In hrbrmstr/deere: Catchall Functions for All Things 'John Deere'

knitr::opts_chunk$set(collapse=TRUE, fig.retina=2, message=FALSE, warning=FALSE)
options(width=120)

deere

Catchall Functions for All Things 'John Deere'

Description

Initially a convenience package to access 'John Deere' 'MowerPlus' databases from 'iOS' backups but perpaps will be something more all-encompassing.

Ref:

• https://rud.is/b/2019/06/02/trawling-through-ios-backups-for-treasure-a-k-a-how-to-fish-for-target-files-in-ios-backups-with-r/
• https://rud.is/b/2019/06/09/wrapping-up-exploration-of-john-deeres-mowerplus-database/

What's Inside The Tin

The following functions are implemented:

• from_coredata_ts: Convert timestampes from Apple "CoreData" format to something usable
• list_ios_backups: List iOS backups available on this system
• platform_ios_backup_dir: List iOS backups available on this system
• src_mowerplus: Find and sync a copy of the latest MowerPlus database file from an iOS backup

Installation

devtools::install_git("https://git.sr.ht/~hrbrmstr/deere.git")
# or
devtools::install_git("https://git.rud.is/hrbrmstr/deere.git")
# or
devtools::install_gitlab("hrbrmstr/deere")
# or
devtools::install_bitbucket("hrbrmstr/deere")
# or
devtools::install_github("hrbrmstr/deere")

Usage

library(deere)
library(hrbrthemes)
library(tidyverse)

# current version
packageVersion("deere")

Sample from the latest mow

list_ios_backups()

mow_db <- src_mowerplus()

mow_db

glimpse(tbl(mow_db, "ZMOWER"))

glimpse(tbl(mow_db, "ZACTIVITY"))

tbl(mow_db, "ZACTIVITY")%>%
  collect() -> activity

activity %>% 
  select(
    mow_date = ZCREATEDAT, 
    area_covered = ZAREACOVERED, 
    avg_speed = ZAVERAGESPEED, 
    distance = ZDISTANCEMOWED, 
    duration = ZMOWINGTIME
  ) %>% 
  arrange(mow_date) %>% 
  mutate(
    duration = duration / 60 / 60, # hours
    mow_date = format(from_coredata_ts(mow_date), "%b %d"), # factors make better bars
    mow_date = factor(mow_date, levels = unique(mow_date)) # when there are just 2-of-em
  ) %>% 
  gather(measure, value, -mow_date) %>% 
  ggplot(aes(mow_date, value)) +
  geom_col(aes(fill = measure), width = 0.5, show.legend = FALSE) +
  scale_y_comma() +
  scale_fill_ipsum() +
  facet_wrap(~measure, scales = "free") +
  theme_ipsum_rc(grid="Y")

zloc <- tbl(mow_db, "ZMOWLOCATION")


zloc %>% 
  select(
    id = ZSESSION,
    zorder = ZORDER,
    lat = ZLATITUDE,
    lng = ZLONGITUDE,
    speed = ZSPEED,
    ts = ZTIMESTAMP
  ) %>% 
  collect() %>% 
  mutate(
    id = factor(id),
    ts = from_coredata_ts(ts)
  ) -> sessions

ggplot(sessions, aes(id, speed)) +
  ggbeeswarm::geom_quasirandom(
    aes(fill = id), show.legend = FALSE,
    shape = 21, size = 2, color = "white", stroke = 0.75
  ) +
  scale_fill_ipsum() +
  labs(x = "Mowing Session", y = "MPH", title = "Mowing Speed Comparison (mph)") +
  theme_ipsum_rc(grid="Y")

arrange(sessions, ts) %>% 
  ggplot(aes(lng, lat)) +
  geom_path(
    aes(color = id, group = id), show.legend = FALSE,
    size = 1, alpha = 1/2
  ) +
  scale_color_ipsum() +
  coord_quickmap() +
  facet_wrap(~id) +
  labs(title = "Mowing Path Comparison") +
  theme_ipsum_rc(grid="Y") +
  ggthemes::theme_map()

deere Metrics

cloc::cloc_pkg_md()

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.

hrbrmstr/deere documentation built on June 20, 2019, 2:21 p.m.