NAME
Rstats - R language build on Perl
Rstats is an experimental project, started to implement R language API in Perl, but stopped development on April 7, 2018.
SYNOPSYS
use Rstats;
# Vector
my $v1 = c_(1, 2, 3);
my $v2 = c_(3, 4, 5);
my $v3 = $v1 + v2;
print $v3;
# Sequence m:n
my $v1 = C_("1:3");
# Matrix
my $m1 = matrix(C_("1:12"), 4, 3);
# Array
my $a1 = array(C_("1:24"), c_(4, 3, 2));
# Complex
my $z1 = 1 + 2 * i_;
my $z2 = 3 + 4 * i_;
my $z3 = $z1 * $z2;
# Special value
my $true = TRUE;
my $false = FALSE;
my $na = NA;
my $nan = NaN;
my $inf = Inf;
my $null = NULL;
# all methods are called from r
my $x1 = r->sum(c_(1, 2, 3));
# Register helper
r->helper(my_sum => sub {
my ($r, $x1) = @_;
my $total = 0;
for my $value (@{$x1->values}) {
$total += $value;
}
return c_($total);
});
my $x2 = r->my_sum(c_(1, 2, 3));FUNCTIONS
c_
# c(1, 2, 3)
c_(1, 2, 3)Create vector. c_ function is equal to c of R.
C_
# 1:24
C_("1:24")C_ function is equal to m:n of R.
array
# array(1:24, c(4, 3, 2))
array(C_("1:24"), c_(4, 3, 2))TRUE
# TRUE
TRUET_
# T
T_Alias of TRUE
FALSE
# FALSE
FALSEF_
# F
F_Alias of FALSE
NA
# NA
NANaN
# NaN
NaNInf
# Inf
InfNULL
# NULL
NULLmatrix
# matrix(1:12, 4, 3)
matrix(C_("1:12"), 4, 3)
# matrix(1:12, nrow=4, ncol=3)
matrix(C_("1:12"), {nrow => 4, ncol => 3});
# matrix(1:12, 4, 3, byrow=TRUE)
matrix(C_("1:12"), 4, 3, {byrow => TRUE});VECTOR ACCESS
Getter
# x1[1]
$x1->get(1)
# x1[1, 2]
$x1->get(1, 2)
# x1[c(1,2), c(3,4)]
$x1->get(c_(1,2), c_(3,4))
# x1[,2]
$x1->get(NULL, 2)
# x1[-1]
$x1->get(-1)
# x1[TRUE, FALSE]
$x1->get(TRUE, FALSE)
# x1[c("id", "title")]
$x1->get(c_("id", "title"))Setter
# x1[1] <- x2
$x1->at(1)->set($x2)
# x1[1, 2] <- x2
$x1->at(1, 2)->set($x2)
# x1[c(1,2), c(3,4)] <- x2
$x1->at(c_(1,2), c_(3,4))->set($x2)
# x1[,2] <- x2
$x1->at(NULL, 2)->set($x2)
# x1[-1] <- x2
$x1->at(-1)->set($x2)
# x1[TRUE, FALSE] <- x2
$x1->at(TRUE, FALSE)->set($x2);
# x1[c("id", "title")] <- x2
$x1->at(c_("id", "title"))->set($x2);OPERATORS
# x1 + x2
$x1 + $x2
# x1 - x2
$x1 - $x2
# x1 * x2
$x1 * $x2
# x1 / x2
$x1 / $x2
# x1 ^ x2 (power)
$x1 ** $x2
# x1 %% x2 (remainder)
$x1 % $x2
# x1 %*% x2 (vector inner product or matrix product)
$x1 x $x2
# x1 %/% x2 (integer quotient)
r->tranc($x1 / $x2)METHODS
abs
# abs(x1)
r->abs($x1)acos
# acos(x1)
r->acos($x1)acosh
# acosh(x1)
r->acosh($x1)append
apply
Arg
array
asin
# asin(x1)
r->asin($x1)asinh
# asinh(x1)
r->asinh($x1)atan2
atan
# atan(x1)
r->atan($x1)atanh
# atanh(x1)
r->atanh($x1)c
vec
charmatch
chartr
cbind
# cbind(c(1, 2), c(3, 4), c(5, 6))
r->cbind(c_(1, 2), c_(3, 4), c_(5, 6));ceiling
# ceiling(x1)
r->ceiling($x1)col
# col(x1)
r->col($x1)colMeans
# colMeans(x1)
r->colMeans($x1)colSums
Conj
cos
# cos(x1)
r->cos($x1)cosh
# cosh(x1)
r->cosh($x1)cummax
cummin
cumsum
cumprod
complex
data_frame
diag
diff
exp
# exp(x1)
r->exp($x1)expm1
# expm1(x1)
r->expm1($x1)factor
F
FALSE
floor
# floor(x1)
r->floor($x1)gl
grep
gsub
head
i
ifelse
interaction
is->element
I
Im
Inf
intersect
kronecker
length
list
log
# log(x1)
r->log($x1)logb
# logb(x1)
r->logb($x1)log2
# log2(x1)
r->log2($x1)log10
# log10(x1)
r->log10($x1)lower_tri
match
median
merge
Mod
NA
NaN
na_omit
ncol
# ncol(x1)
r->ncol($x1)nrow
# nrow(x1)
r->nrow($x1)NULL
numeric
matrix
max
mean
min
nchar
order
ordered
outer
paste
pi
pmax
pmin
prod
range
rank
rbind
# rbind(c(1, 2), c(3, 4), c(5, 6))
r->rbind(c_(1, 2), c_(3, 4), c_(5, 6))Re
quantile
read->table
# read.table(...)
r->read->table(...)rep
replace
rev
rnorm
round
# round(x1)
r->round($x1)
# round(x1, digit)
r->round($x1, $digits)
# round(x1, digits=1)
r->round($x1, {digits => TRUE});row
# row(x1)
r->row($x1)rowMeans
# rowMeans(x1)
r->rowMeans($x1)rowSums
# rowSums(x1)
r->rowSums($x1)sample
seq
sequence
set_diag
setdiff
setequal
sin
# sin(x1)
r->sin($x1)sinh
# sinh(x1)
r->sinh($x1)sum
sqrt
# sqrt(x1)
r->sqrt($x1)sort
sub
subset
sweep
t
# t
r->t($x1)tail
tan
# tan(x1)
r->tan($x1)tanh
# tanh(x1)
r->tanh($x1)tapply
tolower
toupper
T
TRUE
transform
trunc
# trunc(x1)
r->trunc($x1)unique
union
upper_tri
var
which
as->array
# as.array(x1)
r->as->array($x1)as->character
# as.character(x1)
r->as->character($x1)as->complex
# as.complex(x1)
r->as->complex($x1)as->integer
# as.integer(x1)
r->as->integer($x1)as->list
# as.list
r->as->list($x1)as->logical
# as.logical
r->as->logical($x1)as->matrix
# as.matrix(x1)
r->as->matrix($x1)as->numeric
# as.numeric(x1)
r->as->numeric($x1)as->vector
# as.vector(x1)
r->as->vector($x1)is->array
# is.array(x1)
r->is->array($x1)is->character
# is.character(x1)
r->is->character($x1)is->complex
# is.complex(x1)
r->is->complex($x1)is->finite
# is.finite(x1)
r->is->finite($x1)is->infinite
# is.infinite(x1)
r->is->infinite($x1)is->list
# is.list(x1)
r->is->list($x1)is->matrix
# is.matrix(x1)
r->is->matrix($x1)is->na
# is.na(x1)
r->is->na($x1)is->nan
# is.nan(x1)
r->is->nan($x1)is->null
# is.null(x1)
r->is->null($x1)is->numeric
# is.numeric(x1)
r->is->numeric($x1)is->double
# is.double(x1)
r->is->double($x1)is->integer
# is.integer(x1)
r->is->integer($x1)is->logical
# is.logical(x1)
r->is->logical($x1)is->vector
# is.vector(x1)
r->is->vector($x1)labels
# labels(x1)
r->labels($x1)levels
# levels(x1)
r->levels($x1)
# levels(x1) <- c("F", "M")
r->levels($x1 => c_("F", "M"))dim
# dim(x1)
r->dim($x1)
# dim(x1) <- c(1, 2)
r->dim($x1 => c_(1, 2))names
# names(x1)
r->names($x1)
# names(x1) <- c("n1", "n2")
r->names($x1 => c_("n1", "n2"))nlevels
# nlevels(x1)
r->nlevels($x1)dimnames
# dimnames(x1)
r->dimnames($x1)
# dimnames(x1) <- list(c("r1", "r2"), c("c1", "c2"))
r->dimnames($x1 => list(c_("r1", "r2"), c_("c1", "c2")))colnames
# colnames(x1)
r->colnames($x1)
# colnames(x1) <- c("r1", "r2")
r->colnames($x1 => c_("r1", "r2"))rownames
# rownames(x1)
r->rownames($x1)
# rownames(x1) <- c("r1", "r2")
r->rownames($x1 => c_("r1", "r2"))mode
# mode(x1)
r->mode($x1)
# mode(x1) <- c("r1", "r2")
r->mode($x1 => c_("r1", "r2"))str
# str(x1)
r->str($x1)typeof
# typeof(x1)
r->typeof($x1);