R/read-icl.R
In paleolimbot/bsrto: Access Data from the Barrow Strait Real Time Observatory
Defines functions
read_icl_header_lines
read_icl_header
read_icl_vector
read_icl
Documented in
read_icl
read_icl_header
read_icl_header_lines
read_icl_vector
#' Read icl files
#'
#' @inheritParams read_odf
#' @param tz Timezone for which date times are representative.
#' @param file_vector A vector of files or URLs
#' @param pb A [progress bar][progress::progress_bar] or `NULL`.
#'
#' @return A [tibble::tibble()]
#' @export
#'
#' @examples
#' icl_file <- bs_example("icl/SAF2564_20191010_19.txt")
#' read_icl(icl_file)
#' read_icl_vector(icl_file)
#' read_icl_header(icl_file)
#' read_icl_header_lines(icl_file)
#'
read_icl <- function(file, pb = NULL, tz = "UTC") {
bs_tick(pb, file)
header_lines <- try(read_icl_header_lines(file))
if (inherits(header_lines, "try-error")) {
return(tibble::tibble())
}
skip <- length(header_lines) + 1
# need the date from the header
file_date <- stringr::str_extract(header_lines[4], "[0-9-]{10}\\s*$")
file_date_parsed <- readr::parse_date(file_date, "%Y-%m-%d")
# these files are frequently malformed, which causes readr to prematurely
# abandon reading some files
col_names <- readr::read_lines(file, skip = skip, n_max = 1)
col_names <- stringr::str_split_fixed(col_names, stringr::fixed("\t"), n = 416)
lines <- readr::read_lines(file, skip = skip + 1)
lines_split <- stringr::str_split_fixed(lines, stringr::fixed("\t"), n = 416)
colnames(lines_split) <- as.character(col_names)
# need column names to match exactly or it is difficult to process
# vectors of these files
if (!identical(as.character(col_names), icl_col_names)) {
col_names_label <- paste0("'", col_names, "'", collapse = ",")
message(
glue(
"Unexpected column names in file '{ file }':\n{ col_names_label }"
)
)
return(tibble::tibble())
}
result <- tibble::as_tibble(lines_split)
# much easier later on to make this a date + time
file_datetime <- as.POSIXct(file_date_parsed)
attr(file_datetime, "tzone") <- tz
result$Time <- file_datetime + readr::parse_time(result$Time)
numeric_cols <- setdiff(names(result), c("Time", "Comment"))
result[numeric_cols] <- lapply(result[numeric_cols], readr::parse_double)
result
}
#' @rdname read_icl
#' @export
read_icl_vector <- function(file_vector) {
pb <- bs_progress(file_vector)
on.exit(bs_progress_finish(pb))
results <- lapply(file_vector, read_icl, pb = pb)
lengths <- vapply(results, nrow, integer(1))
results_all <- vctrs::vec_rbind(!!! results)
vctrs::vec_cbind(
file = vctrs::vec_rep_each(file_vector, lengths),
results_all
)
}
#' @rdname read_icl
#' @export
read_icl_header <- function(file, header_lines = read_icl_header_lines(file)) {
section_start <- grep(":$", header_lines)
section_end <- grep("^\\s*$", header_lines)
if (length(section_start) != length(section_end)) {
abort(glue("Differing lengths for section start and end in read_icl_header('{ file }')"))
}
section_title <- gsub(":$", "", header_lines[section_start])
section_content <- Map("[", list(header_lines), Map(":", section_start + 1, section_end))
section_content_parsed <- lapply(section_content, function(x) {
x <- x[-length(x)]
split <- stringr::str_split_fixed(x, "\t", 2)
tibble::tibble(key = split[, 1], value = split[, 2])
})
names(section_content_parsed) <- section_title
section_content_parsed
}
#' @rdname read_icl
#' @export
read_icl_header_lines <- function(file, n_header = 29) {
header_lines(
file,
function(x) grepl("^Data:\\s*$", x),
n_header = n_header
)
}
# the way this is set up makes it difficult to use any column names that don't
# match exactly
icl_col_names <- c(
"Time", "Comment", "Temperature [C]", "Humidity [%]", "Sequence #",
"Data Points", "0", "15.63", "31.25", "46.88", "62.5", "78.13",
"93.75", "109.38", "125", "140.63", "156.25", "171.88", "187.5",
"203.13", "218.75", "234.38", "250", "265.63", "281.25", "296.88",
"312.5", "328.13", "343.75", "359.38", "375", "390.63", "406.25",
"421.88", "437.5", "453.13", "468.75", "484.38", "500", "515.63",
"531.25", "546.88", "562.5", "578.13", "593.75", "609.38", "625",
"640.63", "656.25", "671.88", "687.5", "703.13", "718.75", "734.38",
"750", "765.63", "781.25", "796.88", "812.5", "828.13", "843.75",
"859.38", "875", "890.63", "906.25", "921.88", "937.5", "953.13",
"968.75", "984.38", "1000", "1015.63", "1031.25", "1046.88",
"1062.5", "1078.13", "1093.75", "1109.38", "1125", "1140.63",
"1156.25", "1171.88", "1187.5", "1203.13", "1218.75", "1234.38",
"1250", "1265.63", "1281.25", "1296.88", "1312.5", "1328.13",
"1343.75", "1359.38", "1375", "1390.63", "1406.25", "1421.88",
"1437.5", "1453.13", "1468.75", "1484.38", "1500", "1515.63",
"1531.25", "1546.88", "1562.5", "1578.13", "1593.75", "1609.38",
"1625", "1640.63", "1656.25", "1671.88", "1687.5", "1703.13",
"1718.75", "1734.38", "1750", "1765.63", "1781.25", "1796.88",
"1812.5", "1828.13", "1843.75", "1859.38", "1875", "1890.63",
"1906.25", "1921.88", "1937.5", "1953.13", "1968.75", "1984.38",
"2000", "2015.63", "2031.25", "2046.88", "2062.5", "2078.13",
"2093.75", "2109.38", "2125", "2140.63", "2156.25", "2171.88",
"2187.5", "2203.13", "2218.75", "2234.38", "2250", "2265.63",
"2281.25", "2296.88", "2312.5", "2328.13", "2343.75", "2359.38",
"2375", "2390.63", "2406.25", "2421.88", "2437.5", "2453.13",
"2468.75", "2484.38", "2500", "2515.63", "2531.25", "2546.88",
"2562.5", "2578.13", "2593.75", "2609.38", "2625", "2640.63",
"2656.25", "2671.88", "2687.5", "2703.13", "2718.75", "2734.38",
"2750", "2765.63", "2781.25", "2796.88", "2812.5", "2828.13",
"2843.75", "2859.38", "2875", "2890.63", "2906.25", "2921.88",
"2937.5", "2953.13", "2968.75", "2984.38", "3000", "3015.63",
"3031.25", "3046.88", "3062.5", "3078.13", "3093.75", "3109.38",
"3125", "3140.63", "3156.25", "3171.88", "3187.5", "3203.13",
"3218.75", "3234.38", "3250", "3265.63", "3281.25", "3296.88",
"3312.5", "3328.13", "3343.75", "3359.38", "3375", "3390.63",
"3406.25", "3421.88", "3437.5", "3453.13", "3468.75", "3484.38",
"3500", "3515.63", "3531.25", "3546.88", "3562.5", "3578.13",
"3593.75", "3609.38", "3625", "3640.63", "3656.25", "3671.88",
"3687.5", "3703.13", "3718.75", "3734.38", "3750", "3765.63",
"3781.25", "3796.88", "3812.5", "3828.13", "3843.75", "3859.38",
"3875", "3890.63", "3906.25", "3921.88", "3937.5", "3953.13",
"3968.75", "3984.38", "4000", "4015.63", "4031.25", "4046.88",
"4062.5", "4078.13", "4093.75", "4109.38", "4125", "4140.63",
"4156.25", "4171.88", "4187.5", "4203.13", "4218.75", "4234.38",
"4250", "4265.63", "4281.25", "4296.88", "4312.5", "4328.13",
"4343.75", "4359.38", "4375", "4390.63", "4406.25", "4421.88",
"4437.5", "4453.13", "4468.75", "4484.38", "4500", "4515.63",
"4531.25", "4546.88", "4562.5", "4578.13", "4593.75", "4609.38",
"4625", "4640.63", "4656.25", "4671.88", "4687.5", "4703.13",
"4718.75", "4734.38", "4750", "4765.63", "4781.25", "4796.88",
"4812.5", "4828.13", "4843.75", "4859.38", "4875", "4890.63",
"4906.25", "4921.88", "4937.5", "4953.13", "4968.75", "4984.38",
"5000", "5015.63", "5031.25", "5046.88", "5062.5", "5078.13",
"5093.75", "5109.38", "5125", "5140.63", "5156.25", "5171.88",
"5187.5", "5203.13", "5218.75", "5234.38", "5250", "5265.63",
"5281.25", "5296.88", "5312.5", "5328.13", "5343.75", "5359.38",
"5375", "5390.63", "5406.25", "5421.88", "5437.5", "5453.13",
"5468.75", "5484.38", "5500", "5515.63", "5531.25", "5546.88",
"5562.5", "5578.13", "5593.75", "5609.38", "5625", "5640.63",
"5656.25", "5671.88", "5687.5", "5703.13", "5718.75", "5734.38",
"5750", "5765.63", "5781.25", "5796.88", "5812.5", "5828.13",
"5843.75", "5859.38", "5875", "5890.63", "5906.25", "5921.88",
"5937.5", "5953.13", "5968.75", "5984.38", "6000", "6015.63",
"6031.25", "6046.88", "6062.5", "6078.13", "6093.75", "6109.38",
"6125", "6140.63", "6156.25", "6171.88", "6187.5", "6203.13",
"6218.75", "6234.38", "6250", "6265.63", "6281.25", "6296.88",
"6312.5", "6328.13", "6343.75", "6359.38", "6375", "6390.63"
)
paleolimbot/bsrto documentation built on Dec. 12, 2021, 5:44 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions read_icl_header_lines read_icl_header read_icl_vector read_icl
Documented in read_icl read_icl_header read_icl_header_lines read_icl_vector
#' Read icl files
#'
#' @inheritParams read_odf
#' @param tz Timezone for which date times are representative.
#' @param file_vector A vector of files or URLs
#' @param pb A [progress bar][progress::progress_bar] or `NULL`.
#'
#' @return A [tibble::tibble()]
#' @export
#'
#' @examples
#' icl_file <- bs_example("icl/SAF2564_20191010_19.txt")
#' read_icl(icl_file)
#' read_icl_vector(icl_file)
#' read_icl_header(icl_file)
#' read_icl_header_lines(icl_file)
#'
read_icl <- function(file, pb = NULL, tz = "UTC") {
bs_tick(pb, file)
header_lines <- try(read_icl_header_lines(file))
if (inherits(header_lines, "try-error")) {
return(tibble::tibble())
}
skip <- length(header_lines) + 1
# need the date from the header
file_date <- stringr::str_extract(header_lines[4], "[0-9-]{10}\\s*$")
file_date_parsed <- readr::parse_date(file_date, "%Y-%m-%d")
# these files are frequently malformed, which causes readr to prematurely
# abandon reading some files
col_names <- readr::read_lines(file, skip = skip, n_max = 1)
col_names <- stringr::str_split_fixed(col_names, stringr::fixed("\t"), n = 416)
lines <- readr::read_lines(file, skip = skip + 1)
lines_split <- stringr::str_split_fixed(lines, stringr::fixed("\t"), n = 416)
colnames(lines_split) <- as.character(col_names)
# need column names to match exactly or it is difficult to process
# vectors of these files
if (!identical(as.character(col_names), icl_col_names)) {
col_names_label <- paste0("'", col_names, "'", collapse = ",")
message(
glue(
"Unexpected column names in file '{ file }':\n{ col_names_label }"
)
)
return(tibble::tibble())
}
result <- tibble::as_tibble(lines_split)
# much easier later on to make this a date + time
file_datetime <- as.POSIXct(file_date_parsed)
attr(file_datetime, "tzone") <- tz
result$Time <- file_datetime + readr::parse_time(result$Time)
numeric_cols <- setdiff(names(result), c("Time", "Comment"))
result[numeric_cols] <- lapply(result[numeric_cols], readr::parse_double)
result
}
#' @rdname read_icl
#' @export
read_icl_vector <- function(file_vector) {
pb <- bs_progress(file_vector)
on.exit(bs_progress_finish(pb))
results <- lapply(file_vector, read_icl, pb = pb)
lengths <- vapply(results, nrow, integer(1))
results_all <- vctrs::vec_rbind(!!! results)
vctrs::vec_cbind(
file = vctrs::vec_rep_each(file_vector, lengths),
results_all
)
}
#' @rdname read_icl
#' @export
read_icl_header <- function(file, header_lines = read_icl_header_lines(file)) {
section_start <- grep(":$", header_lines)
section_end <- grep("^\\s*$", header_lines)
if (length(section_start) != length(section_end)) {
abort(glue("Differing lengths for section start and end in read_icl_header('{ file }')"))
}
section_title <- gsub(":$", "", header_lines[section_start])
section_content <- Map("[", list(header_lines), Map(":", section_start + 1, section_end))
section_content_parsed <- lapply(section_content, function(x) {
x <- x[-length(x)]
split <- stringr::str_split_fixed(x, "\t", 2)
tibble::tibble(key = split[, 1], value = split[, 2])
})
names(section_content_parsed) <- section_title
section_content_parsed
}
#' @rdname read_icl
#' @export
read_icl_header_lines <- function(file, n_header = 29) {
header_lines(
file,
function(x) grepl("^Data:\\s*$", x),
n_header = n_header
)
}
# the way this is set up makes it difficult to use any column names that don't
# match exactly
icl_col_names <- c(
"Time", "Comment", "Temperature [C]", "Humidity [%]", "Sequence #",
"Data Points", "0", "15.63", "31.25", "46.88", "62.5", "78.13",
"93.75", "109.38", "125", "140.63", "156.25", "171.88", "187.5",
"203.13", "218.75", "234.38", "250", "265.63", "281.25", "296.88",
"312.5", "328.13", "343.75", "359.38", "375", "390.63", "406.25",
"421.88", "437.5", "453.13", "468.75", "484.38", "500", "515.63",
"531.25", "546.88", "562.5", "578.13", "593.75", "609.38", "625",
"640.63", "656.25", "671.88", "687.5", "703.13", "718.75", "734.38",
"750", "765.63", "781.25", "796.88", "812.5", "828.13", "843.75",
"859.38", "875", "890.63", "906.25", "921.88", "937.5", "953.13",
"968.75", "984.38", "1000", "1015.63", "1031.25", "1046.88",
"1062.5", "1078.13", "1093.75", "1109.38", "1125", "1140.63",
"1156.25", "1171.88", "1187.5", "1203.13", "1218.75", "1234.38",
"1250", "1265.63", "1281.25", "1296.88", "1312.5", "1328.13",
"1343.75", "1359.38", "1375", "1390.63", "1406.25", "1421.88",
"1437.5", "1453.13", "1468.75", "1484.38", "1500", "1515.63",
"1531.25", "1546.88", "1562.5", "1578.13", "1593.75", "1609.38",
"1625", "1640.63", "1656.25", "1671.88", "1687.5", "1703.13",
"1718.75", "1734.38", "1750", "1765.63", "1781.25", "1796.88",
"1812.5", "1828.13", "1843.75", "1859.38", "1875", "1890.63",
"1906.25", "1921.88", "1937.5", "1953.13", "1968.75", "1984.38",
"2000", "2015.63", "2031.25", "2046.88", "2062.5", "2078.13",
"2093.75", "2109.38", "2125", "2140.63", "2156.25", "2171.88",
"2187.5", "2203.13", "2218.75", "2234.38", "2250", "2265.63",
"2281.25", "2296.88", "2312.5", "2328.13", "2343.75", "2359.38",
"2375", "2390.63", "2406.25", "2421.88", "2437.5", "2453.13",
"2468.75", "2484.38", "2500", "2515.63", "2531.25", "2546.88",
"2562.5", "2578.13", "2593.75", "2609.38", "2625", "2640.63",
"2656.25", "2671.88", "2687.5", "2703.13", "2718.75", "2734.38",
"2750", "2765.63", "2781.25", "2796.88", "2812.5", "2828.13",
"2843.75", "2859.38", "2875", "2890.63", "2906.25", "2921.88",
"2937.5", "2953.13", "2968.75", "2984.38", "3000", "3015.63",
"3031.25", "3046.88", "3062.5", "3078.13", "3093.75", "3109.38",
"3125", "3140.63", "3156.25", "3171.88", "3187.5", "3203.13",
"3218.75", "3234.38", "3250", "3265.63", "3281.25", "3296.88",
"3312.5", "3328.13", "3343.75", "3359.38", "3375", "3390.63",
"3406.25", "3421.88", "3437.5", "3453.13", "3468.75", "3484.38",
"3500", "3515.63", "3531.25", "3546.88", "3562.5", "3578.13",
"3593.75", "3609.38", "3625", "3640.63", "3656.25", "3671.88",
"3687.5", "3703.13", "3718.75", "3734.38", "3750", "3765.63",
"3781.25", "3796.88", "3812.5", "3828.13", "3843.75", "3859.38",
"3875", "3890.63", "3906.25", "3921.88", "3937.5", "3953.13",
"3968.75", "3984.38", "4000", "4015.63", "4031.25", "4046.88",
"4062.5", "4078.13", "4093.75", "4109.38", "4125", "4140.63",
"4156.25", "4171.88", "4187.5", "4203.13", "4218.75", "4234.38",
"4250", "4265.63", "4281.25", "4296.88", "4312.5", "4328.13",
"4343.75", "4359.38", "4375", "4390.63", "4406.25", "4421.88",
"4437.5", "4453.13", "4468.75", "4484.38", "4500", "4515.63",
"4531.25", "4546.88", "4562.5", "4578.13", "4593.75", "4609.38",
"4625", "4640.63", "4656.25", "4671.88", "4687.5", "4703.13",
"4718.75", "4734.38", "4750", "4765.63", "4781.25", "4796.88",
"4812.5", "4828.13", "4843.75", "4859.38", "4875", "4890.63",
"4906.25", "4921.88", "4937.5", "4953.13", "4968.75", "4984.38",
"5000", "5015.63", "5031.25", "5046.88", "5062.5", "5078.13",
"5093.75", "5109.38", "5125", "5140.63", "5156.25", "5171.88",
"5187.5", "5203.13", "5218.75", "5234.38", "5250", "5265.63",
"5281.25", "5296.88", "5312.5", "5328.13", "5343.75", "5359.38",
"5375", "5390.63", "5406.25", "5421.88", "5437.5", "5453.13",
"5468.75", "5484.38", "5500", "5515.63", "5531.25", "5546.88",
"5562.5", "5578.13", "5593.75", "5609.38", "5625", "5640.63",
"5656.25", "5671.88", "5687.5", "5703.13", "5718.75", "5734.38",
"5750", "5765.63", "5781.25", "5796.88", "5812.5", "5828.13",
"5843.75", "5859.38", "5875", "5890.63", "5906.25", "5921.88",
"5937.5", "5953.13", "5968.75", "5984.38", "6000", "6015.63",
"6031.25", "6046.88", "6062.5", "6078.13", "6093.75", "6109.38",
"6125", "6140.63", "6156.25", "6171.88", "6187.5", "6203.13",
"6218.75", "6234.38", "6250", "6265.63", "6281.25", "6296.88",
"6312.5", "6328.13", "6343.75", "6359.38", "6375", "6390.63"
)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.