R/util.R

In raymondben/datavolley: Reading and Analyzing DataVolley Scout Files

## Accumulate messages for later display
## Internal function, not exported
## severity: 1 = critical
##           2 = informative, may lead to misinterpretation of data
##           3 = minor, esp. those that might have resulted from selective post-processing of combo codes
collect_messages <- function(msgs, msg_text, line_nums, raw_lines, severity, fatal = FALSE, xraw) {
    if (missing(line_nums)) line_nums <- NULL
    if (missing(severity)) severity <- NULL
    if (is.data.frame(msg_text)) {
        if (is.null(line_nums) || all(is.na(line_nums))) line_nums <- msg_text$line_number
        if (is.null(severity) || all(is.na(severity))) severity <- msg_text$severity
        msg_text <- msg_text$message
    }
    n <- length(msg_text)
    if (is.null(line_nums)) line_nums <- rep(NA_integer_, n)
    if (missing(raw_lines)) {
        raw_lines <- rep(NA_character_, n)
        if (!missing(xraw)) {
            raw_lines[!is.na(line_nums)] <- xraw[line_nums[!is.na(line_nums)]]
        }
    }
    if (is.null(severity)) severity <- NA_integer_
    if (length(severity) == 1 & n > 1) severity <- rep(severity, n)
    vt <- rep(NA_real_, n)
    if (!all(is.na(raw_lines))) vt <- video_time_from_raw(raw_lines)
    raw_lines[is.na(raw_lines)] <- "[unknown]"
    if (fatal) {
        lnt <- as.character(line_nums)
        lnt[is.na(lnt)] <- "[unknown]"
        txt <- paste0("line ", lnt, ": ", msg_text, " (line in file is: \"", raw_lines, "\")")
        if (fatal) stop(paste(txt, collapse = " / "))
    } else {
        msgs[[length(msgs)+1]] <- list(file_line_number = line_nums, video_time = vt, message = msg_text, file_line = raw_lines, severity = severity)
    }
    msgs
}

## messages stored as attributes of an object
get_dvmsg <- function(x) attr(x, "dvmessages", exact = TRUE)
set_dvmsg <- function(x, msg) {
    attr(x, "dvmessages") <- msg
    x
}
has_dvmsg <- function(x) !is.null(get_dvmsg(x)) && nrow(get_dvmsg(x)) > 0
clear_dvmsg <- function(x) set_dvmsg(x, NULL)

## video time from raw line, for datavolley format
raw_vt_dv <- function(z) {
    tryCatch({
        if (!is.null(z) && is.character(z) && nzchar(z) && !is.na(z)) {
            as.numeric(strsplit(z, ";")[[1]][13])
        } else {
            NA_integer_
        }},
        error = function(e) NA_integer_)
}

## video time from raw line, for peranavolley format
pv_pparse <- function(z, df = TRUE) {
    temp <- sub("^[A-Z]+~", "", z)
    if (grepl("^\\(?null\\)?", temp, ignore.case = TRUE)) {
        if (df) tibble() else NULL
    } else {
        jsonlite::fromJSON(temp)
    }
}
raw_vt_pv <- function(z) {
    tryCatch({
        if (!is.null(z) && is.character(z) && nzchar(z) && !is.na(z)) {
            as.numeric(pv_pparse(z)$videoDuration)
        } else {
            NA_integer_
        }
    }, error = function(e) NA_integer_)
}

## video time from raw line, vsm format
## can't guarantee that "lines" in vsm are valid json, because we somewhat-arbitrarily split the single-line input file
raw_vt_vsm <- function(z) {
    tryCatch({
        temp <- str_match_all(z, "\"time\"[[:space:]]*:[[:space:]]*([^,\\}\\]]+)")[[1]][, 2]
        if (length(temp) == 1) round(as.numeric(temp) / 10) else NA_integer_
    }, error = function(e) NA_integer_)
}

raw_vt_xml <- function(z) {
    tryCatch({
        temp <- str_match_all(z, "<start>([[:digit:]\\.]+)</start>")[[1]][, 2]
        if (length(temp) == 1) round(as.numeric(temp)) else NA_integer_
    }, error = function(e) NA_integer_)
}

video_time_from_raw <- function(raw_lines) {
    out <- tryCatch(vapply(raw_lines, function(z) {
        if (grepl("~{", z, fixed = TRUE)) raw_vt_pv(z) else if (grepl("\"_id\":", z, fixed = TRUE)) raw_vt_vsm(z) else if (grepl("<start>[[:digit:]\\.]+</start>", z)) raw_vt_xml(z) else raw_vt_dv(z)
    }, FUN.VALUE = 1.0, USE.NAMES = FALSE), error = function(e) rep(NA_real_, length(raw_lines)))
    if (length(out) < 1) out <- NA_real_
    out
}

join_messages <- function(msgs1,msgs2) {
    if (length(msgs2)>0) {
        msgs1 <- c(msgs1,msgs2)
    }
    msgs1
}

# Extract text chunks from datavolley file. Internal function, not exported for users.
#
# @param txt: dv text
# @param token1: starting token, e.g. "[3SET]"
# @param token2: ending token
#
# @return string
text_chunk <- function(txt,token1,token2) {
    idx1 <- grep(token1,txt,fixed=TRUE)
    if (length(idx1)<1) return("")
    if (missing(token2)) {
        ## find next section starting with "["
        idx2=grep("^\\[",txt)
        idx2=idx2[idx2>idx1][1]
    } else {
        idx2=grep(token2,txt,fixed=TRUE)
    }
    if (idx2==(idx1+1)) {
        ""
    } else {
        out <- txt[(idx1+1):(idx2-1)]
        out <- out[sapply(out,is.notempty.string)]##!is.na(out)]
        paste(out,collapse="\n")
    }
}

is.notempty.string <- function(x) {
    (is.character(x) && length(x)==1) && !is.na(x) && nchar(x)>0
}



#' Find each entry in y that follows each entry in x
#'
#' @param x numeric: vector 
#' @param y numeric: vector 
#'
#' @return vector, each entry is the value in y that is next-largest to each corresponding entry in x
#'
#' @examples
#' findnext(c(1,5,10),c(1,2,3,7,8,9))
#' 
#' @export
findnext <- function(x,y) {
    ## return the number in y that comes after each of x
    sapply(x,function(z){
        temp <- y-z
        temp <- temp[temp>0]
        if (length(temp)<1)
            NA
        else
            min(temp)+z
    })
}

##findnext <- function(these,after) {
##    ## return the number in after that comes after each of these
##    sapply(these,function(z){
##        temp <- after-z
##        temp <- temp[temp>0]
##        if (length(temp)<1)
##            NA
##        else
##            min(temp)+z
##    })
##}


#' Find each entry in y that precedes each entry in x
#'
#' @param x numeric: vector 
#' @param y numeric: vector 
#'
#' @return vector, each entry is the value in y that is next-smallest to each corresponding entry in x
#'
#' @examples
#' findprev(c(1,5,10),c(1,2,3,7,8,9))
#' 
#' @export
findprev <- function(x,y) {
    ## return the number in y that comes before each of x
    sapply(x,function(z){
        temp <- z-y
        temp <- temp[temp>0]
        if (length(temp)<1)
            NA
        else
            z-min(temp)
    })
}


##findprev <- function(these,prev) {
##    ## return the number in prev that comes before each of these
##    sapply(these,function(z){
##        temp <- z-prev
##        temp <- temp[temp>0]
##        if (length(temp)<1)
##            NA
##        else
##            z-min(temp)
##    })
##}


## equality with NAs considered false
`%eq%` <- function(x,y) x==y & !is.na(x) & !is.na(y)

## convenience function to replace NAs
na.replace <- function(x,replace_with) {x[is.na(x)] <- replace_with; x}


#' Find a particular match in a list of datavolley objects
#'
#' @param match_id string: match_id to find
#' @param x list: list of datavolley objects as returned by \code{dv_read} 
#'
#' @return numeric index of the match in the list
#'
#' @seealso \code{\link{dv_read}}
#'
#' @export
find_match <- function(match_id,x) {
    which(sapply(x,function(z)z$meta$match_id==match_id))
}


most_common_value <- function(x) {
    ux <- unique(x)
    ux[which.max(tabulate(match(x, ux)))]
}

## preferred can have more than one entry, treated in order of preference
## parse datetimes and dates, removing any that resolve to future
parse_dt <- function(dstr, format, allow_future_dates = FALSE) {
    out <- unique(na.omit(c(lubridate::parse_date_time(dstr, format))))
    if (!allow_future_dates) out <- out[difftime(Sys.time(), out, units = "days") > -5] ## not more than 5 days into the future
    out
}

parse_d <- function(dstr, pfun, allow_future_dates = FALSE) {
    out <- pfun(dstr)
    if (!allow_future_dates) out <- out[difftime(Sys.time(), out, units = "days") > -5] ## not more than 5 days into the future
    out
}

manydates <- function(z, preferred = NULL) {
    z <- z[!is.na(z) & nzchar(z)]
    if (length(z) < 1) return(as.Date(integer(), origin = "1970-01-01"))
    suppressWarnings(
        tries <- list(ymd = unique(as.Date(na.omit(c(parse_d(z, lubridate::ymd), parse_dt(z, "Ymd HMS"))))),
                      dmy = unique(as.Date(na.omit(c(parse_d(z, lubridate::dmy), parse_dt(z, "dmY HMS"))))),
                      mdy = unique(as.Date(na.omit(c(parse_d(z, lubridate::mdy), parse_dt(z, "mdY HMS"))))))
    )
    if (!is.null(preferred)) {
        preferred <- tolower(preferred)
        for (pref in preferred) {
            if (length(tries[[pref]]) > 0) return(tries[[pref]])
        }
    }
    if (length(tries$ymd) < 1 && length(tries$dmy) < 1 && length(tries$mdy) < 1) return(as.Date(integer(), origin = "1970-01-01"))
    unique(c(tries$ymd, tries$dmy, tries$mdy))
}

manydatetimes <- function(z, preferred = NULL) {
    z <- z[!is.na(z) & nzchar(z)]
    if (length(z) < 1) return(as.POSIXct(integer(), origin = "1970-01-01"))
    ## don't use lubridate::ymd_hms etc here, because they will fall foul of e.g.
    ##  https://github.com/tidyverse/lubridate/issues/552
    suppressWarnings(tries <- list(ymd = parse_dt(z, "Ymd HMS"), dmy = parse_dt(z, "dmY HMS"), mdy = parse_dt(z, "mdY HMS")))
    if (!is.null(preferred)) {
        preferred <- tolower(preferred)
        for (pref in preferred) {
            if (length(tries[[pref]]) > 0) return(tries[[pref]])
        }
    }
    if (length(tries$ymd) < 1 && length(tries$dmy) < 1 && length(tries$mdy) < 1) return(as.POSIXct(integer(), origin = "1970-01-01"))
    unique(c(tries$ymd, tries$dmy, tries$mdy))
}

unambiguous_datetime <- function(z) {
    suppressWarnings(tries <- list(ymd = parse_dt(z, format = "Ymd HMS"), dmy = parse_dt(z, format = "dmY HMS"), mdy = parse_dt(z, format = "mdY HMS")))
    ## do we have an unambiguous date? i.e. only one format gives a valid date
    unambiguous <- Filter(length, tries)
    unambiguous <- unique(data.frame(format = names(unambiguous), date = as.Date(as.numeric(unambiguous), origin = "1970-01-01"), stringsAsFactors = FALSE))
    if (nrow(unambiguous) == 1) unambiguous$format else NULL
}

#' Generate a short, human-readable text summary of one or more actions
#'
#' @param x data.frame or tibble: one or more rows from a datavolleyplays object as returned by \code{\link{dv_read}}
#' @param verbosity integer: 1 = least verbose, 2 = more verbose. Currently ignored
#'
#' @return character vector
#'
#' @examples
#' x <- dv_read(dv_example_file())
#' dv_action2text(plays(x)[27:30, ])
#'
#' @export
dv_action2text <- function(x, verbosity = 1) {
    vapply(seq_len(nrow(x)), function(i) do_action2text(x[i, ], verbosity = verbosity), FUN.VALUE = "", USE.NAMES = FALSE)
}

do_action2text <- function(x, verbosity) {
    if (x$skill %in% c("Serve", "Reception", "Set", "Attack", "Block", "Dig", "Freeball")) {
        out <- paste0(skill_extra(x), " by ", x$player_name, " (",
                      action_extra(x),
                      x$evaluation, ")")
    } else if (x$skill %in% c("Timeout")) {
        paste0("Timeout (", x$team, ")")
    } else if (x$skill %in% c("Technical timeout")) {
        "Technical timeout"
    } else {
        NA_character_
    }
}

skill_extra <- function(x) {
    if (x$skill %in% c("Attack", "Serve") && !is.na(x$skill_type)) x$skill_type else x$skill
}
action_extra <- function(x) {
    switch(x$skill,
           "Attack" = if (!is.na(x$attack_code)) paste0(x$attack_code, " - ") else "",
           "")
}

## replacement for enc::read_lines_enc now that enc has been archived Feb 2024
read_lines_enc <- function(path, file_encoding = "UTF-8") {
    con <- file(path, encoding = file_encoding)
    on.exit(close(con), add = TRUE)
    lines <- readLines(con, warn = FALSE, n = -1L, ok = TRUE, skipNul = FALSE, encoding = "UTF-8")
    Encoding(lines) <- "UTF-8"
    stringi::stri_enc_toutf8(lines)
}

get_best_encodings <- function(encodings_to_test, filename, read_from = 10, read_to = 90, expect_tildes = TRUE) {
    if (read_to < read_from) stop("read_to cannot be less than read_from")
    ## badchars/badwords indicate characters/words that we don't expect to see, so the presence of any of these indicates that we've got the wrong file encoding
    badchars <- c(1328:7499, utf8ToInt("\ub3\ua3\u008a\u008e\u009a\u00b3"), 960) ## armenian through to music, then some isolated ones
    ## allow 1025:1327 - cyrillic
    ## may need to consider removing penalty on armenian/arabic chars too
    ## 0x2000 to 0x206f (general punctuation) likely wrong, 0x01-0x07 are control characters we don't expect to see
    badchars <- c(badchars,0x2000:0x206f, 0x00:0x07)
    badchars <- c(badchars, utf8ToInt("\u253c\ud7\u3ad")) ##?? \u44d\u42d
    badchars <- c(badchars, 0x2500:0x25ff) ## box-drawing characters (seen with Japanese misidentified as Korean)
    badwords <- tolower(c("S\u159RENSEN","S\u159gaard","S\u159ren","M\u159LLER","Ish\u159j","Vestsj\u107lland","KJ\u107R","M\u159rk","Hj\u159rn","\u139rhus")) ## these from windows-1252 (or ISO-8859-1) wrongly guessed as windows-1250
    badwords <- c(badwords,tolower(c("\ud9ukas","Pawe\uf9","\ud9omacz",paste0("Mo\ufd","d\ufdonek"),"W\uf9odarczyk"))) ## these from windows-1257/ISO-8859-13 wrongly guessed as windows-1252
    badwords <- c(badwords,tolower(c("\u3a9ukas","Pawe\u3c9","\u3a9omacz",paste0("Mo\u3cd","d\u3cdonek"),"W\u3c9odarczyk"))) ## these from windows-1257/ISO-8859-13 wrongly guessed as windows-1253
    badwords <- c(badwords,tolower(c("\uc4\u15a","\u139\u2dd"))) ## utf-8 wrongly guessed as windows-1250
    badwords <- c(badwords, tolower(c("\uc4\u8d", "\uc5\ubd", "\uc4\u152"))) ## utf-8 wrongly guessed as windows-1252
    badwords <- c(badwords,tolower(c("Nicol\u148"))) ## windows-1252/iso-8859-1 wrongly guessed as windows-1250
    badwords <- c(badwords, c("\u6c\u2116", "\u6a\u2116", "\u77\u2116", "\u64\u2116\u62", "\u45a\u77", "\u45a\u6c", "\u63\u7a\u43a")) ## windows-1250 wrongly guessed as windows-1251
    badwords <- c(badwords, tolower(c("\u6a\u446\u72", "\u68\u446\u68", "\u76\u446\u6c", "\u6d\u44c\u6c", "\u72\u44c\u67", "\u70\u446\u68", "\u6b\u44c\u68"))) ## 1250 as 1251
    badwords <- c(badwords, tolower(c("\uc2\ue4\u77", "\uf1\u7b", "\ue5\ue4", "\ue5\ue3"))) ## japanese SHIFT-JIS wrongly guessed as macintosh
    badwords <- c(badwords, tolower("\u102\u104\u7a"), tolower("\u102\u104\u73"), tolower("\u102\u2c7\u7a"), tolower("\u102\u2c7\u73"))
    badwords <- c(badwords, tolower(c(intToUtf8(c(8222, 162)))))
    badwords <- c(badwords, tolower(c("\u192\u56", "\u192\u2021", "\u192\u67", "\u192\u6f", "\u192\u62", "\u192\u4e", "\u2018\u4f", "\u192\u70", "\u192\u43", "\u192\u76")))
    badwords <- c(badwords, tolower(c("\uf7\u119\uee", "\u2d9\u119\uee", "\uf7\u155\u111", "\uf7\u10d\ued", "\uc2\ueb\u155\ue4\u10d", "\u10f\u10d\uee", "\u10f\u13a\u111", "\u155\u148\uf7"))) ## russian 1251 wrongly detected as 1250
    badwords <- c(badwords, tolower(c("\ue8\ueb\ueb", "\ueb\uea", "\ue4\ue0", "\ue0\ue2", "\ue0\ue5", "\ue5\ue2", "\ued\uee", "\uee\uef", "\udf\uea", "\u1fb\uef\ue8", "\uee\ued\ue0", "\uee\uf1\uf1", "\uf1\uf1\ue8"))) ## russian 1251 wrongly detected as 1258
    badwords <- c(badwords, tolower(c("\u101\ue5", "\ue5\u101", "\u107\u10d", "\ud7\ue5", "\u122\u10d"))) ## russian 1251 wrongly detected as 1257
    ##badwords <- c(badwords, tolower(c("\u10f\u17c\u2dd", "\u43f\u457\u405", "\u3bf\u38f\ubd", "\u5df\ubf\ubd"))) ## this is the unicode replacement char EF BF BD in windows-1250, 1251, 1253 (the encoding should be UTF-8). Note that 1252, 1254 seem to represent this as EF BF BD, so we can't detect that?? Doesn't seem to be reliable anyway
    badwords <- c(badwords, tolower(c("\u56\u49\u444", "\u56\u49\uc6"))) ## windows-1252 wrongly detected as KOI8-R
    badwords <- c(badwords, tolower(c("\u171\ufc", "\u8e\u52"))) ## cp932 wrongly detected as ISO-8859-2 (there are heaps here)
    badwords <- c(badwords, tolower(c("\uc9\u57\uc9", "\ue2\u2122"))) ## cp932 wrongly detected as macintosh
    badwords <- c(badwords, c("\ufd\u79")) ## windows-1254 wrongly detected as 1250
    badwords <- c(badwords, c("\u6e\u434\u45a\u69\u434\u45a", "\u76\u69\u434\u45a")) ## "ncic" and "vic" but c with caron (Serbian/Czech/etc) wrongly detected as cyrillic
    badwords_trans <- c("oooo", "ouuoo", "oouoo", "uuou", "uuoo") ## badwords after transliteration, e.g. wrongly-detected cyrillic
    ## get the \uxx numbers from sprintf("%x",utf8ToInt(tolower(dodgy_string_or_char))) or paste0("\\u", sprintf("%x", utf8ToInt(tolower("dodgy"))), collapse = "")
    read_with_enc <- function(filename, enc_to_test) {
        ## read with specified encoding and convert to UTF8
        tryCatch(read_lines_enc(filename, file_encoding = enc_to_test), warning = function(w) NA_character_, error = function(e) NA_character_)
    }
    testtxt <- lapply(encodings_to_test, read_with_enc, filename = filename)
    suppressWarnings({
        encerrors <- sapply(testtxt, function(z) {
            z <- paste(z[read_from:read_to], collapse = "")
            if (is.na(z)) Inf else sum(utf8ToInt(z) %in% badchars) + 10*sum(sapply(badwords, grepl, tolower(z), fixed = TRUE)) + 10*(sum(sapply(badwords_trans, grepl, stri_trans_general(tolower(z), "latin-ascii"), fixed = TRUE)) - sum(sapply(badwords_trans, grepl, tolower(z), fixed = TRUE)))
            ## the latter term penalizes text that matches badwords_trans when transliterated to ASCII but doesn't match when not transliterated. Which will generally be streams of gibberish accented characters (e.g. Cyrillic processed as something else)
        })
    })
    if (expect_tildes) {
        ## also check whether we get ~'s in the 3SCOUT section (will not get any if CP932 incorrectly detected as SHIFT-JIS, for example)
        tilde_count <- sapply(testtxt, function(z) if (all(is.na(z))) 0L else sum(stringi::stri_count(z, fixed = "~")))
        encerrors[which(tilde_count < 1)] <- encerrors[which(tilde_count < 1)] + 20L
    }
    ## what badwords are matching a given encoding?
    ##cat("bw:\n")
    ##print(lapply(testtxt[encodings_to_test == "CP1251"], function(z) if (all(is.na(z))) Inf else { z <- paste(z[read_from:read_to], collapse = ""); print(z); which(sapply(badwords, grepl, tolower(z), fixed = TRUE))}))
    ## errors per encodings_to_test
    ##cat("encerrors:\n"); print(sort(setNames(encerrors, encodings_to_test)))
    idx <- encerrors==min(encerrors)
    if (!any(idx)) {
        list(encodings = character(), error_score = NA_integer_)
    } else {
        list(encodings = encodings_to_test[idx], error_score = min(encerrors))
    }
}

#' Convert integer colour to RGB
#'
#' DataVolley files use an integer representation of colours. These functions convert to and from hex colour strings as used in R.
#'
#' @param z integer: vector of integers
#' @param x integer: vector of hex colour strings
#'
#' @return Character vector of hex RGB colour strings
#'
#' @examples
#' dv_int2rgb(c(255, 16711680))
#'
#' @export
dv_int2rgb <- function(z) {
    r <- floor(z / 256^2)
    g <- floor((z - r * (256^2)) / 256)
    b <- z - floor(r * (256^2) + g * 256)
    out <- apply(cbind(r, g, b), 1, function(z) sprintf("#%02X%02X%02X", z[1], z[2], z[3]))
    out[z < 0 | z > 16777215 | is.na(z)] <- NA_character_
    out
}

#' @export
#' @rdname dv_int2rgb
dv_rgb2int <- function(x) {
    out <- grDevices::col2rgb(x)
    out <- as.integer(apply(out, 2, function(z) z[1] * 256 * 256 + z[2] * 256 + z[3]))
    out[is.na(x)] <- NA_integer_
    out
}

camel_to_underscore <- function(x) {
    s <- gsub("([a-z0-9])([A-Z])", "\\1_\\L\\2", x, perl = TRUE)
    sub("^(.[a-z])", "\\L\\1", s, perl = TRUE) # make 1st char lower case if second is lower
}

lead0 <- function(x, width = 2, pad = "0", na = NULL) {
    out <- character(length(x))
    naidx <- rep(FALSE, length(x))
    if (!is.null(na)) {
        naidx <- is.na(x) | !nzchar(x)
        out[naidx] <- as.character(na)
    }
    out[!naidx] <- stringr::str_pad(as.numeric(x[!naidx]), width = width, pad = pad)
    out
}

rotpos <- function(p, by = 1L, n = 6L) (p - 1L - by) %% n + 1L
rot_lup <- function(z, by = 1L, n = 6L) {
    ## z is a lineup vector
    z[rotpos(seq_along(z), by = by, n = n)]
}

## mapvalues from plyr, MIT license
mapvalues <- function (x, from, to, warn_missing = TRUE) {
    if (length(from) != length(to)) {
        stop("`from` and `to` vectors are not the same length.")
    }
    if (!is.atomic(x) && !is.null(x)) {
        stop("`x` must be an atomic vector or NULL.")
    }
    if (is.factor(x)) {
        levels(x) <- mapvalues(levels(x), from, to, warn_missing)
        return(x)
    }
    mapidx <- match(x, from)
    mapidxNA <- is.na(mapidx)
    from_found <- sort(unique(mapidx))
    if (warn_missing && length(from_found) != length(from)) {
        message("The following `from` values were not present in `x`: ", 
            paste(from[!(1:length(from) %in% from_found)], collapse = ", "))
    }
    x[!mapidxNA] <- to[mapidx[!mapidxNA]]
    x
}

single_unique_value_or_na_int <- function(x) {
    u <- unique(na.omit(x))
    if (length(u) == 1) u else NA_integer_
}

mean_nna <- function(...) mean(..., na.rm = TRUE)
qmax <- function(...) suppressWarnings(max(..., na.rm = TRUE))
qmin <- function(...) suppressWarnings(min(..., na.rm = TRUE))