2024-11-21 11:32:27 -06:00
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---
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title: "Wisconsin Cycling to School"
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output:
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html_document:
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toc: true
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toc_depth: 5
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toc_float:
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collapsed: false
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smooth_scroll: true
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editor_options:
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chunk_output_type: console
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---
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# Input Data & Configuration
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## Libraries
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```{r libs, eval = TRUE, echo = FALSE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
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date()
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rm(list=ls())
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library(tidyverse)
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library(ggmap)
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library(sf)
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library(osrm)
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library(smoothr)
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library(magick)
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library(ggnewscale)
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library(rsvg)
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library(httr)
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library(jsonlite)
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library(parallel)
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fig.height <- 6
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set.seed(1)
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source("./R/functions.R")
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runLoop <- FALSE
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```
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2024-11-21 11:32:27 -06:00
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## Configuration
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```{r config, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
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options(osrm.server = "http://127.0.0.1:5001/")
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options(osrm.profile = "bike")
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brouter_url <- "http://127.0.0.1:17777/brouter"
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brouter_profile <- "safety"
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register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36))
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WI_schools <- st_transform(st_read(dsn = "data/Schools/Wisconsin_Public_Schools_-5986231931870160084.gpkg"), crs = 4326)
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WI_schools <- WI_schools %>% mutate(geom = SHAPE)
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```
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## Subset Schools
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```{r subsetSchools, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
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WI_schools <- subset(WI_schools, !is.na(LAT) & !is.na(LON) & GRADE_RANGE == "09-12")
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```
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Non-virtual, grades 9-12.
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## Loop through WI Schools
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```{r mainloop, eval = runLoop, echo = FALSE, results = "show", warning = FALSE, error = TRUE, message = TRUE}
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radius <- 3 # miles
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levels <- c(1)
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res <- 100
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threshold <- units::set_units(1, km^2)
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gridList <- list()
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routesList <- list()
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indexVec <- 1:nrow(WI_schools)
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jj <- 1;
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bad.school.vec <- c()
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for(j in indexVec){
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school_location <- WI_schools[j,]
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cycle_boundary_m <- radius*1609
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cycle_boundary_poly <- osrmIsodistance( loc = school_location, breaks = cycle_boundary_m, res = res )
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cycle_boundary_poly <- st_make_valid(cycle_boundary_poly)
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cycle_boundary_poly <- fill_holes(cycle_boundary_poly, threshold)
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cycle_boundary_poly <- st_transform(cycle_boundary_poly, crs = 4326)
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cellsize <- 1e-2
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grid <- st_make_grid(cycle_boundary_poly, cellsize = cellsize, what = "polygons", square = FALSE)
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grid <- st_intersection(cycle_boundary_poly, grid)
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grid <- st_make_valid(grid)
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grid_pts <- st_centroid(grid)
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grid_coods <- st_coordinates(grid_pts)
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school_focus_location <- school_location %>% select(LAT, LON)
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routes <- list(NULL)
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for(i in 1:nrow(grid_coods) ) {
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query <- paste0(
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brouter_url,
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"?lonlats=", grid_coods[i,1], ",",grid_coods[i,2], "|",
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school_focus_location$LON, ",", school_focus_location$LAT,
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"&profile=", brouter_profile,
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"&alternativeidx=0&format=geojson"
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)
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response <- GET(query)
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if( response$status_code == "200" ){
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route_run <- st_read(content <- content(response, as = "text"), quiet = TRUE)
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routes[[i]] <- route_run
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}else{
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routes[[i]] <- NA
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}
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}
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bad.cell <- which(is.na(routes))
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if(length(bad.cell) > 0){
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routes <- routes[-bad.cell]
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grid <- grid[-bad.cell,]
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}
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if(length(routes) > 0){
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routes <- st_transform(bind_rows(routes), crs = 4326)
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gridList[[jj]] <- grid
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routesList[[jj]] <- routes
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jj <- jj + 1
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}else{
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routes <- NA
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bad.school.vec <- c(j, bad.school.vec)
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cat( WI_schools$SCHOOL[j], "has zero routes to school and has been removed from analysis.\n")
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}
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}
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2024-11-21 15:13:37 -06:00
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if(length(bad.school.vec) > 0){
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WI_schools <- WI_schools[-bad.school.vec,]
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}
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saveRDS(WI_schools, "./R/data/WI_schools.rds")
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saveRDS(gridList, "./R/data/gridList.rds")
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saveRDS(routesList, "./R/data/routesList.rds")
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```
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2024-11-21 17:10:46 -06:00
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## Read List Data
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```{r readLists, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
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routesList <- readRDS(file = "./R/data/routesList.rds")
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gridList <- readRDS(file = "./R/data/gridList.rds")
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WI_schools <- readRDS(file = "./R/data/WI_schools.rds")
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not.cycleway.vec <- c()
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for(j in 1:length(gridList)){
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grid <- gridList[[j]]
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routes <- routesList[[j]]
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total.time.vec <- routes %>% pull(total.time)
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grid <- cbind(grid, total.time = as.numeric(total.time.vec))
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x.vec <- c()
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for( i in 1:nrow(grid) ){
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route <- routes[i,"messages"] # Grid cell i to school j
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x <- routeChar(route)
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x.vec <- c(x.vec, x)
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}
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grid <- cbind(grid, T.cycleway = x.vec)
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grid <- cbind( grid, not.cycleway = (grid$total.time - grid$T.cycleway)/60)
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gridList[[j]] <- grid
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not.cycleway.vec <- c(not.cycleway.vec, median(grid$not.cycleway))
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}
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```
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## Plot List Data
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### Best & Worst Schools
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```{r plots, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
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ggplot(data.frame(not.cycleway = not.cycleway.vec), aes(not.cycleway)) + geom_histogram(fill = "grey", color = "black") + theme_bw()
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register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36))
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zoom.level <- 15
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k <- 306 #247
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bbox <- st_bbox(st_buffer(gridList[[k]], dist = 500))
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bbox <- c(left = as.double(bbox[1]),
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bottom = as.double(bbox[2]),
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right = as.double(bbox[3]),
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top = as.double(bbox[4]))
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basemap <- get_stadiamap(bbox = bbox, zoom = zoom.level, maptype = "stamen_toner_lite")
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ggmap(basemap) + geom_sf(data = gridList[[k]], aes(fill= not.cycleway), inherit.aes = FALSE) + scale_fill_gradient(low = "yellow", high = "red", limits = c(0,17), na.value = NA)
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k <- 247 #306
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bbox <- st_bbox(st_buffer(gridList[[k]], dist = 500))
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bbox <- c(left = as.double(bbox[1]),
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bottom = as.double(bbox[2]),
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right = as.double(bbox[3]),
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top = as.double(bbox[4]))
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basemap <- get_stadiamap(bbox = bbox, zoom = zoom.level, maptype = "stamen_toner_lite")
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ggmap(basemap) + geom_sf(data = gridList[[k]], aes(fill= not.cycleway), inherit.aes = FALSE) + scale_fill_gradient(low = "yellow", high = "red", limits = c(0,17), na.value = NA)
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```
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### Statewide Map
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```{r plots2, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
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D <- cbind(WI_schools, not.cycleway.vec)
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zoom.level <- 8
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bbox <- st_bbox(st_buffer(D, dist = 10e3))
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bbox <- c(left = as.double(bbox[1]),
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bottom = as.double(bbox[2]),
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right = as.double(bbox[3]),
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top = as.double(bbox[4]))
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basemap <- get_stadiamap(bbox = bbox, zoom = zoom.level, maptype = "stamen_toner_lite")
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ggmap(basemap) + geom_sf(data = D, aes(size = 2, color = not.cycleway.vec), inherit.aes = FALSE) + scale_color_gradient(low = "yellow", high = "red", na.value = NA) # , limits = c(0,17)
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2024-11-21 14:48:22 -06:00
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```
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# Archive
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```{r chunklast, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
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date()
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sessionInfo()
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```
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