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/26870/?format=api

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

{
    "ob_id": 26870,
    "uuid": "b1b352825f5548a8bf0639afe335f5ae",
    "title": "HadUK-Grid gridded climate observations methodology",
    "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography.",
    "keywords": "gridded observations",
    "inputDescription": null,
    "outputDescription": null,
    "softwareReference": null,
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12118/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12119/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12120/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12121/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12122/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12123/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12117/?format=api"
    ]
}