In JohannesFriedrich/senseBox: senseBox API Wrapper

knitr::opts_chunk$set(echo = FALSE, 
                      fig.align = "center")
library(sp)
library(rworldmap)
library(senseBox)
library(tidyverse)

theme_update(axis.text = element_text(size = 14),
         axis.title = element_text(size = 14, face = "bold"),
         legend.text = element_text(size = 12),
         legend.title = element_text(size = 12, face = "bold"))

# The single argument to this function, points, is a data.frame in which:
#   - column 1 contains the longitude in degrees
#   - column 2 contains the latitude in degrees

countriesSP <- getMap(resolution='high')

coords2country = function(points){

  #countriesSP <- getMap(resolution='high') #you could use high res map from rworldxtra if you were concerned about detail

  # convert our list of points to a SpatialPoints object

  # pointsSP = SpatialPoints(points, proj4string=CRS(" +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0"))

  #setting CRS directly to that from rworldmap
  pointsSP <- SpatialPoints(points, proj4string=CRS(proj4string(countriesSP)))


  # use 'over' to get indices of the Polygons object containing each point
  indices <- over(pointsSP, countriesSP)

  # return the ADMIN names of each country
  return(data.frame(
    country = indices$ADMIN  ,
    continent = indices$REGION))
  #indices$ISO3 # returns the ISO3 code
  #indices$continent   # returns the continent (6 continent model)
  #indices$REGION   # returns the continent (7 continent model)
}

Ids <- get_senseBox_Ids()

infos <- get_senseBox_info(Ids$senseBoxId, parallel = TRUE)

sensor_info <- get_senseBox_sensor_info(Ids$senseBoxId, parallel = TRUE)
locations <- get_senseBox_location(Ids$senseBoxId, parallel = TRUE)

country <- coords2country(locations[,2:3])

locations <- bind_cols(infos[,1:2, ], country) %>% 
  rename("senseBoxId" = "X_id")

DT::datatable(locations, escape = F,
              rownames = FALSE,
              options = list(
                autoWidth = TRUE,
                pageLength = 50))

library(gganimate)
library(ggmap)
library(lubridate)

complete <- bind_cols(infos, country) %>% 
  rename("senseBoxId" = "X_id")

map <- get_map(location = "Germany",source = "osm",
               zoom = 6)

complete %<>% 
  mutate(
    day = day(createdAt),
    year = year(createdAt),
    time = strftime(createdAt, format = "%Y.%m.%d")
  ) %>% 
  filter(country == "Germany")

 p <- ggmap(map) +
  geom_point(data = complete, 
             mapping = aes(x = long, 
                           y = lat, 
                           colour = exposure,
                           frame = time,
                           cumulative = TRUE),
             alpha = 0.5,
             size = 3) +
  guides(colour = guide_legend(override.aes = list(alpha = 1))) + 
  geom_text(aes(x = 4, 
                y = 55, 
                frame = time, 
                label = paste0(time), 
                hjust = "left"), 
            size = 10,
            data = complete)

library(animation)
ani.options(ani.width = 400, ani.height = 300)

gganimate(p = p, 
          filename = "Germany_2018_SenseBox_small.gif",
          saver = "gif",
          interval = 0.1, 
          title_frame = FALSE)