本文整理汇总了Python中neuron.Neuron.clean方法的典型用法代码示例。如果您正苦于以下问题：Python Neuron.clean方法的具体用法？Python Neuron.clean怎么用？Python Neuron.clean使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类neuron.Neuron的用法示例。
在下文中一共展示了Neuron.clean方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: TestNeuron
# 需要导入模块: from neuron import Neuron [as 别名]
# 或者: from neuron.Neuron import clean [as 别名]
class TestNeuron(TestCase):
def setUp(self):
self.max_length = settings.MAX_PATH_LENGTH
self.origin_coor = (0, 0)
self.origin_node = Node(self.origin_coor, 4)
self.neuron = Neuron(self.origin_node)
def test_init(self):
'''Test initiate of neuron.'''
self.assertEqual(self.neuron.vertex, self.origin_node.connections)
self.assertFalse(self.neuron.boundary_nodes)
self.assertFalse(self.neuron.paths)
self.assertFalse(self.neuron.boundary_paths)
self.assertEqual(self.neuron.nodes, [self.origin_node])
def test_hands(self):
'''Number of hands'''
if self.neuron.vertex != 6:
self.assertEqual(self.neuron.hands, self.neuron.vertex)
# Hands test for neuron with 6 connections origin node.
node6 = Node(self.origin_coor, 6)
neuron6 = Neuron(node6)
hands = []
'''The probability that neuron.hands only give 2 unique values in
40 calls is less than 0.00000001'''
for i in range(40):
hands.append(neuron6.hands)
hands = set(hands)
self.assertEqual(hands, set([4, 5, 6]))
def test_born(self):
'''Test for born method of neuron.
After born, a neuron has several boundary_nodes and the same number
of boundary_paths.'''
self.neuron.born()
if self.neuron.vertex != 6:
# Neighbours are now boundary nodes.
self.assertEqual(self.neuron.boundary_nodes, self.neuron.origin.neighbours)
# Number of boundary paths is the same with vertex number.
self.assertEqual(len(self.neuron.boundary_paths), self.neuron.vertex)
# Nodes used by boundary paths.
path_nodes = [path.origin for path in self.neuron.boundary_paths] +\
[path.dest for path in self.neuron.boundary_paths]
# Remove duplicated nodes.
path_nodes = set(path_nodes)
# Nodes used by boundary paths are boundary nodes plus origin node.
self.assertEqual(len(path_nodes), self.neuron.vertex + 1)
# All boundary_paths are now 0.
self.assertTrue(all([x.length == 0 for x in self.neuron.boundary_paths]))
def test_grow(self):
'''Test for grow function. Grow for 1 and 2 steps.'''
# Born first to determine grow directions.
self.neuron.born()
# Grow for one step.
self.neuron.grow()
self.assertTrue(all([x.length == settings.GROW_SPEED for x in self.neuron.boundary_paths]))
# Grow for another 2 steps.
for i in range(2):
self.neuron.grow()
self.assertTrue(all([x.length == settings.GROW_SPEED*3 for x in self.neuron.boundary_paths]))
def test_way_to_go_no_way(self):
'''No way available.'''
# Node coors for neuron.
node_coors = [(0, 1), (-1, 1), (-2, 1), (-2, 0), (-2, -1), (-1, -1), (-1, 0)]
# Test coordinates.
test = (-1, 0)
# Assign nodes to self.neuron
for x in node_coors:
node = Node([y*self.max_length for y in x], 4)
self.neuron.nodes.append(node)
test_node = Node([y*self.max_length for y in test], 4)
# Assert no way available.
self.assertFalse(self.neuron.way_to_go(test_node, True))
def test_way_to_go_one_way(self):
'''Only one way available.'''
# Node coordinates to be assigned.
node_coors = [(0, 1), (0, 2), (-1, 2), (-2, 2), (-2, 1), (-2, 0), (-2, -1), (-1, -1), (-1, 0)]
# Test coordinates.
test = (-1, 0)
# Assign nodes to self.neuron
for x in node_coors:
node = Node([y*self.max_length for y in x], 4)
self.neuron.nodes.append(node)
test_node = Node([y*self.max_length for y in test], 4)
# Assert only one way, the only way is (-1, 1)
target = Node([y*self.max_length for y in (-1, 1)], 4)
self.assertEqual(self.neuron.way_to_go(test_node, True), [target])
def test_clean(self):
'''Test for clean to update boundary conditions.'''
#.........这里部分代码省略.........