def test_NewTree(self): root = Tree("Root") child1 = Tree("C01") child2 = Tree("C02") child21 = Tree("C21") root.addChild(child1) root.addChild(child2) child2.addChild(child21) self.assertEqual(root.data, "Root") self.assertEqual(root.getChildren()[0].data, "C01")
def message_structure_recursively(cls, structure): if type(structure) == dict and 'parts' in structure: current_node = Tree(structure['content-type']) for part in structure['parts']: entry = cls.message_structure_recursively(part) current_node.addChild(entry) return current_node else: if ('file-name' in structure and structure['file-name']) and \ ('attachment-id' in structure and structure['attachment-id']): return Tree(structure) else: return Tree(structure['content-type'])
def __treeGrowth__(self, dataset, attributes, target): """ Grows decision tree based on training set @param dataset: training set @param attributes: attribute set, which may contains target attribute @param target: target attribute """ #Target values tvals = [record[target] for record in dataset] default = self.datasource.majorityValue(dataset) # If the data set is empty or the attributes list is empty, return the # default value. if not dataset or (len(attributes) - 1) <= 0: return Tree(DecisionNode(default)) # If all the records in the data set have the same classification, # return that classification. elif tvals.count(tvals[0]) == len(tvals): return Tree(DecisionNode(tvals[0])) else: # Choose best attribute to best classify data best = self.splitmetric(dataset, attributes, target) # Create a new decision tree/node with the best attribute dtree = Tree(DecisionNode(best)) #Attributes for next iterator, all attributes except already fitted `best` attribute attrs = [attr for attr in attributes if attr != best] # Create a new decision tree/sub-node for each of the values in the # best attribute field for val in self.datasource.uniqueValues(dataset, best): # Create a subtree for the current value under the "best" field subtree = self.__treeGrowth__( self.datasource.subDataSet(dataset, best, val), attrs, target) # Set decision condition, and add the new subtree subtree.data.condition = val dtree.addChild( subtree) return dtree
def test_PrintTree(self): root = Tree('root') t1 = Tree('1') t11 = Tree('11') t111 = Tree('111') t1111 = Tree('1111') t11111 = Tree('11111') t111111 = Tree('111111') t1111111 = Tree('1111111') root.addChild(t1) t1.addChild(t11) t11.addChild(t111) t111.addChild(t1111) t1111.addChild(t11111) t1111.addChild(Tree('44444')) t11111.addChild(t111111) t111111.addChild(t1111111) root.prettyTree()
class TestTree(unittest.TestCase): def setUp(self): """ Test Tree structure: Root |___ C01 | |___ C11 | |___ C111 | |___ C112 |___ C02 |___ C03 | |___ C31 """ self.root = Tree('Root') self.child01 = Tree('C01') self.child02 = Tree('C02') self.child03 = Tree('C03') self.child11 = Tree('C11') self.child31 = Tree('C31') self.child111 = Tree('C111') self.child112 = Tree('C112') self.root.addChildren([self.child01, self.child02, self.child03]) self.child01.addChild(self.child11) self.child03.addChild(self.child31) self.child11.addChild(self.child111) self.child11.addChild(self.child112) #self.root.printTree(T) def test_initialization(self): pass def test_NewTree(self): root = Tree("Root") child1 = Tree("C01") child2 = Tree("C02") child21 = Tree("C21") root.addChild(child1) root.addChild(child2) child2.addChild(child21) self.assertEqual(root.data, "Root") self.assertEqual(root.getChildren()[0].data, "C01") def test_NewTreeSingle(self): child1 = Tree("C01") root = Tree('Root', child1) self.assertEqual(root.data, "Root") self.assertEqual(root.getChildren()[0].data, "C01") def test_NewTreeMulti(self): child1 = Tree("C01") child2 = Tree("C02") root = Tree('Root', [child1, child2]) self.assertEqual(root.data, "Root") self.assertEqual(root.getChildren()[1].data, "C02") def test_Parent(self): self.assertEqual(self.child01.getParent(), self.root) self.assertEqual(self.child02.getParent(), self.root) self.assertEqual(self.child03.getParent(), self.root) self.assertEqual(self.child11.getParent(), self.child01) self.assertEqual(self.child31.getParent(), self.child03) def test_IsRoot(self): self.assertTrue(self.root.isRoot()) self.assertFalse(self.child01.isRoot()) self.assertFalse(self.child31.isRoot()) def test_IsBranch(self): self.assertFalse(self.root.isBranch()) self.assertFalse(self.child01.isBranch()) self.assertFalse(self.child03.isBranch()) self.assertTrue(self.child02.isBranch()) self.assertFalse(self.child11.isBranch()) self.assertTrue(self.child31.isBranch()) def test_ChildrendotAssign(self): #self.root.children = [] with self.assertRaises(AttributeError) as excpt: self.root.children = [] self.assertEqual(excpt.expection, AttributeError) def test_GetRoot(self): self.assertEqual(self.root.getRoot(), self.root); self.assertEqual(self.child01.getRoot(), self.root) self.assertEqual(self.child31.getRoot(), self.root) def test_GetChild(self): self.assertEqual(self.root.getChild(2), self.child03) self.assertEqual(self.child03.getChild(0), self.child31); def test_GetNode(self): self.assertEqual(self.root.getNode('C31'), self.child31) self.assertEqual(self.child11.getNode('C11'), self.child11) self.assertEqual(self.root.getNode('C41'), None) def test_DelChild(self): self.child11.delChild(0); #self.root.prettyTree() def test_DelNode(self): self.root.delNode('C03'); #self.root.prettyTree() def test_PrintTree(self): root = Tree('root') t1 = Tree('1') t11 = Tree('11') t111 = Tree('111') t1111 = Tree('1111') t11111 = Tree('11111') t111111 = Tree('111111') t1111111 = Tree('1111111') root.addChild(t1) t1.addChild(t11) t11.addChild(t111) t111.addChild(t1111) t1111.addChild(t11111) t1111.addChild(Tree('44444')) t11111.addChild(t111111) t111111.addChild(t1111111) root.prettyTree() #self.root.prettyTree() # self.root.nestedTree() def tearDown(self): del self.root