguments:

• ds_id: int id of the uploaded dataset

Returns:

dict of validation warning/errors and a GEOJSON with info from the dataset

delete_observation_dataset

 | delete_observation_dataset(id: int)

Delete existing observation dataset

Arguments:

• id: int id of the dataset

Returns:

Projection datasets

get_projection_datasets

 | get_projection_datasets(type=None, name=None, page=None, size=None, sort_field=None, sort_direction=None)

Get a paginated list of projection datasets

Arguments:

• name: (optional) str dataset name
• page: (optional) int page number
• size: (optional) int number of results per page
• sort_field: (optional) str field to sort results by (either "type" or "name")
• sort_direction: (optional) str sort direction (either "ASC" or "DESC")

Returns:

list of projection datasets

get_projection_datasets_by_id

 | get_projection_datasets_by_id(id: int)

Get a projection dataset info

Arguments:

• id: int id of the projection dataset

Returns:

dict with dataset info

climadjust.clientMethods.experiment_mixin

get_experiments

 | get_experiments(page=None, size=None, sort_field=None, sort_direction=None)

Get a paginated list of experiments

Arguments:

• page: (optional) int page number
• size: (optional) int number of results per page
• sort_field: (optional) str field to sort results by (either "id" or "name")
• sort_direction: (optional) str sort direction (either "ASC" or "DESC")

Returns:

list of experiments

get_experiments_by_id

 | get_experiments_by_id(exp_id)

Get a specific experiment. In case the experiment is being uploaded the uploaded state will also appear.

Arguments:

• exp_id: int id of the experiment

Returns:

the selected experiment information

post_experiment

 | post_experiment(name, temporalResolution, variables, scenarios, models, baconfiguration, spatialResolution, datasetProjection, datasetReference, spatialCoverage, outputFormat, validation, mask)

Arguments:

• name: str experiment name
• temporalResolution: str temporal resolution for the experiment (only "DAILY")
• variables: list list of variables to perform the bias adjustment on
• scenarios: list list of dictionaries, each dictionary contains the scenario name as well as the startDate and the endDate
• models: list list of models / members to use
• baconfiguration: list list of bias adjustment configurations for each variable (variable, method, and parameters)
• spatialResolution: str spatial resolution for the experiment ("NATIVE")
• datasetProjection: dict dictionary with the IDs of the projections datasets that will be used for the experiment
• datasetReference: dict dictionary with the IDs of the reference datasets that will be used for the experiment
• spatialCoverage: shapely.geometry.Polygon() Polygon with the spatial coverage over which to execute the experiment
• outputFormat: str output format (for example "NETCDF", "GRIB", ...)
• validation: str validation activity to perform (for example "NONE")
• mask: str a string explaining if land-mask needs to be used (for example "none")

Returns:

id of the uploaded experiment

delete_experiment

 | delete_experiment(exp_id)

Delete existing experiment

Arguments:

• id: int id of the expoeriment to be deleted

Returns: