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Plot all possible spectral density estimates

Source: R/plot_pairs.R
plot_pairs.Rd

Given a multivariate (multitype) point pattern, use ggplot2 package to visualize all (marginal and cross) spectral density estimates.

Usage

plot_pairs(est.list, ppp, xnorm = TRUE, type = "Re", shared.legend = TRUE)

Arguments

est.list

List. The kernel spectral density estimate from periodogram_smooth().

ppp

A point pattern of class "ppp".

xnorm

Logical. If TRUE (default), plot the radially-averaged spectral estimates. Otherwise, plot the raw values by heatmap.

type

If type = "Re" (default), plot the real part of the estimates. If type = "Im", plot the imaginary part.

shared.legend

Logical. Whether to share the legend across all plots.

Examples

library(spatstat)
lam <- function(x, y, m) {(x^2 + y) * ifelse(m == "A", 2, 1)}
set.seed(227823)
spp <- rmpoispp(lambda = lam, win = square(5), types = c("A","B"))
KSDE.list <- periodogram_smooth(spp, inten.formula = "~ x + y", bandwidth = 1.15)

plot_pairs(est.list = KSDE.list, ppp = spp)

plot_pairs(est.list = KSDE.list, ppp = spp, type = "Im")

plot_pairs(est.list = KSDE.list, ppp = spp, xnorm = FALSE)

plot_pairs(est.list = KSDE.list, ppp = spp, xnorm = FALSE, type = "Im")