class FeaturesTree:
def __init__(self, *args, **kwargs):
self.Tree = Tree(*args, **kwargs)
self.Res = GeoSquizzyResults(*args, **kwargs)
self.Optimum = Optimum(*args, **kwargs)
# self.socket = kwargs.get('socket', None)
@staticmethod
def __new__leaf__():
leaf = dict({'id': None, 'name': None, 'children': [], 'level': None,
'parent': None, 'completed': False, 'values': []})
return leaf
def prepare_new_leaf(self, **kwargs):
new_leaf = self.__new__leaf__()
return {x: kwargs[x] if y is None else y for x, y in new_leaf.items()}
def new_obj(self, omitted):
self.Optimum.update_data(omitted)
def add_leaf(self, leaf=None):
"""
:param leaf new node/leaf dict():
:return:boolean(which mean if node already exist)
"""
self.Optimum.update_seq(leaf=leaf)
# self.socket.write(self.get_all_leafs_paths(progress=True))
# self.socket.run(leaf)
if leaf['parent'] is None:
self.Tree.nodes[leaf['id']] = leaf
elif self.Tree.nodes.get(leaf['id'], None) is None:
self.Tree.nodes[leaf['id']] = leaf
if leaf['id'] not in self.Tree.nodes[leaf['parent']]['children']:
self.Tree.nodes[leaf['parent']]['children'].append(leaf['id'])
if self.Optimum.fit_optimum:
self.Optimum.fit_optimum = False
return self.Optimum.prediction
def add_leaf_values(self, leaf_id=None, leaf_values=None):
self.Tree.nodes[leaf_id]['values'] = leaf_values
def get_all_leafs_paths(self, progress=None):
return self.Res.get_results(nodes=self.Tree.nodes, progress=progress)
def __init__(self, *args, **kwargs):
self.Tree = Tree(*args, **kwargs)
self.Res = GeoSquizzyResults(*args, **kwargs)
self.Optimum = Optimum(*args, **kwargs)
