There's two motivations for this:
- the existing one was getting massive and took ages to run, which was
a pain when developing. Smaller batches allow just a subset of test to
be run which is much faster.
- There's a random segfault on test exit which occurs on Travis. Rather
then disabling these absolutely critical tests altogether, I'm using
this as a method of bisecting exactly which alg is causing this.
K-nearest neighbour joins from the Processing toolbox!
This algorithm takes an input vector layer and creates a new
vector layer that is an with additional attributes in its attribute table
The additional attributes and their values are taken from a second
vector layer, where features are joined by finding the closest features
from each layer.
By default only the single nearest feature is joined, but optionally
the join can use the n-nearest neighboring features instead.
If a maximum distance is specified, then only features which are
closer than this distance will be matched.
Adds X and Y (or latitude/longitude) fields to a point layer.
The X/Y fields can be calculated in a different CRS to the
layer (e.g. creating latitude/longitude fields for a layer in
a project CRS).
Sponsored by SMEC/SJ
These algorithms calculate the boolean OR or AND for a set of input
rasters. For AND, if all of the input rasters have a non-zero value
for a pixel, that pixel will be set to 1 in the output raster, otherwise
it will be set to 0. For OR, if ANY of the input rasters have a non-zero
value for a pixel, that pixel will be set to 1 in the output raster,
else 0.
A reference layer parameter specifies an existing raster layer to use
as a reference when creating the output raster. The output raster will
have the same extent, CRS, and pixel dimensions as this layer
By default, a nodata pixel in ANY of the input layers will result in
a nodata pixel in the output raster. If the 'Treat nodata values
as false' option is checked, then nodata inputs will be treated the
same as a 0 input value.
Makes for much simpler raster boolean logic calculation without
the complexity of using the raster calculator (and that's not
always possible to do anyway, e.g. when ANY of the input rasters
has a nodata pixel). It's also scalable dynamic to any number of
input rasters (unlike raster calc), so is more flexible when
used within models.
causing rings errors
By default the algorithm now uses the strict OGC definition of polygon validity, where
a polygon is marked as invalid if a self-intersecting ring causes an interior hole.
If the "Ignore ring self intersections" option is checked, then this rule will be
ignored and a more lenient validity check will be performed.
Refs #16418, refs #21336
This algorithm cannot output cross-validation results and topographic
parameters simultaneously, hence two tools needed. Thanks to Pedro Venâncio
for finding this and proposing a fix.
The SAGA version of this algorithm is of limited use in QGIS, because the
volume calculated is embedded only in the SAGA terminal output. This prevents
it being saved to a file, or reused within a model as an input to a later
model step.
It's also very user-unfriendly, because users must know to manually scan
the algorithm log to find the SAGA output.
Given that the maths here is trivial, this commit ports the algorithm across
to be a native QGIS c++ algorithm. The algorithm duplicates the SAGA alg
1:1, but outputs the volume (and area) to either a HTML report, or a vector
table. Additionally, the outputs are exported as numeric outputs from the
algorithm, allowing them to be re-used within models.
(It's also considerably faster, because it avoids the forced conversion
to SAGA raster format)
Fixes#8607 (properly, even though that report is closed)
This allows optional creation of geodesic lines, which represent the
shortest distance between the points based on the ellipsoid.
When geodesic mode is used, it is possible to split the created lines
at the antimeridian (±180 degrees longitude), which can improve
rendering of the lines. Additionally, the distance between vertices
can be specified. A smaller distance results in a denser, more accurate
line.
Ports the similar algorithm from the shape tools plugin to c++, and utilises
built in QgsDistanceArea ellipsoidal calculations to split the lines.
This algorithm splits a line into multiple geodesic segments, whenever the
line crosses the antimeridian (±180 degrees longitude)
Splitting at the antimeridian helps the visual display of the lines in some
projections. The returned geometry will always be a multi-part geometry.
Whenever line segments in the input geometry cross the antimeridian,
they will be split into two segments, with the latitude of the breakpoint
being determined using a geodesic line connecting the points either side
of this segment. The current project ellipsoid setting will be used when
calculating this breakpoint.
If the input geometry contains M or Z values, these will be linearly
interpolated for the new vertices created at the antimeridian.
Supports in-place edit mode also.
These algorithms allow users to convert z or m values present in feature
geometries to attributes in the layer. By default the z/m value from the
first vertex in the feature is extracted, but optionally statistics
can be calculated on ALL the z/m values from the geometry (e.g. calculating
mean/min/max/sum/etc of z values).
Like the vector zonal stats algorithm, but this one works with
the zones defined in another raster.
Iterates over the input rasters in blocks to be nice and
memory efficient.
From the algorithm help:
"This algorithm calculates statistics for a raster layer's
values, categorized by zones defined in another raster layer.
If the reference layer parameter is set to "Input layer",
then zones are determined by sampling the zone raster layer
value at the centroid of each pixel from the source raster
layer.
If the reference layer parameter is set to "Zones layer",
then the input raster layer will be sampled at the centroid
of each pixel from the zones raster layer.
If either the source raster layer or the zone raster layer
value is NODATA for a pixel, that pixel's value will be
skipped and not including in the calculated statistics."
