MethodError: no method matching Array(::Type{Float64}, ::Int32, ::Int32)

[prosswienali]

num_data_sets = 1
num_trials = 10
sigma = 1.0
n_vals = round.(Int, exp10.(range(2.0,stop=4.0,length=7)))
k = 5
d = 10
mses = Dict{String, Array{Float64, 2}}()
times = Dict{String, Array{Float64, 2}}()
for algo_name in keys(algos)
mses[algo_name] =Array(Float64, length(n_vals), num_trials * num_data_sets)
times[algo_name] = Array(Float64, length(n_vals), num_trials * num_data_sets)
end

Warm-up for pre-compilation

n_warmup = 100
y, ystar, X = generate_equal_size_random_regression_data(k, n_warmup, d, sigma);
@printf("Warm-up with n = %d\n", n_warmup)
for (algo_name, algo_fun) in algos
yhat_partition = algo_fun(X, y, k)
end

for (nii, n) in enumerate(n_vals)
@printf("n = %d ", n)

tic()
for iidata = 1:num_data_sets
    @printf("*")
    
    for ii = 1:num_trials
        @printf(".")
        #@printf("  trial %d\n", ii)
        y, ystar, X = generate_equal_size_random_regression_data(k, n, d, sigma);

        for (algo_name, algo_fun) in algos
            #@printf("    algorithm %s\n", algo_name)
            start_time = time_ns()
            yhat_partition = algo_fun(X, y, k)
            end_time = time_ns()
            yhat = partition_to_vector(X, yhat_partition)
            mses[algo_name][nii, (iidata - 1) * num_trials + ii] = mse(yhat, ystar)
            times[algo_name][nii, (iidata - 1) * num_trials + ii] = 1e-9 * (end_time - start_time)
        end
    end
end
elapsed = toq()
@printf("  %f seconds\n", elapsed)

end

mses_mean = Dict{AbstractString, Array{Float64, 1}}()
mses_std = Dict{AbstractString, Array{Float64, 1}}()
times_mean = Dict{AbstractString, Array{Float64, 1}}()
times_std = Dict{AbstractString, Array{Float64, 1}}()
for algo_name in keys(mses)
mses_mean[algo_name] = vec(mean(mses[algo_name], 2))
mses_std[algo_name] = vec(std(mses[algo_name], 2))
times_mean[algo_name] = vec(mean(times[algo_name], 2))
times_std[algo_name] = vec(std(times[algo_name], 2))
end

MethodError: no method matching Array(::Type{Float64}, ::Int32, ::Int32)
Closest candidates are:
Array(!Matched::LinearAlgebra.UniformScaling, ::Integer, ::Integer) at C:\cygwin\home\Administrator\buildbot\worker\package_win32\build\usr\share\julia\stdlib\v1.1\LinearAlgebra\src\uniformscaling.jl:345

Stacktrace:
[1] top-level scope at .\In[36]:10

[ChrisRackauckas]

What does this have to do with this library?

[prosswienali]

piecewise_linear_experiments

[ChrisRackauckas]

That's not a function in ODE.jl