Procedure Computation Instance – Django REST framework

Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations.

### Available end points:

- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `uuid`
- `title`
- `keywords`
- `abstract`

### How to use filters:

These filters can be used like django query filters using __ for related model relationships.

- `/computations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/computations/?title__startswith!=DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE`
- `/computations/?abstract__contains=HadCM3 model`

GET /api/v2/computations/44352/?format=api

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 44352,
    "uuid": "3f9fbc185dcc4c5ca76c41fb76ceb5a1",
    "title": "Computation for ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Retrieval of drift-aware sea-ice thickness from radar altimetry and passive microwave drift data",
    "abstract": "The method used to extract sea-ice thickness from radar altimetry data is based on the pioneering work of Peacock and Laxon, 2004; Laxon et al., 2003 for the ERS-2 mission. The method involves separating the radar echoes returning from the ice floes from those returning from the sea surface in the leads between the floes. This step of a surface-type classification is crucial and allows for a separate determination of the ice floe and sea-surface heights. The freeboard that is the elevation of the ice upper side (or ice/snow interface) above the sea level can then be computed by deducting the interpolated sea-surface height at the floe location from the height of the floe. Using the freeboard and additional snow load information, sea-ice thickness is then computed along the satellite track. To account for sea-ice motion, the along-track thickness estimates are combined with drift data from passive microwave sensors (Lavergne & Down, 2023). Individual measurement parcels are advected daily over a one-month period, resulting in drift-aware sea-ice thickness maps that reflect the evolving distribution of the ice.",
    "keywords": "",
    "inputDescription": null,
    "outputDescription": null,
    "softwareReference": null,
    "identifier_set": []
}