Spatstat

analysing spatial point patterns

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RELEASE NOTES

spatstat 1.41-1

27 February 2015

We thank Ahmed El-Gabbas, Ute Hahn, Aruna Jammalamadaka, Ian Renner, Brian Ripley, Torben Tvedebrink and Sasha Voss for contributions.

OVERVIEW

• This is identical to the major release 1.41-0 except for
  minor bug fixes. The change log for 1.41-0 is repeated here
  with minor modifications.

• Version nickname: ‘Ides of March’

• Fixed a bug causing a segmentation fault.

• Standard errors for kernel estimates of intensity.

• Test for segregation.

• Tessellations may now have marks.

• Nested splitting.

• More support for cluster models. Reorganised parametrisation.

• Sparse data representation of linear networks.

• More support for data on a linear network.

• New datasets: ‘spiders’ and ‘dendrite’.

• Improvements and bug fixes.

• spatstat no longer uses Fortran.

• spatstat no longer depends on the package ‘scatterplot3d’.

• spatstat now imports (rather than ‘suggests’) the Matrix package.

NEW DATASETS

• dendrite
  Dendritic spines on the dendrite network of a neuron.
  A point pattern on a linear network.
  Generously contributed by Aruna Jammalamadaka.

• spiders
  Spider webs on the mortar lines of a brick wall.
  A point pattern on a linear network.
  Generously contributed by Sasha Voss.

NEW FUNCTIONS

• segregation.test
  Test of spatial segregation of types in a multitype point pattern.

• clusterfield, clusterkernel
  Compute the cluster kernel (offspring density) of a cluster process model,
  or compute the cluster field generated by superimposing copies
  of the cluster kernel at specified locations.

• clusterradius
  Compute the radius of the support of the offspring density
  of a cluster process model.

• as.linnet.psp
  Convert a line segment pattern to a linear network
  by guessing the connectivity using a distance threshold.

• iplot.linnet, iplot.lpp
  Methods for interactive plotting ‘iplot’ for objects of class lpp and linnet.

• Mathematical operations are now supported for pixel images
  on a linear network. See help(Math.linim)

• dirichlet.network, delaunay.network
  The linear networks formed by the Dirichlet tessellation
  and Delaunay triangulation.

• dirichlet.edges
  The edges of the Dirichlet tessellation.

• selfcut.psp
  Cut line segments where they cross each other.

• vertices.linnet
  Extract the vertices (nodes) of the linear network.

• vertexdegree
  Compute the degree of each vertex in a linear network.

• pixellate.linnet
  Pixellate a linear network.

• subset.hyperframe
  ‘subset’ method for class ‘hyperframe’.

• head.hyperframe, tail.hyperframe
  ‘head’ and ‘tail’ methods for hyperframes.

• clickdist
  Measures the distance between two spatial locations clicked by the user.

• solapply, anylapply
  wrappers for ‘lapply’ which return a list of class ‘solist’ or ‘anylist’.

• Kmark
  Weighted K-function.
  Identical to ‘markcorrint’ and will eventually replace it.

• marks.tess, marks<-.tess, unmark.tess:
  Extract or change the marks associated with the tiles of a tessellation.

• quantess
  Quantile tessellation: divide space into pieces which contain
  equal amounts of ‘stuff’.

• nestsplit
  Nested split

• integral
  New generic function for integrating functions,
  with methods for ‘im’, ‘msr’, ‘linim’ and ‘linfun’.

• selfcut.psp
  Cut line segments where they cross each other

• as.function.im
  Convert a pixel image to a function(x,y).

• as.linnet.linim
  Extract the linear network from a ‘linim’ object.

• pool.fv, pool.anylist
  New methods for ‘pool’

• Window.linnet
  Extract the two-dimensional window containing a linear network.

SIGNIFICANT USER-VISIBLE CHANGES

• linnet, lpp
  A linear network can now be built in ‘sparse matrix’ form
  which requires much less memory.

• chicago
  The Chicago street crimes data are now stored in ‘sparse matrix’ form.
  To convert them to non-sparse form, use as.lpp(chicago, sparse=FALSE)

• kppm
  The parametrisation of cluster models has been reorganised.
  The scale parameter is now always called ‘scale’.
  Results should be backward-compatible.

• cauchy.estK, cauchy.estpcf, matclust.estK, matclust.estpcf,
  thomas.estK, thomas.estpcf, vargamma.estK, vargamma.estpcf
  The parametrisation of cluster models has been reorganised.
  The scale parameter is now always called ‘scale’.

• plot.kppm
  Also plots the cluster kernel.

• density.ppp
  New argument ‘se’ allows calculation of standard errors as well.

• plot.pp3
  Now produces a genuine perspective view.
  New arguments control the eye position for the perspective view.

• Emark, Vmark
  These functions can now work with multiple columns of marks.

• pixellate.psp
  Can now count the number of segments that intersect each pixel,
  instead of the total length of intersection.

• linfun
  If g = linfun(f, L),
  the function f will always be called as f(x,y,seg,tp, …)
  It is no longer expected to handle the case where ‘seg’ and ‘tp’ are absent.
  The resulting function g can now be called as g(X) where X is an lpp object,
  or as g(x,y) or g(x,y,seg,tp) where x,y,seg,tp are coordinates.

• tess
  New argument ‘marks’ allows marks to be associated with tiles.

• anova.lppm
  Outdated argument ‘override’ has been removed.

• split<-.ppp
  Preserves the original ordering of the data, if possible.

• MultiHard, MultiStrauss, MultiStraussHard, HierStrauss
  Zero values in the interaction radii are now treated as NA.
  Improved handling of missing arguments.
  Printed output now respects options(‘width’)

• linearKinhom, linearKcross.inhom, linearKdot.inhom,
  linearpcfinhom, linearpcfcross.inhom, linearpcfdot.inhom
  If the intensity argument lambda, lambdaI, lambdaJ, lambdadot
  is a fitted point process model, the model is first updated
  by re-fitting it to the data, before computing the fitted intensity.

• solutionset
  The expression will be evaluated using pixel arithmetic (Math.im)
  if it cannot be evaluated using eval.im.

• to.grey
  Now uses better weights for the R, G, B channels.

• rVarGamma
  Accelerated.

• summary.mppm, print.mppm
  These functions now respect options(‘width’) and spatstat.options(‘terse’).

• print.quadrattest
  Now respects options(‘width’) and spatstat.options(‘terse’).

• print.pp3
  Now respects options(‘width’)

• print.lpp
  Now respects options(‘width’) and options(‘digits’).

• print.owin, print.im, print.summary.owin, print.summary.im
  Now respect options(‘width’).

• nnmean
  Now yields a vector, instead of a 1-column matrix,
  when there is only a single column of marks.

• pairdist.psp, crossdist.psp, nndist.psp
  The option ‘method=”Fortran”’ is no longer supported.
  The default is ‘method=”C”’.

• [.hyperframe:
  When a row of data is extracted with drop=TRUE, the result
  belongs to class ‘anylist’.

• installation of spatstat
  A Fortran compiler is no longer needed to compile spatstat from source.

• hyperframe class
  The internal structure of hyperframes has changed slightly:
  columns of objects are now stored and returned as
  lists of class ‘anylist’ or ‘solist’.
  There should be no change in behaviour.

• datasets
  Internal format of the datasets
  bdspots, bei, clmfires, demohyper, flu, gorillas, heather,
  Kovesi, murchison, osteo, pyramidal, waterstriders
  has changed slightly to use the classes ‘anylist’ and ‘solist’.
  There should be no change in behaviour.

• K3est
  New argument ‘ratio’.

• spatstat.options
  New option ‘par.points3d’ sets default arguments for plot.pp3.

• diagnose.ppm
  New arguments ‘xlab’, ‘ylab’, ‘rlab’ determine the labels
  in the 4-panel plot, and new argument ‘outer’ controls their position.
  The confusing default value for ‘compute.sd’ has been changed.

• iplot.layered
  New argument ‘visible’ controls which layers are initially visible.

• plot.lpp
  New argument ‘show.window’ controls whether to plot the containing window.

• textstring
  Any number of spatial locations (x,y) can be specified,
  with a corresponding vector of text strings.

• plot.hyperframe
  New argument ‘mar’

• plot.linnet
  New argument ‘do.plot’

• summary.hyperframe
  Improved output.

• eval.linim
  Improved scoping rules.

• pixellate.owin
  Accelerated.

• summary.linnet
  Now prints more information, and respects options(‘digits’).

• rmpoispp, rmpoint
  The vector of possible types of points will default to the ‘names’ vector
  of the argument ‘lambda’, ‘n’, or ‘f’ where appropriate.

• rpoislpp
  Argument ‘L’ can be omitted when lambda is a ‘linim’ or ‘linfun’

• simulate.ppm, simulate.kppm, simulate.lppm, simulate.slrm
  New argument ‘drop’: if nsim = 1 and drop=TRUE, the result is a point pattern
  rather than a list containing one point pattern.

• runifdisc, runifpoint, rpoint, rpoispp, rmpoint, rmpoispp,
  rMaternI, rMaternII, rSSI, rPoissonCluster, rGaussPoisson,
  rstrat, rsyst, rcell, rthin, rNeymanScott, rMatClust, rThomas,
  rCauchy, rVarGamma
  New argument ‘drop’

• spatstat.options
  New option ‘units.paren’ controls the type of parenthesis
  enclosing the explanatory text about the unit of length,
  in print.ppm, plot.fv, etc.

• closepairs, crosspairs
  New option: what=”ijd” returns only the indices i, j and the distance d

• rCauchy, rMatClust, rNeymanScott, rPoissonCluster, rThomas, rVarGamma
  Argument names have changed.

BUG FIXES

1. sumouter
   A segmentation fault could occur if any data were NA.
   Fixed.

2. simulate.kppm
   Simulation failed for log-Gaussian Cox processes (in simulate.kppm only)
   with an error message from the RandomFields package.
   Fixed.

3. ppm, predict.ppm, profilepl
   Crashed sometimes with message
   “interaction evaluator did not return a matrix”.
   Fixed.

4. lppm
   step() did not work correctly on ‘lppm’ objects.
   Fixed.

5. quadscheme
   If quadscheme() was called explicitly, with the stipulated number of tiles
   exceeding the number of dummy points given, then the quadrature weights
   were sometimes vastly inflated - total quadrature weight was
   much larger than window area. Spotted by Ian Renner.
   Fixed.

6. predict.rhohat
   Result was incorrect for data on a non-rectangular window
   (and a warning was issued about incorrect vector length).
   Fixed.

7. Math.im
   Unary operators did not work (e.g.”-x”)
   Fixed.

8. density.ppp
   Crashed when at=”points” if the dataset had exactly 1 point.
   Fixed.

9. rSSI
   Crashed if nsim > 1.
   Fixed.

10. influence.ppm, leverage.ppm, dfbetas.ppm
    Crashed or issued a warning if any quadrature points had
    conditional intensity zero under the model (negative infinite values
    of the sufficient statistic).
    Fixed.

11. clickppp, clickpoly
    Did not work correctly in the RStudio display device.
    Fixed.

12. Iest
    Ignored the arguments ‘r’ and ‘eps’.
    Fixed.

13. markvario
    Result was garbled, when X had more than one column of marks.
    Fixed.

14. rMatClust, rVarGamma, rCauchy, rNeymanScott
    Result was a list, but not a ‘solist’, when nsim > 1.
    Fixed.

15. print.mppm, summary.mppm, subfits
    Crashed if a Poisson interaction was implied but not given explicitly.
    Fixed.

16. Kest
    Crashed if ratio=TRUE and the window was a rectangle.
    Fixed.

17. anova.ppm
    Crashed sometimes with message ‘models were not all fitted
    to the same size of dataset’.
    (This occurred if there were quadrature points with
    conditional intensity equal to zero in some models but not in all models.)
    Fixed.

18. vcov.kppm
    Occasionally ran out of memory.
    Fixed.

19. as.linim.linfun
    Erroneously converted the pixel values to numeric values.
    Fixed.

20. as.owin.layered
    Ignored layers with zero area.
    Fixed.

21. plot.ppm
    Paused the plot between frames even when there was only one frame.
    Fixed.

22. plot.layered
    Did not allocate space for legends of ‘lpp’ objects.
    Fixed.

23. plot.lpp
    Ignored symbolmap arguments like ‘cex’
    and confused the arguments ‘col’ and ‘cols’.
    Fixed.

24. plot.diagppm
    Ignored add=TRUE in some cases.
    Fixed.

25. iplot.layered
    Did not handle ‘diagramobj’ objects correctly.
    Fixed.

26. plot.yardstick
    Changed arguments.

Release notes are available in raw text format here.