Procedure Computation Instance
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/45213/?format=api
{
"ob_id": 45213,
"uuid": "43a33d5a11c44c0ea744391c8a23ac41",
"title": "Crowd-Grid gridded climate observations methodology",
"abstract": "The gridded dataset uses observations from the Met Office's Weather Observation Website (WOW) and other sources, in addition to observations from official Met Office stations, to give a more detailed view of the temperatures people experience, including in built-up areas. Regression and inverse-distance weighted interpolation are used to generate values on a regular 1km grid from the irregularly spaced observations, taking into account factors such as latitude and longitude, altitude, coastal influence, and urban land use.\r\n\r\nThe methods used are an adaptation of the foundational methods described in Hollis et al. (2019) doi:10.1002/gdj3.78. For details on the modifications, refer to Mitchell & Fry (2024) doi:10.1002/joc.8390. An accompanying README describes the sources, processing, interpretation, and guidance for proper use of the grids (doi:10.5281/zenodo.17787357)",
"keywords": "",
"inputDescription": null,
"outputDescription": null,
"softwareReference": null,
"identifier_set": []
}