read_nds.RdRead nodes' information from a file including all nodes and extract nodes of one decoration. Accepted formats are tab separated values ('tsv'), semicolon separated values ('csv'), or shapefile ('shp').
read_nds(site, decor, dir = getwd(), nodes = "nodes", format = "tsv")
| site | Name of the site |
|---|---|
| decor | Name of the decoration |
| dir | Path to the working folder, by default it is the working directory |
| nodes | Name of the nodes file (a dataframe or a shapefile) |
| format | File extension indicating a file format from 'tsv' (tab separated values),
'csv' (semicolon separated values) or 'shp' (shapefile). For 'tsv' and 'csv'
the files must include node coordinates ( |
Dataframe of graph nodes, including at least the columns "site", "decor", "id", "x", "y", with values for each node (row).
# Set data folder dataDir <- system.file("extdata", package = "iconr") # Read dataframe of nodes nds.df <- read_nds(site = "Cerro Muriano", decor = "Cerro Muriano 1", dir = dataDir, format = "tsv") nds.df#> site decor id type x y #> 1 Cerro Muriano Cerro Muriano 1 1 personnage 349.8148 -298.3244 #> 2 Cerro Muriano Cerro Muriano 1 2 casque 349.8148 -243.9851 #> 3 Cerro Muriano Cerro Muriano 1 3 lance 238.4637 -298.3244 #> 4 Cerro Muriano Cerro Muriano 1 4 bouclier 446.0222 -381.1697 #> 5 Cerro Muriano Cerro Muriano 1 5 peigne 283.0041 -358.0086 #> 6 Cerro Muriano Cerro Muriano 1 7 sexe_masculin 342.6884 -427.4917 #> 7 Cerro Muriano Cerro Muriano 1 8 lingot_pdb 451.1489 -237.4782## Dataframe of nodes # Read shapefile of nodes nds.df <- read_nds(site = "Cerro Muriano", decor = "Cerro Muriano 1", dir = dataDir, format = "shp") nds.df#> site decor id type x y #> 1 Cerro Muriano Cerro Muriano 1 1 personnage 349.8148 -298.3244 #> 2 Cerro Muriano Cerro Muriano 1 2 casque 349.8148 -243.9851 #> 3 Cerro Muriano Cerro Muriano 1 3 lance 238.4637 -298.3244 #> 4 Cerro Muriano Cerro Muriano 1 4 bouclier 446.0222 -381.1697 #> 5 Cerro Muriano Cerro Muriano 1 5 peigne 283.0041 -358.0086 #> 6 Cerro Muriano Cerro Muriano 1 7 sexe_masculin 342.6884 -427.4917 #> 7 Cerro Muriano Cerro Muriano 1 8 lingot_pdb 451.1489 -237.4782## Dataframe of nodes