user4050 - 10 months ago 60

R Question

Given the definition of open internal (does not include end points) and closed interval (includes end points), it's easy to understand the

`right`

`reclassify`

`include.lowest`

indicating if a value equal to the lowest value in rcl (or highest

value in the second column, for right = FALSE) should be included

the lowest value in rcl would be the first value, which according to

`right`

so if I have rcl=c(0,1,5, 1,Inf,10) by default it means 0>x>=1 becomes 5, and x>1 becomes 10. What happens if include.lowest is TRUE? 0>=x>=1 and....?

I find it confusing because the example given on the reclassify help file says that

all values >= 0 and <= 0.25 become 1, etc. m <- c(0, 0.25, 1, 0.25, 0.5, 2, 0.5, 1, 3)

but then the reclassify function in the example doesn't use the include.lowest so it shouldn't be all values >= 0 but >0.

EDIT: I find the help page very confusing, and given the answer the example's explanation in the help page is wrong.

Answer

As I said in my comment, the way that `right`

and `include.lowest`

work are exactly the same as in R base function `cut`

. For a simple illustration, I will use `cut`

in below, with vector 1:10 and break points 1, 5, 10.

By default, `right = TRUE`

, so all intervals will be left open and right closed, thus we have two intervals: `(1, 5]`

, `(5, 10]`

. Note these together give another left open right closed interval `(1, 10]`

, where the lowest `1`

is not included. `include.lowest = TRUE`

will consider `[1, 10]`

and do `[1,5]`

, `(5,10]`

. Compare

```
cut(1:10, right = TRUE, breaks = c(1, 5, 10))
# [1] <NA> (1,5] (1,5] (1,5] (1,5] (5,10] (5,10] (5,10] (5,10] (5,10]
#Levels: (1,5] (5,10]
cut(1:10, right = TRUE, breaks = c(1, 5, 10), include.lowest = TRUE)
# [1] [1,5] [1,5] [1,5] [1,5] [1,5] (5,10] (5,10] (5,10] (5,10] (5,10]
#Levels: [1,5] (5,10]
```

Now, if we set `right = FALSE`

, all intervals will be left closed and right open: `[1, 5)`

, `[5, 10)`

. In this case, the `include.lowest = TURE`

essentially includes the highest value. Compare

```
cut(1:10, right = FALSE, breaks = c(1, 5, 10))
# [1] [1,5) [1,5) [1,5) [1,5) [5,10) [5,10) [5,10) [5,10) [5,10) <NA>
#Levels: [1,5) [5,10)
cut(1:10, right = FALSE, breaks = c(1, 5, 10), include.lowest = TRUE)
# [1] [1,5) [1,5) [1,5) [1,5) [5,10] [5,10] [5,10] [5,10] [5,10] [5,10]
#Levels: [1,5) [5,10]
```

Back to `raster::reclassify`

.

I find it confusing because the example given on the reclassify help file says that

all values >= 0 and <= 0.25 become 1, etc.

`m <- c(0, 0.25, 1, 0.25, 0.5, 2, 0.5, 1, 3)`

Why? With above `m`

, you have `rcl`

matrix:

```
matrix(m, ncol = 3L, byrow = TRUE, dimnames = list(NULL, c("from", "to", value)))
# from to value
#[1,] 0.00 0.25 1
#[2,] 0.25 0.50 2
#[3,] 0.50 1.00 3
```

With `right = TRUE`

and `include.lowest = FALSE`

(default behaviour), you have

```
(0.00, 0,25] ---> 1
(0.25, 0.50] ---> 2
(0.50, 1.00] ---> 3
```

with `right = TRUE`

and `include.lowest = TRUE`

, you have

```
[0.00, 0,25] ---> 1
(0.25, 0.50] ---> 2
(0.50, 1.00] ---> 3
```

Source (Stackoverflow)