print & info modify for better README

Author: Ye-Chao-Liu

src/callback.jl

@@ -113,13 +113,13 @@ function build_callback(trajectory_arr, epsilon, max_active, shortcut, shortcut_
         noise_print_update = false
 
         if length(active_set) > max_active
-            verbose > 0 && @info "active set is too large"
+            # verbose > 0 && @info "active set is too large"
             return false
         end
 
         if noise_mixture 
             if rp[] > 1 # stop if the noise is fully added
-                verbose > 0 && @info "noise is fully added"
+                # verbose > 0 && @info "noise is fully added"
                 return false
             end
             noise_update_count += 1
@@ -147,12 +147,12 @@ function build_callback(trajectory_arr, epsilon, max_active, shortcut, shortcut_
         end
 
         if !noise_mixture && shortcut && state.primal / state.dual_gap > shortcut_scale # when gap is large enough -> entangled, stop. (remove if we not use it)
-            verbose > 0 && @info "shortcut"
+            # verbose > 0 && @info "shortcut"
             return false
         end
 
         if state.primal < epsilon # stop if the primal is small enough (main stopping criterion)
-            verbose > 0 &&  @info "primal is small enough"
+            # verbose > 0 &&  @info "primal is small enough"
             return false
         end
 

src/separability_certification.jl

@@ -8,15 +8,15 @@ function separability_certification(C::Array{T, N},
     noise[1] = T(1)
     r_list = T[]
     ϵ_list = T[]
-    @show r_th = separable_ball_radius(T, lmo)
+    r_th = separable_ball_radius(T, lmo)
     res = (active_set = active_set, primal = zero(T))
     for _ in 1:certify_test
         C_rec = (1+ϵ) * C - ϵ * noise
         res = separable_distance(C_rec, lmo; active_set = res.active_set, kwargs...)
         δ = sqrt(res.primal)
-        @show r = δ / ϵ
+        r = δ / ϵ
         if r < r_th
-            println(r, " < ", r_th)
+            # println(r, " < ", r_th)
             return (sep = true, res = res)
         else
             ϵ = (ϵ + ϵ_1) / 2

src/separable_distance.jl

@@ -1,5 +1,5 @@
 """
-    separable_distance(ρ::AbstractMatrix{CT}; dims, measure, fw_algorithm, kwargs...)
+    separable_distance(ρ::AbstractMatrix{CT}, dims::NTuple{N, Int}, lmo::LMO=AlternatingSeparableLMO(float(real(CT)), dims); measure, fw_algorithm, kwargs...)
     separable_distance(C::Array{T, N}; matrix_basis, measure, fw_algorithm, kwargs...)
 
 Computes the distance between the quantum density matrix `ρ` and the separable space under a specific `measure` via a specific `fw_algorithm`:
@@ -60,9 +60,9 @@ function separable_distance(
     epsilon = 1e-6,
     lazy = true,
     max_iteration = 10^5,
-    verbose = 0,
+    verbose = 1,
     logfile = nothing,
-    callback_iter = 10^3,
+    callback_iter = 10^4,
     shortcut = false, # primal > 10 dual_gap stopping criterion
     shortcut_scale = 10,
     kwargs...
@@ -189,6 +189,19 @@ function separable_distance(
             lpad(lmo.fwdata.lmo_counts[1], 7)
             )
     end
+    if verbose > 0
+        if length(active_set) > max_active
+            @info "Stop: active set too large"
+        elseif noise_mixture && rp[] > 1
+            @info "Stop: noise fully added"
+        elseif !noise_mixture && shortcut && primal / dual_gap > shortcut_scale
+            @info "Stop: primal great larger than dual gap (shortcut)"
+        elseif primal < epsilon
+            @info "Stop: primal small enough"
+        else
+            @info "Stop: maximum iteration reached"
+        end
+    end
     flush(logfile)
     return (x = x, v = v, primal = primal, noise_level = rp[], active_set = active_set, lmo = lmo, traj_data = traj_data)
 end