version 0.0.5

DESCRIPTION

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+Package: LandComp
+Title: Analysing Landscape Composition and Structure at Multiple Scales
+Version: 0.0.5
+Authors@R: c(
+    person(given = c("Krisztina", "Dóra"), family = "Konrád", email = "konrad.krisztina@ecolres.hu", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-4414-8766")),
+    person(given = "Ákos", family = "Bede-Fazekas", role = c("aut", "ths", "cph"), comment = c(ORCID = "0000-0002-2905-338X")),
+    person(given = "Sándor", family = "Bartha", role = c("cph"), comment = c(ORCID = "0000-0001-6331-7521")),
+    person(given = "Imelda", family = "Somodi", role = c("ccp", "ths", "cph"), comment = c(ORCID = "0000-0002-6207-3796")))
+Description: Changes of landscape diversity and structure can be detected
+    soon if relying on landscape class combinations and analysing patterns
+    at multiple scales. 'LandComp' provides such an opportunity, based on
+    Juhász-Nagy's functions (Juhász-Nagy P, Podani J 1983
+    <doi:10.1007/BF00129432>). Functions can handle multilayered data.
+    Requirements of the input: binary data contained by a regular square
+    or hexagonal grid, and the grid should have projected coordinates.
+License: MIT + file LICENSE
+Suggests: knitr, rmarkdown, testthat
+Encoding: UTF-8
+Language: En
+RoxygenNote: 7.3.0
+Imports: future, future.apply, sf
+Depends: R (>= 2.10)
+LazyData: true
+VignetteBuilder: knitr
+URL: https://github.com/ladylavender/LandComp,
+        https://ladylavender.github.io/LandComp/
+BugReports: https://github.com/ladylavender/LandComp/issues
+NeedsCompilation: no
+Packaged: 2024-02-05 19:05:20 UTC; Kriszti
+Author: Krisztina Dóra Konrád [aut, cre, cph]
+    (<https://orcid.org/0000-0002-4414-8766>),
+  Ákos Bede-Fazekas [aut, ths, cph]
+    (<https://orcid.org/0000-0002-2905-338X>),
+  Sándor Bartha [cph] (<https://orcid.org/0000-0001-6331-7521>),
+  Imelda Somodi [ccp, ths, cph] (<https://orcid.org/0000-0002-6207-3796>)
+Maintainer: Krisztina Dóra Konrád <konrad.krisztina@ecolres.hu>
+Repository: CRAN
+Date/Publication: 2024-02-06 17:30:08 UTC

LICENSE

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+YEAR: 2024
+COPYRIGHT HOLDER: LandComp authors

MD5

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+c255bed33243656a6e1301e58d62f75f *DESCRIPTION
+bc0d0acbf6942744201d2de53dd34143 *LICENSE
+2a52ee3282aa991369d7ea320622764e *NAMESPACE
+61bd55ad94656d9625684e9e90420368 *NEWS.md
+4ff2514670eede75569ceb60f02d6be1 *R/LandComp.R
+ea7cde865e2f3703be2e810b497fb3be *R/calculate_SpatialUnitSize.R
+943adabcf4851d1ba2b6b435f4c030e9 *R/data.R
+6bb4e7e14cdd2914a81d67dc4e021976 *README.md
+d760edd7966e017bd7433e453cd57c61 *build/vignette.rds
+bd7456fd574f11b720db29192ab502f4 *data/hexagonal_data.rda
+20fb8bb07599682e56f6f199aa65b075 *data/square_data.rda
+35337293cab43b450fea64d1c72a7cf5 *inst/CITATION
+990e6ebfadbef9bb84af23f950ba9eb2 *inst/doc/LandComp.R
+3587a5886b64768d470eab08dc543162 *inst/doc/LandComp.Rmd
+1396685d9e34c23d01691cd98a09fda8 *inst/doc/LandComp.html
+fed3ad40d9e49b7360f33ee0dd35ce35 *man/LandComp.Rd
+ba12b31f9137f12344081b03fcbb8916 *man/calculate_SpatialUnitSize.Rd
+ae527504750a5b012d271f88283fd5d2 *man/figures/README-hexagonal_data-1.png
+39732d475b78f2c588af1804e8736449 *man/figures/README-square_data-1.png
+81df5e3d2836fe9ec7bcdd4da78cc6e6 *man/figures/logo.png
+24d9f0b0826e151545c624599ef52c72 *man/figures/spatial_units_hexagon.png
+b1c0383134f2ba26d50bfa247e03ec2c *man/figures/spatial_units_square.png
+96bcb623f263d449ecea5d586745cc19 *man/hexagonal_data.Rd
+2c882e0f5c2abaa29131c5b902d03c5c *man/square_data.Rd
+bb0b5bdd9cde2b15cfc0ca9eac1b742d *tests/testthat.R
+806bb3bc5d5c20127e4aeeeac0bed374 *tests/testthat/test-LandComp.R
+76840dd75eed1afcd43058e6da76e167 *tests/testthat/test-calculate_SpatialUnitSize.R
+3587a5886b64768d470eab08dc543162 *vignettes/LandComp.Rmd

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(LandComp)
+export(calculate_SpatialUnitSize)

NEWS.md

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+# LandComp 0.0.5
+
+* Updated 'Description' file.
+* The package became compatible with CRAN.
+
+# LandComp 0.0.4
+
+# LandComp 0.0.3
+
+* Updated 'Description' file.
+
+# LandComp 0.0.2
+
+# LandComp 0.0.1
+
+* Initial CRAN submission.

R/calculate_SpatialUnitSize.R

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+#'Number of grid cells covered by enlarged spatial units
+#'
+#'Calculate the number of grid cells covered by the radially enlarged spatial
+#'units.
+#'
+#'@param aggregation_step A numeric vector of length one containing a
+#'  non-negative number. This number expresses the size of the spatial units for
+#'  which calculation of compositional diversity and associatum is required. The
+#'  size is measured by the number of rows of grid cells around the central grid
+#'  cell, where 0 means the original cell without enlargement. Fraction number
+#'  can be also set as input. In this case, the following step's spatial unit
+#'  minus grid cells touching the vertices are used as spatial base units. Note,
+#'  in the case of hexagonal grid, steps falling in the interval ]0,1[ cannot be
+#'  evaluated. Negative, non-finite and missing values are ignored with warning.
+#'@param square A logical vector of length one. Should be `TRUE` if square grid,
+#'  `FALSE`, if is hexagonal grid is used as the basis of calculation.
+#'
+#'@return A numeric vector of length one.
+#'@export
+#'
+#'@examples
+#' calculate_SpatialUnitSize(aggregation_step = 0, square = TRUE)
+#'
+#' foo = c()
+#' for(i in c(0, 0.5, 1, 1.5, 2, 3))
+#'   foo = c(foo, calculate_SpatialUnitSize(aggregation_step = i, square = TRUE))
+#' foo
+#'
+#' vapply(c(0, 1, 1.5, 2, 3), FUN = function(i){
+#'   calculate_SpatialUnitSize(aggregation_step = i, square = FALSE)},
+#'   FUN.VALUE = numeric(length = 1))
+#'
+calculate_SpatialUnitSize = function(aggregation_step, square = FALSE){
+  # Checking parameters
+  if(missing(aggregation_step)) stop("Parameter 'aggregation_step' should be set.")
+  if(any(is.na(aggregation_step))){
+    aggregation_step = aggregation_step[!is.na(aggregation_step)]
+    warning("NA values provided to parameter 'aggregation_step' are ignored.")
+  }
+  if(any(!is.finite(aggregation_step))){
+    aggregation_step = aggregation_step[is.finite(aggregation_step)]
+    warning("Infinite values provided to parameter 'aggregation_step' are ignored.")
+  }
+  if(length(aggregation_step)>1){
+    warning("Parameter 'aggregation_step' has more elements (", as.character(length(aggregation_step)), ") then expected (1). Only the first element is used.")
+    aggregation_step <- aggregation_step[1]
+  } else if(length(aggregation_step)<1) stop("Parameter 'aggregation_step' should be of length one.")
+  if(aggregation_step < 0) stop("Parameter 'aggregation_step' should be non-negative.")
+  if(!is.numeric(aggregation_step)) stop("Parameter 'aggregation_step' should be a numeric.")
+  if(length(square)>1){
+    warning("Parameter 'square' has more elements (", as.character(length(square)), ") then expected (1). Only the first element is used.")
+    square <- square[1]
+  } else if(length(square)<1) stop("Parameter 'square' should be of length one.")
+  if(!is.logical(square)) stop("Parameter 'square' should be logical.")
+  if(is.na(square)) stop("NA values provided to parameter 'square'.")
+  if(aggregation_step >0 & aggregation_step <1 & !square) stop("Value (", aggregation_step,") set to parameter 'aggregation_steps' falling in the range ]0,1[ cannot be evaluated when using hexagonal grid.")
+
+  # Calculation
+  aggregation_step_is_integer = aggregation_step %% 1 == 0
+  if(square){ # square grid
+    count <- (ceiling(aggregation_step)*2+1)^2           # formula to use if the given aggregation_step is integer
+    if(!aggregation_step_is_integer) count <- count - 4 # formula to use if the given aggregation_step is fraction
+  }else{ # hexagonal grid
+    count <- sum((0:ceiling(aggregation_step)) * 6) + 1 # formula to use if the given aggregation_step is integer
+    if(!aggregation_step_is_integer) count <- count - 6 # formula to use if the given aggregation_step is fraction
+  }
+  count
+}

R/data.R

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+#' Sample vegetation data with hexagonal grid
+#'
+#' A generated dataset containing presences and absences of five vegetation types.
+#'
+#' @docType data
+#' @name hexagonal_data
+#' @usage data(hexagonal_data)
+#' @format An `sf` object with 300 rows and 6 variables.
+#' @author Krisztina Dóra Konrád \email{konrad.krisztina@@ecolres.hu}
+"hexagonal_data"
+
+
+#' Sample vegetation data with square grid
+#'
+#' A generated dataset containing presences and absences of five vegetation types.
+#'
+#'
+#' @docType data
+#' @name square_data
+#' @usage data(square_data)
+#' @format An `sf` object with 300 rows and 6 variables.
+#' @author Krisztina Dóra Konrád \email{konrad.krisztina@@ecolres.hu}
+"square_data"

README.md

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+
+<!-- Readme document of LandComp R package -->
+<!-- badges: start -->
+
+[![R-CMD-check](https://github.com/ladylavender/LandComp/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/ladylavender/LandComp/actions/workflows/R-CMD-check.yaml)
+<!-- badges: end -->
+
+# LandComp
+
+A package that enables quantifying landscape diversity and structure at
+multiple scales. For these purposes Juhász-Nagy’s functions,
+i.e. compositional diversity (CD) and associatum (AS), are calculated.
+
+## Installation
+
+You can install the development version of `LandComp` using the
+following command:
+
+``` r
+install.packages("devtools")
+devtools::install_github("ladylavender/LandComp")
+```
+
+## Example
+
+Example regular grids represent demonstrative spatial arrangements. They
+reflect a typical case when having presence/absence data on some
+landscape classes (e.g. vegetation types here) along a landscape. Note,
+there are three requirements of using the `LandComp` package:
+
+- the landscape data should be numeric binary, i.e. it should contain 0
+  or 1 values
+- the geometry of the landscape data should be a regular square or
+  hexagonal grid
+- the geometry of the landscape data should have projected coordinates
+  (i.e. WGS84 is not eligible)
+
+### Regular square grid data
+
+The structure and the visualization of the example square grid data:
+
+``` r
+suppressPackageStartupMessages(library("sf"))
+library(LandComp)
+data("square_data")
+plot(square_data)
+```
+
+![](man/figures/README-square_data-1.png)<!-- -->
+
+``` r
+str(square_data)
+#> Classes 'sf' and 'data.frame':   300 obs. of  6 variables:
+#>  $ VT1     : num  0 0 0 0 0 0 0 0 0 0 ...
+#>  $ VT2     : num  0 0 0 0 0 0 0 0 0 0 ...
+#>  $ VT3     : num  0 0 0 0 1 1 0 0 0 0 ...
+#>  $ VT4     : num  0 0 0 0 0 0 0 1 1 1 ...
+#>  $ VT5     : num  0 0 0 0 0 0 0 0 0 1 ...
+#>  $ geometry:sfc_POLYGON of length 300; first list element: List of 1
+#>   ..$ : num [1:5, 1:2] 400000 400000 405000 405000 400000 ...
+#>   ..- attr(*, "class")= chr [1:3] "XY" "POLYGON" "sfg"
+#>  - attr(*, "sf_column")= chr "geometry"
+#>  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA
+#>   ..- attr(*, "names")= chr [1:5] "VT1" "VT2" "VT3" "VT4" ...
+```
+
+Two values of CD and AS measuring landscape diversity and structure can
+be calculated as e.g.
+
+``` r
+LandComp(x = square_data, aggregation_steps = 0:1)
+#>   AggregationStep SpatialUnit_Size SpatialUnit_Area SpatialUnit_Count
+#> 1               0                1         2.50e+07               300
+#> 2               1                9         2.25e+08               234
+#>   UniqueCombination_Count   CD_bit    AS_bit
+#> 1                      13 2.755349 0.1709469
+#> 2                      18 3.176364 1.0874836
+```
+
+### Regular hexagonal grid data
+
+The structure and the visualization of the example hexagonal grid data:
+
+``` r
+data("hexagonal_data")
+plot(hexagonal_data)
+```
+
+![](man/figures/README-hexagonal_data-1.png)<!-- -->
+
+``` r
+str(hexagonal_data)
+#> Classes 'sf' and 'data.frame':   300 obs. of  6 variables:
+#>  $ VT1     : num  0 0 0 0 0 0 0 0 0 0 ...
+#>  $ VT2     : num  0 0 0 0 0 0 0 0 0 0 ...
+#>  $ VT3     : num  0 0 0 0 0 0 0 0 0 0 ...
+#>  $ VT4     : num  1 1 0 1 1 1 0 1 1 1 ...
+#>  $ VT5     : num  0 0 1 1 0 0 1 0 0 1 ...
+#>  $ geometry:sfc_POLYGON of length 300; first list element: List of 1
+#>   ..$ : num [1:7, 1:2] 649500 649000 649000 649500 650000 ...
+#>   ..- attr(*, "class")= chr [1:3] "XY" "POLYGON" "sfg"
+#>  - attr(*, "sf_column")= chr "geometry"
+#>  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA
+#>   ..- attr(*, "names")= chr [1:5] "VT1" "VT2" "VT3" "VT4" ...
+```
+
+``` r
+LandComp(x = hexagonal_data, aggregation_steps = 0:1)
+#>   AggregationStep SpatialUnit_Size SpatialUnit_Area SpatialUnit_Count
+#> 1               0                1         866025.4               300
+#> 2               1                7        6062177.8               234
+#>   UniqueCombination_Count   CD_bit    AS_bit
+#> 1                      12 1.972863 0.1256525
+#> 2                      16 3.422409 0.5394512
+```
+
+For further information and examples, see both the vignette of the
+package and `?LandComp` after installing the package.  
+Note, if you would like to view the vignette from R using the code
+`vignette("LandComp")`, you should install the package using the
+following command:
+
+``` r
+devtools::install_github("ladylavender/LandComp", build_vignettes = TRUE)
+```

inst/CITATION

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+
+bibentry(
+  bibtype  = "Article",
+  header   = "To cite LandComp in publications use:",
+  textVersion = paste("Konrád KD, Bede-Fazekas Á, Bartha S, Somodi I (2023) Adapting a multiscale approach to assess the compositional diversity of landscapes. Landscape Ecology 38:2731–2747. https://doi.org/10.1007/s10980-023-01759-y"),
+  title    = "Adapting a multiscale approach to assess the compositional diversity of landscapes",
+  author   = c(person(given = c("Krisztina", "Dóra"), family = "KONRÁD", role = "cph"),
+               person(given = "Ákos", family = "BEDE-FAZEKAS", role = "cph"),
+               person(given = "Sándor", family = "BARTHA", role = "cph"),
+               person(given = "Imelda", family = "SOMODI", role = "cph")),
+  journal  = "Landscape Ecology",
+  year     = "2023",
+  volume   = "38",
+  pages    = "2731–2747",
+  url      = "https://doi.org/10.1007/s10980-023-01759-y"
+)

inst/doc/LandComp.R

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+## ----include = FALSE----------------------------------------------------------
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+
+## ----setup--------------------------------------------------------------------
+library(LandComp)
+
+## ----square_data, echo = TRUE-------------------------------------------------
+suppressPackageStartupMessages(library("sf"))
+library(LandComp)
+data("square_data")
+str(square_data)
+
+## ----square_data_plot, out.width = '100%', echo = FALSE-----------------------
+knitr::include_graphics(path = "../man/figures/README-square_data-1.png")
+
+## ----square_example1, echo=TRUE-----------------------------------------------
+LandComp(x = square_data, aggregation_steps = 0)
+
+## ----square_units_plot, out.width = '50%', echo = FALSE-----------------------
+knitr::include_graphics(path = "../man/figures/spatial_units_square.png")
+
+## ----square_example2, echo=TRUE-----------------------------------------------
+LandComp(x = square_data, aggregation_steps = c(0.5, 1))
+
+## ----hexagonal_data, echo = TRUE----------------------------------------------
+data("hexagonal_data")
+str(hexagonal_data)
+
+## ----hexagonal_data_plot, out.width = '100%', echo = FALSE--------------------
+knitr::include_graphics(path = "../man/figures/README-hexagonal_data-1.png")
+
+## ----hexagonal_example1, echo=TRUE--------------------------------------------
+LandComp(x = hexagonal_data, aggregation_steps = 0)
+
+## ----hexagonal_units_plot, out.width = '50%', echo = FALSE--------------------
+knitr::include_graphics(path = "../man/figures/spatial_units_hexagon.png")
+
+## ----hexagonal_example2, echo=TRUE--------------------------------------------
+LandComp(x = hexagonal_data, aggregation_steps = c(1, 1.5))
+