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   45.2ms      21.2   16.19MB     7.94
#> 2 slope_terra    42.8ms   43.3ms      23.0    1.96MB     9.87

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5740 6243

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    44.2ms     45ms      22.2    5.28MB     8.34
#> 2 bilinear2    42.4ms   42.9ms      23.1    1.86MB     7.71
#> 3 simple1      36.6ms   37.2ms      26.7    1.97MB     8.02
#> 4 simple2      36.5ms   37.2ms      26.6    1.98MB    11.8
round(res$`itr/sec` * nrow(r))
#> [1] 6026 6268 7242 7207