docstr: Increases counter for specified bucket_key (leaf of tree) and
  also increases counters along the way from the root to the leaf.
docstr_tok: ["Increases","counter","for","specified","bucket_key","(","leaf","of","tree",")","and","also","increases","counters","along","the","way","from","the","root","to","the","leaf","."]
code: def insert_entry_for_bucket(self, bucket_key, tree_depth):
      """
      Increases counter for specified bucket_key (leaf of tree) and
      also increases counters along the way from the root to the leaf.
      """
  
      # First increase vector count of this subtree
      self.vector_count = self.vector_count + 1
  
      if tree_depth < len(bucket_key):
          hash_char = bucket_key[tree_depth]
  
          # This is not the leaf so continue down into the tree towards the leaves
  
          # print 'hash_char=%c' % hash_char
  
          # If child node for this character ('0' or '1') is not existing yet, create it
          if not hash_char in self.childs:
              # print 'Creating child for %c' % hash_char
              self.childs[hash_char] = RandomBinaryProjectionTreeNode()
  
          # Continue on the child
          self.childs[hash_char].insert_entry_for_bucket(
              bucket_key, tree_depth + 1
          )
      else:
          # This is a leaf, so keep the bucket key
          # print 'Inserting leaf %s(%s, %d), count is %d' % (bucket_key, self.bucket_key, tree_depth, self.vector_count)
          if not self.bucket_key is None:
              if self.bucket_key != bucket_key:
                  raise AttributeError
          self.bucket_key = bucket_key
  
file_path: NearPy/nearpy/hashes/randombinaryprojectiontree.py
imports: import numpy
  import scipy
  import scipy.sparse
  from nearpy.hashes.lshash import LSHash
label_desc: Use image node_id 2 for calling the RandomBinaryProjectionTreeNode obj's underlying member method code with example usage: obj.insert_entry_for_bucket(bucket_key, tree_depth) without return types