
function BruteForceOpt_MaxFreq(Proc_DF::ProcessedDF,FreqList,Inputs)
# inputs should be an Nx1 array of pairs where first item in pair is the name of the variable, and the second is a 1xM vector of possible values

#     VarLengths = zeros(Int8,1,length(Inputs))
#     VarIndex = zeros(Int8,size(VarLengths))
#     for i in 1:length(Inputs)
#         VarLengths[i]=length(Inputs[i][2])
#         VarIndex[i]=findfirst(x -> x==Inputs[i][1],convert(Array{String,1},Proc_DF.DF.Name) )

#     end
#     #FinalData = [[zeros(size(VarLengths))] [zeros(length(Proc_DF.InputList)-1,length(FreqList))]]

#     for ii in 1:VarLengths[1], j in 1:VarLengths[2],k in 1:VarLengths[3]

#         Proc_DF.DF.Value[VarIndex[1]]=Inputs[1][2][ii]
#         Proc_DF.DF.Value[VarIndex[2]]=Inputs[2][2][j]
#         Proc_DF.DF.Value[VarIndex[3]]=Inputs[3][2][k]
#         TrialRes = RunDF(Proc_DF,FreqList)
#         if (ii==1)&(j==1)&(k==1)
#             FinalData=TrialRes
#             println(FinalData)
#         else
#             FinalData = [FinalData;TrialRes]
#         end
#         #FinalData = vcat(FinalData,TrialRes[3,:])

#     end
#     #plot(log10.(abs.(TrialRes[3,:])))


# return FinalData
# end

# function RunDF(DF::ProcessedDF,FreqList)


#     CM = SPICE_DF2Matrix(DF)
#     CondMat(w) =
#         CM.RMat .+ CM.invLMat ./ (im .* w) .+ im .* w .* CM.CMat .+ CM.SrcMat
#     inputs = [0; 0; 0; 0; 0; 1]

#     Results = zeros(length(inputs), length(FreqList))
#     for i = 1:length(FreqList)
#         Freq = FreqList[i]
#         Results[:, i] = abs.(inv(CondMat(2 * pi * Freq)) * inputs)
#     end
#     return Results
end
