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   45.3ms   46.6ms      20.6   21.86MB     7.73
#> 2 slope_terra      44ms   44.8ms      22.3    1.81MB    11.2

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5589 6055

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    45.3ms   46.5ms      21.4    5.15MB    10.7 
#> 2 bilinear2    44.2ms   44.7ms      22.4    1.73MB     4.98
#> 3 simple1      36.7ms   36.9ms      26.9    1.84MB     8.06
#> 4 simple2      38.1ms   38.7ms      25.2    1.84MB     7.57

round(res$`itr/sec` * nrow(r))
#> [1] 5794 6071 7283 6841