calcDIs {pdi}

Calculate Decline Indexes

Description

Calculate Phenotypic Decline Index (PDI) and Decline Acuteness Index (DAI).

Usage

calcDIs(rfModels, PDI = TRUE, DAI = TRUE, invertPDI = TRUE, invertDAI = TRUE)

Arguments

rfModels

list containing random forest models as returned by rf()

PDI

TRUE/FALSE, calculate PDI?

DAI

TRUE/FALSE, calculate DAI?

invertPDI

invert the PDI scale? TRUE/FALSE. Ignored if argument PDI is FALSE

invertDAI

invert the DAI scale? TRUE/FALSE. Ignored if argument DAI is FALSE

Examples

library(dplyr)

## Retrieve file paths for example data
files <- list.files(system.file('phenotypeDataCollectionSheets',
  package = 'pdi'),full.names = TRUE)

## Prepare data
d <- map(files,readPhenotypeSheet) %>%
  map(preparePhenotypeData) %>%
  bind_rows() %>%
  siteAdjustment() %>%
   mutate(`Live crown ratio (%)` = liveCrownRatio(`Total height (m)`,
     `Lower crown height (m)`),
     `Crown condition (%)` = crownCondition(`Missing crown (%)`,
                               `Crown transparency (%)`),
     `Crown volume (m^3)` = crownVolume(`Crown radius (m)`,
                               `Total height (m)`,
                               `Lower crown height (m)`,
                               `Crown condition (%)`),
     `Bleed prevalence (%)` = bleedPrevalence(`Active bleed length (mm)`,
                               `Active bleeds`,
                               `Black staining length (mm)`,
                               `Black staining`,
                               `Diameter at breast height (m)`),
     `Agrilus exit hole density (m^-2)` = agrilusExitHoleDensity(`Agrilus exit holes`,
                               `Diameter at breast height (m)`)
)

t <- makeAnalysisTable(d)

## Generate random forest models
m <- rf(t,cls = NULL,nreps = 10)

## Calculate decline indexese
DIs <- calcDIs(m,DAI = FALSE,invertPDI = FALSE) %>%
  bind_cols(d %>%
    select(Location,ID,Status))