spatstat-internal {spatstat} | R Documentation |
Internal spatstat functions.
affinexy(X, mat = diag(c(1, 1)), vec = c(0, 0)) apply23sum(x) area.xypolygon(polly) AsymmHausdorff.psp(X, Y, method="Fortran") as.breakpts(...) as.fv(x) as.polygonal(W) beachcolours(heightrange, sealevel, monochrome, ncolours) bind.fv(x, y, labl, desc, preferred) bdrylength.xypolygon(polly) breakpts(val, maxi, even = FALSE, npos = NULL, step = NULL) breakpts.from.r(r) cartesian(pp, markset, fac = TRUE) cellmiddles(W, nx, ny, npix, gi) checkfields(X,L) check.hist.lengths(hist,breaks) check.named.vector(x, nam) clip.psp(x, window, check=TRUE) cliprect.psp(x, window) clippoly.psp(s, window) closepairs(X,rmax) crosspairs(X,Y,rmax) cobble.xy(x, y, f, fatal) commasep(x) countingweights(id, areas, check = TRUE) damaged.ppm(object) default.expand(object, m, epsilon) default.clipwindow(object, epsilon) default.n.tiling(X, nd, ntile, npix, verbose) default.ntile(X) densityhack(x, bw, adjust, kernel, window, width, give.Rkern, n, from, to, cut, na.rm, weights) diagnose.ppm.engine(object, ..., type="eem", typename, opt, sigma=NULL, rbord = reach(object), compute.sd=TRUE, compute.cts=TRUE, rv=NULL) discretise(x, xrange, nx) distpl(p, l) distppl(p, l) distppll(p, l, mintype=0, method="Fortran", listit=FALSE) divisors(n) do.call.matched(fname, arglist, funargs, extrargs) edge.Ripley(X, r, W, method) edge.Trans(X, Y, W, exact, paired, trim) ensure2vector(x) equals.quad(Q) eratosthenes(nmax) erode.mask(w,r) even.breaks.owin(w) exactdt(X, ...) exactPdt(w) fasp(fns, titles, formulae, which, dataname, title) FormatFaspFormulae(f, argname) fv(x, argu, ylab, valu, fmla, alim, labl, desc) greatest.common.divisor(n,m) getfields(X, L, fatal = TRUE) getglmfit(object) gridindex(x, y, xrange, yrange, nx, ny) handle.r.b.args(r = NULL, breaks = NULL, window, eps = NULL, rmaxdefault) handle.rshift.args(W, ..., radius, width, height, edge, clip, edgedefault) ho.engine(model, ..., nsim, nrmh, start, control, verb) identical.formulae(x,y) inside.xypolygon(pts, polly, test01 = TRUE, method="Fortran") intX.owin(w) intX.xypolygon(polly) intY.owin(w) intY.xypolygon(polly) is.cadlag(s) is.data(Q) is.fv(x) is.marked(X, ...) is.marked.default(...) is.marked.ppp(X, na.action="warn", ...) is.poisson.ppm(x) is.prime(n) is.stationary.ppm(x) km.rs(o, cc, d, breaks) Kborder.engine(X, rmax, nr, correction, weights) Kount(dIJ, bI, b, breaks) Kwtsum(dIJ, bI, wIJ, b, w, breaks) Kmulti.inhom(X, I, J, lambdaI, lambdaJ, ..., r=NULL, breaks=NULL, correction = c("border", "isotropic", "Ripley", "translate") , lambdaIJ=NULL, Iname = "points satisfying condition I", Jname = "points satisfying condition J") killinteraction(model) least.common.multiple(n,m) ## S3 method for class 'im': levels(x) <- value lookup.im(Z, x, y, naok) make.even.breaks(bmax, npos, bstep) markspace.integral(X) marks.quad(Q) matcolall(x) matcolany(x) matcolsum(x) matrixsample(mat, newdim, phase) matrowall(x) matrowany(x) matrowsum(x) maxflow(costm) meanX.owin(w) meanY.owin(w) mkcor(d, ff, wt, Ef, rvals, method="smrep", ..., nwtsteps=500) mpl.engine(Q, trend, interaction, ..., covariates, correction, rbord, use.gam, forcefit, callstring, precomputed, savecomputed) mpl.get.covariates(covariates, locations, type) mpl.prepare(Q, X, P, trend, interaction, covariates, want.trend, want.inter, correction, rbord, Pname, callstring, ..., precomputed, savecomputed) MultiPair.checkmatrix(mat, n, name) nearest.pixel(x, y, im) no.trend.ppm(x) n.quad(Q) overlap.owin(A,B) overlap.trapezium(xa, ya, xb, yb, verb = FALSE) overlap.xypolygon(P, Q) owinpolycheck(W, verbose=TRUE) param.quad(Q) pixellate(x, ..., weights) ploterodewin(W1, W2, col.edge, col.inside, ...) ploterodeimage(W, Z, ..., Wcol, rangeZ, colsZ) plot.diagppm(x, ..., which, plot.neg="image", plot.smooth="imagecontour", plot.sd=TRUE, spacing=0.1, srange=NULL, monochrome=FALSE, main=NULL) plot.minconfit(x, ...) plot.pppmatching(x, addmatch = NULL, main = NULL, ...) plot.profilepl(x, ..., add=FALSE, main=NULL, tag=TRUE, coeff=NULL, xvariable=NULL) plot.qqppm(x, ..., limits=TRUE, monochrome=FALSE, limcol=if(monochrome) "black" else "red") plot.quadratcount(x, ..., add, entries, dx, dy) plot.quadrattest(x, ...) polynom(x, ...) pppdist.prohorov(X, Y, precision = 7) pppmatching(X, Y, am, ty = "generic") primefactors(n, prmax) print.diagppm(x, ...) print.envelope(x, ...) print.fasp(x, ...) print.fv(x, ...) print.interact(x, ...) print.isf(x, ...) print.minconfit(x, ...) print.plotppm(x, ...) print.pppmatching(x, ...) print.profilepl(x, ...) print.qqppm(x, ...) print.rmhcontrol(x, ...) print.rmhmodel(x, ...) print.rmhstart(x, ...) print.rmhseed(x, ...) print.summary.owin(x, ...) print.summary.ppp(x, ..., dp=3) print.summary.psp(x, ...) quad(data, dummy, w, param) quadrat.breaks(xr, yr, nx = 5, ny = nx, xbreaks = NULL, ybreaks = NULL) quadrat.count.engine(x, y, xbreaks, ybreaks, weights) quadscheme.replicated(data, dummy, method = "grid", ...) quadscheme.spatial(data, dummy, method = "grid", ...) rasterx.im(x) rastery.im(x) rebound.ppp(x, ...) rebound.psp(x, ...) rebound.owin(w, rect) resid4plot(RES, plot.neg="image", plot.smooth="imagecontour", spacing=0.1, srange=NULL,monochrome=FALSE, main=NULL, ...) resid1plot(RES, opt, plot.neg="image", plot.smooth="imagecontour", srange=NULL, monochrome=FALSE, main=NULL, ...) resid1panel(observedX, observedV, theoreticalX, theoreticalV, theoreticalSD, xlab,ylab, ...) resolve.defaults(...) reverse.xypolygon(p) rmax.rule(fun, W, lambda) rotxy(X, angle = pi/2) rmhResolveTypes(model, start, control) rmhcontrol.rmhcontrol(control, ...) rmhcontrol.list(control, ...) rmhEngine(InfoList, ..., verbose, reseed, kitchensink, preponly) rmhmodel.rmhmodel(model, ...) rmhmodel.list(model, ...) rmhseed(iseed) rmhstart.rmhstart(start, ...) rmhstart.list(start, ...) rmhmodel.ppm(model, win, ..., verbose, project, control) rmpoint.I.allim(n, f, types) rpoint.multi(n, f, fmax=NULL, marks = NULL, win = unit.square(), giveup = 1000, verbose = FALSE) runifdisc(n, r = 1, x = 0, y = 0) runifpoispp(lambda, win = owin(c(0, 1), c(0, 1))) runifrect(n, win = owin(c(0, 1), c(0, 1))) second.moment.calc(x, sigma, edge=TRUE, what="Kmeasure", debug=FALSE, ...) shiftxy(X, vec = c(0, 0)) spatstat.rawdata.location(...) sp.foundclass(cname, inlist, formalname, argsgiven) sp.foundclasses(cnames, inlist, formalname, argsgiven) stratrand(window, nx, ny, k = 1) suffstat.generic(model, X, callstring) suffstat.poisson(model, X, callstring) summary.envelope(object,...) summary.pppmatching(object, ...) sympoly(x, y, n) termsinformula(x) tilecentroids(W, nx, ny) trim.rectangle(W, xmargin, ymargin=xmargin) update.interact(object, ...) validate.mask(w, fatal=TRUE) validate.quad(Q, fatal, repair, announce) variablesinformula(x) verifyclass(X, C, N = deparse(substitute(X)), fatal = TRUE) verify.xypolygon(p, fatal=TRUE) whist(x,breaks,weights, trim, right) w.quad(Q) x.quad(Q) y.quad(Q) xypolyselfint(p, eps, proper) xypolygon2psp(p, w)
These are usually not to be called by the user.