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   46.1ms   46.4ms      20.6   16.26MB     7.74
#> 2 slope_terra    43.9ms   44.2ms      22.6    1.96MB    17.0

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5595 6126

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    45.9ms   46.6ms      21.3    5.29MB     8.00
#> 2 bilinear2    44.3ms     45ms      22.0    1.86MB     8.26
#> 3 simple1      37.4ms   38.1ms      26.1    1.97MB    11.6 
#> 4 simple2      40.2ms   40.4ms      24.6    1.98MB     8.21
round(res$`itr/sec` * nrow(r))
#> [1] 5784 5970 7083 6673