```
# show runmed function
k=25; n=200;
x = rnorm(n,sd=30) + abs(seq(n)-n/4)
col = c("black", "red", "green")
m=runmean(x, k)
y=runsd(x, k, center=m)
plot(x, col=col[1], main = "Moving Window Analysis Functions")
lines(m , col=col[2])
lines(m-y/2, col=col[3])
lines(m+y/2, col=col[3])
lab = c("data", "runmean", "runmean-runsd/2", "runmean+runsd/2")
legend(0,0.9*n, lab, col=col, lty=1 )
# basic tests against apply/embed
eps = .Machine$double.eps ^ 0.5
k=25 # odd size window
a = runsd(x,k, endrule="trim")
b = apply(embed(x,k), 1, sd)
stopifnot(all(abs(a-b)<eps));
k=24 # even size window
a = runsd(x,k, endrule="trim")
b = apply(embed(x,k), 1, sd)
stopifnot(all(abs(a-b)<eps));
# test against loop approach
# this test works fine at the R prompt but fails during package check - need to investigate
k=25; n=200;
x = rnorm(n,sd=30) + abs(seq(n)-n/4) # create random data
x[seq(1,n,11)] = NaN; # add NANs
k2 = k
k1 = k-k2-1
a = runsd(x, k)
b = array(0,n)
for(j in 1:n) {
lo = max(1, j-k1)
hi = min(n, j+k2)
b[j] = sd(x[lo:hi], na.rm = TRUE)
}
#stopifnot(all(abs(a-b)<eps));
# compare calculation at array ends
k=25; n=100;
x = rnorm(n,sd=30) + abs(seq(n)-n/4)
a = runsd(x, k, endrule="sd" ) # fast C code
b = runsd(x, k, endrule="func") # slow R code
stopifnot(all(abs(a-b)<eps));
# test if moving windows forward and backward gives the same results
k=51;
a = runsd(x , k)
b = runsd(x[n:1], k)
stopifnot(all(abs(a[n:1]-b)<eps));
# test vector vs. matrix inputs, especially for the edge handling
nRow=200; k=25; nCol=10
x = rnorm(nRow,sd=30) + abs(seq(nRow)-n/4)
x[seq(1,nRow,10)] = NaN; # add NANs
X = matrix(rep(x, nCol ), nRow, nCol) # replicate x in columns of X
a = runsd(x, k)
b = runsd(X, k)
stopifnot(all(abs(a-b[,1])<eps)); # vector vs. 2D array
stopifnot(all(abs(b[,1]-b[,nCol])<eps)); # compare rows within 2D array
# speed comparison
## Not run:
# x=runif(1e5); k=51; # reduce vector and window sizes
# system.time(runsd( x,k,endrule="trim"))
# system.time(apply(embed(x,k), 1, sd))
# ## End(Not run)
```

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