RELEASE NOTES
spatstat 1.55-1
05 April 2018
We thank Jens Astrom, Ines Moncada, Mehdi Moradi and Nicholas Read for contributions.
OVERVIEW
-
More support for tessellations.
-
Improved support for linear networks.
-
Fixed longstanding bug in leverage and influence diagnostics.
-
Minor improvements and bug fixes.
-
Version nickname: “Gamble Responsibly”
NEW FUNCTIONS
-
summary.ssf
Summary method for a spatially sampled function (class ‘ssf’). -
unstack.tess
Given a tessellation with multiple columns of marks,
take the columns one at a time, and return a list of tessellations,
each carrying only one of the original columns of marks.
SIGNIFICANT USER-VISIBLE CHANGES
-
plot.tess
This plot method can now fill each tile with a different colour.
New arguments ‘do.col’, ‘values’, ‘col’ and ‘ribargs’.
Old argument ‘col’ has been renamed ‘border’ for consistency. -
integral.linim, integral.linfun
Argument ‘domain’ can now be a tessellation. -
integral.ssf
Argument ‘domain’ can now be a tessellation. -
as.owin.default
Now accepts a structure with entries named ‘xmin,ymin,xmax,ymax’
in any order. This handles objects of class ‘bbox’ in the ‘sf’ package. -
as.owin.default
Now detects objects of class “SpatialPolygons”
and issues a more helpful error message. -
pseudoR2.ppm, pseudoR2.lppm
The null model now includes any offset terms, by default.
[Suggested by Jens Astrom.]
New argument ‘keepoffset’. -
closepairs.ppp
New argument ‘periodic’ -
fitted.ppm
New argument ‘ignore.hardcore’. -
predict.ppm
New argument ‘ignore.hardcore’. -
leverage.ppm, influence.ppm, dfbetas.ppm
Computation has been vastly accelerated for models with Geyer interaction
fitted using isotropic or translation edge corrections. -
leverage.ppm, influence.ppm, dfbetas.ppm
Virtually all models and edge corrections are now supported,
using a “brute force” algorithm. This can be slow in some cases. -
cdf.test
Monte Carlo test runs faster. -
summary.distfun, summary.funxy
Pixel resolution can now be controlled. -
persp.funxy
Improved z-axis label. -
plot.ppp
Improved placement of symbol legend when argument ‘symap’ is given. -
plot.msr
Changed the default rule for bandwidth for smoothing the density.
BUG FIXES
-
nnmark, as.im.ssf
if marks(X) was a matrix rather than a data frame,
the results were completely incorrect (and had completely wrong format).
Fixed. -
predict.mppm
If the model included random effects, and if the library ‘MASS’ was not loaded,
the predictions were on the log scale (i.e. they were logarithms of the correct values).
[Spotted by Nicholas Read.]
Fixed. -
leverage.ppm, influence.ppm, dfbetas.ppm
Calculations were slightly incorrect for models with a hard core.
Fixed. -
leverage.ppm
The mean leverage value (shown as a contour line in plot.leverage.ppm)
was slightly incorrect for Gibbs models.
Fixed. -
Ops.msr
If the input data contained an auxiliary pixel image of
the density component of the measure (attribute “smoothdensity”)
this image was not updated; it was copied to the output unchanged.
Plots of the resulting measure were incorrect, but calculations
with the measure were correct.
Fixed. -
integral.msr
If the result was a matrix, it was the transpose of the correct answer.
Fixed. -
”[.linim”
The result sometimes had the wrong class.
Fixed. -
”[.linnet”
In calculating L[W] where W is a window, the code ignored
segments of L that crossed W without having a vertex in W.
Fixed. -
nnmap
Crashed if W = NULL.
Fixed. -
density.lpp, nncross.lpp
Crashed sometimes with an obscure message about “z$which”.
[Spotted by Ines Moncada.]
Fixed. -
as.im.distfun
Crashed, for the distfun of a point pattern, if approx=FALSE.
Fixed. -
as.solist
Crashed when x was a ‘layered’ object.
Fixed. -
linnet
Crashed in some trivial cases where there were no points or lines.
Fixed.
Release notes are available in raw text format here.