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   44.6ms   45.2ms      21.8   16.27MB     9.36
#> 2 slope_terra    44.2ms     45ms      22.1    1.96MB    11.0

That is approximately

round(res$`itr/sec` * nrow(r))
#> [1] 5920 5984

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   45.4ms      22.0    5.28MB    27.5 
#> 2 bilinear2    43.5ms   44.7ms      22.5    1.86MB     5.00
#> 3 simple1      36.1ms   36.5ms      26.7    1.97MB     8.01
#> 4 simple2      37.6ms   38.1ms      26.1    1.98MB     7.82

round(res$`itr/sec` * nrow(r))
#> [1] 5966 6099 7232 7065