Added descriptive text to WI-schools-cycle.Rmd

This commit is contained in:
syounkin 2024-11-22 11:08:43 -06:00
parent 15656c9ca0
commit d0eecdc2c5
2 changed files with 55 additions and 22 deletions

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@ -2,7 +2,8 @@ all: data containers cycle
data: osrm-data brouter-data
containers: osrm-container brouter-container
cycle: WI-schools-cycle
WI-cycle: WI-schools-cycle
cycle: cycle_brouter
walk: route_analysis.Rmd
R -e 'library("rmarkdown"); old_path <- Sys.getenv("PATH"); Sys.setenv(PATH = paste(old_path, "/usr/local/bin", sep = ":")); rmarkdown::render(knit_root_dir = "./", output_dir = "./html", input = "./route_analysis.Rmd", output_file = "./html/route_analysis.html")'

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@ -11,24 +11,20 @@ editor_options:
chunk_output_type: console
---
```{r preCode, eval = TRUE, echo = FALSE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
date()
```
# Input Data & Configuration
## Libraries
```{r libs, eval = TRUE, echo = FALSE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
date()
rm(list=ls())
library(tidyverse)
library(ggmap)
library(sf)
library(osrm)
## library(smoothr)
## library(magick)
## library(ggnewscale)
## library(rsvg)
## library(httr)
## library(jsonlite)
## library(parallel)
library(reactable)
fig.height <- 6
set.seed(1)
@ -38,6 +34,8 @@ runLoop <- FALSE
## Configuration
Set configuration parameters for OSRM, brouter, and stadiamaps.
```{r config, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
options(osrm.server = "http://127.0.0.1:5001/")
options(osrm.profile = "bike")
@ -48,16 +46,32 @@ WI_schools <- st_transform(st_read(dsn = "data/Schools/Wisconsin_Public_Schools_
WI_schools <- WI_schools %>% mutate(geom = SHAPE)
```
# Analysis
We focus on the statistic *non-cycleway duration* in this analysis. It
is computed as the duration (in minutes) of the bike trip to school
(brouter, safety) for each grid cell in the school's bikeable
area. A bikeable area is defined as the region within 3 miles of
school by bike (OSRM).
## Subset Schools
```{r subsetSchools, eval = TRUE, echo = TRUE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
WI_schools <- subset(WI_schools, !is.na(LAT) & !is.na(LON) & GRADE_RANGE == "09-12")
```
Non-virtual, grades 9-12.
We keep only schools with coordinates (non-virtual) and, for
simplicity and efficiency of the initial analysis, we keep only
schools with grades 9-12.
## Loop through WI Schools
For each school we compute the grid and the routes sf objects and save
them as lists as R data files, _gridList.rds_ and
_routesList.rds_. These will then be analyzed downstream and this loop
need not be run again. It took around 40 minutes to run. The code here
is suppressed because it is long and ugly.
```{r mainloop, eval = runLoop, echo = FALSE, results = "show", warning = FALSE, error = TRUE, message = TRUE}
radius <- 3 # miles
levels <- c(1)
@ -176,18 +190,31 @@ for(j in 1:length(gridList)){
## Plot List Data
### Shortest and Longest Median Non-Cycleway Duration
### Median Non-Cycleway Duration
First we take a look at the schools with the shortest and longest
median time on cycleway.
#### Histogram
First we investigate the distribution of median non-cycleway duration
across school. Recall that we are considering now only schools grade
9-12.
```{r hist, eval = TRUE, echo = FALSE, results = "show", warning = FALSE, error = TRUE, message = FALSE}
ggplot(data.frame(not.cycleway = not.cycleway.vec), aes(not.cycleway)) + geom_histogram(fill = "orange", color = "black") + theme_bw()
```
Next, we take a look at the schools with the shortest and longest
median time on cycleway. Note that the analysis is peformed across a
gridded area and not with respect to where students live. The median
non-cycleway duration is computed across grid cells, not students.
Note too that this statistics was computed by parsing the *messages*
field of the route returned by brouter. I am not sure if there is a
better way to do this. Within the messages field there is information
on highway type, surface, etc for each segment of the route.
#### Longest
```{r worst, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
ggplot(data.frame(not.cycleway = not.cycleway.vec), aes(not.cycleway)) + geom_histogram(fill = "grey", color = "black") + theme_bw()
```{r worst, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = FALSE}
register_stadiamaps(key = substr(read_file(file = "api_keys/stadia_api_key"), 1, 36))
k <- 306
zoom.level <- 15
@ -207,7 +234,7 @@ The longest is `r WI_schools[k,] |> pull(SCHOOL)`.
#### Shortest
```{r best, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
```{r best, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = FALSE}
k <- 247
bbox <- st_bbox(st_buffer(gridList[[k]], dist = 500))
@ -224,7 +251,7 @@ The shortest is `r WI_schools[k,] |> pull(SCHOOL)`.
### Statewide Map
```{r plots2, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
```{r plots2, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = FALSE}
D <- cbind(WI_schools, not.cycleway.vec)
@ -243,16 +270,21 @@ ggmap(basemap) + geom_sf(data = D, aes(size = 2, color = not.cycleway.vec), inhe
### Statewide Table
The values shown above can be seen below in this clickable table.
```{r table, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
D_table <- as.data.frame(cbind(WI_schools, not.cycleway.vec))
D <- select(D_table, SCHOOL, COUNTY, NONCYCLEWAY = not.cycleway.vec)
D <- D |> mutate(NONCYCLEWAY = round(NONCYCLEWAY,1))
reactable(D)
```
```{r date, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
date()
```
# Archive
```{r chunklast, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
date()
## Session Info
```{r sessionInfo, eval = TRUE, echo = FALSE, results = "show", warning = TRUE, error = TRUE, message = TRUE}
sessionInfo()
```