def test_load_neuron():
nrn = utils.load_neuron(FILENAMES[0])
nt.assert_true(isinstance(NRN, Neuron))
nt.assert_equal(NRN.name, 'Neuron')
_check_neurites_have_no_parent(nrn)
# python2 only test, for unicode strings
if sys.version_info < (3, 0):
nrn = utils.load_neuron(unicode(FILENAMES[0]))
nt.assert_true(isinstance(NRN, Neuron))
nt.assert_equal(NRN.name, 'Neuron')
_check_neurites_have_no_parent(nrn)
def test_load_neuromorpho_3pt_soma():
with warnings.catch_warnings(record=True):
nrn = utils.load_neuron(Path(SWC_PATH, 'soma', 'three_pt_soma.swc'))
assert len(nrn.neurites) == 4
assert len(nrn.soma.points) == 3
assert nrn.soma.radius == 2
_check_neurites_have_no_parent(nrn)
def test_load_neuromorpho_3pt_soma():
nrn = utils.load_neuron(os.path.join(SWC_PATH, 'soma',
'three_pt_soma.swc'))
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.soma.points), 3)
nt.eq_(nrn.soma.radius, 2)
_check_neurites_have_no_parent(nrn)
def test_load_neuromorpho_3pt_soma():
with warnings.catch_warnings(record=True):
nrn = utils.load_neuron(Path(SWC_PATH, 'soma', 'three_pt_soma.swc'))
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.soma.points), 3)
nt.eq_(nrn.soma.radius, 2)
_check_neurites_have_no_parent(nrn)
def test_load_neuron():
nrn = utils.load_neuron(FILENAMES[0])
nt.assert_true(isinstance(NRN, Neuron))
nt.assert_equal(NRN.name, 'Neuron')
_check_neurites_have_no_parent(nrn)
neuron_str = u""" 1 1 0 0 0 1. -1
2 3 0 0 0 1. 1
3 3 0 5 0 1. 2
4 3 -5 5 0 0. 3
5 3 6 5 0 0. 3
6 2 0 0 0 1. 1
7 2 0 -4 0 1. 6
8 2 6 -4 0 0. 7
9 2 -5 -4 0 0. 7
"""
utils.load_neuron(StringIO(neuron_str), reader='swc')
def test_load_neuron_mixed_tree_swc():
nrn_mix = utils.load_neuron(os.path.join(SWC_ORD_PATH, 'sample_mixed_tree_sections.swc'))
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix), [5, 3])
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix),
get('number_of_sections_per_neurite', SWC_ORD_REF))
assert_items_equal(get('number_of_segments', nrn_mix),
get('number_of_segments', SWC_ORD_REF))
assert_items_equal(get('total_length', nrn_mix),
get('total_length', SWC_ORD_REF))
def test_load_neuron_mixed_tree_swc():
nrn_mix = utils.load_neuron(os.path.join(SWC_ORD_PATH, 'sample_mixed_tree_sections.swc'))
nt.assert_items_equal(get('number_of_sections_per_neurite', nrn_mix), [5, 3])
nt.assert_items_equal(get('number_of_sections_per_neurite', nrn_mix),
get('number_of_sections_per_neurite', SWC_ORD_REF))
nt.assert_items_equal(get('number_of_segments', nrn_mix),
get('number_of_segments', SWC_ORD_REF))
nt.assert_items_equal(get('total_length', nrn_mix),
get('total_length', SWC_ORD_REF))
def test_load_neuron_section_order_break_swc():
nrn_mix = utils.load_neuron(Path(SWC_ORD_PATH, 'sample_disordered.swc'))
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix), [5, 3])
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix),
get('number_of_sections_per_neurite', SWC_ORD_REF))
assert_items_equal(get('number_of_segments', nrn_mix),
get('number_of_segments', SWC_ORD_REF))
assert_items_equal(get('total_length', nrn_mix),
get('total_length', SWC_ORD_REF))
def test_load_neuron_section_order_break_swc():
nrn_mix = utils.load_neuron(os.path.join(SWC_ORD_PATH, 'sample_disordered.swc'))
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix), [5, 3])
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix),
get('number_of_sections_per_neurite', SWC_ORD_REF))
assert_items_equal(get('number_of_segments', nrn_mix),
get('number_of_segments', SWC_ORD_REF))
assert_items_equal(get('total_length', nrn_mix),
get('total_length', SWC_ORD_REF))
def test_load_h5_trunk_points_regression():
# regression test for issue encoutnered wile
# implementing PR #479, related to H5 unpacking
# of files with non-standard soma structure.
# See #480.
nrn = utils.load_neuron(os.path.join(DATA_PATH, 'h5', 'v1', 'Neuron.h5'))
nt.ok_(np.allclose(nrn.neurites[0].root_node.points[1],
[0., 0. , 0.1, 0.31646374, 4., 4., 3.]))
nt.ok_(np.allclose(nrn.neurites[1].root_node.points[1],
[0., 0., 0.1, 1.84130445e-01, 3.0, 235., 234.]))
nt.ok_(np.allclose(nrn.neurites[2].root_node.points[1],
[0., 0., 0.1, 5.62225521e-01, 3., 466, 465]))
nt.ok_(np.allclose(nrn.neurites[3].root_node.points[1],
[0., 0., 0.1, 7.28555262e-01, 2., 697, 696]))
def test_load_trees_good_neuron():
'''Check trees in good neuron are the same as trees from loaded neuron'''
filepath = os.path.join(SWC_PATH, 'Neuron.swc')
nrn = utils.load_neuron(filepath)
trees = utils.load_trees(filepath)
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.neurites), len(trees))
nrn2 = MockNeuron(trees)
@pts.point_function(as_tree=False)
def elem(point):
return point
# Check data are the same in tree collection and neuron's neurites
for a, b in izip(iter_neurites(nrn, elem), iter_neurites(nrn2, elem)):
nt.ok_(np.all(a == b))
def test_load_h5_trunk_points_regression():
# regression test for issue encountered while
# implementing PR #479, related to H5 unpacking
# of files with non-standard soma structure.
# See #480.
nrn = utils.load_neuron(os.path.join(DATA_PATH, 'h5', 'v1', 'Neuron.h5'))
nt.ok_(np.allclose(nrn.neurites[0].root_node.points[1],
[0., 0., 0.1, 0.31646374, 4., 4., 3.]))
nt.ok_(np.allclose(nrn.neurites[1].root_node.points[1],
[0., 0., 0.1, 1.84130445e-01, 3.0, 235., 234.]))
nt.ok_(np.allclose(nrn.neurites[2].root_node.points[1],
[0., 0., 0.1, 5.62225521e-01, 3., 466, 465]))
nt.ok_(np.allclose(nrn.neurites[3].root_node.points[1],
[0., 0., 0.1, 7.28555262e-01, 2., 697, 696]))
def test_load_h5_trunk_points_regression():
# regression test for issue encountered while
# implementing PR #479, related to H5 unpacking
# of files with non-standard soma structure.
# See #480.
nrn = utils.load_neuron(Path(DATA_PATH, 'h5', 'v1', 'Neuron.h5'))
assert np.allclose(nrn.neurites[0].root_node.points[1, COLS.XYZR],
[0., 0., 0.1, 0.31646374])
assert np.allclose(nrn.neurites[1].root_node.points[1, COLS.XYZR],
[0., 0., 0.1, 1.84130445e-01])
assert np.allclose(nrn.neurites[2].root_node.points[1, COLS.XYZR],
[0., 0., 0.1, 5.62225521e-01])
assert np.allclose(nrn.neurites[3].root_node.points[1, COLS.XYZR],
[0., 0., 0.1, 7.28555262e-01])
def test_neuron_name():
for fn, nn in zip(FILENAMES, NRN_NAMES):
nrn = utils.load_neuron(fn)
nt.eq_(nrn.name, nn)
def test_load_neuron():
nrn = utils.load_neuron(FILES[0])
nt.ok_(nrn.name == FILES[0].strip('.swc').split('/')[-1])
FILES = [
Path(SWC_PATH, f) for f in [
'Neuron.swc', 'Single_apical_no_soma.swc', 'Single_apical.swc',
'Single_basal.swc', 'Single_axon.swc',
'sequential_trunk_off_0_16pt.swc', 'sequential_trunk_off_1_16pt.swc',
'sequential_trunk_off_42_16pt.swc',
'Neuron_no_missing_ids_no_zero_segs.swc'
]
]
FILENAMES = [
Path(VALID_DATA_PATH, f) for f in ['Neuron.swc', 'Neuron_h5v1.h5']
]
NRN = utils.load_neuron(Path(VALID_DATA_PATH, 'Neuron.swc'))
NO_SOMA_FILE = Path(SWC_PATH, 'Single_apical_no_soma.swc')
DISCONNECTED_POINTS_FILE = Path(SWC_PATH, 'Neuron_disconnected_components.swc')
MISSING_PARENTS_FILE = Path(SWC_PATH, 'Neuron_missing_parents.swc')
INVALID_ID_SEQUENCE_FILE = Path(SWC_PATH,
'non_increasing_trunk_off_1_16pt.swc')
def _mock_load_neuron(filename):
class MockNeuron:
def __init__(self, name):
self.soma = 42
def test_load_neuron_no_consecutive_ids_loads():
utils.load_neuron(NON_CONSECUTIVE_ID_FILE);
def test_load_neuron_deep_neuron():
'''make sure that neurons with deep (ie: larger than the python
recursion limit can be loaded)
'''
deep_neuron = os.path.join(DATA_PATH, 'h5/v1/deep_neuron.h5')
nrn = utils.load_neuron(deep_neuron)
def test_load_neuron_disconnected_points_raises():
utils.load_neuron(DISCONNECTED_POINTS_FILE)
def _load_neuron(name):
if name.endswith('.swc'):
path = os.path.join(SWC_PATH, name)
elif name.endswith('.h5'):
path = os.path.join(H5V1_PATH, name)
return name, load_neuron(path)
def test_load_contour_split_1st_soma_neuron():
nrn = utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'contour_split_1st_soma_neuron.swc'))
nt.eq_(len(nrn.neurites), 3)
nt.eq_(len(nrn.soma.points), 6)
nt.eq_(nrn.soma.radius, 2.0)
_check_neurites_have_no_parent(nrn)
def test_load_neuromorpho_3pt_soma():
nrn = utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'three_pt_soma.swc'))
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.soma.points), 3)
nt.eq_(nrn.soma.radius, 2)
_check_neurites_have_no_parent(nrn)
def test_neuron_name():
for fn, nn in zip(FILENAMES, NRN_NAMES):
nrn = utils.load_neuron(fn)
nt.eq_(nrn.name, nn)
def test_load_neuron():
nrn = utils.load_neuron(FILENAMES[0])
nt.assert_true(isinstance(NRN, Neuron))
nt.assert_equal(NRN.name, 'Neuron')
_check_neurites_have_no_parent(nrn)
def test_load_neuromorpho_3pt_soma():
nrn = utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'three_pt_soma.swc'))
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.soma.points), 3)
nt.eq_(nrn.soma.radius, 2)
_check_neurites_have_no_parent(nrn)
@nt.raises(SomaError)
def test_load_bifurcating_soma_points_raises_SomaError():
utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'bifurcating_soma.swc'))
NRN = utils.load_neuron(FILENAMES[0])
def test_neuron_section_ids():
# check section IDs
for i, sec in enumerate(NRN.sections):
nt.eq_(i, sec.id)
def test_neurites_have_no_parent():
_check_neurites_have_no_parent(NRN)
def test_neuron_sections():
all_nodes = set(NRN.sections)
def test_load_neuron_deep_neuron():
'''make sure that neurons with deep (ie: larger than the python
recursion limit can be loaded)
'''
deep_neuron = os.path.join(DATA_PATH, 'h5/v1/deep_neuron.h5')
utils.load_neuron(deep_neuron)
def test_load_neuron_no_soma_raises_SomaError():
utils.load_neuron(NO_SOMA_FILE)
def test_load_bifurcating_soma_points_raises_SomaError():
utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'bifurcating_soma.swc'))
def test_h5v2_raises():
with pytest.raises(RawDataError):
utils.load_neuron(DATA_PATH / 'h5/v2/Neuron.h5')
def test_load_neuron_missing_parents_raises():
utils.load_neuron(MISSING_PARENTS_FILE)
def test_load_neuron_soma_only():
nrn = utils.load_neuron(os.path.join(DATA_PATH, 'swc', 'Soma_origin.swc'))
nt.eq_(len(nrn.neurites), 0)
nt.assert_equal(nrn.name, 'Soma_origin')
def test_load_neuron_invalid_id_sequence_raises():
utils.load_neuron(INVALID_ID_SEQUENCE_FILE);
def test_load_neuron_soma_only():
nrn = utils.load_neuron(Path(DATA_PATH, 'swc', 'Soma_origin.swc'))
assert len(nrn.neurites) == 0
assert nrn.name == 'Soma_origin.swc'
def test_load_neuron_no_consecutive_ids_raises_NonConsecutiveIDsError():
utils.load_neuron(NON_CONSECUTIVE_ID_FILE);
def test_load_neuron_no_soma_raises_SomaError():
utils.load_neuron(NO_SOMA_FILE)
@nt.raises(SomaError)
def test_load_bifurcating_soma_points_raises_SomaError():
utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'bifurcating_soma.swc'))
def test_load_neuromorpho_3pt_soma():
with warnings.catch_warnings(record=True):
nrn = utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'three_pt_soma.swc'))
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.soma.points), 3)
nt.eq_(nrn.soma.radius, 2)
_check_neurites_have_no_parent(nrn)
NRN = utils.load_neuron(FILENAMES[0])
def test_neuron_section_ids():
# check section IDs
for i, sec in enumerate(NRN.sections):
nt.eq_(i, sec.id)
def test_neurites_have_no_parent():
_check_neurites_have_no_parent(NRN)
def test_neuron_sections():
def test_load_neuron_missing_parents_raises():
utils.load_neuron(MISSING_PARENTS_FILE)
def test_neuron_name():
for fn, nn in zip(FILENAMES, NRN_NAMES):
nrn = utils.load_neuron(fn)
assert nrn.name == nn
def test_load_neuron():
nrn = utils.load_neuron(FILENAMES[0])
nt.assert_true(isinstance(NRN, Neuron))
nt.assert_equal(NRN.name, 'Neuron')
_check_neurites_have_no_parent(nrn)
def test_load_contour_split_1st_soma_neuron():
nrn = utils.load_neuron(os.path.join(SWC_PATH, 'soma', 'contour_split_1st_soma_neuron.swc'))
nt.eq_(len(nrn.neurites), 3)
nt.eq_(len(nrn.soma.points), 6)
nt.eq_(nrn.soma.radius, 2.0)
_check_neurites_have_no_parent(nrn)
def test_load_neuron():
nrn = utils.load_neuron(FILES[0])
nt.ok_(nrn.name == FILES[0].strip('.swc').split('/')[-1])
def test_load_bifurcating_soma_points_raises_SomaError():
utils.load_neuron(Path(SWC_PATH, 'soma', 'bifurcating_soma.swc'))
def test_load_neuron_missing_parents_raises():
with pytest.raises(MissingParentError):
utils.load_neuron(MISSING_PARENTS_FILE)
def test_load_neuron_soma_only():
nrn = utils.load_neuron(Path(DATA_PATH, 'swc', 'Soma_origin.swc'))
nt.eq_(len(nrn.neurites), 0)
nt.assert_equal(nrn.name, 'Soma_origin')
def test_load_neuron_mixed_tree_h5():
nrn_mix = utils.load_neuron(os.path.join(H5_PATH, 'sample_mixed_tree_sections.h5'))
nt.assert_items_equal(get('number_of_sections_per_neurite', nrn_mix), [5, 3])
nt.assert_items_equal(get('number_of_sections_per_neurite', nrn_mix),
get('number_of_sections_per_neurite', H5_ORD_REF))
def test_load_neuron_disconnected_points_raises():
utils.load_neuron(DISCONNECTED_POINTS_FILE)
def _load_neuron(name):
if name.endswith('.swc'):
path = os.path.join(SWC_PATH, name)
elif name.endswith('.h5'):
path = os.path.join(H5V1_PATH, name)
return name, load_neuron(path)
def test_load_neuron_invalid_id_sequence_raises():
utils.load_neuron(INVALID_ID_SEQUENCE_FILE)
@nt.raises(SomaError)
def test_load_bifurcating_soma_points_raises_SomaError():
utils.load_neuron(Path(SWC_PATH, 'soma', 'bifurcating_soma.swc'))
def test_load_neuromorpho_3pt_soma():
with warnings.catch_warnings(record=True):
nrn = utils.load_neuron(Path(SWC_PATH, 'soma', 'three_pt_soma.swc'))
nt.eq_(len(nrn.neurites), 4)
nt.eq_(len(nrn.soma.points), 3)
nt.eq_(nrn.soma.radius, 2)
_check_neurites_have_no_parent(nrn)
NRN = utils.load_neuron(FILENAMES[0])
def test_neuron_section_ids():
# check section IDs
for i, sec in enumerate(NRN.sections):
nt.eq_(i, sec.id)
def test_neurites_have_no_parent():
_check_neurites_have_no_parent(NRN)
def test_neuron_sections():
def test_load_neuron_mixed_tree_h5():
nrn_mix = utils.load_neuron(Path(H5_PATH, 'sample_mixed_tree_sections.h5'))
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix), [5, 3])
assert_items_equal(get('number_of_sections_per_neurite', nrn_mix),
get('number_of_sections_per_neurite', H5_ORD_REF))
def test_neuron3d_no_neurites():
filename = os.path.join(SWC_PATH, 'point_soma.swc')
f, a = view.neuron3d(load_neuron(filename))
