adapt3 (version 1.0.1)

summary.adaptInv: Summarize adaptInv Objects

Description

Function summary.adaptInv() summarizes adaptInv objects.

Usage

# S3 method for adaptInv
summary(object, ...)

Value

This function only produces text summarizing the numbers of variants, time steps, replicates, ESS optima, etc.

Arguments

object

An adaptInv object.

...

Other parameters currently not utilized.

Examples

library(lefko3)
data(cypdata)

sizevector <- c(0, 0, 0, 0, 1, 2.5, 4.5, 8, 17.5)
stagevector <- c("SD", "P1", "SL", "D", "XSm", "Sm", "Md", "Lg", "XLg")
repvector <- c(0, 0, 0, 0, 1, 1, 1, 1, 1)
obsvector <- c(0, 0, 0, 0, 1, 1, 1, 1, 1)
matvector <- c(0, 0, 0, 1, 1, 1, 1, 1, 1)
immvector <- c(0, 1, 1, 0, 0, 0, 0, 0, 0)
propvector <- c(1, 0, 0, 0, 0, 0, 0, 0, 0)
indataset <- c(0, 0, 0, 1, 1, 1, 1, 1, 1)
binvec <- c(0, 0, 0, 0.5, 0.5, 1, 1, 2.5, 7)

cypframe_raw <- sf_create(sizes = sizevector, stagenames = stagevector,
  repstatus = repvector, obsstatus = obsvector, matstatus = matvector,
  propstatus = propvector, immstatus = immvector, indataset = indataset,
  binhalfwidth = binvec)

cypraw_v1 <- verticalize3(data = cypdata, noyears = 6, firstyear = 2004,
  patchidcol = "patch", individcol = "plantid", blocksize = 4,
  sizeacol = "Inf2.04", sizebcol = "Inf.04", sizeccol = "Veg.04",
  repstracol = "Inf.04", repstrbcol = "Inf2.04", fecacol = "Pod.04",
  stageassign = cypframe_raw, stagesize = "sizeadded", NAas0 = TRUE,
  NRasRep = TRUE)

cypsupp2r <- supplemental(stage3 = c("SD", "P1", "SL", "D", 
    "XSm", "Sm", "SD", "P1"),
  stage2 = c("SD", "SD", "P1", "SL", "SL", "SL", "rep",
    "rep"),
  eststage3 = c(NA, NA, NA, "D", "XSm", "Sm", NA, NA),
  eststage2 = c(NA, NA, NA, "XSm", "XSm", "XSm", NA, NA),
  givenrate = c(0.10, 0.40, 0.25, NA, NA, NA, NA, NA),
  multiplier = c(NA, NA, NA, NA, NA, NA, 1000, 1000),
  type =c(1, 1, 1, 1, 1, 1, 3, 3),
  stageframe = cypframe_raw, historical = FALSE)

cypmatrix2r <- rlefko2(data = cypraw_v1, stageframe = cypframe_raw, 
  year = "all", patch = "all", stages = c("stage3", "stage2", "stage1"),
  size = c("size3added", "size2added"), supplement = cypsupp2r,
  yearcol = "year2", patchcol = "patchid", indivcol = "individ")
cypmean <- lmean(cypmatrix2r)

cyp_start <- start_input(cypmean, stage2 = c("SD", "P1", "D"),
  value = c(1000, 200, 4))

c2d_4 <- density_input(cypmean, stage3 = c("P1", "P1"), stage2= c("SD", "rep"),
  style = 2, time_delay = 1, alpha = 0.005, beta = 0.000005, type = c(2, 2))

# A simple projection allows us to find a combination of density dependence
# and running time that produces a stable quasi-equilibrium
cyp_proj <- projection3(cypmean, times = 250, start_frame = cyp_start,
  density = c2d_4, integeronly = TRUE)
plot(cyp_proj)

cyp_ta <- trait_axis(stageframe = cypframe_raw,
  stage3 = rep("P1", 15),
  stage2 = rep("rep", 15),
  multiplier = seq(from = 0.1, to = 10.0, length.out = 15),
  type = rep(2, 15))

cyp_inv <- invade3(axis = cyp_ta, mpm = cypmean, density = c2d_4, times = 350,
  starts = cyp_start, entry_time = c(0, 250), fitness_times = 30,
  var_per_run = 2)
summary(cyp_inv)