<commit_before>import h2o
import math
from h2o.estimators import H2OXGBoostEstimator

class H2OTree():
    """
    Represents a model of a Tree built by one of H2O's algorithms (GBM, Random Forest).
    """

    def __init__(self, model, tree_number, tree_class=None):
        params = {"model": model.model_id,
                  "tree_number": tree_number,
                  "tree_class": tree_class}
        response = h2o.api(endpoint="GET /3/Tree", data=params)

        self._left_children = response['left_children']
        self._right_children = response['right_children']
        self._node_ids = self.__extract_internal_ids(response['root_node_id'])
        self._descriptions = response['descriptions']
        self._model_id = model.model_id
        self._tree_number = response['tree_number']
        self._tree_class = response['tree_class']
        self._thresholds = self.__convert_threshold_nans(response['thresholds'])
        self._features = response['features']
        self._levels = self.__decode_categoricals(model, response['levels'])
        self._nas = response['nas']
        self._predictions = response['predictions']
        self._root_node = self.__assemble_tree(0)

    @property
    def left_children(self):
        """An array with left child nodes of tree's nodes"""
        return self._left_children

    @property
    def right_children(self):
        """An array with right child nodes of tree's nodes"""
        return self._right_children

    @property
    def node_ids(self):
        """Array with identification numbers of nodes. Node IDs are generated by H2O."""
        return self._node_ids

    @property
    def descriptions(self):
        """Descriptions for each node to be found in the tree.
         Contains split threshold if the split is based on numerical column.
         For cactegorical splits, it contains list of categorical levels for transition from the parent node.
         """
        return self._descriptions

    @property
    def model_id(self):
        """
        Name (identification) of the model this tree is related to.
        """
        return self._model_id

    @property
    def tree_number(self):
        """The order in which the tree has been built in the model."""
        return self._tree_number

    @property
    def tree_class(self):
        """The name of a tree's class. Number of tree classes equals to the number of levels in
         categorical response column.

         As there is exactly one class per categorical level, name of tree's class equals to the corresponding
          categorical level of response column.

         In case of regression and binomial, the name of the categorical level is ignored can be omitted,
          as there is exactly one tree built in both cases.
          """
        return self._tree_class

    @property<commit_msg>PUBDEV-6652: fixing syntax errors in tree.py<commit_after>import h2o
import math
from h2o.estimators import H2OXGBoostEstimator

class H2OTree():
    """
    Represents a model of a Tree built by one of H2O's algorithms (GBM, Random Forest).
    """

    def __init__(self, model, tree_number, tree_class=None):
        params = {"model": model.model_id,
                  "tree_number": tree_number,
                  "tree_class": tree_class}
        response = h2o.api(endpoint="GET /3/Tree", data=params)

        self._left_children = response['left_children']
        self._right_children = response['right_children']
        self._node_ids = self.__extract_internal_ids(response['root_node_id'])
        self._descriptions = response['descriptions']
        self._model_id = model.model_id
        self._tree_number = response['tree_number']
        self._tree_class = response['tree_class']
        self._thresholds = self.__convert_threshold_nans(response['thresholds'])
        self._features = response['features']
        self._levels = self.__decode_categoricals(model, response['levels'])
        self._nas = response['nas']
        self._predictions = response['predictions']
        self._root_node = self.__assemble_tree(0)

    @property
    def left_children(self):
        """An array with left child nodes of tree's nodes"""
        return self._left_children

    @property
    def right_children(self):
        """An array with right child nodes of tree's nodes"""
        return self._right_children

    @property
    def node_ids(self):
        """Array with identification numbers of nodes. Node IDs are generated by H2O."""
        return self._node_ids

    @property
    def descriptions(self):
        """Descriptions for each node to be found in the tree.
         Contains split threshold if the split is based on numerical column.
         For categorical splits, it contains list of categorical levels for transition from the parent node.
         """
        return self._descriptions

    @property
    def model_id(self):
        """
        Name (identification) of the model this tree is related to.
        """
        return self._model_id

    @property
    def tree_number(self):
        """The order in which the tree has been built in the model."""
        return self._tree_number

    @property
    def tree_class(self):
        """The name of a tree's class.
        Number of tree classes equals to the number of levels in categorical response column.
        As there is exactly one class per categorical level, name of tree's class equals to the corresponding
            categorical level of response column.
        In case of regression and binomial, the name of the categorical level is ignored can be omitted,
            as there is exactly one tree built in both cases.
        """
        return self._tree_class

    @property
{'fraction_non_alphanumeric': 0.08195580302766661, 'fraction_numerical': 0.003828084217852793, 'mean_word_length': 2.6728434504792333, 'pattern_counts': {'":': 6, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '5594776', 'n_tokens_mistral': 1537, 'n_tokens_neox': 1468, 'n_words': 526}