rework result_type (#140)

* rework result_type

The essence of `result_type` is based on the `eltype(a)`, and
`result_type(::PreMetric, ::AbstractArray, ::AbstractArray)` only
serves as an convenient method.

There's no functionality changes in this commit, only to reorganize
the codes to ease future development.

* update docstring

* delete usage example

Author: johnnychen94

src/generic.jl

@@ -24,7 +24,15 @@ abstract type Metric <: SemiMetric end
 
 # Generic functions
 
-result_type(::PreMetric, ::AbstractArray, ::AbstractArray) = Float64
+"""
+    result_type(dist::PreMetric, Ta::Type, Tb::Type) -> T
+    result_type(dist::PreMetric, a::AbstractArray, b::AbstractArray) -> T
+
+Infer the result type of metric `dist` with input type `Ta` and `Tb`, or input
+data `a` and `b`.
+"""
+result_type(::PreMetric, ::Type, ::Type) = Float64 # fallback
+result_type(dist::PreMetric, a::AbstractArray, b::AbstractArray) = result_type(dist, eltype(a), eltype(b))
 
 
 # Generic column-wise evaluation

src/mahalanobis.jl

@@ -8,8 +8,8 @@ struct SqMahalanobis{T} <: SemiMetric
     qmat::Matrix{T}
 end
 
-result_type(::Mahalanobis{T}, ::AbstractArray, ::AbstractArray) where {T} = T
-result_type(::SqMahalanobis{T}, ::AbstractArray, ::AbstractArray) where {T} = T
+result_type(::Mahalanobis{T}, ::Type, ::Type) where {T} = T
+result_type(::SqMahalanobis{T}, ::Type, ::Type) where {T} = T
 
 # SqMahalanobis
 

src/metrics.jl

@@ -252,9 +252,8 @@ end
     end
     return eval_end(d, s)
 end
-result_type(dist::UnionMetrics, a::AbstractArray, b::AbstractArray) =
-    typeof(evaluate(dist, oneunit(eltype(a)), oneunit(eltype(b))))
-
+result_type(dist::UnionMetrics, Ta::Type, Tb::Type) =
+    typeof(evaluate(dist, oneunit(Ta), oneunit(Tb)))
 eval_start(d::UnionMetrics, a::AbstractArray, b::AbstractArray) =
     zero(result_type(d, a, b))
 eval_end(d::UnionMetrics, s) = s
@@ -352,7 +351,7 @@ evaluate(::CorrDist, a::AbstractArray, b::AbstractArray) = cosine_dist(_centrali
 # Ambiguity resolution
 evaluate(::CorrDist, a::Array, b::Array) = cosine_dist(_centralize(a), _centralize(b))
 corr_dist(a::AbstractArray, b::AbstractArray) = evaluate(CorrDist(), a, b)
-result_type(::CorrDist, a::AbstractArray, b::AbstractArray) = result_type(CosineDist(), a, b)
+result_type(::CorrDist, Ta::Type, Tb::Type) = result_type(CosineDist(), Ta, Tb)
 
 # ChiSqDist
 @inline eval_op(::ChiSqDist, ai, bi) = (d = abs2(ai - bi) / (ai + bi); ifelse(ai != bi, d, zero(d)))
@@ -452,9 +451,8 @@ end
 
 eval_end(::SpanNormDist, s) = s[2] - s[1]
 spannorm_dist(a::AbstractArray, b::AbstractArray) = evaluate(SpanNormDist(), a, b)
-result_type(dist::SpanNormDist, a::AbstractArray, b::AbstractArray) =
-    typeof(eval_op(dist, oneunit(eltype(a)), oneunit(eltype(b))))
-
+result_type(dist::SpanNormDist, Ta::Type, Tb::Type) =
+    typeof(eval_op(dist, oneunit(Ta), oneunit(Tb)))
 
 # Jaccard
 

src/wmetrics.jl

@@ -42,8 +42,8 @@ Base.eltype(x::UnionWeightedMetrics) = eltype(x.weights)
 function evaluate(dist::UnionWeightedMetrics, a::Number, b::Number)
     eval_end(dist, eval_op(dist, a, b, oneunit(eltype(dist))))
 end
-result_type(dist::UnionWeightedMetrics, a::AbstractArray, b::AbstractArray) =
-    typeof(evaluate(dist, oneunit(eltype(a)), oneunit(eltype(b))))
+result_type(dist::UnionWeightedMetrics, Ta::Type, Tb::Type) =
+    typeof(evaluate(dist, oneunit(Ta), oneunit(Tb)))
 
 @inline function eval_start(d::UnionWeightedMetrics, a::AbstractArray, b::AbstractArray)
     zero(result_type(d, a, b))