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invalid doctest block in docs/src/tutorial.md:51-117 Requires `julia> ` or `# output` ```jldoctest; output=false using Plots using MLFlowClient using Random # Parameters αs = [0.0, 0.9, 0.98] n = 100 "Method that generates price paths of length `n` based on `α`" function getpricepath(α, n) x = zeros(n + 1) x[1] = 0.0 for t in 1:n x[t+1] = α * x[t] + rand() end x end p = plot() # Create MLFlow instance mlf = MLFlow("http://localhost:5000/api") # Initiate new experiment experiment_id = createexperiment(mlf, "price-paths") # Create a run in the new experiment exprun = createrun(mlf, experiment_id) # Log parameters and their values for (idx, α) in enumerate(αs) logparam(mlf, exprun, "alpha$(idx)", string(α)) # MLFlow only supports string parameter values end # Obtain pricepaths pricepaths = [getpricepath(α, n) for α in αs] # Log pricepaths in MLFlow for (idx, pricepath) in enumerate(pricepaths) plot!(p, pricepath, title="Random price paths", label="alpha = $(αs[idx])", xlabel="Timestep", ylabel="Price" ) # Log each point in the price path as a separate metric with step parameter for (step, value) in enumerate(pricepath) logmetric(mlf, exprun, "pricepath$(idx)", Float64(value); step=step-1) end end # Save the price path plot as an image plotfilename = "pricepaths-plot.png" png(plotfilename) # TODO: Upload the plot as an artifact when logartifact function is implemented # See: https://github.com/JuliaAI/MLFlowClient.jl/issues/61 # logartifact(mlf, exprun, plotfilename) # Keep the plot file since artifact upload is not yet available # rm(plotfilename) # complete the experiment updaterun(mlf, exprun; status=RunStatus.FINISHED) ```