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include id columns from json
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@tobiste
tobiste committed Aug 1, 2024
1 parent f10bb20 commit 323c938
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Showing 2 changed files with 93 additions and 67 deletions.
156 changes: 91 additions & 65 deletions R/import.R
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@
#'
#' read_strabo_mobile("C:/Users/tobis/Downloads/StraboSpot_Search_06_16_2023.txt")
#'
#' read_strabo_JSON("E:/Lakehead/Field work/StraboSpot_07_02_2023.json", dataset = "TS")
#' read_strabo_JSON("G:/My Drive/Moss_Lake/data.json")
#' }
NULL

Expand Down Expand Up @@ -144,14 +144,13 @@ read_strabo_mobile <- function(file, sf = TRUE) {

#' @rdname strabo
#' @export
read_strabo_JSON <- function(file, dataset = NULL, sf = TRUE) {
stopifnot(!is.null(dataset))
read_strabo_JSON <- function(file, sf = TRUE) {
time <- tag_id <- tag_name <- NULL

dat <- rjson::fromJSON(file = file)

# read tags
tags_list <- dat$project$tags
tags_list <- dat$project$project$tags
tags_df <- spot_tags <- tibble::tibble()
for (t in seq_along(tags_list)) {
spots_t <- data.frame(spot = tags_list[[t]]$spots)
Expand All @@ -176,65 +175,75 @@ read_strabo_JSON <- function(file, dataset = NULL, sf = TRUE) {
# dplyr::select(-tag) |>
tidyr::pivot_wider(names_from = "tag_name", values_from = "tag") |>
dplyr::mutate(dplyr::across(!spot, function(x) ifelse(is.na(x), FALSE, TRUE))) |>
unique()
unique() |>
mutate(spot = as.character(spot)) |>
rename(spot_id = spot)

# read field book data of dataset
# datasets
ds <- seq_along(dat$project$datasets)
ds_name <- character()
ds_name <- ds_name_id <- character()

for (a in ds) {
ds_name[a] <- dat$project$datasets[[a]]$name
ds_name_id[a] <- names(dat$project$datasets)[[a]]
}
ds_df <- data.frame(ds_name = ds_name, ds_id = ds_name_id)

# spot lists
spots <- character()
for (i in ds_name_id) {
ds_spot_ids_i <- dat$project$datasets[[i]]$spotIds
spots <- rbind(spots, cbind(ds_id = rep(i, length(ds_spot_ids_i)), spot_id = ds_spot_ids_i))
}
spots_df <- as.data.frame(spots) |> unique()

# extract the specified dataset
dsn <- data.frame(ds, ds_name) |>
dplyr::filter(ds_name == dataset) |>
# dplyr::filter(ds_name == dataset) |>
dplyr::pull(ds)
ds_name_id <- names(dat$project$datasets)[dsn]


# ds_spot_ids <- dat$project$datasets[[dsn]]$spotIds # spots in dataset
# DSN <- dat$spotsDb[ds_spot_ids]
# for (i in seq_along(dat$spotsDb)) {
# dat$spotsDb[[i]]
# }

DSN <- dat$project$datasets[[dsn]]$spots$features

spot <- notes <- date <- character()
spot_id <- spot <- notes <- date <- character()
altitude <- longitude <- latitude <- gps_accuracy <- numeric()
orient_df <- data.frame(check.names = FALSE)

id <- numeric()
for (i in seq_along(DSN)) {
if (!is.null(DSN[[i]]$geometry)) {
if (DSN[[i]]$geometry$type == "Point" & DSN[[i]]$type == "Feature") {
spot[i] <- DSN[[i]]$properties$name
date[i] <- DSN[[i]]$properties$date
id[i] <- DSN[[i]]$properties$id

notes_i <- DSN[[i]]$properties$notes
for (i in seq_along(dat$spotsDb)) {
spot_i <- dat$spotsDb[[i]]
if (!is.null(spot_i$geometry)) {
if (spot_i$geometry$type == "Point" & spot_i$type == "Feature") {
spot_id[i] <- spot_i$properties$id
spot[i] <- spot_i$properties$name
date[i] <- spot_i$properties$date
id[i] <- spot_i$properties$id

notes_i <- spot_i$properties$notes
notes[i] <- ifelse(is.null(notes_i), NA, notes_i)

altitude_i <- DSN[[i]]$properties$altitude
altitude_i <- spot_i$properties$altitude
altitude[i] <- ifelse(is.null(altitude_i), NA, altitude_i)

longitude[i] <- DSN[[i]]$geometry$coordinates[1]
latitude[i] <- DSN[[i]]$geometry$coordinates[2]
longitude[i] <- spot_i$geometry$coordinates[1]
latitude[i] <- spot_i$geometry$coordinates[2]

gps_accuracy_i <- DSN[[i]]$properties$gps_accuracy
gps_accuracy_i <- spot_i$properties$gps_accuracy
gps_accuracy[i] <- ifelse(is.null(gps_accuracy_i), NA, gps_accuracy_i)
}
}
}
fieldbook <- tibble::tibble(spot = spot, longitude, latitude, altitude, note = notes, time = date, gps_accuracy, id) |>
dplyr::mutate(time = lubridate::as_datetime(time)) |>
dplyr::arrange(time) |>
dplyr::left_join(spot_tags_df, by = c("id" = "spot")) |>
dplyr::select(-id)
if (sf) fieldbook <- sf::st_as_sf(fieldbook, coords = c("longitude", "latitude"), remove = FALSE, crs = "WGS84", na.fail = FALSE)

# read structural data
orient_df <- data.frame(check.names = FALSE)
for (i in seq_along(DSN)) { # loop through each spot
if (!is.null(DSN[[i]]$geometry)) {
if (DSN[[i]]$geometry$type == "Point" & DSN[[i]]$type == "Feature") {
spot <- DSN[[i]]$properties$name

orient_ls_i <- DSN[[i]]$properties$orientation_data
# orientation data
orient_ls_i <- spot_i$properties$orientation_data
if (!is.null(orient_ls_i)) {
orient_df_i <- tibble::tibble()
for (j in seq_along(orient_ls_i)) { # loop through each measurement
orient_ls_ij <- orient_ls_i[[j]]

# concatenate directional_indicators into one column
if (length(orient_ls_ij$directional_indicators) > 1) {
orient_ls_ij$directional_indicators <- toString(orient_ls_ij$directional_indicators)
Expand All @@ -243,9 +252,10 @@ read_strabo_JSON <- function(file, dataset = NULL, sf = TRUE) {
# single P or L measurements
if (is.null(orient_ls_ij$associated_orientation)) {
# append all measurements of spot
orient_df_i <- plyr::rbind.fill(orient_df_i, as.data.frame(orient_ls_ij, check.names = FALSE)) |>
unique()
orient_df_i$spot <- spot
# orient_df_i <- plyr::rbind.fill(orient_df_i, as.data.frame(orient_ls_ij, check.names = FALSE)) |>
orient_df_i <- plyr::rbind.fill(orient_df_i, as.data.frame(orient_ls_ij, check.names = FALSE))
orient_df_i$spot <- spot[i]
orient_df_i$spot_id <- spot_id[i]
orient_df_i$associated <- FALSE
} else {
# P + L measurements
Expand All @@ -261,45 +271,61 @@ read_strabo_JSON <- function(file, dataset = NULL, sf = TRUE) {
## L measurement
PL <- data.frame(check.names = FALSE)
for (k in seq_along(L_ls)) {
L <- L_ls[[k]] |>
as.data.frame(check.names = FALSE) |>
unique()
plunge <- L$plunge
trend <- L$trend
if (!is.na(plunge) & !is.na(trend)) {
L$unix_timestamp <- L$plunge <- L$trend <- NULL # don't need this column twice
colnames(L) <- paste("associated", colnames(L), sep = "_")
L$plunge <- plunge
L$trend <- trend

## combine P + L measurements
PL_k <- cbind(P, L)
PL <- plyr::rbind.fill(PL, PL_k) |>
if (L_ls[[k]]$type != "planar_orientation") {
L <- L_ls[[k]] |>
as.data.frame(check.names = FALSE) |>
unique()
plunge <- L$plunge
trend <- L$trend
if (!is.na(plunge) & !is.na(trend)) {
L$unix_timestamp <- L$plunge <- L$trend <- NULL # don't need this column twice
colnames(L) <- paste("associated", colnames(L), sep = "_")
L$plunge <- plunge
L$trend <- trend

## combine P + L measurements
PL_k <- cbind(P, L)
PL <- plyr::rbind.fill(PL, PL_k) |>
unique()
}
PL$associated <- TRUE
}
PL$associated <- TRUE
}

# append all P+L measurements of spot
orient_df_i <- plyr::rbind.fill(orient_df_i, PL) |>
unique()
orient_df_i$spot <- spot
if (nrow(orient_df_i) > 0) {
orient_df_i <- plyr::rbind.fill(orient_df_i, PL) |>
unique()
orient_df_i$spot <- spot[i]
orient_df_i$spot_id <- spot_id[i]
}

# orient_ls_ij <- NULL
}
# combine all spots
orient_df <- plyr::rbind.fill(orient_df, orient_df_i) |>
unique()
orient_df <- plyr::rbind.fill(orient_df, orient_df_i)
}
}
}
}
}
fieldbook <- tibble::tibble(spot_id = spot_id, spot = spot, longitude, latitude, altitude, note = notes, time = date, gps_accuracy, id) |>
dplyr::mutate(time = lubridate::as_datetime(time)) |>
dplyr::arrange(time) |>
dplyr::distinct() |>
dplyr::left_join(spots_df) |>
dplyr::left_join(ds_df) |>
dplyr::left_join(spot_tags_df) |>
dplyr::select(-c(id))
if (sf) fieldbook <- sf::st_as_sf(fieldbook, coords = c("longitude", "latitude"), remove = FALSE, crs = "WGS84", na.fail = FALSE)

meta <- orient_df |>
tibble::as_tibble() |>
dplyr::left_join(fieldbook) |>
dplyr::arrange(time)
# select_if(function(x) !(all(is.na(x)) | all(x==""))) |>
dplyr::distinct() |>
dplyr::left_join(fieldbook, dplyr::join_by("spot_id")) |>
dplyr::arrange(time) |>
dplyr::select(-c(spot.y, ds_id, spot_id, unix_timestamp, modified_timestamp)) |>
dplyr::rename(spot = spot.x)
#
if (sf) {
meta <- sf::st_as_sf(meta)
Expand Down
4 changes: 2 additions & 2 deletions man/strabo.Rd
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