Add a note on the first value

Author: avik-pal

Diff for: docs/src/basics/Logging.md

@@ -49,6 +49,11 @@ sol = solve(prob; trace_level = TraceAll(), store_trace = Val(true));
 sol.trace
 ```
 
+!!! note
+    
+    For `iteration == 0` only the `norm(fu, Inf)` is guaranteed to be meaningful. The other
+    values being meaningful are solver dependent.
+
 ## API
 
 ```@docs

Diff for: src/gaussnewton.jl

@@ -109,7 +109,7 @@ function SciMLBase.__init(prob::NonlinearLeastSquaresProblem{uType, iip}, alg_::
     abstol, reltol, tc_cache_1 = init_termination_cache(abstol, reltol, fu1, u,
         termination_condition)
     _, _, tc_cache_2 = init_termination_cache(abstol, reltol, fu1, u, termination_condition)
-    trace = init_nonlinearsolve_trace(alg, u, fu1, J, du; kwargs...)
+    trace = init_nonlinearsolve_trace(alg, u, fu1, ApplyArray(__zero, J), du; kwargs...)
 
     return GaussNewtonCache{iip}(f, alg, u, copy(u), fu1, fu2, zero(fu1), du, p, uf,
         linsolve, J, JᵀJ, Jᵀf, jac_cache, false, maxiters, internalnorm, ReturnCode.Default,

Diff for: src/levenberg.jl

@@ -221,7 +221,7 @@ function SciMLBase.__init(prob::Union{NonlinearProblem{uType, iip},
         tc_cache_2 = nothing
     end
 
-    trace = init_nonlinearsolve_trace(alg, u, fu1, J, du; kwargs...)
+    trace = init_nonlinearsolve_trace(alg, u, fu1, ApplyArray(__zero, J), du; kwargs...)
 
     if _unwrap_val(linsolve_with_JᵀJ)
         mat_tmp = zero(JᵀJ)

Diff for: src/pseudotransient.jl

@@ -95,7 +95,7 @@ function SciMLBase.__init(prob::NonlinearProblem{uType, iip}, alg_::PseudoTransi
 
     abstol, reltol, tc_cache = init_termination_cache(abstol, reltol, fu1, u,
         termination_condition)
-    trace = init_nonlinearsolve_trace(alg, u, fu1, J, du; kwargs...)
+    trace = init_nonlinearsolve_trace(alg, u, fu1, ApplyArray(__zero, J), du; kwargs...)
 
     return PseudoTransientCache{iip}(f, alg, u, copy(u), fu1, fu2, du, p, alpha, res_norm,
         uf, linsolve, J, jac_cache, false, maxiters, internalnorm, ReturnCode.Default,

Diff for: src/raphson.jl

@@ -89,7 +89,7 @@ function SciMLBase.__init(prob::NonlinearProblem{uType, iip}, alg_::NewtonRaphso
         termination_condition)
 
     ls_cache = init_linesearch_cache(alg.linesearch, f, u, p, fu1, Val(iip))
-    trace = init_nonlinearsolve_trace(alg, u, fu1, J, du; kwargs...)
+    trace = init_nonlinearsolve_trace(alg, u, fu1, ApplyArray(__zero, J), du; kwargs...)
 
     return NewtonRaphsonCache{iip}(f, alg, u, copy(u), fu1, fu2, du, p, uf, linsolve, J,
         jac_cache, false, maxiters, internalnorm, ReturnCode.Default, abstol, reltol, prob,

Diff for: src/trace.jl

@@ -146,7 +146,9 @@ __copy(x) = x
     trace_level::Tr
 end
 
-reset!(trace::NonlinearSolveTrace) = resize!(trace.history, 0)
+function reset!(trace::NonlinearSolveTrace)
+    (trace.history !== nothing && resize!(trace.history, 0))
+end
 
 function Base.show(io::IO, trace::NonlinearSolveTrace)
     for entry in trace.history
@@ -166,7 +168,7 @@ function init_nonlinearsolve_trace(alg, ::Val{show_trace},
         trace_level::AbstractNonlinearSolveTraceLevel, ::Val{store_trace}, u, fu, J,
         δu, ::Val{uses_jac_inverse}) where {show_trace, store_trace, uses_jac_inverse}
     if show_trace
-        Base.printstyled("\nAlgorithm: "; italic = true)
+        print("\nAlgorithm: ")
         Base.printstyled(alg, "\n\n"; color = :green, bold = true)
     end
     J_ = uses_jac_inverse ? (trace_level isa TraceMinimal ? J : inv(J)) : J
@@ -205,8 +207,8 @@ function update_trace!(trace::NonlinearSolveTrace{ShT, StT}, iter, u, fu, J, δu
         return trace
     end
 
-    show_now = ShT && (iter % trace.trace_level.print_frequency == 0)
-    store_now = StT && (iter % trace.trace_level.store_frequency == 0)
+    show_now = ShT && (iter % trace.trace_level.print_frequency == 1)
+    store_now = StT && (iter % trace.trace_level.store_frequency == 1)
     (show_now || store_now) && (entry = __trace_entry(trace.trace_level, iter, u, fu, J,
         δu, α))
     store_now && push!(trace.history, entry)
@@ -226,8 +228,8 @@ function update_trace_with_invJ!(trace::NonlinearSolveTrace{ShT, StT}, iter, u,
         return trace
     end
 
-    show_now = ShT && (iter % trace.trace_level.print_frequency == 0)
-    store_now = StT && (iter % trace.trace_level.store_frequency == 0)
+    show_now = ShT && (iter % trace.trace_level.print_frequency == 1)
+    store_now = StT && (iter % trace.trace_level.store_frequency == 1)
     if show_now || store_now
         J_ = trace.trace_level isa TraceMinimal ? J : inv(J)
         entry = __trace_entry(trace.trace_level, iter, u, fu, J_, δu, α)

Diff for: src/trustRegion.jl

@@ -340,7 +340,7 @@ function SciMLBase.__init(prob::NonlinearProblem{uType, iip}, alg_::TrustRegion,
 
     abstol, reltol, tc_cache = init_termination_cache(abstol, reltol, fu1, u,
         termination_condition)
-    trace = init_nonlinearsolve_trace(alg, u, fu1, J, du; kwargs...)
+    trace = init_nonlinearsolve_trace(alg, u, fu1, ApplyArray(__zero, J), du; kwargs...)
 
     return TrustRegionCache{iip}(f, alg, u_prev, u, fu_prev, fu1, fu2, p, uf, linsolve, J,
         jac_cache, false, maxiters, internalnorm, ReturnCode.Default, abstol, reltol, prob,

Diff for: src/utils.jl

@@ -354,3 +354,10 @@ end
 
 # Define special concatenation for certain Array combinations
 @inline _vcat(x, y) = vcat(x, y)
+
+__zero(x::AbstractArray) = zero(x)
+__zero(x) = x
+LazyArrays.applied_eltype(::typeof(__zero), x) = eltype(x)
+LazyArrays.applied_ndims(::typeof(__zero), x) = ndims(x)
+LazyArrays.applied_size(::typeof(__zero), x) = size(x)
+LazyArrays.applied_axes(::typeof(__zero), x) = axes(x)