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/8439/?format=api

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

{
    "ob_id": 8439,
    "uuid": "f46794dafe1a45beb1378e3e949bc90b",
    "title": "kriging process of TOPEX data deployed on National Oceanography Center, Southampton (NOCS) Computer",
    "abstract": "This computation involved: kriging process of TOPEX data deployed on National Oceanography Center, Southampton (NOCS) Computer.  Kriging is a group of geostatistical  techniques to interpolate the value of a random field (e.g., the elevation, z, of the landscape as a function of the geographic location) at an unobserved location from observations of its value at nearby locations. This process was used on TOPEX (TOPography EXperiment for Ocean Circulation) data resulting in monthly means on a 1x1 lat/lon grid for 12 years (1993-2004). The dataset was produced by Fangohr, S. and D.K. Woolf of SOCS.\n\nKriging is an optimal interpolation method which is used to fill the gaps which would naturally occur in any altimeter data set as a result of the altimeter's sampling pattern. Apart from offering a clever method of interpolation (in space and time) kriging also produces a measure of variability (standard deviation) of the raw data around the interpolated values that it returns. This process was used on Topex data to produce a kriged gridded altimeter data, Climatologies of gas transfer velocity and CO2 flux.\n\nSee Fangohr, S. and D.K. Woolf (2006). Application of new parameterizations of gas transfer velocity and their impact on regional and global marine CO2 budgets, provisionally accepted by Journal of Marine Systems.",
    "keywords": "",
    "inputDescription": null,
    "outputDescription": null,
    "softwareReference": null,
    "identifier_set": [
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/5387/?format=api",
        "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/5388/?format=api"
    ]
}