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     44ms   44.8ms      21.4   16.19MB     8.02
#> 2 slope_terra    41.6ms     42ms      23.7    1.96MB     8.88

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5793 6415

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    43.1ms   43.9ms      22.7    5.28MB    11.4 
#> 2 bilinear2    41.3ms   41.9ms      23.6    1.86MB     7.86
#> 3 simple1      35.4ms   35.7ms      27.9    1.97MB     7.60
#> 4 simple2      35.8ms   36.3ms      27.5    1.98MB    11.0
round(res$`itr/sec` * nrow(r))
#> [1] 6163 6389 7550 7450