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   45.7ms   46.9ms      21.0   16.12MB     9.00
#> 2 slope_terra    43.2ms   44.3ms      19.6    1.96MB     4.90

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5688 5313

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   45.6ms      21.7    5.28MB    21.7 
#> 2 bilinear2    43.4ms   44.7ms      22.4    1.86MB     4.97
#> 3 simple1      36.2ms   37.1ms      26.3    1.97MB     7.90
#> 4 simple2      37.5ms   37.9ms      25.8    1.98MB     7.73

round(res$`itr/sec` * nrow(r))
#> [1] 5878 6060 7136 6983