improve plots recipes

src/supervised/io.jl

@@ -2,12 +2,13 @@
 Base.print(io::IO, loss::SupervisedLoss, args...) = print(io, typeof(loss).name.name, args...)
 Base.print(io::IO, loss::L1DistLoss, args...) = print(io, "L1DistLoss", args...)
 Base.print(io::IO, loss::L2DistLoss, args...) = print(io, "L2DistLoss", args...)
-Base.print{P}(io::IO, loss::LPDistLoss{P}, args...) = print(io, typeof(loss).name.name, " with P=$(P)", args...)
-Base.print(io::IO, loss::L1EpsilonInsLoss, args...) = print(io, typeof(loss).name.name, " with ɛ=$(loss.ε)", args...)
-Base.print(io::IO, loss::L2EpsilonInsLoss, args...) = print(io, typeof(loss).name.name, " with ɛ=$(loss.ε)", args...)
-Base.print(io::IO, loss::QuantileLoss, args...) = print(io, typeof(loss).name.name, " with τ=$(loss.τ)", args...)
-Base.print(io::IO, loss::SmoothedL1HingeLoss, args...) = print(io, typeof(loss).name.name, " with γ = $(loss.gamma)", args...)
-Base.print(io::IO, loss::PeriodicLoss, args...) = print(io, typeof(loss).name.name, " with circumf=$(round(loss.k / 2π,1))", args...)
+Base.print{P}(io::IO, loss::LPDistLoss{P}, args...) = print(io, typeof(loss).name.name, " with P = $(P)", args...)
+Base.print(io::IO, loss::L1EpsilonInsLoss, args...) = print(io, typeof(loss).name.name, " with \$\\varepsilon\$ = $(loss.ε)", args...)
+Base.print(io::IO, loss::L2EpsilonInsLoss, args...) = print(io, typeof(loss).name.name, " with \$\\varepsilon\$ = $(loss.ε)", args...)
+Base.print(io::IO, loss::QuantileLoss, args...) = print(io, typeof(loss).name.name, " with \$\\tau\$ = $(loss.τ)", args...)
+Base.print(io::IO, loss::SmoothedL1HingeLoss, args...) = print(io, typeof(loss).name.name, " with \$\\gamma\$ = $(loss.gamma)", args...)
+Base.print(io::IO, loss::DWDMarginLoss, args...) = print(io, typeof(loss).name.name, " with q = $(loss.q)", args...)
+Base.print(io::IO, loss::PeriodicLoss, args...) = print(io, typeof(loss).name.name, " with circumf = $(round(loss.k / 2π,1))", args...)
 Base.print(io::IO, loss::ScaledLoss, args...) = print(io, typeof(loss).name.name, " $(loss.factor) * [ $(loss.loss) ]", args...)
 
 # -------------------------------------------------------------
@@ -16,18 +17,46 @@ Base.print(io::IO, loss::ScaledLoss, args...) = print(io, typeof(loss).name.name
 _loss_xguide(loss::MarginLoss) = "y ⋅ h(x)"
 _loss_xguide(loss::DistanceLoss) = "h(x) - y"
 
-@recipe function plot(loss::SupervisedLoss, xmin = -2, xmax = 2)
+@recipe function plot(drv::Deriv, xmin, xmax)
+    xguide --> _loss_xguide(drv.loss)
+    yguide --> "L'(y, h(x))"
+    label  --> string(drv.loss)
+    deriv_fun(drv.loss), xmin, xmax
+end
+
+@recipe function plot(drv::Deriv, rng = -2:0.05:2)
+    xguide --> _loss_xguide(drv.loss)
+    yguide --> "L'(y, h(x))"
+    label  --> string(drv.loss)
+    deriv_fun(drv.loss), rng
+end
+
+@recipe function plot(loss::SupervisedLoss, xmin, xmax)
     xguide --> _loss_xguide(loss)
     yguide --> "L(y, h(x))"
     label  --> string(loss)
     value_fun(loss), xmin, xmax
 end
 
-@recipe function plot{T<:SupervisedLoss}(losses::AbstractVector{T}, xmin = -2, xmax = 2)
+@recipe function plot(loss::SupervisedLoss, rng = -2:0.05:2)
+    xguide --> _loss_xguide(loss)
+    yguide --> "L(y, h(x))"
+    label  --> string(loss)
+    value_fun(loss), rng
+end
+
+@recipe function plot{T<:SupervisedLoss}(losses::AbstractVector{T}, xmin, xmax)
     for loss in losses
         @series begin
             loss, xmin, xmax
         end
     end
 end
+@recipe function plot{T<:SupervisedLoss}(losses::AbstractVector{T}, rng = -2:0.05:2)
+    for loss in losses
+        @series begin
+            loss, rng
+        end
+    end
+end