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     45ms   45.4ms      21.7   16.29MB     9.30
#> 2 slope_terra    43.1ms   44.3ms      22.1    1.96MB     9.46

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5881 5983

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    45.1ms   45.6ms      21.9    5.28MB    16.4 
#> 2 bilinear2    43.4ms   44.5ms      22.5    1.86MB     8.43
#> 3 simple1      36.3ms   36.8ms      26.9    1.97MB     7.33
#> 4 simple2      37.8ms   38.5ms      25.9    1.98MB     7.78

round(res$`itr/sec` * nrow(r))
#> [1] 5933 6092 7283 7029