Benchmarking slopes calculation

library(slopes)
library(bench)
library(raster)
#> Loading required package: sp

Performance

A benchmark can reveal how many route gradients can be calculated per second:

e = dem_lisbon_raster
r = lisbon_road_network
et = terra::rast(e)
res = bench::mark(check = FALSE,
  slope_raster = slope_raster(r, e),
  slope_terra = slope_raster(r, et)
)
res
#> # A tibble: 2 × 6
#>   expression        min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>   <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 slope_raster   18.5ms   18.7ms      52.0    16.2MB     24.5
#> 2 slope_terra    17.5ms   18.4ms      54.2    1.96MB     13.5

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 14104 14680

routes per second using the raster and terra (the default if installed, using RasterLayer and native SpatRaster objects) packages to extract elevation estimates from the raster datasets, respectively.

The message: use the terra package to read-in DEM data for slope extraction if speed is important.

To go faster, you can chose the simple method to gain some speed at the expense of accuracy:

e = dem_lisbon_raster
r = lisbon_road_network
res = bench::mark(check = FALSE,
  bilinear1 = slope_raster(r, e),
  bilinear2 = slope_raster(r, et),
  simple1 = slope_raster(r, e, method = "simple"),
  simple2 = slope_raster(r, et, method = "simple")
)
res
#> # A tibble: 4 × 6
#>   expression      min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 bilinear1    18.4ms   18.7ms      53.0    5.28MB     9.64
#> 2 bilinear2      18ms   18.5ms      53.7    1.86MB    12.8 
#> 3 simple1        15ms   15.2ms      65.7    1.97MB    12.2 
#> 4 simple2      15.2ms   15.4ms      64.7    1.92MB    12.0
round(res$`itr/sec` * nrow(r))
#> [1] 14364 14541 17791 17544