Use inline at function level

README.md

@@ -29,28 +29,28 @@ julia> iter = Iterators.filter(x -> x != 10, 1:10^7);
 julia> wv(el) = 1.0
 
 julia> @btime itsample($rng, $iter, 10^4, algRSWRSKIP);
-  14.578 ms (5 allocations: 156.39 KiB)
+  11.744 ms (5 allocations: 156.39 KiB)
 
 julia> @btime sample($rng, collect($iter), 10^4; replace=true);
-  136.139 ms (20 allocations: 146.91 MiB)
+  131.933 ms (20 allocations: 146.91 MiB)
 
 julia> @btime itsample($rng, $iter, 10^4, algL);
-  10.591 ms (3 allocations: 78.22 KiB)
+  10.260 ms (3 allocations: 78.22 KiB)
 
 julia> @btime sample($rng, collect($iter), 10^4; replace=false);
-  134.352 ms (27 allocations: 147.05 MiB)
+  132.069 ms (27 allocations: 147.05 MiB)
 
 julia> @btime itsample($rng, $iter, $wv, 10^4, algWRSWRSKIP);
-  32.892 ms (12 allocations: 568.83 KiB)
+  32.278 ms (18 allocations: 547.34 KiB)
 
 julia> @btime sample($rng, collect($iter), Weights($wv.($iter)), 10^4; replace=true);
-  545.058 ms (45 allocations: 702.33 MiB)
+  348.220 ms (49 allocations: 675.21 MiB)
 
 julia> @btime itsample($rng, $iter, $wv, 10^4, algAExpJ);
-  41.092 ms (11 allocations: 234.78 KiB)
+  39.965 ms (11 allocations: 234.78 KiB)
 
 julia> @btime sample($rng, collect($iter), Weights($wv.($iter)), 10^4; replace=false);
-  312.880 ms (43 allocations: 370.19 MiB)
+  306.039 ms (43 allocations: 370.19 MiB)
 ```
 
 More information can be found in the [documentation](https://juliadynamics.github.io/StreamSampling.jl/dev/).

docs/src/index.md

@@ -31,7 +31,7 @@ julia> using StreamSampling
 julia> rs = ReservoirSample(Int, 5);
 
 julia> for x in 1:100
-           @inline update!(rs, x)
+           update!(rs, x)
        end
 
 julia> value(rs)

src/StreamSampling.jl

@@ -127,6 +127,11 @@ export update!
 
 Returns the elements collected in the sample at the current 
 sampling stage.
+
+Note that even if the sampling respects the schema it is assigned
+when [`ReservoirSample`](@ref) is instantiated, some ordering in 
+the sample can be more probable than others. To represent each one 
+with the same probability call `shuffle!` over the result.
 """
 function value end
 

src/UnweightedSamplingMulti.jl

@@ -72,41 +72,41 @@ function ReservoirSample(rng::AbstractRNG, T, n::Integer, method::AlgRSWRSKIP; o
     end
 end
 
-function update!(s::Union{SampleMultiAlgR, SampleMultiOrdAlgR}, el)
+@inline function update!(s::Union{SampleMultiAlgR, SampleMultiOrdAlgR}, el)
     n = length(s.value)
     s.seen_k += 1
     if s.seen_k <= n
-        s.value[s.seen_k] = el
+        @inbounds s.value[s.seen_k] = el
     else
         j = rand(s.rng, 1:s.seen_k)
         if j <= n
-            s.value[j] = el
+            @inbounds s.value[j] = el
             update_order!(s, j)
         end
     end
     return s
 end
-function update!(s::Union{SampleMultiAlgL, SampleMultiOrdAlgL}, el)
+@inline function update!(s::Union{SampleMultiAlgL, SampleMultiOrdAlgL}, el)
     n = length(s.value)
     s.seen_k += 1
     s.skip_k -= 1
     if s.seen_k <= n
-        s.value[s.seen_k] = el
+        @inbounds s.value[s.seen_k] = el
         s.seen_k == n && @inline recompute_skip!(s, n)
     elseif s.skip_k < 0
         j = rand(s.rng, 1:n)
-        s.value[j] = el
+        @inbounds s.value[j] = el
         update_order!(s, j)
         @inline recompute_skip!(s, n)
     end
     return s
 end
-function update!(s::AbstractWrReservoirSampleMulti, el)
+@inline function update!(s::AbstractWrReservoirSampleMulti, el)
     n = length(s.value)
     s.seen_k += 1
     s.skip_k -= 1
     if s.seen_k <= n
-        s.value[s.seen_k] = el
+        @inbounds s.value[s.seen_k] = el
         if s.seen_k == n
             recompute_skip!(s, n)
             s.value = sample(s.rng, s.value, n, ordered=is_ordered(s))
@@ -226,7 +226,7 @@ end
 
 function update_all!(s, iter, ordered)
     for x in iter
-        @inline update!(s, x)
+        update!(s, x)
     end
     return ordered ? ordered_value(s) : shuffle!(s.rng, value(s))
 end

src/UnweightedSamplingSingle.jl

@@ -33,15 +33,14 @@ function ReservoirSample(rng::AbstractRNG, T, method::AlgR)
     return SampleSingleAlgR{T, typeof(rng)}(0, rng)
 end
 
-function update!(s::SampleSingleAlgR, el)
+@inline function update!(s::SampleSingleAlgR, el)
     s.state += 1
     if rand(s.rng) <= 1/s.state
         s.value = el
     end
     return s
 end
-
-function update!(s::SampleSingleAlgL, el)
+@inline function update!(s::SampleSingleAlgL, el)
     if s.skip_k > 0
         s.skip_k -= 1
     else
@@ -67,7 +66,7 @@ end
 function reservoir_sample(rng, iter, method::ReservoirAlgorithm = algL)
     s = ReservoirSample(rng, calculate_eltype(iter), method)
     for x in iter
-        @inline update!(s, x)
+        update!(s, x)
     end
     return value(s)
 end

src/WeightedSamplingMulti.jl

@@ -63,7 +63,7 @@ function ReservoirSample(rng::AbstractRNG, T, n::Integer, method::AlgWRSWRSKIP;
     end
 end
 
-function update!(s::SampleMultiAlgARes, el, w)
+@inline function update!(s::SampleMultiAlgARes, el, w)
     n = s.n
     s.seen_k += 1
     priority = -randexp(s.rng)/w
@@ -78,7 +78,7 @@ function update!(s::SampleMultiAlgARes, el, w)
     end
     return s
 end
-function update!(s::SampleMultiAlgAExpJ, el, w)
+@inline function update!(s::SampleMultiAlgAExpJ, el, w)
     n = s.n
     s.seen_k += 1
     s.state -= w
@@ -94,13 +94,13 @@ function update!(s::SampleMultiAlgAExpJ, el, w)
     end
     return s
 end
-function update!(s::Union{SampleMultiAlgWRSWRSKIP, SampleMultiOrdAlgWRSWRSKIP}, el, w)
+@inline function update!(s::Union{SampleMultiAlgWRSWRSKIP, SampleMultiOrdAlgWRSWRSKIP}, el, w)
     n = length(s.value)
     s.seen_k += 1
     s.state += w
     if s.seen_k <= n
-        s.value[s.seen_k] = el
-        s.weights[s.seen_k] = w
+        @inbounds s.value[s.seen_k] = el
+        @inbounds s.weights[s.seen_k] = w
         if s.seen_k == n
             s.value = sample(s.rng, s.value, weights(s.weights), n; ordered = is_ordered(s))
             @inline recompute_skip!(s, n)
@@ -201,7 +201,7 @@ end
 
 function update_all!(s, iter, wv, ordered)
     for x in iter
-        @inline update!(s, x, wv(x))
+        update!(s, x, wv(x))
     end
     return ordered ? ordered_value(s) : shuffle!(s.rng, value(s))
 end

src/WeightedSamplingSingle.jl

@@ -16,7 +16,7 @@ function value(s::SampleSingleAlgAExpJ)
     return s.value
 end
 
-function update!(s::SampleSingleAlgAExpJ, el, weight)
+@inline function update!(s::SampleSingleAlgAExpJ, el, weight)
     s.state += weight
     if s.skip_w <= s.state
         s.value = el
@@ -32,7 +32,7 @@ end
 function itsample(rng::AbstractRNG, iter, wv::Function, method::ReservoirAlgorithm = algAExpJ)
     s = ReservoirSample(rng, Base.@default_eltype(iter), algAExpJ)
     for x in iter
-        @inline update!(s, x, wv(x))
+        update!(s, x, wv(x))
     end
     return value(s)
 end