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     46ms      21.1   16.28MB     9.05
#> 2 slope_terra    42.7ms   43.5ms      22.9    1.96MB     9.83

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5721 6218

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    45.2ms   45.9ms      21.8    5.28MB    21.8 
#> 2 bilinear2      43ms   43.9ms      22.7    1.86MB     7.57
#> 3 simple1      36.1ms   36.5ms      27.1    1.97MB     7.40
#> 4 simple2      37.7ms   38.6ms      25.6    1.98MB     7.69

round(res$`itr/sec` * nrow(r))
#> [1] 5914 6152 7354 6944