Python Tree.add_child Examples

Example #1

File: test_tree.py Project: wvangeit/NeuroM

def test_add_child():
    t = Tree(0)
    t.add_child(Tree(11))
    t.add_child(Tree(22))
    nt.ok_(t.value == 0)
    nt.ok_(len(t.children) == 2)
    nt.ok_([i.value for i in t.children] == [11, 22])

Example #2

File: test_tree.py Project: juanchopanza/NeuroM

def test_is_forking_point():
    t = Tree()
    t.add_child(Tree())
    t.add_child(Tree())
    nt.ok_(t.is_forking_point())
    t.add_child(Tree())
    nt.ok_(t.is_forking_point())

Example #3

def test_is_forking_point():
    t = Tree()
    t.add_child(Tree())
    t.add_child(Tree())
    nt.ok_(t.is_forking_point())
    t.add_child(Tree())
    nt.ok_(t.is_forking_point())

Example #4

File: test_tree.py Project: wvangeit/NeuroM

def test_is_forking_point():
    t = Tree(0)
    t.add_child(Tree(1))
    t.add_child(Tree(2))
    nt.ok_(is_forking_point(t))
    t.add_child(Tree(3))
    nt.ok_(is_forking_point(t))

Example #5

File: test_tree.py Project: wvangeit/NeuroM

def test_add_child():
    t = Tree(0)
    t.add_child(Tree(11))
    t.add_child(Tree(22))
    nt.ok_(t.value == 0)
    nt.ok_(len(t.children) == 2)
    nt.ok_([i.value for i in t.children] == [11, 22])

Example #6

File: test_tree.py Project: wvangeit/NeuroM

def test_is_forking_point():
    t = Tree(0)
    t.add_child(Tree(1))
    t.add_child(Tree(2))
    nt.ok_(is_forking_point(t))
    t.add_child(Tree(3))
    nt.ok_(is_forking_point(t))

Example #7

File: test_tree.py Project: wvangeit/NeuroM

def test_is_bifurcation_point_false():
    t = Tree(0)
    nt.ok_(not is_bifurcation_point(t))
    t.add_child(Tree(1))
    nt.ok_(not is_bifurcation_point(t))
    t.add_child(Tree(2))
    t.add_child(Tree(3))
    nt.ok_(not is_bifurcation_point(t))

Example #8

def test_is_bifurcation_point_false():
    t = Tree()
    nt.ok_(not t.is_bifurcation_point())
    t.add_child(Tree())
    nt.ok_(not t.is_bifurcation_point())
    t.add_child(Tree())
    t.add_child(Tree())
    nt.ok_(not t.is_bifurcation_point())

Example #9

File: test_tree.py Project: wvangeit/NeuroM

def test_is_bifurcation_point_false():
    t = Tree(0)
    nt.ok_(not is_bifurcation_point(t))
    t.add_child(Tree(1))
    nt.ok_(not is_bifurcation_point(t))
    t.add_child(Tree(2))
    t.add_child(Tree(3))
    nt.ok_(not is_bifurcation_point(t))

Example #10

File: test_tree.py Project: juanchopanza/NeuroM

def test_is_bifurcation_point_false():
    t = Tree()
    nt.ok_(not t.is_bifurcation_point())
    t.add_child(Tree())
    nt.ok_(not t.is_bifurcation_point())
    t.add_child(Tree())
    t.add_child(Tree())
    nt.ok_(not t.is_bifurcation_point())

Example #11

File: test_tree.py Project: wvangeit/NeuroM

def test_parent():
    t = Tree(0)
    for i in xrange(10):
        t.add_child(Tree(i))

    nt.ok_(len(t.children) == 10)

    for c in t.children:
        nt.ok_(c.parent is t)

Example #12

File: test_tree.py Project: wvangeit/NeuroM

def test_parent():
    t = Tree(0)
    for i in xrange(10):
        t.add_child(Tree(i))

    nt.ok_(len(t.children) == 10)

    for c in t.children:
        nt.ok_(c.parent is t)

Example #13

File: dendrogram.py Project: christian-oreilly/NeuroM

def _create_root_soma_tree(neuron):
    ''' soma segment to represent the soma as a square of radius equal to the soma one
    '''
    soma_radius = neuron.get_soma_radius()

    soma_node0 = Tree((0., 0., 0., soma_radius, 1.))

    soma_node1 = Tree((soma_radius, 0., 0., soma_radius, 1.))

    soma_node0.add_child(soma_node1)

    return soma_node0

Example #14

File: test_triplets.py Project: Tsolmongerel/NeuroM

def _make_simple_tree():
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 1]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 1]))
    T2 = T1.add_child(Tree([2.0, 2.0, 0.0, 1.0, 1, 1, 1]))
    T3 = T2.add_child(Tree([2.0, 6.0, 0.0, 1.0, 1, 1, 1]))

    T5 = T.add_child(Tree([0.0, 0.0, 2.0, 1.0, 1, 1, 1]))
    T6 = T5.add_child(Tree([2.0, 0.0, 2.0, 1.0, 1, 1, 1]))
    T7 = T6.add_child(Tree([6.0, 0.0, 2.0, 1.0, 1, 1, 1]))

    return T

Example #15

File: test_morphtree.py Project: wvangeit/NeuroM

def _form_simple_tree():
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 1]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 1]))
    T2 = T1.add_child(Tree([0.0, 4.0, 0.0, 1.0, 1, 1, 1]))
    T3 = T2.add_child(Tree([0.0, 6.0, 0.0, 1.0, 1, 1, 1]))
    T4 = T3.add_child(Tree([0.0, 8.0, 0.0, 1.0, 1, 1, 1]))

    T5 = T.add_child(Tree([0.0, 0.0, 2.0, 1.0, 1, 1, 1]))
    T6 = T5.add_child(Tree([0.0, 0.0, 4.0, 1.0, 1, 1, 1]))
    T7 = T6.add_child(Tree([0.0, 0.0, 6.0, 1.0, 1, 1, 1]))
    T8 = T7.add_child(Tree([0.0, 0.0, 8.0, 1.0, 1, 1, 1]))

    return T

Example #16

File: test_morphtree.py Project: Tsolmongerel/NeuroM

def test_principal_direction_extent():

    points = np.array([[-10., 0., 0.],
                        [-9., 0., 0.],
                        [9., 0., 0.],
                        [10., 0., 0.]])

    tree = Tree(np.array([points[0][0], points[0][1], points[0][2], 1., 0., 0.]))
    tree.add_child(Tree(np.array([points[1][0], points[1][1], points[1][2], 1., 0., 0.])))
    tree.children[0].add_child(Tree(np.array([points[2][0], points[2][1], points[2][2], 1., 0., 0.])))
    tree.children[0].add_child(Tree(np.array([points[3][0], points[3][1], points[3][2], 1., 0., 0.])))

    extent = mtr.principal_direction_extent(tree)

    nt.assert_true(np.allclose(extent, [20., 0., 0.]))

Example #17

File: dendrogram.py Project: wvangeit/NeuroM

def _create_root_soma_tree(neuron):
    ''' soma segment to represent the soma as a square of radius equal to the soma one
    '''
    soma_radius = neuron.get_soma_radius()

    soma_center = neuron.soma.center

    soma_node0 = Tree((soma_center[0] - soma_radius, soma_center[1],
                       soma_center[2], soma_radius, 1.))

    soma_node1 = Tree(
        (soma_center[0], soma_center[1], soma_center[2], soma_radius, 1.))

    soma_node0.add_child(soma_node1)

    return soma_node0

Example #18

File: test_points.py Project: Tsolmongerel/NeuroM

def _make_tree():
    '''This tree has 3 branching points'''
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 1.0, 0.0, 2.0, 1, 1, 2]))
    T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 3.0, 1, 1, 2]))
    T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 4.0, 1, 1, 2]))
    T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 5.0, 1, 1, 2]))
    T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 6.0, 1, 1, 2]))
    T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 7.0, 1, 1, 2]))
    return T

Example #19

File: test_morphtree.py Project: wvangeit/NeuroM

def _form_neuron_tree():
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
    T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
    T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
    T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
    T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
    T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
    T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
    T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
    return T

Example #20

File: test_segments.py Project: Tsolmongerel/NeuroM

def _make_neuron_tree():
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
    T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
    T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
    T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
    T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
    T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
    T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
    T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
    return T

Example #21

File: test_morphtree.py Project: wvangeit/NeuroM

def _form_branching_tree():
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
    T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
    T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
    T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
    T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
    T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
    T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
    T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
    T11 = T9.add_child(Tree([0.0, 6.0, 4.0, 0.75, 1, 1, 2]))
    T33 = T3.add_child(Tree([1.0, 5.0, 0.0, 2.0, 1, 1, 2]))
    T331 = T33.add_child(Tree([15.0, 15.0, 0.0, 2.0, 1, 1, 2]))
    return T

Example #22

File: test_bifurcations.py Project: Tsolmongerel/NeuroM

def _make_branching_tree():
    '''This tree has 3 branching points'''
    p = [0.0, 0.0, 0.0, 1.0, 1, 1, 2]
    T = Tree(p)
    T1 = T.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
    T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
    T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
    T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
    T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
    T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
    T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
    T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
    T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))
    T11 = T9.add_child(Tree([0.0, 6.0, 4.0, 0.75, 1, 1, 2]))
    T33 = T3.add_child(Tree([1.0, 5.0, 0.0, 2.0, 1, 1, 2]))
    T331 = T33.add_child(Tree([15.0, 15.0, 0.0, 2.0, 1, 1, 2]))
    return T

Example #23

def test_add_child():
    t = Tree()
    ch11 = t.add_child(Tree())
    ch22 = t.add_child(Tree())
    nt.ok_(len(t.children) == 2)
    nt.ok_(t.children == [ch11, ch22])

Example #24

File: test_tree.py Project: wvangeit/NeuroM

def test_is_root_false():
    t = Tree(0)
    t.add_child(Tree(1))
    nt.ok_(not is_root(t.children[0]))

Example #25

File: test_tree.py Project: wvangeit/NeuroM

def test_is_leaf_false():
    t = Tree(0)
    t.add_child(Tree(1))
    nt.ok_(not is_leaf(t))

Example #26

File: test_tree.py Project: juanchopanza/NeuroM

def test_is_root_false():
    t = Tree()
    t.add_child(Tree())
    nt.ok_(not t.children[0].is_root())

Example #27

def test_is_root_false():
    t = Tree()
    t.add_child(Tree())
    nt.ok_(not t.children[0].is_root())

Example #28

def test_is_bifurcation_point():
    t = Tree()
    t.add_child(Tree())
    t.add_child(Tree())
    nt.ok_(t.is_bifurcation_point())

Example #29

File: test_tree.py Project: wvangeit/NeuroM

def test_is_leaf_false():
    t = Tree(0)
    t.add_child(Tree(1))
    nt.ok_(not is_leaf(t))

Example #30

File: test_tree.py Project: juanchopanza/NeuroM

def test_is_forking_point_false():
    t = Tree()
    nt.ok_(not t.is_forking_point())
    t.add_child(Tree())
    nt.ok_(not t.is_forking_point())

Example #31

File: test_morphtree.py Project: wvangeit/NeuroM

DATA_PATH = './test_data'
SWC_PATH = os.path.join(DATA_PATH, 'swc/')

data    = load_data(SWC_PATH + 'Neuron.swc')
neuron0 = make_neuron(data)
tree0   = neuron0.neurites[0]
tree_types = [TreeType.axon,
              TreeType.basal_dendrite,
              TreeType.basal_dendrite,
              TreeType.apical_dendrite]


# Mock tree holding integers, not points
MOCK_TREE = Tree(0)
MOCK_TREE.add_child(Tree(11))
MOCK_TREE.add_child(Tree(12))
MOCK_TREE.children[0].add_child(Tree(111))
MOCK_TREE.children[0].add_child(Tree(112))
MOCK_TREE.children[1].add_child(Tree(121))
MOCK_TREE.children[1].add_child(Tree(122))
MOCK_TREE.children[1].children[0].add_child(Tree(1211))
MOCK_TREE.children[1].children[0].children[0].add_child(Tree(12111))
MOCK_TREE.children[1].children[0].children[0].add_child(Tree(12112))
T1111 = MOCK_TREE.children[0].children[0].add_child(Tree(1111))
T11111 = T1111.add_child(Tree(11111))
T11112 = T1111.add_child(Tree(11112))
T11113 = T1111.add_child(Tree(11113))


def _form_neuron_tree():

Example #32

File: test_tree.py Project: juanchopanza/NeuroM

def test_is_bifurcation_point():
    t = Tree()
    t.add_child(Tree())
    t.add_child(Tree())
    nt.ok_(t.is_bifurcation_point())

Example #33

File: test_neuron.py Project: wvangeit/NeuroM

    [11, 22, 33, 44, 4, 1, 3],
    [11, 22, 33, 44, 5, 1, 4],
    [11, 22, 33, 44, 6, 1, 5]
]


INVALID_PTS_0 = []

INVALID_PTS_2 = [

    [11, 22, 33, 44, 1, 1, -1],
    [11, 22, 33, 44, 2, 1, 1]
]

TREE = Tree([0.0, 0.0, 0.0, 1.0, 1, 1, 2] )
T1 = TREE.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))

def test_make_SomaA():
    soma = neuron.make_soma(SOMA_A_PTS)
    nt.ok_('SomaA' in str(soma))
    nt.ok_(isinstance(soma, neuron.SomaA))
    nt.assert_equal(soma.center, (11, 22, 33))

Example #34

File: test_tree.py Project: wvangeit/NeuroM

def test_is_bifurcation_point():
    t = Tree(0)
    t.add_child(Tree(1))
    t.add_child(Tree(2))
    nt.ok_(is_bifurcation_point(t))

Example #35

def test_is_leaf_false():
    t = Tree()
    t.add_child(Tree())
    nt.ok_(not t.is_leaf())

Example #36

File: test_neuron.py Project: Tsolmongerel/NeuroM

    [11, 22, 33, 44, 4, 1, 3],
    [11, 22, 33, 44, 5, 1, 4],
    [11, 22, 33, 44, 6, 1, 5]
]


INVALID_PTS_0 = []

INVALID_PTS_2 = [

    [11, 22, 33, 44, 1, 1, -1],
    [11, 22, 33, 44, 2, 1, 1]
]

TREE = Tree([0.0, 0.0, 0.0, 1.0, 1, 1, 2] )
T1 = TREE.add_child(Tree([0.0, 1.0, 0.0, 1.0, 1, 1, 2]))
T2 = T1.add_child(Tree([0.0, 2.0, 0.0, 1.0, 1, 1, 2]))
T3 = T2.add_child(Tree([0.0, 4.0, 0.0, 2.0, 1, 1, 2]))
T4 = T3.add_child(Tree([0.0, 5.0, 0.0, 2.0, 1, 1, 2]))
T5 = T4.add_child(Tree([2.0, 5.0, 0.0, 1.0, 1, 1, 2]))
T6 = T4.add_child(Tree([0.0, 5.0, 2.0, 1.0, 1, 1, 2]))
T7 = T5.add_child(Tree([3.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T8 = T7.add_child(Tree([4.0, 5.0, 0.0, 0.75, 1, 1, 2]))
T9 = T6.add_child(Tree([0.0, 5.0, 3.0, 0.75, 1, 1, 2]))
T10 = T9.add_child(Tree([0.0, 6.0, 3.0, 0.75, 1, 1, 2]))

def test_make_SomaA():
    soma = neuron.make_soma(SOMA_A_PTS)
    nt.ok_('SomaA' in str(soma))
    nt.ok_(isinstance(soma, neuron.SomaA))
    nt.assert_items_equal(soma.center, (11, 22, 33))

Example #37

File: test_tree.py Project: wvangeit/NeuroM

def test_is_forking_point_false():
    t = Tree(0)
    nt.ok_(not is_forking_point(t))
    t.add_child(Tree(1))
    nt.ok_(not is_forking_point(t))

Example #38

File: test_tree.py Project: juanchopanza/NeuroM

def test_add_child():
    t = Tree()
    ch11 = t.add_child(Tree())
    ch22 = t.add_child(Tree())
    nt.ok_(len(t.children) == 2)
    nt.ok_(t.children == [ch11, ch22])

Example #39

File: test_tree.py Project: wvangeit/NeuroM

def test_is_bifurcation_point():
    t = Tree(0)
    t.add_child(Tree(1))
    t.add_child(Tree(2))
    nt.ok_(is_bifurcation_point(t))

Example #40

File: test_morphtree.py Project: wvangeit/NeuroM

def test_trunk_length():
    t = Tree((0, 0, 0, 42))
    tt = t.add_child(Tree((10, 0, 0, 4)))
    tt.add_child(Tree((10, 15, 0, 4)))
    nt.assert_almost_equal(trunk_length(t), 25.0)

Example #41

File: test_tree.py Project: juanchopanza/NeuroM

def test_is_leaf_false():
    t = Tree()
    t.add_child(Tree())
    nt.ok_(not t.is_leaf())

Example #42

File: test_tree.py Project: wvangeit/NeuroM

def test_is_root_false():
    t = Tree(0)
    t.add_child(Tree(1))
    nt.ok_(not is_root(t.children[0]))

Example #43

def test_is_forking_point_false():
    t = Tree()
    nt.ok_(not t.is_forking_point())
    t.add_child(Tree())
    nt.ok_(not t.is_forking_point())

Example #44

File: test_tree.py Project: christian-oreilly/NeuroM

from neurom.core.tree import is_bifurcation_point
from neurom.core.tree import ipreorder
from neurom.core.tree import ipostorder
from neurom.core.tree import iupstream
from neurom.core.tree import isegment
from neurom.core.tree import ileaf
from neurom.core.tree import itriplet
from neurom.core.tree import iforking_point
from neurom.core.tree import ibifurcation_point
from neurom.core.tree import isection
from neurom.core.tree import val_iter
from neurom.core.tree import i_branch_end_points
from copy import deepcopy

REF_TREE = Tree(0)
REF_TREE.add_child(Tree(11))
REF_TREE.add_child(Tree(12))
REF_TREE.children[0].add_child(Tree(111))
REF_TREE.children[0].add_child(Tree(112))
REF_TREE.children[1].add_child(Tree(121))
REF_TREE.children[1].add_child(Tree(122))
REF_TREE.children[1].children[0].add_child(Tree(1211))
REF_TREE.children[1].children[0].children[0].add_child(Tree(12111))
REF_TREE.children[1].children[0].children[0].add_child(Tree(12112))

REF_TREE2 = deepcopy(REF_TREE)
T1111 = REF_TREE2.children[0].children[0].add_child(Tree(1111))
T11111 = T1111.add_child(Tree(11111))
T11112 = T1111.add_child(Tree(11112))
T11113 = T1111.add_child(Tree(11113))

Example #45

File: test_morphtree.py Project: wvangeit/NeuroM

def test_trunk_radius():
    t = Tree((0, 0, 0, 42))
    t.add_child(Tree((1, 0, 0, 4)))
    nt.assert_equal(trunk_radius(t), 42.0)

Example #46

File: test_tree.py Project: wvangeit/NeuroM

from neurom.core.tree import is_bifurcation_point
from neurom.core.tree import ipreorder
from neurom.core.tree import ipostorder
from neurom.core.tree import iupstream
from neurom.core.tree import isegment
from neurom.core.tree import ileaf
from neurom.core.tree import itriplet
from neurom.core.tree import iforking_point
from neurom.core.tree import ibifurcation_point
from neurom.core.tree import isection
from neurom.core.tree import val_iter
from neurom.core.tree import i_branch_end_points
from copy import deepcopy

REF_TREE = Tree(0)
REF_TREE.add_child(Tree(11))
REF_TREE.add_child(Tree(12))
REF_TREE.children[0].add_child(Tree(111))
REF_TREE.children[0].add_child(Tree(112))
REF_TREE.children[1].add_child(Tree(121))
REF_TREE.children[1].add_child(Tree(122))
REF_TREE.children[1].children[0].add_child(Tree(1211))
REF_TREE.children[1].children[0].children[0].add_child(Tree(12111))
REF_TREE.children[1].children[0].children[0].add_child(Tree(12112))

REF_TREE2 = deepcopy(REF_TREE)
T1111 = REF_TREE2.children[0].children[0].add_child(Tree(1111))
T11111 = T1111.add_child(Tree(11111))
T11112 = T1111.add_child(Tree(11112))
T11113 = T1111.add_child(Tree(11113))

Example #47

File: test_tree.py Project: juanchopanza/NeuroM

# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import sys

from nose import tools as nt
from neurom.core.tree import Tree

REF_TREE = Tree()
T11 = REF_TREE.add_child(Tree())
T12 = REF_TREE.add_child(Tree())
T111 = REF_TREE.children[0].add_child(Tree())
T112 = REF_TREE.children[0].add_child(Tree())
T121 = REF_TREE.children[1].add_child(Tree())
T122 = REF_TREE.children[1].add_child(Tree())
T1211 = REF_TREE.children[1].children[0].add_child(Tree())
T12111 = REF_TREE.children[1].children[0].children[0].add_child(Tree())
T12112 = REF_TREE.children[1].children[0].children[0].add_child(Tree())

REF_TREE2 = Tree()
T11_ = REF_TREE2.add_child(Tree())
T12_ = REF_TREE2.add_child(Tree())
T111_ = REF_TREE2.children[0].add_child(Tree())
T112_ = REF_TREE2.children[0].add_child(Tree())
T121_ = REF_TREE2.children[1].add_child(Tree())

Example #48

File: test_tree.py Project: wvangeit/NeuroM

from neurom.core.tree import is_bifurcation_point
from neurom.core.tree import ipreorder
from neurom.core.tree import ipostorder
from neurom.core.tree import iupstream
from neurom.core.tree import isegment
from neurom.core.tree import ileaf
from neurom.core.tree import itriplet
from neurom.core.tree import iforking_point
from neurom.core.tree import ibifurcation_point
from neurom.core.tree import isection
from neurom.core.tree import val_iter
from neurom.core.tree import i_branch_end_points
from copy import deepcopy

REF_TREE = Tree(0)
REF_TREE.add_child(Tree(11))
REF_TREE.add_child(Tree(12))
REF_TREE.children[0].add_child(Tree(111))
REF_TREE.children[0].add_child(Tree(112))
REF_TREE.children[1].add_child(Tree(121))
REF_TREE.children[1].add_child(Tree(122))
REF_TREE.children[1].children[0].add_child(Tree(1211))
REF_TREE.children[1].children[0].children[0].add_child(Tree(12111))
REF_TREE.children[1].children[0].children[0].add_child(Tree(12112))

REF_TREE2 = deepcopy(REF_TREE)
T1111 = REF_TREE2.children[0].children[0].add_child(Tree(1111))
T11111 = T1111.add_child(Tree(11111))
T11112 = T1111.add_child(Tree(11112))
T11113 = T1111.add_child(Tree(11113))

Example #49

File: test_tree.py Project: wvangeit/NeuroM

def test_is_forking_point_false():
    t = Tree(0)
    nt.ok_(not is_forking_point(t))
    t.add_child(Tree(1))
    nt.ok_(not is_forking_point(t))

Example #50

# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import sys
from nose import tools as nt
from neurom.core.tree import Tree

REF_TREE = Tree()
T11 = REF_TREE.add_child(Tree())
T12 = REF_TREE.add_child(Tree())
T111 = REF_TREE.children[0].add_child(Tree())
T112 = REF_TREE.children[0].add_child(Tree())
T121 = REF_TREE.children[1].add_child(Tree())
T122 = REF_TREE.children[1].add_child(Tree())
T1211 = REF_TREE.children[1].children[0].add_child(Tree())
T12111 = REF_TREE.children[1].children[0].children[0].add_child(Tree())
T12112 = REF_TREE.children[1].children[0].children[0].add_child(Tree())

REF_TREE2 = Tree()
T11_ = REF_TREE2.add_child(Tree())
T12_ = REF_TREE2.add_child(Tree())
T111_ = REF_TREE2.children[0].add_child(Tree())
T112_ = REF_TREE2.children[0].add_child(Tree())
T121_ = REF_TREE2.children[1].add_child(Tree())