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   45.2ms   45.7ms      21.7   16.28MB     9.29
#> 2 slope_terra      43ms   43.6ms      22.8    1.96MB     9.78

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5872 6186

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   46.2ms      21.7    5.28MB    21.7 
#> 2 bilinear2    43.4ms     44ms      22.7    1.86MB     7.58
#> 3 simple1      36.1ms   36.8ms      27.1    1.97MB     7.38
#> 4 simple2        38ms   38.9ms      25.8    1.98MB     7.73

round(res$`itr/sec` * nrow(r))
#> [1] 5877 6163 7337 6987