Here is some updated R code from my previous post. It doesn’t throw any warnings when importing tracks with and without heart rate information. Also, it is easier to distinguish types of tracks now (e.g., when you want to plot runs and rides separately). Another thing I changed: You get very basic information on the track when you click on it (currently the name of the track and the total length).

Have fun and leave a comment if you have any questions.



options(stringsAsFactors = F)

rm(list=ls())

library(httr)
library(rjson)
library(leaflet)
library(dplyr)

token <- "“

# Functions —————————————————————

get.coord.df.from.stream <- function (stream.obj) {
  data.frame(lat = sapply(stream.obj[[1]]$data, USE.NAMES = F, FUN = function (x) x[[1]]),
             lon = sapply(stream.obj[[1]]$data, USE.NAMES = F, FUN = function (x) x[[2]]))
}

get.stream.from.activity <- function (act.id, token) {
  stream <- GET("https://www.strava.com/",
                path = paste0(“api/v3/activities/”, act.id, “/streams/latlng”),
                query = list(access_token = token))
  content(stream)
}

get.activities2 <- function (token) {
  activities <- GET("https://www.strava.com/", path = "api/v3/activities",
                    query = list(access_token = token, per_page = 200))
  activities <- content(activities, "text")
  activities <- fromJSON(activities)
  res.df <- data.frame()
  for (a in activities) {
    values <- sapply(c("name", "distance", "moving_time", "elapsed_time", "total_elevation_gain",
                       “type”, “id”, “start_date_local”,
                       “location_country”, “average_speed”, “max_speed”, “has_heartrate”, “elev_high”,
                       “elev_low”, “average_heartrate”, “max_heartrate”), FUN = function (x) {
                         if (is.null(a[[x]])) {
                           NA } else { a[[x]] }
                       })
    res.df <- rbind(res.df, values)
  }
  names(res.df) <- c("name", "distance", "moving_time", "elapsed_time", "total_elevation_gain",
                     “type”, “id”, “start_date_local”,
                     “location_country”, “average_speed”, “max_speed”, “has_heartrate”, “elev_high”,
                     “elev_low”, “average_heartrate”, “max_heartrate”)
  res.df
}

get.multiple.streams <- function (act.ids, token) {
  res.list <- list()
  for (act.id.i in 1:length(act.ids)) {
    if (act.id.i %% 5 == 0) cat(“Actitivy no.”, act.id.i, “of”, length(act.ids), “\n”)
    stream <- get.stream.from.activity(act.ids[act.id.i], token)
    coord.df <- get.coord.df.from.stream(stream)
    res.list[[length(res.list) + 1]] <- list(act.id = act.ids[act.id.i],
                                             coords = coord.df)
  }
  res.list
}

activities <- get.activities2(token)

stream.list <- get.multiple.streams(activities$id, token)

# Leaflet —————————————————————–

lons.range <- c(9.156572, 9.237580)
lats.range <- c(48.74085, 48.82079)

map <- leaflet() %>%
  addProviderTiles(“OpenMapSurfer.Grayscale”, # nice: CartoDB.Positron, OpenMapSurfer.Grayscale, CartoDB.DarkMatterNoLabels
                   options = providerTileOptions(noWrap = T)) %>%
  fitBounds(lng1 = min(lons.range), lat1 = max(lats.range), lng2 <- max(lons.range), lat2 = min(lats.range))

add.run <- function (act.id, color, act.name, act.dist, strlist = stream.list) {
  act.ind <- sapply(stream.list, USE.NAMES = F, FUN = function (x) {
    x$act.id == act.id
  })
  act.from.list <- strlist[act.ind][[1]]
  map <<- addPolylines(map, lng = act.from.list$coords$lon,
               lat = act.from.list$coords$lat,
               color = color, opacity = 1/3, weight = 2,
               popup = paste0(act.name, “, “, round(as.numeric(act.dist) / 1000, 2), ” km”))
}

# plot all
for (i in 1:nrow(activities)) {
  add.run(activities[i, “id”], ifelse(activities[i, “type”] == “Run”, “red”,
                                      ifelse(activities[i, “type”] == “Ride”, “blue”, “black”)),
          activities[i, “name”], activities[i, “distance”])
}

map