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  • Grelot Frederic's avatar
    catnat, population, clc · 9dbbbaeb
    Grelot Frederic authored 
    - catnat dataset remplace gaspar dataset
	- passage en array pour garder les types d'aléa
- estimate_catnat_freq incluse dans la librairie
- population dataset pour la population
- clc_color dataset pour les couleurs et label de clc
- map_so_ii inclus population, gère les légendes pour les thèmes
- dossier script hors librairie por garder la trace des mises à jour des données (doit aller dand floodam.data)

0 errors :heavy_check_mark: | 0 warnings :heavy_check_mark: | 1 note :heavy_multiplication_x:
Mais la note concerne le temps...
    9dbbbaeb
so_ii_scope.R 2.09 KiB
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# code to prepare `so_ii_scope` dataset goes here
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so_ii_scope = read.csv2(
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    current_version("data-common/so-ii/scope"),
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    colClasses = "character"
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)[["code"]]
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so_ii_scope = sort(so_ii_scope)
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# code to prepare `so_ii_commune` dataset goes here
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admin_express = current_version("data-common/data/IGN/ADMIN-EXPRESS/version")
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selection = c("ID", "NOM", "NOM_M", "INSEE_COM", "STATUT", "POPULATION", "SIREN_EPCI")
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so_ii_commune = sf::st_read(file.path(admin_express, "COMMUNE.shp"))[selection]
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names(so_ii_commune) = c("id", "commune", "commune_majuscule", "code", "statut", "pop_2021", "epci", "geometry")
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rownames(so_ii_commune) = so_ii_commune[["code"]]
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so_ii_commune = so_ii_commune[so_ii_scope, ]
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# code to prepare `so_ii_limit` dataset goes here
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so_ii_limit = sf::st_union(so_ii_commune)
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# code to prepare `so_ii_clc` dataset goes here
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so_ii_clc = readRDS("data-common/data/so-ii/so-ii_clc.rds")
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so_ii_clc = so_ii_clc["code_18"]
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names(so_ii_clc) = c("clc_2018", "geometry")
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clc_color = data.frame(
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    color = scales::alpha(
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        c(
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            "red3",
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            "darkolivegreen3",
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            "darkgreen",
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            "#4C90B4",
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            "lightblue"
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        ),
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        .2
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    ),
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    label_fr = c(
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        "Zone urbaine",
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        "Zone agricole",
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        "Forêt, zone naturelle",
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        "Zone humide",
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        "Surface d'eau"
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    ),
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    label_uk = c(
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        "Urban area",
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        "Agricultural area",
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        "Forest, natural area",
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        "Humid area",
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        "Water surface"
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    )
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)
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so_ii_clc[["color"]] = as.character(
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    cut(
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        as.integer(substr(so_ii_clc[["clc_2018"]], 1, 1)),
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        breaks = 5,
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        labels = clc_color[["color"]]
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    )
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)
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# updating datasets
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# actual = setwd(file.path(system.file(package = "geau"), ".."))
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actual = setwd("geau")
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usethis::use_data(so_ii_scope, internal = FALSE, overwrite = TRUE)
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usethis::use_data(so_ii_commune, internal = FALSE, overwrite = TRUE)
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usethis::use_data(so_ii_limit, internal = FALSE, overwrite = TRUE)
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usethis::use_data(so_ii_clc, internal = FALSE, overwrite = TRUE)
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usethis::use_data(clc_color, internal = FALSE, overwrite = TRUE)
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setwd(actual)
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