Remove a bunch of manual "max" values for numeric parameters
where the maximum just represents a 'large number' and not a real
constraint, and let the default parameter max value handling kick in instead.
In the case of random selection the max value exceeded the possible
range for integers in spin boxes and broke the widget.
Fixes#20015
Include descriptive text with the specified parameter value
in error, and always check that sources were loaded to avoid
raw Python exceptions when they are not
- Output interpolated points when travel cost falls mid-way along
an edge
- Output all intermediate reachable points also
- Make outputting upper/lower bound points optional, and non-default.
Now by default we just output all definitely reachable points and
the interpolated points along edges which correspond to the travel cost.
This allows the output to be used to correctly generate service areas
e.g. by concave/convex polygons and all reachable nodes will be
included in the area.
- Allow algorithm to optionally output a line layer (and make the
point layer optional too, and default to just the line layer output)
containing all reachable line segments (including interpolated
segments of lines when the travel cost sits midway along that
edge). This output is more easily understandably for users.
initAlgorithm() method
This allows 2 benefits:
- algorithms can be subclassed and have subclasses add additional
parameters/outputs to the algorithm. With the previous approach
of declaring parameters/outputs in the constructor, it's not
possible to call virtual methods to add additional parameters/
outputs (since you can't call virtual methods from a constructor).
- initAlgorithm takes a variant map argument, allowing the algorithm
to dynamically adjust its declared parameters and outputs according
to this configuration map. This potentially allows model algorithms which
can be configured to have variable numbers of parameters and
outputs at run time. E.g. a "router" algorithm which directs
features to one of any number of output sinks depending on some
user configured criteria.
Algorithms and other processing code should use this method
(instead of dataobjects.getLayerFromString) to
retrieve layers from a string, as it considers the processing
context and allows resolving strings to temporarily stored layers.
This permits processing models to function correctly when
intermediate results are stored as memory layers. Subsequent
model algorithms can then access these temporary layers as inputs.
All temporary layers will be removed when the context object
is destroyed after the model algorithm is run.
Also
- simplify and add tests
- remove large memory leak (persistant store of all non-project layers)
- remove broken support for direct loading postgres/virtual layers
by string (Python version was very broken and would never match
a postgres/virtual layer)
Because
- OTF reprojection is mature and stable
- Should be no cost when not required - transforms are shortcut
when not required
- Reduces code complexity
- Canvas OTF support was being incorrectly used as a flag for
whether measurements should be made in ellipsoidal mode. Instead
the project's ellipsoid setting should be checked for this.
- Should simplify behavior for new users
