Welcome to branchpro’s documentation!

The branchpro source code is hosted on GitHub.

• Visualisation Apps
  • IncidenceNumberPlot
    • IncidenceNumberPlot
      • IncidenceNumberPlot.add_data()
      • IncidenceNumberPlot.add_simulation()
      • IncidenceNumberPlot.show_figure()
      • IncidenceNumberPlot.update_labels()
  • ReproductionNumberPlot
    • ReproductionNumberPlot
      • ReproductionNumberPlot.add_ground_truth_rt()
      • ReproductionNumberPlot.add_interval_rt()
      • ReproductionNumberPlot.show_figure()
      • ReproductionNumberPlot.update_labels()
  • Sliders
    • _SliderComponent
      • _SliderComponent.add_slider()
      • _SliderComponent.get_sliders_div()
      • _SliderComponent.slider_ids()
  • Apps
    • BranchProDashApp
      • BranchProDashApp.add_collapsed_text()
      • BranchProDashApp.add_text()
      • BranchProDashApp.parse_contents()
      • BranchProDashApp.refresh_user_data_json()
  • Simulation Apps
    • IncidenceNumberSimulationApp
      • IncidenceNumberSimulationApp.update_figure()
      • IncidenceNumberSimulationApp.update_simulation()
      • IncidenceNumberSimulationApp.update_sliders()
  • Inference Apps
    • BranchProInferenceApp
      • BranchProInferenceApp.update_data_figure()
      • BranchProInferenceApp.update_inference_figure()
      • BranchProInferenceApp.update_posterior()
      • BranchProInferenceApp.update_sliders()
• Core classes and methods
  • Forward model
    • ForwardModel
      • ForwardModel.simulate()
• Data Library
  • Dataset Library
    • DatasetLibrary
      • DatasetLibrary.french_flu()
• Figures
  • plot_forward_simulations()
  • plot_r_inference()
• Models
  • Poisson Noise Branching Process Models
  • Branch Process model
    • BranchProModel
      • BranchProModel.get_r_profile()
      • BranchProModel.get_serial_intervals()
      • BranchProModel.set_r_profile()
      • BranchProModel.set_serial_intervals()
      • BranchProModel.simulate()
  • Local and Imported Branch Process model
    • LocImpBranchProModel
      • LocImpBranchProModel.set_epsilon()
      • LocImpBranchProModel.set_imported_cases()
      • LocImpBranchProModel.simulate()
  • Multiple categories Poisson Branch Process model
    • MultiCatPoissonBranchProModel
      • MultiCatPoissonBranchProModel.get_contact_matrix()
      • MultiCatPoissonBranchProModel.get_serial_intervals()
      • MultiCatPoissonBranchProModel.get_transmissibility()
      • MultiCatPoissonBranchProModel.set_contact_matrix()
      • MultiCatPoissonBranchProModel.set_serial_intervals()
      • MultiCatPoissonBranchProModel.set_transmissibility()
      • MultiCatPoissonBranchProModel.simulate()
  • Local and Imported Multiple categories Poisson Branch Process model
    • LocImpMultiCatPoissonBranchProModel
      • LocImpMultiCatPoissonBranchProModel.set_epsilon()
      • LocImpMultiCatPoissonBranchProModel.set_imported_cases()
      • LocImpMultiCatPoissonBranchProModel.simulate()
  • Negative Binomial Noise Branching Process Models
  • Negative binomial Branch Process model
    • NegBinBranchProModel
      • NegBinBranchProModel.get_overdispersion()
      • NegBinBranchProModel.set_overdispersion()
      • NegBinBranchProModel.simulate()
  • Local and Imported negative binomial Branch Process model
    • LocImpNegBinBranchProModel
      • LocImpNegBinBranchProModel.get_overdispersion()
      • LocImpNegBinBranchProModel.set_overdispersion()
      • LocImpNegBinBranchProModel.simulate()
  • Stochastic Negative binomial Branch Process model
    • StochasticNegBinBranchProModel
      • StochasticNegBinBranchProModel.simulate()
  • Local and Imported Stochastic negative binomial Branch Process model
    • StochasticLocImpNegBinBranchProModel
      • StochasticLocImpNegBinBranchProModel.simulate()
  • Poisson-Binomial Noise Branching Process Models
  • Poisson-Binomial Branch Process model
    • PoiBinBranchProModel
      • PoiBinBranchProModel.get_mean_contact()
      • PoiBinBranchProModel.get_next_gen()
      • PoiBinBranchProModel.set_mean_contact()
      • PoiBinBranchProModel.set_next_gen()
      • PoiBinBranchProModel.simulate()
• Posterior Distribution
  • Branch Process Posterior Distribution
    • BranchProPosterior
      • BranchProPosterior.get_intervals()
      • BranchProPosterior.get_serial_intervals()
      • BranchProPosterior.last_time_r_threshold()
      • BranchProPosterior.proportion_time_r_more_than_1()
      • BranchProPosterior.run_inference()
      • BranchProPosterior.set_serial_intervals()
  • Branch Process Posterior Distribution with Multiple Serial Intervals
    • BranchProPosteriorMultSI
      • BranchProPosteriorMultSI.get_intervals()
      • BranchProPosteriorMultSI.get_serial_intervals()
      • BranchProPosteriorMultSI.run_inference()
      • BranchProPosteriorMultSI.set_serial_intervals()
  • Local and Imported Branch Process Posterior Distribution
    • LocImpBranchProPosterior
      • LocImpBranchProPosterior.run_inference()
      • LocImpBranchProPosterior.set_epsilon()
  • Local and Imported Branch Process Posterior Distribution with Multiple Serial Intervals
    • LocImpBranchProPosteriorMultSI
      • LocImpBranchProPosteriorMultSI.run_inference()
  • Gamma distribution
    • GammaDist
      • GammaDist.big_pdf()
  • New Posterior Classes using MCMC Sampling algorithms
  • Branch Process with Poisson Noise
  • Log-likelihood Class
    • PoissonBranchProLogLik
      • PoissonBranchProLogLik.evaluateS1()
      • PoissonBranchProLogLik.get_serial_intervals()
      • PoissonBranchProLogLik.n_parameters()
      • PoissonBranchProLogLik.set_epsilon()
      • PoissonBranchProLogLik.set_serial_intervals()
  • Log-posterior Class
    • PoissonBranchProLogPosterior
      • PoissonBranchProLogPosterior.return_loglikelihood()
      • PoissonBranchProLogPosterior.return_logposterior()
      • PoissonBranchProLogPosterior.return_logprior()
      • PoissonBranchProLogPosterior.run_inference()
      • PoissonBranchProLogPosterior.run_optimisation()
  • Multiple Categories Branch Process with Poisson Noise
  • Log-likelihood Class
    • MultiCatPoissonBranchProLogLik
      • MultiCatPoissonBranchProLogLik.evaluateS1()
      • MultiCatPoissonBranchProLogLik.get_serial_intervals()
      • MultiCatPoissonBranchProLogLik.n_parameters()
      • MultiCatPoissonBranchProLogLik.set_serial_intervals()
  • Log-posterior Class
    • MultiCatPoissonBranchProLogPosterior
      • MultiCatPoissonBranchProLogPosterior.return_loglikelihood()
      • MultiCatPoissonBranchProLogPosterior.return_logposterior()
      • MultiCatPoissonBranchProLogPosterior.return_logprior()
      • MultiCatPoissonBranchProLogPosterior.run_inference()
      • MultiCatPoissonBranchProLogPosterior.run_optimisation()
  • Branch Process with Negative Binomial Noise
  • Log-likelihood Class
    • NegBinBranchProLogLik
      • NegBinBranchProLogLik.get_overdispersion()
      • NegBinBranchProLogLik.n_parameters()
      • NegBinBranchProLogLik.set_overdispersion()
  • Log-posterior Class
    • NegBinBranchProLogPosterior
      • NegBinBranchProLogPosterior.run_inference()
      • NegBinBranchProLogPosterior.run_optimisation()
• Simulation
  • SimulationController
    • SimulationController
      • SimulationController.run()
      • SimulationController.switch_resolution()

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