SYMBOL INDEX (450 symbols across 30 files)

FILE: dtreeviz/ai_explanation.py
  function _convert_to_json_serializable (line 60) | def _convert_to_json_serializable(obj):
  function get_completion (line 91) | def get_completion(prompt, model=None):
  function _get_library (line 105) | def _get_library(tree: ShadowDecTree):
  function _get_tree_structure_knowledge (line 111) | def _get_tree_structure_knowledge(tree: ShadowDecTree):
  function _get_training_set_knowledge (line 128) | def _get_training_set_knowledge(tree: ShadowDecTree):
  function _get_leaf_nodes_knowledge (line 146) | def _get_leaf_nodes_knowledge(tree: ShadowDecTree):
  function _get_internal_nodes_knowledge (line 185) | def _get_internal_nodes_knowledge(tree: ShadowDecTree):
  function _get_session_history (line 218) | def _get_session_history(session_id: str, max_messages: int = None) -> I...
  function setup_chat (line 254) | def setup_chat(tree: ShadowDecTree, session_id: str = "default", model: ...
  function build_node_stats_prompt (line 348) | def build_node_stats_prompt(shadow_tree: ShadowDecTree, node_id: int) ->...

FILE: dtreeviz/classifiers.py
  function decision_boundaries (line 16) | def decision_boundaries(model, X: np.ndarray, y: np.ndarray,
  function decision_boundaries_bivar (line 134) | def decision_boundaries_bivar(model, X:np.ndarray, y:np.ndarray,
  function _compute_tiling (line 237) | def _compute_tiling(model, X:np.ndarray, y:np.ndarray, binary_threshold,
  function _get_grid_colors (line 305) | def _get_grid_colors(grid_proba, grid_pred, class_values, colors):
  function _draw_tiles (line 335) | def _draw_tiles(ax, grid_points, facecolors, tile_alpha, h, w):
  function _draw_boundary_edges (line 346) | def _draw_boundary_edges(ax, grid_points, grid_pred_as_matrix, boundary_...
  function decision_boundaries_univar (line 374) | def decision_boundaries_univar(model, x: np.ndarray, y: np.ndarray,
  function _predict_proba (line 501) | def _predict_proba(model, X):

FILE: dtreeviz/colors.py
  function get_hex_colors (line 41) | def get_hex_colors(n_classes, cmap_name="RdYlBu"):
  function adjust_colors (line 111) | def adjust_colors(colors, n_classes=None, cmp="RdYlBu"):

FILE: dtreeviz/compatibility.py
  function _warning_on_one_line (line 15) | def _warning_on_one_line(message, category, filename, lineno, file=None,...
  function rtreeviz_univar (line 21) | def rtreeviz_univar(tree_model,
  function rtreeviz_bivar_heatmap (line 48) | def rtreeviz_bivar_heatmap(tree_model,
  function rtreeviz_bivar_3D (line 76) | def rtreeviz_bivar_3D(tree_model,
  function ctreeviz_univar (line 106) | def ctreeviz_univar(tree_model,
  function ctreeviz_bivar (line 129) | def ctreeviz_bivar(tree_model,
  function dtreeviz (line 160) | def dtreeviz(tree_model,
  function viz_leaf_samples (line 261) | def viz_leaf_samples(tree_model,
  function viz_leaf_criterion (line 354) | def viz_leaf_criterion(tree_model,
  function ctreeviz_leaf_samples (line 421) | def ctreeviz_leaf_samples(tree_model,
  function viz_leaf_target (line 491) | def viz_leaf_target(tree_model,
  function describe_node_sample (line 559) | def describe_node_sample(tree_model,
  function explain_prediction_path (line 604) | def explain_prediction_path(tree_model,

FILE: dtreeviz/interpretation.py
  function explain_prediction_plain_english (line 16) | def explain_prediction_plain_english(shadow_tree: ShadowDecTree,
  function explain_prediction_sklearn_default (line 94) | def explain_prediction_sklearn_default(shadow_tree: ShadowDecTree,

FILE: dtreeviz/models/lightgbm_decision_tree.py
  class ShadowLightGBMTree (line 12) | class ShadowLightGBMTree(ShadowDecTree):
    method __init__ (line 14) | def __init__(self,
    method _get_nodes_info (line 33) | def _get_nodes_info(self):
    method is_fit (line 74) | def is_fit(self) -> bool:
    method is_classifier (line 77) | def is_classifier(self) -> bool:
    method is_categorical_split (line 86) | def is_categorical_split(self, id) -> bool:
    method get_class_weights (line 93) | def get_class_weights(self):
    method get_thresholds (line 96) | def get_thresholds(self) -> np.ndarray:
    method get_features (line 111) | def get_features(self) -> np.ndarray:
    method criterion (line 122) | def criterion(self) -> str:
    method get_class_weight (line 125) | def get_class_weight(self):
    method nclasses (line 128) | def nclasses(self) -> int:
    method classes (line 134) | def classes(self) -> np.ndarray:
    method get_node_samples (line 138) | def get_node_samples(self):
    method get_split_samples (line 151) | def get_split_samples(self, id):
    method get_root_edge_labels (line 165) | def get_root_edge_labels(self):
    method get_node_nsamples (line 168) | def get_node_nsamples(self, id):
    method get_children_left (line 174) | def get_children_left(self) -> np.ndarray:
    method get_children_right (line 177) | def get_children_right(self) -> np.ndarray:
    method get_node_split (line 180) | def get_node_split(self, id) -> (int, float):
    method get_node_feature (line 183) | def get_node_feature(self, id) -> int:
    method get_node_nsamples_by_class (line 186) | def get_node_nsamples_by_class(self, id):
    method get_prediction (line 192) | def get_prediction(self, id):
    method nnodes (line 201) | def nnodes(self) -> int:
    method get_node_criterion (line 204) | def get_node_criterion(self, id):
    method get_feature_path_importance (line 207) | def get_feature_path_importance(self, node_list):
    method get_max_depth (line 210) | def get_max_depth(self) -> int:
    method get_score (line 215) | def get_score(self) -> float:
    method get_min_samples_leaf (line 218) | def get_min_samples_leaf(self) -> (int, float):
    method shouldGoLeftAtSplit (line 222) | def shouldGoLeftAtSplit(self, id, x):

FILE: dtreeviz/models/shadow_decision_tree.py
  class ShadowDecTree (line 12) | class ShadowDecTree(ABC):
    method __init__ (line 28) | def __init__(self,
    method is_fit (line 66) | def is_fit(self) -> bool:
    method is_classifier (line 71) | def is_classifier(self) -> bool:
    method get_class_weights (line 76) | def get_class_weights(self):
    method get_thresholds (line 81) | def get_thresholds(self) -> np.ndarray:
    method get_features (line 89) | def get_features(self) -> np.ndarray:
    method criterion (line 97) | def criterion(self) -> str:
    method get_class_weight (line 105) | def get_class_weight(self):
    method nclasses (line 113) | def nclasses(self) -> int:
    method classes (line 121) | def classes(self) -> np.ndarray:
    method get_node_samples (line 129) | def get_node_samples(self):
    method get_split_samples (line 136) | def get_split_samples(self, id):
    method get_node_nsamples (line 141) | def get_node_nsamples(self, id):
    method get_children_left (line 146) | def get_children_left(self) -> np.ndarray:
    method get_children_right (line 154) | def get_children_right(self) -> np.ndarray:
    method get_node_split (line 162) | def get_node_split(self, id) -> (int, float):
    method get_node_feature (line 173) | def get_node_feature(self, id) -> int:
    method get_node_nsamples_by_class (line 184) | def get_node_nsamples_by_class(self, id):
    method get_prediction (line 195) | def get_prediction(self, id):
    method nnodes (line 206) | def nnodes(self) -> int:
    method get_node_criterion (line 211) | def get_node_criterion(self, id):
    method get_feature_path_importance (line 222) | def get_feature_path_importance(self, node_list):
    method get_max_depth (line 235) | def get_max_depth(self) -> int:
    method get_score (line 240) | def get_score(self) -> float:
    method get_min_samples_leaf (line 248) | def get_min_samples_leaf(self) -> (int, float):
    method shouldGoLeftAtSplit (line 253) | def shouldGoLeftAtSplit(self, id, x):
    method get_root_edge_labels (line 257) | def get_root_edge_labels(self):
    method is_categorical_split (line 260) | def is_categorical_split(self, id) -> bool:
    method get_split_node_heights (line 268) | def get_split_node_heights(self, X_train, y_train, nbins) -> Mapping[i...
    method predict (line 297) | def predict(self, x: np.ndarray) -> Number:
    method predict_path (line 319) | def predict_path(self, x: np.ndarray) -> List:
    method get_leaf_sample_counts (line 343) | def get_leaf_sample_counts(self, min_samples=0, max_samples=None):
    method get_leaf_criterion (line 365) | def get_leaf_criterion(self):
    method get_leaf_sample_counts_by_class (line 375) | def get_leaf_sample_counts_by_class(self):
    method _get_tree_nodes (line 385) | def _get_tree_nodes(self):
    method _get_x_data (line 409) | def _get_x_data(X_train):
    method _get_y_data (line 415) | def _get_y_data(y_train):
    method get_shadow_tree (line 421) | def get_shadow_tree(tree_model, X_train, y_train, feature_names, targe...
  class ShadowDecTreeNode (line 474) | class ShadowDecTreeNode():
    method __init__ (line 481) | def __init__(self, shadow_tree: ShadowDecTree, id: int, left=None, rig...
    method split (line 488) | def split(self) -> (int, float):
    method feature (line 492) | def feature(self) -> int:
    method feature_name (line 496) | def feature_name(self) -> (str, None):
    method samples (line 502) | def samples(self) -> List[int]:
    method nsamples (line 506) | def nsamples(self) -> int:
    method n_sample_classes (line 514) | def n_sample_classes(self):
    method criterion (line 533) | def criterion(self):
    method split_samples (line 536) | def split_samples(self) -> Tuple[np.ndarray, np.ndarray]:
    method isleaf (line 540) | def isleaf(self) -> bool:
    method isclassifier (line 543) | def isclassifier(self) -> bool:
    method is_categorical_split (line 546) | def is_categorical_split(self) -> bool:
    method prediction (line 549) | def prediction(self) -> (Number, None):
    method prediction_name (line 558) | def prediction_name(self) -> (str, None):
    method class_counts (line 573) | def class_counts(self) -> (List[int], None):
    method __str__ (line 586) | def __str__(self):
  class VisualisationNotYetSupportedError (line 596) | class VisualisationNotYetSupportedError(Exception):
    method __init__ (line 597) | def __init__(self, method_name, model_name):

FILE: dtreeviz/models/sklearn_decision_trees.py
  class ShadowSKDTree (line 11) | class ShadowSKDTree(ShadowDecTree):
    method __init__ (line 12) | def __init__(self, tree_model,
    method is_fit (line 22) | def is_fit(self):
    method is_classifier (line 25) | def is_classifier(self):
    method get_class_weights (line 28) | def get_class_weights(self):
    method get_thresholds (line 33) | def get_thresholds(self):
    method get_features (line 36) | def get_features(self):
    method criterion (line 39) | def criterion(self):
    method get_class_weight (line 42) | def get_class_weight(self):
    method nclasses (line 45) | def nclasses(self):
    method classes (line 48) | def classes(self):
    method get_node_samples (line 52) | def get_node_samples(self):
    method get_split_samples (line 68) | def get_split_samples(self, id):
    method get_root_edge_labels (line 78) | def get_root_edge_labels(self):
    method get_node_nsamples (line 81) | def get_node_nsamples(self, id):
    method get_children_left (line 84) | def get_children_left(self):
    method get_children_right (line 87) | def get_children_right(self):
    method get_node_split (line 90) | def get_node_split(self, id) -> (int, float):
    method get_node_feature (line 93) | def get_node_feature(self, id) -> int:
    method get_node_nsamples_by_class (line 96) | def get_node_nsamples_by_class(self, id):
    method get_prediction (line 111) | def get_prediction(self, id):
    method nnodes (line 118) | def nnodes(self):
    method get_node_criterion (line 121) | def get_node_criterion(self, id):
    method get_feature_path_importance (line 124) | def get_feature_path_importance(self, node_list):
    method get_max_depth (line 140) | def get_max_depth(self):
    method get_score (line 143) | def get_score(self):
    method get_min_samples_leaf (line 146) | def get_min_samples_leaf(self):
    method shouldGoLeftAtSplit (line 149) | def shouldGoLeftAtSplit(self, id, x):

FILE: dtreeviz/models/spark_decision_tree.py
  class ShadowSparkTree (line 15) | class ShadowSparkTree(ShadowDecTree):
    method __init__ (line 17) | def __init__(self, tree_model: (DecisionTreeClassificationModel, Decis...
    method _get_nodes_info (line 30) | def _get_nodes_info(self, tree_model):
    method is_fit (line 53) | def is_fit(self) -> bool:
    method is_classifier (line 58) | def is_classifier(self) -> bool:
    method is_categorical_split (line 61) | def is_categorical_split(self, id) -> bool:
    method get_class_weights (line 68) | def get_class_weights(self):
    method get_class_weight (line 71) | def get_class_weight(self):
    method get_thresholds (line 74) | def get_thresholds(self) -> np.ndarray:
    method get_features (line 91) | def get_features(self) -> np.ndarray:
    method criterion (line 102) | def criterion(self) -> str:
    method nclasses (line 105) | def nclasses(self) -> int:
    method classes (line 115) | def classes(self) -> np.ndarray:
    method get_node_samples (line 119) | def get_node_samples(self):
    method get_split_samples (line 134) | def get_split_samples(self, id):
    method get_root_edge_labels (line 148) | def get_root_edge_labels(self):
    method get_node_nsamples (line 151) | def get_node_nsamples(self, id):
    method get_children_left (line 162) | def get_children_left(self) -> np.ndarray:
    method get_children_right (line 165) | def get_children_right(self):
    method get_node_split (line 168) | def get_node_split(self, id) -> (int, float, list):
    method get_node_feature (line 171) | def get_node_feature(self, id) -> int:
    method get_node_nsamples_by_class (line 174) | def get_node_nsamples_by_class(self, id):
    method get_prediction (line 193) | def get_prediction(self, id):
    method nnodes (line 196) | def nnodes(self) -> int:
    method get_node_criterion (line 199) | def get_node_criterion(self, id):
    method get_feature_path_importance (line 202) | def get_feature_path_importance(self, node_list):
    method get_max_depth (line 205) | def get_max_depth(self) -> int:
    method get_score (line 208) | def get_score(self) -> float:
    method get_min_samples_leaf (line 211) | def get_min_samples_leaf(self) -> (int, float):
    method shouldGoLeftAtSplit (line 214) | def shouldGoLeftAtSplit(self, id, x):
    method _get_pyspark_major_version (line 220) | def _get_pyspark_major_version():
    method _get_tree_model_parameter_value (line 223) | def _get_tree_model_parameter_value(self, name):

FILE: dtreeviz/models/tensorflow_decision_tree.py
  class ShadowTensorflowTree (line 13) | class ShadowTensorflowTree(ShadowDecTree):
    method __init__ (line 18) | def __init__(self, model: RandomForestModel,
    method _get_column_dataspec (line 39) | def _get_column_dataspec(self):
    method is_fit (line 45) | def is_fit(self) -> bool:
    method get_children_left (line 52) | def get_children_left(self):
    method get_children_right (line 55) | def get_children_right(self):
    method is_classifier (line 58) | def is_classifier(self) -> bool:
    method get_class_weights (line 64) | def get_class_weights(self):
    method get_thresholds (line 67) | def get_thresholds(self) -> np.ndarray:
    method get_features (line 88) | def get_features(self) -> np.ndarray:
    method criterion (line 101) | def criterion(self) -> str:
    method get_class_weight (line 105) | def get_class_weight(self):
    method nclasses (line 108) | def nclasses(self) -> int:
    method classes (line 115) | def classes(self) -> np.ndarray:
    method get_node_samples (line 119) | def get_node_samples(self):
    method get_split_samples (line 132) | def get_split_samples(self, id):
    method get_node_nsamples (line 146) | def get_node_nsamples(self, id):
    method get_node_split (line 149) | def get_node_split(self, id) -> (int, float):
    method get_node_feature (line 152) | def get_node_feature(self, id) -> int:
    method get_node_nsamples_by_class (line 156) | def get_node_nsamples_by_class(self, id):
    method get_prediction (line 162) | def get_prediction(self, id):
    method is_categorical_split (line 172) | def is_categorical_split(self, id) -> bool:
    method nnodes (line 179) | def nnodes(self) -> int:
    method get_node_criterion (line 182) | def get_node_criterion(self, id):
    method get_feature_path_importance (line 185) | def get_feature_path_importance(self, node_list):
    method get_max_depth (line 188) | def get_max_depth(self) -> int:
    method get_score (line 191) | def get_score(self) -> float:
    method get_min_samples_leaf (line 194) | def get_min_samples_leaf(self) -> (int, float):
    method shouldGoLeftAtSplit (line 197) | def shouldGoLeftAtSplit(self, id, x):
    method get_root_edge_labels (line 202) | def get_root_edge_labels(self):
    method _get_nodes_info (line 205) | def _get_nodes_info(self):

FILE: dtreeviz/models/xgb_decision_tree.py
  class ShadowXGBDTree (line 16) | class ShadowXGBDTree(ShadowDecTree):
    method __init__ (line 25) | def __init__(self, booster: Booster,
    method is_fit (line 47) | def is_fit(self):
    method get_class_weights (line 51) | def get_class_weights(self):
    method get_class_weight (line 55) | def get_class_weight(self):
    method criterion (line 58) | def criterion(self):
    method get_children_left (line 61) | def get_children_left(self):
    method get_children_right (line 64) | def get_children_right(self):
    method get_node_split (line 67) | def get_node_split(self, id) -> (float):
    method get_node_feature (line 75) | def get_node_feature(self, id) -> int:
    method get_features (line 82) | def get_features(self):
    method get_node_samples (line 90) | def get_node_samples(self):
    method get_split_samples (line 114) | def get_split_samples(self, id):
    method get_root_edge_labels (line 124) | def get_root_edge_labels(self):
    method get_node_nsamples (line 127) | def get_node_nsamples(self, id):
    method _get_leaf_prediction_path (line 130) | def _get_leaf_prediction_path(self, leaf):
    method _get_tree_dataframe (line 157) | def _get_tree_dataframe(self):
    method _get_column_value (line 160) | def _get_column_value(self, column_name):
    method _get_nodes_values (line 163) | def _get_nodes_values(self, column_name):
    method _split_column_value (line 169) | def _split_column_value(self, column_name):
    method _change_no_children_value (line 178) | def _change_no_children_value(self, children):
    method _calculate_children (line 181) | def _calculate_children(self, column_name):
    method get_feature_path_importance (line 187) | def get_feature_path_importance(self, node_list):
    method get_node_criterion (line 190) | def get_node_criterion(self):
    method get_thresholds (line 194) | def get_thresholds(self):
    method get_node_nsamples_by_class (line 199) | def get_node_nsamples_by_class(self, id):
    method get_prediction (line 205) | def get_prediction(self, id):
    method is_classifier (line 214) | def is_classifier(self):
    method nnodes (line 222) | def nnodes(self):
    method nclasses (line 225) | def nclasses(self):
    method classes (line 231) | def classes(self):
    method get_max_depth (line 235) | def get_max_depth(self):
    method get_score (line 238) | def get_score(self):
    method get_min_samples_leaf (line 241) | def get_min_samples_leaf(self):
    method shouldGoLeftAtSplit (line 244) | def shouldGoLeftAtSplit(self, id, x):

FILE: dtreeviz/trees.py
  class DTreeVizAPI (line 33) | class DTreeVizAPI:
    method __init__ (line 41) | def __init__(self, shadow_tree: ShadowDecTree, ai_chat: bool = False, ...
    method _require_ai_explanation (line 54) | def _require_ai_explanation():
    method chat (line 68) | def chat(self, question, stream=True):
    method _chat_invoke (line 84) | def _chat_invoke(self, question):
    method _chat_stream (line 111) | def _chat_stream(self, question):
    method leaf_sizes (line 240) | def leaf_sizes(self,
    method ctree_leaf_distributions (line 344) | def ctree_leaf_distributions(self,
    method view (line 486) | def view(self,
    method leaf_purity (line 1061) | def leaf_purity(self,
    method node_stats (line 1176) | def node_stats(self, node_id: int, ai_chat: Optional[bool] = None) -> ...
    method instance_feature_importance (line 1223) | def instance_feature_importance(self, x,
    method explain_prediction_path (line 1279) | def explain_prediction_path(self, x: np.ndarray) -> str:
    method rtree_leaf_distributions (line 1301) | def rtree_leaf_distributions(self,
    method ctree_feature_space (line 1364) | def ctree_feature_space(self,
    method rtree_feature_space (line 1431) | def rtree_feature_space(self, fontsize: int = 10, ticks_fontsize=8, sh...
    method rtree_feature_space3D (line 1487) | def rtree_feature_space3D(self,
  function _class_split_viz (line 1550) | def _class_split_viz(node: ShadowDecTreeNode,
  function _class_leaf_viz (line 1682) | def _class_leaf_viz(node: ShadowDecTreeNode,
  function _regr_split_viz (line 1717) | def _regr_split_viz(node: ShadowDecTreeNode,
  function _regr_leaf_viz (line 1819) | def _regr_leaf_viz(node: ShadowDecTreeNode,
  function _draw_legend (line 1868) | def _draw_legend(shadow_tree, target_name, filename, colors, fontname):
  function _draw_piechart (line 1892) | def _draw_piechart(counts, size, colors, filename, label, fontname, grap...
  function _draw_barh_chart (line 1929) | def _draw_barh_chart(counts, size, colors, filename, label, fontname, gr...
  function _prop_size (line 1966) | def _prop_size(n, counts, output_range=(0.00, 0.3)):
  function _get_num_bins (line 1978) | def _get_num_bins(histtype, n_classes):
  function _get_leaf_target_input (line 1985) | def _get_leaf_target_input(shadow_tree: ShadowDecTree, precision: int):
  function _ctreeviz_univar (line 2008) | def _ctreeviz_univar(shadow_tree,
  function _ctreeviz_bivar (line 2108) | def _ctreeviz_bivar(shadow_tree, fontsize, ticks_fontsize, fontname, show,
  function _rtreeviz_univar (line 2168) | def _rtreeviz_univar(shadow_tree, fontsize, ticks_fontsize, fontname, show,
  function _rtreeviz_bivar_heatmap (line 2231) | def _rtreeviz_bivar_heatmap(shadow_tree, fontsize, ticks_fontsize, fontn...
  function _rtreeviz_bivar_3D (line 2290) | def _rtreeviz_bivar_3D(shadow_tree, fontsize, ticks_fontsize, fontname,
  function model (line 2353) | def model(model,

FILE: dtreeviz/utils.py
  function criterion_remapping (line 17) | def criterion_remapping(criterion):
  function inline_svg_images (line 32) | def inline_svg_images(svg) -> str:
  function get_SVG_shape (line 97) | def get_SVG_shape(svg) -> Tuple[Number,Number,Sequence[Number]]:
  function scale_SVG (line 112) | def scale_SVG(svg:str, scale:float) -> str:
  function myround (line 148) | def myround(v,ndigits=2):
  function _extract_final_feature_names (line 152) | def _extract_final_feature_names(pipeline, features):
  function _normalize_class_names (line 184) | def _normalize_class_names(class_names, nclasses):
  function extract_params_from_pipeline (line 197) | def extract_params_from_pipeline(pipeline, X_train, feature_names):
  function check_tree_index (line 226) | def check_tree_index(tree_index, nr_of_trees):
  class DTreeVizRender (line 233) | class DTreeVizRender:
    method __init__ (line 237) | def __init__(self, dot, scale=1.0):
    method _repr_svg_ (line 241) | def _repr_svg_(self):
    method svg (line 244) | def svg(self):
    method view (line 251) | def view(self):
    method show (line 257) | def show(self):
    method save_svg (line 262) | def save_svg(self):
    method save (line 269) | def save(self, filename):
  function add_classifier_legend (line 316) | def add_classifier_legend(ax, class_names, class_values, facecolors, tar...
  function _format_axes (line 347) | def _format_axes(ax, xlabel, ylabel, colors, fontsize, fontname, ticks_f...
  function _draw_wedge (line 373) | def _draw_wedge(ax, x, node, color, is_classifier, h=None, height_range=...
  function _set_wedge_ticks (line 416) | def _set_wedge_ticks(ax, ax_ticks, wedge_ticks, separation=0.1):
  function tessellate (line 443) | def tessellate(root, X_train, featidx):
  function is_numeric (line 482) | def is_numeric(A:np.ndarray) -> bool:

FILE: testing/cancer.py
  function viz_breast_cancer (line 27) | def viz_breast_cancer(orientation="TD",

FILE: testing/gen_feature_space_samples.py
  function viz_digits (line 22) | def viz_digits(features, feature_names, max_depth):
  function viz_wine (line 48) | def viz_wine(features, feature_names, max_depth):
  function viz_knowledge (line 74) | def viz_knowledge(features, feature_names, max_depth):
  function viz_diabetes (line 103) | def viz_diabetes(features, feature_names, max_depth):
  function viz_boston (line 129) | def viz_boston(features, feature_names, max_depth):

FILE: testing/gen_samples.py
  function viz_boston (line 36) | def viz_boston(orientation="TD",
  function viz_diabetes (line 74) | def viz_diabetes(orientation="TD",
  function viz_sweets (line 107) | def viz_sweets(orientation="TD",
  function viz_fires (line 144) | def viz_fires(orientation="TD",
  function viz_iris (line 186) | def viz_iris(orientation="TD",
  function viz_digits (line 227) | def viz_digits(orientation="TD",
  function viz_wine (line 264) | def viz_wine(orientation="TD",
  function viz_breast_cancer (line 297) | def viz_breast_cancer(orientation="TD",
  function viz_knowledge (line 330) | def viz_knowledge(orientation="TD",
  function save (line 367) | def save(name, dirname, orientation, max_depth, fancy=True, pickX=False,...

FILE: testing/iris.py
  function viz_iris (line 25) | def viz_iris(orientation="TD",

FILE: testing/paper_examples.py
  function viz_boston_one_feature (line 7) | def viz_boston_one_feature(orientation="TD", max_depth=3, random_state=6...
  function viz_knowledge_one_feature (line 24) | def viz_knowledge_one_feature(orientation="TD", max_depth=3, random_stat...

FILE: testing/testlib/models/conftest.py
  function dataset (line 11) | def dataset() -> pd.DataFrame:
  function x_dataset_classifier (line 16) | def x_dataset_classifier() -> pd.DataFrame:
  function y_dataset_classifier (line 22) | def y_dataset_classifier() -> pd.Series:
  function x_dataset_regressor (line 27) | def x_dataset_regressor() -> pd.DataFrame:
  function y_dataset_regressor (line 33) | def y_dataset_regressor(dataset) -> pd.Series:
  function dataset_spark_tensorflow (line 38) | def dataset_spark_tensorflow() -> pd.DataFrame:
  function dataset_lightgbm (line 42) | def dataset_lightgbm() -> pd.DataFrame:

FILE: testing/testlib/models/test_decision_tree_lightgbm_classifier.py
  function lgb_dec_tree (line 8) | def lgb_dec_tree():
  function shadow_dec_tree (line 13) | def shadow_dec_tree(lgb_dec_tree, dataset_lightgbm) -> ShadowLightGBMTree:
  function test_is_fit (line 19) | def test_is_fit(shadow_dec_tree: ShadowLightGBMTree):
  function test_is_classifier (line 23) | def test_is_classifier(shadow_dec_tree: ShadowLightGBMTree):
  function test_get_children_left (line 27) | def test_get_children_left(shadow_dec_tree: ShadowLightGBMTree):
  function test_get_children_right (line 32) | def test_get_children_right(shadow_dec_tree):
  function test_get_node_nsamples (line 37) | def test_get_node_nsamples(shadow_dec_tree):
  function test_get_thresholds (line 47) | def test_get_thresholds(shadow_dec_tree: ShadowLightGBMTree):
  function test_nnodes (line 58) | def test_nnodes(shadow_dec_tree):
  function test_get_features (line 62) | def test_get_features(shadow_dec_tree: ShadowLightGBMTree):
  function test_nclasses (line 67) | def test_nclasses(shadow_dec_tree: ShadowLightGBMTree):
  function test_classes (line 71) | def test_classes(shadow_dec_tree: ShadowLightGBMTree):
  function test_get_node_samples (line 75) | def test_get_node_samples(shadow_dec_tree: ShadowLightGBMTree):
  function test_get_split_samples (line 86) | def test_get_split_samples(shadow_dec_tree: ShadowLightGBMTree):
  function test_get_min_samples_leaf (line 106) | def test_get_min_samples_leaf(shadow_dec_tree: ShadowLightGBMTree):

FILE: testing/testlib/models/test_decision_tree_spark_classifier.py
  function tree_model (line 11) | def tree_model() -> (DecisionTreeClassificationModel):
  function spark_dtree (line 25) | def spark_dtree(tree_model, dataset_spark_tensorflow) -> ShadowSparkTree:
  function test_is_fit (line 31) | def test_is_fit(spark_dtree):
  function test_is_classifier (line 35) | def test_is_classifier(spark_dtree):
  function test_get_children_left (line 39) | def test_get_children_left(spark_dtree):
  function test_get_children_right (line 44) | def test_get_children_right(spark_dtree):
  function test_get_node_nsamples (line 49) | def test_get_node_nsamples(spark_dtree):
  function test_get_features (line 59) | def test_get_features(spark_dtree):
  function test_nclasses (line 65) | def test_nclasses(spark_dtree):
  function test_get_node_feature (line 69) | def test_get_node_feature(spark_dtree):
  function test_get_node_nsamples_by_class (line 79) | def test_get_node_nsamples_by_class(spark_dtree):
  function test_get_prediction (line 89) | def test_get_prediction(spark_dtree):
  function test_nnodes (line 101) | def test_nnodes(spark_dtree):
  function test_get_max_depth (line 105) | def test_get_max_depth(spark_dtree):
  function test_get_min_samples_leaf (line 109) | def test_get_min_samples_leaf(spark_dtree):
  function test_get_thresholds (line 113) | def test_get_thresholds(spark_dtree):
  function test_predict (line 120) | def test_predict(spark_dtree, dataset_spark_tensorflow):
  function test_predict_path (line 134) | def test_predict_path(spark_dtree, dataset_spark_tensorflow):
  function test_get_node_samples (line 151) | def test_get_node_samples(spark_dtree):
  function test_is_categorical_split (line 160) | def test_is_categorical_split(spark_dtree):

FILE: testing/testlib/models/test_decision_tree_tensorflow_classifier.py
  function features_clf (line 9) | def features_clf():
  function tf_rf_model (line 14) | def tf_rf_model(dataset_spark_tensorflow):
  function tf_shadow_clf (line 30) | def tf_shadow_clf(tf_rf_model, dataset_spark_tensorflow, features_clf):
  function test_is_fit (line 44) | def test_is_fit(tf_shadow_clf):
  function test_get_children_left (line 48) | def test_get_children_left(tf_shadow_clf):
  function test_get_children_right (line 52) | def test_get_children_right(tf_shadow_clf):
  function test_nclasses (line 56) | def test_nclasses(tf_shadow_clf):
  function test_classes (line 60) | def test_classes(tf_shadow_clf):
  function test_get_features (line 64) | def test_get_features(tf_shadow_clf):
  function test_get_node_feature (line 68) | def test_get_node_feature(tf_shadow_clf):
  function test_get_thresholds (line 74) | def test_get_thresholds(tf_shadow_clf):
  function test_get_node_samples (line 78) | def test_get_node_samples(tf_shadow_clf):
  function test_get_node_nsamples (line 85) | def test_get_node_nsamples(tf_shadow_clf):
  function test_get_node_nsamples_by_class (line 92) | def test_get_node_nsamples_by_class(tf_shadow_clf):
  function test_get_prediction (line 98) | def test_get_prediction(tf_shadow_clf):
  function test_get_max_depth (line 108) | def test_get_max_depth(tf_shadow_clf):
  function test_is_categorical_split (line 112) | def test_is_categorical_split(tf_shadow_clf):

FILE: testing/testlib/models/test_decision_tree_xgb_regressor.py
  function xgb_booster (line 10) | def xgb_booster() -> xgb.Booster:
  function xgb_tree (line 15) | def xgb_tree(xgb_booster, x_dataset_regressor, y_dataset_regressor) -> S...
  function test_x_dataset (line 21) | def test_x_dataset(x_dataset_regressor):
  function test_y_dataset (line 27) | def test_y_dataset(y_dataset_regressor):
  function test_feature_names (line 33) | def test_feature_names(xgb_booster):
  function test_get_prediction (line 37) | def test_get_prediction(xgb_tree):
  function test_get_max_depth (line 47) | def test_get_max_depth(xgb_tree):
  function test_get_leaf_sample_counts (line 51) | def test_get_leaf_sample_counts(xgb_tree):

FILE: testing/testlib/models/test_decision_trees_sk_classifier.py
  function dec_tree (line 10) | def dec_tree() -> (DecisionTreeClassifier, DecisionTreeRegressor):
  function shadow_dec_tree (line 15) | def shadow_dec_tree(dec_tree, dataset) -> ShadowSKDTree:
  function test_x_dataset (line 22) | def test_x_dataset(x_dataset_classifier):
  function test_feature_number (line 28) | def test_feature_number(shadow_dec_tree):
  function test_is_fit (line 32) | def test_is_fit(shadow_dec_tree):
  function test_is_classifier (line 36) | def test_is_classifier(shadow_dec_tree):
  function test_class_weight (line 40) | def test_class_weight(shadow_dec_tree):
  function test_criterion (line 44) | def test_criterion(shadow_dec_tree):
  function test_nclasses (line 48) | def test_nclasses(shadow_dec_tree):
  function test_classes (line 52) | def test_classes(shadow_dec_tree):
  function test_get_node_samples (line 57) | def test_get_node_samples(shadow_dec_tree):
  function test_get_class_weights (line 66) | def test_get_class_weights(shadow_dec_tree):
  function test_get_tree_nodes (line 70) | def test_get_tree_nodes(shadow_dec_tree):
  function test_get_children_left (line 75) | def test_get_children_left(shadow_dec_tree):
  function test_get_children_right (line 80) | def test_get_children_right(shadow_dec_tree):
  function test_get_node_split (line 85) | def test_get_node_split(shadow_dec_tree):
  function test_get_node_feature (line 92) | def test_get_node_feature(shadow_dec_tree):
  function test_get_max_depth (line 100) | def test_get_max_depth(shadow_dec_tree):
  function test_get_score (line 104) | def test_get_score(shadow_dec_tree):
  function test_get_min_samples_leaf (line 108) | def test_get_min_samples_leaf(shadow_dec_tree): \
  function test_nnodes (line 112) | def test_nnodes(shadow_dec_tree):
  function test_get_leaf_sample_counts (line 116) | def test_get_leaf_sample_counts(shadow_dec_tree):
  function test_get_thresholds (line 124) | def test_get_thresholds(shadow_dec_tree):
  function test_predict (line 129) | def test_predict(shadow_dec_tree, x_dataset_classifier):
  function test_predict_path (line 146) | def test_predict_path(shadow_dec_tree, x_dataset_classifier):
  function test_get_prediction (line 165) | def test_get_prediction(shadow_dec_tree):
  function test_get_node_nsamples_by_class (line 176) | def test_get_node_nsamples_by_class(shadow_dec_tree):

FILE: testing/testlib/models/test_decision_trees_sk_pipeline.py
  function dec_tree_pipeline (line 26) | def dec_tree_pipeline(x_dataset_classifier, y_dataset_classifier) -> (Pi...
  function shadow_dec_tree (line 37) | def shadow_dec_tree(dec_tree_pipeline, dataset) -> ShadowSKDTree:
  function test_extract_feature_names (line 56) | def test_extract_feature_names(dec_tree_pipeline):
  function test_feature_number (line 70) | def test_feature_number(shadow_dec_tree):
  function test_is_fit (line 74) | def test_is_fit(shadow_dec_tree):

FILE: testing/testlib/models/test_decision_trees_xgb_classifier.py
  function xgb_booster (line 10) | def xgb_booster() -> xgb.Booster:
  function xgb_tree (line 15) | def xgb_tree(xgb_booster, x_dataset_classifier, y_dataset_classifier) ->...
  function test_x_dataset (line 22) | def test_x_dataset(x_dataset_classifier):
  function test_y_dataset (line 28) | def test_y_dataset(y_dataset_classifier):
  function test_feature_names (line 33) | def test_feature_names(xgb_booster):
  function test_get_children_left (line 37) | def test_get_children_left(xgb_tree):
  function test_get_children_right (line 42) | def test_get_children_right(xgb_tree):
  function test_get_node_feature (line 46) | def test_get_node_feature(xgb_tree):
  function test_get_features (line 54) | def test_get_features(xgb_tree):
  function test_get_node_samples (line 58) | def test_get_node_samples(xgb_tree):
  function test_get_node_nsamples_by_class (line 69) | def test_get_node_nsamples_by_class(xgb_tree):
  function test_get_prediction (line 76) | def test_get_prediction(xgb_tree):
  function test_nclasses (line 83) | def test_nclasses(xgb_tree):
  function test_classes (line 87) | def test_classes(xgb_tree):
  function test_get_thresholds (line 91) | def test_get_thresholds(xgb_tree):
  function test_is_classifier (line 95) | def test_is_classifier(xgb_tree):
  function test_get_leaf_sample_counts (line 99) | def test_get_leaf_sample_counts(xgb_tree):

FILE: testing/testone.py
  function viz_iris (line 8) | def viz_iris(orientation="TD", max_depth=5, random_state=666, fancy=True):
  function viz_boston (line 42) | def viz_boston(orientation="TD", max_depth=3, random_state=666, fancy=Tr...
  function viz_knowledge (line 63) | def viz_knowledge(orientation="TD", max_depth=3, random_state=666, fancy...
  function viz_diabetes (line 83) | def viz_diabetes(orientation="TD", max_depth=3, random_state=666, fancy=...
  function viz_digits (line 117) | def viz_digits(orientation="TD", max_depth=3, random_state=666, fancy=Tr...
  function viz_wine (line 137) | def viz_wine(orientation="TD", max_depth=3, random_state=666, fancy=True...
  function weird_binary_case (line 159) | def weird_binary_case():

FILE: testing/tf-catvars.py
  function split_dataset (line 15) | def split_dataset(dataset, test_ratio=0.30):

FILE: testing/tf_catvars3.py
  function split_dataset (line 10) | def split_dataset(dataset, test_ratio=0.30):

FILE: testing/tf_regr_catvars.py
  function split_dataset (line 15) | def split_dataset(dataset, test_ratio=0.30, seed=1234):