spatstat.linnet-internal: Internal spatstat.linnet functions

In spatstat.linnet: Linear Networks Functionality of the 'spatstat' Family

Internal spatstat.linnet functions

Description

Internal spatstat.linnet functions.

Usage

ApplyConnected(X, Engine, r, ..., rule, auxdata)
DoCountEnds(X, D, toler)
DoCountCrossEnds(X, I, J, DIJ, toler)
FDMKERNEL(lppobj, dtt, dtx, M, nsave, weights,
          stepnames, setuponly, verbose)
## S3 method for class 'linfun'
as.linfun(X, ...)
## S3 method for class 'lintess'
as.owin(W, ...)
## S3 method for class 'lppm'
getglmdata(object, ...)
## S3 method for class 'lppm'
getglmfit(object, ...)
## S3 method for class 'lppm'
getglmsubset(object, ...)
## S3 method for class 'lppm'
hasglmfit(object)
default.linnet.tolerance(L)
evaluateNetCovariate(covariate, locations, ...)
evaluateNetCovariateAlongNetwork(covariate, locations, ..., types)
evaluateNetCovariateAtPoints(covariate, locations, ..., allow.column)
exactlppm(X, baseline, ..., subset)
## S3 method for class 'exactlppm'
is.poisson(x)
## S3 method for class 'exactlppm'
is.stationary(x)
makeLinnetTolerance(toler)
## S3 method for class 'exactlppm'
predict(object, locations,...)
## S3 method for class 'exactlppm'
print(x, ...)
## S3 method for class 'lintess'
print(x, ...)
## S3 method for class 'summary.linim'
print(x, ...)
## S3 method for class 'summary.linnet'
print(x, ...)
## S3 method for class 'summary.lintess'
print(x, ...)
## S3 method for class 'lintess'
summary(object, ...)
## S3 method for class 'exactlppm'
response(object)
## S3 method for class 'lintess'
nobjects(x)
## S3 method for class 'lintess'
Window(X, ...)
## S3 replacement method for class 'linnet'
Window(X, ..., check=TRUE) <- value
## S3 replacement method for class 'lpp'
Window(X, ..., check=TRUE) <- value
densitypointsLPP(x, sigma, ...,
                 weights, nsigma, leaveoneout, fast,
                 fastmethod, floored,
                 dx, dt, iterMax, verbose, debug)
flatdensityfunlpp(X, ..., disconnect, weights, what)
flatdensityatpointslpp(X, ..., leaveoneout, disconnect, weights, what)
local2lpp(L, seg, tp, X, df.only)
looHeatLPP(U0, Amatrix, npts, niter, nsave,
           lixelweight, lixelmap, verbose) 
looVoronoiLPP(X)
validate.lpp.coords(X, fatal, context)
## S3 method for class 'lppm'
as.ppm(object)
pointsAlongNetwork(L, delta)
lineardiscEngine(L, x, r, want)
linearEuclidEngine(X, fun, ..., r, reweight, denom,
                   samplesize, showworking, correction)
linearKengine(X, ..., r, reweight, denom, samplesize,
              correction, ratio, showworking)
linearKmulti(X, I, J, r, ..., correction)
linearKmulti.inhom(X, I, J, lambdaI, lambdaJ, r, ..., correction,
             normalise, sigma)
linearpcfengine(X, ..., r, reweight, denom, samplesize, correction, ratio)
linearpcfmulti(X, I, J, r, ..., correction)
linearpcfmulti.inhom(X, I, J, lambdaI, lambdaJ, r, ...,
                     correction, normalise,
                     sigma, adjust.sigma, bw, adjust.bw)
linearKmultiEngine(X, I, J, ...,
                   r, reweight, denom, samplesize, correction, showworking)
linearPCFmultiEngine(X, I, J, ...,
                   r, reweight, denom, samplesize, correction, showworking)
resampleNetworkDataFrame(df, template)
## S3 method for class 'lpp'
resolve.lambda(X, lambda, subset, ...,
       update, leaveoneout, everywhere, loo.given, sigma, lambdaname)
sortalongsegment(df)
## S3 method for class 'lppm'
spatialCovariateEvidence(model, covariate, ..., lambdatype, 
          eps, dimyx, xy, rule.eps,
          delta, nd, interpolate, jitter, jitterfactor,
          modelname, covname, dataname, subset, clip.predict)
## S3 method for class 'exactlppm'
spatialCovariateEvidence(model, covariate, ...,
          lambdatype, interpolate, jitter, jitterfactor,
          modelname, covname, dataname, subset, clip.predict)
vnnFind(seg, tp, ns, nv, from, to, seglen, huge, tol, kmax)
ldtEngine(nv, ns, from, to, seglen, huge,
          coUXord, vnndist, vnnwhich, vnnlab)
resolve.heat.steps(sigma, ..., dx, dt,
                   niter, iterMax, nsave,
                   seglengths, maxdegree, AMbound, L,
                   finespacing, fineNsplit, fineNlixels,
                   W, eps, dimyx, xy, 
                   allow.adjust, warn.adjust,
                   verbose, stepnames)
rmaxEuclidean(L, verbose, show)
qkdeEngine(x, sigma, ..., at, what,
           leaveoneout, diggle, raw, edge2D, edge,
           weights, varcov, positive, shortcut,
           precomputed, savecomputed)
## S3 method for class 'lppm'
updateData(model, X, ...)
Math(x, ...)
Ops(e1, e2)
Complex(z)
Summary(..., na.rm = FALSE)




LinimOp(e1, e2, op)
LinimListOp(e1, e2, op)
traceTessLinnet(A, L)

Details

These internal spatstat.linnet functions should not be called directly by the user. Their names and capabilities may change without warning from one version of spatstat.linnet to the next.

Value

The return values of these functions are not documented, and may change without warning.

spatstat.linnet documentation built on Sept. 20, 2024, 5:06 p.m.