Full API

• pydruglogics.execution.Executor module
  • execute()
  • predict()
  • timed_execution()
  • train()
• pydruglogics.input.ModelOutputs module
  • ModelOutputs
    • ModelOutputs.get_model_output()
    • ModelOutputs.max_output
    • ModelOutputs.min_output
    • ModelOutputs.model_outputs
    • ModelOutputs.node_names
    • ModelOutputs.print()
    • ModelOutputs.size()
• pydruglogics.input.Perturbations module
  • Perturbation
    • Perturbation.drug_effects
    • Perturbation.drug_names
    • Perturbation.drug_targets
    • Perturbation.drugs
    • Perturbation.perturbations
    • Perturbation.print()
• pydruglogics.input.TrainingData module
  • TrainingData
    • TrainingData.observations
    • TrainingData.print()
    • TrainingData.response
    • TrainingData.responses
    • TrainingData.size()
    • TrainingData.weight_sum
    • TrainingData.weights
• pydruglogics.model.BooleanModel module
  • BooleanModel
    • BooleanModel.add_perturbations()
    • BooleanModel.attractor_tool
    • BooleanModel.attractor_type
    • BooleanModel.attractors
    • BooleanModel.binary_boolean_equations
    • BooleanModel.boolean_equations
    • BooleanModel.calculate_attractors()
    • BooleanModel.calculate_global_output()
    • BooleanModel.clone()
    • BooleanModel.from_binary()
    • BooleanModel.get_stable_states()
    • BooleanModel.global_output
    • BooleanModel.has_attractors()
    • BooleanModel.has_global_output()
    • BooleanModel.has_stable_states()
    • BooleanModel.model_name
    • BooleanModel.mutation_type
    • BooleanModel.print()
    • BooleanModel.reset_attractors()
    • BooleanModel.to_binary()
• pydruglogics.model.BooleanModelOptimizer module
  • BooleanModelOptimizer
    • BooleanModelOptimizer.run()
    • BooleanModelOptimizer.save_to_file_models()
• pydruglogics.model.InteractionModel module
  • InteractionModel
    • InteractionModel.all_targets
    • InteractionModel.get_activating_regulators()
    • InteractionModel.get_inhibitory_regulators()
    • InteractionModel.get_interaction()
    • InteractionModel.get_target()
    • InteractionModel.interactions
    • InteractionModel.model_name
    • InteractionModel.print()
    • InteractionModel.size()
• pydruglogics.model.ModelPredictions module
  • ModelPredictions
    • ModelPredictions.get_prediction_matrix()
    • ModelPredictions.predicted_synergy_scores
    • ModelPredictions.run_simulations()
    • ModelPredictions.save_to_file_predictions()
• pydruglogics.model.Statistics module
  • compare_two_simulations()
  • sampling_with_ci()
• pydruglogics.utils.Logger module
  • Logger
    • Logger.set_logger()
• pydruglogics.utils.PlotUtil module
  • PlotUtil
    • PlotUtil.plot_pr_curve_with_ci()
    • PlotUtil.plot_roc_and_pr_curve()
• pydruglogics.utils.BNetworkUtil module
  • BNetworkUtil
    • BNetworkUtil.bnet_string_to_dict()
    • BNetworkUtil.create_equation_from_bnet()
    • BNetworkUtil.create_interaction()
    • BNetworkUtil.get_file_extension()
    • BNetworkUtil.is_numeric_string()
    • BNetworkUtil.parse_interaction()
    • BNetworkUtil.read_lines_from_file()
    • BNetworkUtil.remove_extension()
    • BNetworkUtil.to_bnet_format()