Extend CosineDist support for number types other than Float64 (#61)

* Cleanup whitespace

* Fix for #55: `CosineDist` fails with Ints

The reason CosineDist was failing for integers was because
`eval_start` was only defined for subtypes of AbstractFloat instead
of Number. Since `zero` has a method in Base for any Number, it seemed
reasonable to widen the net on the types of arrays that `eval_start`
instead of writing a new method on Integers.

* Change CosineDist type from Number to Real

Doing this to avoid ambiguities with Complex numbers.

* Add unit tests for CosineDist on integers

* Fix type coercion for compatibility with v0.4

Author: ntdef

src/metrics.jl

@@ -37,10 +37,10 @@ immutable RenyiDivergence{T <: Real} <: PreMetric
         is_zero = q ≈ zero(T)
         is_one = q ≈ one(T)
         is_inf = isinf(q)
-        
+
         # Only positive Rényi divergences are defined
         !is_zero && q < zero(T) && throw(ArgumentError("Order of Rényi divergence not legal, $(q) < 0."))
-        
+
         new(q - 1, !(is_zero || is_one || is_inf), is_zero, is_one, is_inf)
     end
 end
@@ -132,7 +132,7 @@ hamming(a::AbstractArray, b::AbstractArray) = evaluate(Hamming(), a, b)
 hamming{T <: Number}(a::T, b::T) = evaluate(Hamming(), a, b)
 
 # Cosine dist
-function eval_start{T<:AbstractFloat}(::CosineDist, a::AbstractArray{T}, b::AbstractArray{T})
+function eval_start{T<:Real}(::CosineDist, a::AbstractArray{T}, b::AbstractArray{T})
     zero(T), zero(T), zero(T)
 end
 @inline eval_op(::CosineDist, ai, bi) = ai * bi, ai * ai, bi * bi

test/test_dists.jl

@@ -53,6 +53,8 @@ for (x, y) in (([4., 5., 6., 7.], [3., 9., 8., 1.]),
 
     @test_throws DimensionMismatch cosine_dist(1.:2, 1.:3)
     @test cosine_dist(x, y) ≈ (1.0 - 112. / sqrt(19530.))
+    x_int, y_int = map(Int64, x), map(Int64, y)
+    @test cosine_dist(x_int, y_int) == (1.0 - 112. / sqrt(19530.))
 
     @test corr_dist(x, x) < 1.0e-14
     @test corr_dist(x, y) ≈ cosine_dist(x .- mean(x), vec(y) .- mean(y))