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   47.9ms   49.1ms      20.2   16.27MB    10.1 
#> 2 slope_terra    44.9ms   45.9ms      21.5    1.96MB     6.15

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5487 5838

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    47.2ms   47.6ms      20.8    5.28MB    20.8 
#> 2 bilinear2    45.2ms   46.5ms      21.5    1.86MB     4.79
#> 3 simple1      37.6ms   38.7ms      25.9    1.97MB     7.77
#> 4 simple2      39.3ms   40.4ms      24.7    1.98MB     8.24

round(res$`itr/sec` * nrow(r))
#> [1] 5629 5838 7022 6695