website

.Rbuildignore

@@ -6,3 +6,4 @@
 ^_pkgdown\.yml$
 ^docs$
 ^pkgdown$
+^codecov\.yml$

DESCRIPTION

@@ -2,25 +2,36 @@ Package: mammalcol
 Title: Access to the List of Mammals Species of Colombia
 Version: 0.1.0
 Authors@R: 
-    person("Diego J.", "Lizcano", , 
-    "[email protected]", role = c("aut", "cre"),
+    person("Diego J.", "Lizcano", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-9648-0576"))
 Maintainer: Diego J. Lizcano <[email protected]>
-Description: Allows access to the data found in the species list featured in the renowned "Ramírez-Chaves, et al. 2021. Checklist of the Mammals (Mammalia) of Colombia”. Mammalogy Notes 7(2),253. <https://doi.org/10.47603/mano.v7n2.253>. This publication stands as one of Colombia's most comprehensive reviews of mammal diversity. The dataset incorporates detailed species accounts and has been meticulously structured for effortless utilization within the R environment.
+Description: Allows access to the data found in the species list featured
+    in the renowned "Ramírez-Chaves, et al. 2021. Checklist of the Mammals
+    (Mammalia) of Colombia”. Mammalogy Notes 7(2),253.
+    <https://doi.org/10.47603/mano.v7n2.253>. This publication stands as
+    one of Colombia's most comprehensive reviews of mammal diversity. The
+    dataset incorporates detailed species accounts and has been
+    meticulously structured for effortless utilization within the R
+    environment.
 License: MIT + file LICENSE
-Imports:
-    dplyr,
-    ggplot2,
-    sf
-Suggests: 
-    testthat (>= 3.0.0),
-    dplyr  
-Config/testthat/edition: 3
-Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
-URL: https://github.com/dlizcano/mamalcol, https://dlizcano.github.io/mammalcol/
+URL: https://github.com/dlizcano/mamalcol,
+    https://dlizcano.github.io/mammalcol/
 BugReports: https://github.com/dlizcano/mammalcol/issues
 Depends: 
     R (>= 2.10)
+Imports:
+    ggplot2
+Suggests:
+    dplyr,
+    finch,
+    geodata,
+    readr,
+    readxl,
+    sf,
+    stringr,
+    testthat (>= 3.0.0)
+Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: true
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.3.1

R/mammalmap.R

@@ -9,6 +9,7 @@
 #' It is advised to run first the search_mammalcol function.
 #'
 #' @param species A character string containing the name of the species to plot the map.
+#' 
 #'
 #' @return A map for the species.
 #'
@@ -17,6 +18,8 @@
 #' species <- "Tapirus pinchaque" 
 #' mammalmap(species)
 #'
+#' @importFrom rlang taxon
+#' @importFrom rlang colmap
 #' @export
 mammalmap <- function(species){
 
@@ -34,8 +37,8 @@ mammalmap <- function(species){
   distribution_list <-
     strsplit(taxon$distribution, "\\|") # trimws () removes spaces
 
-  deptos <- as.data.frame( cbind(Depto=unique(colmap$NAME_1), fill="white"))
-  sp_id <- which(taxon$scientificName==species)
+  deptos <- as.data.frame(cbind(Depto=unique(colmap$NAME_1), fill="white"))
+  sp_id <- which(taxon$scientificName == species)
   unos <- trimws(distribution_list[[ sp_id ]]) # species number
 
   # nested loop to get deptos

README.Rmd

@@ -192,6 +192,8 @@ mammalmap <- function(species){
 # mammalcol <img src="man/figures/logo.png" align="right" height="139" alt="" />
 <!-- badges: start -->
 [![R-CMD-check](https://github.com/dlizcano/mammalcol/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/dlizcano/mammalcol/actions/workflows/R-CMD-check.yaml)
+[![Codecov test coverage](https://codecov.io/gh/dlizcano/mammalcol/branch/main/graph/badge.svg)](https://app.codecov.io/gh/dlizcano/mammalcol?branch=main)
+[![CRAN status](https://www.r-pkg.org/badges/version/mammalcol)](https://CRAN.R-project.org/package=mammalcol)
 <!-- badges: end -->
 
 The goal of mammalcol is to allow easy access to the List of Mammal Species of Colombia.

README.md

@@ -6,6 +6,10 @@
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/dlizcano/mammalcol/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/dlizcano/mammalcol/actions/workflows/R-CMD-check.yaml)
+[![Codecov test
+coverage](https://codecov.io/gh/dlizcano/mammalcol/branch/main/graph/badge.svg)](https://app.codecov.io/gh/dlizcano/mammalcol?branch=main)
+[![CRAN
+status](https://www.r-pkg.org/badges/version/mammalcol)](https://CRAN.R-project.org/package=mammalcol)
 <!-- badges: end -->
 
 The goal of mammalcol is to allow easy access to the List of Mammal

codecov.yml

@@ -0,0 +1,14 @@
+comment: false
+
+coverage:
+  status:
+    project:
+      default:
+        target: auto
+        threshold: 1%
+        informational: true
+    patch:
+      default:
+        target: auto
+        threshold: 1%
+        informational: true

data-raw/convert_tables.R

@@ -0,0 +1,208 @@
+
+require(readr)
+require(geodata)
+require(finch)
+library(stringr)
+library(dplyr)
+library(readxl)
+
+
+###########
+# read ipt
+##########
+
+ipt.files <-
+  dwca_read(
+    "https://ipt.biodiversidad.co/sib/archive.do?r=mamiferos_col",
+    read = T,
+    na.strings = "",
+    encoding = "UTF-8"
+  )
+
+taxon <- ipt.files$data$taxon.txt
+distribution <- ipt.files$data$distribution.txt
+vernacularname <- ipt.files$data$vernacularname.txt
+
+
+####################
+# read from had disk
+####################
+
+colmap <- sf::st_as_sf(gadm(country="COL", level=1, path=tempdir()))
+#Let’s apply st_simplify with a tolerance of 1km:
+colmap <- st_simplify(colmap, preserveTopology = FALSE, dTolerance = 1000)
+
+# taxon <- read_delim("C:/Users/usuario/Downloads/mammal_col_2024/taxon.csv",
+#                    delim = "\t", escape_double = FALSE)
+
+# distribution <- read_delim("C:/Users/usuario/Downloads/mammal_col_2024/distribution.csv",
+#                    delim = "\t", escape_double = FALSE)
+
+
+MDD <-  read_csv("C:/Users/usuario/Downloads/mammal_col_2024/MDD_v1.12.1_6718species.csv")
+#vernacularname <- read_delim("C:/Users/usuario/Downloads/mammal_col_2024/vernacularname.csv",
+#                             delim = "\t", escape_double = FALSE,
+#                             trim_ws = TRUE) %>% filter(language=="es")
+
+
+redlist <- read_excel("C:/Users/usuario/Downloads/mammal_col_2024/Mamíferos_Evaluados_2021-2022.xlsx")
+names(redlist) <- c("scientificName", "Año de evaluación", "redlist", "Taller")
+
+####################
+
+
+
+MDD$scientificName <-  stringr::str_replace(MDD$sciName, "_", " ")
+
+
+# left join
+MamCol_MDD <- left_join(taxon, MDD, by="scientificName")
+MamCol_MDD$inMDD <- is.na(MamCol_MDD$sciName)
+MamCol_redlist <- left_join(taxon, redlist, by="scientificName")
+MamCol_distribution <- left_join(taxon, distribution, by="id")
+MamCol_vernacular <- left_join(taxon, vernacularname, by="id")
+
+####
+index_notMDD <- which(is.na(MamCol_MDD$sciName))
+taxon$inMDD <- 1# ifelse(is.na(MamCol_MDD$inMDD$inMDD), 0, 1) #All to 1
+# convert true NA to 0
+taxon$inMDD[index_notMDD] <- 0 # asign if is in MDD
+taxon$Col_redlist <- MamCol_redlist$redlist # national redlist
+taxon$distribution <- MamCol_distribution$locality # present in depto
+taxon$source <- MamCol_distribution$source
+index_endemic <- which(MamCol_distribution$establishmentMeans == "Endémica")
+taxon$endemic <- "No"
+taxon$endemic[index_endemic] <- "Yes"
+taxon$english_name <- MamCol_MDD$mainCommonName
+#taxon$spanish_name <- MamCol_vernacular$vernacularName
+#taxon$name_language <- MamCol_vernacular$language
+
+
+
+###################
+fix.encoding <- function(df, originalEncoding = "UTF-8") {
+  numCols <- ncol(df)
+  df <- data.frame(df)
+  for (col in 1:numCols)
+  {
+    if(class(df[, col]) == "character"){
+      Encoding(df[, col]) <- originalEncoding
+    }
+
+    if(class(df[, col]) == "factor"){
+      Encoding(levels(df[, col])) <- originalEncoding
+    }
+  }
+  return(as.data.frame(df))
+}
+#################
+# remove cols
+taxon <- taxon[,-c(1,2,3,5,15,17,18)]
+# mammal_colombia_2024 <- fix.encoding(taxon) # rename
+
+
+
+#save as RDS
+save (taxon, file="C:/CodigoR/Mammal_Col/mammalcol/data/taxon.rda")
+# load(file="C:/CodigoR/Mammal_Col/MammalCol/data/taxon.rda")#, encoding = "UTF-8")
+save (colmap, file="C:/CodigoR/Mammal_Col/MammalCol/data/colmap.rda")
+
+
+
+#######################
+# hex package logo
+
+library(showtext)
+## Loading Google fonts (http://www.google.com/fonts)
+# font_add_google("Gochi Hand", "gochi")
+font_add_google("Open Sans")
+## Automatically use showtext to render text for future devices
+showtext_auto()
+
+library(magick)
+library(hexSticker)
+img.n <- image_read("C:/CodigoR/Mammal_Col/MammalCol_old/man/figures/SCMas_Small.png")
+#SCMas_png <- image_convert(img.n, "png")
+image_info(img.n)
+sticker(img.n, package="mammalcol", p_size=20, s_x=1, s_y=.85,
+        s_width=1.3, s_height=1.3,
+        h_size=1.5,
+        p_color="#0c0706",
+        p_family="Open Sans",
+        p_fontface = "bold",
+        h_color= "#4a7092",
+        h_fill= "#F0F8FF",
+        filename="inst/figures/mammalcol_hex.png")
+
+
+###############
+# ocurrence by Depto
+
+occurrence <- function(states, type = c("any", "only", "all"), taxa = NULL) {
+  if (length(states) == 0) stop("Please provide at least one Colombian Departamento")
+  type <- match.arg(type)
+  states <- sort(states)
+  # states <- paste("BR-", states, sep = "")
+  if (length(states) == 0) stop("Please provide at least one Colombian Departamento")
+  # res <- lapply(occurrences, match, states)
+  if (type == "any") {
+    #res <- lapply(res, function(x) any(!is.na(x)))
+    res <- subset(distribution, grepl(paste(states, collapse = "|"), occurrence))
+  }
+  if (type == "only") {
+    res <- subset(distribution, grepl(paste("^", paste(states, collapse = "\\|"), "$", sep = ""), occurrence))
+  }
+  if (type == "all") {
+    res <- subset(distribution, grepl(paste(states, collapse = ".*"), occurrence))
+  }
+  # res <- distribution[unlist(res), ]
+  if (nrow(res) == 0) {
+    return(NA)
+  }
+  if (is.null(taxa)) {
+    merge(all.taxa[, c("id", "family", "search.str")], res[, c("id", "occurrence")], by = "id")
+  } else {
+    merge(all.taxa[all.taxa$search.str %in% taxa, c("id", "family", "search.str")], res[, c("id", "occurrence")], by = "id")
+  }
+}
+
+
+
+#### test
+# test <- subset(distribution, grepl(paste("^", paste("Atlántico" , collapse = "\\|"), "$", sep = ""), taxon))
+
+distribution_list <-
+    strsplit(distribution$locality, "\\|") # trimws () removes spaces
+
+# trimws(distribution_list[[55]])
+
+mammalmap <- function(species){
+
+  deptos <- as.data.frame( cbind(Depto=unique(colmap$NAME_1), fill="white"))
+  sp_id <- which(taxon$scientificName==species)
+  unos <- trimws(distribution_list[[ sp_id ]]) # species number
+
+  # nested loop to get deptos
+  for (i in 1:length(deptos[,1])){
+    for (j in 1:length(unos)){
+         if(deptos$Depto[i]==unos[j]){deptos$fill[i] <- "blue"}
+    }
+  }
+
+  # make the map
+  ggplot(colmap) +
+    geom_sf(aes(fill = NAME_1)) +
+    scale_fill_manual(values = deptos$fill) +
+    # ggtitle(taxon$scientificName[25]) + #species name number
+    labs(subtitle = taxon$scientificName[sp_id])+
+    theme(legend.position="right", # locatio legend
+          legend.title = element_blank(),#element_text(size=7),#,
+          legend.text = element_text(size=7,), # text depto size
+          plot.subtitle = element_text(face = "italic") # italica
+                    )#,
+}
+
+
+
+
+