# Plot Functions

JuliaSimModelOptimizer.plot_experiment_prob_xFunction
plot(experiment::AbstractExperiment, prob::InverseProblem, x=get_states(prob))

Plots the trajectories for each state of experiment, when point x is used to provide parameter and/or initial condition values that are optimized in InverseProblemprob.

Vector x defaults to the default values of each parameter and initial condition to be optimized, as they were specified during model definition.

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JuliaSimModelOptimizer.plot_vp_trialFunction
plot(vp::AbstractQSPResult, trial::AbstractExperiment; kwargs...)

Plots the trajectories for each state of trial for each set of the optimized parameters and/or initial conditions in virtual population vp.

Keyword Arguments

• summary: Bool, defaults to true. Determines whether summary statistics of the trajectories are plotted. If true, a mean trajectory is shown with a band around it representing a lower and upper quantile of the state distribution at each saved timepoint.
• quantile: Defaults to [0.05, 0.95]. A vector of two elements, corresponding to the lower and upper quantile of the distribution of each state at each saved timepoint, to be plotted if summary == true.
• states: a Vector of model states, whose trajectories are plotted. Defaults to all saved states in trial.
• show_data: Bool, defaults to false. Determines whether data of trial is also plotted. If true data is plotted as a scatter plot on top of the state trajectories.
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JuliaSimModelOptimizer.plot_vp_probFunction
plot(vp::AbstractQSPResult, prob::InverseProblem; kwargs...)

Plots the state trajectories of trials that are part of InverseProblemprob, using each set of the optimized parameters and/or initial conditions in virtual population vp. Each trial is shown in a separate subplot.

Keyword Arguments

• trial_names: Vector containing the names of trials to be plotted. These trials need to be part of prob.
• layout: Tuple{Int, Int}. Determines how trials are shown on the plotting window. Defaults to one trial per row. The Tuple should look like (number_of_rows, number_of_columns).
• summary: Bool, defaults to true. Determines whether summary statistics of the trajectories are plotted. If true, a mean trajectory is shown with a band around it representing a lower and upper quantile of the state distribution at each saved timepoint.
• quantile: Defaults to [0.05, 0.95]. A vector of two elements, corresponding to the lower and upper quantile of the distribution of each state at each saved timepoint, to be plotted if summary == true.
• show_data: Bool, defaults to false. Determines whether data of each plotted trial is also shown. If true data is plotted as a scatter plot on top of the state trajectories.
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JuliaSimModelOptimizer.confidenceplotFunction

julia confidenceplot(trial::AbstractExperiment, vp::AbstractQSPResult)

Plots the trajectories for each state of trial for a given confidence value of the quantile

Keyword Arguments

• confidence: Defaults to 0.8. A scalar value that shows the level of confidence that the obtained plot is a good fit in comparision to the actual experimental data, out of the generated virtual population members.
• show_data: Bool, defaults to true, in order to show the dergee of fit with the actual data. Determines whether data of trial is also plotted. If true data is plotted as a scatter plot on top of the state trajectories.
• states: a Vector of model states, whose trajectories are plotted. Defaults to all saved states in trial.
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JuliaSimModelOptimizer.confidence_plot_shooting_segmentsFunction

julia confidence_plot_shooting_segments(experiment::AbstractExperiment, ps::AbstractParametricUncertaintyEnsemble)

Plots the trajectories for each state of trial for a given confidence value of the quantile

Keyword Arguments

• confidence: Defaults to 0.8. A scalar value that shows the level of confidence that the obtained plot is a good fit in comparision to the actual experimental data, out of the generated virtual population members.
• show_data: Bool, defaults to true, in order to show the dergee of fit with the actual data. Determines whether data of trial is also plotted. If true data is plotted as a scatter plot on top of the state trajectories.
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