Exemplo n.º 1
0
	def testCrossover(self):
		print "\n\n----- testing single_crossover(tree1Node, tree2Node) -----"
		root = ScalarNode(self.methodFactory.getScalar('tr'))
		node1 = UnaryNode(self.methodFactory.getUnary('log'))
		node2 = BinaryNode(self.methodFactory.getBinary('multiply'))
		constant1 = DataNode(self.methodFactory.getData('1/N'))
		constant2 = DataNode(self.methodFactory.getData('e'))
		tree = AlgorithmTree(root)
		root.setChildren(node1)
		node1.setChildren(node2)
		node2.setChildren(constant1,constant2)
		print 'Trees before the swap (node,id): '
		print 'Tree One:'
		self.testTree()
		print 'Tree Two:'
		tree()
		CGAGenerator.single_crossover(self.node2, node1)
		print 'Trees after the swap (node,id): '
		print 'Tree One:'
		self.testTree()
		print 'Tree Two:'
		tree()
Exemplo n.º 2
0
	def setUp(self):
		self.methodFactory = CGAFunctions.DataMethodFactory()
		# set up the tree
		self.root = ScalarNode(self.methodFactory.getScalar('sum_ij'))
		self.node1 = BinaryNode(self.methodFactory.getBinary('add'))
		self.node2 = BinaryNode(self.methodFactory.getBinary('subtract'))
		self.node3 = UnaryNode(self.methodFactory.getUnary('log'))
		# immutable data - stored
		self.constant1 = DataNode(self.methodFactory.getData('e'))
		self.constant2 = DataNode(self.methodFactory.getData('pi'))
		self.constant3 = DataNode(self.methodFactory.getData('1/N'))
		# set up the tree
		self.testTree = AlgorithmTree(self.root)
		self.root.setChildren(self.node1)
		self.node1.setChildren(self.node2,self.node3)
		self.node2.setChildren(self.constant1,self.constant2)
		self.node3.setChildren(self.constant3)
Exemplo n.º 3
0
class CGAGeneratorTests(unittest.TestCase):
	def setUp(self):
		self.methodFactory = CGAFunctions.DataMethodFactory()
		# set up the tree
		self.root = ScalarNode(self.methodFactory.getScalar('sum_ij'))
		self.node1 = BinaryNode(self.methodFactory.getBinary('add'))
		self.node2 = BinaryNode(self.methodFactory.getBinary('subtract'))
		self.node3 = UnaryNode(self.methodFactory.getUnary('log'))
		# immutable data - stored
		self.constant1 = DataNode(self.methodFactory.getData('e'))
		self.constant2 = DataNode(self.methodFactory.getData('pi'))
		self.constant3 = DataNode(self.methodFactory.getData('1/N'))
		# set up the tree
		self.testTree = AlgorithmTree(self.root)
		self.root.setChildren(self.node1)
		self.node1.setChildren(self.node2,self.node3)
		self.node2.setChildren(self.constant1,self.constant2)
		self.node3.setChildren(self.constant3)
		
	def testExtend(self):
		print "\n\n----- testing extension -----"
		print 'Tree before extension (node,id): '
		self.testTree()
		newNode = BinaryNode(self.methodFactory.getBinary('multiply'))
		CGAGenerator._extend(self.constant1,newNode)
		print 'Tree after extension (node,id): '
		self.testTree()
		
	def testGrow(self):
		print "\n\n----- testing grow(tree,tNode) -----"
		print "Tree before extension (node,id): "
		self.testTree()
		CGAGenerator.grow(self.testTree,self.constant2)
		print "Tree after extension (node,id): "
		self.testTree()
		
	def testDelete(self):
		print "\n\n----- testing deletion -----"
		print 'Tree before deletion (node, id): '
		self.testTree()
		CGAGenerator._delete(self.node2)
		print 'Tree after deletion (node, id): '
		self.testTree()
	
	def testPrune(self):
		print "\n\n----- testing prune(tree,node) -----"
		print "Tree before pruning (node,id): "
		self.testTree()
		CGAGenerator.prune(self.testTree,self.node3)
		print "Tree after pruning (node,id): "
		self.testTree()
		
	def testNonRootReplace(self):
		print "\n\n----- testing non-root replacement -----"
		print 'Tree before replacement (node,id): '
		self.testTree()
		newNode = BinaryNode(self.methodFactory.getBinary('multiply'))
		CGAGenerator._replace(self.testTree, self.node1, newNode)
		print 'Tree after replacement (node,id): '
		self.testTree()
	
	def testRootReplace(self):
		print "\n\n----- testing replacement of root node -----"
		print 'Tree before root replacement (node,id): '
		self.testTree()
		print 'Root : ', self.testTree.root
		print 'Root header : ', self.testTree.root.getHeader()
		newNode = ScalarNode(self.methodFactory.getScalar('tr'))
		CGAGenerator._replace(self.testTree,self.testTree.root,newNode)
		print 'Tree after root replacement (node, id): '
		self.testTree()
		print 'Root : ', self.testTree.root
		print 'Root header : ', self.testTree.root.getHeader()
		
	def testSwap(self):
		print "\n\n----- testing subtree swap -----"
		root = ScalarNode(self.methodFactory.getScalar('tr'))
		node1 = UnaryNode(self.methodFactory.getUnary('log'))
		node2 = BinaryNode(self.methodFactory.getBinary('multiply'))
		constant1 = DataNode(self.methodFactory.getData('1/N'))
		constant2 = DataNode(self.methodFactory.getData('e'))
		tree = AlgorithmTree(root)
		root.setChildren(node1)
		node1.setChildren(node2)
		node2.setChildren(constant1,constant2)
		print 'Trees before the swap (node,id): '
		print 'Tree One:'
		self.testTree()		
		print 'Tree Two:'
		tree()
		CGAGenerator._swap(self.node2, node1)
		print 'Trees after the swap (node,id): '
		print 'Tree One:'
		self.testTree()
		print 'Tree Two:'
		tree()
	
	def testCrossover(self):
		print "\n\n----- testing single_crossover(tree1Node, tree2Node) -----"
		root = ScalarNode(self.methodFactory.getScalar('tr'))
		node1 = UnaryNode(self.methodFactory.getUnary('log'))
		node2 = BinaryNode(self.methodFactory.getBinary('multiply'))
		constant1 = DataNode(self.methodFactory.getData('1/N'))
		constant2 = DataNode(self.methodFactory.getData('e'))
		tree = AlgorithmTree(root)
		root.setChildren(node1)
		node1.setChildren(node2)
		node2.setChildren(constant1,constant2)
		print 'Trees before the swap (node,id): '
		print 'Tree One:'
		self.testTree()
		print 'Tree Two:'
		tree()
		CGAGenerator.single_crossover(self.node2, node1)
		print 'Trees after the swap (node,id): '
		print 'Tree One:'
		self.testTree()
		print 'Tree Two:'
		tree()
		
	def testGenerate(self):
		print "\n\n----- testing generate(tree) -----"
		tree = CGAGenerator.generate(3)
		tree()		
	
	def testExpGenerate(self):
		print "\n\n----- testing expgenerate(tree) -----"
		tree = CGAGenerator.expgenerate(0.85)
		tree()
	
	def testPointMutate(self):
		print "\n\n----- testing point_mutate(tree,node) -----"
		print "Tree before mutation (node,id): "
		self.testTree()
		CGAGenerator.point_mutate(self.testTree,random.choice(self.testTree.getNodes()))
		print "Tree after mutation (node,id): "
		self.testTree()

	def testRepeatedPointMutate(self):
		print "\n\n----- testing repeated runs of point_mutate(tree,node) -----"
		print "Tree before mutation (node,id): "
		self.testTree()
		for i in xrange(0,10000):
			CGAGenerator.point_mutate(self.testTree, random.choice(self.testTree.getNodes()))
		print "Tree after mutation (node,id): "
		self.testTree()
	
	def testSpecialTreeGeneration(self):
		print "\n\n----- testing generation of 'special' trees -----"
		treeset = ['MI','OMES','DOES NOT EXIST']
		for t in treeset:
			tree = CGAGenerator.generate_special_tree(t)
			if tree is not None:
				print '%s : %s', (t,tree.getString())
			else:
				print 'Tree %s does not exist.' % t
Exemplo n.º 4
0
	def generate_special_tree(treename):
		"""Generates and returns a "special" tree.  Allowed treenames are:
				['MI','OMES']."""
		if treename == 'MI':
			root = ScalarNode(CGAFunctions.DataMethodFactory().getScalar('sum_ij'))
			n1 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('subtract'))
			n2 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			n3 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('add'))
			d1 = DataNode(CGAFunctions.DataMethodFactory().getData('p_ij'))
			n4 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('log'))
			n5 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			n6 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			d2 = DataNode(CGAFunctions.DataMethodFactory().getData('p_ij'))
			d3 = DataNode(CGAFunctions.DataMethodFactory().getData('1/N'))
			n7 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			d4 = DataNode(CGAFunctions.DataMethodFactory().getData('1/N'))
			n8 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			d5 = DataNode(CGAFunctions.DataMethodFactory().getData('p_i'))
			n9 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('log'))
			n10 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('transpose'))
			n11 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('log'))
			d6 = DataNode(CGAFunctions.DataMethodFactory().getData('p_i'))
			d7 = DataNode(CGAFunctions.DataMethodFactory().getData('p_j'))
			n12 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('transpose'))
			d8 = DataNode(CGAFunctions.DataMethodFactory().getData('p_j'))
			# set up the tree
			specialTree = AlgorithmTree(root)
			root.setChildren(n1)
			n1.setChildren(n2,n3)
			n2.setChildren(d1,n4)
			n4.setChildren(d2)
			n3.setChildren(n5,n6)
			n5.setChildren(d3,n7)
			n6.setChildren(d4,n8)
			n7.setChildren(d5,n9)
			n8.setChildren(n10,n11)
			n9.setChildren(d6)
			n10.setChildren(d7)
			n11.setChildren(n12)
			n12.setChildren(d8)			
		elif treename == 'OMES':
			root = ScalarNode(CGAFunctions.DataMethodFactory().getScalar('sum_ij'))
			n1 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('divide'))
			n2 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('square'))
			n3 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			n4 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('subtract'))
			d1 = DataNode(CGAFunctions.DataMethodFactory().getData('p_i'))
			n5 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('transpose'))
			d2 = DataNode(CGAFunctions.DataMethodFactory().getData('p_ij'))
			n6 = BinaryNode(CGAFunctions.DataMethodFactory().getBinary('multiply'))
			d3 = DataNode(CGAFunctions.DataMethodFactory().getData('p_j'))
			d4 = DataNode(CGAFunctions.DataMethodFactory().getData('p_i'))
			n7 = UnaryNode(CGAFunctions.DataMethodFactory().getUnary('transpose'))
			d5 = DataNode(CGAFunctions.DataMethodFactory().getData('p_j'))
			# set up the tree
			specialTree = AlgorithmTree(root)
			root.setChildren(n1)
			n1.setChildren(n2,n3)
			n2.setChildren(n4)
			n3.setChildren(d1,n5)
			n4.setChildren(d2,n6)
			n5.setChildren(d3)
			n6.setChildren(d4,n7)
			n7.setChildren(d5)
		else:
			specialTree = None
		return specialTree