2021-09-27
Last updated: 2021-09-30
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Knit directory: Test/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| html | 8cd6144 | cfcforever | 2021-09-29 | Build site. |
| Rmd | 3ebdc7c | cfcforever | 2021-09-28 | some changes |
| html | 6289c69 | cfcforever | 2021-09-28 | Build site. |
| html | f8288b3 | cfcforever | 2021-09-28 | Build site. |
| html | 2846b2e | cfcforever | 2021-09-28 | Build site. |
| html | 72db555 | cfcforever | 2021-09-28 | Build site. |
| Rmd | eac5eb1 | cfcforever | 2021-09-28 | add the new analysis |
| html | 52bf4a0 | cfcforever | 2021-09-28 | Build site. |
| Rmd | a6c4cce | cfcforever | 2021-09-28 | add the new analysis |
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)
names_tag <- read.table(file = "data/tag_names_20210924.txt", header = T, sep = "\t")
names_tag = names_tag[names_tag$id%in%tagId, ]
tagId = names_tag$id
nb_tag = length(tagId)
dat = dat[dat$tag%in%tagId,]
dat$label = factor(dat$tag, levels = names_tag$id, labels = names_tag$label)
list_tag <- split(dat, dat$tag)quality of collecting data
table_tag <- data.frame(tag = names_tag$id, label = names_tag$label)
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 | label | first_record | last_record | number | number_NA | ratio_non_NA | freq_1Q | freq_median | freq_3Q |
|---|---|---|---|---|---|---|---|---|---|
| 2a51 | BLA | 2021-09-27 06:23:11 | 2021-09-27 23:59:59 | 50022 | 72 | 1.00 | 0.545 | 0.594 | 0.645 |
| 0da6 | BRA1 | 2021-09-27 06:25:17 | 2021-09-27 23:59:59 | 50057 | 285 | 0.99 | 0.544 | 0.594 | 0.646 |
| 2f7b | BRA2 | 2021-09-27 06:25:55 | 2021-09-27 23:59:59 | 45244 | 454 | 0.99 | 0.545 | 0.596 | 0.652 |
| 2f40 | BRA4 | 2021-09-27 06:27:38 | 2021-09-27 23:59:59 | 49155 | 4713 | 0.90 | 0.552 | 0.593 | 0.642 |
| 2f77 | BRP1 | 2021-09-27 08:29:44 | 2021-09-27 23:59:59 | 96091 | 2269 | 0.98 | 0.200 | 0.442 | 0.595 |
| 2b9c | BRP2 | 2021-09-27 06:25:10 | 2021-09-27 23:59:59 | 198074 | 3689 | 0.98 | 0.200 | 0.200 | 0.259 |
| 0d82 | CDS1 | 2021-09-27 06:23:11 | 2021-09-27 23:59:59 | 50176 | 40 | 1.00 | 0.540 | 0.594 | 0.651 |
| 2c57 | DYN1 | 2021-09-27 06:25:15 | 2021-09-27 23:59:59 | 50135 | 11408 | 0.77 | 0.541 | 0.593 | 0.649 |
| 2e8d | DYN3 | 2021-09-27 07:05:21 | 2021-09-27 23:59:59 | 13436 | 42 | 1.00 | 0.583 | 0.638 | 0.691 |
| 0baf | ELC | 2021-09-27 06:23:11 | 2021-09-27 23:59:59 | 50092 | 385 | 0.99 | 0.539 | 0.594 | 0.670 |
| 0db4 | FAU | 2021-09-27 08:02:04 | 2021-09-27 23:59:59 | 163868 | 46281 | 0.72 | 0.200 | 0.200 | 0.536 |
| 28d2 | ORD | 2021-09-27 06:23:17 | 2021-09-27 23:59:59 | 49719 | 905 | 0.98 | 0.546 | 0.594 | 0.647 |
| 2e55 | SCO | 2021-09-27 06:23:11 | 2021-09-27 23:59:59 | 49662 | 555 | 0.99 | 0.543 | 0.593 | 0.647 |
plot with NAs
timestamp_breaks = as.numeric(as.POSIXct(paste0(today, " ", sprintf("%02d", 0:23), ":00:00 CEST"))) + 3600*6
p <- ggplot(dat) + theme_bw() +
geom_point(aes(x=record_timestamp, y=label, col=label)) +
scale_x_continuous(breaks = timestamp_breaks, labels = 0:23) +
coord_cartesian(xlim = c(timestamp_breaks[1], timestamp_breaks[23]+3600)) +
theme(legend.position = "None") +
labs(x = "hour", y = "", title = today)
print(p)
| Version | Author | Date |
|---|---|---|
| 8cd6144 | cfcforever | 2021-09-29 |
plot without NAs
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 NA positions:", length(x_na), "/", length(tagId_seq), "(=",
length(x_na)/length(tagId_seq)*100, "%)", "\n")number of NA positions: 71098 / 958230 (= 7.419722 %) if (length(x_na)!=0){
dat = dat[-x_na,]
}timestamp_breaks = as.numeric(as.POSIXct(paste0(today, " ", sprintf("%02d", 0:23), ":00:00 CEST"))) + 3600*6
p <- ggplot(dat) + theme_bw() +
geom_point(aes(x=record_timestamp, y=label, col=label)) +
scale_x_continuous(breaks = timestamp_breaks, labels = 0:23) +
coord_cartesian(xlim = c(timestamp_breaks[1], timestamp_breaks[23]+3600)) +
theme(legend.position = "None") +
labs(x = "hour", y = "", title = today)
print(p)
| Version | Author | Date |
|---|---|---|
| 8cd6144 | cfcforever | 2021-09-29 |
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$record_timestamp[-nrow(dd)])
list_tag[tag][[1]] = dd
}
}
dat = do.call(rbind.data.frame, list_tag)plot
plan <- read_excel("data/plan/Wall_lignes_firminy.xlsx")
plan = as.data.frame(plan)
plan$`Start X` <- as.numeric(plan$`Start X`)/100
plan$`Start Y` <- as.numeric(plan$`Start Y`)/100
plan$`End X` <- as.numeric(plan$`End X`)/100
plan$`End Y` <- as.numeric(plan$`End Y`)/100
colnames(plan) = c("Name", "Length", "Linetype Scale", "Angle", "Delta X",
"Delta Y", "Delta Z", "EndX", "EndY", "EndZ",
"StartX", "StartY", "StartZ")
p <- ggplot(plan) + theme_bw() +
geom_segment(aes(x=StartX, y=StartY, xend=EndX, yend=EndY))for (k in 1:nb_tag){
tag = names_tag$id[k]
label = names_tag$label[k]
cat("\n")
cat("## ", label, "\n")
dd = list_tag[tag][[1]]
q <- p +
geom_point(data = dd, aes(x=x,y=y), col="red", size = 1) +
coord_equal(ratio = 1, xlim = c(-35,5), ylim = c(-60,5)) +
labs(x = "", y = "", title = paste0(tag, " - ", names_tag$Matériel[names_tag$id==tag]))
print(q)
cat("\n")
}
SCO
| Version | Author | Date |
|---|---|---|
| 8cd6144 | cfcforever | 2021-09-29 |
sessionInfo()R version 4.0.5 (2021-03-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
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] zh_CN.UTF-8/zh_CN.UTF-8/zh_CN.UTF-8/C/zh_CN.UTF-8/zh_CN.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] readxl_1.3.1 lubridate_1.7.10 dplyr_1.0.5 nnet_7.3-15
[5] kableExtra_1.3.4 rjson_0.2.20 cowplot_1.1.1 gganimate_1.0.7
[9] ggplot2_3.3.3 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] progress_1.2.2 tidyselect_1.1.0 xfun_0.22 bslib_0.2.4
[5] purrr_0.3.4 colorspace_2.0-0 vctrs_0.3.7 generics_0.1.0
[9] viridisLite_0.4.0 htmltools_0.5.1.1 yaml_2.2.1 utf8_1.2.1
[13] rlang_0.4.10 jquerylib_0.1.3 later_1.1.0.1 pillar_1.6.0
[17] glue_1.4.2 withr_2.4.1 tweenr_1.0.2 lifecycle_1.0.0
[21] stringr_1.4.0 cellranger_1.1.0 munsell_0.5.0 gtable_0.3.0
[25] rvest_1.0.0 evaluate_0.14 labeling_0.4.2 knitr_1.32
[29] httpuv_1.5.5 fansi_0.4.2 highr_0.8 Rcpp_1.0.6
[33] promises_1.2.0.1 scales_1.1.1 webshot_0.5.2 jsonlite_1.7.2
[37] systemfonts_1.0.1 farver_2.1.0 fs_1.5.0 hms_1.0.0
[41] digest_0.6.27 stringi_1.5.3 grid_4.0.5 rprojroot_2.0.2
[45] tools_4.0.5 magrittr_2.0.1 sass_0.3.1 tibble_3.1.0
[49] crayon_1.4.1 whisker_0.4 pkgconfig_2.0.3 ellipsis_0.3.1
[53] xml2_1.3.2 prettyunits_1.1.1 svglite_2.0.0 rmarkdown_2.10
[57] httr_1.4.2 rstudioapi_0.13 R6_2.5.0 git2r_0.28.0
[61] compiler_4.0.5