Tagged as feature to be included in release notes.
Because:
- The use case for this algorithm is very unclear for users - the name
does not describe what the algorithm does, and there's no help
documentation available for the algorithm either. Given this I suspect
that the algorithm is not being put into use.
- The algorithm needs enhancement to be more useful. There's no logic
in place which dictates how neighbouring features are chosen to
dissolve into the selected feature (it's effectively random - you're
just as likely to get a huge narrow polygon stretching across a map as
you are a nice compact cluster). To be more useful the algorithm would
need logic to either minimise the area of the dissolved feature, or
minimise the total number of dissolved features, or ... ?
Also modify alg to export a vector table of candidates instead of
a HTML list, since a vector table is more useful inside of
models and can be used for further analysis steps.
Check that all parameter's values pass the validity check,
even if not returned as QgsProcessingModelChildParameterSource.
In case of list, tests that it is really a QgsProcessingModelChildParameterSource list,
and create a QgsProcessingModelChildParameterSource from the list if it is not the case
(useful for custom parameters that return lists as ParameterFieldsMapping).
Improvements:
- Maintain Z/M values
- Keep original data type for group/order fields
- Group field is optional
- Added unit tests
- Don't export text files for features by default
Improvements:
- transparent reprojection to match hub/spoke CRS
- keep all attributes from matched hub/spoke features
- don't break after matching one hub point to spoke - instead
join ALL hub/spoke points with matching id values
Improvements:
- slight optimisation to feature requests - don't request attributes
which are not used
- Remove "method" param. Now the decision to group by field or
not is made only on whether a class field was selected or not
