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## ----setup, echo=FALSE, results='hide', warning=FALSE, error=FALSE, message=FALSE, cache=FALSE----
library(knitr)
opts_chunk$set(
cache = FALSE,
echo = TRUE,
warning = FALSE,
error = FALSE,
message = FALSE,
out.width = 700,
fig.width = 12,
fig.height = 8,
dpi = 84,
concordance = TRUE,
collapse = TRUE,
comment = "#>"
)
library(narray)
## ----namespace, eval=FALSE----------------------------------------------------
# # example referencing the package namespace
# # do not load the package with 'library(...)' here
# narray::stack(...)
## ----stack--------------------------------------------------------------------
A = matrix(1:4, nrow=2, ncol=2, dimnames=list(c('a','b'),c('x','y')))
B = matrix(5:6, nrow=2, ncol=1, dimnames=list(c('b','a'),'z'))
C = stack(A, B, along=2)
C
D = stack(m=A, n=C, along=3) # we can also introduce new dimensions
D
## ----split--------------------------------------------------------------------
split(C, along=2, subsets=c('s1','s1','s2'))
## ----map----------------------------------------------------------------------
map(C, along=2, function(x) x*2) # return same length vector
map(C, along=2, mean, subsets=c('s1', 's1', 's2')) # summarize each subset to scalar
## ----lambda-------------------------------------------------------------------
dot = function(x, y) sum(x * y)
lambda(~ dot(A, B), along=c(A=1, B=2))
lambda(~ dot(A, B), along=c(A=1, B=2), simplify=FALSE)
## ----intersect----------------------------------------------------------------
E = matrix(1:6, nrow=3, dimnames=list(c('a','b','d'), c('x','y')))
F = matrix(7:9, nrow=3, dimnames=list(c('b','a','c'), 'z'))
intersect(E, F, along=1)
E
F
## ----construct----------------------------------------------------------------
DF = data.frame(k1=base::rep(letters[1:3],2),
k2=base::rep(letters[24:25],3), v=1:6)[-6,]
construct(v ~ k1 + k2, data=DF)
## ----mask---------------------------------------------------------------------
G = list(a='e1', b=c('e1','e2'), c='e2')
mask(G)
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