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     46ms   46.8ms      21.2   16.27MB     9.07
#> 2 slope_terra    44.1ms   44.5ms      22.4    1.94MB    11.2

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5735 6059

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    46.1ms   46.2ms      21.7    5.28MB    28.9 
#> 2 bilinear2    43.6ms   44.2ms      22.5    1.86MB     5.01
#> 3 simple1      36.5ms   37.5ms      26.2    1.97MB     7.87
#> 4 simple2      38.6ms   39.8ms      25.2    1.98MB     7.57

round(res$`itr/sec` * nrow(r))
#> [1] 5868 6111 7113 6840