All Errors Fixed

Author: ParamThakkar123

benchmarks/ParameterEstimation/FitzHughNagumoParameterEstimation.jmd

@@ -192,7 +192,7 @@ Vern9 solver with reltol=1e-9 and abstol=1e-9 is used and the dataset is increas
 
 
 ```julia
-obj = build_loss_objective(prob,Vern9(),L2Loss(t,data),Optimization.AutoForwardDiff(),tstops=t,reltol=1e-9,abstol=1e-9)
+obj = build_loss_objective(prob,Vern9(),L2Loss(time_points,data),Optimization.AutoForwardDiff(),tstops=time_points,reltol=1e-9,abstol=1e-9)
 optprob = OptimizationProblem(obj, glo_init, lb = first.(glo_bounds), ub = last.(glo_bounds))
 @btime res1 = solve(optprob, BBO_adaptive_de_rand_1_bin(), maxiters = 4e3)
 ```

benchmarks/ParameterEstimation/LorenzParameterEstimation.jmd

@@ -5,8 +5,6 @@ author: finmod, Chris Rackauckas, Vaibhav Dixit
 
 # Estimate the parameters of the Lorenz system from the dataset
 
-
-
 Note: If data is generated with a fixed time step method and then is tested against with the same time step, there is a biased introduced since it's no longer about hitting the true solution, rather it's just about retrieving the same values that the ODE was first generated by! Thus this version uses adaptive timestepping for all portions so that way tests are against the true solution.
 
 ```julia
@@ -219,7 +217,7 @@ Vern9 solver with reltol=1e-9 and abstol=1e-9 has been established to be accurat
 
 ```julia
 # BB with Vern9 converges very slowly. The final values are within the NarrowBounds.
-obj = build_loss_objective(prob,Vern9(),L2Loss(t,data),tstops=t,reltol=1e-9,abstol=1e-9)
+obj = build_loss_objective(prob,Vern9(),L2Loss(time_points,data),tstops=time_points,reltol=1e-9,abstol=1e-9)
 optprob = OptimizationProblem(obj, GloIniPar, lb = first.(LooserBounds), ub = last.(LooserBounds))
 @btime res1 = solve(optprob, BBO_adaptive_de_rand_1_bin(); maxiters = 4e3) # Default adaptive_de_rand_1_bin_radiuslimited 33 sec [10.2183, 24.6711, 2.28969]
 #@btime res1 = bboptimize(obj;SearchRange = LooserBounds, Method = :adaptive_de_rand_1_bin, MaxSteps = 4e3) # Method 32 sec [13.2222, 25.8589, 2.56176]