Last updated: 2021-09-28

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Knit directory: Test/

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load data.json

today = "2021-09-27"
cat("data on:", today, "\n")
data on: 2021-09-27 
json_data = fromJSON(file = paste0("data/json/", today, "/position.json"))
cat("Total collected positions: ", length(json_data), "\n")
Total collected positions:  958230 
tagId_seq = unlist(lapply(json_data, function(x){x["tag_id"][[1]]}))
tagId = unique(tagId_seq)
nb_tag = length(tagId)

cat("Tags are: ", tagId, "\n")
Tags are:  28d2 2f77 0db4 2e55 2f7b 2c57 0da6 2e8d 2f40 0d82 2b9c 0baf 2a51 19ab 2e5b 2c5d 
table(tagId_seq)
tagId_seq
  0baf   0d82   0da6   0db4   19ab   28d2   2a51   2b9c   2c57   2c5d   2e55 
 50092  50176  50057 163868  41645  49719  50022 198074  50135    422  49662 
  2e5b   2e8d   2f40   2f77   2f7b 
   432  13436  49155  96091  45244 

general analysis

dat <- data.frame(tag = unlist(lapply(json_data, function(x){x["tag_id"][[1]]})),
                  x = unlist(lapply(json_data, function(x){x["x"][[1]]})),
                  y = unlist(lapply(json_data, function(x){x["y"][[1]]})),
                  record_timestamp = unlist(lapply(json_data, function(x){x["record_timestamp"][[1]]})))
dat = dat[order(dat$record_timestamp),]
dat = cbind.data.frame(dat, convert_date(dat$record_timestamp))
dat$x = as.numeric(dat$x)
dat$y = as.numeric(dat$y)

list_tag <- split(dat, dat$tag)

quality of collecting data

table_tag <- data.frame(tag = tagId)
table_tag$first_record = NA
table_tag$last_record = NA
table_tag$number = NA
table_tag$number_NA = NA
table_tag$ratio_non_NA = NA
table_tag$freq_1Q = NA
table_tag$freq_median = NA
table_tag$freq_3Q = NA


for (k in 1:nb_tag){
  tag = table_tag$tag[k]
  temp = list_tag[tag][[1]]
  temp$diff_ts = c(0, temp$record_timestamp[-1]-temp$record_timestamp[-nrow(temp)])
  
  table_tag$first_record[k] = head(as.character(temp$date),1)
  table_tag$last_record[k] = tail(as.character(temp$date),1)
  table_tag$number[k] = nrow(temp)
  table_tag$number_NA[k] = sum(is.na(temp$x))
  table_tag$ratio_non_NA[k] = round(1-table_tag$number_NA[k]/table_tag$number[k],2)
  table_tag$freq_1Q[k] = round(quantile(temp$diff_ts, 0.25), 3)
  table_tag$freq_median[k] = round(quantile(temp$diff_ts, 0.5), 3)
  table_tag$freq_3Q[k] = round(quantile(temp$diff_ts, 0.75), 3)
}

kable(table_tag) %>%
  kable_styling(bootstrap_options = "striped", full_width = F)
tag first_record last_record number number_NA ratio_non_NA freq_1Q freq_median freq_3Q
28d2 2021-09-27 06:23:17 2021-09-27 23:59:59 49719 905 0.98 0.546 0.594 0.647
2f77 2021-09-27 08:29:44 2021-09-27 23:59:59 96091 2269 0.98 0.200 0.442 0.595
0db4 2021-09-27 08:02:04 2021-09-27 23:59:59 163868 46281 0.72 0.200 0.200 0.536
2e55 2021-09-27 06:23:11 2021-09-27 23:59:59 49662 555 0.99 0.543 0.593 0.647
2f7b 2021-09-27 06:25:55 2021-09-27 23:59:59 45244 454 0.99 0.545 0.596 0.652
2c57 2021-09-27 06:25:15 2021-09-27 23:59:59 50135 11408 0.77 0.541 0.593 0.649
0da6 2021-09-27 06:25:17 2021-09-27 23:59:59 50057 285 0.99 0.544 0.594 0.646
2e8d 2021-09-27 07:05:21 2021-09-27 23:59:59 13436 42 1.00 0.583 0.638 0.691
2f40 2021-09-27 06:27:38 2021-09-27 23:59:59 49155 4713 0.90 0.552 0.593 0.642
0d82 2021-09-27 06:23:11 2021-09-27 23:59:59 50176 40 1.00 0.540 0.594 0.651
2b9c 2021-09-27 06:25:10 2021-09-27 23:59:59 198074 3689 0.98 0.200 0.200 0.259
0baf 2021-09-27 06:23:11 2021-09-27 23:59:59 50092 385 0.99 0.539 0.594 0.670
2a51 2021-09-27 06:23:11 2021-09-27 23:59:59 50022 72 1.00 0.545 0.594 0.645
19ab 2021-09-27 06:23:11 2021-09-27 23:59:57 41645 1129 0.97 1.000 1.000 1.100
2e5b 2021-09-27 06:25:48 2021-09-27 13:41:50 432 321 0.26 59.998 60.000 60.002
2c5d 2021-09-27 06:25:40 2021-09-27 13:40:51 422 420 0.00 59.999 60.000 60.002
x_na = which(is.na(dat$x))
y_na = which(is.na(dat$y))
cat("if x_na = y_na:", identical(x_na, y_na), "\n")
if x_na = y_na: TRUE 
cat("number of invalid positions:", length(x_na), "/", length(tagId_seq), "(=", 
    length(x_na)/length(tagId_seq)*100, "%)", "\n")
number of invalid positions: 72968 / 958230 (= 7.614873 %) 
if (length(x_na)!=0){
  dat = dat[-x_na,]
}
list_tag <- split(dat, dat$tag)

for (tag in names(list_tag)){
  if (!is.null(list_tag[tag][[1]])){
    dd = list_tag[tag][[1]]
    dd[,c("x","y")] = dd[,c("x","y")]/100
    rownames(dd) = 1:nrow(dd)
    dd$num = 1:nrow(dd)
    dd$timediff = c(0, dd$record_timestamp[-1] - dd$record_timestamp[-nrow(dd)])
    
    list_tag[tag][[1]] = dd
  }
}

dat = do.call(rbind.data.frame, list_tag)

plot

for (tag in names(list_tag)){
  dd = list_tag[tag][[1]]
  
  p <- ggplot(dd) + theme_bw() +
    geom_point(aes(x=x,y=y)) +
    coord_equal(ratio = 1, xlim = c(-30,5), ylim = c(-60,5)) +
    labs(title = tag)
  print(p)
}

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sessionInfo()
R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.6

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] fr_FR.UTF-8/fr_FR.UTF-8/fr_FR.UTF-8/C/fr_FR.UTF-8/fr_FR.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] lubridate_1.7.10 dplyr_1.0.6      nnet_7.3-14      kableExtra_1.1.0
[5] rjson_0.2.20     cowplot_1.1.0    gganimate_1.0.7  ggplot2_3.3.3   
[9] workflowr_1.6.2 

loaded via a namespace (and not attached):
 [1] progress_1.2.2    tidyselect_1.1.0  xfun_0.25         purrr_0.3.4      
 [5] colorspace_1.4-1  vctrs_0.3.8       generics_0.1.0    viridisLite_0.3.0
 [9] htmltools_0.5.0   yaml_2.2.1        utf8_1.1.4        rlang_0.4.11     
[13] later_1.1.0.1     pillar_1.6.0      glue_1.4.1        withr_2.4.2      
[17] DBI_1.1.1         tweenr_1.0.1      lifecycle_1.0.0   stringr_1.4.0    
[21] munsell_0.5.0     gtable_0.3.0      rvest_1.0.0       evaluate_0.14    
[25] labeling_0.3      knitr_1.33        httpuv_1.5.4      fansi_0.4.1      
[29] gifski_0.8.6      highr_0.8         Rcpp_1.0.5        readr_1.4.0      
[33] promises_1.1.1    scales_1.1.1      backports_1.1.8   webshot_0.5.2    
[37] farver_2.0.3      fs_1.5.0          hms_1.0.0         digest_0.6.25    
[41] stringi_1.4.6     grid_4.0.2        rprojroot_1.3-2   tools_4.0.2      
[45] magrittr_2.0.1    tibble_3.1.1      crayon_1.4.1      whisker_0.4      
[49] pkgconfig_2.0.3   ellipsis_0.3.1    xml2_1.3.2        prettyunits_1.1.1
[53] httr_1.4.2        rstudioapi_0.13   assertthat_0.2.1  rmarkdown_2.10   
[57] R6_2.4.1          git2r_0.28.0      compiler_4.0.2