Nothing
R/recode_replace.R
In collapse: Advanced and Fast Data Transformation
Defines functions
pad
pad_atomic
replace_outliers
mad_trans
mad_limits
sd_limits
Crepoutl
replace_inf
replace_na
na_focb_ph
na_locf_ph
na_focb
na_locf
recode_char
recode_num
scv
Documented in
na_focb
na_locf
pad
recode_char
recode_num
replace_inf
replace_na
replace_outliers
# Note: don't change the order of these arguments !!!
scv <- function(x, v, r, set = FALSE, inv = FALSE, vind1 = FALSE) .Call(C_setcopyv, x, v, r, inv, set, vind1)
# inspired by ?dplyr::recode
# Think about adopting this code for as_numeric_factor and as_character_factor
recode_num <- function(X, ..., default = NULL, missing = NULL, set = FALSE) {
if(missing(...)) stop("recode_num requires arguments of the form: value = replacement")
args <- list(...)
nam <- as.numeric(names(args))
# nzchar(names(args)) ... check non-empty names ? -> nah, this package is not for dummies
if(anyNA(nam)) stop(paste("Non-numeric arguments:", paste(names(args)[is.na(nam)], collapse = ", ")))
arglen <- length(args)
missingl <- !is.null(missing)
if(missingl && any(nam == missing)) warning(paste0("To improve performance missing values are replaced prior to recode, so this replaces all missing values with ",
missing, " and those are then again replaced with ", args[[which(nam == missing)]], ". If this is not desired, call replace_na after recode with missing = NULL."))
if(arglen == 1L) {
args <- args[[1L]]
if(is.null(default)) {
if(missingl) {
repfun <- function(y) if(is.numeric(y)) {
z <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
scv(z, nam, args, TRUE) # `[<-`(y, y == nam, value = args)
} else y
} else {
repfun <- function(y) if(is.numeric(y)) scv(y, nam, args, set) else y # `[<-`(y, y == nam, value = args)
}
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.numeric(y)) {
nas <- is.na(y)
z <- scv(y, nas, missing, set, vind1 = TRUE)
ind <- whichv(z, nam)
scv(z, nas, default, TRUE, TRUE, vind1 = TRUE) # duplAttributes(alloc(default, nr), y)
scv(z, ind, args, TRUE, vind1 = TRUE) # y == nam
} else y
} else {
repfun <- function(y) if(is.numeric(y)) scv(scv(y, nam, default, set, TRUE), nam, args, TRUE) else y # `[<-`(duplAttributes(alloc(default, nr), y), y == nam, value = args)
}
}
} else {
seqarg <- seq_len(arglen)
if(is.null(default)) {
repfun <- function(y) if(is.numeric(y)) {
if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
else if(!set) y <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
# repfun <- function(y) if(is.numeric(y)) {
# if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
# if(set) { # Note: not strictly the way this should work...
# for(i in seqarg) scv(y, nam[i], args[[i]], TRUE)
# return(y)
# }
# z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
# for(i in seqarg) scv(z, whichv(y, nam[i]), args[[i]], TRUE, vind1 = TRUE)
# z
# } else y
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.numeric(y)) {
nas <- is.na(y)
y <- scv(y, nas, missing, set, vind1 = TRUE)
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
scv(y, nas, default, TRUE, TRUE, vind1 = TRUE)
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
repfun <- function(y) if(is.numeric(y)) {
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
y <- scv(y, nam[1L], default, set, TRUE) # duplAttributes(alloc(default, nr), y)
scv(y, nam[1L], args[[1L]], TRUE)
for(i in seqarg[-1L]) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
}
}
}
if(is.list(X)) {
if(set) {
lapply(unattrib(X), repfun)
return(invisible(X))
}
res <- duplAttributes(lapply(unattrib(X), repfun), X)
return(if(inherits(X, "data.table")) alc(res) else res)
}
if(!is.numeric(X)) stop("X needs to be numeric or a list")
res <- repfun(X)
return(if(set) invisible(res) else res)
}
recode_char <- function(X, ..., default = NULL, missing = NULL, regex = FALSE,
ignore.case = FALSE, fixed = FALSE, set = FALSE) {
if(missing(...)) stop("recode_char requires arguments of the form: value = replacement")
args <- list(...)
nam <- names(args)
arglen <- length(args)
missingl <- !is.null(missing)
if(missingl && any(nam == missing)) warning(paste0("To improve performance missing values are replaced prior to recode, so this replaces all missing values with ",
missing, " and those are then again replaced with ", args[[which(nam == missing)]], ". If this is not desired, call replace_na after recode with missing = NULL."))
if(regex) {
if(arglen == 1L) {
args <- args[[1L]]
if(is.null(default)) {
if(missingl) {
repfun <- function(y) if(is.character(y)) {
y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
scv(y, grepl(nam, y, ignore.case, FALSE, fixed), args, TRUE, vind1 = TRUE)
} else y
} else {
repfun <- function(y) if(is.character(y)) scv(y, grepl(nam, y, ignore.case, FALSE, fixed), args, set, vind1 = TRUE) else y
}
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
z <- scv(y, nas, missing, set, vind1 = TRUE)
ind <- grepl(nam, z, ignore.case, FALSE, fixed)
scv(z, nas, default, TRUE, TRUE, vind1 = TRUE) # duplAttributes(alloc(default, nr), y)
scv(z, ind, args, TRUE, vind1 = TRUE)
} else y
} else {
repfun <- function(y) if(is.character(y)) {
ind <- grepl(nam, y, ignore.case, FALSE, fixed)
scv(scv(y, ind, default, set, TRUE, vind1 = TRUE), ind, args, TRUE, vind1 = TRUE)
} else y
}
}
} else {
seqarg <- seq_len(arglen)
if(is.null(default)) {
repfun <- function(y) if(is.character(y)) {
if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
else if(!set) y <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
for(i in seqarg) scv(y, grepl(nam[i], z, ignore.case, FALSE, fixed), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
y <- scv(y, nas, missing, set, vind1 = TRUE)
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
scv(y, nas, default, TRUE, TRUE, vind1 = TRUE)
for(i in seqarg) scv(y, grepl(nam[i], z, ignore.case, FALSE, fixed), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
repfun <- function(y) if(is.character(y)) {
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
y <- scv(y, seq_along(y), default, set, vind1 = TRUE) # Initialize all to default
for(i in seqarg) scv(y, grepl(nam[i], z, ignore.case, FALSE, fixed), args[[i]], TRUE, vind1 = TRUE)
y
} else y
}
}
}
} else {
if(arglen == 1L) {
args <- args[[1L]]
if(is.null(default)) {
if(missingl) {
repfun <- function(y) if(is.character(y)) {
z <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
scv(z, nam, args, TRUE) # `[<-`(y, y == nam, value = args)
} else y
} else {
repfun <- function(y) if(is.character(y)) scv(y, nam, args, set) else y # `[<-`(y, y == nam, value = args)
}
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
z <- scv(y, nas, missing, set, vind1 = TRUE)
ind <- whichv(z, nam)
scv(z, nas, default, TRUE, TRUE, vind1 = TRUE) # duplAttributes(alloc(default, nr), y)
scv(z, ind, args, TRUE, vind1 = TRUE) # y == nam
} else y
} else {
repfun <- function(y) if(is.character(y)) scv(scv(y, nam, default, set, TRUE), nam, args, TRUE) else y # `[<-`(duplAttributes(alloc(default, nr), y), y == nam, value = args)
}
}
} else {
seqarg <- seq_len(arglen)
if(is.null(default)) {
repfun <- function(y) if(is.character(y)) {
if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
else if(!set) y <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
y <- scv(y, nas, missing, set, vind1 = TRUE)
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
scv(y, nas, default, TRUE, TRUE, vind1 = TRUE)
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
repfun <- function(y) if(is.character(y)) {
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
y <- scv(y, nam[1L], default, set, TRUE) # duplAttributes(alloc(default, nr), y)
scv(y, nam[1L], args[[1L]], TRUE)
for(i in seqarg[-1L]) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
}
}
}
}
if(is.list(X)) {
if(set) {
lapply(unattrib(X), repfun)
return(invisible(X))
}
res <- duplAttributes(lapply(unattrib(X), repfun), X)
return(if(inherits(X, "data.table")) alc(res) else res)
}
if(!is.character(X)) stop("X needs to be character or a list")
res <- repfun(X)
return(if(set) invisible(res) else res)
}
na_locf <- function(x, set = FALSE) .Call(C_na_locf, x, set)
na_focb <- function(x, set = FALSE) .Call(C_na_focb, x, set)
na_locf_ph <- function(x, ph1, ph2, set = FALSE) .Call(C_na_locf, x, set)
na_focb_ph <- function(x, ph1, ph2, set = FALSE) .Call(C_na_focb, x, set)
replace_na <- function(X, value = 0L, cols = NULL, set = FALSE, type = "const") {
FUN <- switch(type, const =, value = scv, locf = na_locf_ph, focb = na_focb_ph,
stop("Unknown type:", type))
if(set) {
if(is.list(X)) {
if(is.null(cols)) {
lapply(unattrib(X), FUN, NA, value, TRUE)
} else if(is.function(cols)) {
lapply(unattrib(X), function(y) if(cols(y)) FUN(y, NA, value, TRUE) else y)
} else {
cols <- cols2int(cols, X, attr(X, "names"), FALSE)
lapply(unattrib(X)[cols], FUN, NA, value, TRUE)
}
} else FUN(X, NA, value, TRUE) # `[<-`(X, is.na(X), value = value)
return(invisible(X))
}
if(is.list(X)) {
if(is.null(cols)) return(condalc(duplAttributes(lapply(unattrib(X), FUN, NA, value), X), inherits(X, "data.table"))) # function(y) `[<-`(y, is.na(y), value = value)
if(is.function(cols)) return(condalc(duplAttributes(lapply(unattrib(X),
function(y) if(cols(y)) FUN(y, NA, value) else y), X), inherits(X, "data.table")))
clx <- oldClass(X)
oldClass(X) <- NULL
cols <- cols2int(cols, X, names(X), FALSE)
X[cols] <- lapply(unattrib(X[cols]), FUN, NA, value) # function(y) `[<-`(y, is.na(y), value = value)
return(condalc(`oldClass<-`(X, clx), any(clx == "data.table")))
}
FUN(X, NA, value) # `[<-`(X, is.na(X), value = value)
}
replace_NA <- replace_na
# Remove Inf (Infinity) and NaN (Not a number) from vectors or data frames:
replace_inf <- function(X, value = NA, replace.nan = FALSE, set = FALSE) {
if(set) {
if(is.list(X)) {
lapply(unattrib(X), if(replace.nan) (function(y) if(is.numeric(y)) scv(y, is.infinite(y) | is.nan(y), value, TRUE, vind1 = TRUE) else y) else
(function(y) if(is.numeric(y)) scv(y, is.infinite(y), value, TRUE, vind1 = TRUE) else y))
}
if(!is.numeric(X)) stop("Infinite values can only be replaced in numeric objects!")
if(replace.nan) scv(X, is.infinite(X) | is.nan(X), value, TRUE, vind1 = TRUE) else scv(X, is.infinite(X), value, TRUE, vind1 = TRUE)
return(invisible(X))
}
if(is.list(X)) {
# if(!inherits(X, "data.frame")) stop("replace_non_finite only works with atomic objects or data.frames")
res <- duplAttributes(lapply(unattrib(X),
if(replace.nan) (function(y) if(is.numeric(y)) scv(y, is.infinite(y) | is.nan(y), value, vind1 = TRUE) else y) else
(function(y) if(is.numeric(y)) scv(y, is.infinite(y), value, vind1 = TRUE) else y)), X)
return(if(inherits(X, "data.table")) alc(res) else res)
}
if(!is.numeric(X)) stop("Infinite values can only be replaced in numeric objects!")
if(replace.nan) return(scv(X, is.infinite(X) | is.nan(X), value, vind1 = TRUE)) # !is.finite(X) also replaces NA
scv(X, is.infinite(X), value, vind1 = TRUE)
}
replace_Inf <- replace_inf
# replace_non_finite <- function(X, value = NA, replace.nan = TRUE) {
# .Deprecated("replace_Inf")
# replace_Inf(X, value, replace.nan)
# }
Crepoutl <- function(x, limits, value, single_limit, set = FALSE) .Call(C_replace_outliers, x, limits, value, single_limit, set)
sd_limits <- function(x, limits) {
st <- fbstatsCpp(x, stable.algo = FALSE, setn = FALSE)
st[2L] + st[3L] * c(-limits, limits)
}
mad_limits <- function(x, limits) {
med <- fmedian.default(x)
mad <- fmedian.default(abs(x - med))
med + mad * c(-limits, limits)
}
# scaling data using MAD
mad_trans <- function(x) {
if(inherits(x, c("pseries", "pdata.frame"))) {
g <- GRP(x)
tmp <- fmedian(x, g, TRA = "-")
tmp %/=% fmedian(if(is.list(tmp)) lapply(tmp, abs) else abs(tmp), g, TRA = "fill", set = TRUE)
return(tmp)
}
tmp <- fmedian(x, TRA = "-")
tmp %/=% fmedian(if(is.list(tmp)) dapply(tmp, abs) else abs(tmp), TRA = "fill", set = TRUE)
return(tmp)
}
replace_outliers <- function(X, limits, value = NA,
single.limit = c("sd", "mad", "min", "max"),
ignore.groups = FALSE,
set = FALSE) {
if(length(limits) == 1L) {
# "overall_" arguments are legacy, now accommodated via the ignore.groups argument
sl <- switch(single.limit[1L], SDs = 4L, min = 2L, max = 3L,
overall_SDs = 5L, sd = 4L, mad = 6L,
MADs = 6L, overall_MADs = 7L, # Just in case
stop("Unknown single.limit option: ", single.limit[1L]))
if(sl == 5L || sl == 7L) ignore.groups <- TRUE
} else sl <- 0L
if(sl > 3L) { # Outliers according to standard deviation or MAD threshold
if(is.list(X)) {
if(!ignore.groups && inherits(X, c("grouped_df", "pdata.frame"))) {
if(is.character(value)) stop("clipping is not yet supported with grouped/panel data and SDs/MADs thresholds.")
num <- .Call(C_vtypes, X, 1L) # vapply(unattrib(X), is.numeric, TRUE)
num <- if(inherits(X, "grouped_df")) num & !fgroup_vars(X, "logical") else
num & attr(findex(X), "names") %!in% attr(X, "names")
clx <- oldClass(X)
STDXnum <- if(sl > 5L) mad_trans(fcolsubset(X, num)) else fscale(fcolsubset(X, num))
oldClass(X) <- NULL
res <- .mapply(function(z, y) scv(z, abs(y) > limits, value, set, vind1 = TRUE),
list(unattrib(X[num]), unattrib(STDXnum)), NULL)
if(set) return(invisible(X))
X[num] <- res
res <- `oldClass<-`(X, clx)
} else {
limit_fun <- if(sl > 5L) mad_limits else sd_limits
res <- lapply(unattrib(X), function(y) if(is.numeric(y)) Crepoutl(y, limit_fun(y, limits), value, sl, set) else y)
if(set) return(invisible(X))
res <- duplAttributes(res, X)
}
return(if(inherits(res, "data.table")) alc(res) else res)
}
if(is.matrix(X)) {
if(is.character(value)) stop("clipping is not yet supported with matrices and SDs/MADs thresholds.")
res <- scv(X, abs(if(sl > 5L) mad_trans(X) else fscale(X)) > limits, value, set, vind1 = TRUE)
} else {
res <- Crepoutl(X, if(sl > 5L) mad_limits(X, limits) else sd_limits(X, limits), value, sl, set)
}
return(if(set) invisible(res) else res)
}
# Standard cases
if(set) {
if(is.list(X)) lapply(unattrib(X), function(y) if(is.numeric(y)) Crepoutl(y, limits, value, sl, set) else y) else
Crepoutl(X, limits, value, sl, set)
return(invisible(X))
}
if(is.list(X)) {
res <- duplAttributes(lapply(unattrib(X), function(y) if(is.numeric(y)) Crepoutl(y, limits, value, sl, set) else y), X)
return(if(inherits(res, "data.table")) alc(res) else res)
}
Crepoutl(X, limits, value, sl, set)
}
# pad or fpad? x is vector, matrix or data.frame
pad_atomic <- function(x, i, n, value) {
ax <- attributes(x)
tx <- typeof(x)
if(typeof(value) != tx) value <- as.vector(value, tx)
if(is.matrix(x)) {
k <- dim(x)[2L]
m <- .Call(C_alloc, value, n * k, TRUE) # matrix(value, n, k)
dim(m) <- c(n, k)
m[i, ] <- x
if(length(ax) == 1L) return(m)
ax[["dim"]] <- c(n, k)
# Could also pad row-names? perhaps with names of i ??
if(length(ax[["dimnames"]][[1L]])) ax[["dimnames"]] <- list(NULL, ax[["dimnames"]][[2L]])
if(is.object(x)) ax[["class"]] <- NULL
return(`attributes<-`(m, ax)) # fastest ??
}
r <- .Call(C_alloc, value, n, TRUE) # matrix(value, n) # matrix is faster than rep_len !!!!
r[i] <- x
if(is.null(ax)) return(r)
if(length(names(x))) {
if(length(ax) == 1L) return(r)
ax[["names"]] <- NULL
}
return(`attributes<-`(r, ax))
}
# microbenchmark::microbenchmark(x[-i] <- ri, x[i2] <- ri)
# Unit: milliseconds
# expr min lq mean median uq max neval cld
# x[-i] <- ri 255.16654 420.7083 491.7369 446.0340 476.3324 1290.7396 100 b
# x[i2] <- ri 80.18755 136.8012 157.0027 146.8156 166.7158 311.5526 100 a
# microbenchmark::microbenchmark(seq_along(x)[-i])
# Unit: milliseconds
# expr min lq mean median uq max neval
# seq_along(x)[-i] 506.0745 541.7975 605.0245 567.8115 585.8384 1341.035 100
pad <- function(X, i, value = NA, method = c("auto", "xpos", "vpos")) { # 1 - i is same length as X, fill missing, 2 - i is positive: insert missing values in positions
ilog <- is.logical(i)
ineg <- i[1L] < 0L
n <- if(is.list(X) || is.matrix(X)) fnrow(X) else length(X)
xpos <- switch(method[1L], auto = if(ilog) bsum(i) == n else if(ineg) FALSE else length(i) == n,
xpos = TRUE, vpos = FALSE, stop("Unknown method: ", method[1L]))
n <- if(ilog) length(i) else if(xpos && !ineg) bmax(i) else n + length(i)
if(is.atomic(X)) return(pad_atomic(X, if(xpos || ineg) i else if(ilog) !i else -i, n, value))
if(!is.list(X)) stop("X must be atomic or a list")
if(ilog) {
i <- if(xpos) which(i) else whichv(i, FALSE)
} else if(!xpos) {
i <- seq_len(n)[if(ineg) i else -i]
}
ax <- attributes(X)
attributes(X) <- NULL
res <- lapply(X, pad_atomic, i, n, value)
if(length(ax[["row.names"]])) ax[["row.names"]] <- .set_row_names(n)
return(condalcSA(res, ax, any(ax[["class"]] == "data.table")))
}
# Something like this already exists?? -> should work with lists as well...
Try the collapse package in your browser
Any scripts or data that you put into this service are public.
collapse documentation built on Nov. 3, 2024, 9:08 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 pad pad_atomic replace_outliers mad_trans mad_limits sd_limits Crepoutl replace_inf replace_na na_focb_ph na_locf_ph na_focb na_locf recode_char recode_num scv
Documented in na_focb na_locf pad recode_char recode_num replace_inf replace_na replace_outliers
# Note: don't change the order of these arguments !!!
scv <- function(x, v, r, set = FALSE, inv = FALSE, vind1 = FALSE) .Call(C_setcopyv, x, v, r, inv, set, vind1)
# inspired by ?dplyr::recode
# Think about adopting this code for as_numeric_factor and as_character_factor
recode_num <- function(X, ..., default = NULL, missing = NULL, set = FALSE) {
if(missing(...)) stop("recode_num requires arguments of the form: value = replacement")
args <- list(...)
nam <- as.numeric(names(args))
# nzchar(names(args)) ... check non-empty names ? -> nah, this package is not for dummies
if(anyNA(nam)) stop(paste("Non-numeric arguments:", paste(names(args)[is.na(nam)], collapse = ", ")))
arglen <- length(args)
missingl <- !is.null(missing)
if(missingl && any(nam == missing)) warning(paste0("To improve performance missing values are replaced prior to recode, so this replaces all missing values with ",
missing, " and those are then again replaced with ", args[[which(nam == missing)]], ". If this is not desired, call replace_na after recode with missing = NULL."))
if(arglen == 1L) {
args <- args[[1L]]
if(is.null(default)) {
if(missingl) {
repfun <- function(y) if(is.numeric(y)) {
z <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
scv(z, nam, args, TRUE) # `[<-`(y, y == nam, value = args)
} else y
} else {
repfun <- function(y) if(is.numeric(y)) scv(y, nam, args, set) else y # `[<-`(y, y == nam, value = args)
}
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.numeric(y)) {
nas <- is.na(y)
z <- scv(y, nas, missing, set, vind1 = TRUE)
ind <- whichv(z, nam)
scv(z, nas, default, TRUE, TRUE, vind1 = TRUE) # duplAttributes(alloc(default, nr), y)
scv(z, ind, args, TRUE, vind1 = TRUE) # y == nam
} else y
} else {
repfun <- function(y) if(is.numeric(y)) scv(scv(y, nam, default, set, TRUE), nam, args, TRUE) else y # `[<-`(duplAttributes(alloc(default, nr), y), y == nam, value = args)
}
}
} else {
seqarg <- seq_len(arglen)
if(is.null(default)) {
repfun <- function(y) if(is.numeric(y)) {
if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
else if(!set) y <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
# repfun <- function(y) if(is.numeric(y)) {
# if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
# if(set) { # Note: not strictly the way this should work...
# for(i in seqarg) scv(y, nam[i], args[[i]], TRUE)
# return(y)
# }
# z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
# for(i in seqarg) scv(z, whichv(y, nam[i]), args[[i]], TRUE, vind1 = TRUE)
# z
# } else y
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.numeric(y)) {
nas <- is.na(y)
y <- scv(y, nas, missing, set, vind1 = TRUE)
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
scv(y, nas, default, TRUE, TRUE, vind1 = TRUE)
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
repfun <- function(y) if(is.numeric(y)) {
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
y <- scv(y, nam[1L], default, set, TRUE) # duplAttributes(alloc(default, nr), y)
scv(y, nam[1L], args[[1L]], TRUE)
for(i in seqarg[-1L]) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
}
}
}
if(is.list(X)) {
if(set) {
lapply(unattrib(X), repfun)
return(invisible(X))
}
res <- duplAttributes(lapply(unattrib(X), repfun), X)
return(if(inherits(X, "data.table")) alc(res) else res)
}
if(!is.numeric(X)) stop("X needs to be numeric or a list")
res <- repfun(X)
return(if(set) invisible(res) else res)
}
recode_char <- function(X, ..., default = NULL, missing = NULL, regex = FALSE,
ignore.case = FALSE, fixed = FALSE, set = FALSE) {
if(missing(...)) stop("recode_char requires arguments of the form: value = replacement")
args <- list(...)
nam <- names(args)
arglen <- length(args)
missingl <- !is.null(missing)
if(missingl && any(nam == missing)) warning(paste0("To improve performance missing values are replaced prior to recode, so this replaces all missing values with ",
missing, " and those are then again replaced with ", args[[which(nam == missing)]], ". If this is not desired, call replace_na after recode with missing = NULL."))
if(regex) {
if(arglen == 1L) {
args <- args[[1L]]
if(is.null(default)) {
if(missingl) {
repfun <- function(y) if(is.character(y)) {
y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
scv(y, grepl(nam, y, ignore.case, FALSE, fixed), args, TRUE, vind1 = TRUE)
} else y
} else {
repfun <- function(y) if(is.character(y)) scv(y, grepl(nam, y, ignore.case, FALSE, fixed), args, set, vind1 = TRUE) else y
}
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
z <- scv(y, nas, missing, set, vind1 = TRUE)
ind <- grepl(nam, z, ignore.case, FALSE, fixed)
scv(z, nas, default, TRUE, TRUE, vind1 = TRUE) # duplAttributes(alloc(default, nr), y)
scv(z, ind, args, TRUE, vind1 = TRUE)
} else y
} else {
repfun <- function(y) if(is.character(y)) {
ind <- grepl(nam, y, ignore.case, FALSE, fixed)
scv(scv(y, ind, default, set, TRUE, vind1 = TRUE), ind, args, TRUE, vind1 = TRUE)
} else y
}
}
} else {
seqarg <- seq_len(arglen)
if(is.null(default)) {
repfun <- function(y) if(is.character(y)) {
if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
else if(!set) y <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
for(i in seqarg) scv(y, grepl(nam[i], z, ignore.case, FALSE, fixed), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
y <- scv(y, nas, missing, set, vind1 = TRUE)
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
scv(y, nas, default, TRUE, TRUE, vind1 = TRUE)
for(i in seqarg) scv(y, grepl(nam[i], z, ignore.case, FALSE, fixed), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
repfun <- function(y) if(is.character(y)) {
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
y <- scv(y, seq_along(y), default, set, vind1 = TRUE) # Initialize all to default
for(i in seqarg) scv(y, grepl(nam[i], z, ignore.case, FALSE, fixed), args[[i]], TRUE, vind1 = TRUE)
y
} else y
}
}
}
} else {
if(arglen == 1L) {
args <- args[[1L]]
if(is.null(default)) {
if(missingl) {
repfun <- function(y) if(is.character(y)) {
z <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
scv(z, nam, args, TRUE) # `[<-`(y, y == nam, value = args)
} else y
} else {
repfun <- function(y) if(is.character(y)) scv(y, nam, args, set) else y # `[<-`(y, y == nam, value = args)
}
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
z <- scv(y, nas, missing, set, vind1 = TRUE)
ind <- whichv(z, nam)
scv(z, nas, default, TRUE, TRUE, vind1 = TRUE) # duplAttributes(alloc(default, nr), y)
scv(z, ind, args, TRUE, vind1 = TRUE) # y == nam
} else y
} else {
repfun <- function(y) if(is.character(y)) scv(scv(y, nam, default, set, TRUE), nam, args, TRUE) else y # `[<-`(duplAttributes(alloc(default, nr), y), y == nam, value = args)
}
}
} else {
seqarg <- seq_len(arglen)
if(is.null(default)) {
repfun <- function(y) if(is.character(y)) {
if(missingl) y <- scv(y, NA, missing, set) # y[is.na(y)] <- missing
else if(!set) y <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
z <- scv(y, 1L, y[1L], vind1 = TRUE) # copy
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
nr <- if(is.atomic(X)) NROW(X) else fnrow(X)
if(missingl) {
repfun <- function(y) if(is.character(y)) {
nas <- is.na(y)
y <- scv(y, nas, missing, set, vind1 = TRUE)
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
scv(y, nas, default, TRUE, TRUE, vind1 = TRUE)
for(i in seqarg) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
} else {
repfun <- function(y) if(is.character(y)) {
z <- scv(y, 1L, y[1L], vind1 = TRUE) # Copy
y <- scv(y, nam[1L], default, set, TRUE) # duplAttributes(alloc(default, nr), y)
scv(y, nam[1L], args[[1L]], TRUE)
for(i in seqarg[-1L]) scv(y, whichv(z, nam[i]), args[[i]], TRUE, vind1 = TRUE)
y
} else y
}
}
}
}
if(is.list(X)) {
if(set) {
lapply(unattrib(X), repfun)
return(invisible(X))
}
res <- duplAttributes(lapply(unattrib(X), repfun), X)
return(if(inherits(X, "data.table")) alc(res) else res)
}
if(!is.character(X)) stop("X needs to be character or a list")
res <- repfun(X)
return(if(set) invisible(res) else res)
}
na_locf <- function(x, set = FALSE) .Call(C_na_locf, x, set)
na_focb <- function(x, set = FALSE) .Call(C_na_focb, x, set)
na_locf_ph <- function(x, ph1, ph2, set = FALSE) .Call(C_na_locf, x, set)
na_focb_ph <- function(x, ph1, ph2, set = FALSE) .Call(C_na_focb, x, set)
replace_na <- function(X, value = 0L, cols = NULL, set = FALSE, type = "const") {
FUN <- switch(type, const =, value = scv, locf = na_locf_ph, focb = na_focb_ph,
stop("Unknown type:", type))
if(set) {
if(is.list(X)) {
if(is.null(cols)) {
lapply(unattrib(X), FUN, NA, value, TRUE)
} else if(is.function(cols)) {
lapply(unattrib(X), function(y) if(cols(y)) FUN(y, NA, value, TRUE) else y)
} else {
cols <- cols2int(cols, X, attr(X, "names"), FALSE)
lapply(unattrib(X)[cols], FUN, NA, value, TRUE)
}
} else FUN(X, NA, value, TRUE) # `[<-`(X, is.na(X), value = value)
return(invisible(X))
}
if(is.list(X)) {
if(is.null(cols)) return(condalc(duplAttributes(lapply(unattrib(X), FUN, NA, value), X), inherits(X, "data.table"))) # function(y) `[<-`(y, is.na(y), value = value)
if(is.function(cols)) return(condalc(duplAttributes(lapply(unattrib(X),
function(y) if(cols(y)) FUN(y, NA, value) else y), X), inherits(X, "data.table")))
clx <- oldClass(X)
oldClass(X) <- NULL
cols <- cols2int(cols, X, names(X), FALSE)
X[cols] <- lapply(unattrib(X[cols]), FUN, NA, value) # function(y) `[<-`(y, is.na(y), value = value)
return(condalc(`oldClass<-`(X, clx), any(clx == "data.table")))
}
FUN(X, NA, value) # `[<-`(X, is.na(X), value = value)
}
replace_NA <- replace_na
# Remove Inf (Infinity) and NaN (Not a number) from vectors or data frames:
replace_inf <- function(X, value = NA, replace.nan = FALSE, set = FALSE) {
if(set) {
if(is.list(X)) {
lapply(unattrib(X), if(replace.nan) (function(y) if(is.numeric(y)) scv(y, is.infinite(y) | is.nan(y), value, TRUE, vind1 = TRUE) else y) else
(function(y) if(is.numeric(y)) scv(y, is.infinite(y), value, TRUE, vind1 = TRUE) else y))
}
if(!is.numeric(X)) stop("Infinite values can only be replaced in numeric objects!")
if(replace.nan) scv(X, is.infinite(X) | is.nan(X), value, TRUE, vind1 = TRUE) else scv(X, is.infinite(X), value, TRUE, vind1 = TRUE)
return(invisible(X))
}
if(is.list(X)) {
# if(!inherits(X, "data.frame")) stop("replace_non_finite only works with atomic objects or data.frames")
res <- duplAttributes(lapply(unattrib(X),
if(replace.nan) (function(y) if(is.numeric(y)) scv(y, is.infinite(y) | is.nan(y), value, vind1 = TRUE) else y) else
(function(y) if(is.numeric(y)) scv(y, is.infinite(y), value, vind1 = TRUE) else y)), X)
return(if(inherits(X, "data.table")) alc(res) else res)
}
if(!is.numeric(X)) stop("Infinite values can only be replaced in numeric objects!")
if(replace.nan) return(scv(X, is.infinite(X) | is.nan(X), value, vind1 = TRUE)) # !is.finite(X) also replaces NA
scv(X, is.infinite(X), value, vind1 = TRUE)
}
replace_Inf <- replace_inf
# replace_non_finite <- function(X, value = NA, replace.nan = TRUE) {
# .Deprecated("replace_Inf")
# replace_Inf(X, value, replace.nan)
# }
Crepoutl <- function(x, limits, value, single_limit, set = FALSE) .Call(C_replace_outliers, x, limits, value, single_limit, set)
sd_limits <- function(x, limits) {
st <- fbstatsCpp(x, stable.algo = FALSE, setn = FALSE)
st[2L] + st[3L] * c(-limits, limits)
}
mad_limits <- function(x, limits) {
med <- fmedian.default(x)
mad <- fmedian.default(abs(x - med))
med + mad * c(-limits, limits)
}
# scaling data using MAD
mad_trans <- function(x) {
if(inherits(x, c("pseries", "pdata.frame"))) {
g <- GRP(x)
tmp <- fmedian(x, g, TRA = "-")
tmp %/=% fmedian(if(is.list(tmp)) lapply(tmp, abs) else abs(tmp), g, TRA = "fill", set = TRUE)
return(tmp)
}
tmp <- fmedian(x, TRA = "-")
tmp %/=% fmedian(if(is.list(tmp)) dapply(tmp, abs) else abs(tmp), TRA = "fill", set = TRUE)
return(tmp)
}
replace_outliers <- function(X, limits, value = NA,
single.limit = c("sd", "mad", "min", "max"),
ignore.groups = FALSE,
set = FALSE) {
if(length(limits) == 1L) {
# "overall_" arguments are legacy, now accommodated via the ignore.groups argument
sl <- switch(single.limit[1L], SDs = 4L, min = 2L, max = 3L,
overall_SDs = 5L, sd = 4L, mad = 6L,
MADs = 6L, overall_MADs = 7L, # Just in case
stop("Unknown single.limit option: ", single.limit[1L]))
if(sl == 5L || sl == 7L) ignore.groups <- TRUE
} else sl <- 0L
if(sl > 3L) { # Outliers according to standard deviation or MAD threshold
if(is.list(X)) {
if(!ignore.groups && inherits(X, c("grouped_df", "pdata.frame"))) {
if(is.character(value)) stop("clipping is not yet supported with grouped/panel data and SDs/MADs thresholds.")
num <- .Call(C_vtypes, X, 1L) # vapply(unattrib(X), is.numeric, TRUE)
num <- if(inherits(X, "grouped_df")) num & !fgroup_vars(X, "logical") else
num & attr(findex(X), "names") %!in% attr(X, "names")
clx <- oldClass(X)
STDXnum <- if(sl > 5L) mad_trans(fcolsubset(X, num)) else fscale(fcolsubset(X, num))
oldClass(X) <- NULL
res <- .mapply(function(z, y) scv(z, abs(y) > limits, value, set, vind1 = TRUE),
list(unattrib(X[num]), unattrib(STDXnum)), NULL)
if(set) return(invisible(X))
X[num] <- res
res <- `oldClass<-`(X, clx)
} else {
limit_fun <- if(sl > 5L) mad_limits else sd_limits
res <- lapply(unattrib(X), function(y) if(is.numeric(y)) Crepoutl(y, limit_fun(y, limits), value, sl, set) else y)
if(set) return(invisible(X))
res <- duplAttributes(res, X)
}
return(if(inherits(res, "data.table")) alc(res) else res)
}
if(is.matrix(X)) {
if(is.character(value)) stop("clipping is not yet supported with matrices and SDs/MADs thresholds.")
res <- scv(X, abs(if(sl > 5L) mad_trans(X) else fscale(X)) > limits, value, set, vind1 = TRUE)
} else {
res <- Crepoutl(X, if(sl > 5L) mad_limits(X, limits) else sd_limits(X, limits), value, sl, set)
}
return(if(set) invisible(res) else res)
}
# Standard cases
if(set) {
if(is.list(X)) lapply(unattrib(X), function(y) if(is.numeric(y)) Crepoutl(y, limits, value, sl, set) else y) else
Crepoutl(X, limits, value, sl, set)
return(invisible(X))
}
if(is.list(X)) {
res <- duplAttributes(lapply(unattrib(X), function(y) if(is.numeric(y)) Crepoutl(y, limits, value, sl, set) else y), X)
return(if(inherits(res, "data.table")) alc(res) else res)
}
Crepoutl(X, limits, value, sl, set)
}
# pad or fpad? x is vector, matrix or data.frame
pad_atomic <- function(x, i, n, value) {
ax <- attributes(x)
tx <- typeof(x)
if(typeof(value) != tx) value <- as.vector(value, tx)
if(is.matrix(x)) {
k <- dim(x)[2L]
m <- .Call(C_alloc, value, n * k, TRUE) # matrix(value, n, k)
dim(m) <- c(n, k)
m[i, ] <- x
if(length(ax) == 1L) return(m)
ax[["dim"]] <- c(n, k)
# Could also pad row-names? perhaps with names of i ??
if(length(ax[["dimnames"]][[1L]])) ax[["dimnames"]] <- list(NULL, ax[["dimnames"]][[2L]])
if(is.object(x)) ax[["class"]] <- NULL
return(`attributes<-`(m, ax)) # fastest ??
}
r <- .Call(C_alloc, value, n, TRUE) # matrix(value, n) # matrix is faster than rep_len !!!!
r[i] <- x
if(is.null(ax)) return(r)
if(length(names(x))) {
if(length(ax) == 1L) return(r)
ax[["names"]] <- NULL
}
return(`attributes<-`(r, ax))
}
# microbenchmark::microbenchmark(x[-i] <- ri, x[i2] <- ri)
# Unit: milliseconds
# expr min lq mean median uq max neval cld
# x[-i] <- ri 255.16654 420.7083 491.7369 446.0340 476.3324 1290.7396 100 b
# x[i2] <- ri 80.18755 136.8012 157.0027 146.8156 166.7158 311.5526 100 a
# microbenchmark::microbenchmark(seq_along(x)[-i])
# Unit: milliseconds
# expr min lq mean median uq max neval
# seq_along(x)[-i] 506.0745 541.7975 605.0245 567.8115 585.8384 1341.035 100
pad <- function(X, i, value = NA, method = c("auto", "xpos", "vpos")) { # 1 - i is same length as X, fill missing, 2 - i is positive: insert missing values in positions
ilog <- is.logical(i)
ineg <- i[1L] < 0L
n <- if(is.list(X) || is.matrix(X)) fnrow(X) else length(X)
xpos <- switch(method[1L], auto = if(ilog) bsum(i) == n else if(ineg) FALSE else length(i) == n,
xpos = TRUE, vpos = FALSE, stop("Unknown method: ", method[1L]))
n <- if(ilog) length(i) else if(xpos && !ineg) bmax(i) else n + length(i)
if(is.atomic(X)) return(pad_atomic(X, if(xpos || ineg) i else if(ilog) !i else -i, n, value))
if(!is.list(X)) stop("X must be atomic or a list")
if(ilog) {
i <- if(xpos) which(i) else whichv(i, FALSE)
} else if(!xpos) {
i <- seq_len(n)[if(ineg) i else -i]
}
ax <- attributes(X)
attributes(X) <- NULL
res <- lapply(X, pad_atomic, i, n, value)
if(length(ax[["row.names"]])) ax[["row.names"]] <- .set_row_names(n)
return(condalcSA(res, ax, any(ax[["class"]] == "data.table")))
}
# Something like this already exists?? -> should work with lists as well...
Try the collapse package in your browser
Any scripts or data that you put into this service are public.
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.