pybdt package

A fast, Pythonic BDT implementation.

Submodules

• pybdt.convertdsmodule module
  • ConvertDS
    • ConvertDS.Configure()
    • ConvertDS.Finish()
    • ConvertDS.Physics()
• pybdt.histlite module
  • Binner
    • Binner.bins
    • Binner.hist()
    • Binner.kwargs
    • Binner.range
  • Binner2D
    • Binner2D.bins
    • Binner2D.hist()
    • Binner2D.kwargs
    • Binner2D.range
  • Hist
    • Hist.cumulative_left
    • Hist.cumulative_right
    • Hist.efficiency()
    • Hist.integral
    • Hist.integral_normed
    • Hist.rebin()
    • Hist.sample()
    • Hist.sum
    • Hist.sum_normed
  • Hist2D
    • Hist2D.colcumulative_left
    • Hist2D.colcumulative_right
    • Hist2D.colintegrals
    • Hist2D.colintegrals_normed
    • Hist2D.colsums
    • Hist2D.colsums_normed
    • Hist2D.cumulative_left
    • Hist2D.cumulative_right
    • Hist2D.efficiency()
    • Hist2D.integral
    • Hist2D.integral_normed
    • Hist2D.rowcumulative_left
    • Hist2D.rowcumulative_right
    • Hist2D.rowintegrals
    • Hist2D.rowintegrals_normed
    • Hist2D.rowsums
    • Hist2D.rowsums_normed
    • Hist2D.sum
    • Hist2D.sum_normed
    • Hist2D.xhist
    • Hist2D.xhists
    • Hist2D.yhist
    • Hist2D.yhists
  • Line
    • Line.at()
    • Line.bin_centers
    • Line.bins
    • Line.bins_match()
    • Line.errors
    • Line.values
  • Plotter
    • Plotter.add()
    • Plotter.axes
    • Plotter.expx
    • Plotter.finish()
    • Plotter.legend()
    • Plotter.line_axes
    • Plotter.line_styles
    • Plotter.lines
    • Plotter.log
    • Plotter.twin_axes
    • Plotter.twin_log
  • Style
    • Style.copy()
    • Style.errorbars
    • Style.errorcaps
    • Style.kwargs
    • Style.line
    • Style.markers
    • Style.update()
  • Surface2D
    • Surface2D.bins_match()
    • Surface2D.errors
    • Surface2D.values
    • Surface2D.xbins
    • Surface2D.ybins
  • function_to_surface()
  • plot_surface()
  • plot_surface_lines()
• pybdt.ml module
  • BDTLearner
    • BDTLearner.add_after_pruner()
    • BDTLearner.add_before_pruner()
    • BDTLearner.after_pruners
    • BDTLearner.before_pruners
    • BDTLearner.beta
    • BDTLearner.clear_after_pruners()
    • BDTLearner.clear_before_pruners()
    • BDTLearner.dtlearner
    • BDTLearner.frac_random_events
    • BDTLearner.num_trees
    • BDTLearner.quiet
    • BDTLearner.set_defaults()
    • BDTLearner.use_purity
  • BDTModel
    • BDTModel.alphas
    • BDTModel.dtmodels
    • BDTModel.event_variable_importance()
    • BDTModel.get_subset_bdtmodel()
    • BDTModel.get_subset_bdtmodel_list()
    • BDTModel.get_trimmed_bdtmodel()
    • BDTModel.n_dtmodels
    • BDTModel.variable_importance()
  • CostComplexityPruner
    • CostComplexityPruner.gain()
    • CostComplexityPruner.rho()
    • CostComplexityPruner.strength
  • DTLearner
    • DTLearner.linear_cuts
    • DTLearner.max_depth
    • DTLearner.min_split
    • DTLearner.num_cuts
    • DTLearner.num_random_variables
    • DTLearner.separation_type
    • DTLearner.set_defaults()
  • DTModel
    • DTModel.event_variable_importance()
    • DTModel.root
    • DTModel.variable_importance()
  • DTNode
    • DTNode.feature_id
    • DTNode.feature_name
    • DTNode.feature_val
    • DTNode.is_leaf
    • DTNode.left
    • DTNode.max_depth
    • DTNode.n_bg
    • DTNode.n_leaves
    • DTNode.n_sig
    • DTNode.n_total
    • DTNode.prune()
    • DTNode.purity
    • DTNode.right
    • DTNode.sep_gain
    • DTNode.sep_index
    • DTNode.tree_size
    • DTNode.w_bg
    • DTNode.w_sig
    • DTNode.w_total
  • DataSet
    • DataSet.eval()
    • DataSet.get_subset()
    • DataSet.livetime
    • DataSet.n_events
    • DataSet.n_features
    • DataSet.names
    • DataSet.to_dict()
  • ErrorPruner
    • ErrorPruner.node_error()
    • ErrorPruner.strength
    • ErrorPruner.subtree_error()
  • Learner
    • Learner.train()
    • Learner.train_given_weights()
  • Model
    • Model.feature_names
    • Model.score()
    • Model.score_DataSet()
    • Model.score_dict()
    • Model.score_event()
  • MultiModel1D
    • MultiModel1D.get_cut()
    • MultiModel1D.score_DataSet()
    • MultiModel1D.score_dict()
    • MultiModel1D.score_event()
  • MultiModel1DCut
    • MultiModel1DCut.decision()
  • Pruner
    • Pruner.prune()
  • SameLeafPruner
  • VineLearner
    • VineLearner.learner
    • VineLearner.quiet
    • VineLearner.vine_feature
    • VineLearner.vine_feature_max
    • VineLearner.vine_feature_min
    • VineLearner.vine_feature_step
    • VineLearner.vine_feature_width
  • VineModel
  • get_epsilon()
  • set_epsilon()
  • unwrapped()
  • wrapped()
• pybdt.util module
  • load()
  • load_sklearn()
  • mkdir()
  • save()
  • sklearn_to_BDTModel()
• pybdt.validate module
  • Validator
    • Validator.Proxy
    • Validator.add_data()
    • Validator.add_weighting()
    • Validator.bdt
    • Validator.clear_weightings()
    • Validator.create_correlation_matrix_plot()
    • Validator.create_correlation_ratio_matrix_plot()
    • Validator.create_overtrain_check_plot()
    • Validator.create_plot()
    • Validator.create_variable_pair_plot()
    • Validator.data
    • Validator.eval()
    • Validator.full_label
    • Validator.get_Hist()
    • Validator.get_clone()
    • Validator.get_correlation()
    • Validator.get_key_wkey()
    • Validator.get_kolmogorov_smirnov_probability()
    • Validator.get_range()
    • Validator.get_values_weights()
    • Validator.label
    • Validator.load_all_data()
    • Validator.plot_variable()
    • Validator.pscores
    • Validator.scores
    • Validator.setup_total_mc()
    • Validator.style
    • Validator.weight_label
    • Validator.weights
• pybdt.viz module
  • dtmodel_to_graphviz()
  • dtmodel_to_text()
  • float_to_scientific_notation()
  • variable_importance_to_text()