smooth_data <- function(x, s1, s2){
d1 <- ceiling(dim(x)[1]/s1)
d2 <- ceiling(dim(x)[2]/s2)
y <- matrix(0, nrow=d1, ncol=d2)
r.st <- 1
r.en <- s1
c.st <- 1
c.en <- s2
for(i in 1:d1){
for(j in 1:d2){
y[i, j] <- mean(x[r.st:r.en, c.st:c.en])
c.st <- min(c.st + s2, dim(x)[2])
c.en <- min(c.en + s2, dim(x)[2])
}
c.st <- 1
c.en <- s2
r.st <- min(r.st + s1, dim(x)[1])
r.en <- min(r.en + s1, dim(x)[1])
}
return(y)
}
unitize <- function(z) {
# Mean and SD normalization
mean.z <- mean(z)
sd.z <- sd(z)
if (sd.z == 0)
return(z)
(z - mean.z)/sd.z
}
remove_infinite_values <- function(X, cols){
# X has the features
# Cols are columns with infinite values
df <- as.data.frame(X[,cols])
iqr.vals <- apply(df,2, function(x)IQR(x, na.rm=TRUE))
for(ii in 1:length(cols)){
# recs<- which(is.infinite(X[,cols[ii]]))
tf <- sapply(X[,cols[ii]], simplify = 'matrix', is.infinite)
recs <- which(tf)
X[recs,cols[ii]] <- 5*iqr.vals[ii]*sign(X[recs,cols[ii]])
}
return(X)
}
meshgrid3d <- function(xx,yy,zz){
xnum <- length(xx)
ynum <- length(yy)
znum <- length(zz)
out <- matrix(0, nrow=xnum*ynum*znum, ncol=3)
out[,1] <- rep(xx,ynum*znum)
out[,2] <- rep(rep(yy,each=xnum),znum)
out[,3] <- rep(zz,each=xnum*ynum)
return(out)
}
# Taken from AtmRay R package after getting email from Kurt Hornik
# asking to fix reverse dependencies
meshgrid <- function(a,b){
return(list( x=outer(b*0,a,FUN="+"), y=outer(b,a*0,FUN="+") ))
}
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