Closed SpatLyu closed 2 months ago
I have tested the terra
1.7.80, the result is also wrong:
library(terra)
#> terra 1.7.80
r = rast(ncols=3, nrows=3)
values(r) = c(-2, -3, -1, -1.96, 0, 1, 2, 3, 1.96)
z = terra::classify(r,
matrix(c(-1.96, 1.96, 2,
1.96, Inf, 1,
-Inf, -1.96, 3), byrow = T, nrow = 3),
include.lowest = TRUE, right = TRUE)
plot(z, col = c("white", "green", "red"))
coords = xyFromCell(r, 1:ncell(r))
original_vals = values(r)
for (i in 1:nrow(coords)) {
text(coords[i, 1], coords[i, 2], labels=round(original_vals[i], 2),
cex=0.8, col="black")
}
z1 = terra::classify(r,
matrix(c(-1.96, 1.96, 2,
1.96, Inf, 1,
-Inf, -1.96, 3), byrow = T, nrow = 3))
plot(z1, col = c("white", "green", "red"))
coords = xyFromCell(r, 1:ncell(r))
original_vals = values(r)
for (i in 1:nrow(coords)) {
text(coords[i, 1], coords[i, 2], labels=round(original_vals[i], 2),
cex=0.8, col="black")
}
z2 = terra::classify(r,
matrix(c(-1.96, 1.96, 2,
1.96, Inf, 1,
-Inf, -1.96, 3), byrow = T, nrow = 3),
include.lowest = FALSE, right = FALSE)
plot(z2, col = c("white", "green", "red"))
coords = xyFromCell(r, 1:ncell(r))
original_vals = values(r)
for (i in 1:nrow(coords)) {
text(coords[i, 1], coords[i, 2], labels=round(original_vals[i], 2),
cex=0.8, col="black")
}
z3 = terra::classify(r,
matrix(c(-1.96, 1.96, 2,
1.96, Inf, 1,
-Inf, -1.96, 3), byrow = T, nrow = 3),
include.lowest = FALSE, right = FALSE, others = 2)
plot(z3, col = c("white", "green", "red"))
coords = xyFromCell(r, 1:ncell(r))
original_vals = values(r)
for (i in 1:nrow(coords)) {
text(coords[i, 1], coords[i, 2], labels=round(original_vals[i], 2),
cex=0.8, col="black")
}
Created on 2024-07-03 with reprex v2.1.0
I think you want right=NA
in this case
library(terra)
r <- rast(ncols=3, nrows=3)
values(r) <- c(-3, -2, -1.96, -1, 0, 1, 1.96, 2, 3)
m <- matrix(c(-1.96, 1.96, 2, 1.96, Inf, 1, -Inf, -1.96, 3), byrow = TRUE, nrow = 3)
z <- terra::classify(r, m, right = NA, include.lowest=TRUE)
values(c(r, z))
# lyr.1 lyr.1
# [1,] -3.00 3
# [2,] -2.00 3
# [3,] -1.96 2
# [4,] -1.00 2
# [5,] 0.00 2
# [6,] 1.00 2
# [7,] 1.96 2
# [8,] 2.00 1
# [9,] 3.00 1
But note that you are using 1.96 as if it were an integer. That may not be appropriate because
1.96 == 1.96000000000000000001
#[1] TRUE
1.96 == 1.9599999999999999999
# [1] TRUE
This would probably be a better approach
m2 <- matrix(c(-1.96, 1.96, 2,
1.96, Inf, 1), byrow = TRUE, ncol = 3)
zx <- terra::classify(r, m2, right = T, include.lowest=TRUE, others=3)
You can also use ifel
. That has a clear syntac, but it is much less efficient
zy <- ifel(r < -1.96, 3, ifel(r > 1.96, 1, 2))
values(c(r, z, zx, zy))
# lyr.1 lyr.1 lyr.1 lyr.1
# [1,] -3.00 3 3 3
# [2,] -2.00 3 3 3
# [3,] -1.96 2 2 2
# [4,] -1.00 2 2 2
# [5,] 0.00 2 2 2
# [6,] 1.00 2 2 2
# [7,] 1.96 2 2 2
# [8,] 2.00 1 1 1
# [9,] 3.00 1 1 1
I found that
classify()
did not work properly when testing a small demo withterra
. I need to classify values greater than 1.96 as 1; values greater than or equal to -1.96 and less than or equal to 1.96 are classified as 2; values less than -1.96 are classified as 3, here are a few examples:Created on 2024-07-02 with reprex v2.1.0
As you can see, setting
include.lowest
andright
toTRUE
does not work. Also, wheninclude.lowest
andright
are set toFALSE
, theothers
parameter also not take effect.I don't know if I misunderstoodMy
terra
package configuration information is as follows:Created on 2024-07-02 with reprex v2.1.0