Soft bounds on x_abschange (#503)

* Soft bounds on x_abschange * Use right type in checked_dphi0
JuliaNLSolvers · Jan 3, 2018 · 9b75e90 · 9b75e90
1 parent 5099dd4
commit 9b75e90
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Showing 2 changed files with 3 additions and 3 deletions.
diff --git a/src/utilities/assess_convergence.jl b/src/utilities/assess_convergence.jl
@@ -47,7 +47,7 @@ end
 function default_convergence_assessment(state::AbstractOptimizerState, d, options)
     x_converged, f_converged, f_increased, g_converged = false, false, false, false
 
-    if x_abschange(state.x, state.x_previous) < options.x_tol
+    if x_abschange(state.x, state.x_previous) ≤ options.x_tol
         x_converged = true
     end
 

diff --git a/src/utilities/perform_linesearch.jl b/src/utilities/perform_linesearch.jl
@@ -2,7 +2,7 @@ checked_dphi0!(state, d, method) = vecdot(gradient(d), state.s)
 function checked_dphi0!(state, d, method::M) where M<:Union{BFGS, LBFGS}
     # If invH is not positive definite, reset it
     dphi0 = vecdot(gradient(d), state.s)
-    if dphi0 >= 0.0
+    if dphi0 >= zero(dphi0)
         # "reset" Hessian approximation
         if M <: BFGS
             copy!(state.invH, method.initial_invH(state.x))
@@ -19,7 +19,7 @@ end
 function checked_dphi0!(state, d, method::ConjugateGradient)
     # Reset the search direction if it becomes corrupted
     dphi0 = vecdot(gradient(d), state.s)
-    if dphi0 >= 0
+    if dphi0 >= zero(dphi0)
         state.s .= .-state.pg
         dphi0 = vecdot(gradient(d), state.s)
     end