R/fitfile combining.r

In martinpastoors/mptools:

# ====================================================================================
# FITfileR codes to read fit files and add to database
# 
# To do: deal with breaks in between; calculate time between recordings; 
# ====================================================================================

library(FITfileR)    # remotes::install_github("grimbough/FITfileR")
library(tidyverse)
# library(leaflet)
# library(tidygeocoder)
library(RJSONIO)     #install.packages("RJSONIO")
# library(OpenStreetMap)
library(osmdata)
# library(rJava)

options(dplyr.summarise.inform = FALSE)

source("r/my utils.r")

# set path
my.filepath <- file.path(get_dropbox(),"Hardloop")

# load data frames
# rec        <- loadRData(file=file.path(my.filepath, "rdata", "rec.RData"))
# session    <- loadRData(file=file.path(my.filepath, "rdata", "session.RData"))
# lap        <- loadRData(file=file.path(my.filepath, "rdata", "laps.RData"))

# rec_gm     <- loadRData(file=file.path(my.filepath, "rdata", "rec_gm.RData"))
# session_gm <- loadRData(file=file.path(my.filepath, "rdata", "session_gm.RData"))
# lap_gm     <- loadRData(file=file.path(my.filepath, "rdata", "laps_gm.RData"))

# session %>% filter(id %in% session_gm$id) %>% View()
# session_gm %>% filter(id %in% session$id) %>% View()

# CONTINUE HERE 14/10/2022
# session_comb <- 
#   bind_rows(loadRData(file=file.path(my.filepath, "rdata", "session_sp.RData")) ) %>% 
#   bind_rows(loadRData(file=file.path(my.filepath, "rdata", "session_tt.RData")) ) %>% 
#   bind_rows(session ) %>% 
#   bind_rows(session_gm %>% filter(!id %in% session$id))  

# rec_comb <- 
#   bind_rows(loadRData(file=file.path(my.filepath, "rdata", "rec_sp.RData")) ) %>% 
#   bind_rows(loadRData(file=file.path(my.filepath, "rdata", "rec_tt.RData")) ) %>% 
#   bind_rows(rec ) %>% 
#   bind_rows(rec_gm %>% filter(!id %in% rec$id))  

# session_comb <- session_comb %>% distinct(id, sport, start_time, .keep_all = TRUE) 

# save(session_comb, file=file.path(my.filepath, "rdata", "session_comb.RData"))
# save(rec_comb,     file=file.path(my.filepath, "rdata", "rec_comb.RData"))

load(file=file.path(my.filepath, "rdata", "session_comb.RData"))
load(file=file.path(my.filepath, "rdata", "rec_comb.RData"))


# ======================================================================================
h <- data.frame(lat = 52.81355, lon=6.54193)

t <- session_comb %>% filter(municipality=="Midden-Drenthe", sport=="running", distance >=9800, distance <10400) 

t2 <-
  rec_comb %>% 
  filter(id %in% t$id) %>% 
  # filter(lat < 52.82) %>% 
  drop_na(start_time, lat, lon, cum_distance) %>% 
  group_by(id) %>% 
  mutate(
    xmin = round(min(lon, na.rm=TRUE), digits=2),
    xmax = round(max(lon, na.rm=TRUE), digits=2),
    ymin = round(min(lat, na.rm=TRUE), digits=2),
    ymax = round(max(lat, na.rm=TRUE), digits=2),
    distance2 = round(max(cum_distance, na.rm=TRUE)/1000, digits=1), 
    round = paste(
      paste0(distance2,"km"),
      paste(xmin, xmax, sep="-"),
      paste(ymin, ymax, sep="-"), 
      sep="\n")
  ) 

xlim <- range(t2$lon, na.rm=TRUE)
ylim <- range(t2$lat, na.rm=TRUE)

t2 %>% 
  ggplot(aes(x=lon, y=lat)) +
  theme_minimal() +
  coord_quickmap(xlim=xlim, ylim=ylim) +
  geom_point(aes(group=as.Date(start_time)), size=0.5) +
  geom_point(data=h, size=1.2, colour="red") +
  facet_wrap(~round, ncol=10)


t2_sf <-
  t2 %>% 
  sf::st_as_sf(coords = c("lon", "lat"), crs = 4326) %>% 
  dplyr::group_by(id, round) %>% 
  dplyr::summarise() %>%
  sf::st_cast("LINESTRING")

coords <- 
  matrix(c(xlim[1],xlim[2],ylim[1],ylim[2]), 
         byrow = TRUE, 
         nrow = 2, 
         ncol = 2, 
         dimnames = list(c('x','y'),c('min','max'))) 

map <- coords %>% osmdata::opq() %>% osmdata::osmdata_sf()
plot(map)

ggplot() +
  theme_publication() +
  theme(legend.position="none") +
  # geom_sf(data=map) +
  geom_sf(data=t2_sf, aes(colour=id)) +
  facet_wrap(~round, ncol=8)

# leaflet solution
# map <- leaflet()  %>% addTiles() 
# map <- map %>%   
#   # addCircleMarkers(data=df1, radius = 8, color = 'red', fill = TRUE, label = ~as.character(row_rank), labelOptions=c(noHide=TRUE)) %>%
#   addPolylines(data=t2, lng = ~lon, lat = ~lat, group=id)
# map