Like the main Join Attributes by Location algorithm, this algorithm
takes two layers and combines the attributes based on a spatial
criteria.
However this algorithm calculates summaries for the attributes for
all matching features, e.g. calculating the mean/min/max/etc.
The list of fields to summaries, and the summaries to
calculate for those, can be selected.
Improvements:
- transparently handle different source/join CRS
- added option to create output feature for EVERY joined
feature (i.e. 1 to many type join)
- added option to select joined fields to take
- optimised performance of algorithm
The previous option to create a summary of joined features has been
removed, and will be moved to a separate 'Join by location (summary)'
algorithm.
This algorithm is no longer required - it's been replaced by
the 'Promote to multipart' and 'Collect geometries" algorithms.
Tagged as feature to remember to include in release notes
This is basically the equivalent of the dissolve algorithm, but
instead of a dissolving overlapping geometries the geometries
are instead just collected together into a multipart geometry.
It's designed to slot between the 'promote to multipart' algorithm
(which performs no collection of geometries - it just converts
singleparts to multiparts with 1 part) and the more complex
all-encompassing 'aggregate' algorithm.
This algorithm is basically the equivalent of the ST_Multi(...)
command - it forces a feature's geometry to become multipart,
regardless of the input geometry type.
If input geometries are singlepart, they will output as
multipart with just 1 part. If they are already multipart,
they will be output unchanged.
Now that the extra features of the "polygon from vector layer extent"
algorithm are covered by the new "Minimum bounding geometry" algorithm,
we can replace the previous two "polygon from vector extent" and
"polygon from raster extent" algorithms by a single "polygon
from layer extent" algorithm.
feature based algorithms
Instead of algorithms which handle both whole layers/groups
of features/individual features, we leave the whole layer
and group of features handling to the "Minimum bounding
geometry" algorithm.
The feature-by-feature algorithms are now native c++
algorithms.
This affects:
- bounding boxes
- convex hulls
- minimum enclosing circle
- minimum oriented rectangles
This algorithm creates geometries which enclose the features
from an input layer.
Numerous enclosing geometry types are supported, including
bounding boxes (envelopes), oriented rectangles, circles and
convex hulls.
Optionally, the features can be grouped by a field. If set,
this causes the output layer to contain one feature per grouped
value with a minimal geometry covering just the features with
matching values.
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.
processing tests
Some algorithms will return results in different orders, e.g.
due to the use of dicts or other methods which do not guarantee
a fixed return order.
Using a primary key to do the feature match allows us to flexibly
handle these situations and provide tests for these algorithms.
Differences in gdal libraries mean the hash value may differ between
platforms. Allow multiple acceptable hashes to be listed for
expected test results
