# Benchmarking slopes calculation

    library(slopes)
    library(bench)

# Performance

A benchmark can reveal how many route gradients can be calculated per second using different interpolation methods:

    e = dem_lisbon()
    r = lisbon_road_network
    res = bench::mark(check = FALSE,
      bilinear = slope_raster(r, e),
      simple   = slope_raster(r, e, method = "simple")
    )

    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 bilinear       20ms   20.3ms      48.7   17.98MB     39.8
    #> 2 simple       17.3ms   17.7ms      56.3    2.01MB     41.3

That is approximately

    round(res$`itr/sec` * nrow(r))
    #> [1] 13194 15249

routes per second using `bilinear` and `simple` interpolation methods, respectively.

To go faster, you can chose the `simple` method to gain some speed at the expense of accuracy:

    res2 = bench::mark(check = FALSE,
      bilinear = slope_raster(r, e, method = "bilinear"),
      simple   = slope_raster(r, e, method = "simple")
    )

    res2
    #> # A tibble: 2 × 6
    #>   expression      min   median `itr/sec` mem_alloc `gc/sec`
    #>   <bch:expr> <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
    #> 1 bilinear       21ms   21.7ms      45.6    1.86MB     41.5
    #> 2 simple       17.3ms   18.1ms      54.4    1.94MB     49.4

    round(res2$`itr/sec` * nrow(r))
    #> [1] 12369 14735