# link and zone shapefiles converted to R objects
processLinks <- FALSE
processZones <- TRUE
library(maptools)
library(readr)
library(rgdal)
library(dplyr)
library(ggplot2)
options(stringsAsFactors = FALSE)
ogic <- CRS("+proj=lcc +lat_1=43 +lat_2=45.5 +lat_0=41.75 +lon_0=-120.5 +x_0=399999.9999999999 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=ft +no_defs")
wgs84 <- CRS("+proj=longlat +datum=WGS84 +no_defs")
if(processLinks) {
# links
links_shp <- readShapeLines(
"data-raw/links_link.shp",
proj4string = ogic
) %>%
spTransform(., wgs84)
links_data <- links_shp@data %>%
tbl_df() %>%
mutate(
id = as.character(row_number() - 1),
# there's a really annoying feature of R that reads in data as factors. But
# even more annoying is the fact that the length fields in visum are written
# as 0.159mi, which means that the numeric field gets read in as a factor.
LENGTH = as.character(levels(LENGTH)[LENGTH])
) %>%
mutate(
LENGTH = as.numeric(gsub("[^0-9$.]", "", LENGTH))
)
links <- fortify(links_shp) %>%
left_join(links_data, by = "id") %>%
filter(!(TSYSSET %in% c("m", "n"))) %>%
tbl_df()
devtools::use_data(links)
}
if(processZones) {
# zones
zones_shp <- readShapePoly(
"data-raw/zones_zone.shp",
proj4string = ogic
) %>%
spTransform(., wgs84)
regions <- read_csv("data-raw/regions.csv")
zones_shp@data <- zones_shp@data %>%
left_join(regions) %>%
transmute(
NO,
id = as.character(row_number() - 1),
AZONE = as.numeric(as.character(NO)),
BZONE,
COUNTY = as.character(COUNTY),
ALDREGION = as.character(ALDREGION),
MPO = as.character(MPO),
DOT_REGION,
STATE = as.character(STATE)
)
zones <- fortify(zones_shp) %>% tbl_df() %>%
left_join(zones_shp@data, by = "id")
zones_data <- zones_shp@data
devtools::use_data(zones, overwrite = TRUE)
devtools::use_data(zones_data, overwrite = TRUE)
devtools::use_data(zones_shp, overwrite = TRUE)
}
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