truncated_svd() is unable to handle complex matrices

truncated_svd appears to be unable to handle complex matrices (both with the method of truncation by explicit rank or tolerance). The following code which uses truncated_svd() via DMDSVD() fails.

using DataDrivenDiffEq
freq1 = 2
freq2 = 3
freq3 = 11

dt = 0.1
t = 0:dt:30

x = exp.(1im*freq1*t);
y = exp.(1im*freq2*t);
z = exp.(1im*freq3*t);

X = hcat(x,y,z)';

problem = DiscreteDataDrivenProblem(X, t);
res = solve(problem, DMDSVD());

with errors:

 [1] min(x::Float64, y::ComplexF64)
   @ Base ./operators.jl:433
 [2] truncated_svd(A::Matrix{ComplexF64}, truncation::Float64)
   @ DataDrivenDiffEq ~/.julia/packages/DataDrivenDiffEq/s9jl3/src/koopman/algorithms.jl:3

Start in koopman/algorithms.jl at truncated_svd, then reproduce the failure with the supplied complex-matrix example through DMDSVD(). Check both explicit-rank and tolerance truncation paths; done means the example completes without the shown type error for complex matrices.