Represent OptimizationTrace as a Vector (#257)

JuliaNLSolvers · Aug 12, 2016 · f255ff4 · f255ff4
1 parent 013d264
commit f255ff4
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Showing 19 changed files with 38 additions and 53 deletions.
diff --git a/src/accelerated_gradient_descent.jl b/src/accelerated_gradient_descent.jl
@@ -80,7 +80,7 @@ function optimize{T}(d::DifferentiableFunction,
     lsr = LineSearchResults(T)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @agdtrace
 

diff --git a/src/api.jl b/src/api.jl
@@ -3,35 +3,35 @@ minimizer(r::OptimizationResults) = r.minimum
 minimum(r::OptimizationResults) = r.f_minimum
 iterations(r::OptimizationResults) = r.iterations
 iteration_limit_reached(r::OptimizationResults) = r.iteration_converged
-trace(r::OptimizationResults) = length(r.trace.states) > 0 ? r.trace : error("No trace in optimization results. To get a trace, run optimize() with store_trace = true.")
+trace(r::OptimizationResults) = length(r.trace) > 0 ? r.trace : error("No trace in optimization results. To get a trace, run optimize() with store_trace = true.")
 
 function x_trace(r::UnivariateOptimizationResults)
 	tr = trace(r)
-	!haskey(tr.states[1].metadata, "x_minimum") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
-    [state.metadata["x_minimum"] for state in tr.states]
+	!haskey(tr[1].metadata, "x_minimum") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
+    [ state.metadata["x_minimum"] for state in tr ]
 end
 function x_lower_trace(r::UnivariateOptimizationResults)
 	tr = trace(r)
-	!haskey(tr.states[1].metadata, "x_lower") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
-    [state.metadata["x_lower"] for state in tr.states]
+	!haskey(tr[1].metadata, "x_lower") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
+    [ state.metadata["x_lower"] for state in tr ]
 end
 x_lower_trace(r::MultivariateOptimizationResults) = error("x_lower_trace is not implemented for $(method(r)).")
 function x_upper_trace(r::UnivariateOptimizationResults)
 	tr = trace(r)
-	!haskey(tr.states[1].metadata, "x_upper") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
-    [state.metadata["x_upper"] for state in tr.states]
+	!haskey(tr[1].metadata, "x_upper") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
+    [ state.metadata["x_upper"] for state in tr ]
 end
 x_upper_trace(r::MultivariateOptimizationResults) = error("x_upper_trace is not implemented for $(method(r)).")
 
 function x_trace(r::MultivariateOptimizationResults)
 	tr = trace(r)
-	!haskey(tr.states[1].metadata, "x") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
-    [state.metadata["x"] for state in tr.states]
+	!haskey(tr[1].metadata, "x") && error("Trace does not contain x. To get a trace of x, run optimize() with extended_trace = true")
+    [ state.metadata["x"] for state in tr ]
 end
 
-f_trace(r::OptimizationResults) = [state.value for state in trace(r).states]
+f_trace(r::OptimizationResults) = [ state.value for state in trace(r) ]
 g_norm_trace(r::OptimizationResults) = error("g_norm_trace is not implemented for $(method(r)).")
-g_norm_trace(r::MultivariateOptimizationResults) = [state.g_norm for state in trace(r).states]
+g_norm_trace(r::MultivariateOptimizationResults) = [ state.g_norm for state in trace(r) ]
 
 f_calls(r::OptimizationResults) = r.f_calls
 

diff --git a/src/bfgs.jl b/src/bfgs.jl
@@ -88,7 +88,7 @@ function optimize{T}(d::DifferentiableFunction,
     I = eye(size(invH)...)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @bfgstrace
 

diff --git a/src/brent.jl b/src/brent.jl
@@ -61,7 +61,7 @@ function optimize{T <: AbstractFloat}(
     converged = false
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = store_trace || show_trace || extended_trace || callback != nothing
     @brenttrace
 

diff --git a/src/cg.jl b/src/cg.jl
@@ -145,7 +145,7 @@ function optimize{T}(df::DifferentiableFunction,
     lsr = LineSearchResults(T)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @cgtrace
 

diff --git a/src/golden_section.jl b/src/golden_section.jl
@@ -51,7 +51,7 @@ function optimize{T <: AbstractFloat}(f::Function, x_lower::T, x_upper::T,
     converged = false
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = store_trace || show_trace || extended_trace || callback != nothing
     @goldensectiontrace
 

diff --git a/src/gradient_descent.jl b/src/gradient_descent.jl
@@ -75,7 +75,7 @@ function optimize{T}(d::DifferentiableFunction,
     lsr = LineSearchResults(T)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @gdtrace
 

diff --git a/src/l_bfgs.jl b/src/l_bfgs.jl
@@ -148,7 +148,7 @@ function optimize{T}(d::DifferentiableFunction,
     twoloop_q, twoloop_alpha = Array(T, n), Array(T, mo.m)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @lbfgstrace
 

diff --git a/src/levenberg_marquardt.jl b/src/levenberg_marquardt.jl
@@ -60,7 +60,7 @@ function levenberg_marquardt{T}(f::Function, g::Function, initial_x::AbstractVec
     m_buffer = Vector{T}(m)
 
     # Maintain a trace of the system.
-    tr = OptimizationTrace(LevenbergMarquardt())
+    tr = OptimizationTrace{typeof(LevenbergMarquardt())}()
     if show_trace
         d = Dict("lambda" => lambda)
         os = OptimizationState(iterCt, sumabs2(fcur), NaN, d)

diff --git a/src/momentum_gradient_descent.jl b/src/momentum_gradient_descent.jl
@@ -73,7 +73,7 @@ function optimize{T}(d::DifferentiableFunction,
     lsr = LineSearchResults(T)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @mgdtrace
 

diff --git a/src/nelder_mead.jl b/src/nelder_mead.jl
@@ -151,7 +151,7 @@ function optimize{T}(f::Function,
     # Maintain a trace
     f_x_previous, f_x = NaN, nmobjective(f_simplex, m, n)
     f_lowest = f_simplex[i_order[1]]
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.show_trace || o.store_trace || o.extended_trace || o.callback != nothing
     @nmtrace
 

diff --git a/src/newton.jl b/src/newton.jl
@@ -82,7 +82,7 @@ function optimize{T}(d::TwiceDifferentiableFunction,
     lsr = LineSearchResults(T)
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @newtontrace
 

diff --git a/src/newton_trust_region.jl b/src/newton_trust_region.jl
@@ -284,7 +284,7 @@ function optimize{T}(d::TwiceDifferentiableFunction,
     lambda = NaN
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @newton_tr_trace
 

diff --git a/src/particle_swarm.jl b/src/particle_swarm.jl
@@ -123,7 +123,7 @@ function optimize{T}(cost_function::Function,
         X[j, 1] = initial_x[j]
         X_best[j, 1] = initial_x[j]
     end
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
 
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @swarmtrace

diff --git a/src/simulated_annealing.jl b/src/simulated_annealing.jl
@@ -70,7 +70,7 @@ function optimize{T}(cost::Function,
     best_f_x = f_x
 
     # Trace the history of states visited
-    tr = OptimizationTrace(mo)
+    tr = OptimizationTrace{typeof(mo)}()
     tracing = o.store_trace || o.show_trace || o.extended_trace || o.callback != nothing
     @satrace
 

diff --git a/src/types.jl b/src/types.jl
@@ -46,15 +46,11 @@ immutable OptimizationState{T <: Optimizer}
     metadata::Dict
 end
 
-immutable OptimizationTrace{T<:Optimizer}
-    states::Vector{OptimizationState{T}}
-end
-
-OptimizationTrace{T}(m::T) = OptimizationTrace(Array{OptimizationState{T}}(0))
+typealias OptimizationTrace{T} Vector{OptimizationState{T}}
 
 abstract OptimizationResults
 
-type MultivariateOptimizationResults{T,N} <: OptimizationResults
+type MultivariateOptimizationResults{T,N,M} <: OptimizationResults
     method::String
     initial_x::Array{T,N}
     minimum::Array{T,N}
@@ -67,12 +63,12 @@ type MultivariateOptimizationResults{T,N} <: OptimizationResults
     f_tol::Float64
     g_converged::Bool
     g_tol::Float64
-    trace::OptimizationTrace
+    trace::OptimizationTrace{M}
     f_calls::Int
     g_calls::Int
 end
 
-type UnivariateOptimizationResults{T} <: OptimizationResults
+type UnivariateOptimizationResults{T,M} <: OptimizationResults
     method::String
     initial_lower::T
     initial_upper::T
@@ -83,7 +79,7 @@ type UnivariateOptimizationResults{T} <: OptimizationResults
     converged::Bool
     rel_tol::Float64
     abs_tol::Float64
-    trace::OptimizationTrace
+    trace::OptimizationTrace{M}
     f_calls::Int
 end
 
@@ -110,21 +106,10 @@ function Base.show(io::IO, t::OptimizationState)
     return
 end
 
-Base.push!(t::OptimizationTrace, s::OptimizationState) = push!(t.states, s)
-Base.getindex(t::OptimizationTrace, i::Integer) = getindex(t.states, i)
-Base.endof(t::OptimizationTrace) = endof(t.states)
-Base.length(t::OptimizationTrace) = length(t.states)
-
-function Base.setindex!(t::OptimizationTrace,
-                        s::OptimizationState,
-                        i::Integer)
-    setindex!(t.states, s, i)
-end
-
-function Base.show(io::IO, t::OptimizationTrace)
+function Base.show(io::IO, tr::OptimizationTrace)
     @printf io "Iter     Function value   Gradient norm \n"
     @printf io "------   --------------   --------------\n"
-    for state in t.states
+    for state in tr
         show(io, state)
     end
     return
@@ -181,7 +166,7 @@ function Base.append!(a::MultivariateOptimizationResults, b::MultivariateOptimiz
     a.x_converged = x_converged(b)
     a.f_converged = f_converged(b)
     a.g_converged = g_converged(b)
-    append!(a.trace.states, b.trace.states)
+    append!(a.trace, b.trace)
     a.f_calls += f_calls(b)
     a.g_calls += g_calls(b)
 end

diff --git a/test/callbacks.jl b/test/callbacks.jl
@@ -12,7 +12,7 @@ let
                    SimulatedAnnealing())
         ot_run = false
         cb = tr -> begin
-            @test tr.states[end].iteration % 3 == 0
+            @test tr[end].iteration % 3 == 0
             ot_run = true
         end
         optimize(f, initial_x, method = method, callback = cb, show_every=3, store_trace=true)
@@ -33,7 +33,7 @@ let
                    MomentumGradientDescent())
         ot_run = false
         cb = tr -> begin
-            @test tr.states[end].iteration % 3 == 0
+            @test tr[end].iteration % 3 == 0
             ot_run = true
         end
         optimize(d2, initial_x, method = method, callback = cb, show_every=3, store_trace=true)
@@ -51,7 +51,7 @@ let
     for method in (Newton(),)
         ot_run = false
         cb = tr -> begin
-            @test tr.states[end].iteration % 3 == 0
+            @test tr[end].iteration % 3 == 0
             ot_run = true
         end
         optimize(d3, initial_x, method = method, callback = cb, show_every=3, store_trace=true)

diff --git a/test/newton_trust_region.jl b/test/newton_trust_region.jl
@@ -109,7 +109,7 @@ let
     d = TwiceDifferentiableFunction(f, g!, h!)
 
     results = Optim.optimize(d, [0.0], method=NewtonTrustRegion())
-    @assert length(results.trace.states) == 0
+    @assert length(results.trace) == 0
     @assert results.g_converged
     @assert norm(results.minimum - [5.0]) < 0.01
 

diff --git a/test/types.jl b/test/types.jl
@@ -1,7 +1,7 @@
 let
     solver = NelderMead()
     T = typeof(solver)
-    trace = OptimizationTrace(solver)
+    trace = OptimizationTrace{T}()
     push!(trace,OptimizationState{T}(1,1.0,1.0,Dict()))
     push!(trace,OptimizationState{T}(2,1.0,1.0,Dict()))
     @test length(trace) == 2