Rationale:
- the correct use for this option is unclear, and users are
mistakenly using it as a 'tolerance' option
- it's very likely to generate invalid geometries as a result
of the snapping, causing unreliable results
Given these substantial issues, it's safer to remove this
option and require that users who need the snap to grid
precision change explicitly do this via an extra model
step before running the algorithm.
Changes:
- handle different CRS transparently
- don't build a spatial index on the selection layer. Instead
only use feature requests to fetch features which are within
the desired bounds, and rely on the presence of an appropriate
spatial index at the provider's backend. Otherwise, we force
every user of this algorithm to have a full iteration of the
source table, regardless of how large the table is. That means
that trying to select a set of addresses which fall within
a specific locality from a table which contains the addresses
for a whole state will FORCE every address in the state to
be initially read before any calculation begins. With this
change only those features within the bounding box of the
selected localities will ever be fetched from the provider,
resulting in huge speed improvements for the algorithm.
- use prepared geometries for the spatial relation tests.
This dramatically speeds up the algorithm in the case
where the intersection layer features cover multiple
features from the 'selection' layer.
- Add a 'select within current selection' mode
- Optimise feature requests for efficiency (especially
with respect to the 'disjoint' selection mode)
- allow non spatial inputs
- allow calculation of stats on any field type, with specific
string and datetime stats calculated when field type matches
- output a full set of stats for numeric fields (including median
, quartiles, etc)
- also calculate stats for 'null' category
