From f16a80752ebdd35aaf846dae383bf73faad714bf Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fr=C3=A9d=C3=A9ric=20Grelot?= <frederic.grelot@irstea.fr>
Date: Sun, 23 Jan 2022 00:41:07 +0100
Subject: [PATCH] =?UTF-8?q?geau=20Version=201.0.7.0=200=20errors=20?=
=?UTF-8?q?=E2=9C=94=20|=200=20warnings=20=E2=9C=94=20|=200=20notes=20?=
=?UTF-8?q?=E2=9C=94?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
- map_so_ii
- ajout du thème onrn, gestion des detail n_catnat, freq_sin, cost, cost_hab, cost_mean, ratio, balance, ppri_year
- réorganisation du code pour theme dans l'ordre alphabétique
- so_ii_onrn dataset
- inclusion & aide
- so_ii_clc
- correction de l'aide
- so_ii_limit
- correction de l'aide
Refs #7
---
geau/DESCRIPTION | 2 +-
geau/R/data.r | 193 +++++++++++--------
geau/R/map_so_ii.r | 378 ++++++++++++++++++++++++-------------
geau/data-raw/so_ii_onrn.R | 28 +++
geau/data/so_ii_onrn.rda | Bin 0 -> 2936 bytes
geau/man/map_so_ii.Rd | 4 +-
geau/man/so_ii_clc.Rd | 8 +-
geau/man/so_ii_limit.Rd | 10 -
geau/man/so_ii_onrn.Rd | 50 +++++
9 files changed, 453 insertions(+), 220 deletions(-)
create mode 100644 geau/data-raw/so_ii_onrn.R
create mode 100644 geau/data/so_ii_onrn.rda
create mode 100644 geau/man/so_ii_onrn.Rd
diff --git a/geau/DESCRIPTION b/geau/DESCRIPTION
index 168cad4..6d9acb0 100644
--- a/geau/DESCRIPTION
+++ b/geau/DESCRIPTION
@@ -1,6 +1,6 @@
Package: geau
Title: Utilities very useful to share within geau-inondation team
-Version: 1.0.6.1
+Version: 1.0.7.0
Authors@R:
c(
person(given = "Frédéric",
diff --git a/geau/R/data.r b/geau/R/data.r
index 7528b6f..11d1c53 100644
--- a/geau/R/data.r
+++ b/geau/R/data.r
@@ -1,10 +1,55 @@
-#' Local collectivities included in so-ii
+#' Color and label for CLC
#'
-#' A dataset containing the INSEE code of all local collectivities
-#' (communes) included in so-ii
+#' A dataset proposing default colors and labels for plotting CLC
#'
-#' @format a vector of 78 INSEE code
-"so_ii_scope"
+#' @format data.frame 5 rows, 3 variables
+"clc_color"
+
+#' Catchment areas of interest within the so-ii perimeter
+#'
+#' A dataset containing the official catchments areas of interest from the BD
+#' TOPAGE within the so-ii perimeter. For degre = 3, the data are basically
+#' what is found in BD TOPAGE. For degres 1 and 2, the data result from
+#' sf::st_union of data of degre 3 to give a more synthetic representation.
+#'
+#' @format sf data.frame 15 rows, 4 variables
+#' \describe{
+#' \item{id}{id, from BD TOPAGE (corresponding to CdOh) or NA when catchment
+#' is constructed by so-ii team.}
+#' \item{name}{character, name of the catchment area in BD TOPAGE, or given
+#' name for catchments constructed by so-ii team.}
+#' \item{degre}{factor, importance of the catchment used to plot the
+#' catchment areas with different levels of detail ("1", "2", "3").}
+#' }
+#'
+#' @source \url{http://bdtopage.eaufrance.fr/page/objectifs}
+"so_ii_catchment"
+
+#' Number of Cat Nat events for the municipalities of so-ii
+#'
+#' A dataset containing the number of Cat Nat events (linked to flood) by year
+#' and so-ii municipality according to the GASPAR database.
+#'
+#' @format array with 3 dimensions
+#' \describe{
+#' \item{first}{commune as in so_ii_scope}
+#' \item{second}{year of Cat Nat events}
+#' \item{third}{type of hazard}
+#' }
+#'
+#' @source \url{https://www.georisques.gouv.fr/donnees/bases-de-donnees/base-gaspar} # nolint
+"so_ii_catnat"
+
+#' CLC information for so-ii
+#'
+#' A dataset containing the Corine Land Cover information on so-ii.
+#'
+#' @format sf data.frame 1337 rows, 2 variables
+#' \describe{
+#' \item{clc_2018}{character, classification from CLC 2018}
+#' \item{color}{character, default color to be used to plot so_ii_clc}
+#' }
+"so_ii_clc"
#' Spatial definition of collectivities included in so-ii
#'
@@ -37,6 +82,25 @@
#' @source \url{https://www.data.gouv.fr/fr/datasets/admin-express/}
"so_ii_collectivity"
+#' Hydrographic network within the so-ii perimeter
+#'
+#' A dataset containing the official hydrographic network from the BD TOPAGE
+#' within the so-ii perimeter.
+#'
+#' @format sf data.frame 125 rows, 4 variables
+#' \describe{
+#' \item{id}{id, from BD TOPAGE (corresponding to CdOh)}
+#' \item{name}{character, name of the hydrographic elements in the BD TOPAGE}
+#' \item{degre}{factor, level of importance of the hydrographic element
+#' used to plot the hydrographic network with different levels of
+#' detail ("1", "2", "3").}
+#' \item{type}{factor, type of hydrographic element ("canal", "river",
+#' "waterbody")}
+#' }
+#'
+#' @source \url{http://bdtopage.eaufrance.fr/page/objectifs}
+"so_ii_hydro"
+
#' Spatial perimeter of so-ii
#'
#' A dataset containing the perimeter of so-ii.
@@ -47,16 +111,53 @@
#' @format sfc_POLYGON of length 1
"so_ii_limit"
-#' CLC information for so-ii
+#' Local collectivities included in so-ii
#'
-#' A dataset containing the Corine Land Cover information on so-ii.
+#' A dataset containing the INSEE code of all local collectivities
+#' (communes) included in so-ii
#'
-#' @format sf data.frame 1337 rows, 2 variables
+#' @format a vector of 78 INSEE code
+"so_ii_scope"
+
+#' ONRN information for so-ii
+#'
+#' A dataset containing part of the information available at the ONRN for so-ii
+#' communities. The information chosen is exclusively related to floods. It is
+#' mainly related to impacts and therefore to the claims in from the Cat-Nat
+#' system. These data on claims are taken from the CCR, the others from the
+#' gaspar database.
+#'
+#' @format data.frame 78 rows, 23 variables
#' \describe{
-#' \item{clc_2018}{character, classification from CLC 2018}
-#' \item{color}{character, default color to be used to plot so_ii_clc}
+#' \item{n_catnat}{Number of Cat Nat events}
+#' \item{freq_sin}{Number of claims divided by number of contracts
+#' for 1995 to 2018. freq_sin is calculated as the mean of freq_sin_min
+#' and freq_sin_max (range for each category).}
+#' \item{cost}{Cumulative cost of claims for 1995 to 2018. Cost is calculated
+#' as the mean of cost_min and cost_max (range for each category).}
+#' \item{cost_mean}{Mean cost of claims (cost divided by claims) for 1995 to
+#' 2018. cost_mean is calculated as the mean of cost_mean_min and
+#' cost_mean_max (range for each category).}
+#' \item{cost_hab}{Cost divided by the population for 1995 to 2018. cost_hab
+#' is calculated as the mean of cost_hab_min and cost_hab_max (range for
+#' each category).}
+#' \item{ratio}{Cost divided by premium for 1995 to 2018. ratio is calculated
+#' as the mean of cost_hab_min and cost_hab_max (range for each
+#' category).}
+#' \item{balance}{Cost minus premium for 1995 to 2018. This is an estimation
+#' made by so-ii team by considering a mean premium for each habitant
+#' of 24.92829 euro per habitant (total premium in 2018 divided by
+#' total population)}
+#' \item{ppri_year}{Year given for the last PPRI.}
+#' \item{ppri_state}{State of the last PPRI.}
+#' \item{ppri_state_sub}{Some details on the state of the last PPRI.}
+#' \item{ppri_state_age}{State of the last PPRI for age information.}
+#' \item{ppri_age_min}{Lower boundary for the age of the PPRI.}
+#' \item{ppri_age_min}{Upper boundary for the age of the PPRI..}
#' }
-"so_ii_limit"
+#'
+#' @source \url{https://www.georisques.gouv.fr/articles-risques/acceder-aux-indicateurs-sinistralite}
+"so_ii_onrn"
#' Population for so-ii
#'
@@ -69,72 +170,4 @@
#' }
#'
#' @source \url{https://www.insee.fr/fr/statistiques/2522602}
-"so_ii_population"
-
-#' Number of Cat Nat events for the municipalities of so-ii
-#'
-#' A dataset containing the number of Cat Nat events (linked to flood) by year
-#' and so-ii municipality according to the GASPAR database.
-#'
-#' @format array with 3 dimensions
-#' \describe{
-#' \item{first}{commune as in so_ii_scope}
-#' \item{second}{year of Cat Nat events}
-#' \item{third}{type of hazard}
-#' }
-#'
-#' @source \url{https://www.georisques.gouv.fr/donnees/bases-de-donnees/base-gaspar} # nolint
-"so_ii_catnat"
-
-#' CLC information for so-ii
-#'
-#' A dataset containing the 2018 version of CLC information for so-ii
-#'
-#' @format sf object
-"so_ii_clc"
-
-#' Color and label for CLC
-#'
-#' A dataset proposing default colors and labels for plotting CLC
-#'
-#' @format data.frame 5 rows, 3 variables
-"clc_color"
-
-#' Hydrographic network within the so-ii perimeter
-#'
-#' A dataset containing the official hydrographic network from the BD TOPAGE
-#' within the so-ii perimeter.
-#'
-#' @format sf data.frame 125 rows, 4 variables
-#' \describe{
-#' \item{id}{id, from BD TOPAGE (corresponding to CdOh)}
-#' \item{name}{character, name of the hydrographic elements in the BD TOPAGE}
-#' \item{degre}{factor, level of importance of the hydrographic element
-#' used to plot the hydrographic network with different levels of
-#' detail ("1", "2", "3").}
-#' \item{type}{factor, type of hydrographic element ("canal", "river",
-#' "waterbody")}
-#' }
-#'
-#' @source \url{http://bdtopage.eaufrance.fr/page/objectifs}
-"so_ii_hydro"
-
-#' Catchment areas of interest within the so-ii perimeter
-#'
-#' A dataset containing the official catchments areas of interest from the BD
-#' TOPAGE within the so-ii perimeter. For degre = 3, the data are basically
-#' what is found in BD TOPAGE. For degres 1 and 2, the data result from
-#' sf::st_union of data of degre 3 to give a more synthetic representation.
-#'
-#' @format sf data.frame 15 rows, 4 variables
-#' \describe{
-#' \item{id}{id, from BD TOPAGE (corresponding to CdOh) or NA when catchment
-#' is constructed by so-ii team.}
-#' \item{name}{character, name of the catchment area in BD TOPAGE, or given
-#' name for catchments constructed by so-ii team.}
-#' \item{degre}{factor, importance of the catchment used to plot the
-#' catchment areas with different levels of detail ("1", "2", "3").}
-#' }
-#'
-#' @source \url{http://bdtopage.eaufrance.fr/page/objectifs}
-"so_ii_catchment"
\ No newline at end of file
+"so_ii_population"
\ No newline at end of file
diff --git a/geau/R/map_so_ii.r b/geau/R/map_so_ii.r
index d165283..5eb7b23 100644
--- a/geau/R/map_so_ii.r
+++ b/geau/R/map_so_ii.r
@@ -16,6 +16,8 @@
#' levels of detail or "canal", "river", "waterbody" for types of
#' hydrographic elements. If missing, "none" will be chosen, and
#' everything is plotted.}
+#' \item{\strong{onrn}: detail must be chosen in "n_catnat", "freq_sin",
+#' "cost", "cost_hab", "cost_mean", "ratio", "balance", "ppri_year".}
#' }
#' }
#' \subsection{year specification}{
@@ -55,7 +57,7 @@
map_so_ii = function(
dataset,
dataset_legend = NULL,
- theme = c("none", "collectivity", "catchment", "catnat", "clc", "hydro", "population"),
+ theme = c("none", "collectivity", "catchment", "catnat", "clc", "hydro", "onrn", "population"),
bar = TRUE,
path = NULL,
legend_theme = FALSE,
@@ -79,6 +81,102 @@ map_so_ii = function(
graphics::par(mai = c(.65, .60, .50, .15))
plot(geau::so_ii_limit, axes = TRUE)
+ if ("catchment" %in% theme) {
+ if (missing(detail)) {
+ detail = "1"
+ }
+ detail = match.arg(
+ as.character(detail),
+ choices = levels(geau::so_ii_catchment[["degre"]])
+ )
+ selection = geau::so_ii_catchment[["degre"]] == detail
+ geometry = geau::so_ii_catchment[["geometry"]][selection]
+ catchment = as.factor(geau::so_ii_catchment[["catchment_name"]][selection])
+ color_legend = grDevices::hcl.colors(nlevels(catchment), "Pastel 1", alpha = .3)
+ color = color_legend[catchment]
+ border = "grey80"
+ lwd = 2
+ theme_legend = list(
+ title = sprintf("Bassin versant"),
+ legend = levels(catchment),
+ x = "topright",
+ cex = .8,
+ bg = "white",
+ inset = 0.01,
+ fill = color_legend,
+ border = border
+ )
+ if (detail == "3") rm(theme_legend)
+
+ plot(geometry, border = border, col = color, lwd = lwd, add = TRUE)
+ }
+
+ if ("catnat" %in% theme) {
+ if (missing(detail)) {
+ detail = dimnames(geau::so_ii_catnat)[["hazard"]]
+ }
+ detail = match.arg(
+ detail,
+ dimnames(geau::so_ii_catnat)[["hazard"]],
+ several.ok = TRUE
+ )
+ border = NA
+ color = NA
+ if (!missing(year)) {
+ year = match.arg(
+ as.character(year),
+ dimnames(geau::so_ii_catnat)[["period"]]
+ )
+ border = "grey80"
+ catnat = apply(
+ geau::so_ii_catnat[, year, detail, drop = FALSE],
+ 1:2,
+ sum
+ )
+ color = ifelse(
+ catnat > 0,
+ scales::alpha("grey80", .5),
+ NA
+ )
+ theme_legend = list(
+ title = sprintf("Cat-Nat %s", year),
+ legend = c("Sans d\u00e9claration", "Avec d\u00e9claration"),
+ x = "topright",
+ cex = .8,
+ bg = "white",
+ inset = 0.01,
+ fill = unique(color),
+ border = border
+ )
+ }
+
+ plot(
+ geau::so_ii_collectivity[["geometry"]],
+ border = border,
+ col = color,
+ add = TRUE
+ )
+ }
+
+ if ("clc" %in% theme) {
+ plot(
+ geau::so_ii_clc[["geometry"]],
+ border = NA,
+ col = geau::so_ii_clc[["color"]],
+ add = TRUE
+ )
+
+ theme_legend = list(
+ title = "CLC (2018)",
+ legend = geau::clc_color[["label_fr"]],
+ x = "topright",
+ cex = .8,
+ bg = "white",
+ inset = 0.01,
+ fill = geau::clc_color[["color"]]
+ )
+ }
+
if ("collectivity" %in% theme) {
if (missing(detail)) {
detail = "none"
@@ -136,23 +234,167 @@ map_so_ii = function(
}
}
- if ("clc" %in% theme) {
+ if ("hydro" %in% theme) {
+ if (missing(detail)) {
+ detail = "none"
+ }
+ detail = match.arg(
+ as.character(detail),
+ choices = c(
+ "none",
+ levels(geau::so_ii_hydro[["degre"]]),
+ levels(geau::so_ii_hydro[["type"]])
+ )
+ )
+ color = scales::alpha("blue", .3)
+ bg = scales::alpha("blue", .3)
+ border = NA
+ selection = seq(nrow(geau::so_ii_hydro))
+ theme_legend = list(
+ title = sprintf("R\u00e9seau hydrographique"),
+ legend = "\u00e9l\u00e9ment du r\u00e9seau",
+ x = "topright",
+ cex = .8,
+ bg = "white",
+ inset = 0.01,
+ col = color,
+ lwd = 1
+ )
+ if (detail %in% levels(geau::so_ii_hydro[["type"]])) {
+ selection = as.character(geau::so_ii_hydro[["type"]]) == detail
+ theme_legend[["legend"]] = detail
+ }
+ if (detail %in% levels(geau::so_ii_hydro[["degre"]])) {
+ selection = as.character(geau::so_ii_hydro[["degre"]]) <= detail
+ }
+ geometry = geau::so_ii_hydro[["geometry"]][selection]
+ lwd = 4 - as.numeric(geau::so_ii_hydro[["degre"]][selection])
+
+ plot(geometry, col = color, lwd = lwd, border = border, add = TRUE)
+ }
+
+ if ("onrn" %in% theme) {
+ if (missing(detail)) {
+ detail = "cost"
+ }
+ detail = match.arg(
+ as.character(detail),
+ sort(colnames(geau::so_ii_onrn)[1:8])
+ )
+
+ onrn_palette = switch(
+ EXPR = detail,
+ "n_catnat" = scales::colour_ramp(c("white", "red"), alpha = .5),
+ "freq_sin" = scales::colour_ramp(c("white", "red"), alpha = .5),
+ "cost" = scales::colour_ramp(c("white", "red"), alpha = .5),
+ "cost_hab" = scales::colour_ramp(c("white", "red"), alpha = .5),
+ "cost_mean" = scales::colour_ramp(c("white", "red"), alpha = .5),
+ "ratio" = scales::colour_ramp(c("green", "white", "red"), alpha = .5),
+ "balance" = scales::colour_ramp(c("red", "white", "green"), alpha = .5),
+ "ppri_year" = scales::colour_ramp(c("grey80", "grey50"), alpha = .5),
+ NULL
+ )
+ onrn_trans = switch(
+ EXPR = detail,
+ "n_catnat" = scales::identity_trans(),
+ "freq_sin" = scales::identity_trans(),
+ "cost" = scales::sqrt_trans(),
+ "cost_hab" = scales::sqrt_trans(),
+ "cost_mean" = scales::sqrt_trans(),
+ "ratio" = scales::sqrt_trans(),
+ "balance" = scales::modulus_trans(.5),
+ "ppri_year" = scales::identity_trans(),
+ NULL
+ )
+ onrn_range = switch(
+ EXPR = detail,
+ "ratio" = c(0, 4),
+ "balance" = max(abs(range(geau::so_ii_onrn[["balance"]]))) * c(-1, 1),
+ NULL
+ )
+
+ color = scales::cscale(
+ c(onrn_range, geau::so_ii_onrn[[detail]]),
+ onrn_palette,
+ trans = onrn_trans)
+ if (length(onrn_range) > 0) {
+ color = color[-seq(onrn_range)]
+ }
+ border = "grey80"
plot(
- geau::so_ii_clc[["geometry"]],
- border = NA,
- col = geau::so_ii_clc[["color"]],
+ geau::so_ii_collectivity[["geometry"]],
+ border = border,
+ col = color,
add = TRUE
)
+ if (sprintf("%s_min", detail) %in% names(geau::so_ii_onrn)) {
+ selection = c(detail, sprintf("%s_min", detail), sprintf("%s_max", detail))
+ temp = unique(geau::so_ii_onrn[selection])
+ temp = temp[order(temp[[detail]]), ]
+ text_legend = gsub("0 - 0", "0",
+ sprintf(
+ "%s - %s",
+ temp[[sprintf("%s_min", detail)]],
+ temp[[sprintf("%s_max", detail)]]
+ )
+ )
+ value_legend = temp[[detail]]
+ }
+ if (detail %in% c("n_catnat", "ppri_year")) {
+ value_legend = round(
+ seq(
+ min(geau::so_ii_onrn[[detail]], na.rm = TRUE),
+ max(geau::so_ii_onrn[[detail]], na.rm = TRUE),
+ length.out = 5
+ )
+ )
+ text_legend = value_legend
+ }
+ if (detail %in% c("balance")) {
+ value_legend = unique(
+ c(
+ seq(min(geau::so_ii_onrn[[detail]]), 0, length.out = 4),
+ seq(0, max(geau::so_ii_onrn[[detail]]), length.out = 4)
+ )
+ )
+ text_legend = formatC(
+ as.integer(signif(round(value_legend), 2)),
+ big.mark = " "
+ )
+ }
+ color_legend = scales::cscale(
+ c(onrn_range, value_legend),
+ onrn_palette,
+ trans = onrn_trans
+ )
+ if (length(onrn_range) > 0) {
+ color_legend = color_legend[-seq(onrn_range)]
+ }
+ title_onrn = switch(
+ EXPR = detail,
+ "n_catnat" = "N arr\u00eat\u00e9s Cat-Nat (ONRN)",
+ "freq_sin" = "Sinistre / Risque [1995-2018]",
+ "cost" = "Co\u00fbt cumul\u00e9 (\u20AC) [1995-2018]",
+ "cost_hab" = "Co\u00fbt / hab (\u20ac) [1995-2018]",
+ "cost_mean" = "Co\u00fbt / sinistre (\u20ac) [1995-2018]",
+ "ratio" = "Co\u00fbt / Prime [1995-2018]",
+ "balance" = "Co\u00fbt - Prime (\u20ac) [1995-2018]",
+ "ppri_year" = "Ann\u00e9e des PPRI",
+ NULL
+ )
+
theme_legend = list(
- title = "CLC (2018)",
- legend = geau::clc_color[["label_fr"]],
+ title = title_onrn,
+ legend = text_legend,
x = "topright",
cex = .8,
bg = "white",
inset = 0.01,
- fill = geau::clc_color[["color"]]
+ fill = color_legend,
+ border = border
)
+ rm(text_legend)
}
if ("population" %in% theme) {
@@ -204,122 +446,6 @@ map_so_ii = function(
)
}
- if ("catnat" %in% theme) {
- if (missing(detail)) {
- detail = dimnames(geau::so_ii_catnat)[["hazard"]]
- }
- detail = match.arg(
- detail,
- dimnames(geau::so_ii_catnat)[["hazard"]],
- several.ok = TRUE
- )
- border = NA
- color = NA
- if (!missing(year)) {
- year = match.arg(
- as.character(year),
- dimnames(geau::so_ii_catnat)[["period"]]
- )
- border = "grey80"
- catnat = apply(
- geau::so_ii_catnat[, year, detail, drop = FALSE],
- 1:2,
- sum
- )
- color = ifelse(
- catnat > 0,
- scales::alpha("grey80", .5),
- NA
- )
- theme_legend = list(
- title = sprintf("Cat-Nat %s", year),
- legend = c("Sans d\u00e9claration", "Avec d\u00e9claration"),
- x = "topright",
- cex = .8,
- bg = "white",
- inset = 0.01,
- fill = unique(color),
- border = border
- )
- }
-
- plot(
- geau::so_ii_collectivity[["geometry"]],
- border = border,
- col = color,
- add = TRUE
- )
- }
-
- if ("hydro" %in% theme) {
- if (missing(detail)) {
- detail = "none"
- }
- detail = match.arg(
- as.character(detail),
- choices = c(
- "none",
- levels(geau::so_ii_hydro[["degre"]]),
- levels(geau::so_ii_hydro[["type"]])
- )
- )
- color = scales::alpha("blue", .3)
- bg = scales::alpha("blue", .3)
- border = NA
- selection = seq(nrow(geau::so_ii_hydro))
- theme_legend = list(
- title = sprintf("R\u00e9seau hydrographique"),
- legend = "\u00e9l\u00e9ment du r\u00e9seau",
- x = "topright",
- cex = .8,
- bg = "white",
- inset = 0.01,
- col = color,
- lwd = 1
- )
- if (detail %in% levels(geau::so_ii_hydro[["type"]])) {
- selection = as.character(geau::so_ii_hydro[["type"]]) == detail
- theme_legend[["legend"]] = detail
- }
- if (detail %in% levels(geau::so_ii_hydro[["degre"]])) {
- selection = as.character(geau::so_ii_hydro[["degre"]]) <= detail
- }
- geometry = geau::so_ii_hydro[["geometry"]][selection]
- lwd = 4 - as.numeric(geau::so_ii_hydro[["degre"]][selection])
-
- plot(geometry, col = color, lwd = lwd, border = border, add = TRUE)
- }
-
- if ("catchment" %in% theme) {
- if (missing(detail)) {
- detail = "1"
- }
- detail = match.arg(
- as.character(detail),
- choices = levels(geau::so_ii_catchment[["degre"]])
- )
- selection = geau::so_ii_catchment[["degre"]] == detail
- geometry = geau::so_ii_catchment[["geometry"]][selection]
- catchment = as.factor(geau::so_ii_catchment[["catchment_name"]][selection])
- color_legend = grDevices::hcl.colors(nlevels(catchment), "Pastel 1", alpha = .3)
- color = color_legend[catchment]
- border = "grey80"
- lwd = 2
- theme_legend = list(
- title = sprintf("Bassin versant"),
- legend = levels(catchment),
- x = "topright",
- cex = .8,
- bg = "white",
- inset = 0.01,
- fill = color_legend,
- border = border
- )
- if (detail == "3") rm(theme_legend)
-
- plot(geometry, border = border, col = color, lwd = lwd, add = TRUE)
- }
-
if (!missing(dataset)) plot(dataset[["geometry"]], add = TRUE, ...)
plot(geau::so_ii_limit, lwd = 2, add = TRUE)
@@ -344,9 +470,9 @@ map_so_ii = function(
do.call(graphics::legend, dataset_legend)
}
- if (legend_theme == TRUE && exists("theme_legend")) {
+ if (legend_theme == TRUE && exists("theme_legend", inherits = FALSE)) {
temp = do.call(graphics::legend, theme_legend)
- if (exists("text_legend")) {
+ if (exists("text_legend", inherits = FALSE)) {
graphics::text(
x = temp[["rect"]][["left"]] + temp[["rect"]][["w"]],
y = temp[["text"]][["y"]],
diff --git a/geau/data-raw/so_ii_onrn.R b/geau/data-raw/so_ii_onrn.R
new file mode 100644
index 0000000..a6118f0
--- /dev/null
+++ b/geau/data-raw/so_ii_onrn.R
@@ -0,0 +1,28 @@
+# code to prepare `so_ii_onrn` dataset goes here
+
+so_ii_onrn = read.csv2(
+ geau::current_version("data-common/so-ii/onrn"),
+ row.names = 1
+)
+class(so_ii_population) = "data.frame"
+rownames(so_ii_population) = so_ii_population[["CODGEO"]]
+selection = grep(
+ "PMUN|PSCDC|PTOT",
+ colnames(so_ii_population),
+ value = TRUE
+)
+so_ii_population = as.matrix(
+ so_ii_population[geau::so_ii_scope, selection]
+)
+year = gsub("PMUN", "20", selection)
+year = gsub("PTOT", "19", year)
+year = gsub("1919", "19", year)
+year = gsub("1918", "18", year)
+dimnames(so_ii_population)[[2]] = year
+
+# updating datasets
+
+# actual = setwd(file.path(system.file(package = "geau"), ".."))
+actual = setwd("geau")
+usethis::use_data(so_ii_population, internal = FALSE, overwrite = TRUE)
+setwd(actual)
diff --git a/geau/data/so_ii_onrn.rda b/geau/data/so_ii_onrn.rda
new file mode 100644
index 0000000000000000000000000000000000000000..5985ecbfe976d7619b844a785b0f048fdb6ff0eb
GIT binary patch
literal 2936
zcmYjMc{tPy7ye~tEW>oiE`8MuW3o@yHg3NrG&A-Ygt!exnJib~mT@t|j5UR_?;2z6
zX30(@`*Kr;EQur`CD|(B%e~L{Jm34r`<`>&bIx-P-qGWv)>#KE#bKgtAr(M=+1*3V
z?&fajPYwO4yUSa9rRBYR58KnC&QnGLNwUq$;Nibc>|c9nz-NZ<E4INTX)B#k4T<mJ
zuB~GklpcAnyL^3K+<gjNsAw(w{*d)Tv~G~i_^mq>J_KA#55#5{E;5CRzZVuU(&<0>
z@O=}|5FFI!{p>UZ4JhV9#j_b!LxVZoNN`^+@DqYehzS!w?1cb;kpEZzwE%=6hG<Bf
z9fp8n{C|yqSoi-}sAz8l!!OV?FJ5%v4i14s;2=O>*vDf&kN@e2F%e>E05FIE5RkL?
zO~O%vOh8^<kd+GvLqLzcMT2|v&jAqde;KeBiZKBUfhDeA81G>&pG{n(^N33%YJ?<u
z{<%<5YdRoL>t2g2PIw1V<m>8sc(gGhi-5Mv@q_EXSV8zh;%xfQkGlm$c>ZFvhILYy
zYSrQRqI=2uN3W1ODjzsd;S?f_;LX+LCm5?dffAKqcmYXTMy7-pEuWwG-YVfKgVQqJ
zly2!S{yv{DnPB+r{K<D~4;&n#F({@u5GKE)%-4N2$P|YPoJ&h(!S9jp_3~xB^G0l9
zl#tQqNG2dY;aGAWmnf-WYijR_>#huUjOr-O-*(i(`ez?A?cm@lH(?0*WaEjzlX9Ck
zw^AheEXHSp?t%WZZ_AQ+y|wX%&0CwFb#IRt%}irpYFe%6s}(3v<nt8~3@0h$p+7~M
z%(B%v&nY4BZ>ba*Gk$?|TiCW6#rbglfPm%R^L7@L%0zE?uZki*O(NDNw-~JyZr(sI
zfT2+1C>C?n@ky5a*uef-Gg>-2enPUEVW&_nrJDb)0Ux7DP?he=div&Slk+8_b!?E1
zrAA1K^{E)GvSSuIiw!HqGuP+pC?Yw_ksM_<$?8iQbRNm<)e~VkGIdt`#)WD6MsG-H
zm1OEId_n*4fulcO#Fl(!V~pomTx5Ahx`eu2YA3>xRVUcN5<dp27TXfe*LxUC-OghZ
zHLi>I(AI_sPSb&>pQq2oCp?~dyz=9+Vtc`nA(FY;YFXq<%M5h5Zq0U`?78LiiGYiN
z)BUdtYOmQmvM7{s+^NHZ$uZ9aM~4F4-2O}&rC9i5qHd)*Y56{>I4;)H1LYUzTia5j
z>JZvOVshhNlG5B<b5gqc<>Ls0R<4@u!~<EP9|r4&Q}>b2R9Akmk(yb2&`$|2V%1>;
zuk7rzdPTsW)sE<WQ<q4%fcs!j7{1eFfxDE`c|FhZ&c%aM)6_Tl3ilP~&Ix5^iGmM^
zBxzwKckkwTvjOww9jOqD-+V&4^s0S9);GxObte(|><r3T<4d^@@<ukkACf={X|~2E
z4JkR49eu@zXyePAy_KjXR?PD8Q7(p?tWCD1T=QOQA?1?sUM?<TL<}5b)$N|_*qGQS
zU2}D&uen|T*&)yxgA^{8k|RJ{bCHoYJ+7ceDou`XMF#`SlqEX4#@j}coWq)eh9yiR
zO!24+v~*NO6jwo64P&oB#7Z-rld|y=j_y(LDxei5N8@OlYS@+~37+Z|cD0xMg;k7*
zX5rMCTpMboF;*9u0|jX8_~!CsH;xRXj1XYG9t3i3uCf9sRZqVw!&d!fq&oABruXS^
z9v!`??H;c&*lBAP=1zeQ7(38)ii2FRaVg=ep7+psu-7;f&nurjzEWD0d!Y@l5q?43
zZj!JMs@RNI^n1FcyN}0`u2caSiy0y;9lyl~G<JG_EwmH~{Wu3L^E?PYnUjV~n8Upt
z>$VqEM2;<}ehr8+c7@-uh(qsKV6q}Keh4>BUY2@6>J)sp-2gC`8VKFml3HI*EH6w?
zkDhM&bWH^bo0T(2YSy3f6FPke@J5l#IrkZuDh2Co0g@Lnpr*c_i=i|XRxaWa4H2Qs
ze&e&`qcy9){=sk-UeemGNqv;(HXL-mk(bRL!l$^%iC-@=gTAVRvIJD$+_IXE7?OZG
zurA86vCoN-`lM(TVw#O~G|-7s_cC*V)-gS7Dov&O3zg_LcvRRSPusZ(R>?k5Xarcr
z>kIgHmreitARj0-GmFh&_gis%iOfVOTL8*Y?LzG{b)*r6nTOnaJ;>wW1Q@$HLyLjW
zmWyD>Y;3Pzd;aTUmY$KlI9NxIzT3wd{C*HCX~EYCJbloqbe%RlIhDRYy4k?BYF()4
zc}68T;zbSakKQ)ujCcWxi!dbs7m{L$@2}<a;)et+FLXJ3Z(<Q+*Y8z<_;&TH*hP+N
zl~%@dwZ^gt_r_F&{<PRPYeFs$|HXy^Pbqjrj#cyq2Yyg73URuoG-2{QLB)?`6mwgM
z)SI7M3UxUdd2luKH`%GStx4&(TF=MZzif}B0HWS*O4g~-dN{k3h~2`<zeS`*#a|H6
zTv!t1tMxv0%_F%)DO}?=7*;|YquR**dF2XYOKXMn`)Uicg!KM)BzbqWu{+=L#;mXY
z>2vN?PAdogj?VYXoIIkZca--OxR`lIU@CL+VOhM8J?DpvY*(F&#yYA75Ft^v<=_Qn
z3mxr@j7FS8-Y3B)Tf)RbL{U^nLaecrLadadYO;Eb7D3>cANh1#vfkv;<FW6$^4@n3
zi3WB?jMdgec^w+btGJpT)}x}N^zz}?4_KgokOGaFnvhZGJ78;7k}IPghfs!#!l`gp
zg@S}cUoy1|zu;#hcG0}1am@9S&Ld=%-Lvs$OeY&^wlRBc6WUkey1<;bYW1LN<vmi}
z32i3Qaq}M{?jm1E{5^vdvMw22xxk_Gw49#al{pvjB_K5s-!l@{UYgJqHZB9>Gtb0;
zaz$9CX;C65^8)D83$FhSDR6;f6`%aJN8|ms!pyD~4-QpBx#H1086d^p{A;HVff5lt
z;PS>C8kVsb&_+FHu7M{W#KDv-gUws*m=eS9eNk{<{ef4RA3L`}*t4w6kCo{RW(Cx~
z1b&uKDlTny{5XJcT;7_cHND-)5593J`|@TeX5;f0v)f}3q^;Q*AJ_&662z#tTusm`
zt78w{WRq%#?G_3RMcF4zaZ^*1QSB3qXBV-KKfop8hKVRlPB|=0ORhrVcz%G`sV@Q&
z@;uP;SoL;oGkk;LYlp|LSLjS7W7~Y5nIE1~mh_!lYY1t3L6%-WQkNJU`XpTG_jm3A
zJrY>YthtakDA~>gW`C+Arp+uuQtYs{RF+OV+Gm}A?*;^WAiePTHPgtl*z!*~feh2m
z6|_YMWd9L|Sng7bXZ?XzfyXy4$Y-r}87I!XWB<oOn+RRbnQc_mWNMVEZs-*O*Gu(+
zm;A~-Ts~eoadlEGd0k_~JhNyh>dfRSIxT`Y5&_iaoN1}<ny|+3P^P2f)Uml-!Ulb5
zX7z{7A<bGZ(w`NJP6ge;nyxQRz{uu5+*gzQgEv#x7)z1qh_$CFIvGD&rfvjOe!W`p
z@OowA9aE(^Nw-J?DC)LbP<ZI_u&d>n(8lC<gKC#r)Y#b{T8JpN)7*&_%t{}Rw9-(2
zYE!!FT*LFnhdHu=JX(l>Y|)=RZWAgy!LpW-C1>uV6)bFDXTNo6p1d-fr_iUSfxX_y
z2T12(-QPt%cdIS?hr-f=%scG7=u>p6{<=y3Q=)Dx&f5cDvAzE+U~K459(Ut~?t|@)
z5o<#H?5dyp+gqvYyC!jhpf#NW3RbN*ds5BAse>z@wic@&p2e`{DA9^ab1gB6LbWTq
z=E0gz*GVC)om0A%_L{jSZ+Bv5x20o9YITQ82gpPy-_y|~=yd5E;3SynB-Sd67ucQo
OL@0zy9K7kQ1N;|l^gf9I
literal 0
HcmV?d00001
diff --git a/geau/man/map_so_ii.Rd b/geau/man/map_so_ii.Rd
index 63263ef..592e5ef 100644
--- a/geau/man/map_so_ii.Rd
+++ b/geau/man/map_so_ii.Rd
@@ -8,7 +8,7 @@
map_so_ii(
dataset,
dataset_legend = NULL,
- theme = c("none", "collectivity", "catchment", "catnat", "clc", "hydro",
+ theme = c("none", "collectivity", "catchment", "catnat", "clc", "hydro", "onrn",
"population"),
bar = TRUE,
path = NULL,
@@ -59,6 +59,8 @@ and only the boundaries of collectivities are plotted.}
levels of detail or "canal", "river", "waterbody" for types of
hydrographic elements. If missing, "none" will be chosen, and
everything is plotted.}
+\item{\strong{onrn}: detail must be chosen in "n_catnat", "freq_sin",
+"cost", "cost_hab", "cost_mean", "ratio", "balance", "ppri_year".}
}
}
\subsection{year specification}{
diff --git a/geau/man/so_ii_clc.Rd b/geau/man/so_ii_clc.Rd
index 0d62e5c..2f08e4b 100644
--- a/geau/man/so_ii_clc.Rd
+++ b/geau/man/so_ii_clc.Rd
@@ -5,12 +5,16 @@
\alias{so_ii_clc}
\title{CLC information for so-ii}
\format{
-sf object
+sf data.frame 1337 rows, 2 variables
+\describe{
+\item{clc_2018}{character, classification from CLC 2018}
+\item{color}{character, default color to be used to plot so_ii_clc}
+}
}
\usage{
so_ii_clc
}
\description{
-A dataset containing the 2018 version of CLC information for so-ii
+A dataset containing the Corine Land Cover information on so-ii.
}
\keyword{datasets}
diff --git a/geau/man/so_ii_limit.Rd b/geau/man/so_ii_limit.Rd
index c54cc95..64c439b 100644
--- a/geau/man/so_ii_limit.Rd
+++ b/geau/man/so_ii_limit.Rd
@@ -6,22 +6,12 @@
\title{Spatial perimeter of so-ii}
\format{
sfc_POLYGON of length 1
-
-sf data.frame 1337 rows, 2 variables
-\describe{
-\item{clc_2018}{character, classification from CLC 2018}
-\item{color}{character, default color to be used to plot so_ii_clc}
-}
}
\usage{
-so_ii_limit
-
so_ii_limit
}
\description{
A dataset containing the perimeter of so-ii.
-
-A dataset containing the Corine Land Cover information on so-ii.
}
\details{
Basically, this dataset is obtained as
diff --git a/geau/man/so_ii_onrn.Rd b/geau/man/so_ii_onrn.Rd
new file mode 100644
index 0000000..0991fd9
--- /dev/null
+++ b/geau/man/so_ii_onrn.Rd
@@ -0,0 +1,50 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data.r
+\docType{data}
+\name{so_ii_onrn}
+\alias{so_ii_onrn}
+\title{ONRN information for so-ii}
+\format{
+data.frame 78 rows, 23 variables
+\describe{
+\item{n_catnat}{Number of Cat Nat events}
+\item{freq_sin}{Number of claims divided by number of contracts
+for 1995 to 2018. freq_sin is calculated as the mean of freq_sin_min
+and freq_sin_max (range for each category).}
+\item{cost}{Cumulative cost of claims for 1995 to 2018. Cost is calculated
+as the mean of cost_min and cost_max (range for each category).}
+\item{cost_mean}{Mean cost of claims (cost divided by claims) for 1995 to
+2018. cost_mean is calculated as the mean of cost_mean_min and
+cost_mean_max (range for each category).}
+\item{cost_hab}{Cost divided by the population for 1995 to 2018. cost_hab
+is calculated as the mean of cost_hab_min and cost_hab_max (range for
+each category).}
+\item{ratio}{Cost divided by premium for 1995 to 2018. ratio is calculated
+as the mean of cost_hab_min and cost_hab_max (range for each
+category).}
+\item{balance}{Cost minus premium for 1995 to 2018. This is an estimation
+made by so-ii team by considering a mean premium for each habitant
+of 24.92829 euro per habitant (total premium in 2018 divided by
+total population)}
+\item{ppri_year}{Year given for the last PPRI.}
+\item{ppri_state}{State of the last PPRI.}
+\item{ppri_state_sub}{Some details on the state of the last PPRI.}
+\item{ppri_state_age}{State of the last PPRI for age information.}
+\item{ppri_age_min}{Lower boundary for the age of the PPRI.}
+\item{ppri_age_min}{Upper boundary for the age of the PPRI..}
+}
+}
+\source{
+\url{https://www.georisques.gouv.fr/articles-risques/acceder-aux-indicateurs-sinistralite}
+}
+\usage{
+so_ii_onrn
+}
+\description{
+A dataset containing part of the information available at the ONRN for so-ii
+communities. The information chosen is exclusively related to floods. It is
+mainly related to impacts and therefore to the claims in from the Cat-Nat
+system. These data on claims are taken from the CCR, the others from the
+gaspar database.
+}
+\keyword{datasets}
--
GitLab