[WIP] Bugfixing approaches for midpointsplitting

[Biswajitghosh98]

I uncommented the tests for midpointsplitting, so that I can use its prototype for implementing a Midpoint Magnus Method approach, as suggested by @ChrisRackauckas
1.While running the tests for "linear_method_tests.jl", the second parameter for DiffEqArrayOperator threw an error, treating 'f' as a variable, rather than a function.

Linear Methods Tests: Error During Test at /home/biswajit/.julia/packages/SafeTestsets/A83XK/src/SafeTestsets.jl:25
  Got exception outside of a @test
  LoadError: MethodError: no method matching DiffEqBase.DiffEqArrayOperator(::Array{Int64,2}, ::Main.##422.var"#1#2")
  Closest candidates are:
    DiffEqBase.DiffEqArrayOperator(::AType; update_func) where AType at /home/biswajit/.julia/packages/DiffEqBase/y3Q1t/src/operators/basic_operators.jl:90
  Stacktrace: 

2. So, to fix that, I mapped f to the matrix. Then I got the error prompting that argument names of the function p are not unique. I saw that not typecasting p can bypass this error. So, just to see what happens next, I moved forward with it

Linear Methods Tests: Error During Test at /home/biswajit/.julia/packages/SafeTestsets/A83XK/src/SafeTestsets.jl:25
  Got exception outside of a @test
  LoadError: syntax: function argument names not unique
  Stacktrace:

3. Now, I am prompted the same error which I encountered in Added low storage SSPRK53_H #1055 , because I had used @. for broadcasting in perform_step, whereas using @.. solved the issue.
   I tried working on similar lines here, but that didn't quite work out.

Linear Methods Tests: Error During Test at /home/biswajit/.julia/packages/SafeTestsets/A83XK/src/SafeTestsets.jl:25
  Got exception outside of a @test
  LoadError: MethodError: no method matching alg_cache(::OrdinaryDiffEq.MidpointSplitting, ::Array{Float64,1}, ::Array{Float64,1}, ::Type{Float64}, ::Type{Float64}, ::Type{Float64}, ::Array{Float64,1}, ::Array{Float64,1}, ::DiffEqBase.ODEFunction{true,DiffEqBase.AffineDiffEqOperator{Float64,Tuple{Array{Float64,2},Array{Float64,2}},Tuple{},Array{Float64,1}},LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}, ::Float64, ::Float64, ::Float64, ::DiffEqBase.NullParameters, ::Bool, ::Val{true})
  Closest candidates are:
    alg_cache(!Matched::OrdinaryDiffEq.SplitEuler, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Val{true}) at /home/biswajit/Desktop/GSOC/OrdinaryDiffEq.jl/src/caches/low_order_rk_caches.jl:18
    alg_cache(!Matched::OrdinaryDiffEq.Euler, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Any, ::Val{true}) at /home/biswajit/Desktop/GSOC/OrdinaryDiffEq.jl/src/caches/low_order_rk_caches.jl:26

Any pointers on how to move forward with it will be very helpful !
Thank You !

[ChrisRackauckas]

This is not the same: this is not a time-dependent operator!

[codecov]

Codecov Report

Merging #1061 into master will increase coverage by 0.07%.
The diff coverage is 83.33%.

@@            Coverage Diff             @@
##           master    #1061      +/-   ##
==========================================
+ Coverage   76.99%   77.07%   +0.07%     
==========================================
  Files          95       95              
  Lines       31323    31318       -5     
==========================================
+ Hits        24118    24139      +21     
+ Misses       7205     7179      -26

Impacted Files	Coverage Δ
src/OrdinaryDiffEq.jl	100% <ø> (ø)	⬆️
src/alg_utils.jl	27.72% <0%> (ø)	⬆️
src/perform_step/linear_perform_step.jl	64.51% <100%> (+30.69%)	⬆️
src/algorithms.jl	84.28% <100%> (+0.05%)	⬆️
src/caches/linear_caches.jl	81.81% <50%> (+15.15%)	⬆️
src/misc_utils.jl	75% <0%> (-1.2%)	⬇️

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[coveralls]

Coverage decreased (-20.5%) to 66.516% when pulling 5b2fcfb on Biswajitghosh98:Debug_Midpointsplitting into 309f0be on JuliaDiffEq:master.