Optimize W matrix formation and fix fastconvergence judgment
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@@ Coverage Diff @@
## master #706 +/- ##
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+ Coverage 72.69% 72.75% +0.05%
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Files 93 93
Lines 29177 29220 +43
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+ Hits 21211 21259 +48
+ Misses 7966 7961 -5
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BNGNetwork: julia> sol_cvodebdf = @time solve(prob, CVODE_BDF());
29.039184 seconds (1.80 M allocations: 112.732 MiB, 0.83% gc time)
julia> sol_cvodebdf.destats
DiffEqBase.DEStats
Number of function 1 evaluations: 1309
Number of function 2 evaluations: -1
Number of W matrix evaluations: 152
Number of linear solves: -1
Number of Jacobians created: 26
Number of nonlinear solver iterations: 1305
Number of nonlinear solver convergence failures: 0
Number of rootfind condition calls: 0
Number of accepted steps: 736
Number of rejected steps: 55
julia> sol_kencarp4 = @time solve(prob, KenCarp4(autodiff=false));
24.699485 seconds (4.23 k allocations: 26.708 MiB, 0.03% gc time)
julia> sol_kencarp4.destats
DiffEqBase.DEStats
Number of function 1 evaluations: 275678
Number of function 2 evaluations: 0
Number of W matrix evaluations: 242
Number of linear solves: 4103
Number of Jacobians created: 242
Number of nonlinear solver iterations: 3909
Number of nonlinear solver convergence failures: 51
Number of rootfind condition calls: 0
Number of accepted steps: 193
Number of rejected steps: 1 |
ChrisRackauckas
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Mar 21, 2019
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ηoldis approximatelyndz/ndzprev, so the lower it is, the faster convergence the Newton iteration has.