_computescale methods for maximum and mean (#46)

* _computescale methods for maximum and mean

* simplify _computescale for scale=mean

only divide by the number of items once;
do not change types (just work with Float64)

* doc comment

Author: heliosdrm

src/matrices.jl

@@ -169,8 +169,9 @@ by the following keyword arguments:
 * `scale=1` : a function of the distance matrix (see [`distancematrix`](@ref)),
   or a fixed number, used to scale the value of `ε`. Typical choices are
   `maximum` or `mean`, such that the threshold `ε` is defined as a ratio of the
-  maximum or the mean distance between data points, respectively.
-  Use `1` to keep the distances unscaled (default).
+  maximum or the mean distance between data points, respectively (using
+  `mean` or `maximum` calls specialized versions that are faster than the naive
+  approach).  Use `1` to keep the distances unscaled (default).
 * `fixedrate::Bool=false` : a flag that indicates if `ε` should be
   taken as a target fixed recurrence rate (see [`recurrencerate`](@ref)).
   If `fixedrate` is set to `true`, `ε` must be a value between 0 and 1,
@@ -231,6 +232,23 @@ end
 # distance matrix; otherwise return the value of `scale` itself
 _computescale(scale::Function, x, y, metric) = scale(distancematrix(x, y, metric))
 _computescale(scale::Real, args...) = scale
+# specific methods to avoid `distancematrix`
+function _computescale(scale::typeof(maximum), x::T, y::T, metric::Metric) where {T}
+    maxvalue = zero(eltype(x))
+    @inbounds for xi in x, yj in y
+        newvalue = evaluate(metric, xi, yj)
+        (newvalue > maxvalue) && (maxvalue = newvalue)
+    end
+    return maxvalue
+end
+function _computescale(scale::typeof(mean), x, y, metric::Metric)
+    meanvalue = 0.0
+    @inbounds for xi in x, yj in y
+        meanvalue += evaluate(metric, xi, yj)
+    end
+    return meanvalue/(length(x)*length(y))
+end
+
 
 # Internal methods to calculate the matrix:
 # If the metric is supplied as a string, get the corresponding Metric from Distances