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/26134/?format=api

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

{
    "ob_id": 26134,
    "uuid": "deb97019774242e09e0627aee7c5edc6",
    "title": "INVICAT data assimilation framework",
    "abstract": "INVICAT is the inverse modelling framework based on the TOMCAT 3-D global chemical transport model, developed and maintained at the University of Leeds as part of the National Centre for Earth Observation (NCEO). It uses four-dimensional variational data assimilation (4D-Var) to optimise gridded distributions of sources and sinks of atmospheric trace gases from atmospheric observations. INVICAT incorporates ATOMCAT, the adjoint version of TOMCAT, to efficiently calculate sensitivities required for the optimisation. INVICAT can assimilate observations from surface monitoring networks, aircraft campaigns and satellite instruments.\r\n\r\nINVICAT has been applied to greenhouse gases, halocarbons and other trace species, including carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), ethane (C₂H₆), carbonyl sulfide (OCS), sulfur hexafluoride (SF₆) and various chlorofluorocarbons (CFCs). The modular framework can readily be extended to additional species. Fluxes can currently be optimised at horizontal resolutions of up to 1.125° × 1.125°, and posterior uncertainty estimates can optionally be calculated.",
    "keywords": "Emissions, Troposphere, Greenhouse Gases, Data Assimilation",
    "inputDescription": null,
    "outputDescription": null,
    "softwareReference": null,
    "identifier_set": [
        "https://catalogue.ceda.ac.uk/api/v2/identifiers/13959/?format=api"
    ]
}