如何编写多个if语句R

Question

I am manipulating raster data in R with the rgdal and raster packages. I want to get rid of all infinite, no values, negative values and replace them with zero:

NoNA <- function (x) { 
    x[is.infinite(x) | is.na(x) | is.nan(x) | is.null(x) | is.na(x < 0)] <- 0
}
ndii_noNA <- calc(ndii, NoNA)

Then the ndii_noNA have only a value of 0. I tried if else statement but it raises an error in

.calcTest(x[1:5], fun, na.rm, forcefun, forceapply).

Is there any way to solve this?

Answer 1

You are very close, but have made two errors:

1. You need to use which() in the index of x , rather than just the truth statement. Otherwise, you will index either x[TRUE] or x[FALSE] , which is not what you want. which() will return the indices of all "bad" elements in your vector.
2. When you make the assignment with <- , the local copy of x will be changed, not the one that was passed. If you want to change x in place, you need to use <<- . That said, you would be wise to stick to R's functional paradigm, in which you would make the change to the local copy, then return it with return(x) , rather than change in place.

Here is the function you want:

# The "change in place" method (may be considered bad style)
NoNA <- function(x) {
  x[which(is.infinite(x) | is.na(x) | is.nan(x) | is.null(x) | is.na(x < 0))] <<- 0
}
# The functional way (recommended)
NoNA <- function(x) {
  x[which(is.infinite(x) | is.na(x) | is.nan(x) | is.null(x) | is.na(x < 0))] <- 0
  return(x)
}

Answer 2

Edit: ifelse() is cleaner but the @cgmil's answer is indeed faster.

    x = rep(c(Inf, -Inf, NULL, NaN, NA, 1), 250e3)

    no_na = function(x){

      ifelse(
        is.infinite(x) | is.na(x) | is.nan(x) | is.null(x) | is.na(x < 0), 0, x
      )

    }


NoNA <- function(x) {
  x[which(is.infinite(x) | is.na(x) | is.nan(x) | is.null(x) | is.na(x < 0))] <- 0
  return(x)
}

microbenchmark(
  no_na(x), NoNA(x),
  times = 50
)

# Unit: milliseconds
# expr      min       lq     mean   median       uq      max neval
# no_na(x) 380.9375 399.7520 416.7729 424.5490 429.6005 451.0534    50
# NoNA(x) 242.8555 249.0034 255.8857 251.3694 254.8176 285.1451    50