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   44.9ms   47.6ms      20.6   21.86MB     8.82
#> 2 slope_terra    43.5ms   44.1ms      22.7    1.81MB     9.71

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5578 6140

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    43.7ms   44.9ms      22.3    5.15MB     8.35
#> 2 bilinear2    43.2ms   43.7ms      22.8    1.74MB     4.57
#> 3 simple1      36.4ms   36.9ms      26.9    1.84MB     8.08
#> 4 simple2      38.7ms   39.8ms      25.1    1.84MB     8.37

round(res$`itr/sec` * nrow(r))
#> [1] 6037 6187 7302 6806