Fixup doc

Zentrik · Zentrik · commit fe42d847ce67 · 2024-06-21T11:41:14.000+01:00
diff --git a/docs/src/manual.md b/docs/src/manual.md
@@ -29,7 +29,7 @@ BenchmarkTools.Trial: 10000 samples with 1000 evaluations.
  Time  (median):     1.453 ns              ┊ GC (median):    0.00%
  Time  (mean ± σ):   1.462 ns ±  0.566 ns  ┊ GC (mean ± σ):  0.00% ± 0.00%
 
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   1.44 ns           Histogram: frequency by time           1.46 ns (top 1%)
 
@@ -50,7 +50,7 @@ BenchmarkTools.Trial: 10000 samples with 1000 evaluations.
  Time  (median):     1.453 ns             ┊ GC (median):    0.00%
  Time  (mean ± σ):   1.456 ns ± 0.056 ns  ┊ GC (mean ± σ):  0.00% ± 0.00%
 
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   1.44 ns          Histogram: frequency by time           1.46 ns (top 1%)
 
@@ -86,7 +86,7 @@ You can pass the following keyword arguments to `@benchmark`, `@benchmarkable`,
 - `time_tolerance`: The noise tolerance for the benchmark's time estimate, as a percentage. This is utilized after benchmark execution, when analyzing results. Defaults to `BenchmarkTools.DEFAULT_PARAMETERS.time_tolerance = 0.05`.
 - `memory_tolerance`: The noise tolerance for the benchmark's memory estimate, as a percentage. This is utilized after benchmark execution, when analyzing results. Defaults to `BenchmarkTools.DEFAULT_PARAMETERS.memory_tolerance = 0.01`.
 
-The following keyword arguments relate to [Running custom benchmarks] are experimental and subject to change, see [Running custom benchmarks] for furthe details.:
+The following keyword arguments relate are experimental and subject to change, see [Running custom benchmarks](@ref) for further details:
 
 - `run_customizable_func_only`: If `true`, only the customizable benchmark. Defaults to `BenchmarkTools.DEFAULT_PARAMETERS..run_customizable_func_only = false`.
 - `enable_customizable_func`: If `:ALL` the customizable benchmark runs on every sample, if `:LAST` the customizable benchmark runs on the last sample, if `:FALSE` the customizable benchmark is never run. Defaults to `BenchmarkTools.DEFAULT_PARAMETERS.enable_customizable_func = :FALSE`
@@ -125,7 +125,7 @@ BenchmarkTools.Trial: 10000 samples with 10 evaluations.
  Time  (median):     1.363 μs               ┊ GC (median):    0.00%
  Time  (mean ± σ):   1.786 μs ±   4.612 μs  ┊ GC (mean ± σ):  9.58% ±  3.70%
 
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   1.15 μs         Histogram: log(frequency) by time          3.8 μs (top 1%)
 
@@ -139,7 +139,7 @@ BenchmarkTools.Trial: 10000 samples with 963 evaluations.
  Time  (median):     84.497 ns               ┊ GC (median):    0.00%
  Time  (mean ± σ):   85.125 ns ±   5.262 ns  ┊ GC (mean ± σ):  0.00% ± 0.00%
 
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   84.5 ns         Histogram: log(frequency) by time           109 ns (top 1%)
 
@@ -158,7 +158,7 @@ BenchmarkTools.Trial: 10000 samples with 54 evaluations.
  Time  (median):       1.073 μs              ┊ GC (median):     0.00%
  Time  (mean ± σ):     1.296 μs ±  2.004 μs  ┊ GC (mean ± σ):  14.31% ±  8.76%
 
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   889 ns             Histogram: frequency by time            2.92 μs (top 1%)
 
@@ -237,7 +237,7 @@ BenchmarkTools.Trial: 819 samples with 1 evaluations.
  Time  (median):     6.019 ms              ┊ GC (median):    0.00%
  Time  (mean ± σ):   6.029 ms ± 46.222 μs  ┊ GC (mean ± σ):  0.00% ± 0.00%
 
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   5.98 ms           Histogram: frequency by time           6.18 ms (top 1%)
 
@@ -292,7 +292,7 @@ BenchmarkTools.Trial: 10000 samples with 1000 evaluations.
  Time  (median):     3.176 ns              ┊ GC (median):    0.00%
  Time  (mean ± σ):   3.262 ns ±  0.882 ns  ┊ GC (mean ± σ):  0.00% ± 0.00%
 
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   3.18 ns           Histogram: frequency by time           4.78 ns (top 1%)
 
@@ -301,7 +301,7 @@ BenchmarkTools.Trial: 10000 samples with 1000 evaluations.
 
 The key point here is that these two benchmarks measure different things, even though their code is similar. In the first example, Julia was able to optimize away `view(a, 1:2, 1:2)` because it could prove that the value wasn't being returned and `a` wasn't being mutated. In the second example, the optimization is not performed because `view(a, 1:2, 1:2)` is a return value of the benchmark expression.
 
-BenchmarkTools will faithfully report the performance of the exact code that you provide to it, including any compiler optimizations that might happen to elide the code completely. It's up to you to design benchmarks which actually exercise the code you intend to exercise. 
+BenchmarkTools will faithfully report the performance of the exact code that you provide to it, including any compiler optimizations that might happen to elide the code completely. It's up to you to design benchmarks which actually exercise the code you intend to exercise.
 
 A common place julia's optimizer may cause a benchmark to not measure what a user thought it was measuring is simple operations where all values are known at compile time. Suppose you wanted to measure the time it takes to add together two integers:
 ```julia
@@ -312,7 +312,7 @@ julia> @btime $a + $b
   0.024 ns (0 allocations: 0 bytes)
 3
 ```
-in this case julia was able to use the properties of `+(::Int, ::Int)` to know that it could safely replace `$a + $b` with `3` at compile time. We can stop the optimizer from doing this by referencing and dereferencing the interpolated variables  
+in this case julia was able to use the properties of `+(::Int, ::Int)` to know that it could safely replace `$a + $b` with `3` at compile time. We can stop the optimizer from doing this by referencing and dereferencing the interpolated variables
 ```julia
 julia> @btime $(Ref(a))[] + $(Ref(b))[]
   1.277 ns (0 allocations: 0 bytes)
@@ -341,7 +341,7 @@ BenchmarkTools.Trial: 10000 samples with 1 evaluations.
  Time  (median):     30.818 μs              ┊ GC (median):    0.00%
  Time  (mean ± σ):   31.777 μs ± 25.161 μs  ┊ GC (mean ± σ):  1.31% ±  1.63%
 
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   26.5 μs           Histogram: frequency by time            41.3 μs (top 1%)
 
@@ -378,35 +378,35 @@ As you can see from the above, a couple of different timing estimates are pretty
 
 ```julia
 julia> minimum(t)
-BenchmarkTools.TrialEstimate: 
+BenchmarkTools.TrialEstimate:
   time:             26.549 μs
   gctime:           0.000 ns (0.00%)
   memory:           16.36 KiB
   allocs:           19
 
 julia> maximum(t)
-BenchmarkTools.TrialEstimate: 
+BenchmarkTools.TrialEstimate:
   time:             1.503 ms
   gctime:           1.401 ms (93.21%)
   memory:           16.36 KiB
   allocs:           19
 
 julia> median(t)
-BenchmarkTools.TrialEstimate: 
+BenchmarkTools.TrialEstimate:
   time:             30.818 μs
   gctime:           0.000 ns (0.00%)
   memory:           16.36 KiB
   allocs:           19
 
 julia> mean(t)
-BenchmarkTools.TrialEstimate: 
+BenchmarkTools.TrialEstimate:
   time:             31.777 μs
   gctime:           415.686 ns (1.31%)
   memory:           16.36 KiB
   allocs:           19
 
 julia> std(t)
-BenchmarkTools.TrialEstimate: 
+BenchmarkTools.TrialEstimate:
   time:             25.161 μs
   gctime:           23.999 μs (95.38%)
   memory:           16.36 KiB
